obial processes - university of california, berkeley · 2018. 10. 10. · although rare earth...

Utilizing “Omics” Based Approaches to Investigate Targeted Microbial Processes

By

Vanessa Lynn Brisson

A dissertation submitted in partial satisfaction of the

requirements for the degree of

Doctor of Philosophy

in

Engineering – Civil and Environmental Engineering

in the

Graduate Division

of the

University of California, Berkeley

Committee in charge:

Professor Lisa Alvarez-Cohen, Chair

Professor Kara Nelson

Professor Fiona Doyle

Spring 2015


Copyright © 2015

By


1

Abstract


by


Doctor of Philosophy in Engineering – Civil and Environmental Engineering

University of California, Berkeley

Professor Lisa Alvarez-Cohen, Chair

Metabolomic, genomic, and metagenomic analyses were used to provide insight into two

different environmentally relevant microbial processes: bioleaching of rare earth elements from

monazite sand and reductive dechlorination of chlorinated ethenes. Although rare earth elements

are important for a variety of technologies, current extraction techniques are severely

environmentally damaging. The research presented here demonstrates that some

microorganisms are capable of biological leaching of rare earth elements from monazite, opening

the possibility of a novel, environmentally sustainable bioleaching extraction process.

Metabolomic analysis of a monazite bioleaching microorganism was used to further our

understanding of the bioleaching process. Chlorinated ethenes are common groundwater

contaminants with human health risks. Dehalococcoides mccartyi bacteria are the only

organisms known to completely reduce chlorinated ethenes to the harmless product ethene.

However, D. mccartyi dechlorinate these chemicals more effectively and grow more robustly in

mixed microbial communities than in isolation. Genomic and metagenomic analyses were used

to advance our understanding of D. mccartyi in a mixed microbial community and in isolation.

Successful isolation and characterization of monazite bioleaching microorganisms provided a

proof of concept for monazite bioleaching as an environmentally friendly alternative to

conventional extraction of rare earth elements from monazite, a rare earth phosphate mineral.

Three fungal strains were found to be capable of bioleaching monazite, utilizing the mineral as a

phosphate source and releasing rare earth cations into solution. These organisms include one

known phosphate solubilizing fungus, Aspergillus niger ATCC 1015, as well as two newly

isolated fungi: an Aspergillus terreus strain ML3-1 and a Paecilomyces spp. strain WE3-F. The

rare earth elements were released in proportions similar to those present in the monazite, which

was dominated by cerium, lanthanum, neodymium, and praseodymium. Although monazite also

contains the radioactive element thorium, bioleaching by these fungi preferentially solubilized

rare earth elements over thorium, leaving the thorium in the solid residual. Adjustments in

growth medium composition improved bioleaching performance measured as rare earth release.

Cell-free spent medium generated during growth of A. terreus strain ML3-1 and Paecilomyces

spp. strain WE3-F in the presence of monazite retained robust bioleaching capacity, indicating

that compounds exogenously released by these organisms contribute substantially to leaching

activity. Organic acids released by the organisms were identified and quantified. Abiotic

leaching with laboratory prepared solutions of the identified organic acids was not as effective as

bioleaching or leaching with cell-free spent medium at releasing rare earths from monazite,

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indicating that compounds other than the identified organic acids contribute to leaching

performance.

Metabolomic analysis of a monazite bioleaching microorganism was performed in order to better

understand the bioleaching process. Overall metabolite profiling, in combination with biomass

accumulation data, identified a lag in growth phase when this organism was grown under

phosphate limitation stress. Analysis of the relationships between metabolite concentrations,

rare earth element solubilization levels, and bioleaching growth conditions identified several

metabolites potentially associated with bioleaching. Further investigation using laboratory

prepared solutions of 17 of these metabolites indicated significant leaching contributions from

citric and citramalic acids only. These contributions were relatively small compared to

bioleaching effectiveness of microbial supernatant, suggesting that other still unknown factors

contribute to bioleaching activity. Further investigations of bioleaching supernatant using gel

permeation chromatography indicated that the compounds involved in leaching form only

weakly held complexes, like those of citric acid, with the solubilized rare earth elements, rather

than forming more strongly held complexes.

The phylogenetic composition and gene content of a functionally stable trichloroethene

degrading microbial community was examined using metagenomic sequencing and analysis. For

phylogenetic classification, contiguous sequences (contigs) longer than 2,500 bp were grouped

into classes according to tetranucleotide frequencies and assigned to taxa based on rRNA genes

and other phylogenetic marker genes. Classes were identified for Clostridiaceae,

Dehalococcoides, Desulfovibrio, Methanobacterium, Methanospirillum, as well as a Spirochaete,

a Synergistete, and an unknown Deltaproteobacterium. D. mccartyi contigs were also identified

based on sequence similarity to previously sequenced genomes, allowing the identification of

170 kb on contigs shorter than 2,500 bp. Examination of metagenome sequences affiliated with

D. mccartyirevealed 406 genes not found in previously sequenced D. mccartyi genomes,

including nine cobalamin biosynthesis genes related to corrin ring synthesis. This is the first

time that a D. mccartyi strain has been found to possess genes for synthesizing this cofactor

critical to reductive dechlorination. Besides D. mccartyi, several other members of this

community appear to have genes for complete or near-complete cobalamin biosynthesis

pathways. Seventeen genes for putative reductive dehalogenases were identified, including 11

novel ones, all associated with D. mccartyi. Genes for hydrogenase components (271 in total)

were widespread, highlighting the importance of hydrogen metabolism in this community.

PhyloChip microarray analysis confirmed the stability of this microbial community over time.

Bioinformatic analyses using genomic and metagenomic data were used to further advance

investigations of organisms from the genus Dehalococcoides. In the first of these analyses,

metagenomic sequencing data from three dechlorinating microbial communities was used to

evaluate the specificity of a genus wide microarray targeting Dehalococcoides genes from four

sequenced Dehalococcoides genomes. Based on this analysis, the microarray was found to

detect sequences with a minimum estimated sequence identity of 90 to 95%, remaining highly

specific for the target sequences while allowing for small sequence variation. However, the

microarray did not detect all genes with > 95% sequence identity, and failed to detect some

genes with apparently 100% sequence identity. In the second analysis, a comparative genomics

analysis was used to evaluate the prevalence of the recently reported incomplete Wood-

Ljungdahl pathway of Dehalococcoides. This analysis revealed that the genetic pattern of genes

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associated with this incomplete pathway is unique to the Dehalococcoides genus among

sequenced bacterial and archaeal genomes.

i

Dedication

To Gabriel, Abigail, and Madeline

ii

Table of Contents

Abstract............................................................................................................................................1

Dedication.........................................................................................................................................i

Table of Contents.............................................................................................................................ii

List of Figures.................................................................................................................................vi

List of Tables................................................................................................................................viii

Acknowledgements.........................................................................................................................ix

Chapter 1: Introduction and Background...................................................................................1

1.1 “Omics” techniques...................................................................................................................2

1.2 Targeted microbial processes.....................................................................................................3

1.2.1 Bioleaching of rare earth elements from monazite...........................................................3

1.2.2 Microbial reductive dehalogenation of chlorinated ethenes.............................................7

1.3 Dissertation overview................................................................................................................9

Chapter 2: Bioleaching of Rare Earth Elements from Monazite Sand..................................11

2.1 Introduction..............................................................................................................................12

2.2 Materials and methods.............................................................................................................13

2.2.1 Enrichment and isolation of rare earth element solubilizing microorganisms...............13

2.2.2 DNA extraction, amplification, sequencing, and sequence analysis..............................13

2.2.3 Bioleaching growth conditions.......................................................................................13

2.2.4 Abiotic leaching conditions............................................................................................15

2.2.5 Biomass measurements...................................................................................................15

2.2.6 Analytical methods.........................................................................................................15

2.2.7 Statistical analysis...........................................................................................................16

2.2.7.1 Analysis of biomass growth...................................................................................16

2.2.7.2 Analysis of bioleaching performance....................................................................16

2.2.7.3 Analysis of proportional release of rare earth elements and thorium....................17

2.2.7.4 Analysis of abiotic leaching with hydrochloric acid, organic acids, and spent

medium..............................................................................................................................17

2.3 Results and discussion.............................................................................................................17

2.3.1 Enrichment, isolation, and identification of bioleaching microorganisms.....................17

2.3.2 Biomass growth during bioleaching...............................................................................19

2.3.3 Bioleaching performance under different growth conditions.........................................19

2.3.4 Proportional release of rare earth elements and thorium during bioleaching.................25

2.3.5 Organic acid production during bioleaching...................................................................26

2.3.6 Abiotic leaching with hydrochloric acid and organic acids............................................27

2.3.7 Abiotic leaching with spent medium from bioleaching..................................................31

2.3.8 Statistical analysis results...............................................................................................32

iii

Chapter 3: Metabolomic Analysis of a Monazite Bioleaching Fungus...................................33

3.1 Introduction..............................................................................................................................34


3.2.1 Organism and bioleaching growth conditions................................................................35

3.2.2 Quantification of rare earth elements, thorium, phosphate, glucose, pH, and biomass..35

3.2.3 Metabolomic analysis.....................................................................................................35

3.2.4 Identification of metabolites of potential bioleaching importance.................................36

3.2.5 Abiotic leaching conditions............................................................................................36

3.2.6 Gel permeation chromatographic separation of rare earth element complexes and free

rare earth elements...................................................................................................................37


3.3.1 Bioleaching performance................................................................................................37

3.3.2 Overall metabolomic profile...........................................................................................39

3.3.3 Identification of metabolites of potential bioleaching importance.................................41

3.3.3.1 Metabolites released at higher concentrations when soluble phosphate was not

available.............................................................................................................................41

3.3.3.2 Metabolites whose concentration correlated with rare earth element

concentration......................................................................................................................43

3.3.3.3 High signal intensity metabolites...........................................................................44

3.3.4 Abiotic leaching effectiveness of identified metabolites................................................44

3.3.5 Gel permeation chromatographic separation of complexed rare earth elements............46

Chapter 4: Metagenomic Analysis of a Functionally Stable Trichloroethene Degrading

Microbial Community.................................................................................................................48

4.1 Introduction..............................................................................................................................49


4.2.1 ANAS enrichment culture and DNA sample preparation...............................................50

4.2.2 Metagenome sequencing, assembly, and annotation......................................................50

4.2.3 Analysis of metagenomic sequence data........................................................................50

4.2.3.1 Identification of Dehalococcoides contigs by sequence similarity........................50

4.2.3.2 Classification of ANAS contigs by tetranucleotide frequencies............................51

4.2.3.2 Comparisons to reference genomes and identification of novel Dhc genes..........51

4.2.4 Confirmation of novel Dehalococcoides genes in Dehalococcoides isolates from

ANAS.......................................................................................................................................52

4.2.5 Trichloroethene dechlorination by Dehalococcoides isolate ANAS2 and ANAS

Subcultures...............................................................................................................................52

4.2.6 PhyloChip assessment of community composition........................................................53

4.3 Results......................................................................................................................................54

4.3.1 ANAS metagenome overview........................................................................................54

4.3.2 Dehalococcoides in ANAS.............................................................................................54

4.3.2.1 Identification of Dehalococcoides contigs.............................................................54

4.3.2.2 Metagenome coverage of Dehalococcoides genes detected by microarray..........55

4.3.2.3 Co-assembly of sequence from distinct Dehalococcoides strains.........................56

4.3.2.4 Identification of novel Dehalococcoides genes.....................................................56

iv

4.3.2.5 Trichloroethene dechlorination by Dehalococcoides isolate ANAS2 under

different cobalamin conditions..........................................................................................59

4.3.3 ANAS community structure...........................................................................................59

4.3.3.1 Tetranucleotide classification of metagenome contigs..........................................59

4.3.3.2 Comparisons to previously sequenced genomes....................................................61

4.3.3.3 PhyloChip analysis of ANAS community composition........................................63

4.3.4 Metabolic functions in ANAS........................................................................................63

4.3.4.1 Metagenome gene content overview.....................................................................63

4.3.4.2 Reductive dechlorination.......................................................................................65

4.3.4.3 Hydrogen production and consumption.................................................................67

4.3.4.4 Cobalamin biosynthesis.........................................................................................67

4.3.4.5 Trichloroethene dechlorination by ANAS subcultures under different cobalamin

conditions...........................................................................................................................69

4.4 Discussion................................................................................................................................69

Chapter 5: Evaluation of microarray specificity for detecting Dehalococcoides mccartyi

genes in mixed microbial communities using metagenomic sequence data............................73

5.1 Introduction..............................................................................................................................74

5.2 Methods....................................................................................................................................74

5.2.1.1 Microbial communities................................................................................................74

5.2.1.2 Metagenome and microarray datasets..........................................................................75

5.2.1.3 Evaluation of microarray specificity through comparison of datasets.........................75


Chapter 6: Comparative genomics of Wood-Ljungdahl pathways in Dehalococcoides

mccartyi and in other fully sequenced bacteria and archaea...................................................82

6.1 Introduction..............................................................................................................................83

6.2 Methods....................................................................................................................................83


Chapter 7: Conclusions and Suggestions for Future Work.....................................................86

7.1 Bioleaching of rare earth elements from monazite..................................................................87

7.2 Microbial reductive dehalogenation of chlorinated ethenes....................................................89

References.....................................................................................................................................91

Appendices..................................................................................................................................108

Appendix 1. Calculation of total Nd solubilized from NdPO4 as a function of pH....................109

Appendix 2. Metabolomics signal intensities for all metabolites and time points.....................113

Appendix 3. Heatmap showing average levels of all detected metabolites during monazite

bioleaching...................................................................................................................................154

Appendix 4. Novel ANAS Dehalococcoides genes with product predictions beyond

"hypothetical protein"..................................................................................................................157

v

Appendix 5. Genes for hydrogenase components identified in the ANAS metagenome

contigs..........................................................................................................................................165

Appendix 6. Cobalamin biosynthesis genes identified in the ANAS metagenome contigs.......182

Appendix 7. Bacterial and archaeal sequenced genomes lacking genes for methylene

tetrahydrofolate reductase (MTHFR)..........................................................................................189

vi

List of Figures

Figure 1.1. Total Nd solubilized from NdPO4 at varying pH.

Figure 1.2. Reductive dechlorination of chlorinated ethenes.

Figure 2.1. Initial characterization of rare earth element solubilization from unground monazite

by fungal and bacterial isolates.

Figure 2.2. Biomass production measured as volatile solids after six days incubation with

different phosphate sources.

Figure 2.3. Bioleaching of rare earth elements from monazite under different growth conditions.

Figure 2.4. Total sugar concentrations during bioleaching of monazite.

Figure 2.5. pH during bioleaching of monazite.

Figure 2.6. Proportions of rare earth elements and thorium in monazite and in bioleaching

supernatant after six days of bioleaching.

Figure 2.7. Abiotic leaching of rare earth elements from monazite by hydrochloric acid

solutions, organic acids, and bioleaching spent medium.

Figure 2.8. Relationship between pH and solubilization of thorium for abiotic leaching of

monazite with solutions of hydrochloric acid.

Figure 2.9. Abiotic leaching of Th by different organic acids and by spent medium from three

bioleaching organisms.

Figure 3.1. Bioleaching of monazite in the absence or presence of soluble phosphate (K2HPO4).

Figure 3.2. Heatmap showing average levels of identified metabolites detected during monazite

bioleaching for each growth condition and time point.

Figure 3.3. Metabolites of potential bioleaching importance identified by higher concentrations

for growth with monazite only than for growth with K2HPO4 and monazite.

Figure 3.4. Correlations between metabolite signal intensities and rare earth element

concentrations.

Figure 3.5. Abiotic solubilization of rare earth elements from monazite by selected metabolites.

Figure 3.6. Abiotic solubilization of Th from monazite by selected metabolites.

Figure 3.7. Chromatographic separation of free Nd3+ and EDTA-Nd3+ complexes at

circumneutral pH.

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Figure 3.8. Chromatographic separation of Nd3+ and Nd3+ complexes at pH 2.5.

Figure 4.1. Comparison of metagenomic Dehalococcoides coverage with ANAS genes detected

by microarray.

Figure 4.2. Alignment of ANAS metagenome Dehalococcoides contigs (identified by

tetranucleotide frequency and/or sequence similarity) to the Dehalococcoides strain 195 genome.

Figure 4.3. Operon structure for genes for the first (corrin ring synthesis) part of the cobalamin

biosynthesis pathway identified in an ANAS metagenome contig associated with

Dehalococcoides.

Figure 4.4. Evidence for the association of contig ANASMEC_C6240 (containing cobalamin

biosynthesis genes) with Dehalococcoides.

Figure 4.5. Ethene production during trichloroethene degradation by Dehalococcoides isolate

ANAS2.

Figure 4.6. Ethene production during trichloroethene dechlorination by ANAS subcultures.

Figure 5.1. Distribution of genes among profile categories.

Figure 5.2. Fraction of genes identified as “Present” as a function of the number of probes for

that gene with N mismatches where N = 0, 1, 2, 3, or > 3 (unaligned).

Figure 5.3. Relationships between profile mismatch distributions and microarray “Present”/

“Absent” identification.

Figure 6.1. Identification of targeted Wood-Ljungdahl pathway genes in fully sequenced

bacterial and archaeal genomes.

Figure 7.1. Effect of monazite sand grain size on abiotic leaching with 10 mM citric acid.

viii

List of Tables

Table 2.1. Bioleaching growth media compositions.

Table 2.2. Molar ratio of total rare earth elements to phosphate measured after bioleaching with

different media compositions.

Table 2.3. Maximum observed concentrations of identified organic acids produced by three

fungal isolates during bioleaching and percentage of bioleaching flasks for which each acid was

detected.

Table 2.4. P-values for statistical analyses reported in the text for bioleaching and abiotic

leaching of monazite.

Table 4.1. PCR primers and annealing temperatures for novel Dehalococcoides genes.

Table 4.2. Classification of contigs by tetranucleotide frequency and identification of contig

classes by 16S and 23S BLAST comparisons.

Table 4.3. Comparison of ANAS contig classes to the most similar sequenced genomes.

Table 4.4. Overview of ANAS gene content by clusters of orthologous genes.

Table 4.5. Reductive dehalogenase genes identified in ANAS metagenome contigs.

Table 4.6. Cobalamin biosynthesis genes identified in ANAS metagenome contigs.

Table 5.1. Non-determinant probe set (gene) mismatch profiles.

ix

Acknowledgements

I would like to thank my advisor Lisa Alvarez-Cohen for her guidance over the past five years,

along with all the members of the Alvarez-Cohen research group, especially three post-doctoral

scholars, Dr. Patrick K. H. Lee, Dr. Wei-Qin Zhuang, and Dr. Shan Yi, for their advice and

support.

I would also like to thank a number of individuals for their specific contributions that made this

work possible. Dr. Karl Lalonde and Dr. Geoffrey A. Dorn assisted with the collection of

monazite samples, including leading me on collection expedition in the Colorado Rockies. Dr.

Negassi Hadgu provided assistance with ICP-MS analysis of rare earth elements and thorium for

the bioleaching studies described in Chapters 2 and 3. Several people contributed work that

made the metagenomic analysis in Chapter 4 possible. Kimberlee West collected ANAS cell

samples and performed nucleic acid extractions. Dr. Susannah G. Tringe and other staff

members at the Department of Energy Joint Genome Institute (JGI) performed the metagenome

sequencing, assembly, and initial annotation. Kimberlee West and Dr. Eoin Brodie carried out

and performed the initial analyses on the PhyloChip experiments. Dr. Yujie Men provided the

microarray and metagenomic sequencing datasets for HiTCEB12 and HiTCE analysed in

Chapter 5.

Additionally, I would like to thank the funding organizations that supported this work. The

monazite bioleaching research described in Chapters 2 and 3 was supported by Siemens

Corporate Research, a division of Siemens Corporation, through award number UCB_CKI-2012-

Industry_IS-001-Doyle. The dechlorination research described in Chapters 4, 5, and 6 was

supported by the Strategic Environmental Research and Development Program (SERDP) through

grant ER-1587 and the NIEHS Superfund Basic Research Project ES04705-19. Funding for

metagenomic sequencing was provided under the JGI Community Sequencing Program of the

Department of Energy Office of Biological and Environmental Research. Part of the

metagenomics work was performed at Lawrence Berkeley National Lab supported by the Office

of Science, U. S. Department of Energy under Contract No. 470 DE-AC02-05CH11231.

This dissertation incorporates material from the following coauthored/previously published

studies.

Brisson, Vanessa L., Wei-Qin Zhuang and Lisa Alvarez-Cohen (submitted 2015).

"Bioleaching of Rare Earth Elements from Monazite Sand." Biotechnology and

Bioengineering.

Brisson, Vanessa L., Kimberlee A. West, Patrick. K. H. Lee, Susannah G. Tringe, Eoin L.

Brodie and Lisa Alvarez-Cohen (2012). "Metagenomic analysis of a stable trichloroethene-

degrading microbial community." The ISME Journal 6(9): 1702-1714.

Zhuang, Wei-Qin, Shan Yi, Markus Bill, Vanessa L. Brisson, Xueyang Feng, Yujie Men,

Mark E. Conrad, Yinjie J. Tang and Lisa Alvarez-Cohen (2014). "Incomplete Wood–

Ljungdahl pathway facilitates one-carbon metabolism in organohalide-respiring

Dehalococcoides mccartyi." Proceedings of the National Academy of Sciences 111(17):

6419-6424.

1

Chapter 1:

Introduction and Background

2

1.1 “Omics” techniques

“Omics” refers to the evaluation of the content of a particular class of molecules in an organism

or biological system. Technological advances over the past few decades have advanced our

ability to analyze the contents of a living organism or system in increasingly comprehensive

ways. The four interrelated “omics” analyses reviewed here are genomics, transcriptomics,

proteomics, and metabolomics, which respectively describe gene content, gene transcription to

mRNA, mRNA translation to proteins, and metabolite production/consumption by reactions

catalyzed by proteins.

Genomics is the analysis of the total genetic content of an organism, while metagenomics is the

extension of that analysis to the genetic content of a community of organisms. Metagenomic

data provide a broad view of the genetic composition of a community, including information

about the identity and potential metabolic capabilities of community members. Advances in

DNA sequencing technologies and analysis tools have facilitated the metagenomic analysis of

increasingly complex microbial communities. In addition to sequencing, microarrays, such as

the PhyloChip for phylogenetic profiling (Brodie, DeSantis et al. 2006) and the GeoChip for

functional genes (He, Gentry et al. 2007), provide another approach to examining the

metagenome of a microbial community. Microarray analyses are limited to detecting the

targeted genes but can detect them with high sensitivity, while sequencing based approaches can

detect novel gene sequences but are limited in their sensitivity to low abundance genes due to

random sampling effects (Zhou, Kang et al. 2008, Zhou, Wu et al. 2011).

Genomic/metagenomic sequencing also provide a basis for transcriptomic and proteomic

analyses.

Transcriptomic analyses examine the genes that are transcribed from DNA to mRNA. Since this

is also an analysis of nucleic acids, transcriptomics relies on similar technologies to genomics

and metagenomics. In addition to identifying transcribed genes, these analyses elucidate

differences in transcription levels between different growth conditions, providing information on

organisms’ response to conditions in terms of transcriptional regulation of genes.

In proteomics, the complement of proteins produced by an organism or group of organisms are

analyzed. Like transcriptomics, proteomics can be used to evaluate regulatory responses to

different conditions, in this case at the level of translation of mRNA sequences into proteins. The

majority of proteomics studies utilize mass spectrometry (MS) techniques to analyze peptides

from digested proteins and map those back to a database of proteins or to those proteins

predicted from genomic/metagenomic sequences (VerBerkmoes, Denef et al. 2009, Altelaar,

Munoz et al. 2013). Improvements in genomic/metagenomic sequencing and analyses have also

facilitated proteomic analyses by providing improved reference sets of predicted proteins for

analysis of MS results (VerBerkmoes, Denef et al. 2009).

Metabolomics refers to the analysis of small molecules present in or excreted by organisms.

Metabolomic analyses applied to excreted metabolites are sometimes referred to as

exometabolomics or metabolic footprinting while endometabolomics or metabolic fingerprinting

refers to analysis of internal metabolites (Kell, Brown et al. 2005). Similar to transcriptomics

and proteomics, metabolomic analyses are useful for comparing responses to differing growth

conditions. However, unlike the above analyses, metabolomic analyses do not require

3

genomic/metagenomic sequencing to provide a reference set of predicted transcripts or proteins

for comparison (Kell, Brown et al. 2005). The two main analytical tools used in metabolomics

are various forms of MS (usually coupled to liquid chromatography or gas chromatography) and

nuclear magnetic resonance (NMR) (Patti, Yanes et al. 2012). These analyses can be either

targeted (focusing on more detailed measurement of a small predefined set of metabolites) or

untargeted (detecting as large a set of metabolites as possible) depending on the desired

application (Patti, Yanes et al. 2012).

1.2 Targeted microbial processes

1.2.1 Bioleaching of rare earth elements from monazite

Over recent years, the rare earth elements (REEs) have become increasingly important for their

use in a number of different technologies, several of which are related to energy efficiency and

alternative energy generation (USDoE 2011, Alonso, Sherman et al. 2012). For instance,

permanent magnets, used in wind turbines as well as many other applications, are made with Nd,

Pr, and Dy (USDoE 2011). High efficiency batteries used in hybrid electric cars use a variety of

REEs including Ce, La, Nd, and Pr (USDoE 2011). Although these are generally considered

environmentally beneficial technologies, current processing techniques for extraction of REEs

from ores are environmentally damaging due to their high energy inputs and use of harsh

chemicals, which result in the production of environmentally damaging waste streams (Gupta

and Krishnamurthy 1992, Alonso, Sherman et al. 2012).

The REEs include the naturally occurring elements of the lanthanide series (La, Ce, Pr, Nd, Sm,

Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu) (atomic numbers 57 to 60 and 62 to 71) as well as Y

and Sc (atomic numbers 57 to 60 and 62 to 71), which have similar chemical behavior to the

lanthanides (Gupta and Krishnamurthy 1992, Cotton 2006). Pm, also a lanthanide, is not

included because all of its isotopes decay radioactively, and thus it is not found naturally (Cotton

2006). The REEs are further subdivided into the light REEs (La-Gd, Sc) and the heavy REEs

(Tb-Lu, Y) (Gupta and Krishnamurthy 1992, Cotton 2006). This division is based on atomic

size, which decreases with increasing atomic number across the lanthanides, and on the electron

configuration (Cotton 2006).

REEs are not truly rare and can be found in many locations around the globe (Gupta and

Krishnamurthy 1992, Rudnick and Gao 2003). The three main REE ores that are currently

mined for production are bastnasite (REE-FCO3), monazite (light REE-PO4), and xenotime

(heavy REE-PO4), together representing approximately 95% of known REE minerals (Gupta and

Krishnamurthy 1992, Rosenblum and Fleischer 1995). Of these, monazite and bastnasite are

much more abundant than xenotime (Gupta and Krishnamurthy 1992). Monazite is further

classified as monazite-Ce, monazite-La, and monazite-Nd, depending on which REE is dominant

in the mineral (Rosenblum and Fleischer 1995). In addition to REE-PO4, monazite usually

contains Th and sometimes U, both of which are radioactive, presenting a challenge for

separation and disposal when they are extracted along with REEs (Gupta and Krishnamurthy

1992). Th is usually present as either cheralite (ThCa(PO4)2) or huttonite (ThSiO4) (Nitze 1896,

Rosenblum and Fleischer 1995). In addition to the REEs, Th, and U, other elements commonly

4

present in monazite ore include Si, Ca, Al, Mg, Fe, Mn, and Pb (Nitze 1896, Zhu and O'Nions

1999).

REEs are generally difficult to extact from monazite, and conventional monazite processing uses

caustic chemicals to leach REEs from the ore at high temperatures. Since monazite is the focus

of the bioleaching process presented in this dissertation, conventional monazite leaching

processes are reviewed here briefly. There are two main treatment processes for monazite: acid

treatment and alkali treatment (Gupta and Krishnamurthy 1992). In the acid treatment process,

concentrated inorganic acid, usually H2SO4, is used to digest the ore at approximately 200 ºC.

REEs and Th are then recovered separately through a series of neutralization and precipitation

steps. In the alkali treatment process, concentrated NaOH solution is used to decompose the ore

at approximately 140 ºC in order to recover Na3PO4 as a product stream, converting the REE

phosphates to REE hydroxides. These are then dissolved with concentrated inorganic acid and

further processed to recover the REEs. The use of harsh chemicals and high temperatures results

in the production of toxic waste streams and high energy usage. Also, the co-extraction of

radioactive elements (Th and U) early in the process necessitates further downstream processing

to separate this radioactive material from other process streams and to dispose of it appropriately.

Bioleaching offers a potentially more environmentally friendly approach to extraction of REEs

from ores.

Phosphate solubilizing microorganisms (PSMs), which include both bacterial and fungal species,

are capable of releasing phosphate from otherwise low solubility phosphate minerals (Rodrı́guez

and Fraga 1999). All organisms need phosphate to survive. Phosphate is an important part of

the structure of DNA, RNA, and cytoplasmic membranes, and it is also needed for adenosine tri-

phosphate, which stores energy for cells in phosphate bonds (Madigan, Martinko et al. 2008).

However, in many environmental systems phosphate is not readily available, but is instead

locked away in insoluble minerals (Rodrı́guez and Fraga 1999). This provides a selective

pressure for the evolution of organisms capable of solubilizing these minerals in order to make

the phosphates bioavailable.

Most research with PSMs has focused on agricultural applications with the objectives of

understanding how microorganisms make phosphate more bioavailable to plants and developing

approaches for using microorganisms to enhance the effectiveness of phosphate fertilizers (Asea,

Kucey et al. 1988, Illmer and Schinner 1992, Rodrı́guez and Fraga 1999, Gyaneshwar, Naresh

Kumar et al. 2002, Arcand and Schneider 2006, Vassilev, Vassileva et al. 2006, Chuang, Kuo et

al. 2007, Morales, Alvear et al. 2007, Osorio and Habte 2009, Chai, Wu et al. 2011, Braz and

Nahas 2012). In addition to agriculturally important studies, there has also been research on

using PSM’s to extract phosphate from apatite ores (Costa, Medronho et al. 1992) and to remove

phosphates from iron ores to make these ores more suitable for iron production (Delvasto,

Valverde et al. 2008, Delvasto, Ballester et al. 2009, Adeleke, Cloete et al. 2010). Most of these

studies have focused on calcium phosphate minerals including tricalcium phosphate, dicalcium

phosphate, hydroxyapatite, and rock phosphate (Illmer and Schinner 1992, Illmer and Schinner

1995, Altomare, Norvell et al. 1999, Rodrı́guez and Fraga 1999), but a few have addressed other

phosphate minerals, including AlPO4, FePO4, and turquoise (CuAl6(PO4)4(OH)8·4H2O) (Illmer,

Barbato et al. 1995, Souchie, Azcón et al. 2006, Chuang, Kuo et al. 2007, Delvasto, Valverde et

al. 2008, Chai, Wu et al. 2011). For the studied PSMs, solubilization varied between minerals,

with FePO4 and turquoise exhibiting much lower solubility than AlPO4 and calcium phosphates.

5

To the best of our knowledge, no previous research has evaluated the potential for PSM

bioleaching of monazite.

Several mechanisms have been proposed to explain phosphate solubilization by PSMs, but the

production of organic acids is thought to be a major contributor (Rodrı́guez and Fraga 1999,

Nautiyal, Bhadauria et al. 2000, Gyaneshwar, Naresh Kumar et al. 2002, Scervino, Papinutti et

al. 2011). In addition to reducing the pH, which somewhat increases the solubility of phosphate

minerals, some organic acids can act as chelating agents, forming complexes with the cations

released from the phosphate minerals and thus improving overall solubilization (Bolan, Naidu et

al. 1994, Gadd 1999, Gyaneshwar, Naresh Kumar et al. 2002, Arcand and Schneider 2006).

PSMs have been observed to produce a variety of organic acids including citric, gluconic, oxalic,

succinic, acetic, malonic, propionic, 2-ketogluconic, lactic, isovaleric, isobutyric, and glycolic

acid (Cunningham and Kuiack 1992, Illmer and Schinner 1995, Rodrı́guez and Fraga 1999,

Chen, Rekha et al. 2006, Chuang, Kuo et al. 2007). In some studies, the detected acids

predominantly account for the levels of solubilization observed, while in others low production

of organic acids indicates that other factors contribute to solubilization (Illmer and Schinner

1992, Illmer, Barbato et al. 1995, Altomare, Norvell et al. 1999, Rodrı́guez and Fraga 1999,

Chen, Rekha et al. 2006, Chuang, Kuo et al. 2007). Additionally, some studies have found what

appeared to be other organic acids that were not identifiable (Chen, Rekha et al. 2006).

Since monazite is a REE phosphate mineral, we hypothesized that some PSMs may be able to

solubilize monazite for the extraction of REEs. However, there are a number of factors that

make solubilization of monazite more challenging than solubilization of calcium phosphates

typically used in PSM studies. For instance, REE-phosphates are known to have particularly low

solubilities in water, on the order of 10-13 M (10-11 g/L) (Firsching and Brune 1991), whereas the

solubility of Ca3(PO4)2 is 3.9×10-6 M (0.0012 g/L) (Haynes ed. 2015). Figure 1.1 shows the

predicted relationship between pH and total Nd solubilization for NdPO4 (see Appendix 1 for

calculations). From this we can see that even at a pH of 2, the total dissolved Nd is still below

10-5 M, whereas the corresponding dissolved Ca concentration at this pH is ≥ 1 M for Ca3(PO4)2

and a variety of other calcium phosphates (Akiyama and Kawasaki 2012). Based on these data,

those PSMs that rely on acidification alone for solubilization of Ca phosphate minerals can be

expected to be much less effective at solubilizing monazite. Thus, the production of effective

complexing agents will likely be critical to facilitate monazite solubilization.

6

Figure 1.1. Total Nd solubilized (log scale) from NdPO4 over a pH range. Curve was

calculated based on equilibrium data from (Puigdomenech 2013). Calculations are shown in

Appendix 1.

Some of the organic acids identified in PSM studies have also been shown to form complexes

with REEs. For instance, REE citrate complexes have been studied by a number of researchers,

and several different complexes between REEs and citrate have been proposed (Wood 1993,

Goyne, Brantley et al. 2010). The stability constant for the formation of 1:1 REE citrate

complexes has been estimated at about 109 (Martell and Smith 1974, Goyne, Brantley et al.

2010). One study evaluated citrate, along with oxalate, phthalate, and salicylate complexation of

REEs from monazite in the context of metal mobilization in soils (Goyne, Brantley et al. 2010).

They found citrate to be the most effective at releasing REEs from monazite under their

experimental conditions. In addition to organic acids, other chelating molecules could also be

involved in solubilization of REEs. For instance, some siderophores, iron complexing molecules

produced by many bacteria and fungi, have also been found to form complexes with REEs

(Christenson and Schijf 2011).

Another challenge for REE solubilization is that once solubilized, REEs may be removed from

the medium by other processes including re-precipitation or adsorption. For instance, REE

oxalates are highly insoluble (Gadd 1999) and therefore, the production of oxalic acid will need

to be monitored closely in a bioleaching process to minimize the precipitation of REE oxalates.

Also, REEs have been found to adsorb to the cell walls and extracellular polymers of some

organisms or be absorbed into cells (Moriwaki and Yamamoto 2013). Such effects could result

in the removal of solubilized REEs from the bulk medium.

7

1.2.2 Microbial reductive dehalogenation of chlorinated ethenes

Chlorinated ethenes are common groundwater contaminants in the United States (McCarty 1997,

Moran, Zogorski et al. 2007, US_Dept._of_H&HS 2007, Doherty 2014). Industrial use of

tetrachloroethene (PCE) and trichloroethene (TCE), used for their properties as organic solvents,

began in the early 1900s (Doherty 2014). Important industrial applications include metal

degreasing and dry cleaning (Mohn and Tiedje 1992, McCarty 1997). TCE was also used

historically for coffee decaffeination (Doherty 2014). Although use of these chemicals has

greatly decreased in recent decades, due to a combination of regulations and public concern,

existing contamination is expected to present a persistent problem for decades to come (Doherty

2014). Due to poor disposal practices as well as accidental spills and leaks, chlorinated ethene

contamination of groundwater is a widespread problem, with over half of Superfund sites having

TCE contamination (US_Dept._of_H&HS 1997).

TCE has been tied to a number of both acute and chronic human health effects including

neurological, kidney, liver, reproductive, and immune system effects (US_Dept._of_H&HS

1997, US_EPA 2011). Dichloroethene (cis-DCE and trans-DCE) and vinyl chloride (VC),

intermediates of PCE and TCE dechlorination, are also both highly toxic, and VC is a known

human carcinogen while PCE and TCE are suspected carcinogens (Kielhorn, Melber et al. 2000,

US_Dept._of_H&HS 2005).

A variety of remediation approaches have been studied for the treatment of chlorinated ethene

contamination in groundwater. Zero-valent iron particles, which are capable of donating

electrons for the reduction of chlorinated organics, represent an important abiotic approach to

remediation that has been widely studied and used for remediation (Gillham and O'Hannesin

1994, Arnold and Roberts 2000, Liu, Majetich et al. 2005). Biological degradation of TCE can

occur co-metabolically with some aerobic microorganisms in which oxygenase enzymes that

target other substrates also catalyze the oxidation of TCE due to a lack of enzyme specificity

(Bradley 2003). Anaerobic biodegradation of chlorinated ethenes via reductive dehalogenation

is another important bioremediation process and is one focus of research presented in this

dissertation.

Some anaerobic microorganisms are capable of reductive dechlorination of chlorinated organics

like PCE and TCE. In this process, the microorganisms use a chlorinated organic as their

terminal electron acceptor for energy metabolism (Smidt and de Vos 2004). The reduction of the

chlorinated organic, and the replacement of the chlorine with a hydrogen atom, is coupled to the

oxidation of an electron donor, usually hydrogen (Figure 1.2). A number of different

microorganisms have been identified that are capable of partially dechlorinating PCE and TCE to

the toxic intermediate DCE (Scholz-Muramatsu, Neumann et al. 1995, Sharma and McCarty

1996, Holliger, Hahn et al. 1998, Luijten, de Weert et al. 2003, Löffler, Cole et al. 2004).

However, only members of the genus Dehalococcoides (Dhc) have been found to be capable of

fully dechlorinating chlorinated ethenes to ethene (Maymo-Gatell, Chien et al. 1997, Smidt and

de Vos 2004).

8

Figure 1.2. Reductive dechlorination of chlorinated ethenes. Each successive chlorine

removal step involves the oxidation of one mole of H2 per mole of chlorinated ethene

reduced, with the transfer of two moles of electrons. (a) PCE reduction to TCE. (b) TCE

reduction to cis-DCE or trans-DCE. (c) cis-DCE or trans-DCE reduction to VC. (d) VC

reduction to ethene.

Dhc are strictly anaerobic bacteria that use chlorinated ethenes and other chlorinated organics as

electron acceptors (Maymo-Gatell, Chien et al. 1997, Smidt and de Vos 2004). These reductive

dechlorination reactions are catalyzed by membrane associated enzymes called reductive

dehalogenases (RDases) (Smidt and de Vos 2004). Genome sequencing of several Dhc strains

has revealed a large variety of putative RDase genes. The complement of RDase genes varies

greatly between strains and corresponds to variation in dechlorination abilities (Kube, Beck et al.

2005, Seshadri, Adrian et al. 2005, McMurdie, Behrens et al. 2009, Lee, Cheng et al. 2011).

Further, the suite of Dhc RDase genes that have been tied to functional activity are far fewer,

currently numbering six in all (pceA, tceA, vcrA, bvcA, cbrA, and mbrA) (Magnuson, Stern et al.

1998, Magnuson, Romine et al. 2000, Krajmalnik-Brown, Holscher et al. 2004, Muller, Rosner

et al. 2004, Adrian, Rahnenfuhrer et al. 2007, Chow, Cheng et al. 2010).

Dhc species have strict metabolic needs for growth and dechlorination. All known Dhc require

anaerobic conditions with certain chlorinated organics as terminal electron acceptors, hydrogen

as the electron donor, and acetate as a carbon source (Maymo-Gatell, Chien et al. 1997, Adrian,

Szewzyk et al. 2000, He, Ritalahti et al. 2003, Smidt and de Vos 2004). Further, although

cobalamin is a necessary cofactor for RDases (Smidt and de Vos 2004), no Dhc strains have

been reported to be capable of synthesizing cobalamin de novo (Kube, Beck et al. 2005,

Seshadri, Adrian et al. 2005, He, Holmes et al. 2007). Previously sequenced Dhc strains have

9

genes encoding for enzymes in the second part of the cobalamin biosynthesis pathway, lower

ligand attachment and rearrangement (Maymo-Gatell, Chien et al. 1997, Kube, Beck et al. 2005,

McMurdie, Behrens et al. 2009), but not for the first part of the pathway, corrin ring synthesis.

Additionally, although Dhc can produce all essential amino acids and Dhc strain 195 is capable

of nitrogen fixation, Dhc grows more robustly when certain amino acids and fixed nitrogen are

available for uptake from the environment (Lee, He et al. 2009, Zhuang, Yi et al. 2011). A

recent study also showed that, due to an incomplete Wood-Ljungdahl pathway, Dhc produces

carbon monoxide (CO) as a byproduct of acetate assimilation for methionine production

(Zhuang, Yi et al. 2014). Without other organisms capable of removing it, CO builds up during

Dhc growth, resulting in inhibition of Dhc growth and dechlorination.

Dhc has been shown to grow more robustly and dechlorinate more rapidly when grown in mixed

microbial communities or defined consortia, likely due to the ability of other organisms to

facilitate the specific growth requirements of Dhc (Maymo-Gatell, Chien et al. 1997, He, Holmes

et al. 2007, Lee, Cheng et al. 2011, Men, Feil et al. 2012). The improved performance of Dhc in

these communities, along with the greater relevance of these conditions to in situ dechlorination

at contaminated sites, make the study of complex dechlorinating communities important for

development of effective bioremediation strategies.

1.3 Dissertation overview

This dissertation describes investigations into the microbial processes discussed above, with a

guiding theme of using “omics” based approaches to deepen our understanding of

environmentally relevant microbial processes. The remainder of this dissertation is organized

into four chapters detailing those investigations followed by an additional chapter summarizing

the results and suggesting future research directions based on those findings.

Chapter 2 describes the establishment and characterization of a monazite bioleaching process.

This includes the initial enrichment and isolation of bioleaching microorganisms as well as the

optimization of bioleaching growth parameters. It also includes an analysis of organic acid

production during bioleaching and the potential contribution of those organic acids to overall

bioleaching effectiveness.

In Chapter 3, one of the organisms isolated in Chapter 2 was selected for an untargeted

metabolomic analysis of the bioleaching supernatant to further understand the bioleaching

process. This study investigated the excretion of metabolites by a monazite bioleaching fungus

when grown with and without an additional soluble phosphate source (K2HPO4). The gas

chromatography time of flight mass spectrometry (GC-TOF-MS) technique employed in this

chapter enabled a more comprehensive analysis of excreted metabolites and identification of

compounds potentially associated with bioleaching effectiveness.

Chapter 4 switches to an analysis of a more complex mixed microbial community degrading

TCE, as opposed to the bioleaching isolates studied in Chapters 2 and 3. This chapter describes

a metagenomic sequencing based analysis of the target community, revealing new information

about both the phylogenetic makeup of that community and its genetic content. In addition to

10

profiling the whole community, this chapter also has a particular focus on the Dhc strains within

that community, who are responsible for the community’s dechlorination activity.

Chapters 5 and 6 contain further metagenomic/genomic sequence based investigations of Dhc

strains in microbial communities and as isolates. In the Chapter 5, three Dhc containing

dechlorinating mixed communities were investigated using both metagenomic sequencing and a

Dhc genus wide microarray. The metagenomic sequencing data were then used to evaluate the

sensitivity and specificity of the microarray for detecting the targeted Dhc genes. In Chapter 6,

fully sequenced bacterial and archaeal genomes were analyzed bioinformatically for patterns of

genes (presence and absence of certain genes) that parallel the gene pattern associated with the

recently identified incomplete Wood-Ljungdahl pathway found in Dhc in order to determine

whether other known organisms share this newly identified version of the pathway.

Conclusions drawn from the above investigations and suggestions for future work are

summarized in Chapter 7.

11

Chapter 2:

Bioleaching of Rare Earth Elements from Monazite Sand

A version of this chapter has been submitted for publication as:

Brisson, Vanessa L., Wei-Qin Zhuang and Lisa Alvarez-Cohen (submitted 2015). "Bioleaching

of Rare Earth Elements from Monazite Sand." Biotechnology and Bioengineering.

12

2.1 Introduction

Rare earth elements (REEs) are increasingly in demand for a variety of technologies including

efficient batteries for hybrid and electric vehicles; permanent magnets used in wind turbines;

high efficiency electric lights; and a variety of consumer electronics (USDoE 2011, Alonso,

Sherman et al. 2012). Unfortunately, current processing techniques applied for extraction of

REEs from mineral ores require high energy inputs and use harsh chemicals, producing

environmentally damaging waste streams (Gupta and Krishnamurthy 1992, Alonso, Sherman et

al. 2012).

Phosphate solubilizing microorganisms (PSMs) can solubilize phosphate from otherwise low

solubility phosphate minerals (Rodrı́guez and Fraga 1999). A variety of both bacterial and

fungal PSMs have been identified and studied. Most of that work has focused on solubilization

of calcium phosphate minerals in the context of agricultural applications with the goals of

enhancing phosphate fertilizer effectiveness and promoting plant growth (Asea, Kucey et al.

1988, Illmer and Schinner 1992, Rodrı́guez and Fraga 1999, Gyaneshwar, Naresh Kumar et al.

2002, Arcand and Schneider 2006, Vassilev, Vassileva et al. 2006, Chuang, Kuo et al. 2007,

Morales, Alvear et al. 2007, Osorio and Habte 2009, Chai, Wu et al. 2011, Braz and Nahas

2012).

Organic acid production is considered to be a primary contributor to phosphate solubilization by

PSMs (Rodrı́guez and Fraga 1999, Nautiyal, Bhadauria et al. 2000, Gyaneshwar, Naresh Kumar

et al. 2002, Scervino, Papinutti et al. 2011). This activity is thought to be due to both pH

reduction and the formation of complexes between the organic acid and the cations released from

the phosphate minerals (Bolan, Naidu et al. 1994, Gadd 1999, Gyaneshwar, Naresh Kumar et al.

2002, Arcand and Schneider 2006).

Some organic acids identified in PSM studies have been analyzed for their ability to form

complexes with REEs. For example, the stability constants for the formation of 1:1 REE citrate

complexes have been estimated around109 (Martell and Smith 1974, Goyne, Brantley et al.

2010), and other REE citrate complexes have been proposed (Wood 1993). Beyond organic

acids, other chelating molecules, such as siderophores, can also interact with REEs and may

therefor be relevant to REE solubilization (Christenson and Schijf 2011).

Bioleaching offers a potentially more environmentally friendly alternative to conventional

extraction of REEs from ores. Since monazite is a REE phosphate mineral, the objectives of this

study were to investigate the potential of using PSMs to solubilize monazite for the extraction of

REEs and to evaluate the contributions of different organic acids to REE bioleaching. To the

best of our knowledge, no previous research has evaluated the potential use of PSMs for this

purpose.

13

2.2 Materials and methods

2.2.1 Enrichment and isolation of REE solubilizing microorganisms

REE-phosphate solubilizing enrichment cultures were established in National Botanical

Research Institute phosphate growth medium (NBRIP medium), a commonly used medium for

phosphate solubilization studies (Nautiyal 1999). See Table 2.1 for medium composition.

Inoculating source material was placed in 50 mL centrifuge tubes, covered with NBRIP medium,

and shaken to release cells. Soil and sand particles were allowed to settle and supernatant was

collected and used to inoculate enrichment bottles containing NBRIP medium with 10 g/L

glucose (added as carbon and energy source) and insoluble NdPO4 (phosphate source) [Sigma-

Aldrich, St. Louis, MO]. Enrichment cultures were shaken continuously and approximately 50%

of the growth medium was exchanged for fresh medium weekly.

REE-phosphate solubilizing microorganisms were isolated from enrichment cultures on selective

plates containing NBRIP medium solidified with 1.5% agar and containing powdered NdPO4 as

the phosphate source and 10 g/L glucose as carbon and energy source. Plates were inoculated

with 100 µL of enrichment culture and incubated at 30 °C. Once growth was observed,

individual colonies were selected and transferred to new plates. 10 µL sterile water was used to

help fungal spores to adhere to the sterile loop for transfer. This process was repeated for several

transfers to achieve isolated strains. Once fungal strains were isolated, they were maintained on

potato dextrose agar plates. Six known PSMs from culture collections (Aspergillus niger ATCC

1015, Burkholderia ferrariae FeG101, Microbacterium ulmi XIL02, Pseudomonas

rhizosphaerae IH5, Pseudomonas fluorescens, Sterptomyces youssoufiensis X4) were also tested

to their ability to grow on NBRIP-NdPO4 selective plates.

Organisms capable of growth on selective plates were screened for their ability to leach REEs

from monazite in liquid culture. These tests took place in 250 mL bottles, each containing 100

mL NBRIP medium with 10 g/L glucose and 7.5 g raw (unground) monazite sand. Bottles were

stirred continuously at 250 RPM at room temperature (25 to 28 ºC) and supernatant REE

concentrations were monitored over two weeks incubation.

2.2.2 DNA extraction, amplification, sequencing, and sequence analysis

For DNA extraction, biomass was collected from cultures grown on potato dextrose agar plates.

Biomass was scraped off of the agar, frozen under liquid nitrogen, and crushed with a mortar and

pestle to disrupt cell walls. DNA was extracted using the Qiagen DNeasy Plant Minikit. Fungal

18S and 5.8S genes and ITS regions were amplified by PCR using the NS1, NS3, NS4, NS8,

ITS1, and ITS4 universal fungal primers (White, Bruns et al. 1990). PCR reactions were carried

out using Qiagen Taq DNA polymerase. PCR products were purified by precipitation with

polyethylene glycol precipitation followed by ethanol wash, drying, and re-suspension in sterile

water (Sánchez, McFadden et al. 2003). Sanger sequencing was performed at the UC Berkeley

DNA sequencing facility.

2.2.3 Bioleaching growth conditions

Bioleaching experiments were carried out in 250 mL Erlenmeyer flasks with foam stoppers.

Each flask contained 0.5 g monazite sand [City Chemical LLC, West Haven, CT] ground to finer

14

than 75µm (200 mesh) and 50 mL growth medium. Chemical digestion and ICP-MS analysis of

the sand determined that it contained approximately 23.5% REEs by weight, indicating the

presence of other minerals besides monazite. The growth medium composition and carbon

source varied with each experiment. Four different basic media were used: NBRIP medium

(Nautiyal 1999), modified Pikovskaya medium (PVK medium) (Pikovskaya 1948, Nautiyal

1999), PVK medium without Mn and Fe, and modified ammonium salts medium (AMS

medium) (Parales, Adamus et al. 1994). See Table 2.1 for media compositions.

Table 2.1. Bioleaching growth media compositions.

Medium

Component

NBRIP

mediuma

PVK

mediumb

PVK mediumb

without Mn and Fe

AMS

meidumc

MgCl2·6H2O 5 g/L -- -- --

MgSO4·7H2O 0.25 g/L 0.1 g/L 0.1 g/L 1.0 g/L

KCl 0.2 g/L 0.2 g/L 0.2 g/L 0.2 g/L

(NH4)2SO4 0.1 g/L 0.5 g/L 0.5 g/L 0.66 g/L

NaCl -- 0.2 g/L 0.2 g/L --

MnSO4·H2O -- 0.002 g/L -- --

FeSO4·7H2O -- 0.002 g/L -- --

Trace elements

stock (1000x)d -- -- -- 1.0 mL/L

Stock A

(1000x)e -- -- -- 1.0 mL/L

aSee reference (Nautiyal 1999). bThis is a modification of the original Pikovskaya medium, with yeast extract omitted. See

references (Pikovskaya 1948, Nautiyal 1999). cThis is a modification of the original ammonium salts medium, with phosphate buffer omitted.

See reference (Parales, Adamus et al. 1994) dTrace elements stock contained FeSO4·7H2O (0.5 g/L), ZnSO4·7H2O (0.4 g/L), MnSO4·H2O

(0.02 g/L), H3BO3 (0.015 g/L), NiCl2·6H2O (0.01 g/L), EDTA (0.25 g/L), CoCl2·6H2O (0.05

g/L), and CuCl2·2H2O (0.005 g/L). eStock A contained FeNaEDTA (5 g/L) and NaMoO4·2H2O (2 g/L).

One of five carbon sources (glucose, fructose, sucrose, xylose, or starch) was added to the

medium prior to sterilization. After sterilization, flasks were inoculated with conidia (asexual

spores) collected from cultures maintained on potato dextrose agar. Conidia were collected from

plates by scraping with a sterile loop and suspended in sterile deionized water. Necessary

dilutions to achieve a spore concentration to 107 CFU per mL were determined by using

15

calibration curves relating optical density at 600 nm to CFU concentration. Each bioleaching

flask was inoculated with 1 mL (107 CFU) of spore suspension. Flasks were incubated at room

temperature (25 to 28 °C) and stirred with a one inch magnetic stir bar at 250 rpm for the

duration of the six day bioleaching experiments. All bioleaching experiments were conducted

with three biological replicates for each condition unless otherwise noted.

2.2.4 Abiotic leaching conditions

Abiotic leaching experiments were conducted in 50 mL flat bottomed polypropylene tubes. Each

tube contained 0.1 g monazite sand ground to finer than 75 µm (200 mesh) and 10 mL of the

desired leaching solution. Tubes were incubated at room temperature (25 to 28 °C) and stirred

with 0.5 inch stir bars at 250 rpm for 48 hours.

For abiotic leaching with organic acids and hydrochloric acid, acid solutions were prepared with

deionized water and filter sterilized through 0.2 µm filters prior to leaching. Acetic, citric,

itaconic, oxalic, and succinic acids [Sigma-Aldrich, St. Louis, MO] were tested at two

concentrations each: 2 mM and 20 mM, while gluconic acid [Sigma-Aldrich, St. Louis, MO] was

tested at 1.8 mM and 18 mM. HCl solutions were prepared to provide a range of pH from 1.8 to

3.7. Three experimental replicates were done for each acid concentration.

For abiotic leaching with spent medium, bioleaching spent medium was collected after six days

of bioleaching and filter sterilized through 0.2 µm filters. Filtered spent medium was treated to

remove REEs by adding 15 mL spent medium to a 50 mL tube containing 0.5 g Amberlite IR120

resin [Sigma-Aldrich, St. Louis, MO] and shaking horizontally for one hour. 10 mL of treated

spent medium was then used for leaching. Six replicates were done for each organism, each

from a separate bioleaching flask.

2.2.5 Biomass measurements

Volatile solids (VS) were determined as a measure of biomass production. VS was used rather

than dry weight because monazite sand becomes entrapped in the biomass during bioleaching.

By measuring VS, the organic portion of the total dry weight could be measured. Samples

comprising the entire contents of a bioleaching flask were filtered on glass microfiber filters.

Filtered samples were dried overnight at 105 ºC, cooled to room temperature, and weighed.

Samples were then ashed at 550 ºC for four hours, cooled to room temperature, and weighed

again. The difference between the dried weight and the ashed weight was determined as VS.

2.2.6 Analytical methods

To quantify REEs, Th and U concentrations, supernatant samples were collected, filtered with

0.2 µm filters, and diluted 100-fold in deionized water acidified with 1.5% nitric acid [70%, trace

metals grade, Fisher Scientific, Pittsburgh, PA] and 0.5% hydrochloric acid [36%, ACS Plus

grade, Fisher Scientific, Pittsburgh, PA]. Samples were analyzed on an Agilent Technologies

7700 series ICP-MS.

To quantify sugars and organic acids, supernatant samples were collected and filtered with 0.2

µm filters. 1.5 mL samples were acidified by adding 10 µL 6 M sulfuric acid [ACS grade,

Fisher Scientific, Pittsburgh, PA] and analyzed on a Waters 2695 HPLC system using a BioRad

16

Aminex HPX-87H carbohydrate/organic acids analysis column with 5 mM H2SO4 as the mobile

phase at a flow rate of 0.6 mL/min. Sugars were detected using a Waters 2414 refractive index

detector. Organic acids were detected using a Waters 2996 UV absorption detector monitoring

absorption at 210 nm. Calibration curves were prepared for concentration ranges of 0.1 to 10 g/L

for sugars and 0.5 mM to 20 mM for organic acids, with the exception of acetic acid, which

could only be detected to a minimum concentration of 1 mM. Sugar standards prepared included

glucose, fructose, sucrose, and xylose. Organic acid standards included acetic, citric, gluconic,

itaconic, lactic, oxalic, and succinic acids.

pH was measured using a Hanna Instruments HI1330B glass pH electrode and HI 2210 pH

meter. Although this meter is designed to measure pH in the range of -2 to 16, the lowest pH

standard allowed by the automatic calibration is 4.01. In order to test the accuracy for more

acidic samples, the meter was first calibrated with pH 4.01 and 7.01 standards and then used to

measure a pH 1.00 standard. This consistently gave a reading of 0.9, indicating that pH

measurements between 1.0 and 4.0 should be within 0.1 pH units of the correct value.

Phosphate concentrations were determined using the BioVision Phosphate Colorometric Assay

Kit according to the manufacturer’s instructions.

2.2.7 Statistical analyses

Statistical analyses were performed in Python using the StatsModels module. A significance

level of α = 0.05 was used for all analyses. Details of statistical methods used for each analysis

are given below. P-values from statistical analyses are tabulated in Table 2.4 at the end of this

chapter. Average concentrations and amounts are reported as mean ± standard deviation for

three replicates. For all analyses involving multiple comparisons, p-values were adjusted using

the Šidák correction (Šidák 1967) to maintain a significance level of α = 0.05. The correction is

given by:

padjusted = 1 − (1 − punadjusted)n

where n is the number of comparisons performed. Average concentrations and amounts are

reported as mean ± standard deviation for three replicates unless otherwise noted.

2.2.7.1 Analysis of biomass growth

Biomass (measured as VS) results were analyzed by performing pairwise comparisons to

positive and negative controls using a two-tailed T-test for independent samples with unequal

variance. This analysis was performed on the log transformed data, a common transformation

for biomass and cell count data due to the typical positive skew of such data (Olsen 2003, Olsen

2014).

2.2.7.2 Analysis of bioleaching performance

Differences in performance under different growth conditions were analyzed using a two-tailed

T-test for independent samples with unequal variance to compare total REE concentrations at the

17

end of six days of incubation. For each organism, data from different growth conditions (e.g.

different medium compositions) were compared by pairwise comparisons.

2.2.7.3 Analysis of proportional release of REEs and thorium

The proportional release of REEs during bioleaching was compared with the proportion of REEs

present in monazite by using Hotelling’s T2 test for two independent samples with unequal

covariance matrices. Each data point represented four measured values, which were the

proportions of La, Ce, Pr, and Nd, the dominant REEs in our monazite. Pairwise comparisons

were performed to compare leachate from each of the organisms to the monazite composition.

Differences in the release of Th in proportion to REE release were analyzed using a two-tailed

Student’s t-test for independent samples with unequal variance. Pairwise comparisons were

performed to compare Th in leachate from each of the organisms to the monazite composition

and to compare leachate from each of the organisms to each other.

2.2.7.4 Analysis of abiotic leaching with hydrochloric acid, organic acids, and spent

medium

For analysis of abiotic leaching of REEs, a weighted linear model was used in order to analyze

the effects of one continuous (pH) and one categorical (different acids or spent supernatant from

different organisms) independent variable on the dependent variable (REE concentration). The

sample variances were first estimated for each acid and for the supernatant from each organism.

These variances were then used to determine weights in the model. In order to estimate the

sample variances, a least squares linear fit between pH and REE concentration was first

performed for the HCl data. The slope of this line was then used to estimate a linear fit for each

of the other acids and for the supernatant data. The sum squared error in relation to that linear fit

was used to estimate the variance for each and those variance estimates were used to weight the

model.

For analysis of abiotic leaching of Th, an initial least squares regression analysis of the data from

HCl solutions ranging in pH from 1.8 to 3.7 showed no correlation between pH and Th

solubilization. Therefore, data were analyzed using a two-tailed Student’s T-test for independent

samples with unequal variance to do pairwise comparisons of each organic acid and supernatant

solution to the HCl solution. Different concentrations of each organic acid were analyzed

separately.

2.3 Results and discussion

2.3.1 Enrichment, isolation and identification of bioleaching microorganisms

Source inoculation materials for establishing REE-phosphate solubilizing enrichment cultures

were collected from two different locations: tree root associated soil from the UC Berkeley

campus and sand and sediment samples from Mono Lake in California. We hypothesized that

root associated soil might yield PSMs because root associated microbial communities are known

to support plant growth by improving nutrient availability (Rodrı́guez and Fraga 1999), and that

18

since Mono Lake is an alkaline salt lake with high concentrations of heavy metals and REEs

(Johannesson and Lyons 1994), it might serve as a source of microorganisms that are tolerant of

high REE concentrations.

Enrichment cultures capable of utilizing monazite as their sole phosphate source were

successfully cultivated from both source materials. Two known PSMs from culture collections

(Aspergillus niger ATCC 1015, Burkholderia ferrariae FeG101) were also capable of growth on

NBRIP-NDPO4 selective plates. Initial screening of these organisms identified the three most

promising bioleaching organisms for further study, all of which were fungi: Aspergillus niger

ATCC 1015, isolate ML3-1 from a Mono Lake enrichment culture, and isolate WE3-F from a

tree root soil enrichment culture (Figure 2.1).

Figure 2.1. Initial characterization of REE solubilization from unground monazite by fungal

and bacterial isolates. Note that these initial characterizations used unground monazite sand.

Subsequent experiments were performed with ground monazite.

Sequences of 18S, 5.8S, and ITS regions of ML3-1 and WE3-F were determined and have been

deposited in Genbank with accession numbers KM874778, KM874779, KM874780, and

KM874781. Based on BLAST comparisons of these sequences to the NBRIP nucleotide

database, ML3-1 and WE3-F showed high sequence similarity (≥ 99%) to Aspergillus terreus

and Paeciliomyces sp. respectively. Microscopic observation of ML3-1 and WE3-F showed

morphological characteristics consistent with these identifications. Previous studies have

reported phosphate solubilizing activity for some strains of both the Aspergillus and

Paeciliomyces genera (Ahuja, Ghosh et al. 2007, Chuang, Kuo et al. 2007, Braz and Nahas 2012,

Mendes, Vassilev et al. 2013).

19

2.3.2 Biomass growth during bioleaching

Biomass production after six days of growth with monazite as sole phosphate source was

compared to growth with 0.4 g/L K2HPO4 as phosphate source (positive control) and to growth

without added phosphate (negative control) (Figure 2.2). For all three organisms, growth on

monazite resulted in average VS concentrations approximately tenfold greater than the negative

control. This difference was statistically significant for all three organisms. Significant

differences in VS production were not observed between growth on monazite and growth on

K2HPO4, demonstrating that these organisms can utilize monazite as a phosphate source for

growth.

Figure 2.2. Biomass production measured as VS after six days incubation with different

phosphate sources: 10 g/L monazite, 0.4 g/L K2HPO4 (positive control), or no added

phosphate i.e. growth on trace phosphate contamination in medium and inoculum (negative

control). All incubations were in AMS medium with 10 g/L glucose. Error bars indicate

95% confidence intervals around the geometric means.

2.3.3 Bioleaching performance under different growth conditions

Several previous studies have tried to optimize the solubilization of phosphate minerals by PSMs

(Asea, Kucey et al. 1988, Nautiyal 1999, Nautiyal, Bhadauria et al. 2000, Chuang, Kuo et al.

2007, Chai, Wu et al. 2011). Factors addressed include carbon source, nitrogen source, and

medium composition, including variations in metals concentrations. In general, carbon source

and medium composition were found to have significant effects, which sometimes varied

between different organisms in the same study (Nautiyal 1999, Nautiyal, Bhadauria et al. 2000,

20

Chai, Wu et al. 2011). Studies addressing nitrogen source found either minimal effect or a

preference for ammonium, particularly for studies involving fungal PSMs (Asea, Kucey et al.

1988, Nautiyal, Bhadauria et al. 2000, Chuang, Kuo et al. 2007, Chai, Wu et al. 2011).

Therefore, in this study, medium composition and carbon source were the focus of growth

condition optimization while the nitrogen source was fixed as ammonium. Results of these

experiments are shown in Figures 2.3, 2.4, and 2.5, and are discussed below.

Figure 2.3. Bioleaching of REEs from monazite under different growth conditions. Error

bars indicate standard deviations around the means. (a) Different growth media: PVK

medium, PVK medium without Fe or Mn, AMS medium, and NBRIP medium, all containing

10 g/L glucose as carbon source. (b) Different carbon sources: glucose, fructose, sucrose,

xylose, and starch, all in AMS medium with initial carbon source concentrations of 10 g/L.

(c) Different starting glucose concentrations: 5 g/L, 10 g/L, and 100 g/L, all in AMS

medium.

21

Figure 2.4. Total sugar concentrations during bioleaching of monazite. Error bars indicate

standard deviations around the means. (a) Different growth media: PVK medium, PVK

medium without Fe or Mn, AMS medium, and NBRIP medium, all containing 10 g/L

glucose as carbon source. (b) Different carbon sources: glucose, fructose, sucrose, xylose,

and starch, all in AMS medium with initial carbon source concentrations of 10 g/L. For the

sucrose medium, data include the sum of glucose, fructose and sucrose concentrations. For

starch medium, data include only glucose concentrations rather than starch, which could not

be determined by the detection method used. (c) Different initial glucose concentrations: 5

g/L, 10 g/L, and 100 g/L, all in AMS medium. For the 100g/L glucose condition, glucose

concentration remained above the scale of the graph throughout bioleaching.

22

Figure 2.5. pH during bioleaching of monazite. Error bars indicate standard deviations

around the means. (a) Different growth media: PVK medium, PVK medium without Fe or

Mn, AMS medium, and NBRIP medium, all containing 10 g/L glucose as carbon source. (b)

Different carbon sources: glucose, fructose, sucrose, xylose, and starch, all in AMS medium

with initial carbon source concentrations of 10 g/L. (c) Different initial glucose

concentrations: 5 g/L, 10 g/L, and 100 g/L, all in AMS medium.

23

Varying growth media influenced REE solubilization performance (Figure 2.3-a), with the

highest average REE solubilization for all organisms occurring with AMS medium which

resulted in average total REE concentrations after six days of bioleaching of 86 ± 6, 101 ± 27,

and 112 ± 16 mg/L for A. niger, ML3-1, and WE3-F respectively. These concentrations

correspond to 3, 4, and 5% recovery of the total REEs present in the monazite sand. Growth on

NBRIP medium consistently resulted in poor solubilization performance, with average total REE

concentrations after six days of bioleaching of 30 ± 2, 28 ± 1, and 30 ± 2 mg/L for A. niger,

ML3-1, and WE3-F respectively. In pairwise comparisons, the difference in REE solubilization

between AMS medium and NBRIP medium was statistically significant for A. niger and WE3-F,

and was marginally significant for ML3-1 (p = 0.065), likely due to high variability and low

sample size.

Phosphate concentrations observed during bioleaching were much lower than REE

concentrations. The molar ratio of REEs to phosphate in the monazite sand is expected to be ≈ 1.

However, the observed molar ratio of REEs to phosphate in solution at the end of bioleaching

was well above one, and varied for different organisms and different media compositions (Table

2.2). This ratio ranged from 5 ± 1 for ML3-1 grown on NBRIP medium to 170 ± 30 for A. niger

grown on AMS medium. These data indicate that much of the phosphate associated with REEs

in the monazite was either not released or was removed from solution. As indicated by the

biomass measurements, some of the phosphate released from the monazite was used for biomass

production. Estimates of phosphate incorporated into biomass made by assuming 3% dry weight

biomass phosphorus content (Rittmann and McCarty 2001) suggest that 77 mg/L, 67 mg/L and

61 mg/L phosphorus (i.e. 230 mg/L, 210 mg/L and 190 mg/L phosphate) would need to be taken

up to support the 2.6 g/L, 2.2 g/L and 2.0 g/L biomass generated by A. niger, ML3-1, and WE3-F

respectively after six days of growth on AMS with 10 g/L glucose. Assuming equimolar release

of REEs and phosphate from the monazite, the amount of phosphate required to support biomass

growth is two to six times greater than the REE quantities released under these conditions,

suggesting that phosphate consumption for growth accounts for the low phosphate

concentrations in solution. Altomare et al. observed a similar reduction in phosphate

concentration concurrent with an increase in calcium solubilization during growth of

Trichoderma harzanum Rifai 1295-22 on hydroxyapatite, which they also attributed to phosphate

uptake by the organism (Altomare, Norvell et al. 1999). The apparently low REE concentration

compared to the estimated phosphate in the biomass may be due to the inherent uncertainty in the

estimation of biomass as VS and the assumption of 3% phosphate concentration. This

discrepancy may also be due to the removal of REEs from the system by other processes

including re-pricipitation (e.g. as REE-oxalates) (Gadd 1999) or adhesion to microbial cells

(Moriwaki and Yamamoto 2013). If these processes are occurring, they may limit the potential

for total recovery of REEs by bioleaching.

Table 2.2. Molar ratio of total REEs to phosphate measured after bioleaching with different

media compositions (mean ± standard deviation).

Medium A. niger ML3-1 WE3-F

PVK 29 ± 23 11 ± 1 126 ± 8

PVK without Mn for Fe 62 ± 98 14 ± 2 68 ± 45

AMS 166 ± 25 9 ± 4 102 ± 78

NBRIP 8 ± 4 5 ± 1 5 ± 0

24

Previous PSM studies of Ca3(PO4)2 solubilization have reported phosphate concentrations in

liquid cultures on the order of 250 to 520 mg/L (Rodrı́guez and Fraga 1999, Chen, Rekha et al.

2006, Chuang, Kuo et al. 2007, Chai, Wu et al. 2011, Scervino, Papinutti et al. 2011). In

contrast, the maximum phosphate concentration observed in this study during monazite

solubilization with different media compositions was 15 mg/L (ML3-1 grown on AMS medium).

Differences in solubilization between different phosphate minerals has been previously reported,

even when using the same PSMs (Illmer and Schinner 1995, Rodrı́guez and Fraga 1999,

Souchie, Azcón et al. 2006, Chuang, Kuo et al. 2007, Delvasto, Valverde et al. 2008, Adeleke,

Cloete et al. 2010). Also, REE-phosphates are known to have particularly low solubilities in

water, on the order of 10-13 M (10-11 g/L) (Firsching and Brune 1991), whereas the solubility of

Ca3(PO4)2 is 3.9×10-6 M (0.0012 g/L)(Haynes ed. 2015).

With AMS medium and both versions of PVK medium, glucose was completely or almost

completely consumed (≤ 0.6 g/L remaining) by the end of the experiment (Figure 2.4-a). In

contrast, with NBRIP medium, glucose concentrations were only reduced to 6.3 ± 0.1, 7.4 ± 0.1,

and 7.1 ± 0.0 g/L for A. niger, ML3-1, and WE3-F respectively. Growth on NBRIP medium also

resulted in smaller reductions in pH than growth on other media (Figure 2.5-a).

In the study by Nautiyal that introduced NBRIP medium, several versions of the medium were

compared with several modifications of Pikovskaya medium, including the yeast extract free

version used in this study (PVK) (Nautiyal 1999). They showed significantly enhanced

solubilization of phosphate from Ca3(PO4)2 by a variety of bacterial strains (five Pseudomonas

and three Bacillus strains) with NBRIP medium. However, the generally poor performance of

NBRIP medium in this study with fungi indicates that despite its widespread use in phosphate

solubilization studies, NBRIP medium is not well suited for some PSMs and/or solubilization of

some phosphate minerals.

Among the five carbon sources tested, there was no clear over-performer (Figure 2.3-b). For

ML3-1 and WE3-F, REE solubilization profiles were similar for all carbon sources tested. REE

solubilization performance for A. niger was much more variable between replicates with the

same carbon source. However, pairwise comparison of REE solubilization revealed an apparent

(and statistically significant) preference by A. niger for starch over fructose. In contrast to the

variability in REE solubilization, pH and carbon source consumption profiles were similar for A.

niger for all carbon sources tested, as they also were for the other two isolates (Figures 2.4-b and

2.5-b).

In the glucose concentration range tested (5 g/L, 10 g/L, and 100 g/L), higher glucose

concentrations did not correspond to improved REE solubilization for ML3-1 and WE3-F

(Figure 2.3-c). For A. niger, the performance was again quite variable, and although the average

REE concentration was highest for 100 g/L glucose, this difference was not statistically

significant. The pH reduction was comparable for all glucose concentrations tested (Figure 2.5-

c). Interestingly, for the lowest glucose concentration (5 g/L), the glucose was consumed by the

fourth day (Figure 2.4-c), but REE concentrations continued to rise through the end of the

experiment. For the highest glucose concentration (100 g/L), glucose levels remained above 10

g/L for the entire experiment. These data indicate that glucose availability was not the limiting

factor for bioleaching under the conditions tested.

25

Although we found no previous studies of bioleaching of REEs from monazite, one study

examined bioleaching of REEs from red mud, a byproduct of bauxite ore processing for alumina

production (Qu and Lian 2013). In that study, a fungus, Penicillium tricolor RM-10, was

isolated and its REE leaching abilities were evaluated. For direct bioleaching of the red mud, a

similar process to the monazite bioleaching in this study, they reported leaching efficiencies of

20% to 40% for total REEs (10% to 80% for individual REEs) depending on the amount of red

mud provided. The highest red mud concentrations corresponded to the lowest efficiency,

indicating that the process may have been approaching a solubility limitation at the highest red

mud concentration. The leaching efficiency for monazite bioleaching in this study under

standard conditions (AMS medium, 10 g/L glucose) was 3% to 5% of total REEs present in the

monazite. Although bioleaching efficiency for the red mud was higher than for the monazite, the

absolute REE concentrations in the red mud leachate ranged from 20 to 60 mg/L total REEs,

compared to 60 to 120 mg/L for monazite bioleaching by ML3-1 and WE3-F in this study.

Given the differences in the two studies, it is not surprising that leaching efficiencies differ.

Some of the most obvious differences are the ores (red mud vs. monazite) and the experimental

time scales (50 days vs. 6 days). Additionally, for monazite bioleaching, the monazite served as

a phosphate source for growth, whereas phosphate was provided in the growth medium for red

mud bioleaching. .The stress caused by the low phosphate concentration during monazite

bioleaching may have induced a different bioleaching mechanism. Differences in pH may have

also affected the process. Since the red mud was highly alkaline, the initial pH for red mud

bioleaching was between 9 and 11, as compared to 5 for monazite bioleaching. However, during

red mud bioleaching, the pH dropped to acidic conditions for all but the highest red mud

concentrations tested.

2.3.4 Proportional release of REEs and thorium during bioleaching

Proportions of REEs and Th in monazite (seven replicates) and in bioleaching supernatant (nine

replicates for each organism) are shown in Figure 2.6. The monazite sand used in this study is

dominated by Ce, La, Nd, and Pr, and the bioleaching supernatant reflected this composition.

Release of Th during bioleaching was low in proportion to REEs. For standard growth

conditions (AMS medium, 10 g/L glucose), averages for released Th were 0.026 ± 0.046, 0.0003

± 0.0001, and 0.0028 ± 0.0039 mole Th per mole REEs for A. niger, ML3-1, and WE3-F

respectively (nine replicates each). In comparison, the monazite contained 0.11 ± 0.02 mole Th

per mole REEs (seven replicates). Differences in Th release between organisms were not

statistically significant.

26

Figure 2.6. Proportions of (a) REEs and (b) Th in monazite and in bioleaching supernatant

after six days of bioleaching. Concentrations are normalized to total REE content of

samples. Error bars indicate standard deviations around the means. Bioleaching samples are

from growth on AMS medium with 10 g/L glucose.

Proportions of REEs in bioleaching supernatant generally reflect the proportions present in the

monazite (Figure 2.6-a). Analysis revealed only small, but statistically significant differences

between the REE composition of the bioleaching supernatant and that of the monazite.

Supernatant from all organisms contained a slightly higher proportion of La as compared to the

monazite and slightly lower proportions of Ce and Nd. Some previous studies suggest possible

explanations for these variations in REE proportions. For example, in their study of REE release

from monazite by organic acids, Goyne et al. found that several organic acids preferentially

released Nd over Ce and La (Goyne, Brantley et al. 2010). Another possible contributing factor

is the preferential adsorption of some REEs to microbial cell walls after release from monazite,

as was shown previously for a number of different bacteria (Moriwaki and Yamamoto 2013).

2.3.5 Organic acid production during bioleaching

Organic acid production was observed for all organisms, with each organism producing a

different set of acids, some of which could be identified based on known standards. For a given

organism, organic acid production was variable, and not all acids were detected in all biological

replicates. Table 2.3 lists the maximum observed concentrations for identified organic acids

during bioleaching experiments along with the percentage of bioleaching flasks for which each

acid was detected.

27

Table 2.3. Maximum observed concentrations of identified organic acids produced by three

fungal isolates during bioleaching and percentage of bioleaching flasks for which each acid was

detected.

Organic

Acid

A. niger ML3-1 WE3-F

Maximum

concentration

Percentage

of flasks

Maximum

concentration

Percentage

of flasks

Maximum

concentration

Percentage

of flasks

Acetic 0% 0% 3.8 mM 8%

Citric 15.9 mM 78% 0% 0%

Gluconic 5.3 mM 17% 0% 1.2 mM 67%

Itaconic 0% >20 mM 97% 0%

Lactic 0% 0% 0%

Oxalic 2.0 mM 17% 0% 0%

Succinic 1.6 mM 56% 4.0 mM. 28% 5.4 mM 11%

A. niger produced citric, gluconic, oxalic, and succinic acids. A. niger is known to produce these

acids and is used industrially to produce citric and gluconic acids (Magnuson and Lasure 2004,

Papagianni 2004). Optimization of A. niger acid production has revealed that low pH (< 2)

favors citric acid production while higher pH (> 4) favors gluconic and oxalic acid production

(Magnuson and Lasure 2004, Ramachandran, Fontanille et al. 2006). In this study, the pH of the

A. niger bioleaching cultures ranged from 2.0 to 2.8 in the later part of the bioleaching process (t

= 4 or 6 days), closer to the optimal conditions for production of citric acid. The production of

higher concentrations of oxalic acid corresponded with lower concentrations of REEs, which is

consistent with the known low solubility of REE-oxalates (Gadd 1999). Oxalic acid production

by A. niger was observed at the end of some bioleaching experiments, and is likely responsible

for the decrease in soluble REEs observed on the final day of these experiments.

ML3-1 produced primarily itaconic and succinic acids and WE3-F produced acetic, gluconic,

and succinic acids. As noted above, ML3-1 showed high sequence similarity to A. terreus, some

strains of which have been used industrially to produce itaconic acid (Magnuson and Lasure

2004). A. niger and WE3-F also produced some compounds that generated large peaks in the

HPLC UV absorbance chromatogram, but could not be identified based on the available

standards. Other PSM studies have also observed additional compounds presumed to be other

organic acids potentially involved in phosphate solubilizing activity (Chen, Rekha et al. 2006).

2.3.6 Abiotic leaching with hydrochloric acid and organic acids

Leaching with inorganic hydrochloric acid solutions representing a range of acidities (five pHs

ranging from 1.8 to 3.7) indicated an inverse correlation between pH and REE solubilization that

was approximately linear within the range tested (r2 = 0.96) (Figure 2.7-a). Leaching with the

28

most acidic solution (pH 1.8) resulted in the greatest REE solubilization, achieving a

concentration of 19 ± 2 mg/L. This inverse relationship is consistent with what is expected for

this pH range. Oelkers and Poitrasson studied monazite solubility in HCl acidified water

(Oelkers and Poitrasson 2002). Although their results cannot be directly compared to the results

of this study due to the different experimental methods, they also found an inverse relationship

between pH and REE solubilization.

All organic acids tested, with the exception of oxalic acid, leached REEs from monazite to

concentrations greater than 1 mg/L (Figure 2.7-a). The low observed REE solubilization with

oxalic acid, even at low pH, is consistent with the known insolubility of REE-oxalates. Because

this behavior is known and is particular to oxalic acid, oxalic acid was excluded from the

statistical analysis of abiotic leaching of REEs by other acids and spent supernatant.

For acetic, gluconic, itaconic, and succinic acids, the solubilization of REEs was not significantly

different from what would be expected for the direct effect of pH. However, for citric acid, REE

solubilization was slightly higher (approximately 3 mg/L, statistically significant) than would be

expected based solely on pH reduction. Goyne et al. studied the ability of several organic acids

to dissolve REEs from monazite, and found that citrate leached more REEs than the other acids

tested (Goyne, Brantley et al. 2010). However, the observed REE solubilization levels for all

organic acids tested (≤ 18 mg/L) were substantially lower than those observed for the active

cultures (averages 60-120 mg/L for ML3-1 and WE3-F depending on growth conditions).

29

Figure 2.7. Abiotic leaching of REEs from monazite by HCl solutions, organic acids, and

bioleaching spent medium. Grey lines show the least squares fit to the HCl data (r2 = 0.96).

(a) Leaching with organic acids compared to HCl. (b) Leaching with spent medium from

bioleaching compared to HCl. REE concentrations observed at the end of bioleaching are

shown with unfilled markers for comparison.

With respect to solubilization of radioactive Th during abiotic monazite leaching, a correlation

was not detected between pH and Th solubilization (Figure 2.8) and solubilization of Th was low

overall in the HCl solutions (≤ 0.01 mg/L in 14 of 15 samples). Citric and oxalic acids

solubilized Th from monazite significantly more than HCl solutions (1.0 ± 0.1 mg/L, 1.4 ± 0.1

mg/L, 0.5 ± 0.1 mg/L, and 3.2 ± 0.1 mg/L for 2 mM citric, 20 mM citric, 2 mM oxalic, and 20

mM oxaic respectively) (Figure 2.9). Acetic, gluconic, itaconic, and succinic acids did not

solubilize Th, resulting in Th concentrations below 0.1 mg/L for each acid tested.

30

Figure 2.8. Relationship between pH and solubilization of Th for abiotic leaching of

monazite with solutions of HCl. (a) All data (b) Data excluding apparent outlier at pH = 2.8,

[Th] = 0.41 mg/L. Lines show least squares linear fits to the data. Neither linear fit is

statistically significant.

Figure 2.9. Abiotic leaching of Th by different organic acids and by spent medium from

three bioleaching organisms. Error bars indicate sample standard deviations around the

means. (n = 15 for HCl, n = 3 for each concentration of organic acid, n = 6 for spent

supernatant for each organism)

31

2.3.7 Abiotic leaching with spent medium from bioleaching

After six days of growth with monazite, medium from the fungal bioleaching experiments (six

biological replicates for each organism) was filtered to remove cells and treated with Amberlite

IR-120 resin to remove REEs from solution, reducing total REE concentrations to less than 0.8

mg/L. The spent medium samples were then tested for monazite solubilization capabilities.

Spent medium from ML3-1 and WE3-F solubilized REEs to levels above what would be

expected based on the low pH of the spent medium (Figure 2.7-b). Furthermore, citric acid was

not detected in medium from bioleaching with these organisms (Table 2.3), so no additional REE

solubilization could be attributed to citric acid. Spent medium from A. niger was not effective at

leaching REEs from monazite, likely due to the presence of oxalic acid, a known REE

precipitant (Gadd 1999). Spent medium from A. niger solubilized Th significantly more than the

HCl solutions while spent medium from ML3-1 and WE3-F did not (Figure 2.9).

The ability of spent medium to leach REEs from monazite indicates that the presence of

microorganisms is not necessary for at least some portion of the observed solubilization.

However, the higher REE concentrations observed for active bioleaching compared to spent

medium indicate that the microorganisms’ presence promote the most effective leaching. One

contributing factor may be consumption of phosphate by the microorganisms that hinders

precipitation. As noted above, the high molar ratios of REEs to phosphate during bioleaching

indicate that the majority of phosphate released from monazite during bioleaching is removed

from solution for incorporation into biomass.

These data indicate that both ML3-1 and WE3-F release as yet unidentified compounds into

solution that are more effective than the identified organic acids at solubilizing REEs from

monazite. Based on these results, ML3-1 and WE3-F are more promising organisms for the

development of bioleaching for processing monazite than A. niger. This study provides a proof

of concept for such a bioleaching process. Further study is needed to understand bioleaching

mechanisms and to optimize the process to achieve an economically viable alternative to

conventional REE extraction processes.

32

2.3.8 Statistical analyses results

Table 2.4. P-values for statistical analyses reported in the text for bioleaching and abiotic

leaching of monazite. For analyses involving multiple comparisons, p-values are Šidák adjusted.

Unless otherwise noted, only p-values indicating statistical significance (p < 0.05) are given.

Comparison Condition p-value

(Šidák adjusted for multiple

comparisons)

Growth difference between monazite

and negative control (Figure 2.2)

A. niger

ML3-1

WE3-F

0.0028

0.0013

0.017

REE solubilization differences between

AMS and NBRIP (Figure 2.3-a)

A. niger

ML3-1

WE3-F

0.0029

0.065 (marginally significant)

0.0018


fructose and starch (Figure 2.3-b)

A. niger

0.045

Proportional release of Th during

bioleaching in comparison to Th

content of monazite (Figure 2.6-b)

A. niger

ML3-1

WE3-F

0.0013

<0.0001

<0.0001

Proportional release of different REEs

in comparison to REE proportions in

monazite (Figure 2.6-a)

A. niger

ML3-1

WE3-F

0.037

<0.0001

<0.0001

Linear correlation between REE

solubilization and pH (Figure 2.7-a)

HCl solutions <0.0001


organic acids / spent medium and HCl

control (Figure 2.7-a and 2.7-b)

citric acid

ML3-1

WE3-F

0.0001

0.0003

<0.0001

Th solubilization difference between

organic acids / spent medium and HCl

(Figure 2.9)

2 mM citric acid

20 mM citric acid

2 mM oxalic acid

20 mM oxalic acid

A. niger

0.0079

0.0005

0.0008

0.0019

0.015

33

Chapter 3:

Metabolomic Analysis of a Monazite Bioleaching Fungus

34

3.1 Introduction

Bioleaching of monazite by phosphate solubilizing microorganisms (PSMs) offers a possible

alternative to conventional monazite extraction, potentially resulting in a more environmentally

sustainable extraction process. PSMs are microorganisms that have the ability to solubilize

phosphate ions from otherwise insoluble phosphate compounds and minerals (Rodrı́guez and

Fraga 1999). As was demonstrated in Chapter 2, some PSMs are capable of releasing REEs

from monazite sand and thus could be useful for a potential monazite bioleaching process. The

organism used in this study is a fungal monazite bioleaching PSM, designated as WE3-F and

identified as a Paeciliomyces species. The isolation, identification, and initial characterization of

this organism were described in Chapter 2. This organism was selected for further study based

on its consistent bioleaching performance in that study.

Current understanding of the mechanisms of phosphate solubilization by PSMs indicates that two

main contributing factors are acidification of the medium and the formation of complexes

between organic acids produced by the PSMs and cations associated with phosphate in the

mineral and released during solubilization (Bolan, Naidu et al. 1994, Rodrı́guez and Fraga 1999,

Nautiyal, Bhadauria et al. 2000, Gyaneshwar, Naresh Kumar et al. 2002, Arcand and Schneider

2006, Scervino, Papinutti et al. 2011). The investigation of monazite bioleaching described in

Chapter 2 indicated that although both acidification and complexation with citric acid were able

to contribute to monazite leaching, these contributions did not account for the levels of leaching

seen during bioleaching or when leaching with spent bioleaching medium. Therefore, in order to

better understand the bioleaching process, another approach was necessary to identify a larger

array of small molecules released during bioleaching that might be associated with bioleaching

effectiveness.

Untargeted metabolomics technologies provide the opportunity to accurately detect a large

number of different organic molecules and compare relative concentrations across different

conditions, providing insight into biological processes. Metabolomic analyses applied to

excreted metabolites are sometimes referred to as exometabolomics or metabolic footprinting

(Kell, Brown et al. 2005). Metabolomic footprinting has been applied to investigate other

eukaryotic microbial processes including wine production by yeast and microalgae growth in

bioreactors (Howell, Cozzolino et al. 2006, Sue, Obolonkin et al. 2011, Richter, Dunn et al.

2013).

In this study an untargeted metabolomics approach using gas chromatography time of flight mass

spectrometry (GC-TOF-MS) was used to analyze metabolites excreted into the growth medium

during monazite bioleaching under two different growth conditions: growth with monazite as the

only phosphate source (using phosphate limitation to force monazite solubilization) and growth

with the addition of a soluble phosphate source (relieving the phosphate limitation stress). This

analysis had two parallel goals. One was to identify metabolites excreted into solution that may

contribute to monazite solubilization, and the second was to examine the effects of phosphate

availability on growth and metabolic processes of a bioleaching microorganism.

35


3.2.1 Organism and bioleaching growth conditions

Bioleaching experiments were performed with monazite bioleaching fungal isolate ML3-1,

whose isolation and identification as a Paeciliomyces species were described in Chapter 2.

Growth conditions were based on those described in Chapter 2 with some modifications.

Briefly, bioleaching was conducted in 250 mL Erlenmeyer flasks, each containing 0.5 g ground

monazite sand [City Chemical LLC, West Haven, CT] (finer than 200 mesh) and 50 mL

modified ammonium salts medium (AMS medium) (Parales, Adamus et al. 1994). AMS

medium contained 1.0 g/L MgSO4·7H2O, 0.2 g/L KCl, 0.66 g/L (NH4)2SO4, 1.0 mL/L 1000x

trace elements stock solution, and 1.0 mL/L stock A. The 1000x trace elements stock solution

contained 0.5 g/L FeSO4·7H2O, 0.4 g/L ZnSO4·7H2O, 0.02 g/L MnSO4·H2O, 0.015 g/L H3BO3,

0.01 g/L NiCl2·6H2O, 0.25 g/L EDTA, 0.05 g/L CoCl2·6H2O, and 0.005 g/L CuCl2·2H2O. Stock

A contained 5 g/L FeNaEDTA and 2 g/L NaMoO4·2H2O. 10 g/L glucose was added as a carbon

and energy source and air in the headspace served as oxygen source. Each flask was inoculated

with 1 mL of spore suspension containing approximately 107 CFU and sealed with a foam

stopper. Flasks were stirred continuously at 250 RPM and incubated at 28 ºC for the duration of

the bioleaching experiment.

Two different growth conditions were compared to study the effects of a soluble phosphate

source: growth with monazite only and growth with K2HPO4 and monazite. For the K2HPO4 and

monazite condition flasks, 0.4 g/L K2HPO4 was added.

3.2.2 Quantification of REEs, Th, phosphate, glucose, pH and biomass

REE, Th, phosphate, glucose, pH, and biomass were quantified by the analytical methods

described in Chapter 2. Briefly, REE and Th concentrations were measured by ICP-MS.

Phosphate concentration was measured by colorimetric assay. Glucose was measured by HPLC

with refractive index detection. pH was measured using a Hanna Instruments HI 2210 pH meter.

Biomass was measured as total volatile solids by drying and subsequent ashing of filter collected

samples. REE, Th, phosphate, glucose, and pH measurements were taken for six biological

replicates for each time point (0, 2, 4, and 6 days after inoculation), while biomass measurements

were taken for three biological replicates at time points 2, 4, and 6 days.

3.2.3 Metabolomic analysis

Samples of bioleaching supernatant were collected, filtered through 0.2 µm syringe filters to

remove cells, and immediately frozen and stored at -80 ºC. Six replicate samples were collected

at each time point (0, 2, 4, and 6 days after inoculation). Metabolomic analysis was performed

by the West Coast Metabolomics Center at the University of California, Davis. At the

Metabolomics Center, the samples were extracted and a silylation derivitization with N-Methyl-

N-(trimethylsilyl) trifluoroacetamide (MSTFA) was performed prior to analysis by GC-TOF-

MS.

Hierarchical clustering of metabolites based on concentration profiles was performed in Python

using the SciPy cluster module. Signal intensity data for each metabolite were first centered by

36

subtracting the mean signal intensity for that metabolite, and normalized by dividing by the

standard deviation. Hierarchical clustering was performed using the “complete” method, also

called the farthest point algorithm, with Euclidian distances.

3.2.4 Identification of metabolites of potential bioleaching importance

Metabolites that were potentially relevant to bioleaching performance were identified by three

methods. The first method identified metabolites that were released at higher concentrations

under the monazite only condition than under the K2HPO4 plus monazite condition. Signal

intensities for each metabolite were compared between the two conditions using a two-tailed T-

test for independent samples. P-values were corrected for multiple comparisons using the

Benjamini/Hochberg correction for false discovery rate for independent samples (Benjamini and

Hochberg 1995). For this analysis only, all metabolites whose p-values were marginally

significant (p < 0.1) were selected for further study. This less stringent p-value criterion was

used at this intermediate stage in order to identify a large number of metabolites for the final set

of experiments. This analysis was performed independently for time points 2, 4, and 6 days.

The second approach to selecting metabolites of interest was to identify correlations between

metabolite concentration (signal intensity) and REE concentration. This analysis was performed

on data from the monazite only condition, using measurements of metabolite concentrations and

REE concentrations at each time point. A least squares linear regression was performed to

identify correlations. P-values were corrected for multiple comparisons using the Šidák

correction (Šidák 1967), as described in Chapter 2. Metabolites whose linear regression had a

positive slope and a significant corrected p-value (p > 0.05) were selected for further study.

The final approach was to select metabolites with the highest signal intensities. Metabolites

whose average signal intensity was greater than 105 for any condition and time point were

selected for further study.

3.2.5 Abiotic leaching conditions

Abiotic leaching conditions were a modification of those used in Chapter 2. Leaching was

conducted in 50 mL flat bottomed polypropylene tubes, each containing 0.1 g ground monazite

sand (200 mesh). 10 mL leaching solution was added to autoclaved tubes and stirred for 48

hours at 250 rpm at room temperature (25 to 28 ºC). All leaching solutions were tested in

triplicate.

Leaching solutions contained selected metabolites at a concentration of 10 mM, with the

exception of stearic acid. Stearic acid, whose solubility in water is extremely low (0.003 g/L or

0.01 mM at 20 ºC) (Anneken, Both et al. 2000), was dissolved in water for 20 minutes with

vortexing and filtered to remove undissolved particles. Additionally, a combined leaching

solution containing all selected metabolites, each at a concentration of 10 mM (except for stearic

acid), was also tested. All leaching solutions were adjusted to pH 2.5 by the addition of HCl in

order to mimic the pH observed during bioleaching and to eliminate the effects of variations in

pH observed in Chapter 2. Leaching solutions were filter sterilized through 0.2 µm syringe

filters prior to leaching experiments.

37

Statistical significance of leaching effectiveness was determined using a two-tailed T-test for

independent samples to compare REEs released by each leaching solution to a control solution of

HCl at a pH of 2.5. P-values were corrected for multiple comparisons using the Šidák

correction, as described in Chapter 2.

3.2.6 Gel permeation chromatographic separation of REE complexes and free REEs

Conditions for gel permeation chromatography experiments were based on those described by

Altomare et al. for separation of iron and manganese complexes (Altomare, Norvell et al. 1999),

and modified for application to REE bioleaching samples.

Low pressure chromatography experiments were conducted with Econo-Column glass columns

(1 cm diameter, 20 cm length) [Bio-Rad Laboratories Inc., Hercules, CA] packed to a bed height

of 15 cm with BioGel P2 Polyacrilamide Gel [Bio-Rad Laboratories Inc., Hercules, CA]

according to the manufacturer’s instructions. Two columns were prepared, one at circumneutral

pH and one at pH 2.5. The solvent for the circumneutral column was 20 mM NaCl in water.

The solvent for the pH 2.5 column contained 20 mM NaCl and in water adjusted to pH 2.5 with

HCl.

200 µL samples were injected via stopcock and Econo-Column flow adapter [Bio-Rad

Laboratories Inc., Hercules, CA]. Solvent flow rate was maintained at 0.250 mL/min using an

ISMATEC IPC High Precision Multichannel Dispenser [IDEX Health & Science SA,

Glattbrugg, Switzerland]. Effluent was collected in 1.25 mL (5 minute) fractions for 2 hours for

each sample. The column was flushed for an additional hour before the next sample was applied.

For circumneutral pH experiments, controls contained 2 mM NdCl3 with or without 1 mM

disodium EDTA. For pH 2.5 experiments, controls contained 0.1 mM NdCl3. The pH 2.5 citric

acid control contained 10 mM citric acid, and the pH2.5 EDTA control contained 10 mM

disodium EDTA. Controls were adjusted to pH 2.5 with HCl. Bioleaching samples were filtered

with 0.2 µm syringe filters to remove cells and frozen and stored at -80 ºC prior to

chromatography experiments.


3.3.1 Bioleaching performance

The results of monazite bioleaching with and without a soluble phosphate source (K2HPO4) are

summarized in Figure 3.1. REE solubilization was greater for the monazite only condition, when

a soluble phosphate source was not provided, reaching concentrations of 42 ± 15 mg/L after six

days of leaching (Figure 3.1-a). This is consistent both with forcing the organisms to solubilize

phosphate for growth and with possible re-precipitation of REE-PO4 in the medium that contains

K2HPO4 at a relatively high phosphate content. However, some solubilization of REEs did occur

in the cultures provided with K2HPO4, reaching concentrations of 14 ± 9 mg/L after six days of

bioleaching. Althoug Th release was small for both conditions, it was consistently greater for the

monazite only condition (0.6 ± 0.3 mg/L) than for K2HPO4 plus monazite (0.04 ± 0.02 mg/L).

38

Figure 3.1. Bioleaching of monazite in the absence or presence of soluble phosphate

(K2HPO4). Shown are (a) REE concentrations, (b) Th concentrations, (c) phosphate

concentrations, (d) glucose concentrations, (e) pH, and (f) biomass measured as volatile

solids. REE, phosphate, glucose, and pH data are for six biological replicates. Biomass data

are for three biological replicates. Error bars indicate standard deviations around the mean.

Free phosphate concentrations (Figure 3.1-c) remained very low (maximum observed

concentration in a single sample: 0.005 mM) when monazite was the only phosphate source.

When K2HPO4 was added to the medium, phosphate levels decreased from their initial

concentration but still remained high throughout the experiment (minimum observed

concentration in a single sample: 0.68 mM). This indicates that the concentration of K2HPO4

provided was sufficient to avoid phosphate limiting conditions during bioleaching for this growth

condition.

Glucose consumption (Figure 3.1-d) for the monazite only growth condition lagged behind

glucose consumption when K2HPO4 was provided. The pH was reduced at a faster rate when

soluble phosphate was provided (Figure 3.1-e), resulting in a slightly lower pH for this condition

on day two of bioleaching despite the higher initial pH of the medium with added K2HPO4.

However, by the fourth day, both conditions had similar pHs.

39

Biomass production (Figure 3.1-f) for the monazite only condition also lagged behind growth

with K2HPO4 plus monazite. By the sixth day, however, biomass accumulation was comparable

under both growth conditions (2.8 ± 0.03 g/L for monazite only and 2.9 ± 0.2 g/L for K2HPO4

with monazite).

Together, the phosphate, glucose, pH, and biomass data indicate that although low phosphate

levels may be slowing initial growth rates, by the end of the six day bioleaching experiment,

phosphate is not the limiting factor for growth. The depletion of glucose by the end of the

experiment in both cases may suggest a glucose growth limitation. However, as was shown in

Chapter 2, increasing the glucose concentration to 100 g/L did not improve bioleaching

performance.

Nitrogen availability is another possible growth limiting factor. Some estimates of the nitrogen

content of fungal mycelia range from 0.2% to 9% of dry weight (Lahoz, Reyes et al. 1966,

Dawson, Maddox et al. 1989, Watkinson, Bebber et al. 2006). Assuming a typical value of 5%

nitrogen content, the 0.66 g/L of (NH4)2SO4 (i.e. 0.14 g/L N) provided in AMS medium would

correspond to the production of approximately 2.8 g/L of dry biomass, suggesting that nitrogen

availability may be limiting biomass production to this level. Scervino et al. found nitrogen

limitation to enhance phosphate mineral solubilization by Penicillium purpurogenum, another

phosphate solubilizing fungus (Scervino, Papinutti et al. 2011), indicating that nitrogen limitation

of growth may be desirable for bioleaching performance. Nitrogen limitation has also been

found to enhance citric acid production in some fungi (Cunningham and Kuiack 1992,

Papagianni 2007).

3.3.2 Overall metabolomic profile

Metabolomic analyses of the fungal supernatant from the two conditions detected 210

metabolites (Appendix 2). Of these 87 could be identified as known chemicals. The remaining

123 were identified only with BinBase ID numbers based on their characteristic mass spectra.

Concentration profiles of all metabolites identified by name are summarized in Figure 3.2 for all

time points and conditions (see Appendix 3 for concentration profiles of all detected metabolites,

including those identified only by BinBase IDs). Overall, the lag in growth when monazite was

the only phosphate source, observed above in glucose consumption, pH reduction, and biomass

growth (Figure 3.1-d, -e, and -f), was paralleled in the concentration time profiles for many

metabolites, with metabolite concentrations peaking at earlier time points when K2HPO4 was

provided.

40

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41

Hierarchical clustering of metabolites based on these profiles identified several groups of

metabolites with similar behaviors. For instance, most of the components of the tricarboxylic

acid cycle (TCA cycle) (Figure 3.2, yellow highlights), including citric, isocitric, alpha-

ketoglutaric, succinic, fumaric, and malic acids, clustered together. The concentrations of these

TCA cycle components peaked on day four when K2HPO4 was added and on day six when

monazite was the only phosphate source. Aconitic acid, also in the TCA cycle, had a different

concentration profile, peaking on day six for both growth conditions, while oxaloacetic acid was

not detected. This overall trend is consistent with the earlier depletion of glucose when K2HPO4

was provided (Figure 3.1-d) since glucose, through glycolysis and the TCA cycle, feeds into the

production of these metabolites (Madigan, Martinko et al. 2008). Once the glucose is depleted,

these TCA cycle components are consumed and not replenished, resulting in the reduced

concentrations by day six when K2HPO4 is provided (Figure 3.2). The importance of

maintaining high sugar concentrations for the production and excretion of citric acid by

Aspergillus niger, a commercially important production process, have been well documented

(Magnuson and Lasure 2004, Papagianni 2007).

Long chain fatty acids (longer than eight carbons) (Figure 3.2, blue highlights) also clustered

together, with concentrations peaking on day six when K2HPO4 was provided, and remaining at

much lower levels when monazite was the only phosphate source. Long chain fatty acids

observed were azelaic, capric, lauric, oleic, palmitic, pelargonic, and stearic acids. This increase

in long chain fatty acid production corresponds with the depletion of glucose and the leveling off

in biomass production (Figure 3.1-d and f), and may be related to a transition from exponential

growth to stationary phase. Long chain fatty acids and their derivatives have been associated

with changes in fungal physiology and morphology, and specifically with the transition from

growth to spore formation (Mysyakina and Feofilova 2011).

3.3.3 Identification of metabolites of potential bioleaching importance

3.3.3.1 Metabolites released at higher concentrations when soluble phosphate was not

available

Direct comparison of metabolite levels for the two growth conditions identified metabolites with

higher concentrations for the monazite only growth condition. This analysis identified 15 and 13

metabolites for the 2 day and 4 day time points respectively. Three metabolites were identified

for both time points. However, none of these had identification beyond BinBase ID numbers

(20282, 2044, and 1681). No metabolites were identified from the analysis at the 6 day time

point because differences in concentration were not found to be statistically significant, likely

due to the high variability at this time point.

Of the eleven metabolites identified by name (eight for 2 days and three for 4 days) seven were

selected for further study of their leaching abilities (ribose, ribitol, nicotinic acid, isothreonic

acid, gluconic acid, histidine, and citric acid). Sulfuric acid was not considered because the

focus of this analysis was organic metabolites. Glucose was not considered because it was the

provided substrate rather than a metabolite and its higher concentration in the monazite-only

condition at 4 days was already shown (Figure 3.1-d) Fructose, which was tested as a carbon

source in Chapter 2 and was found not to have any benefits over glucose in REE solubilization,

was also rejected. Ribonic acid was not selected because it was not commercially available.

42

Figure 3.3. Metabolites of potential bioleaching importance identified by occurrence at

higher concentrations in the monazite-only condition compared to K2HPO4 plus monazite.

(a) Metabolites identified at 2 days. (b) Metabolites identified for at 4 days. Signal

intensities are normalized to the maximum observed signal intensity for each metabolite at

that time point. Height and error bars indicate mean and standard deviation for six biological

replicates.

43

3.3.3.2 Metabolites whose concentrations correlated with REE concentrations

Fifteen metabolites, eight of which were identified by chemical name, were found to have

positive correlations with REE concentrations (Figure 3.4). Six of these (galactinol, citramalic

acid, 4-hydroxybenzoic acid, 3,4-dihydroxybenzoic acid, 1-deoxyerythritol, 2-deoxyerythritol)

were selected for further leaching studies based on their commercial availability.

Figure 3.4. Correlations between metabolite signal intensities and REE concentrations.

Only compounds found to have a significant positive correlation and having identification

beyond BinBase ID numbers are shown. P-values are Šidák adjusted.

44

3.3.3.3 High signal intensity metabolites

Seven named metabolites had high overall signal intensities (average signal intensity > 105 for at

least one condition and time point). Four of these compounds (sorbitol, glycerol, p-cresol, and

stearic acid) were selected for further study, while three (glucose, sulfuric acid, and phosphate),

were rejected for previously stated reasons.

3.3.4 Abiotic leaching effectiveness of identified metabolites

Of all the tested metabolites, only citric acid and citramalic acid showed statistically significant

improvements in REE solubilization greater than the pH 2.5 HCl control (p = 0.008 and 0.04

after Šidák correction for citric and citramalic acid respectively) (Figure 3.5). Leaching with a

combination of all selected metabolites did not improve solubilization significantly beyond the

combined effects of individual metabolites, with increases of only approximately 6.5 and 5.1

mg/L above controls for citric and citramalic acids respectively, and did not approach the REE

concentrations achieved by direct bioleaching (42 ± 15 mg/L, see figure 3.1-a). Although the

effect of citric acid appears to be somewhat larger here than that reported in Chapter 2 (6.5 mg/L

here as opposed to 3 mg/L in Chapter 2), the experimental protocols were quite different (see

Materials and methods section). This experiment supports the overall result from Chapter 2 that

citric acid provides some additional REE solubilization, but not sufficient improvements to

account for the majority of the bioleaching effectiveness. Citramalic acid has previously been

shown to solubilize phosphate from low phosphate soils amended with monocalcium phosphate

dihydrate (Ca(H2PO4)2·H2O) (Khorassani, Hettwer et al. 2011).

With regard to Th release during bioleaching, only citric acid, citramalic acid, and the

combination of all selected metabolites resulted in leaching of detectable levels of thorium

release (Figure 3.6). Notably, these are the same metabolites that contributed to additional REE

solubilization. However, citric acid leached significantly more Th than citramalic acid (1.18 ±

0.01 mg/L as opposed to 0.25 ± 0.0 mg/L), indicating that citramalic acid may have more

desirable leaching characteristics.

45

Figure 3.5. Abiotic solubilization of REEs from monazite by selected metabolites. Heights

and error bars indicate means and standard deviations for three replicates.

Figure 3.6. Abiotic solubilization of Th from monazite by selected metabolites. Heights and

error bars indicate means and standard deviations for three replicates.

46

3.3.5 Gel permeation chromatographic separation of complexed REEs

In order to determine whether the formation of large, highly stable complexes contributed to

bioleaching effectiveness, a gel permeation chromatography approach was developed to separate

free REEs from REE complexes. Initial testing of low pressure gel permeation chromatography

was successful at separating free Nd3+ from EDTA-Nd3+ complexes at circumneutral pH (Figure

3.7).

Figure 3.7. Chromatographic separation of free Nd3+ and EDTA-Nd3+ complexes at

circumneutral pH.

Due to the low pH of the bioleaching cultures, an additional gel permeation chromatography

column was prepared and operated at pH 2.5 (Figure 3.8). Unlike the circumneutral results, the

NdCl3 plus EDTA did not show a clear separation of Nd3+ and EDTA-Nd3+ complex under these

conditions, instead resulting in a smeared peak between 30 and 100 minutes retention time. The

combination of NdCl3 and citric acid, a weaker complexing agent, resulted in Nd release in a

single peak between 70 and 100 minutes retention time, peaking between 80 and 90 minutes, the

same retention time as the NdCl3 control without any complexing agents. This result is

unsurprising for the weaker complexes that dissociate more readily within the chromatography

column (Collins 2004). The equilibrium constant for complexes of EDTA with REEs has been

estimated at 1014 to 1020 (Wheelwright, Spedding et al. 1953), whereas the equilibrium constant

for complexes of citrate with REEs are on the order of 109 (Martell and Smith 1974, Goyne,

Brantley et al. 2010).

47

Samples from three bioleaching bottles also resulted in single peaks of Nd with retention times

of 70 to 100 minutes (peak at 80 to 90 minutes), similar to the NdCl3 and NdCl3 with citric acid

controls. These chromatography results indicate that the compounds responsible for REE

bioleaching do not form strong complexes, like those of EDTA, which are able to remain

somewhat intact during chromatographic separation. Instead, any complexes formed in these

bioleaching samples are more similar to the weaker complexes formed between REEs and citric

acid.

Figure 3.8. Chromatographic separation of Nd3+ and Nd3+ complexes at pH 2.5.

In combination, the metabolomics analysis along with the gel permeation chromatography results

provide some insight into the nature of the compounds responsible for bioleaching effectiveness.

The chromatography results suggest that any complexes formed are relatively weak. This is

consistent with the ability of the Amberlite IR120 resin to remove REEs from bioleaching spent

medium as was reported in Chapter 2. The metabolomics analysis and subsequent abiotic

leaching experiments indicate that while citric acid and citramalic acid contribute to leaching,

they do not completely explain bioleaching effectiveness. Any contributions of other identified

metabolites were not great enough to be detected. Together these results suggest that a

combination of many compounds forming weak complexes with REEs contribute to fungal

bioleaching effectiveness. These may include some of the unknowns identified by BinBase

numbers in this metabolomics analysis, but they may also include others not detectable by the

GC-TOF-MS approach or not in the reference mass spectra database used by the West Coast

Metabolomics Center for this analysis.

48

Chapter 4:

Metagenomic Analysis of a Functionally Stable Trichloroethene Degrading Microbial

Community

A version of the following chapter has been published as:

Brisson, Vanessa L., Kimberlee A. West, Patrick. K. H. Lee, Susannah G. Tringe, Eoin L. Brodie

and Lisa Alvarez-Cohen (2012). "Metagenomic analysis of a stable trichloroethene-degrading

microbial community." The ISME Journal 6(9): 1702-1714.

49

4.1 Introduction

Chlorinated ethenes are common groundwater contaminants that pose human health risks

(McCarty 1997, Moran, Zogorski et al. 2007, US_Dept._of_H&HS 2007). Although several

groups of organisms can reductively dechlorinate tetrachloroethene (PCE) and trichloroethene

(TCE) to the toxic intermediate dichloroethene (cis-DCE and trans-DCE) (Scholz-Muramatsu,

Neumann et al. 1995, Sharma and McCarty 1996, Holliger, Hahn et al. 1998, Luijten, de Weert

et al. 2003, Löffler, Cole et al. 2004), Dehalococcoides (Dhc) species are the only organisms

known to dechlorinate these compounds completely to the harmless product ethene (Maymo-

Gatell, Chien et al. 1997, Smidt and de Vos 2004). Dhc species have been found to grow more

robustly and reduce chlorinated organics more effectively when grown in mixed communities

rather than in isolation, likely due to Dhc’s stringent metabolic needs (Maymo-Gatell, Chien et

al. 1997, He, Holmes et al. 2007).

The dechlorinating community studied here is an enrichment culture that has been stably

dechlorinating TCE to ethene for over ten years. This culture was derived from sediment

collected at the Alameda Naval Air Station and is referred to as ANAS (Richardson,

Bhupathiraju et al. 2002). The phylogenetic composition of ANAS has been studied using clone

libraries (Richardson, Bhupathiraju et al. 2002, Lee, Johnson et al. 2006), and the Dhc strains in

ANAS have been analyzed using qPCR and whole-genome microarrays (Holmes, He et al. 2006,

West, Johnson et al. 2008, Lee, Cheng et al. 2011). ANAS contains two Dhc strains, which have

recently been isolated (Holmes, He et al. 2006, Lee, Cheng et al. 2011). A comparative

genomics analysis showed these strains to have very similar core genomes, but different RDase

genes, with correspondingly different dechlorination abilities (Lee, Cheng et al. 2011).

Metagenomic sequencing analysis was used in this study to examine the Dhc component in the

context of the ANAS microbial community. Metagenomic approaches have been used to study a

variety of microbial communities, including those inhabiting termite guts, human intestines,

wastewater treatment plants, and acid mines (Tyson, Chapman et al. 2004, Gill, Pop et al. 2006,

Warnecke, Luginbuhl et al. 2007, Sanapareddy, Hamp et al. 2009). In the case of dechlorinating

communities, metagenomic data can provide insights into the organisms that support

dechlorination activity (Waller 2009).

In this study DNA sequences of Dhc and other ANAS community members are identified and

examined from metagenomic sequence data. This study focuses on three categories of functional

genes related to dechlorination activity: genes for reductive dehalogenases (RDases), genes for

cobalamin biosynthesis enzymes, and genes for hydrogenases. RDases are the enzymes that

catalyze the reductive dehalogenation reactions. Cobalamin biosynthesis was targeted because

cobalamin is a required cofactor for RDases (Smidt and de Vos 2004). Hydrogenases, which

catalyze the reversible oxidation of molecular hydrogen, were targeted because Dhc couple

reductive dechlorination to hydrogen oxidation (Maymo-Gatell, Chien et al. 1997, Adrian,

Szewzyk et al. 2000, He, Ritalahti et al. 2003).

50


4.2.1 ANAS enrichment culture and DNA sample preparation

Culture conditions and maintenance procedures for ANAS have been described previously

(Richardson, Bhupathiraju et al. 2002). Briefly, 350 mL of culture was grown at 25 to 28 °C and

1.8 atm with a N2-CO2 (90:10) headspace in a 1.5 L continuously stirred semi-batch reactor. The

culture was amended with 13 μL TCE and 25 mM lactate every 14 days.

Cells were collected from 30 mL culture samples by vacuum filtration onto hydrophilic

Durapore membrane filters (0.22 µm pore size, 47 mm diameter [Millipores, Billerica, MA]),

and filters were stored in 2 mL microcentrifuge tubes at –80 °C until further processing. For

PhyloChip experiments, samples were collected from the same time point (27 hrs) from three

different 14-day cycles of the culture to achieve biological triplication. For metagenomic

sequencing, samples from the same time point (27 hrs) from four different feeding cycles were

pooled in order to collect enough material for sequencing. Total nucleic acids were extracted

from frozen filters using a modified version of the bead beating and phenol extraction method

described previously (West, Johnson et al. 2008).

4.2.2 Metagenome sequencing, assembly, and annotation

Metagenome sequencing, assembly, and annotation were performed at the Department of Energy

Joint Genome Institute (JGI). A combination of 454-Titanium sequencing (453,944 reads) and

paired-end short-insert Sanger sequencing (76,272 mate pairs, approximate insert size 3 kb) was

used. 454-Titanium sequencing reads were assembled into contiguous sequences (contigs) using

Newbler [454 Life Sciences, Roche Applied Sciences, Branford, CT, USA]. Those contigs were

shredded to resemble overlapping Sanger sequencing reads, which were then combined into an

assembly with the paired-end Sanger sequencing reads using the Paracel Genome Assembler

[Paracel Inc., Pasadena, CA, USA]. Similar methods have been used by other researchers to

combine Sanger and 454-Titanium sequencing data (Goldberg, Johnson et al. 2006, Woyke, Xie

et al. 2009). The contigs resulting from this second assembly, as well as Sanger reads and

Newbler contigs that could not be further assembled, were annotated through a version of the JGI

microbial annotation pipeline (Mavromatis, Ivanova et al. 2009) adapted to metagenomes, which

includes prediction of protein coding and RNA genes and product naming. Annotation was

automated and no manual annotation was performed. Data were loaded into the Integrated

Microbial Genomes with Microbiome Samples (IMG/M) database (Markowitz, Chen et al. 2010)

and used in the following analyses.

4.2.3 Analysis of metagenomic sequence data

4.2.3.1 Identification of Dhc contigs by sequence similarity

Dhc contigs were identified in a two stage sequence similarity (SS) process. In the first stage,

contigs were identified by comparison to previously sequenced Dhc reference genomes (Dhc

strains 195, BAV1, CBDB1, VS and GT). Reference genome sequences were retrieved from the

National Center for Biotechnology Information (NCBI) genomes database

[ftp://ftp.ncbi.nlm.nih.gov/genomes], and blastn (Zhang, Schwartz et al. 2000) was used to

compare the reference genome sequences against a database of all metagenome contig

51

sequences. For each reference genome, the top 250 BLAST hit contigs were selected for the

second stage comparison (at this cutoff, additional contigs did not expand the useful contig set),

where their identities were checked by comparison to the NCBI genomes database using

megablast (Zhang, Schwartz et al. 2000). All contigs whose top BLAST hit (lowest expect

value) in the genomes database was to Dhc were selected and expect values were checked for

significance. For all contigs identified as Dhc, the expect value of the identifying BLAST hit

was ≤ 10-35.

4.2.3.2 Classification of ANAS contigs by tetranucleotide frequencies

ANAS contigs larger than 2,500 bp were grouped by tetranucleotide frequencies (TF) using a

procedure based on one described by Dick et al. (Dick, Andersson et al. 2009) with some

modifications described here. Clustered regularly interspaced short palindromic repeat

(CRISPR) and rRNA gene sequences were removed from contig sequences prior to classification

because these sequence regions are known to have atypical nucleotide compositions compared to

their genomes (Reva and Tummler 2005, Dick, Andersson et al. 2009). Next, all contig

sequences larger than 2,500 bp were selected for classification, with contigs larger than 7,500 bp

divided into 5,000 bp fragments. Sequence fragments were classified based on TF using the

Databionics ESOM Tools program (Ultsch and Moerchen 2005, Databionics 2006). Dick et al.’s

method for clustering of sequences (Dick, Andersson et al. 2009) was used with the following

modifications. Online training was used instead of the k-batch algorithm because online training

provides more accurate, albeit slower, performance (Databionics 2006). A map size of 120x196

and an initial radius of 60 were selected based on the size of the dataset.

4.3.3.3 Comparisons to reference genomes and identification of novel Dhc genes

To identify regions of similarity and difference between a set of metagenome contigs and a

reference genome, each contig in the set was compared to the reference genome using blastn,

with an expect value cutoff of (10-12) unless otherwise stated. Based on the results of these

searches, aligning and non-aligning regions were identified in the contigs and the reference

genome.

Two measures of overall similarity between contigs and reference are reported. The first, contig

match, is the percentage of total bases in all contigs that are part of an alignment to the reference

genome. The second, reference match, is the percentage of bases in the reference genome that

are part of an alignment to some contig in the set.

To identify contig regions containing potentially novel Dhc genes, Dhc metagenome contigs

were compared to five sequenced Dhc genomes (strains 195, BAV1, CBDB1, VS, and GT) that

were publicly available in August 2010. Contig regions that were not in alignments to any

reference genomes and were over 100 bases in length were investigated further. A less stringent

expect value cutoff (10-6) was used to ensure that only low similarity regions were included in

the analysis. All annotated genes contained in the non-aligning regions, or overlapping the

regions by at least five bases were identified as novel.

52

4.2.4 Confirmation of novel Dhc genes in Dhc isolates from ANAS

Selected novel Dhc genes identified in the metagenome were amplified and sequenced from Dhc

strains previously isolated from ANAS. Primers were designed based on the metagenome gene

sequence using Primer3 (Table 4.1). PCR reactions were performed in 0.2 mL tubes in using

Qiagen Taq DNA Polymerase. The thermocycler program was as follows: 12 minutes at 94 C;

40 cycles of one minute at 94C, 45 seconds at annealing temperature (Table 4.1), and two

minutes at 72 C; 12 minutes at 72 C. Genomic DNA (gDNA) from Dhc strains ANAS1 and

ANAS2 were used as templates for separate reactions. ANAS metagenomic DNA was used as a

positive control template and Dhc strain 195 gDNA was used as a negative control template.

PCR products were visualized on agarose gels and purified using the QIAquick PCR Purification

Kit. Purified PCR products were sequenced by Sanger sequencing.

Table 4.1. PCR primers and annealing temperatures for novel Dhc genes.

Target

Gene

Name

JGI IMG

Gene Object

ID

Primer sequences Annealing

Temp. for

PCR Forward Reverse

cbiD 2014753801 ACCGCCAGCCTCAGGGTTGA ACAGCCGCCATGGCACACAG 59 °C

cbiF 2014753804 CGCTGTCTGGAAGAAGCCGACC TGCATGGCGGAGGCCAGATT 57 °C

cbiC 2014753814 CGCCGTTGTCCGCCAGCTTA TTTCACCCGCCGCTTCTGCC 58 °C

4.2.5 TCE dechlorination by Dhc Isolate ANAS2 and ANAS Subcultures

Dhc isolate ANAS2 was grown in 120 mL serum bottles with H2/CO2 (80%/20%) in the

headspace. Bottles contained 99 mL Bav1 medium (He, Ritalahti et al. 2003) with 5 mM acetate

as a carbon source and 7 µL TCE, but no cobalamin. Bottles were either amended with 50 µg/L

(37 nM) cobalamin or 5.4 µg/L (37 nM) 5,6-dimethylbenzimidazole (DMB), or were left un-

amended. Bottles were inoculated with 1 mL of active ANAS2 culture stock, which had been

growing on Bav1 medium with 5 mM acetate and 50 mM cobalamin, and incubated at 34 ºC

until they had completely dechlorinated 7 µL of TCE to ethene.

Subcultures of the ANAS microbial community were grown in 120 mL serum bottles with

N2/CO2 (90%/10%) in the headspace. Growth medium was the same as that used in the ANAS

culture, but with varying concentrations of cobalamin. 20 mM lactate was provided as an

electron donor and carbon source, and 2 µL TCE was provided as an electron acceptor. 5 mL of

inoculum was added to 45 mL of growth medium, for a final liquid volume of 50 mL in each

bottle. Inoculant for the first stage subcultures was taken from the ANAS culture. The second

stage subcultures were inoculated from first stage subculture bottles with the same cobalamin

concentration. Bottles were incubated at room temperature (approximately 25 ºC)

Chlorinated ethene concentrations were monitored by gas chromatography on an Agilent

Technologies 7890A GC system using a previously described protocol (Lee, Johnson et al.

2006).

53

4.2.6 PhyloChip assessment of community composition

Metagenomic DNA and RNA extracted from ANAS were applied to separate PhyloChip

microarrays to examine the phylogenetic composition of ANAS. The methods for these

experiments draw on several previously published methods (Cole, Truong et al. 2004, Brodie,

DeSantis et al. 2006, DeSantis, Brodie et al. 2007, West, Johnson et al. 2008).

Total nucleic acids were extracted as previously described (West, Johnson et al. 2008). DNA

and RNA were separated using the Qiagen AllPrep DNA/RNA Kit according to manufacturer’s

instructions. RNA was further purified using the Qiagen RNase-free DNase Set, per

manufacturer’s instructions. RT-qPCR was performed to confirm that RNA samples contained

no DNA contamination. The masses of DNA and RNA per volume were quantified using a

fluorometer [model TD-700, Turner Designs, Sunnyvale, CA] and the Quant-iT PicoGreen

dsDNA and Quant-iT RiboGreen RNA reagents [Invitrogen Molecular Probes, Carlsbad, CA],

respectively, according to the manufacturer's instructions.

The bacterial and archaeal 16S rRNA genes were amplified from the extracts using the following

primers: bacterial primer 27F (5′-AGRGTTTGATCMTGGCTCAG), archaeal primer 4F (5'-

TCC GGT TGA TCC TGC CGG-3'), and universal primer 1492R (5′-

GGTTACCTTGTTACGACTT). For DNA PhyloChips, PCR was performed using the TaKaRa

Ex Taq system [Takara Bio Inc., Japan] and DNA was prepared for the microarrays as previously

described (DeSantis, Brodie et al. 2007).

For RNA PhyloChips, a direct hybridization method was employed as follows. 16S rRNA was

enriched from total RNA by gel extraction. Direct analysis of rRNA was achieved using a

modification of the protocol of Cole et al. (Cole, Truong et al. 2004). To account for technical

variation between hybridizations, a set of internal RNA spikes were added to each sample

preparation. These spikes consisted of transcripts generated by T7 or T3 mediated in vitro

transcription from linearized plasmids pGIBS-LYS (containing Bacillus subtilis lysA, ATCC

87482), pGIBS-PHE (containing Bacillus subtilis Phe gene, ATCC 87483) and pGIBS-THR

(containing Bacillus subtilis Thr gene, ATCC 87484). To each RNA fragmentation reaction,

1.35×1010, 3.13×1010 and 3.13×1011 transcripts of LysA, Thr, and Phe respectively were added in

a volume of 1 μL. Combined sample RNA (1 µg) and spike mix was fragmented and

dephosphorylated simultaneously using 0.1U RNaseIII/µg RNA, shrimp alkaline phosphatase

[USB, OH, USA] 0.2U/µg RNA in a buffer containing 10 mM Tris-HCl, 10 mM MgCl2, 50 mM

NaCl, 1mM DTT (pH7.9) in a final volume of 20 µL. The mixtures were then incubated at 37

°C for 35 min followed by inactivation at 65 °C for 20 min. RNA labeling with multiple biotin

residues utilized an efficient labeling system that employs T4 RNA ligase to attach a 3'-

biotinylated donor molecule [pCp-Biotin3, Trilink Biotech, San Diego, CA, USA] to target RNA

(Cole, Truong et al. 2004). Labeling was performed with 20 µL of fragmented/dephosphorylated

RNA, 20U T4 RNA ligase [NEB, MA, USA], 100 µM pCp-Biotin3 in a buffer containing 50

mM Tris-HCl, 10 mM MgCl2, 10 mM DTT, 1 mM ATP (pH 7.8), 16% v/v PEG 8000. The final

volume was 45 µL. The reaction mixture was incubated at 37 °C for 2h and inactivated at 65 °C

for 15 min. The mixture was then prepared for PhyloChip hybridization without any further

purification and was processed according to standard Affymetrix expression analysis technical

manual procedures for cDNA.

54

PhyloChips were hybridized at 50 °C in an Affymetrix hybridization oven for 16 h at 60 rpm.

Microarrays were stained according to the Affymetrix protocol and then immediately scanned

using a GeneChip Scanner 3000 7G [Affymetrix, Santa Clara CA]. To process captured

fluorescent images into taxon hybe scores, images were background corrected and probe pairs

scored as previously described (Brodie, DeSantis et al. 2006).

4.3 Results

4.3.1 ANAS metagenome overview

ANAS metagenome sequences were assembled into 26,293 contigs, totaling 41,065,977 bp of

DNA sequence. Contigs ranged in length from 78 bp to 921,258 bp, with an N50 length of 2,149

bp. 60,992 protein coding genes and 565 RNA genes were identified. The annotation is

available through IMG/M [http://img.jgi.doe.gov/cgi-bin/m/main.cgi] (Taxon Object ID

2014730001) (Kyrpides, Markowitz et al. 2008).

4.3.2 Dhc in ANAS

4.3.2.1 Identification of Dhc contigs

The SS method identified 301 contigs as Dhc. In the TF analysis, one class containing 45

contigs was identified as Dhc based on the presence of 16S and 23S rRNA genes that were 100%

and 99% identical to those of Dhc strain 195.

The Dhc contigs identified by SS and by TF were compared to evaluate the two methods. Of the

301 Dhc contigs (1,810,488 bp total) identified by SS, 49 (1,643,099 bp total) were sufficiently

long (> 2,500 bp) for classification by TF. Of those, the TF method classified 45 as Dhc (the

class of 45 identified above) and one (ANASMEC_C10442) as a Synergistete, leaving three

(ANASMEC_C5086, ANASMEC_C818, and ANASMEC_C10029) unclassified.

The four contigs identified by SS but not by TF were further examined to determine possible

reasons for the discrepancy. The BLAST alignments identifying these contigs by SS covered

25% or less of each contig’s length. In the non-aligning sequence regions, two contigs

(ANASMEC_5086 and ANASMEC_C818) contained several phage related genes and

recombinases, indicating possible horizontal DNA transfer, which could explain non-Dhc TF

classification of sequences from a Dhc genome. The other contigs (ANASMEC_C10029 and

ANASMEC_C10442) did not contain genes that were obvious indicators of horizontal transfer,

although this does not rule out that explanation. Mis-assembly may also be responsible for the

presence of both Dhc and non-Dhc sequence in these contigs. Given this uncertainty, the

following analyses consider contigs identified by TF and SS separately, and make special note

when these four contigs are relevant to a particular analysis.

55

4.3.2.2 Metagenome coverage of Dhc genes detected by microarray

Metagenome coverage of Dhc genes was assessed by comparison to results from a previous

comparative genomics study performed with microarrays targeting 98.6% of annotated genes in

Dhc strains 195, BAV1, CBDB1, and VS (Lee, Cheng et al. 2011). Coverage was evaluated by

identifying Dhc genes detected in ANAS by the microarray analysis and determining which of

those genes were present in the metagenome sequences (Figure 4.1). Presence of Dhc genes in

the metagenome was determined by blastn comparisons of the genome sequences of Dhc strains

195, BAV1, CBDB1, and VS to all metagenome contigs (expect value cutoff of 1×10-12).

Figure 4.1. Comparison of metagenomic Dhc coverage with ANAS genes detected by

microarray. Although the analysis was performed for genes from Dhc strains 195, BAV1,

CBDB1, and VS, only results for Dhc strain 195 are shown here for simplicity. Circles

represent the Dhc strain 195 genome, with the origin of replication at the top. The inner

circle shows regions with ANAS metagenome / strain 195 alignments in magenta. The outer

circle shows ANAS genes detected by microarray in blue-green.

56

The metagenome contigs contained 96.2% (1,311 of 1,363) of the genes identified as present by

the microarray analysis. Another 3.4% (47 genes) were partially present, overlapping the contig

end. Only five of the 1,363 Dhc genes identified by microarray were not found in any of

metagenome contigs. These were all genes from the Dhc195 genome, and include fabG

(DET1277), nusB (DET1278), and three genes coding for hypothetical proteins (DET0768,

DET1405, and DET1406). Based on the alignment of the metagenome contigs to the Dhc 195

genome, these genes appear to fall in gaps between contigs. Blastn comparisons of these genes to

the raw sequencing reads revealed that all five genes had significant alignments (expect value <

1×10-50) to 454-Titanium sequencing reads but not to Sanger sequencing reads, indicating that

they were missed by Sanger sequencing.

4.3.2.3 Co-assembly of sequence from distinct Dhc strains

Comparisons to the previous comparative genomics microarray analysis (Lee, Cheng et al. 2011)

were also used to determine whether sequences from the two distinct Dhc strains were co-

assembled in the metagenome. The presence of two different Dhc strains (ANAS1 and ANAS2)

in the ANAS community has been established previously (Holmes, He et al. 2006, Lee, Cheng et

al. 2011), and the previous study identified 60 genes distinct to ANAS1 and 36 genes distinct to

ANAS2 (Lee, Cheng et al. 2011). The metagenome contigs containing these non-shared genes

were identified using BLAST and identifications were confirmed by BLAST comparison of

metagenome sequences to the NCBI non-redundant nucleotide database. Although all genes

analyzed had significant (expect value < 10-12) alignments in the contigs, alignment of at least

75% of gene length was also required for positive identification for this analysis. 5 genes

distinct to ANAS1 failed this alignment length requirement and were not considered. Six

contigs, representing 541,431 bp combined, were found to be co-assembled because each

contained at least one gene distinct to ANAS1 and one gene distinct to ANAS2. In total, 17

contigs contained genes distinct to ANAS1, and 15 contigs contained genes distinct to ANAS2.

4.3.2.4 Identification of novel Dhc genes

406 novel genes, 184 with annotated functions (Appendix 4), were identified on 26 contigs (15

identified as Dhc by both TF and SS, four identified by SS alone as described above, and seven

that were too short for TF analysis but were identified by SS) (Figure 4.2). The most surprising

finding was the presence of nine genes predicted to be involved in corrin ring synthesis, the first

half of the cobalamin biosynthesis pathway.

57

Figure 4.2. Alignment of ANAS metagenome Dhc contigs (identified by TF and/or SS) to

the Dhc strain 195 genome. The inner circle represents the reference strain 195 genome,

with the origin of replication at the top. Magenta areas indicate alignment to ANAS

metagenome contigs while grey areas indicate regions with no alignment. Each contiguous

bar in the outer circles represents a contig, positioned based on its aligning regions, with

contigs plotted on different circles to avoid overlap. Green areas indicate regions with no

alignment to the reference genome, potentially containing novel Dhc genes (if they also do

not align to other Dhc reference genomes).

58

The corrin ring synthesis genes are on contig ANASEMC_C6240, which was identified as Dhc

by both SS and by TF. Eight of the nine genes are oriented in the same direction and appear to be

in a single operon, along with seven genes for ATP-binding cassette transporter (ABC-

transporter) components (Figure 4.3), some specifically annotated as cobalamin transporters. All

regions of this contig aligning to reference Dhc genomes aligned to previously identified High

Plasticity Regions (HPRs), which contain much of the variation between sequenced Dhc

genomes (McMurdie, Behrens et al. 2009). Based on the TF analysis, the region of this contig

containing the cobalamin biosynthesis genes grouped with the Dhc sequences and not with any

other contig class (Figure 4.4)

Figure 4.3. Operon structure for genes for the first (corrin ring synthesis) part of the

cobalamin biosynthesis pathway identified in an ANAS metagenome contig associated with

Dhc. Genes in white are the corrin ring synthesis genes, labeled with the gene name. Genes

with hatching are genes for ABC-transporter components.

Figure 4.4. Evidence for the association of contig ANASMEC_C6240 (containing cobalamin

biosynthesis genes) with Dhc. (A.) The top bar shows how different segments of the contig

were grouped with Dhc based on TF analysis, while (B.) the bottom bar shows which parts of

the contig aligned with previously sequenced Dhc genomes (magenta matches Dhc and green

does not). The location of the apparent cobalamin biosynthesis operon is indicated and has a

Dhc TF composition but does not align to previously sequenced Dhc genomes.

PCR amplification and sequencing were used to confirm the presence of three of the cobalamin

biosynthesis genes in Dhc strains previously isolated from ANAS. Genes tested included two

from the apparent cobalamin biosynthesis operon (cbiD and cbiF) and the one from elsewhere on

the same contig (cbiC). All three genes were successfully amplified and sequenced from gDNA

from Dhc strain ANAS2 as well as from ANAS metagenomic DNA but not from Dhc strain

ANAS1 or strain 195. Sequences had 99.6-100% nucleotide identity with corresponding

metagenome sequences. Amplification with the primers for cbiF produced products of a

different size than the target sequence when gDNA from Dhc strain ANAS1 or strain 195 was

59

used as the template. Sequencing of PCR products confirmed that these were a different

sequence from the target, the result of non-specific primer binding.

Several other groups of genes are well represented among the novel Dhc genes identified here.

15 novel genes for ABC-transporter components were identified, including 13 on the same

contig as the corrin ring synthesis genes. 15 genes for phage proteins and 14 genes for

recombinases were also present. 11 novel genes for RDases were identified. However, for one

RDase, the first third of the gene matched (98% ID) the Dhc strain 195 gene DET0088, an

RDase domain gene that is approximately one third the length of a typical RDase gene. Together

with the remaining two thirds of the RDase gene, this appears to be a full length novel Dhc

RDase gene in the ANAS metagenome.

4.3.2.5 TCE dechlorination by Dhc isolate ANAS2 under different cobalamin conditions

Figure 4.5 shows ethene produced during TCE dechlorination by Dhc isolate ANAS2. ANAS2

was able to completely dechlorinate 60 µmol TCE per bottle to ethene within 20 days of

incubation when provided with 50 µg/L cobalamin. However, when provided with no

cobalamin, ethene levels remained below 2 µmol ethene per bottle, regardless of whether DMB

was present.

Figure 4.5. Ethene production during TCE degradation by Dhc isolate ANAS2.

4.3.3 ANAS community structure

4.3.3.1 TF classification of metagenome contigs

TF was used to analyze all contigs longer than 2 500 bp, comprising 2 323 contigs representing

46% of the total sequence length of all contigs. Of these contigs, 95% were classified into 10

classes (Table 4.2). 141 contigs were left unclassified because they did not cluster with other

contigs.

60

Table 4.2. Classification of contigs by TF and identification of contig classes by 16S and 23S

BLAST comparisons.

Classa

Number

of

Contigs

Total

Sequence

Length (bp)

Median

Contig

Length

(bp)

Avg.

Read

Depth Taxa

16S rRNA gene

Closest BLAST

Hitb (23S when 16S

not present)

%ID

of

Closest

BLAS

T Hitb

Class 1 13 2,279,508 39,051 53 Clostridiaeceae Clostridiaceae

bacterium SH021

95

Class 2 45 1,483,420 14,384 39 Dehalococcoides Dehalococcoides

sp. MB and

Dehalococcoides

ethenogenes 195

100

Class 3 77 2,654,085 27,104 18 Spirochaetes Spirochaetes

bacterium

enrichment culture

clone DhR^2/LM-

B02

92

Class 4 152 2,550,033 11,242 11 Methanobacterium Methanobacterium

formicicum strain

FCam

99

Class 5 382 2,249,123 4,714 8 Desulfovibrio (Desulfovibrio

desulfuricans

subsp.

Desulfuricans str.

ATCC 27774)c

(96)c

Class 6 449 2,295,796 4,122 7 unknown taxa no rRNA genes

Class 7 550 2,732,616 3,821 7 Synergistetes Synergistetes

bacterium

enrichment culture

clone DhR^2/LM-

F01

98

Class 8 205 791,052 3,346 6 Delta-

proteobacterium

no rRNA genes

Class 9 191 675,183 3,112 6 unknown taxa no rRNA genes

Class 10 118 421,953 3,156 5 Methanospirillum Methanospirillum

hungatei JF-1

99

Unclassified 141 864,492 3,451 All Classes 2,323 18,997,261 4,003

aClasses are ordered by average read depth. bIdentity and %ID are presented for the top 16S (or 23S) rRNA gene BLAST hit in the NCBI nucleotide database

that was identified beyond “uncultured bacterium”. BLAST searches were performed in August, 2010.

Based on 16S and 23S rRNA genes present on the contigs, seven of the 10 classes were

attributed to the following taxa: a Clostridiaceae, Dhc, Desulfovibrio (23S only),

Methanobacterium, Methanospirillum, a Spirochaete, and a Synergistete. The remaining three

classes did not contain 16S or 23S rRNA genes. Notably, an additional contig

(ANASMEC_C9204) containing a set of rRNA gene sequences from a Clostridium did not

cluster with any contig class, although it was more similar to the Clostridiaceae class than to

other contig classes. This 8 722 bp contig also contains genes for subunits of a type IIA

topoisomerase and a gene for a hypothetical protein. A partial 23S rRNA gene belonging to a

61

Bacteroides and a 16S gene belonging to a Desulfovibrio were also identified, but were on

contigs smaller than the 2,500 bp cutoff used for the TF analysis.

IMG/M Phylogenetic Marker COGs (Markowitz, Ivanova et al. 2008) were used to try to

identify the remaining three classes. One class was identified as a Deltaproteobacterium, likely

from the Desulfovibrionales order. Marker genes in Class 6 did not give a clear identification,

and Class 9 contained no marker genes.

4.3.3.2 Comparisons to previously sequenced reference genomes

Contig classes were compared to relevant reference genomes in the NCBI genomes database

(accessed September 2010). Desulfovibrio and Methanospirillum contigs were compared to fully

sequenced genomes from the same genus. Methanobacterium contigs were compared to

genomes of members of the Methanobacteriaceae family. Clostridiaceae contigs were compared

to Clostridium genomes (most similar genus based on 16S and 23S sequences). Comparisons

were not performed for the Spirochaete, Synergistete, or unknown Deltaproteobacterium contigs

because sufficiently close relatives (same family or genus) could not be identified.

Dhc contigs had the most similarity to reference genomes, while Clostridiaceae and

Methanobacterium contigs had < 4% contig match (percent of contig bases in alignments to

reference genome) or reference match (percent of reference genome bases in alignments to

contigs) (Table 4.3). For comparison, it is useful to consider what these values are for a set of

contigs compared to a reference genome that is not closely related. A comparison of the Dhc

contigs to seven Desulfovibrio reference genomes results in contig matches and reference

matches of 0.1% to 0.2%. For Methanospirillum contigs, the disparity between contig match and

reference match is probably due to poor sequencing coverage (0.5 Mbp compared to 3.5 Mbp for

Methanospirillum hungatei).

62

Table 4.3. Comparisons of ANAS metagenome contigs to reference genomes.

Contig Class Reference Genome Contig Matchb Reference Matchc

Dehalococcoides Dehalococcoides ethenogenes str. 195 81.7% 82.2%

Dehalococcoides Dehalococcoides str. BAV1 73.9% 78.9%

Dehalococcoides Dehalococcoides str. CBDB1 74.7% 76.9%

Dehalococcoides Dehalococcoides str. VS 76.0% 77.4%

Dehalococcoides Dehalococcoides str. GT 72.4% 76.6%

Desulfovibrio Desulfovibrio desulfuricans ATCC 27774 32.9% 26.1%

Desulfovibrio Desulfovibrio desulfuricans G20 5.1% 3.3%

Desulfovibrio Desulfovibrio magneticus RS 1 3.8% 1.9%

Desulfovibrio Desulfovibrio salexigens DSM 2638 1.6% 1.2%

Desulfovibrio Desulfovibrio vulgaris DP4 6.6% 4.8%

Desulfovibrio Desulfovibrio vulgaris Hildenborough 6.5% 4.5%

Desulfovibrio Desulfovibrio vulgaris Miyazaki 9.1% 5.4%

Methanobacteria Methanobrevibacter ruminantium M1 0.9% 0.9%

Methanobacteria Methanobrevibacter smithii ATCC 35061 0.8% 1.4%

Methanobacteria Methanosphaera stadtmanae DSM 3091 0.7% 1.6%

Methanobacteria Methanothermobacter thermautotrophicus 2.1% 3.2%

Methanospirillum Methanospirillum hungatei 46.5% 6.1%

Clostridiaceae Clostridium acetobutylicum 0.5% 1.1%

Clostridiaceae Clostridium beijerinckii 0.8% 1.1%

Clostridiaceae Clostridium botulinum A 0.4% 1.0%

Clostridiaceae Clostridium botulinum A2 Kyoto 0.4% 0.9%

Clostridiaceae Clostridium botulinum A3 Loch Maree 0.4% 0.9%

Clostridiaceae Clostridium botulinum A ATCC 19397 0.4% 0.9%

Clostridiaceae Clostridium botulinum A Hall 0.4% 0.9%

Clostridiaceae Clostridium botulinum B1 Okra 0.4% 0.9%

Clostridiaceae Clostridium botulinum Ba4 657 0.4% 0.9%

Clostridiaceae Clostridium botulinum B Eklund 17B 0.6% 1.3%

Clostridiaceae Clostridium E3 Alaska E43 0.6% 1.3%

Clostridiaceae Clostridium botulinum F 230613 uid47575 0.5% 1.0%

Clostridiaceae Clostridium botulinum F Langeland 0.5% 1.0%

Clostridiaceae Clostridium cellulolyticum H10 0.8% 1.0%

Clostridiaceae Clostridium difficile 630 0.5% 1.0%

Clostridiaceae Clostridium difficile R20291 uid38039 0.5% 0.9%

Clostridiaceae Clostridium kluyveri DSM 555 1.1% 1.1%

Clostridiaceae Clostridium kluyveri NBRC 12016 1.1% 1.1%

Clostridiaceae Clostridium ljungdahlii ATCC 49587 0.6% 0.9%

Clostridiaceae Clostridium novyi NT 0.8% 2.0%

Clostridiaceae Clostridium perfringens 0.4% 1.3%

Clostridiaceae Clostridium perfringens ATCC 13124 0.4% 1.0%

Clostridiaceae Clostridium perfringens SM101 uid12521 0.4% 1.4%

Clostridiaceae Clostridium phytofernentans ISDg 0.9% 1.0%

Clostridiaceae Clostridium tetani E88 0.4% 1.0%

Clostridiaceae Clostridium thermocellum ATCC 27405 0.5% 0.6%

aMost similar sequenced genomes for each contig class are indicted in bold bContig match is the percentage of total bases in all contigs in the set that are part of an alignment to the

reference genome. cReference match is the percentage of total bases in the reference genome that are part of an alignment to

some contig in the set.

63

4.3.3.3 PhyloChip analysis of ANAS community composition

PhyloChip analysis of metagenomic DNA identified 1,056 bacterial and archaeal taxa in ANAS

(37 bacterial phyla, two archaeal phyla). Of these, 285 taxa were identified as highly active by

detection when hybridizing RNA to the PhyloChip (29 bacterial phyla, two archaeal phyla).

The community composition of ANAS as detected by DNA PhyloChip experiments remained

stable between the three feeding cycles sampled (mean coefficient of variation for normalized

signal intensity: 0.083). The greatest variation was seen for taxa with the lowest average signal

intensity. 11 taxa, all among the lowest 5% of average signal intensity, had coefficients of

variation ≥ 0.20. The highest coefficient of variation (0.48) was for a Methanosarcinaceae.

The highly active taxa (taxa detected by RNA PhyloChip experiments) were also stable between

the three sampling time points (mean coefficient of variation: 0.085). Only four taxa, the four

Methanobacteriaceae detected, had coefficients of variation > 0.20 for the RNA PhyloChip

experiments. These had coefficients of variation ranging from 0.24 to 0.36 and fell within the

lowest 15% of signal intensity.

For all contig class taxa (Clostridiaceae, Dhc, Desulfovibrio, Deltaproteobacteria,

Methanobacterium, Methanospirillum, Spirochaetes, and Synergistetes) except for

Methanospirillum, representatives of the same taxa were detected as both present and active by

PhyloChip experiments using DNA and RNA respectively. Representatives of all bacterial

contig class taxa were among the highest 10% of average signal intensity in DNA PhyloChip

experiments, consistent with these taxa being dominant members of the community. However,

all Methanobacterium detected were among the lowest 15% of signal intensity, and

Methanospirillum were not detected by the PhyloChips. In the RNA PhyloChip experiments,

Dhc was the only contig class taxa among the top 10% of signal intensity, although several

Clostridiales not identified as Clostridiaceae were also in this most active group. One

Spirochaete also appeared in the top 15% of signal intensity.

4.3.4 Metabolic functions in ANAS

4.3.4.1 Metagenome gene content overview

The ANAS metagenome contains 60,992 putative protein coding genes. Of these, 36,101 could

be assigned to clusters of orthologous genes (COGs), and 32,520 of those were assigned to

categories beyond general function prediction (Table 4.4).

64

Table 4.4. Overview of ANAS gene content by clusters of orthologus genes.

COG Categorya

Number

of genes

Percentage of genes

(out of genes with

function prediction

beyond general function)

Amino acid Transport and metabolism 4,046 12.4%

Energy production and conversion 3,364 10.3%

Carbohydrate transport and metabolism 2,684 8.3%

Translation, ribosomal structure, and biogenesis 2,540 7.8%

Signal transduction mechanisms 2,499 7.7%

Replication, recombination, and repair 2,363 7.3%

Cell wall / membrane / envelope biogenesis 2,227 6.8%

Transcription 2,201 6.8%

Coenzyme transport and metabolism 1,952 6.0%

Inorganic ion transport and metabolism 1,922 5.9%

Posttranslational modification, protein turnover,

chaperones

1,436 4.4%

Nucleotide transport and metabolism 1,266 3.9%

Lipid transport and metabolism 961 3.0%

Defense mechanisms 733 2.3%

Cell motility 694 2.1%

Intracellular trafficking, secretion, and vesicular

transport

670 2.1%

Secondary metabolites biosynthesis, transport and

catabolism

505 1.6%

Cell cycle control, cell division, chromosome

partitioning

422 1.3%

Chromatin structure and dynamics 33 0.1%

Cytoskeleton 1 0.0%

RNA processing and modification 1 0.0%

Function unknown 2,535

General function prediction only 4,577

Not in COGs 25,456

aCOG categories are ordered by number of genes in category

Three types of functional genes related to dechlorination (genes directly involved in

dechlorination, genes involved in cobalamin biosynthesis, and genes involved in hydrogen

production and consumption) were selected for further analysis because they may provide insight

into the dechlorinating abilities of this community and the interactions between community

members that result in an efficient dechlorinating consortium.

65

4.3.4.2 Reductive dechlorination

Fifteen putative RDase genes located on six contigs were identified in the JGI annotation of the

ANAS metagenome contigs (Table 4.5). In addition, three RDase genes identified by previous

microarray analysis (Lee, Cheng et al. 2011) but not annotated in the JGI annotation were found

by BLAST search on an additional contig (ANASMEC_C7898) and gene identities were

confirmed by comparison to the NCBI non-redundant nucleotide database. Two of these were

present as full length RDase genes. The third, matching Dhc strain 195 gene DET1535, was

present as two partial RDase genes disrupted by an apparent frame-shift mutation. Of the seven

contigs containing RDase genes, six were identified as Dhc by both SS and TF. The remaining

contig (ANASMEC_C818), which contained only one RDase gene, was identified as Dhc by the

SS method, but was left unclassified in the TF analysis. This contig had significant sequence

similarity to Dhc strain 195 over approximately 25% of its length, including the RDase gene

region. The non-aligning contig regions contained recombinases and phage related genes,

indicating possible horizontal transfer and perhaps accounting for the atypical tetranucleotide

composition.

Of the 17 full length RDase genes identified, seven were matched to putative RDase genes in the

NCBI non-redundant protein database (≥ 98% amino acid ID). Together with the partial RDase

genes mentioned above that match DET1535 (97% amino acid ID), these correspond to the eight

RDase genes identified as present in ANAS (or Dhc isolates from ANAS) by the previous

microarray study (Lee, Cheng et al. 2011). These include two (tceA and vcrA) that have been

linked to enzymes with demonstrated RDase activity, and one (DET0088) that appears as a

truncated RDase gene in Dhc strain 195, but which is extended to a full length novel RDase gene

in the ANAS metagenome as noted above. Of the other ten putative RDase genes, one had 91%

amino acid identity to another putative RDase and the remaining nine had less than 70% identity

to any sequences in the NCBI protein database as of July 2011.

66

Tab

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67

4.3.4.3 Hydrogen production and consumption

Hydrogenases, enzymes that catalyze the reversible oxidation of molecular hydrogen, appear to

be widespread in the ANAS community, with 271 genes annotated as hydrogenase components

(Appendix 5). Of those, 126 genes were present on contigs that were large enough for

classification by TF, spread across all classes except the Methanospirillum class. However, this

is likely a false negative result given the low coverage of this genome as described above.

Methanospirillum are expected to have genes for hydrogenases used in methanogenesis

(Madigan, Martinko et al. 2008). Of the 126 hydrogenase genes in large contigs, the

Methanobacterium class had the largest proportion (36 genes), followed by the Desulfovibrio

class (26 genes) and Dhc (17 genes). The Clostridiaceae class contained only three genes for

hydrogenase components.

4.3.4.4 Cobalamin biosynthesis

In total, twenty genes along the first (corrin ring synthesis) and second (lower ligand attachment

and rearrangement) parts of the cobalamin biosynthesis pathway were targeted for analysis

(Kanehisa and Goto 2000, Warren, Raux et al. 2002). Near complete cobalamin biosynthesis

pathways appear to be present in the Dhc, Methanobacterium, and Clostridiaceae classes (Table

4.6, Appendix 6).

Genes for incomplete biosynthesis pathways were identified in both the ANAS Desulfovibrio

and Methanospirillum contigs. However, the total sequence length of these contig classes is

significantly smaller than would be expected for a full genome (Desulfovibrio contigs, 2,249,123

bp total, represent 43% to 78% of the length of sequenced Desulfovibrio genomes;

Methanospirillum contigs, 421,953 bp total, represent 12% of the length of the Methanospirillum

hungatei genome), indicating incomplete coverage.

68

Table 4.6. Cobalamin biosynthesis genes identified in ANAS metagenome contigs.

Contig Classifications

Genesa Clo

stri

dia

ceae

Deh

alo

cocc

oid

es

Spir

och

aete

s

Met

hanobact

eriu

m

Des

ulf

ovi

bri

o

(cla

ss 6

)

Syner

gis

tete

s

Del

tapro

teobac

teri

um

(cla

ss 9

)

Met

hanosp

iril

lum

uncl

assi

fied

short

conti

gs

cbiX/cbiK(cobN)b x x x x x x

cbiL (cobI)c x x x x x x

cbiH (cobJ) c, d x x x x x x

cbiF (cobM) c, d x x x x x x x

cbiG c x x x x x x

cbiD (cobF ) c x x x x x x x x

cbiJ (cobK ) c x x x x

cbiE (cobL) c, d, e x x x x x x x

cbiT (cobL) c, d x x x x x

cbiC (cobH) c, d x x x x x x

cbiA (cobB) d, e x x x x x x x

cobA (cobO) d, e x x x x x

cbiP (cobQ) d, e x x x x x x x

cbiB (cobD) d, e x x x x x x

cobU (cobP) d, e x x x x x x

cobT (cobU) d, e x x x x

cobC (cobU) e x

cobS (cobV) d, e x x x x x x

aGene names are given for the anaerobic (early cobalt insertion) cobalamin biosynthesis

pathway, with the names for the aerobic pathway genes with the same function in parentheses. bcbiX and cbiK (and cobN) are grouped together because they code for alternative

cobaltochelatases cGenes involved in corrin ring synthesis, the first part of the cobalamin synthesis pathway dGenes present in Hodgkinia cicadicola eGenes present in Dhc strain 195

69

4.3.4.5 TCE dechlorination by ANAS subcultures under different cobalamin conditions

Figure 4.6 shows ethene production during TCE dechlorination by subcultures of the ANAS

microbial community. Subcultures were capable of dechlorinating TCE to ethene, even when

additional cobalamin was not provided. However, dechlorination was more rapid when higher

concentrations of cobalamin were provided.

Figure 4.6. Ethene production during TCE dechlorination by ANAS subcultures. (a.) First

subculture. (b.) Second subculture.

4.4 Discussion

In this study, metagenomic sequencing and analysis were used to examine the phylogenetic

composition of ANAS and the genes present in the dominant community members, with a focus

on Dhc. Although Dhc and non-Dhc metagenome contigs were classified based on TF

(tetranucleotide frequency), an alternative SS (sequence similarity) approach was also used to

identify Dhc contigs. Both approaches have advantages: SS can identify smaller contigs, while

TF works even when closely related reference genomes are unavailable.

Metagenomic analysis has provided some insight into the functions and interactions of different

community members in the context of overall TCE dechlorination activity. The widespread

presence of genes for hydrogenases emphasizes the importance of hydrogen metabolism in this

community. In the ANAS bioreactor, lactate is fermented to acetate and hydrogen, which are

used by Dhc and by other organisms. Because hydrogenases can catalyze both the formation and

degradation of molecular hydrogen, the presence of hydrogenase genes does not differentiate the

organisms that are producing hydrogen from those that are consuming it. Based on knowledge

of other organisms in these taxonomic groups, however, the Clostridiaceae, the Desulfovibrio,

and the Spirochaete are potential fermenters that produce hydrogen, although some may also be

homoacetogens, consuming hydrogen and carbon dioxide to produce acetate (Leadbetter,

70

Schmidt et al. 1999, Madigan, Martinko et al. 2008). The methanogens likely consume

hydrogen as an electron donor, competing with Dhc (Madigan, Martinko et al. 2008). These

different hydrogen producers and consumers (fermenters, homoacetogens, reductive

dechlorinators, and methanogens) have different thermodynamic requirements and different

hydrogen thresholds. However, in this community they appear to have developed working

syntrophic relationships, allowing stable long-term dechlorination activity.

With respect to dechlorination reactions, although other organisms are known to reductively

dechlorinate TCE to DCE in many environments (Scholz-Muramatsu, Neumann et al. 1995,

Sharma and McCarty 1996, Holliger, Hahn et al. 1998, Löffler, Cole et al. 2004), the association

of all RDase genes in the metagenome with Dhc contigs implies that Dhc is the dominant, and

possibly sole dechlorinator in ANAS. Previous studies have indicated that ANAS contains two

distinct Dhc strains (Holmes, He et al. 2006, Lee, Cheng et al. 2011). Consequently, the

metagenomic dataset was analyzed to determine whether sequences from these strains were co-

assembled. Although co-assembly at the domain level has been reported for both real and

simulated metagenomic datasets, these errors are expected to be rare and easy to identify

(DeLong 2005, Mavromatis, Ivanova et al. 2007). Co-assembly of closely related species or

strains is more common and more difficult to detect (Mavromatis, Ivanova et al. 2007, Kunin,

Copeland et al. 2008). In this study, co-assembly of sequences from the two Dhc strains was

detected for at least six contigs, representing 541,431 bp. Considering the similarity between

these two strains (Lee, Cheng et al. 2011), this amount of co-assembly is not surprising.

However, it is worth recognizing as one characteristic of this approach and highlights the

importance of parallel sequencing of isolates and/or single cells to metagenome studies.

Because the medium provided for ANAS contains only 2 µg/L cobalamin, a lower than optimal

concentration for Dhc (He, Holmes et al. 2007), cobalamin synthesis in the bioreactor is likely

necessary to support the observed dechlorination abilities. Several community members,

including Dhc, appear to have genes for complete or near complete cobalamin biosynthesis

pathways. Although some genes appear to be missing, not all genes identified in the pathway are

necessary for de novo cobalamin synthesis. For example, Hodgkinia cicadicola, an

endosymbiont of cicadas with a highly streamlined genome, retains cobalamin synthesis

capabilities despite its lack of several of the enzymes in the pathway (Table 4.6) (McCutcheon,

McDonald et al. 2009). Subcultures of the ANAS microbial community continued to be able to

dechlorinate TCE to ethene without additional cobalamin despite 10 (subculture 1) and 100-fold

(subculture 2) dilutions of residual cobalamin carried over in the ANAS inoculum, confirming

that cobalamin production is functional within this microbial community.

Since previously sequenced Dhc do not have these genes and Dhc are assumed to obtain this

cofactor from other organisms, the association of genes for corrin ring synthesis (the first part of

cobalamin biosynthesis) with Dhc was unexpected (Kube, Beck et al. 2005, Seshadri, Adrian et

al. 2005, He, Holmes et al. 2007). The contig regions containing the corrin ring synthesis genes

have TF compositions that were grouped with the Dhc sequences and not with any of the other

contig classes (Figure 4.4), implying that these genes were not recently horizontally transferred

to Dhc, but have been maintained in the ANAS Dhc for some time. Given that Dhc are known to

have relatively streamlined genomes (Kube, Beck et al. 2005, Seshadri, Adrian et al. 2005,

McMurdie, Behrens et al. 2009), it is interesting that the ANAS Dhc appear to be maintaining

genes for this pathway even though other community members appear to be capable of supplying

71

this cofactor and cobalamin has been supplied in the medium, albeit at a low level, for over ten

years. Since PCR amplification and sequencing have confirmed the presence of these genes in

Dhc strain ANAS2, preliminary experiments were performed to investigate the functionality of

the Dhc cobalamin biosynthesis pathway in that strain. In these experiments, DMB was

provided to some cultures because DMB is the lower ligand of the cobalamin molecule. The

metagenomic analysis did not reveal a DMB synthesis pathway, indicating that exogenous DMB

may be necessary for cobalamin production even if the identified corrin ring synthesis genes are

functional. Only minimal ethene production was observed when this strain was grown without

cobalamin (Figure 4.5), indicating that the predicted cobalamin synthesis pathway was not

actively providing cobalamin under these conditions. A previous study showed that Dhc is

capable of scavenging and modifying corrinoids from their environment (Yi, Seth et al. 2012)

and these newly identified cobalamin synthesis genes may represent an extension of that

scavenging system. Further investigations are necessary to determine whether this pathway is

utilized under other conditions, either for de novo cobalamin synthesis or for corrinoid

scavenging and repair.

The description of the community composition derived from metagenomic analysis is generally

consistent with those of previous 16S clone library studies (Richardson, Bhupathiraju et al. 2002,

Lee, Johnson et al. 2006) and the PhyloChip study presented here. Overall, data from the clone

libraries and metagenome sequencing agreed on the most abundant bacterial taxa, which were

also detected by the PhyloChip. The PhyloChip also detected many other taxa because it is

more effective at detecting low abundance organisms (Brodie, DeSantis et al. 2006, DeSantis,

Brodie et al. 2007). This is because the PhyloChip is less sensitive to random sampling effects

that impact sequencing based approaches (Zhou, Kang et al. 2008, Zhou, Wu et al. 2011). With

the exception of Methanospirillum, the archaeal taxa detected in the metagenome were also

detected by the PhyloChip, along with several other archaea. No Archaeal clone libraries have

yet been prepared for ANAS.

One notable discrepancy between the bacterial clone libraries and the metagenome was in the

relative abundance of taxa detected by the two methods. Specifically, the Spirochaete exhibited

only low abundance (1-2% of clones) in both clone library experiments (Richardson,

Bhupathiraju et al. 2002, Lee, Johnson et al. 2006). Based on the median contig length and

average read depth of Spirochaete contigs (Table 4.2) however, the Spirochaete appears to be

one of the more abundant organisms in ANAS. Studies of other Dhc containing dechlorinating

microbial communities have also detected Spirochaetes (Gu, Hedlund et al. 2004, Macbeth,

Cummings et al. 2004, Duhamel and Edwards 2006). Based on what is known of Spirochaetes

in general, they may be fermenters or homoacetogens in these communities (Leadbetter, Schmidt

et al. 1999, Madigan, Martinko et al. 2008). Clone libraries are known to be susceptible to PCR

and cloning biases (von Wintzingerode, Gobel et al. 1997), and some studies have found

Spirochaetes in particular to be underrepresented in some clone libraries (Campbell and Cary

2001, Hongoh, Ohkuma et al. 2003). However, recent studies suggest that estimates of relative

abundance based on metagenomic sequencing read depth are also biased (Amend, Seifert et al.

2010, Morgan, Darling et al. 2010).

The notable discrepancies between the metagenome and the PhyloChip results were with the

methanogens. The PhyloChip did not detect any Methanospirillum, and although the read depth

and contig length of the Methanobacterium contigs indicates that they were dominant community

72

members, their low signal intensity using the PhyloChip suggests otherwise. Because these

experiments involved amplification of 16S genes prior to PhyloChip hybridization, the low

signal intensity may be due to poor amplification. Methanogens had the highest coefficients of

variation in both the PhyloChip DNA and RNA results, lending weight to the explanation that

the methanogen population is less stable than the rest of this microbial community.

In this study the metagenome sequences were also compared with a previous comparative

genomics study that used microarrays to detect known Dhc genes in ANAS (Lee, Cheng et al.

2011). The agreement between the two approaches in detecting Dhc genes (Figure 4.1) confirms

that the coverage of Dhc in the metagenomic sequence data was very high. Most differences

between the results of the two methods are regions of the reference Dhc genomes for which no

genes were detected in ANAS by microarray, but which had an alignment in the metagenome

contigs. This highlights the specificity of the microarray to detect only very closely matched

sequences. Alternatively, metagenomic sequencing allows the detection of somewhat more

divergent versions of genes as well as unexpected or novel genes.

This analysis of metagenomic sequence data has advanced our understanding of this

dechlorinating microbial community. The phylogenetic composition of ANAS described by

metagenomic sequencing generally confirms the composition described by PhyloChip and

previous 16S clone library studies, with a few discrepancies in the relative abundances of some

taxa and possible variability in the methanogen population. More importantly, the analysis of

functional genes relevant to dechlorination provides insight into the capabilities of microbial

community members. Dhc appear to be the dominant reductive dechlorinators in ANAS since

all RDase genes identified were associated with Dhc. Genes related to the synthesis of

cobalamin, an important cofactor for reductive dechlorination, are present in several community

members, including Dhc, highlighting the importance of this cofactor in the function of ANAS.

This is the first time that genes for the first part of the cobalamin biosynthesis pathway have been

identified in a Dhc strain, further highlighting the unique adaptation of the ANAS strains to

reductive dechlorination, but also suggesting that the non-Dhc community members likely have

additional important roles beyond cobalamin biosynthesis.

73

Chapter 5:

Evaluation of microarray specificity for detecting Dehalococcoides mccartyi genes in mixed

microbial communities using metagenomic sequence data

74

5.1 Introduction

Members of the bacterial species Dehalococcoides mccartyi (Dhc) are the only organisms known

to be able to fully dechlorinate the potentially carcinogenic groundwater contaminants

tetrachloroethene (PCE) and trichloroethene (TCE) to the harmless end product ethene via

reductive dechlorination (Maymo-Gatell, Chien et al. 1997, Smidt and de Vos 2004). Because of

this apparently unique capability, Dhc has been heavily studied in isolation, in defined microbial

consortia, in mixed microbial communities, and in isolation using a variety of approaches (Ding

and He 2012, Löffler, Ritalahti et al. 2013).

Microarrays have been used to study the presence, gene content, and gene expression of Dhc in

communities and in isolation (West, Johnson et al. 2008, Conrad, Brodie et al. 2010, Hug, Salehi

et al. 2011, Lee, Cheng et al. 2011, Waller, Hug et al. 2012, Mansfeldt, Rowe et al. 2014). When

conducting and interpreting microarray study results, it is helpful to understand the specificity of

the microarray for the targeted sequences, especially when targeting organisms in mixed

communities whose genetic sequences may not be identical to those used to design the

microarray. Previous studies have reported a wide range of microarray specificity depending on

type of microarray, probe design, and protocols (Kane, Jatkoe et al. 2000, Koltai and

Weingarten-Baror 2008, Oh, Yoder-Himes et al. 2010). However, most previous studies used

well defined, known DNA samples to examine microarray specificity and sensitivity (Kane,

Jatkoe et al. 2000, Oh, Yoder-Himes et al. 2010). While informative, such studies cannot

capture the complexities introduced by using microarrays to profile the genetic content of mixed

microbial communities (Dugat-Bony, Peyretaillade et al. 2012).

In this study, microarray specificity in the context of complex, mixed microbial communities

was evaluated using metagenomic sequencing data from three communities, including the ANAS

community analyzed in Chapter 4. The microarray evaluated here, which targets 98.6% of genes

from four sequenced Dhc isolates, has been used previously to profile Dhc genes in

dechlorinating microbial communities and un-sequenced Dhc isolates (Lee, Cheng et al. 2011,

Lee, Cheng et al. 2013, Men, Lee et al. 2013, West, Lee et al. 2013). This microarray is capable

of differentiating between closely related Dhc strains, indicating high specificity (Lee, Cheng et

al. 2011).

5.2 Methods

5.2.1 Microbial communities

Three TCE dechlorinating microbial communities containing Dhc were evaluated. The first was

the ANAS community described in Chapter 4. The remaining two communities were developed

by Dr. Yujie Men and are described in detail in (Men, Lee et al. 2013). Briefly, these were

cultures inoculated with groundwater samples and enriched over many generations to ferment

lactate and to dechlorinate TCE. Culture HiTCEB12 was enriched with 100 µg/L (74 nM)

cobalamin amendment, while culture HiTCE was enriched without exogenous cobalamin.

75

5.2.2 Metagenome and microarray datasets

Metagenome sequences for ANAS were described in Chapter 4. All raw sequencing reads were

used in this analysis, including 453,944 454-Titanium sequencing reads and 76,272 mate pairs of

Sanger sequencing reads.

Metagenome sequences for HiTCEB12 and HiTCE were provided by Dr. Yujie Men. Prior to

analysis, raw Illumina sequencing reads were processed to trim adapter contamination sequences

and low quality (q < 20) bases using Scythe and Sickle.

The microarray datasets used in this analysis used the microarray described in (Lee, Cheng et al.

2011). Briefly, these were Affymetrix GeneChips targeting 98.6% of genes from four Dhc

genomes (strains 195, BAV1, CBDB1 and VS). This microarray targets each gene with a probe

set consisting of 11 exact match probes, each 25 bases long, along with 11 corresponding single

mismatch probes in which the thirteenth base is a mismatch for the target gene sequence. All

microarray datasets were analyzed as previously described (West, Johnson et al. 2008, Lee,

Cheng et al. 2011). A gene was deemed “Present” if it had a p-value < 0.05, indicating

differential hybridization to exact match probes over mismatch probes, and a signal intensity >

140 for all three replicates (Lee, Cheng et al. 2011, Men, Lee et al. 2013).

Microarray data for ANAS were reported by Lee et al. (Lee, Cheng et al. 2011) and were

provided by Dr. Patrick K. H. Lee. Microarray data for HiTCEB12 and HiTCE were reported by

Men et al. (Men, Lee et al. 2013) and were provided by Dr. Yujie Men.

5.2.3 Evaluation of microarray specificity through comparison of datasets

Microarray exact match probe sequences were aligned to metagenome sequences using the

Bowtie aligner to find the best match between the probe and the metagenome sequences. Bowtie

options were set to allow up to three mismatches in an alignment.

Based on the alignment results, a probe mismatch profile was determined for each microarray

probe set. A probe set’s mismatch profile included five numbers: the number of probes whose

best alignment in the metagenomic sequences had zero, one, two, or three genes and the number

of probes that did not align. For example, a probe set (gene) that had six probes with zero

mismatches, one probe with one mismatch, two probes with two mismatches, two probes with

three mismatches, and zero unaligned probes would be represented by the profile [6, 1, 2, 2, 0].

Once mismatch profiles were determined, the relationships between these profiles and the

presence/absence of genes according to the microarray analysis were evaluated


The distribution of genes among different categories of profiles is shown in Figure 5.1. Of the

1,365 possible mismatch profiles, 676 were detected for at least one gene in at least one of the

datasets (378, 441, and 436 for ANAS, HiTCEB12, and HiTCE datasets respectively). Of these,

a majority of profiles (453 profiles, 67%) always corresponded to “Absent” identifications in the

microarray analysis. Most of the remaining profiles (200 profiles, 30%) always corresponded to

76

“Present” identifications. Only 23 profiles were non-determinant, corresponding to some genes

that were “Absent” and some genes that were “Present”. However, a few of these non-

determinant profiles corresponded to a large number of genes, resulting in a nearly even

distribution of genes between the always “Present” and non-determinant profile categories

(Figure 5.1, Table 5.1)

Figure 5.1. Distribution of genes among profile categories. Profile categories: always

“Absent”, always “Present”, and non determinant. The large pie chart is for all datasets

combined. Small pie charts are for individual datasets. Numbers on the wedges of the small

pie charts indicate the number of genes in that dataset represented by that profile category.

Details of the non-determinant profiles are given in Table 5.1. Notably, for both the HiTCEB12

and HiTCE datasets but not for ANAS, there were a small number of genes that were identified

as “Absent” in the microarray analysis for which exact matches were found in the metagenomic

sequencing reads for all eleven probe sequences. These included six genes for HiTCEB12

(DET_tRNA-Val-1, DET_tRNA-Ala-1, DET_tRNA-Pro-2, DET_tRNA-Val-3, DET_tRNA-Ala-

2, and DET1376) and three genes for HiTCE (DET1463, DET_tRNA-Val-3, and DET1376).

77

Further review of the microarray data revealed that the probe sets for these genes all had p-values

less than 0.05, an indication of the presence of the gene, but were considered “Absent” due to

low signal intensity of one or more replicate samples.

The microarray analysis was highly specific for sequences with low divergence from the target

sequence. The fraction of a genes identified as “Present” was high when most probes had exact

matches or only one mismatch, while that fraction was very low if three or more probes had three

mismatches or were unaligned (Figure 5.2). The ANAS dataset showed slightly lower

specificity than the other datasets, identifying a larger fraction of genes as “Present” when

multiple probes had two mismatches (Figure 5.2 grey squares).

Figure 5.2. Fraction of genes identified as “Present” as a function of the number of probes

for that gene with exactly N mismatches where N = 0, 1, 2, 3, or > 3 (unaligned). The large

graph is for all datasets combined. Small graphs are for individual datasets.

78

Tab

le 5

.1.

Non-d

eter

min

ant

pro

be

set

(gen

e) m

ism

atch

pro

file

s.

All

Dat

aset

s

frac

tio

n

"Pre

sent"

1.0

0

0.9

9

0.9

9

0.9

8

0.9

6

0.9

5

0.9

1

0.8

5

0.7

8

0.6

7

0.6

7

0.6

7

0.6

4

0.5

0

0.3

3

0.3

3

0.3

3

0.2

5

0.2

0

0.0

2

0.0

2

0.0

1

0.0

1

nu

m

gen

es

46

5

99

4

17

1

42

24

44

11

13

9

3

3

6

11

2

3

9

3

4

5

44

61

15

6

12

6

HiT

CE

frac

tio

n

"Pre

sent"

0.9

9

0.9

9

1.0

0

1.0

0

1.0

0

0.9

0

n/a

0.6

7

1.0

0

n/a

0.5

0

0.5

0

0.6

7

n/a

n/a

0.3

3

n/a

0.0

0

0.0

0

0.0

0

0.0

0

0.0

0

0.0

0

nu

m

gen

es

18

1

33

9

54

10

5

10

0

3

1

0

2

2

3

0

0

3

0

1

2

2

26

45

54

HiT

CE

B1

2

frac

tio

n

"Pre

sent"

1.0

0

0.9

9

0.9

7

0.9

2

0.8

3

0.9

2

0.6

7

0.6

7

0.5

0

n/a

n/a

0.0

0

0.5

0

n/a

0.0

0

0.0

0

n/a

0.0

0

0.0

0

0.0

0

0.0

0

0.0

0

0.0

0

num

gen

es

147

417

35

12

6

12

3

3

4

0

0

1

4

0

1

4

0

1

1

4

19

38

63

AN

AS

frac

tion

"Pre

sent"

1.0

0

1.0

0

1.0

0

1.0

0

1.0

0

1.0

0

1.0

0

1.0

0

1.0

0

0.6

7

1.0

0

1.0

0

0.7

5

0.5

0

0.5

0

1.0

0

0.3

3

0.5

0

0.5

0

0.0

3

0.0

6

0.0

1

0.1

1

num

gen

es

137

238

82

20

13

22

8

7

4

3

1

3

4

2

2

2

3

2

2

38

16

73

9

The

Pro

file

num

unal

igned

pro

bes

0

0

0

0

0

0

0

0

0

0

0

0

0

1

5

0

3

4

0

4

3

9

4

num

pro

bes

wit

h 3

mis

mat

ches

0

0

0

0

1

0

1

0

0

2

1

0

0

2

1

0

5

3

0

7

6

1

4

nu

m p

robes

wit

h 2

mis

mat

ches

0

0

0

2

0

0

1

0

3

2

1

3

0

2

2

4

0

1

8

0

2

1

3

nu

m p

rob

es

wit

h 1

mis

mat

ch

2

0

4

2

2

6

4

8

4

1

6

5

11

5

2

4

3

3

3

0

0

0

0

num

pro

bes

wit

h 0

mis

mat

ches

9

11

7

7

8

5

5

3

4

6

3

3

0

1

1

3

0

0

0

0

0

0

0

79

Relationships between profile mismatch distributions and microarray “Present”/”Absent”

identification are shown in more detail in Figure 5.3. Considering genes for which all probes

aligned, the maximum number of mismatches observed for a gene that was still considered

“Present” were 27, 18, and 15 for the ANAS, HiTCEB12, and HiTCE datasets respectively,

corresponding to an estimated 90% to 95% sequence identity (indicated with arrows in Figure

5.3). For all datasets, there were a small number (0.3% to 2%) of genes identified as “Present”

for which none of the probes had perfect matches (27, 5, and 4 genes for ANAS, HiTCEB12, and

HiTCE respectively) (top row of symbols in Figure 5.3). The HiTCEB12 and HiTCE datasets

also contained some genes identified as “Present” with up to four unaligned probes, while the

ANAS dataset contained one gene identified as “Present” despite nine unaligned probes.

The microarray analysis was highly specific for the targeted gene sequences but did not

exclusively require exact matches, requiring a minimum estimated sequence identity of 90-95%

in sequences targeted by probes for a gene to be identified as “Present”. This is despite the use

of single mismatch probes to account for non-specific hybridization (West, Johnson et al. 2008,

Lee, Cheng et al. 2011). The high specificity of this microarray is consistent with its previously

demonstrated ability to differentiate between genes from closely related Dhc strains (Lee, Cheng

et al. 2011).

The specificity of these microarray analyses may come at the cost of sensitivity by causing some

genes to be identified as “Absent” for which exact or very close matches to the probe target

sequences are actually present. As noted above, this was seen for an extremely small number of

genes (6 and 3 genes respectively) in the HiTCEB12 and HiTCE datasets, and none for the

ANAS dataset. Further investigation of the effects of parameters used in microarray analysis on

specificity and sensitivity could improve interpretation of microarray results. Previous studies

have found that several factors including probe length, GC content, and probe sequence, can

affect hybridization efficiencies, thus influencing microarray specificity and sensitivity

(Letowski, Brousseau et al. 2004, Harrison, Binder et al. 2013). The location of mismatches,

which was not considered in this analysis, has also been shown to be a factor in probe

hybridization efficiencies (Letowski, Brousseau et al. 2004).

80

Fig

ure

5.3

. R

elat

ionsh

ips

bet

wee

n p

rofi

le m

ism

atch

dis

trib

uti

ons

and m

icro

arra

y “

Pre

sent”

/ “A

bse

nt”

iden

tifi

cati

on

. T

he

larg

e

gra

ph i

s fo

r al

l dat

aset

s co

mbin

ed. S

mal

l gra

phs

are

for

indiv

idual

dat

aset

s. G

reen

cir

cles

indic

ate

“Pre

sent”

gen

es a

nd r

ed X

s

indic

ate

“Abse

nt”

gen

es.

Mar

ker

siz

e is

pro

port

ional

to n

um

ber

of

gen

es. A

rrow

s in

dic

ate

the

gre

ates

t num

ber

of

mis

mat

ches

for

whic

h a

ny g

enes

wer

e “P

rese

nt”

fo

r ea

ch d

atas

et.

81

This analysis also revealed only small apparent differences between the ANAS dataset and the

HiTCEB12 and HiTCE datasets, with the analysis of the ANAS dataset indicating slightly lower

microarray specificity. The ANAS dataset resulted in a higher fraction of genes declared

“Present” when a majority of probes had either one or two mismatches (Figure 5.2, small

graphs), and allowed a higher number of total mismatches to still be identified as “Present”

(Figure 5.3, arrows on small graphs). However, these differences affect the results for only a

very small portion (2%) of genes, as indicated by the small marker sizes in the relevant regions

of Figure 5.3. Differences in metagenomic sequencing or in the microarray experiments may

have contributed to the observed differences in the specificity analysis results.

The ANAS metagenome was sequenced using a combination of 454-Titanium and Sanger

sequencing, generating a total of 0.3 Gbp of sequence. In comparison, the metagenome datasets

for HiTCEB12 and HiTCE totaled 17.3 Gbp and 14.0 Gbp of sequence (after trimming)

respectively, generated using Illumina HiSeq. The lower sequence quantity for ANAS implies

lower sequencing depth, which could miss low abundance variants in the Dhc population.

Microarray approaches are more effective at detecting low abundant variants because they are

less susceptible to sampling biases that affect sequencing (Brodie, DeSantis et al. 2006,

DeSantis, Brodie et al. 2007, Zhou, Kang et al. 2008, Zhou, Wu et al. 2011). However, the

analysis of the ANAS metagenome indicated high sequencing depth for Dhc contigs (Table 4.2)

(Brisson, West et al. 2012). Further, when Lee et al. applied DNA from the two Dhc strains

isolated from ANAS (ANAS1 and ANAS2) to the same microarray, they found that these two

dominant strains entirely account for the Dhc genes identified in the microarray analysis of the

ANAS community (Lee, Cheng et al. 2011), indicating that low abundance variants were not

responsible for the anomalously declared “Present” genes. This suggests that sequencing

differences are unlikely to account for the observed differences in specificity analyses between

datasets.

Differences between microarray experiments may also have contributed to the small differences

observed in the specificity analyses. Sample preparation and processing for ANAS were

performed by different personnel and at different times from the HiTCEB12 and HiTCE

samples, which could have contributed to small differences in microarray specificity results. In

their study of microarray expression analysis variability, Bammler et al. found variability within

and between laboratories for microarray analysis results even with standardized protocols and

sample material (Bammler, Beyer et al. 2005).

82

Chapter 6:

Comparative genomics of Wood-Ljungdahl pathways in Dehalococcoides mccartyi and

other fully sequenced bacteria and archaea

A version of the following chapter has been published as part of:

Zhuang, Wei-Qin, Shan Yi, Markus Bill, Vanessa L. Brisson, Xueyang Feng, Yujie Men, Mark

E. Conrad, Yinjie J. Tang and Lisa Alvarez-Cohen (2014). "Incomplete Wood–Ljungdahl

pathway facilitates one-carbon metabolism in organohalide-respiring Dehalococcoides

mccartyi." Proceedings of the National Academy of Sciences 111(17): 6419-6424.

83

6.1 Introduction

Detailed studies of Dehalococcoides mccartyi (Dhc) in isolation have revealed a variety of

capabilities and limitations of Dhc’s metabolism. For example, Dhc’s dependence on cobalamin

was discussed in Chapter 4. Dhc strain 195 has been shown to be capable of nitrogen fixation,

although growth and dechlorination are more robust when fixed nitrogen is provided (Lee, He et

al. 2009). Similarly, although Dhc can produce all essential amino acids, provision of exogenous

amino acids has been shown to enhance growth and dechlorination activity (Zhuang, Yi et al.

2011).

Recently, examination of the Dhc genome and subsequent experimental results revealed an

incomplete Wood-Ljungdahl pathway not previously reported for other microorganisms

(Zhuang, Yi et al. 2014). The Wood-Ljungdahl pathway is used by many microorganisms in

various forms for energy metabolism and carbon fixation (Fuchs 1994, Zhuang, Yi et al. 2014).

All sequenced Dhc strains have a version of this pathway that is missing key genes (Kube, Beck

et al. 2005, Seshadri, Adrian et al. 2005, McMurdie, Behrens et al. 2009). Specifically, the gene

for methylene-tetrahydrofolate reductase (MTHFR), which is used for the production of methyl-

tetrahydrofolate, a precursor for methionine synthesis (Rüdiger and Jaenicke 1973), is missing.

Zhuang et al. showed that Dhc instead produces methyl-tetrahydrofolate by cleaving acetyl-CoA

using acetyl-CoA synthase (ACS), using the Wood-Ljungdahl pathway in the reverse direction

(Zhuang, Yi et al. 2014). In the process, Dhc produces carbon monoxide, which accumulates

(since Dhc also lacks a gene for carbon monoxide dehydrogenase) and inhibits growth unless

other organisms are present that can remove carbon monoxide.

In this study, a bioinformatic analysis was performed to determine whether the pattern of genes

corresponding to this incomplete version of this pathway (absence of MTHFR and presence of

ACS) is present in other known microorganisms.

6.2 Methods

A comparative genomic analysis was performed to evaluate the prevalence of MTHFR genes in

sequenced microbial genomes and to identify organisms lacking this gene. The search was

performed using all bacterial and archaeal genomes in the National Center for Biotechnology

Information (NCBI) genomes database, downloaded in February of 2013. Initially, all genome

annotations were searched for identified MTHFR genes. Based on the genes identified in this

search, a database of corresponding protein sequences was created of all annotated bacterial and

archaeal MTHFR protein sequences. To find previously unannotated MTHFR genes, all

genomes that lack annotated MTHFRs were compared with the new MTHFR protein sequence

database using blastx. An expect value cutoff of 10-15 was used to positively identify previously

unannotated MTHFR genes. The set of genomes without blast hits of MTHFR genes was

manually queried in the Kyoto Encyclopedia of Genes and Genomes (KEGG) and

Microbesonline databases for genes encoding MTHFR functions, including MTHFR (ferredoxin)

(EC 1.5.7.1), MTHFR [NAD(P)H] (EC 1.5.1.20), and a bifunctional homocysteine S-

methyltransferase (EC 2.1.1.10).

84

In the genomes lacking MTHFR genes, the presence of acetyl-CoA synthase (ACS) (EC

2.3.1.169) genes was searched using the same process to assess the distribution of incomplete

Wood–Ljungdahl pathways in other prokaryotes (Pierce, Xie et al. 2008). Finally, all D. mccartyi

strains were searched for the homologs of betaine-homocysteine methyltransferase (EC 2.1.1.5)

using the bacterial protein sequences in BRENDA (in August of 2013) and elsewhere (Rodionov,

Vitreschak et al. 2004).


Because the substitution of missing MTHFR function by acetyl-CoA cleavage had not been

previously reported, a bioinformatics analyses was performed on the sequenced bacterial and

archaeal genomes to determine whether the pattern of genes for this characteristic is present in

other microorganisms besides Dhc. Figure 5.4 summarizes the results of this analysis. Of 2,277

bacterial and archaeal genomes in the NCBI genomes database (as of February of 2013), 1,548

were found to have annotated MTHFR genes. A blastx search comparing the remaining 729

genomes to the annotated MTHFR protein sequences identified an additional 303 genomes

containing MTHFR homologous genes, and another seven genomes with MTHFR genes were

identified by manual curation. MTHFR genes were not identified in 419 genomes (Appendix 7).

Many of these genomes belonged to parasitic or symbiotic organisms, whose close association

with a host may explain the absence of this functionality. Further analysis of the 419 genomes

without MTHFR genes focused on the presence of the ACS gene. Within this group, homologs

of this gene were found only in sequenced Dhc strains, but not in other genomes.

Figure 6.1. Identification of targeted Wood-Ljungdahl pathway genes in fully sequenced

bacterial and archaeal genomes.

Others have previously suggested that some soil and marine bacteria use an alternative

methionine biosynthesis pathway, using betaine instead of CH3-THF as the methyl donor to

85

homocysteine via the activity of betaine-homocysteine methyltransferase (Rodionov, Vitreschak

et al. 2004, Barra, Fontenelle et al. 2006, Sowell, Norbeck et al. 2008, Hug, Beiko et al. 2012).

Therefore, all Dhc genomes were also searched for gene homologs of this gene to determine

whether this alternative pathway might account for the absence of MTHFR. No homologs of

bacterial betaine-homocysteine methyltransferase were found in any of the Dhc genomes,

indicating the absence of this alternative pathway in Dhc.

Although variations in C1 metabolism, such as the replacement of tetrahydrofolate by

polyglutamate or methanopterins and NAD(P)H instead of ferredoxin as the cofactor for

MTHFR (Schauder, Preuß et al. 1988, Thauer, Kaster et al. 2008, Fuchs 2011), have previously

been reported for bacteria and archaea, the complete replacement of the MTHFR function with

acetyl-CoA cleavage had not been reported prior to its identification in Dhc (Zhuang, Yi et al.

2014). The above comparative genomics analysis suggests that this strategy for generating CH3-

THF is not found in other sequenced bacteria and archaea, highlighting the apparent novelty of

this pathway. However, it is still unclear whether this strategy has wider distribution in the

environment, given the limited numbers of sequenced organisms and the inherent challenges

associated with growing carbon monoxide generating organisms in isolation.

86

Chapter 7:

Conclusions and Suggestions for Future Work

87

The research presented in this dissertation investigated two different microbial processes:

bioleaching of rare earth elements (REEs) from monazite sand and microbial reductive

dehalogenation of chlorinated ethenes. These studies utilized metabolomic, metagenomic, and

genomic approaches to supplement and support microbiological studies of these processes.

7.1 Bioleaching of rare earth elements from monazite

The work in Chapter 2 demonstrated that some microorganisms are capable of bioleaching rare

earth elements (REEs) from monazite sand. A variety of both bacterial and fungal

microorganisms were tested for their monazite bioleaching capabilities, including two known

phosphate solubilizing microorganisms (PSMs) (Aspergillus niger ATCC 1015 and Burkholderia

ferrariae FeG101) as well as nine microorganisms isolated in this study. The most effective

bioleaching microorganisms were all fungi and included Aspergillus niger ATCC 1015 and two

strains isolated in this study: Aspergillus terreus strain ML3-1 and Paecilomyces spp. strain

WE3-F. Bioleaching of monazite has not been previously reported and suggests a possible

environmentally less damaging alternative to conventional REE extraction methods.

Further investigations in Chapters 2 and 3 sought to gain an understanding the mechanisms of

monazite solubilization. The analysis of organic acids in Chapter 2 indicated that although the

reduction in pH did result in some solubilization, most of the organic acids tested did not achieve

significant additional solubilization through complex formation. Citric acid provided some

additional solubilizing power, but this effect was small and did not account for observed

bioleaching effectiveness. In contrast, the spent medium experiments showed that other

unidentified compounds released by the microorganisms did contribute significantly to

bioleaching. The goal of identifying these compounds motivated the exometabolomic analysis

described in Chapter 3. In addition to confirming that citric acid does contribute some to REE

solubilization, the metabolomics analysis also identified citramalic acid as a potential

contributor. However, the contributions of citric and citramalic acid were shown to be relatively

small. The results of the gel permeation experiments presented in Chapter 3 indicated that large,

highly stable complexes, like those of EDTA, were not present in the bioleaching supernatant,

suggesting that solubilization is instead potentially driven by the combination of many weaker

complexing compounds with interactions more similar to those of citric acid. Further

investigation is necessary to identify additional compounds contributing to bioleaching.

Even under the best growth conditions identified in Chapter 2, the maximum recovery of REEs

from monazite was still only 5%. Significant process improvements and growth condition

optimization will be required to increase REE recovery to make bioleaching an economically

viable alternative to conventional processes.

One approach to improving performance would be to do a more extensive search for effective

bioleaching microorganisms. The enrichments and isolations described in Chapter 2 were

derived from only two environmental source materials, and the most effective bioleaching

isolates from these enrichments outperformed known PSMs. Now that the possibility of

monazite bioleaching has been established, the enrichment and isolation of organisms from more

sources, especially from locations where monazite occurs naturally, could result in the isolation

88

of more effective bioleaching microorganisms. Organisms from sites where monazite occurs

may already be adapted to using it as a phosphate source and can also be expected to have

improved tolerance for radioactivity from Th.

Further optimization of growth conditions is also necessary for development of a viable process.

Characterization of bioleaching performance with different growth media compositions in

Chapter 2 resulted in improved REE solubilization. The comparison of growth with and without

soluble phosphate presented in Chapter 3 indicated that although low phosphate availability

resulted in a lag in growth, phosphate was not ultimately the growth limiting factor. Further

investigation suggested that nitrogen may have been the limiting factor for growth. Some

previous work has suggested that nitrogen limitation may be desirable for organic acid

production and phosphate mineral solubilization by fungi (Cunningham and Kuiack 1992,

Papagianni 2007, Scervino, Papinutti et al. 2011). Further investigation of the effects of nitrogen

availability on the bioleaching process could be a useful direction for process optimization.

In addtions to identifying more effective microorganisms and optimizing their growth conditions,

other process improvements could also increase leaching efficiency. For instance, grinding the

monazite to a finer grain size may facilitate more effective leaching. Preliminary abiotic

leaching experiments using 10 mM citric acid to leach monazite ground to different gain sizes

(same abiotic leaching protocol as in Capter 2) demonstraded improved leaching with more

finely ground sand (Figure 7.1). Increasing the leaching time may also be effective. Over six

days of bioleaching, REE concentrations did not appear to have leveled off (Figure 2.3), and a

longer leaching time could increase REE yield. Alternatively, the same monazite could be

leached several times with fresh medium and organisms to extract more REEs, or a continuous

flow process could be used in which the monazite is retained via settling while the leachate is

continuously recovered. Removal of phosphate from the system, possibly by the use of

phosphate accumulating microrgansism, could also help drive the leaching process and prevent

re-precipitation of REEs.

Figure 7.1 Effect of monazite sand grain size on abiotic leaching with 10 mM citric acid.

89

Further identification of the unknown compounds that contribute to REE solubilization would

also provide a useful basis for guiding process optimization for the production of desirable

metabolites. Of the metabolites identified as potentially associated with bioleaching in Chapter

3, several were identified by BinBase ID but not by chemical name. Further investigation into

the mass spectra associated with these metabolites could be done to identify characteristics of

these molecules. However, such an analysis will be complicated by the effects of the silylation

derivatization performed to prepare the samples for gas chromatography.

In addition to REE solubilization, the fate of Th from monazite is also a critical consideration for

development of an alternative monazite bioleaching process. The analysis in Chapter 2 yielded

the promising result that the microorganisms preferentially released REEs over Th from

monazite. Further results from Chapter 3 found that while citric and citramalic acid both

contributed somewhat to REE solubilization, citramalic acid solubilized less Th. This is

consistent with the previously published different affinities of various ligands for REEs and Th

(Martell and Smith 1974, Yong and Macaskie 1997). Future investigations of bioleaching

compounds must continue to examine Th solubilization in order to guide optimization for

increased solubilization of REEs while minimizing Th solubilization.

7.2 Microbial reductive dehalogenation of chlorinated ethenes

The metagenomic analysis described in Chapter 5 provided information about the structure of the

ANAS microbial community and about the strains of Dehalococcoides mccartyi (Dhc) operating

within that community. Metagenome contigs were grouped into ten classes based on

tetranucleotide frequency. Based on the presence of phylogenetic marker genes, eight of these

classes could be given taxonomic identification: Clostridiaceae, Dhc, Desulfovibrio,

Methanobacterium, Methanospirillum, as well as a Spirochaete, a Synergistete, and an unknown

Deltaproteobacterium. Clostridiaceae and Dhc had much higher read depths than other contig

classes, and thus are likely the most abundant taxa in the community. Reductive dehalogenase

genes were only found on contigs associated with Dhc, indicating that Dhc dominates the

dechlorination activity of the ANAS culture.

Some of the most interesting findings of the metagenomic analysis involved genes related to the

biosynthesis of cobalamin, an important cofactor for reductive dehalogenase enzymes.

Cobalamin biosynthesis genes were wide spread among the different contig classes, including

genes for a nearly complete biosynthesis pathway in Dhc, something that had not been

previously reported. The presence of these genes was confirmed in Dhc strain ANAS2.

However, preliminary experiments were not able to demonstrate the ability of this strain to grow

without exogenous cobalamin.

Further study is necessary to investigate the functionality of the cobalamin biosynthesis genes

identified in the metagenomic analysis. In order to understand cobalamin production within the

ANAS community, a metatranscriptomic analysis focused on these genes should be performed.

This analysis should investigate the transcription of all identified cobalamin biosynthesis genes

in the metagenomic data over the course of a TCE degradation cycle. This should help to

identify which organisms are important for cobalamin production in this community and when

90

they are producing it. Once an initial analysis is performed, a more targeted investigation of

selected genes could be performed using RT-qPCR (reverse transcription quantitative

polymerase chain reaction) in order to achieve a more quantitative analysis of critical genes for

this process.

Additional studies with the Dhc ANAS2 isolate should also be performed to further investigate

the functionality of the cobalamin biosynthesis genes identified in this isolate. One possible

approach would be defined co-culture experiments with other organisms that cannot synthesize

cobalamin but are able to support Dhc growth in other ways. This could produce more optimal

growth conditions that would allow Dhc to invest the energy required for cobalamin production.

Alternatively, instead of encoding a fully functional cobalamin biosynthesis pathway, these

genes may instead represent an extension of Dhc’s previously reported corrinoid scavenging

capabilities (Yi, Seth et al. 2012). This possibility could be tested by investigating the ability of

this strain to grow and dechlorinate with degraded cobalamin.

In Chapters 5 and 6, additional bioinformatics analyses to support other investigations of Dhc

were explored. The comparative analysis, presented in Chapter 6, of the Wood–Ljungdahl

pathway genes in Dhc and in genome sequences from other bacteria and archaea helped to

support the investigation of this version of the pathway and its novelty among known

microorganisms (Zhuang, Yi et al. 2014). In Chapter 5, the use of metagenomic sequencing data

to evaluate microarray specificity provides a new assessment of how a microarray performs

when applied to a complex microbial community. This analysis indicated that this particular

microarray could detect sequences with 90 to 95% sequence identity to the target sequences, but

also showed some variation of detection/non detection of genes having the same level of

sequence identity. Re-evaluation of the microarrays with different criteria for gene

“Presence”/”Absence” calls followed by a repeat of the analysis in Chapter 5 could shed more

light on how selection of these criteria affect the specificity of microarray analyses in the context

of complex microbial communities.

91

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Appendices

109

Appendix 1:

Calculation of total Nd solubilized from NdPO4 as a function of pH

110

Appendix 1. Calculation of total Nd solubilized from NdPO4 as a function of pH.

Equilibrium equations, with equilibrium constants from (Puigdomenech 2013):

Phosphate/Phosphoric Acid

1 H3PO4 ⇌ H2PO4− + H+ Ka1 =

[H3PO4]

[H2PO4−][H+]

= 10−2.149

2 H2PO4− ⇌ HPO4

2− + H+ Ka2 =[H2PO4

−]

[HPO42−][H+]

= 10−7.207

3 HPO42− ⇌ PO4

3− + H+ Ka3 =[HPO4

2−]

[PO43−][H+]

= 10−12.346

Neodymium Hydroxides

4 Nd3+ + H2O ⇌ NdOH2++H+ β1 =[H+][NdOH2+]

[Nd3+]= 10−8.16

5 Nd3+ + 2H2O ⇌ Nd(OH)2++2H+ β2 =

[H+]2[Nd(OH)2+]

[Nd3+]= 10−17.04

6 Nd3+ + 3H2O ⇌ Nd(OH)3(aq)0 +3H+ β3 =

[H+]3[Nd(OH)3(aq)0 ]

[Nd3+]= 10−26.41

7 Nd3+ + 4H2O ⇌ Nd(OH)4−+4H+ β4 =

[H+]4[Nd(OH)4−]

[Nd3+]= 10−37.1

8 Nd(OH)3(s)0 +3H+ ⇌ Nd3+ + 3H2O KspNd(OH)3 =

[Nd3+]

[H+]3= 1018.1

Neodymium Phosphates

9 NdPO4(s)0 ⇌ Nd3+ + PO4

3− KspNdPO4= [Nd3+][PO4

3−] = 10−26.2

10 Nd3+ + PO43− ⇌ NdPO4(aq)

0 KNdPO4(aq)0 =

[NdPO4(aq)0 ]

[Nd3+][PO43−]

= 1011.8

111

11 Nd3+ + 2PO43− ⇌ Nd(PO4)2

3− KNd(PO4)23− =

[Nd(PO4)23−]

[Nd3+][PO43−]2

= 1019.5

12 Nd3+ + PO43− + H+ ⇌ NdHPO4

+ KNdHPO4+ =

[NdHPO4+]

[Nd3+][PO43−][H+]

= 1018.237

13 Nd3+ + 2PO43− + 2H+ ⇌ Nd(HPO4)2

− KNd(HPO4)2− =

[Nd(HPO4)2−]

[Nd3+][PO43−]2[H+]2

= 1033.36

14 Nd3+ + PO43− + 2H+ ⇌ NdH2PO4

2+ KNdH2PO42+ =

[NdH2PO42+]

[Nd3+][PO43−][H+]2

= 1022.284

Mass Balance:

Assuming no precipitation of Nd(OH)3(s)0 , the total concentration of neodymium must be equal

to the total concentration of phosphate for dissolution of NdPO4. We will check this assumption

at the end.

[Nd]tot = [PO4]tot

First, we substitute in all dissolved forms of neodymium and phosphate seen in equations 1-14

above.

[Nd3+] + [NdOH2+] + [Nd(OH)2+] + [Nd(OH)3(aq)

0 ] + [Nd(OH)4−] + [NdPO4(aq)

0 ]

+ [Nd(PO4)23−] + [NdHPO4

+] + [Nd(HPO4)2−] + [NdH2PO4

2+]

= [PO43−] + [HPO4

2−] + [H2PO4−] + [H3PO4] + [NdPO4(aq)

0 ] + 2[Nd(PO4)23−]

+ [NdHPO4+] + 2[Nd(HPO4)2

−] + [NdH2PO42+]

Then we eliminate terms that appear on both sides of the equation.

[Nd3+] + [NdOH2+] + [Nd(OH)2+] + [Nd(OH)3(aq)

0 ] + [Nd(OH)4−]+

= [PO43−] + [HPO4

2−] + [H2PO4−] + [H3PO4] + [Nd(PO4)2

3−] + [Nd(HPO4)2−]

Then we substitute in equations 4-7, 11, and 13 above to get everything in terms of [Nd3+], [PO4

3−], and [H+].

[Nd3+] +β1[Nd

3+]

[H+]+β2[Nd

3+]

[H+]2+β3[Nd

3+]

[H+]3+β4[Nd

3+]

[H+]4

= [PO43−] +

[H+][PO43−]

Ka3+[H+]2[PO4

3−]

Ka2 ∙ Ka3+

[H+]3[PO43−]

Ka1 ∙ Ka2 ∙ Ka3+ KNd(PO4)2

3−[Nd3+][PO43−]2 + KNd(HPO4)2

−[Nd3+][PO43−]2[H+]2

112

Since we are looking at the dissolution of NdPO4, we will assume that this is in equilibrium with

NdPO4(s)0 , and use equation 9 to get [PO4

3−] in terms of [Nd3+] and then eliminate [PO43−] from

the equation.

[Nd3+] +β1[Nd

3+]

[H+]+β2[Nd

3+]

[H+]2+β3[Nd

3+]

[H+]3+β4[Nd

3+]

[H+]4

=KspNdPO4

[Nd3+]+KspNdPO4

[H+]

Ka3[Nd3+]+

KspNdPO4[H+]2

Ka2 ∙ Ka3[Nd3+]+

KspNdPO4[H+]3

Ka1 ∙ Ka2 ∙ Ka3[Nd3+]

+KNd(PO4)2

3−(KspNdPO4)2

[Nd3+]+KNd(HPO4)2

−(KspNdPO4)2[H+]2

[Nd3+]

We then rearrange to solve for [Nd3+] as a function of [H+].

[Nd3+]

= √KspNdPO4 (1 +

[H+]Ka3

+[H+]2

Ka2 ∙ Ka3+

[H+]3

Ka1 ∙ Ka2 ∙ Ka3+ KNd(PO4)2

3−KspNdPO4 + KNd(HPO4)2−KspNdPO4[H

+]2)

(1 +β1[H+]

+β2

[H+]2+

β3[H+]3

+β4

[H+]4)

We then use this to calculate [Nd3+] at a range of pH from 0 to 12. From that, we use equations

4-7 and 10-14 to calculate all other dissolved Nd species. We then sum up the concentrations of

all dissolved Nd species to calculate [Nd]tot for plotting Figure 1.2.

Now we need to check that our initial assumption that Nd(OH)3(s)0

does not precipitate was valid.

To do this, we use equation 9 and check that the following is satisfied at all pH in range:

[Nd3+] < KspNd(OH)3[H+]3

Doing this, we find that the above holds for pH < 12.55, so the assumption of no precipitation of

Nd(OH)3(s)0 is valid for the pH range of 0 to 12 used to plot Figure 1.2. At higher pH (≥ 12.55),

the concentration of hydroxide ions is sufficiently high to make precipitation of Nd(OH)3(s)0 a

factor.

113

Appendix 2:

Metabolomics signal intensities for all metabolites and time points

114

Appendix 2. Metabolomics signal intensities for all metabolites and time points.

aData for each time point are in a separate table.

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45

0

31

3

20

2

58

42

82

75

25

29

27

62

43

94

88

18

241

29

85

42

9

32

0

77

10

5

31

3

22

2

11

73

flas

k 5

16

2

24

3

64

7

49

5

54

0

81

7

24

2

29

40

69

52

3

92

70

12

6

60

65

29

968

15

60

20

53

42

9

10

8

13

5

70

1

24

4

15

23

flas

k 4

17

4

22

0

80

9

45

9

25

8

11

95

15

2

40

67

57

53

3

58

12

1

94

75

48

24

827

19

33

99

0

37

5

10

9

10

1

61

3

28

4

12

93

flas

k 3

11

1

17

3

10

55

58

4

24

48

10

35

48

1

32

13

54

16

19

10

5

57

33

17

649

20

437

17

18

53

7

20

8

11

5

18

7

28

41

22

2

21

02

flas

k 2

18

7

95

8

10

49

51

4

41

7

50

9

90

46

98

98

69

1

12

0

10

8

79

90

55

28

203

22

75

12

81

42

5

10

1

38

41

7

17

9

15

36

flas

k 1

17

0

16

6

62

7

45

4

37

6

79

6

33

6

44

20

47

29

74

65

95

10

3

12

816

18

153

29

83

10

31

36

3

87

65

67

4

18

1

17

17

Met

abo

lite

Nam

e o

r B

inB

ase

ID

lact

ito

l

lact

ulo

se

lau

ric

acid

Lev

og

luco

san

lyx

ito

l

lyx

ose

mal

ic a

cid

mal

tose

mal

totr

iose

my

o-i

no

sito

l

nic

oti

nic

aci

d

ole

ic a

cid

ox

alic

aci

d

pal

mit

ic a

cid

p-c

reso

l

pel

arg

on

ic a

cid

ph

osp

hat

e

pro

pan

e-1

,3-d

iol

pu

tres

cin

e

py

ruv

ic a

cid

rib

ito

l

rib

on

ic a

cid

rib

ose

117

Sig

nal

In

ten

sity

at

0 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

10

6

47

0

27

4

10

005

86

31

678

49

4

86

34

065

0

14

50

23

8

25

8

81

13

7

60

34

9

23

2

19

94

39

6

31

4

17

16

12

08

82

6

13

465

83

flas

k 5

79

79

6

83

58

702

9

37

378

13

6

70

40

660

0

14

16

11

0

22

9

56

42

3

63

88

11

3

14

88

39

5

44

2

13

15

90

1

34

3

21

719

83

flas

k 4

51

27

4

16

3

94

194

8

84

351

28

7

47

29

215

0

15

26

17

9

25

3

72

51

8

70

35

4

44

5

16

71

40

3

29

4

22

00

71

2

11

09

10

842

18

flas

k 3

91

10

18

89

69

658

9

54

932

94

64

47

854

3

16

28

10

0

18

9

85

43

6

51

73

12

4

15

77

42

0

31

0

15

34

10

86

41

2

26

080

19

flas

k 2

99

88

0

15

4

67

073

8

45

501

22

9

55

39

028

2

19

26

12

7

15

6

72

43

4

44

16

7

34

4

16

54

42

5

58

7

16

20

95

2

48

2

24

910

12

flas

k 1

82

23

33

12

4

67

130

7

32

821

59

7

36

50

182

8

16

97

11

2

23

4

10

1

51

6

57

15

0

30

7

17

87

46

9

28

2

15

31

96

0

57

0

24

842

36

Mo

naz

ite

On

ly

flas

k 6

68

68

4

10

7

70

008

6

32

217

40

7

68

87

974

8

18

06

10

5

21

0

66

34

4

70

12

3

18

5

15

51

40

0

29

1

13

33

13

81

42

7

23

480

20

flas

k 5

10

7

12

34

34

1

95

547

5

25

370

13

51

23

69

266

1

18

16

26

9

45

2

10

7

52

1

10

2

26

9

29

0

18

08

37

2

32

8

16

51

13

19

67

7

10

719

79

flas

k 4

10

9

56

8

27

8

86

287

4

49

227

60

4

15

3

75

686

1

19

92

17

4

39

8

92

31

6

33

19

9

42

3

18

76

34

6

37

1

15

59

15

53

46

8

17

182

88

flas

k 3

92

95

1

18

0

60

816

7

64

064

58

5

30

84

068

0

14

66

26

8

20

9

90

45

4

35

24

9

77

7

18

15

40

8

41

9

12

94

13

15

42

0

20

534

40

flas

k 2

84

20

24

24

2

87

455

0

41

136

30

0

41

2

33

385

0

22

25

11

2

19

9

96

18

6

63

14

3

28

2

17

28

37

1

55

0

14

71

90

8

86

5

29

585

85

flas

k 1

89

82

8

23

8

65

196

2

62

928

12

38

31

91

527

3

17

29

14

9

21

5

42

47

4

67

17

5

41

1

14

57

41

2

26

2

15

08

10

10

44

3

23

503

08

Met

abo

lite

Nam

e o

r B

inB

ase

ID

rib

ose

-5-p

ho

sph

ate

s(-)

-wil

lard

iin

e

shik

imic

aci

d

sorb

ito

l

stea

ric

acid

succ

inic

aci

d

sucr

ose

sulf

uri

c ac

id

tag

ato

se

thre

ito

l

tran

s-4

-hyd

rox

y-L

-pro

lin

e

tyro

sol

UD

P-g

lucu

ron

ic a

cid

ura

cil

xy

lito

l

xy

lon

ola

cto

ne

xy

lose

xy

lulo

se

39

47

62

91

99

118

Sig

nal

In

ten

sity

at

0 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

38

3

28

0

44

9

40

1

55

2

24

84

61

9

37

8

11

71

21

335

29

7

25

74

87

3

12

49

72

8

12

53

39

9

24

26

77

4

41

0

73

73

7

87

flas

k 5

15

9

15

0

43

2

15

9

49

5

61

3

37

9

34

5

38

7

55

508

19

8

10

60

30

6

75

9

50

2

67

4

30

7

69

98

49

1

23

6

16

2

73

8

92

flas

k 4

32

7

29

7

45

0

78

3

45

8

28

7

56

0

36

5

94

7

20

126

23

3

24

61

53

9

12

15

81

9

14

67

52

1

33

29

68

3

64

6

17

0

76

1

12

6

flas

k 3

37

7

24

21

45

7

22

7

52

1

96

5

41

0

36

7

37

6

10

390

5

14

4

10

46

35

2

10

03

62

1

84

8

42

7

81

31

71

9

37

3

72

11

06

11

7

flas

k 2

30

6

37

9

40

5

19

9

59

0

13

43

37

3

38

2

61

7

11

681

9

14

7

17

87

36

9

10

22

63

8

11

16

49

7

80

32

62

6

53

7

75

64

7

12

0

flas

k 1

35

7

21

7

41

0

79

5

70

2

18

9

57

4

39

3

30

5

15

109

8

95

15

63

37

1

97

0

64

3

11

82

54

2

80

49

53

5

54

5

15

5

56

7

79

Mo

naz

ite

On

ly

flas

k 6

32

0

22

64

19

5

25

8

31

6

31

50

86

4

41

5

43

6

18

437

3

13

9

12

41

31

3

10

73

68

9

91

6

38

4

66

45

58

6

53

2

10

5

53

7

11

4

flas

k 5

34

2

20

4

37

5

27

6

55

7

77

4

49

3

72

1

10

81

43

865

29

4

24

98

75

2

11

90

77

8

13

34

74

20

42

11

89

32

2

28

8

73

4

11

8

flas

k 4

32

2

21

78

27

9

19

2

54

6

25

9

71

8

59

4

87

0

66

167

19

6

16

89

49

7

11

58

99

0

12

26

51

9

31

82

63

3

38

4

19

0

68

9

15

5

flas

k 3

23

6

34

5

28

4

24

8

94

5

14

43

63

3

57

6

89

8

77

446

45

8

24

36

27

3

96

9

72

2

11

92

34

0

50

85

61

5

44

4

13

3

52

5

13

1

flas

k 2

21

6

12

64

30

1

40

0

63

8

40

3

77

8

68

7

61

7

46

114

15

0

16

53

51

5

10

13

65

2

85

3

76

4

40

68

10

98

69

0

22

7

75

3

11

7

flas

k 1

31

0

12

9

19

1

20

8

22

1

21

92

89

4

41

7

89

3

20

608

7

21

7

20

22

40

7

10

73

85

0

12

87

40

2

64

43

62

1

48

9

10

8

58

5

95

Met

abo

lite

Nam

e o

r B

inB

ase

ID

13

7

16

8

25

7

65

7

80

9

89

2

10

64

11

73

16

73

16

81

16

90

17

15

18

70

18

72

18

75

18

78

19

13

20

44

20

61

20

81

20

95

20

97

28

21

119

Sig

nal

In

ten

sity

at

0 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

26

52

11

46

53

5

15

7

11

761

33

91

23

905

40

6

15

9

55

3

90

7

28

9

30

2

24

8

17

4

96

8

23

4

25

1

37

14

11

56

23

92

64

9

31

5

flas

k 5

40

18

84

2

38

0

13

9

83

81

55

43

12

036

42

4

32

5

81

7

12

34

17

2

21

4

16

6

21

9

72

8

22

1

17

6

26

67

89

2

48

36

16

24

30

3

flas

k 4

54

31

10

99

51

0

16

8

11

267

33

56

30

445

43

7

10

4

38

2

79

4

26

6

23

7

16

7

92

11

30

20

6

24

8

35

23

91

0

11

90

61

1

31

9

flas

k 3

47

67

10

30

39

7

29

9

10

241

63

76

47

19

31

74

28

2

14

02

13

65

40

4

24

6

20

6

21

5

91

9

10

1

19

6

32

18

11

70

30

07

12

68

31

3

flas

k 2

46

76

10

97

36

7

15

5

92

86

63

03

16

234

13

75

29

6

90

8

12

12

23

6

21

8

15

5

12

7

10

43

20

9

17

2

30

55

13

45

30

65

17

52

34

3

flas

k 1

42

81

11

39

31

2

15

7

95

87

59

82

11

116

80

1

30

3

23

33

11

07

18

9

18

8

14

1

10

3

10

61

19

5

19

3

34

94

10

43

54

18

91

6

31

9

Mo

naz

ite

On

ly

flas

k 6

42

49

80

9

29

7

16

6

84

99

54

16

11

895

69

2

26

9

86

4

90

3

20

4

18

4

14

8

57

10

23

16

4

32

4

30

53

58

8

58

73

11

82

28

5

flas

k 5

59

68

16

09

45

2

15

5

11

130

37

75

12

676

45

6

20

9

14

85

77

1

35

5

23

2

17

0

11

7

10

58

23

0

61

3

50

14

88

5

15

46

68

3

31

5

flas

k 4

63

50

11

07

31

3

21

5

10

538

50

26

90

76

71

3

30

6

63

8

70

4

28

1

27

2

13

0

86

11

32

28

6

57

1

40

24

54

0

29

25

87

0

33

1

flas

k 3

45

82

12

96

74

1

12

4

90

66

40

12

19

770

36

3

24

3

10

33

12

11

20

7

26

6

10

1

11

1

93

0

17

4

32

8

27

70

74

8

23

24

10

20

28

7

flas

k 2

57

44

13

07

29

2

28

5

11

366

60

23

24

297

14

74

16

2

22

33

10

21

38

8

96

7

27

2

19

7

90

8

24

9

46

2

33

09

21

86

36

67

12

85

34

5

flas

k 1

43

80

95

3

38

6

13

3

85

13

56

39

92

92

29

5

34

8

96

7

92

2

23

8

25

3

12

5

10

4

11

30

10

8

32

9

42

51

74

9

43

39

76

1

23

6

Met

abo

lite

Nam

e o

r B

inB

ase

ID

29

44

30

83

31

73

32

47

34

42

37

81

45

41

45

43

47

13

47

32

47

95

47

97

48

19

49

37

49

76

53

46

55

76

61

04

63

30

66

46

93

20

14

694

16

561

120

Sig

nal

In

ten

sity

at

0 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

17

37

46

9

23

0

11

33

27

7

87

4

30

3

33

3

93

63

3

11

56

57

9

67

11

18

16

839

26

91

89

1

64

6

52

7

33

5

31

2

22

430

22

0

flas

k 5

27

04

32

0

10

1

23

9

42

9

17

44

27

5

53

7

45

13

93

86

0

43

8

71

12

64

19

823

38

96

14

75

70

9

44

3

44

0

33

7

11

575

84

flas

k 4

31

95

49

8

14

2

10

58

20

9

91

0

24

0

23

5

82

49

1

94

8

42

0

64

75

2

98

58

26

59

10

89

67

5

17

62

37

2

34

7

14

751

16

8

flas

k 3

30

58

37

0

80

44

2

11

5

12

09

30

4

27

6

16

5

12

40

94

1

30

2

56

16

06

20

290

45

61

19

61

91

8

54

9

26

2

52

4

14

250

17

2

flas

k 2

29

54

40

7

80

42

6

39

1

16

08

23

0

60

4

18

1

10

23

82

3

25

3

60

19

99

22

736

42

69

23

25

90

0

70

0

31

2

26

4

15

451

16

3

flas

k 1

30

04

37

6

97

21

7

48

0

71

1

28

6

23

0

18

3

23

37

82

7

36

3

92

14

07

25

907

38

51

14

83

88

9

39

23

25

4

24

9

14

640

13

0

Mo

naz

ite

On

ly

flas

k 6

22

05

40

1

11

7

38

6

45

5

11

82

23

7

45

3

13

0

89

8

79

5

24

9

66

16

37

22

146

38

25

19

86

75

2

34

53

57

4

29

1

18

890

11

9

flas

k 5

17

09

34

4

10

5

11

37

38

8

68

3

22

2

23

4

10

0

11

16

11

89

49

8

10

2

92

3

17

585

26

79

82

6

74

2

26

87

34

2

31

5

23

151

25

4

flas

k 4

16

88

44

5

89

70

7

38

5

87

0

19

6

21

9

88

67

8

10

30

36

8

88

97

3

10

927

25

97

11

48

71

6

19

82

56

9

19

6

26

112

20

9

flas

k 3

28

48

39

8

18

1

57

57

39

1

10

47

23

7

42

4

91

10

75

84

1

31

0

65

14

80

18

501

30

16

14

60

77

8

30

98

29

7

29

6

18

156

16

2

flas

k 2

17

89

35

8

16

2

51

0

44

9

65

2

95

8

76

4

10

2

22

86

10

98

37

2

71

11

00

18

953

46

10

13

49

93

8

33

25

60

1

39

6

24

499

26

8

flas

k 1

34

02

35

2

10

1

64

9

53

8

84

6

19

1

28

2

89

99

6

82

8

32

7

65

16

00

19

640

34

87

15

57

65

3

33

14

40

4

35

0

14

813

20

8

Met

abo

lite

Nam

e o

r B

inB

ase

ID

16

817

16

850

16

855

17

068

17

069

17

140

17

425

17

471

17

651

17

830

18

082

18

173

18

226

18

241

20

282

21

704

22

967

25

801

30

962

31

359

41

682

41

689

41

808

121

Sig

nal

In

ten

sity

at

0 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

25

4

91

2

25

6

16

1

24

7

37

1

36

9

44

8

33

6

13

5

43

2

26

4

21

2

14

51

12

0

93

8

12

3

59

9

12

438

46

23

32

24

84

4

91

flas

k 5

13

9

47

3

16

4

66

4

17

9

12

3

29

6

29

6

10

6

96

18

3

19

7

27

0

97

6

92

54

0

69

45

5

19

462

31

85

34

89

19

83

12

5

flas

k 4

22

3

62

7

23

2

54

0

21

3

40

0

51

2

35

0

48

6

12

3

19

2

37

2

28

7

13

73

13

4

12

55

12

3

42

8

13

355

43

58

26

79

10

17

97

flas

k 3

17

8

77

9

41

4

28

3

20

3

18

6

45

4

35

8

25

3

68

18

6

39

0

20

5

10

57

10

0

61

1

72

48

5

17

626

38

75

39

71

22

99

14

1

flas

k 2

14

3

88

9

38

8

99

0

11

4

21

9

41

0

41

0

22

4

84

27

5

37

3

22

8

12

42

93

63

8

87

86

18

247

37

71

37

42

16

78

13

1

flas

k 1

20

3

73

9

28

1

92

8

29

3

24

9

31

4

31

4

26

3

90

19

4

26

8

19

6

12

85

73

50

9

56

37

9

16

272

36

13

39

72

96

1

85

Mo

naz

ite

On

ly

flas

k 6

17

8

70

1

18

4

83

1

28

6

15

3

23

5

23

5

18

4

10

5

15

1

30

8

26

6

99

6

10

9

53

3

54

41

2

84

74

27

16

36

20

39

68

81

flas

k 5

19

7

10

02

20

3

60

3

27

9

44

3

44

5

29

0

33

2

14

1

24

9

30

9

25

4

12

34

12

5

67

2

89

62

2

64

55

43

96

30

49

39

40

12

0

flas

k 4

12

9

97

0

23

2

77

4

13

6

23

1

53

5

39

3

27

5

10

7

17

5

27

4

27

3

10

41

89

47

5

10

4

66

1

68

82

42

59

31

08

40

34

90

flas

k 3

10

2

60

5

29

4

85

9

16

4

26

4

24

2

24

2

25

5

85

20

9

26

9

16

5

72

3

73

83

3

40

40

3

10

181

29

23

34

29

53

28

11

8

flas

k 2

17

1

84

8

32

1

33

3

24

0

26

9

33

2

21

3

21

9

12

5

25

9

39

6

28

2

13

15

11

7

94

9

88

55

1

15

520

40

49

37

49

51

35

83

flas

k 1

98

62

1

32

4

89

3

26

8

22

7

38

2

38

2

17

4

91

19

8

26

8

18

7

90

2

73

42

9

69

46

9

77

40

30

74

33

19

25

60

85

Met

abo

lite

Nam

e o

r B

inB

ase

ID

41

811

41

938

42

205

47

170

48

522

49

382

53

724

54

643

87

877

88

911

89

221

97

326

97

332

10

076

8

10

086

9

10

088

0

10

090

8

10

129

9

10

222

3

10

261

6

10

266

1

10

266

2

10

267

9

122

Sig

nal

In

ten

sity

at

0 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

64

6

92

44

31

6

77

8

10

3

15

3

30

033

15

64

56

17

9

13

3

52

15

2

93

2

10

0

91

16

2

42

81

21

6

65

11

9

11

53

62

9

flas

k 5

25

0

11

574

50

4

11

04

12

0

28

1

17

523

23

43

15

1

25

6

13

3

77

91

93

7

16

9

52

13

7

36

86

89

81

15

6

16

51

38

4

flas

k 4

75

6

91

30

32

2

75

4

89

17

9

24

008

13

67

17

7

15

4

15

9

73

12

0

92

7

11

1

73

11

3

37

54

10

0

99

91

97

1

39

2

flas

k 3

24

9

12

586

53

1

12

12

12

2

30

6

23

109

28

67

93

24

5

96

69

12

0

83

9

12

5

13

4

32

7

91

6

10

3

72

14

7

25

33

55

8

flas

k 2

35

2

12

452

46

4

16

63

13

1

30

1

19

548

27

70

12

7

18

5

18

7

40

11

9

96

7

12

9

80

17

3

36

36

10

2

46

15

1

11

43

58

1

flas

k 1

34

1

12

334

52

8

14

69

15

7

29

2

20

102

41

39

14

6

12

6

72

71

14

3

90

5

23

1

96

12

0

41

18

99

87

16

8

16

39

54

6

Mo

naz

ite

On

ly

flas

k 6

39

0

11

812

50

7

11

55

17

6

21

2

20

549

20

23

13

3

16

9

65

42

96

11

81

11

7

88

13

7

35

91

96

72

74

11

63

80

5

flas

k 5

52

3

10

962

29

4

81

1

16

0

11

1

27

265

13

20

18

3

22

0

11

8

61

20

2

10

85

11

7

11

9

13

8

26

72

12

0

13

8

12

1

97

8

78

0

flas

k 4

39

1

84

79

34

8

86

5

94

15

2

22

266

17

28

76

11

8

12

7

81

12

4

95

7

80

12

8

90

33

64

55

71

10

3

87

2

96

8

flas

k 3

43

1

11

488

70

0

12

26

90

2

57

20

437

39

35

78

9

38

3

91

63

19

7

12

54

19

9

12

3

12

9

31

06

89

54

10

4

12

00

73

7

flas

k 2

42

9

10

540

53

3

12

50

18

0

18

6

25

141

19

95

30

3

24

3

17

6

73

76

12

39

14

0

11

3

16

8

34

45

14

3

93

20

9

16

91

12

64

flas

k 1

49

4

11

398

49

1

11

31

13

7

17

6

20

047

23

50

17

2

97

18

3

78

93

10

68

10

8

72

12

1

31

18

59

10

0

65

10

83

59

2

Met

abo

lite

Nam

e o

r B

inB

ase

ID

10

271

1

10

271

4

10

271

5

10

271

6

10

272

7

10

272

8

10

272

9

10

273

0

10

273

1

10

273

2

10

273

3

10

273

4

10

273

5

10

274

0

10

274

1

10

274

6

10

274

7

10

274

9

10

277

6

10

278

4

10

279

0

10

279

1

10

279

3

123

Sig

nal

In

ten

sity

at

0 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

66

0

23

0

13

5

flas

k 5

85

9

10

1

12

5

flas

k 4

54

6

14

2

10

9

flas

k 3

89

3

80

13

0

flas

k 2

92

8

80

16

4

flas

k 1

78

3

97

11

5

Mo

naz

ite

On

ly

flas

k 6

72

2

11

7

11

1

flas

k 5

80

5

10

5

13

1

flas

k 4

62

8

89

78

flas

k 3

70

1

18

1

90

flas

k 2

10

05

16

2

19

2

flas

k 1

73

7

10

1

72

Met

abo

lite

Nam

e o

r B

inB

ase

ID

10

280

8

10

280

9

10

282

1

124

Sig

nal

In

ten

sity

at

2 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

11

67

81

4

57

79

3

57

5

15

65

41

28

23

89

56

4

18

5

56

2

49

8

25

23

12

8

50

0

70

4

96

6

18

1

11

96

67

327

21

14

21

9

11

205

flas

k 5

94

3

41

7

16

4

13

16

58

4

11

22

33

52

18

70

52

7

80

20

7

27

7

15

81

83

27

0

28

23

84

6

51

67

2

29

243

18

85

80

53

95

flas

k 4

39

9

64

4

15

7

98

6

51

6

10

55

10

153

20

33

52

7

98

16

0

23

4

16

41

90

37

5

34

23

76

5

12

5

88

0

28

922

14

36

20

2

61

59

flas

k 3

89

9

89

9

13

5

10

46

66

5

76

9

45

35

28

13

53

0

91

33

3

28

0

15

40

89

41

1

13

01

81

0

16

8

86

4

18

057

15

25

23

2

32

47

flas

k 2

47

6

73

8

93

10

95

58

9

11

68

24

17

19

47

47

8

89

27

7

29

8

19

44

74

36

5

32

50

90

3

14

9

10

74

34

968

18

09

20

3

73

24

flas

k 1

10

57

10

57

37

91

6

61

3

12

33

27

64

19

68

42

5

85

22

8

22

8

16

01

78

31

7

24

83

63

9

11

6

76

6

25

048

15

69

17

7

52

27

Mo

naz

ite

On

ly

flas

k 6

46

3

46

3

16

0

54

9

18

5

17

6

42

17

12

60

43

5

12

9

29

1

11

2

15

46

15

3

32

3

23

0

19

5

11

9

88

4

46

33

96

7

19

5

11

70

flas

k 5

42

0

33

1

81

58

9

24

1

23

7

11

202

17

98

36

3

52

22

4

66

13

36

65

20

4

28

8

33

3

98

71

4

59

21

75

0

14

6

12

53

flas

k 4

49

3

24

0

91

46

8

27

1

36

3

36

73

23

74

55

2

95

25

3

14

5

16

73

95

30

1

35

1

37

3

10

1

71

8

13

094

16

28

15

9

26

60

flas

k 3

27

9

33

6

63

32

2

15

0

30

2

28

30

20

45

96

79

20

3

65

11

40

96

31

3

30

9

16

9

74

51

5

45

48

39

4

13

4

10

96

flas

k 2

48

9

42

1

11

8

53

6

22

2

20

4

34

00

22

33

41

3

84

23

8

86

13

27

66

30

3

45

1

65

5

16

2

83

7

74

00

95

2

15

3

18

42

flas

k 1

40

8

46

6

14

4

66

5

27

0

30

2

41

04

27

44

69

8

11

4

26

4

12

7

16

54

12

0

40

0

57

9

37

2

11

5

89

5

90

42

13

74

22

1

21

09

Met

abo

lite

Nam

e o

r B

inB

ase

ID

1-d

eox

yer

yth

rito

l

2-d

eox

yer

yth

rito

l

2-h

yd

roxy

adip

ic a

cid

2-h

yd

roxy

glu

tari

c ac

id

2-i

sop

rop

ylm

alic

aci

d

3,4

-dih

yd

rox

yb

enzo

ic a

cid

3,6

-anh

ydro

-D-g

luco

se

3,6

-anh

ydro

-d-h

exo

se

3-d

eox

yh

exit

ol

3-h

yd

roxy

-3-m

eth

ylg

luta

ric

acid

3-h

yd

roxy

pro

pio

nic

aci

d

4-h

yd

roxy

ben

zoat

e

5-h

yd

roxy

met

hy

l-2

-fu

roic

aci

d

aco

nit

ic a

cid

adip

ic a

cid

alan

ine

alp

ha-

ket

og

luta

rate

azel

aic

acid

ben

zoic

aci

d

bet

a-g

enti

ob

iose

bu

tan

e-2,3

-dio

l

cap

ric

acid

cell

ob

iose

125

Sig

nal

In

ten

sity

at

2 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

11

19

15

25

61

5

49

88

30

17

60

8

49

20

20

12

30

1

14

69

26

702

5

11

487

22

5

61

5

29

728

2

61

87

22

6

61

1

10

234

34

57

14

8

20

8

84

79

flas

k 5

12

14

79

3

29

8

44

35

19

15

45

7

39

09

12

64

11

0

12

89

39

949

7

57

44

11

4

45

9

35

223

9

27

22

26

5

21

6

11

989

19

42

63

11

3

10

593

flas

k 4

10

80

98

0

64

2

48

53

19

08

60

2

37

06

12

48

10

5

10

34

21

603

7

72

43

82

45

9

30

270

6

36

46

18

9

28

2

10

789

21

23

91

11

6

10

153

flas

k 3

71

5

85

7

37

9

52

19

15

29

39

6

61

66

99

9

16

3

23

03

50

074

7

41

34

11

1

48

3

27

089

4

23

44

58

37

8

15

585

24

11

92

21

3

90

62

flas

k 2

85

1

14

60

55

6

43

92

23

26

46

7

49

24

15

46

15

8

11

92

21

606

4

81

05

11

7

54

4

33

593

7

27

56

16

3

42

2

13

537

20

09

11

3

15

6

10

397

flas

k 1

10

23

11

83

60

9

44

07

20

75

54

0

26

56

13

15

18

7

11

40

14

707

0

50

82

53

42

5

35

863

1

30

92

16

8

41

7

13

158

20

99

12

9

16

0

10

542

Mo

naz

ite

On

ly

flas

k 6

40

1

14

48

28

4

23

15

10

35

39

1

71

11

68

2

18

1

17

23

34

062

5

46

23

14

7

55

0

23

645

9

88

9

60

62

5

17

049

13

45

12

3

23

6

53

83

flas

k 5

38

1

61

8

25

4

18

20

94

0

29

6

67

31

71

9

86

25

13

33

396

9

59

6

13

7

37

0

18

801

6

17

70

76

23

4

10

736

76

8

65

21

5

46

62

flas

k 4

48

3

10

19

32

0

27

33

14

45

58

0

63

74

10

09

14

8

23

47

93

149

33

43

90

52

8

27

671

7

26

75

66

31

8

13

540

12

27

86

23

2

39

06

flas

k 3

24

7

13

27

24

4

15

43

63

2

19

3

56

89

31

2

17

8

23

88

24

352

6

20

12

60

27

7

17

349

7

13

13

54

27

6

11

103

10

27

11

4

18

5

30

21

flas

k 2

35

6

12

30

23

0

30

48

11

19

43

4

62

33

85

4

16

6

21

27

26

938

1

29

60

15

1

46

5

27

505

7

22

31

91

24

6

13

580

14

05

11

4

22

6

33

01

flas

k 1

35

5

10

16

27

9

23

18

12

40

28

3

54

16

13

10

23

2

14

30

20

236

6

29

34

12

2

37

2

21

756

8

16

10

10

2

35

8

21

122

17

75

13

4

24

2

61

26

Met

abo

lite

Nam

e o

r B

inB

ase

ID

citr

amal

ic a

cid

citr

ic a

cid

deh

ydro

abie

tic

acid

dih

yd

rox

yac

eto

ne

ery

thri

tol

ery

thro

nic

aci

d

fru

cto

se

fum

aric

aci

d

gal

acti

no

l

glu

con

ic a

cid

glu

cose

glu

cose

-1-p

ho

sph

ate

glu

tari

c ac

id

gly

ceri

c ac

id

gly

cero

l

gly

cero

l-3

-gal

acto

sid

e

gly

cero

l-al

ph

a-ph

osp

hat

e

gly

coli

c ac

id

his

tid

ine

hy

dro

xy

lam

ine

iso

citr

ic a

cid

iso

thre

on

ic a

cid

lact

ic a

cid

126

Sig

nal

In

ten

sity

at

2 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

15

83

12

43

20

77

33

86

74

624

13

8

53

75

11

754

15

2

90

0

10

3

13

3

26

0

87

12

36

471

28

14

87

635

57

7

85

11

38

20

55

14

4

21

53

flas

k 5

48

0

61

2

39

8

11

29

32

202

13

7

43

00

12

385

10

8

33

8

85

57

82

61

09

20

011

11

57

61

061

16

9

21

3

14

42

38

523

14

8

21

65

flas

k 4

52

0

50

6

10

21

18

72

37

590

33

5

39

55

97

53

10

9

42

3

85

85

90

71

42

25

088

33

81

77

636

50

4

15

7

11

85

24

17

13

7

18

73

flas

k 3

23

2

73

0

31

59

11

77

28

118

51

7

30

71

71

38

10

3

10

65

67

12

6

13

5

78

27

27

584

37

57

98

283

45

7

20

5

99

8

33

718

19

1

17

02

flas

k 2

12

79

66

5

54

6

22

26

46

971

16

8

50

21

12

933

88

33

0

13

6

10

5

98

65

52

24

089

37

94

76

769

50

6

30

9

16

06

13

50

15

2

22

26

flas

k 1

78

1

47

2

34

82

13

09

48

492

64

5

42

16

92

17

49

73

6

76

11

1

27

50

28

23

286

30

48

76

222

46

2

22

0

10

96

28

08

92

25

48

Mo

naz

ite

On

ly

flas

k 6

27

0

23

4

85

6

78

24

530

11

65

21

12

35

62

82

71

3

22

7

98

50

72

42

26

391

16

45

78

5

69

9

16

2

10

07

28

981

21

9

53

23

flas

k 5

25

1

18

1

31

3

80

8

25

620

47

5

20

82

65

08

59

11

67

14

6

84

12

5

69

86

18

395

25

82

47

7

20

5

12

3

22

26

30

877

18

8

45

41

flas

k 4

21

1

40

2

60

4

13

46

40

611

20

41

24

83

14

479

54

11

06

20

6

11

0

19

6

65

76

27

539

19

82

23

8

38

0

19

7

61

7

49

371

20

0

10

422

flas

k 3

20

5

24

2

67

1

66

6

16

809

14

6

86

2

30

28

49

18

62

17

7

87

13

9

10

979

19

504

15

24

40

3

33

1

76

37

26

20

406

15

7

26

21

flas

k 2

38

0

25

3

15

71

30

8

31

780

95

9

18

84

23

290

74

66

0

13

1

10

2

40

91

95

22

982

19

51

73

3

36

4

19

6

16

72

38

597

18

5

89

39

flas

k 1

22

1

22

7

12

61

90

9

49

731

49

0

33

72

90

01

12

6

91

8

22

9

14

0

13

9

75

64

32

534

19

80

24

8

61

8

16

2

13

43

61

931

18

7

60

49

Met

abo

lite

Nam

e o

r B

inB

ase

ID

lact

ito

l

lact

ulo

se

lau

ric

acid

lev

og

luco

san

lyx

ito

l

lyx

ose

mal

ic a

cid

mal

tose

mal

totr

iose

my

o-i

no

sito

l

nic

oti

nic

aci

d

ole

ic a

cid

ox

alic

aci

d

pal

mit

ic a

cid

p-c

reso

l

pel

arg

on

ic a

cid

ph

osp

hat

e

pro

pan

e-1

,3-d

iol

pu

tres

cin

e

py

ruv

ic a

cid

rib

ito

l

rib

on

ic a

cid

rib

ose

127

Sig

nal

In

ten

sity

at

2 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

11

0

52

37

69

2

50

665

0

38

659

13

468

23

5

45

579

3

22

02

23

2

28

8

36

0

36

57

10

2

12

73

40

8

22

45

83

2

75

4

28

53

15

61

90

8

88

333

3

flas

k 5

16

2

44

93

24

3

48

027

0

25

260

12

956

80

43

193

4

14

26

11

8

27

3

26

3

10

62

57

24

20

24

3

16

64

59

5

30

7

16

27

84

7

38

4

17

880

72

flas

k 4

13

6

33

92

51

4

69

878

9

45

662

11

452

12

5

42

732

4

14

83

12

3

39

5

19

9

12

86

69

17

62

37

0

19

43

54

2

44

0

20

56

82

4

72

9

97

628

1

flas

k 3

18

9

17

36

17

2

35

399

6

34

665

82

57

10

8

50

842

4

21

95

13

5

29

1

20

7

94

6

77

14

72

29

3

23

41

63

6

30

4

19

39

10

92

86

8

26

398

49

flas

k 2

18

6

37

38

40

7

70

947

5

43

079

14

003

97

36

464

9

15

87

97

33

9

16

1

16

81

14

0

22

31

29

3

19

84

57

1

61

6

16

94

10

72

73

7

84

943

4

flas

k 1

13

6

26

06

31

3

73

618

3

19

756

12

316

64

43

380

1

14

94

12

6

40

0

21

4

10

09

26

2

18

41

26

4

20

37

61

0

25

9

20

03

86

9

89

7

10

109

21

Mo

naz

ite

On

ly

flas

k 6

82

18

62

41

0

13

296

9

27

590

52

19

89

10

779

18

18

68

37

2

40

6

11

8

79

1

53

85

8

42

6

20

44

57

9

55

9

20

77

10

90

71

0

22

018

45

flas

k 5

40

37

90

21

9

30

092

9

22

649

52

57

55

97

595

7

16

06

11

5

19

2

15

9

55

8

55

11

17

20

5

15

70

61

3

38

1

12

44

10

60

40

8

21

995

69

flas

k 4

84

53

82

41

7

35

002

1

30

764

58

52

25

99

840

4

18

63

28

3

26

1

19

3

73

9

64

92

3

85

4

26

58

10

25

31

2

17

04

97

0

47

8

24

194

44

flas

k 3

85

14

00

22

0

62

173

4

42

625

23

70

10

2

77

917

3

13

52

87

19

4

10

6

41

7

54

49

0

14

3

12

64

44

9

24

9

14

42

76

7

52

3

23

100

10

flas

k 2

10

8

30

31

41

9

32

247

7

60

067

42

43

11

0

85

148

3

15

32

16

2

35

5

15

8

61

8

57

10

89

24

8

18

88

83

8

48

0

17

97

94

4

40

2

23

723

29

flas

k 1

15

1

32

50

16

5

46

663

9

32

644

76

76

15

3

80

917

4

20

28

12

1

25

8

25

3

66

9

77

12

51

21

6

15

80

78

0

60

8

22

62

14

54

84

1

15

514

78

Met

abo

lite

Nam

e o

r B

inB

ase

ID

rib

ose

-5-p

ho

sph

ate

s(-)

-wil

lard

iin

e

shik

imic

aci

d

sorb

ito

l

stea

ric

acid

succ

inic

aci

d

sucr

ose

sulf

uri

c ac

id

tag

ato

se

thre

ito

l

tran

s-4

-hyd

rox

y-L

-pro

lin

e

tyro

sol

UD

P-g

lucu

ron

ic a

cid

ura

cil

xy

lito

l

xy

lon

ola

cto

ne

xy

lose

xy

lulo

se

39

47

62

91

99

128

Sig

nal

In

ten

sity

at

2 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

38

9

45

3

72

8

41

3

52

7

54

1

12

36

46

5

60

0

28

704

25

7

11

66

53

5

26

36

12

33

37

74

39

5

18

52

15

12

88

9

24

7

97

9

21

3

flas

k 5

22

6

22

48

37

6

19

4

57

5

18

37

80

2

25

7

44

2

29

900

20

6

72

8

48

0

14

65

60

3

19

52

31

3

25

51

51

8

48

7

45

82

3

10

5

flas

k 4

32

6

21

8

27

9

35

0

53

6

63

7

95

7

39

4

65

8

40

915

16

5

93

1

48

1

16

78

80

2

20

33

38

6

21

67

74

6

62

1

20

5

66

1

15

1

flas

k 3

35

8

14

32

55

3

18

8

48

4

27

2

10

53

34

8

28

0

61

361

12

0

10

21

64

9

16

92

10

58

20

18

61

3

36

97

93

7

50

3

19

6

89

6

15

4

flas

k 2

42

8

24

73

29

0

86

6

34

1

73

6

12

81

36

8

62

2

30

086

22

2

10

70

61

4

17

80

11

73

22

97

78

1

20

96

60

2

71

8

20

7

62

0

15

6

flas

k 1

39

6

38

6

26

0

24

8

28

1

34

2

89

1

29

2

24

6

34

242

18

3

10

16

43

3

17

66

87

7

21

62

24

8

20

25

87

6

52

4

11

2

99

0

16

6

Mo

naz

ite

On

ly

flas

k 6

28

8

71

3

20

0

23

1

54

5

74

9

60

0

75

1

92

2

44

359

38

1

34

48

51

2

16

11

97

1

18

35

58

0

33

47

81

4

65

5

20

6

65

6

51

flas

k 5

23

4

53

9

24

5

16

6

26

9

12

71

11

85

40

9

19

8

15

149

4

18

1

11

81

30

7

77

6

55

7

15

02

71

1

68

34

59

6

43

6

13

8

63

6

92

flas

k 4

29

8

93

6

25

0

26

0

43

6

18

79

33

5

48

9

18

23

99

321

52

9

45

57

57

6

14

98

67

1

18

24

60

1

38

87

65

6

44

2

21

0

59

8

82

flas

k 3

37

6

37

71

40

3

13

6

73

7

30

5

60

9

49

3

42

5

89

709

18

1

10

46

32

8

13

39

62

1

13

99

44

1

41

34

99

0

46

6

94

82

5

72

flas

k 2

30

1

13

6

22

9

19

3

31

4

36

96

65

7

54

7

75

7

86

239

24

5

20

90

47

2

16

21

76

1

18

53

24

2

36

37

65

7

75

3

14

1

93

1

11

9

flas

k 1

40

8

13

114

71

3

23

2

83

8

91

3

24

3

68

1

49

0

45

481

27

0

11

40

75

7

20

30

11

50

29

73

30

9

32

72

14

21

55

8

19

8

92

3

17

4

Met

abo

lite

Nam

e o

r B

inB

ase

ID

13

7

16

8

25

7

65

7

80

9

89

2

10

64

11

73

16

73

16

81

16

90

17

15

18

70

18

72

18

75

18

78

19

13

20

44

20

61

20

81

20

95

20

97

28

21

129

Sig

nal

In

ten

sity

at

2 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

72

16

14

90

42

9

30

9

16

535

15

763

19

682

14

27

10

324

42

3

10

97

11

07

35

8

34

9

35

1

19

13

25

7

30

9

63

00

57

0

28

25

76

07

55

8

flas

k 5

42

85

96

3

19

6

31

92

68

15

539

97

83

10

59

42

43

61

7

99

1

66

3

25

0

22

5

11

4

94

3

17

9

20

0

40

41

37

9

38

16

90

88

34

4

flas

k 4

49

93

12

52

49

5

22

11

241

11

676

11

658

11

82

46

67

12

82

61

6

49

5

21

2

17

1

12

9

11

62

17

8

33

5

44

11

58

4

22

32

58

46

31

0

flas

k 3

58

43

13

96

23

7

23

7

12

587

39

32

17

452

12

98

32

95

75

8

12

02

78

7

23

5

27

9

20

8

10

62

23

5

18

3

51

27

98

6

33

19

51

02

40

7

flas

k 2

49

76

15

41

30

9

53

11

110

48

40

85

72

71

7

56

36

34

3

61

9

56

5

39

4

19

7

10

8

12

61

46

9

21

9

47

25

42

6

23

81

63

84

33

5

flas

k 1

45

88

80

0

27

4

59

10

447

11

862

10

439

36

2

37

45

77

9

87

8

43

7

20

8

20

3

50

12

22

63

2

30

9

48

11

71

4

11

52

43

29

37

9

Mo

naz

ite

On

ly

flas

k 6

61

76

15

64

94

4

22

6

11

055

23

68

21

743

13

14

14

45

54

3

80

4

39

7

25

4

25

3

13

7

10

52

25

6

29

2

48

42

11

13

28

83

54

82

38

7

flas

k 5

36

86

11

34

24

8

16

9

79

46

86

02

13

741

40

7

16

44

83

7

10

18

24

5

19

6

87

19

5

71

8

19

9

16

4

36

65

37

8

41

37

96

94

27

8

flas

k 4

35

63

10

92

65

1

24

6

11

390

20

117

16

542

59

8

38

44

15

45

97

7

27

4

43

3

24

2

73

10

42

25

5

42

5

49

46

42

6

43

53

12

157

39

6

flas

k 3

38

61

10

30

23

7

17

0

78

28

19

25

12

442

26

1

13

34

93

3

73

6

24

3

24

9

22

4

11

4

78

6

64

31

6

36

63

53

8

39

67

53

80

26

1

flas

k 2

46

24

10

25

42

9

21

2

10

733

12

061

10

590

32

4

31

14

58

8

70

8

37

1

32

5

14

2

78

10

67

21

3

41

7

49

00

74

4

20

95

11

093

33

5

flas

k 1

73

99

13

45

37

3

21

3

14

824

35

00

24

354

14

93

23

99

65

0

65

0

47

0

15

3

35

2

27

8

15

46

38

5

64

6

60

78

10

91

22

22

96

07

29

2

Met

abo

lite

Nam

e o

r B

inB

ase

ID

29

44

30

83

31

73

32

47

34

42

37

81

45

41

45

43

47

13

47

32

47

95

47

97

48

19

49

37

49

76

53

46

55

76

61

04

63

30

66

46

93

20

14

694

16

561

130

Sig

nal

In

ten

sity

at

2 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

23

81

14

96

52

97

11

01

61

69

98

81

14

210

35

0

15

4

16

06

10

73

82

1

44

0

26

1

13

609

55

550

54

3

16

52

68

6

10

54

48

4

20

485

35

9

flas

k 5

16

96

44

7

19

84

46

1

16

17

11

769

42

85

18

3

72

74

5

75

0

60

6

56

7

10

18

10

034

18

071

13

55

45

7

55

2

77

4

30

6

13

444

22

2

flas

k 4

21

67

10

21

14

45

41

0

19

06

76

41

46

70

25

1

11

7

21

15

11

24

50

9

41

9

29

0

10

657

22

835

31

7

10

87

10

46

89

8

40

0

15

406

14

0

flas

k 3

30

27

51

6

58

3

37

3

12

14

70

81

41

04

38

4

92

11

27

14

42

50

3

77

5

12

49

16

077

14

592

13

51

15

19

33

71

76

6

54

4

17

926

25

7

flas

k 2

17

17

78

1

20

68

84

8

23

27

82

87

58

24

30

1

91

80

9

78

1

92

6

10

62

42

3

89

29

27

663

15

47

47

9

49

4

80

1

42

7

15

536

17

9

flas

k 1

14

74

75

7

15

83

62

2

16

35

55

86

39

94

28

7

85

12

67

87

6

69

3

40

3

82

7

89

19

18

951

32

6

11

13

25

8

80

8

35

1

15

089

24

4

Mo

naz

ite

On

ly

flas

k 6

20

61

44

6

22

3

10

69

63

5

71

25

83

6

35

2

70

29

7

11

82

84

2

52

3

99

9

28

359

71

42

10

65

68

5

50

25

71

8

25

2

14

530

37

2

flas

k 5

21

52

22

5

26

8

42

9

12

50

12

990

94

1

52

6

71

96

5

78

0

58

3

26

4

14

58

18

078

11

603

12

37

60

3

33

00

50

1

37

9

10

215

19

1

flas

k 4

27

57

52

9

28

0

89

9

16

65

15

487

20

07

54

4

77

14

07

10

58

53

9

24

4

10

07

15

342

18

040

12

75

50

3

12

03

49

9

20

3

14

356

12

9

flas

k 3

21

77

19

8

93

17

8

84

0

70

98

82

6

29

4

64

10

19

99

0

42

6

19

7

81

6

16

777

99

32

10

62

48

8

56

4

53

6

19

5

10

249

30

7

flas

k 2

25

10

30

7

12

7

78

2

12

15

14

446

13

67

76

3

17

1

11

01

95

2

46

1

22

3

11

46

16

834

10

480

12

84

51

4

29

53

39

7

50

7

11

546

21

5

flas

k 1

22

82

42

7

41

1

21

5

13

77

12

247

16

28

57

2

12

9

71

3

91

4

15

78

35

4

98

6

14

416

16

264

11

91

64

8

81

4

76

6

44

7

15

678

30

9

Met

abo

lite

Nam

e o

r B

inB

ase

ID

16

817

16

850

16

855

17

068

17

069

17

140

17

425

17

471

17

651

17

830

18

082

18

173

18

226

18

241

20

282

21

704

22

967

25

801

30

962

31

359

41

682

41

689

41

808

131

Sig

nal

In

ten

sity

at

2 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

28

0

93

0

39

7

38

3

27

8

52

7

65

9

90

6

34

0

87

8

12

04

81

5

35

9

17

87

41

1

14

48

44

9

73

1

25

931

61

62

15

65

18

16

35

9

flas

k 5

20

4

73

1

23

6

35

2

20

6

20

1

49

0

36

1

18

0

25

0

66

6

36

4

27

8

10

87

63

1

56

7

45

8

41

1

34

251

38

03

10

33

15

27

16

8

flas

k 4

28

6

74

9

30

7

23

9

31

2

32

6

31

3

21

8

15

8

35

7

65

9

41

5

38

7

14

66

52

4

61

9

35

3

31

7

26

550

43

68

10

36

99

7

62

7

flas

k 3

19

1

78

1

34

0

23

4

35

0

26

3

58

1

43

0

26

2

35

0

53

9

34

7

12

0

13

90

30

8

80

1

14

7

61

6

40

236

47

18

15

74

18

60

15

2

flas

k 2

15

2

75

4

45

4

28

6

39

0

47

4

33

5

46

5

31

9

51

6

86

6

45

2

42

7

16

28

57

0

52

0

60

9

41

2

24

290

43

05

11

53

76

0

26

1

flas

k 1

12

1

57

8

25

2

32

6

20

8

20

1

28

8

28

8

21

7

39

8

64

4

44

1

51

14

31

42

1

57

1

33

9

46

2

24

888

38

99

10

59

81

22

1

Mo

naz

ite

On

ly

flas

k 6

24

7

71

8

30

7

90

8

33

0

14

6

60

2

43

7

28

6

10

8

62

6

34

6

24

6

13

60

19

9

95

3

15

4

44

3

14

036

40

38

27

98

32

03

11

3

flas

k 5

16

4

47

2

25

8

97

4

27

8

21

5

24

5

18

6

15

9

11

3

46

7

28

9

15

6

10

63

14

0

54

3

15

9

36

9

16

551

31

91

23

62

36

84

11

6

flas

k 4

17

3

90

4

30

1

79

24

1

22

5

22

0

14

9

24

0

14

5

43

2

29

5

25

6

13

27

20

2

74

8

45

9

47

0

13

527

37

55

16

13

77

10

0

flas

k 3

12

8

55

8

27

7

16

5

10

8

20

9

52

4

52

4

22

3

10

6

33

0

26

4

12

6

84

9

93

51

2

14

3

45

3

66

29

31

92

21

03

36

04

80

flas

k 2

10

5

83

1

38

5

27

1

33

1

23

7

31

9

31

9

32

6

94

33

3

26

4

17

7

13

92

19

0

51

0

36

2

47

0

10

653

41

89

19

36

34

13

12

2

flas

k 1

37

4

11

32

34

3

61

1

27

7

25

5

67

6

53

4

29

4

17

1

42

8

49

5

31

3

14

89

24

4

10

04

32

6

80

7

85

40

52

94

21

58

10

226

68

Met

abo

lite

Nam

e o

r B

inB

ase

ID

41

811

41

938

42

205

47

170

48

522

49

382

53

724

54

643

87

877

88

911

89

221

97

326

97

332

10

076

8

10

086

9

10

088

0

10

090

8

10

129

9

10

222

3

10

261

6

10

266

1

10

266

2

10

267

9

132

Sig

nal

In

ten

sity

at

2 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

46

2

11

935

81

237

12

380

3

34

897

20

951

32

447

59

398

11

064

11

032

68

09

62

21

63

20

29

28

34

74

23

54

17

54

31

762

69

2

83

9

19

4

11

68

84

4

flas

k 5

43

1

99

04

49

445

49

097

15

525

88

44

18

249

64

531

25

89

33

68

23

14

10

10

26

93

17

04

94

2

18

80

15

41

10

184

23

2

47

3

59

62

8

39

9

flas

k 4

37

2

12

221

53

378

55

395

15

783

93

68

22

913

44

082

62

73

33

82

29

66

13

90

25

52

17

54

26

10

21

15

11

98

23

961

27

4

49

5

99

10

93

51

1

flas

k 3

43

6

14

120

30

136

23

420

50

60

41

75

25

101

19

833

75

79

98

9

15

37

19

2

93

9

18

87

37

34

25

24

55

5

32

394

19

3

38

8

87

88

5

45

6

flas

k 2

43

3

98

45

60

428

69

160

21

926

11

720

21

735

58

245

52

91

55

42

37

90

21

57

38

25

19

58

22

82

20

27

16

00

18

929

35

5

55

5

12

0

58

0

69

8

flas

k 1

31

8

97

48

39

652

40

611

15

965

70

22

20

966

45

057

56

51

30

28

21

32

98

4

28

32

16

16

27

18

17

81

13

47

24

072

36

5

49

1

10

3

80

0

41

6

Mo

naz

ite

On

ly

flas

k 6

55

3

12

832

65

76

49

54

97

7

11

60

29

619

43

08

62

4

31

0

50

6

72

26

1

18

86

11

6

95

3

23

0

17

22

97

60

6

14

6

13

78

44

1

flas

k 5

31

4

13

839

96

05

73

01

17

55

12

78

18

395

90

62

71

0

14

0

35

6

68

49

3

14

77

12

1

13

06

21

9

25

42

13

9

21

0

65

12

90

38

7

flas

k 4

74

4

11

877

19

855

15

669

23

14

37

85

27

539

78

98

31

4

56

7

87

3

24

8

44

8

14

10

14

1

17

56

19

5

16

48

14

5

51

7

96

11

19

63

3

flas

k 3

30

0

99

43

71

47

54

81

54

9

97

6

19

504

31

99

56

0

14

0

49

2

59

91

10

87

12

4

98

2

20

1

16

84

69

22

1

14

9

10

54

31

7

flas

k 2

40

8

10

845

11

406

89

02

10

19

20

07

22

982

40

80

39

5

33

3

48

2

34

2

30

5

13

87

89

13

98

11

1

17

28

10

3

29

7

12

0

10

34

32

8

flas

k 1

42

0

13

522

14

096

10

294

25

39

22

60

34

853

56

14

53

1

30

4

85

6

21

6

50

8

14

65

18

2

17

41

29

3

24

44

17

4

32

7

17

2

14

54

61

2

Met

abo

lite

Nam

e o

r B

inB

ase

ID

10

271

1

10

271

4

10

271

5

10

271

6

10

272

7

10

272

8

10

272

9

10

273

0

10

273

1

10

273

2

10

273

3

10

273

4

10

273

5

10

274

0

10

274

1

10

274

6

10

274

7

10

274

9

10

277

6

10

278

4

10

279

0

10

279

1

10

279

3

133

Sig

nal

In

ten

sity

at

2 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

10

750

43

33

68

1

flas

k 5

31

16

15

91

29

3

flas

k 4

41

39

18

54

44

7

flas

k 3

23

50

74

5

21

2

flas

k 2

46

22

26

18

27

7

flas

k 1

34

90

20

66

34

6

Mo

naz

ite

On

ly

flas

k 6

14

58

22

3

12

2

flas

k 5

21

00

15

9

14

4

flas

k 4

33

94

40

2

11

7

flas

k 3

18

08

93

87

flas

k 2

11

86

18

7

13

7

flas

k 1

27

51

28

6

19

5

Met

abo

lite

Nam

e o

r B

inB

ase

ID

10

280

8

10

280

9

10

282

1

134

Sig

nal

In

ten

sity

at

4 D

ays K

2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

14

62

25

99

24

1

85

2

33

2

16

58

33

86

94

3

32

8

19

2

17

9

37

8

20

99

13

1

32

3

32

0

19

98

12

0

57

8

12

665

18

355

11

5

29

65

flas

k 5

25

51

39

88

93

8

32

2

21

6

10

013

36

03

15

66

22

2

40

5

33

7

20

89

35

57

17

0

95

8

85

4

14

6

20

2

20

81

15

57

18

32

50

5

41

4

flas

k 4

30

47

52

02

17

42

24

47

30

2

11

169

59

70

22

11

48

2

71

8

67

2

24

63

57

66

39

7

19

52

17

22

25

52

48

9

31

62

14

96

21

71

56

1

49

9

flas

k 3

39

28

75

31

10

31

25

83

55

2

97

97

62

45

11

29

50

1

52

8

72

8

17

85

59

01

21

3

14

13

19

39

31

41

44

6

18

12

34

211

75

95

50

3

13

74

flas

k 2

21

88

38

03

21

7

17

30

75

3

38

74

20

36

46

0

44

5

30

0

39

2

89

7

36

94

10

3

41

3

65

9

10

922

10

5

72

8

29

943

95

97

14

7

63

72

flas

k 1

38

10

64

23

16

15

41

0

41

0

14

494

45

43

15

36

38

9

62

1

82

0

22

32

55

95

38

1

15

36

20

87

60

0

32

3

39

22

15

20

50

52

96

5

68

3

Mo

naz

ite

On

ly

flas

k 6

12

58

13

03

12

9

53

0

33

7

19

8

37

97

23

02

53

9

12

3

17

8

27

5

89

0

15

8

28

0

15

5

27

2

82

42

9

27

131

44

68

17

0

60

62

flas

k 5

56

7

78

5

68

27

1

35

0

43

6

11

26

41

1

34

2

43

12

6

12

3

17

20

77

14

2

26

0

72

2

48

34

7

20

347

38

57

82

33

01

flas

k 4

12

68

17

20

80

34

4

60

1

20

68

23

96

35

1

37

1

96

19

7

67

0

17

03

21

5

28

2

57

9

42

56

53

80

7

15

306

2

46

47

15

4

29

751

flas

k 3

12

86

13

70

13

5

35

0

33

5

33

5

33

82

20

62

52

9

90

13

5

13

6

18

73

18

2

25

4

19

8

30

3

59

63

9

30

497

46

78

17

6

68

79

flas

k 2

49

8

13

80

99

21

5

25

2

42

7

22

24

60

2

49

0

67

20

5

10

3

22

24

77

22

3

58

2

15

4

93

50

4

17

195

16

47

91

39

14

flas

k 1

14

75

15

00

50

62

7

49

2

60

2

27

35

42

4

44

5

64

15

9

16

0

23

38

19

0

28

4

37

9

11

11

58

18

8

26

274

12

346

72

58

46

Met

abo

lite

Nam

e o

r B

inB

ase

ID

1-d

eox

yer

yth

rito

l

2-d

eox

yer

yth

rito

l

2-h

yd

roxy

adip

ic a

cid

2-h

yd

roxy

glu

tari

c ac

id

2-i

sop

rop

ylm

alic

aci

d

3,4

-dih

yd

rox

yb

enzo

ic a

cid

3,6

-anh

ydro

-D-g

luco

se

3,6

-anh

ydro

-d-h

exo

se

3-d

eox

yh

exit

ol

3-h

yd

roxy

-3-m

eth

ylg

luta

ric

acid

3-h

yd

roxy

pro

pio

nic

aci

d

4-h

yd

roxy

ben

zoat

e

5-h

yd

roxy

met

hy

l-2

-fu

roic

aci

d

aco

nit

ic a

cid

adip

ic a

cid

alan

ine

alp

ha-

ket

og

luta

rate

azel

aic

acid

ben

zoic

aci

d

bet

a-g

enti

ob

iose

bu

tan

e-2,3

-dio

l

cap

ric

acid

cell

ob

iose

135

Sig

nal

In

ten

sity

at

4 D

ays K

2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

73

2

27

26

37

7

26

4

13

517

65

2

45

86

83

95

23

3

10

03

11

460

33

75

86

77

2

41

046

1

10

143

13

1

32

8

10

68

17

17

33

6

13

8

20

479

flas

k 5

78

8

32

8

13

35

21

27

72

6

11

89

76

9

48

9

13

33

20

8

37

4

42

27

16

2

10

35

85

72

50

65

23

7

10

15

18

9

59

77

33

9

22

5

29

19

flas

k 4

18

20

97

1

18

27

44

77

35

20

23

62

29

68

53

69

11

22

99

4

74

1

28

60

27

2

24

08

12

596

2

22

019

50

5

14

01

83

0

81

35

72

8

38

7

81

64

flas

k 3

30

86

61

71

12

37

50

7

12

296

21

59

11

439

64

02

11

21

31

39

15

698

76

46

21

3

29

20

22

388

2

41

273

43

8

14

25

25

2

63

53

96

9

61

3

15

584

flas

k 2

98

7

37

18

43

0

36

40

19

820

83

9

83

47

36

134

30

8

26

59

29

847

56

35

68

18

49

85

445

6

19

330

19

1

56

8

89

5

20

23

45

1

19

4

11

809

flas

k 1

13

62

63

4

16

03

37

60

12

55

57

85

72

9

71

2

10

77

40

2

58

8

42

12

29

8

14

74

48

720

40

67

27

3

20

25

92

3

13

049

36

0

58

8

21

08

Mo

naz

ite

On

ly

flas

k 6

53

8

15

232

41

3

27

72

67

12

81

5

18

54

21

84

23

6

26

13

15

612

0

44

15

11

6

64

9

37

621

8

37

45

73

17

4

61

8

97

6

33

2

19

7

23

22

flas

k 5

31

2

63

27

24

7

19

58

25

09

42

1

16

36

37

00

10

4

12

59

36

962

26

30

37

40

4

60

323

5

10

226

37

15

8

57

27

47

1

15

4

98

25

21

flas

k 4

56

0

43

11

50

6

12

03

39

99

11

32

43

63

12

374

69

3

95

0

61

24

38

66

10

0

50

2

22

621

9

10

460

9

78

41

2

28

9

14

45

11

9

17

4

39

09

flas

k 3

52

1

17

267

36

7

28

79

57

50

46

1

25

14

14

97

29

9

17

74

15

847

2

62

96

10

8

56

4

55

718

6

10

173

62

23

8

64

81

93

5

31

2

15

2

26

15

flas

k 2

35

2

83

28

32

2

33

33

33

53

28

7

34

03

13

02

22

3

13

74

11

955

4

30

60

67

49

9

62

770

9

71

52

41

28

6

46

43

79

9

20

5

10

9

23

22

flas

k 1

34

9

18

916

45

3

19

20

57

02

33

3

30

18

66

54

20

4

14

51

11

871

3

76

88

87

59

3

41

067

6

10

242

78

25

6

61

43

75

2

34

8

12

1

59

59

Met

abo

lite

Nam

e o

r B

inB

ase

ID

citr

amal

ic a

cid

citr

ic a

cid

deh

ydro

abie

tic

acid

dih

yd

rox

yac

eto

ne

ery

thri

tol

ery

thro

nic

aci

d

fru

cto

se

fum

aric

aci

d

gal

acti

no

l

glu

con

ic a

cid

glu

cose

glu

cose

-1-p

ho

sph

ate

glu

tari

c ac

id

gly

ceri

c ac

id

gly

cero

l

gly

cero

l-3

-gal

acto

sid

e

gly

cero

l-al

ph

a-ph

osp

hat

e

gly

coli

c ac

id

his

tid

ine

hy

dro

xy

lam

ine

iso

citr

ic a

cid

iso

thre

on

ic a

cid

lact

ic a

cid

136

Sig

nal

In

ten

sity

at

4 D

ays K

2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

48

2

11

90

14

05

11

70

87

140

53

6

23

840

70

6

10

7

30

6

55

59

11

4

45

74

20

650

14

88

57

519

49

9

60

24

95

89

52

84

10

865

flas

k 5

29

3

45

1

30

42

61

5

10

33

24

7

39

5

77

20

6

33

7

24

7

13

1

50

3

10

692

94

280

40

48

14

905

6

11

29

27

0

39

3

48

6

33

9

43

74

flas

k 4

36

4

38

4

40

41

58

1

32

57

52

8

69

18

22

11

36

7

78

4

51

5

43

6

29

8

20

537

11

804

4

86

79

16

528

3

19

75

34

8

58

7

68

82

31

2

11

680

flas

k 3

40

49

10

20

39

55

67

75

23

729

10

90

18

279

12

159

42

3

68

9

24

9

20

0

43

4

12

300

69

102

34

17

16

893

4

69

9

37

6

71

0

14

946

58

9

20

839

flas

k 2

10

51

19

72

10

84

22

50

14

969

3

85

4

22

424

20

13

15

9

49

4

76

11

4

11

6

54

91

25

789

17

21

12

023

6

48

4

11

8

66

0

14

768

14

0

37

635

flas

k 1

35

2

83

7

27

17

10

48

11

43

10

15

38

9

33

5

66

7

64

2

53

4

42

2

81

2

19

426

14

992

0

71

64

23

256

0

24

93

32

7

71

2

84

5

59

2

29

07

Mo

naz

ite

On

ly

flas

k 6

84

1

45

4

56

2

14

99

36

371

52

0

12

207

11

493

70

51

0

52

0

70

96

55

66

24

501

18

87

43

3

45

7

11

0

43

45

78

19

7

81

06

flas

k 5

93

6

42

4

10

97

80

5

64

747

38

7

11

175

10

287

41

49

5

24

2

26

13

3

24

50

13

784

77

2

51

5

26

9

28

7

16

2

76

67

99

83

62

flas

k 4

99

0

75

79

16

59

70

61

55

353

29

9

79

59

25

981

20

87

38

8

96

96

10

6

56

82

33

654

25

22

21

1

35

4

12

9

44

73

89

18

8

57

70

flas

k 3

99

3

65

7

21

79

18

41

40

169

95

10

574

12

580

68

52

3

57

4

92

14

0

48

96

22

971

87

2

80

9

50

0

13

8

18

9

27

34

16

2

70

81

flas

k 2

49

4

39

8

31

8

78

3

96

717

21

6

42

91

46

05

60

72

7

33

2

38

83

31

07

17

219

10

55

59

3

25

5

46

7

47

50

47

11

0

16

825

flas

k 1

16

99

58

8

19

13

19

89

61

268

46

9

22

569

71

8

81

19

0

73

3

72

12

1

46

16

21

275

13

44

23

9

48

0

10

7

14

5

60

49

14

5

64

52

Met

abo

lite

Nam

e o

r B

inB

ase

ID

lact

ito

l

lact

ulo

se

lau

ric

acid

lev

og

luco

san

lyx

ito

l

lyx

ose

mal

ic a

cid

mal

tose

mal

totr

iose

my

o-i

no

sito

l

nic

oti

nic

aci

d

ole

ic a

cid

ox

alic

aci

d

pal

mit

ic a

cid

p-c

reso

l

pel

arg

on

ic a

cid

ph

osp

hat

e

pro

pan

e-1

,3-d

iol

pu

tres

cin

e

py

ruv

ic a

cid

rib

ito

l

rib

on

ic a

cid

rib

ose

137

Sig

nal

In

ten

sity

at

4 D

ays K

2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

50

0

82

74

50

7

71

272

9

45

627

15

876

7

85

29

160

9

90

1

40

1

36

3

27

43

20

48

44

57

45

16

2

18

33

96

3

26

6

16

54

10

14

69

6

34

348

flas

k 5

31

77

29

50

14

95

19

46

64

119

16

55

11

0

15

675

26

15

8

42

2

63

2

84

2

51

8

21

8

31

81

25

4

24

47

18

23

57

8

50

85

40

89

22

25

20

0

flas

k 4

17

45

28

11

17

38

53

76

10

854

4

64

313

32

5

11

901

55

40

0

51

2

15

91

30

64

55

4

26

9

61

24

43

6

22

400

24

96

26

11

71

11

53

53

29

91

28

2

flas

k 3

39

81

14

543

16

81

17

26

72

057

86

811

24

9

96

894

4

20

90

85

5

71

2

31

61

47

03

36

0

12

893

56

4

45

38

41

10

87

3

50

67

29

18

28

01

39

589

flas

k 2

14

90

13

877

79

3

21

27

30

863

10

031

4

11

3

35

556

9

17

65

50

3

23

0

38

24

50

50

10

5

97

82

27

8

31

14

30

15

28

9

20

81

13

72

54

2

47

930

flas

k 1

21

58

76

6

23

11

14

78

10

315

5

53

8

33

5

12

946

29

31

1

54

2

19

92

26

83

62

5

45

1

38

55

34

0

28

90

23

27

17

60

86

34

62

49

39

63

89

9

Mo

naz

ite

On

ly

flas

k 6

93

52

18

31

8

25

462

6

20

207

28

552

21

94

126

4

20

31

25

2

15

4

85

4

10

86

71

35

34

23

7

22

75

13

86

58

1

17

77

10

48

56

8

71

160

6

flas

k 5

54

44

61

20

1

49

023

1

99

76

18

143

11

2

63

047

7

10

10

98

21

1

50

4

10

61

25

14

46

14

0

11

70

12

70

14

3

11

12

50

5

34

1

36

639

3

flas

k 4

80

87

643

31

8

18

872

9

30

350

12

668

17

6

92

241

6

87

8

13

7

23

5

40

4

53

12

51

11

56

24

2

93

8

66

6

77

2

21

66

14

53

70

3

27

835

flas

k 3

65

48

80

23

0

24

273

4

20

540

26

130

10

6

75

435

5

18

33

29

6

20

5

66

1

16

30

68

24

47

17

3

19

62

85

4

33

8

19

50

11

38

42

5

53

480

6

flas

k 2

38

40

69

26

2

42

780

0

11

542

88

83

12

7

56

757

3

13

07

12

3

91

44

8

84

0

50

99

6

71

12

431

15

97

16

8

12

70

63

5

48

7

52

249

2

flas

k 1

93

57

51

24

5

38

022

4

21

294

44

667

18

4

74

801

5

17

04

25

7

23

3

14

02

17

58

44

21

81

20

9

19

12

10

16

40

2

16

80

10

03

55

3

28

550

3

Met

abo

lite

Nam

e o

r B

inB

ase

ID

rib

ose

-5-p

ho

sph

ate

s(-)

-wil

lard

iin

e

shik

imic

aci

d

sorb

ito

l

stea

ric

acid

succ

inic

aci

d

sucr

ose

sulf

uri

c ac

id

tag

ato

se

thre

ito

l

tran

s-4

-hyd

rox

y-L

-pro

lin

e

tyro

sol

UD

P-g

lucu

ron

ic a

cid

ura

cil

xy

lito

l

xy

lon

ola

cto

ne

xy

lose

xy

lulo

se

39

47

62

91

99

138

Sig

nal

In

ten

sity

at

4 D

ays K

2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

31

4

23

74

21

8

10

62

11

06

19

7

74

6

21

3

53

6

10

08

89

39

9

41

3

19

14

68

1

27

76

43

6

33

1

10

14

38

9

12

5

75

5

15

7

flas

k 5

72

8

24

39

13

53

20

81

10

04

39

88

14

12

75

7

24

7

18

1

32

2

28

9

14

93

29

42

21

33

26

65

46

2

53

8

38

34

17

82

39

7

22

16

25

8

flas

k 4

13

19

15

390

15

45

95

1

22

67

12

17

29

85

26

77

52

8

63

6

59

0

37

4

26

11

68

91

35

49

41

92

27

68

54

4

49

43

24

80

51

8

29

91

24

6

flas

k 3

92

2

70

5

99

4

19

08

15

19

32

45

32

47

14

64

10

90

11

74

27

2

58

9

13

62

49

61

19

24

39

00

29

51

73

8

27

63

15

15

34

6

17

32

35

2

flas

k 2

34

5

85

2

43

9

84

8

65

0

82

9

11

23

24

8

85

4

10

34

19

9

69

1

68

4

25

10

10

57

43

31

75

2

52

6

10

23

56

0

15

9

71

1

21

6

flas

k 1

17

48

44

35

13

79

47

66

46

92

15

69

37

77

16

44

60

9

19

9

36

4

89

0

40

04

61

08

33

92

44

43

26

46

61

3

57

15

33

83

36

0

33

58

13

7

Mo

naz

ite

On

ly

flas

k 6

29

8

94

0

63

6

21

0

49

9

17

98

68

9

50

0

16

8

23

864

24

0

10

35

38

5

16

01

72

5

20

09

55

2

19

64

66

2

31

5

18

0

61

1

14

7

flas

k 5

13

7

11

1

13

6

11

9

28

5

60

7

35

6

33

1

10

8

18

093

12

0

68

9

27

4

10

37

51

3

21

32

40

2

10

85

34

4

23

4

26

28

6

85

flas

k 4

22

1

65

4

66

5

50

2

44

1

40

5

10

00

68

9

33

7

11

67

11

4

30

5

49

5

21

34

90

0

28

69

43

2

27

0

15

23

37

0

19

9

80

4

23

6

flas

k 3

25

5

22

8

50

5

12

2

63

0

31

8

72

4

49

4

40

9

12

726

15

2

74

0

32

1

18

61

89

3

21

00

41

5

13

82

62

3

34

8

17

7

52

5

17

8

flas

k 2

18

3

11

0

30

4

35

8

27

1

98

9

40

8

52

2

21

6

22

044

10

2

34

7

36

2

11

62

51

0

27

11

48

5

13

93

66

8

40

6

60

50

1

52

flas

k 1

25

8

17

84

30

0

14

7

44

2

53

4

10

00

59

7

46

9

10

635

12

8

73

4

23

2

17

74

81

7

24

09

53

0

11

25

93

9

45

9

74

55

5

10

8

Met

abo

lite

Nam

e o

r B

inB

ase

ID

13

7

16

8

25

7

65

7

80

9

89

2

10

64

11

73

16

73

16

81

16

90

17

15

18

70

18

72

18

75

18

78

19

13

20

44

20

61

20

81

20

95

20

97

28

21

139

Sig

nal

In

ten

sity

at

4 D

ays K

2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

43

45

87

1

14

4

53

8

10

886

87

4

31

73

64

6

21

83

63

2

21

91

61

3

13

50

13

2

12

5

10

06

43

0

18

1

52

07

18

5

84

2

28

35

22

3

flas

k 5

16

836

35

36

26

8

23

5

33

905

46

8

23

3

61

1

26

4

13

24

28

1

14

49

40

3

76

9

10

56

31

33

63

4

35

1

94

76

34

9

36

74

11

23

10

00

flas

k 4

24

095

71

08

57

1

53

8

52

445

13

58

60

7

12

86

65

6

54

09

12

37

20

14

39

0

11

32

94

1

44

22

98

7

11

12

18

942

73

8

69

60

72

10

10

86

flas

k 3

14

469

36

64

71

2

13

19

30

945

13

474

30

59

17

93

86

70

12

04

10

008

18

24

11

86

87

5

92

2

29

12

18

67

62

2

12

940

73

2

27

83

78

42

10

74

flas

k 2

54

73

11

87

20

6

87

8

13

422

27

95

35

95

75

5

47

22

53

9

42

81

88

4

18

19

18

0

18

1

13

88

49

8

20

6

49

02

25

0

19

04

67

13

29

0

flas

k 1

30

197

65

80

10

93

43

9

65

077

11

31

48

5

91

1

19

9

27

17

41

8

36

77

56

7

13

83

43

9

52

26

18

35

15

86

18

979

67

1

45

39

47

6

25

38

Mo

naz

ite

On

ly

flas

k 6

54

80

10

81

37

5

10

6

11

585

86

37

17

809

10

67

33

05

12

43

15

05

65

7

37

6

16

8

10

6

10

61

23

0

29

6

44

48

59

7

17

08

93

50

35

7

flas

k 5

26

05

46

4

17

5

13

2

52

14

77

28

73

31

24

6

28

67

10

52

11

75

26

0

51

1

92

26

70

9

16

0

82

26

88

21

7

73

7

67

60

14

0

flas

k 4

60

22

11

21

45

8

26

42

13

045

31

314

89

48

87

7

23

856

55

5

26

636

92

4

54

95

24

8

34

6

11

50

32

2

32

3

42

65

23

7

15

84

21

721

36

0

flas

k 3

52

26

10

82

23

4

37

10

872

10

565

14

629

10

79

42

79

39

9

14

23

39

9

30

5

22

6

11

5

11

83

28

3

35

0

41

15

36

5

18

61

93

68

30

5

flas

k 2

34

98

10

44

19

0

14

1

71

62

61

60

75

14

57

6

22

69

10

90

78

8

31

1

45

4

13

2

98

64

2

16

8

19

4

32

01

40

2

87

0

59

07

19

4

flas

k 1

46

22

95

7

23

5

18

8

10

071

67

53

13

318

79

7

38

31

92

1

11

96

46

7

54

1

22

0

89

10

82

21

2

25

1

38

59

28

9

60

8

78

54

30

1

Met

abo

lite

Nam

e o

r B

inB

ase

ID

29

44

30

83

31

73

32

47

34

42

37

81

45

41

45

43

47

13

47

32

47

95

47

97

48

19

49

37

49

76

53

46

55

76

61

04

63

30

66

46

93

20

14

694

16

561

140

Sig

nal

In

ten

sity

at

4 D

ays K

2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

80

1

11

29

20

998

58

5

10

51

93

3

20

84

49

3

80

63

77

63

8

67

3

14

9

18

3

91

1

13

394

18

13

45

3

78

2

59

6

19

6

98

86

27

1

flas

k 5

11

64

31

54

37

6

17

84

32

0

55

7

41

4

49

1

22

0

25

32

26

09

12

20

93

1

17

7

72

1

34

5

17

7

12

74

78

2

16

57

18

1

33

7

62

4

flas

k 4

15

81

83

94

44

3

31

42

44

9

52

68

49

9

71

8

40

7

12

176

36

97

24

08

19

42

28

5

83

3

61

7

39

4

20

80

26

57

26

93

21

3

83

54

96

1

flas

k 3

22

66

32

10

37

44

14

33

62

06

67

44

96

46

31

04

28

2

27

835

18

65

23

56

17

28

30

5

18

53

54

449

14

3

17

42

23

07

20

37

22

9

37

388

60

7

flas

k 2

96

6

12

11

19

159

91

7

24

46

12

63

50

15

70

3

13

1

11

877

77

2

11

45

10

16

21

2

13

22

27

425

47

8

87

1

16

48

94

5

19

5

16

011

38

1

flas

k 1

15

86

92

43

36

0

44

35

56

3

57

1

68

3

72

9

66

3

27

12

38

55

18

63

19

46

53

8

10

10

61

7

40

6

16

03

96

9

31

60

31

9

11

80

71

2

Mo

naz

ite

On

ly

flas

k 6

14

41

94

5

64

98

29

1

29

8

12

418

45

81

89

0

89

20

33

93

6

54

9

31

7

70

2

87

09

53

792

34

0

43

9

21

39

65

4

31

9

24

028

45

2

flas

k 5

80

7

43

3

94

40

34

6

36

88

86

54

42

41

23

6

61

29

92

48

9

47

8

26

4

24

6

47

22

33

008

46

5

39

1

53

1

42

3

18

7

93

31

16

5

flas

k 4

37

13

10

67

30

40

8

14

567

40

26

36

643

23

35

17

3

68

966

79

3

58

4

35

5

26

3

48

75

14

298

7

19

8

62

8

10

431

64

2

85

64

12

25

6

flas

k 3

13

80

97

5

58

75

27

6

56

16

12

114

50

83

53

5

12

2

26

53

88

9

57

3

28

7

58

1

45

92

51

038

15

32

74

4

17

31

59

7

30

0

22

082

21

8

flas

k 2

99

9

36

3

14

11

14

9

39

10

78

13

30

56

21

1

12

5

16

95

66

8

53

9

36

5

37

8

61

43

36

337

14

8

42

3

65

6

38

9

26

0

14

119

23

7

flas

k 1

13

70

91

1

13

195

29

1

47

85

10

102

46

12

93

2

97

32

85

66

3

57

5

39

3

10

57

37

16

41

398

12

58

86

3

12

73

41

5

20

3

18

861

17

6

Met

abo

lite

Nam

e o

r B

inB

ase

ID

16

817

16

850

16

855

17

068

17

069

17

140

17

425

17

471

17

651

17

830

18

082

18

173

18

226

18

241

20

282

21

704

22

967

25

801

30

962

31

359

41

682

41

689

41

808

141

Sig

nal

In

ten

sity

at

4 D

ays K

2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

12

3

63

6

15

0

19

7

33

4

32

0

23

6

35

4

21

0

81

1

45

78

38

1

13

39

10

19

44

4

95

41

97

4

38

0

64

67

37

80

52

9

77

2

48

63

flas

k 5

48

9

19

46

10

64

34

7

10

46

11

06

12

85

16

78

68

6

16

53

30

71

20

06

13

43

24

70

37

6

29

5

18

3

16

96

22

2

14

406

23

35

83

39

64

9

flas

k 4

74

8

25

98

11

05

10

99

87

3

12

23

18

86

24

73

85

9

27

00

62

81

33

65

24

80

45

76

16

24

11

369

30

8

25

16

47

2

19

687

22

17

53

73

79

4

flas

k 3

30

9

20

80

79

7

81

2

10

24

55

0

32

5

65

2

18

67

35

54

87

42

22

62

21

90

47

03

17

30

12

369

12

51

14

23

19

18

12

821

27

24

33

82

13

60

flas

k 2

15

8

61

5

26

1

14

3

22

0

39

5

26

3

39

1

18

8

90

5

49

28

66

7

47

3

16

28

11

83

32

213

24

94

60

9

25

11

43

38

12

06

36

7

98

42

flas

k 1

67

1

55

12

66

3

66

7

14

91

17

89

12

51

16

15

12

30

70

40

64

31

37

97

42

24

60

13

40

6

57

1

49

3

30

69

65

0

27

393

24

81

43

5

89

4

Mo

naz

ite

On

ly

flas

k 6

19

0

78

2

28

8

29

2

16

4

25

2

30

0

43

2

21

0

16

6

17

66

38

7

34

2

10

33

19

7

16

86

16

17

62

2

64

41

37

07

14

89

34

79

40

4

flas

k 5

12

9

37

9

16

5

15

0

17

7

10

1

22

0

13

9

10

2

27

6

11

59

19

3

14

0

65

7

17

1

29

67

16

13

26

9

29

11

17

89

68

4

37

62

0

flas

k 4

14

2

74

4

21

9

16

8

29

1

24

4

23

1

47

3

24

9

33

6

19

81

61

5

25

6

99

1

29

0

10

166

56

4

64

1

65

4

45

24

61

3

11

403

21

42

flas

k 3

14

2

69

2

28

3

26

5

17

1

22

5

16

4

36

1

24

8

19

6

13

86

38

1

29

9

94

6

37

0

18

49

20

67

50

0

62

06

39

66

10

27

78

41

26

8

flas

k 2

11

3

49

2

11

6

16

0

18

6

20

6

21

0

33

1

12

3

46

0

59

6

26

9

45

9

87

0

11

0

71

3

34

80

35

0

38

24

25

50

84

6

51

24

16

5

flas

k 1

14

3

48

5

24

7

31

4

18

1

29

4

14

3

30

0

20

3

19

1

19

02

42

8

11

3

85

6

29

2

37

63

16

52

33

5

92

95

33

61

85

0

50

22

99

0

Met

abo

lite

Nam

e o

r B

inB

ase

ID

41

811

41

938

42

205

47

170

48

522

49

382

53

724

54

643

87

877

88

911

89

221

97

326

97

332

10

076

8

10

086

9

10

088

0

10

090

8

10

129

9

10

222

3

10

261

6

10

266

1

10

266

2

10

267

9

142

Sig

nal

In

ten

sity

at

4 D

ays K

2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

35

3

12

10

36

70

43

12

39

027

16

63

18

739

70

090

11

659

71

78

43

5

61

6

68

49

56

0

20

13

15

32

21

22

74

36

23

51

10

26

12

1

16

72

60

5

flas

k 5

17

30

43

60

46

4

80

3

22

9

41

6

79

431

37

8

20

6

25

6

45

9

17

7

22

7

88

4

16

0

22

5

23

9

43

49

17

7

33

89

30

1

97

1

20

6

flas

k 4

79

0

88

04

56

4

44

6

11

71

39

4

10

344

1

11

38

28

406

28

2

31

8

41

0

55

4

89

2

26

08

33

1

28

2

35

021

32

5

45

92

57

1

32

21

36

4

flas

k 3

95

5

15

850

33

49

91

43

65

569

32

39

62

352

19

533

26

581

67

21

12

66

15

75

11

693

23

76

27

28

13

27

54

0

20

058

51

5

51

82

43

6

20

45

98

8

flas

k 2

46

6

56

68

43

19

78

90

15

191

1

30

02

23

459

35

282

13

822

14

220

90

6

16

61

26

242

11

90

15

07

53

02

91

6

45

66

21

91

21

94

16

4

22

29

11

22

flas

k 1

16

32

33

17

53

4

86

5

37

3

56

7

13

276

0

99

8

35

2

47

6

40

2

32

7

32

7

11

22

34

4

35

6

49

3

65

06

40

2

58

43

53

0

65

4

44

3

Mo

naz

ite

On

ly

flas

k 6

12

65

12

204

35

960

38

909

46

547

65

55

24

501

92

83

11

681

41

08

19

98

93

8

72

36

12

46

12

78

21

96

18

1

63

79

89

5

16

83

13

8

82

6

10

24

flas

k 5

63

0

50

31

23

097

34

923

39

567

60

91

13

784

16

129

97

1

10

987

20

64

15

51

64

39

74

9

27

6

79

3

43

2

13

72

12

02

45

8

37

2

69

1

45

0

flas

k 4

27

1

97

0

12

58

28

707

48

919

40

83

28

362

57

74

27

3

73

90

62

1

26

21

85

55

14

00

11

3

17

03

16

8

17

20

72

6

12

80

48

9

50

9

29

3

flas

k 3

14

14

10

084

46

215

53

430

33

476

91

64

20

783

12

409

11

080

93

44

29

32

17

63

63

32

13

46

23

26

17

78

37

0

87

07

75

5

16

39

30

1

39

7

10

84

flas

k 2

70

7

77

40

23

472

24

369

97

38

42

92

13

110

78

80

41

1

47

18

13

36

54

0

17

53

68

6

17

9

97

9

20

2

14

42

49

3

56

1

27

7

52

6

60

2

flas

k 1

16

52

81

55

40

512

51

657

64

781

89

22

19

533

34

455

21

928

10

696

31

09

22

06

11

484

11

02

55

36

14

91

93

9

15

584

16

28

14

99

42

6

62

0

97

9

Met

abo

lite

Nam

e o

r B

inB

ase

ID

10

271

1

10

271

4

10

271

5

10

271

6

10

272

7

10

272

8

10

272

9

10

273

0

10

273

1

10

273

2

10

273

3

10

273

4

10

273

5

10

274

0

10

274

1

10

274

6

10

274

7

10

274

9

10

277

6

10

278

4

10

279

0

10

279

1

10

279

3

143

Sig

nal

In

ten

sity

at

4 D

ays K

2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

25

33

17

221

10

73

flas

k 5

92

3

37

6

20

6

flas

k 4

71

8

44

3

79

0

flas

k 3

10

774

47

50

48

12

flas

k 2

19

16

16

027

39

46

flas

k 1

10

31

36

0

35

6

Mo

naz

ite

On

ly

flas

k 6

84

54

53

01

91

7

flas

k 5

49

37

76

75

80

6

flas

k 4

16

515

54

74

27

53

flas

k 3

78

60

46

58

69

9

flas

k 2

52

04

18

07

23

6

flas

k 1

62

78

10

255

13

73

Met

abo

lite

Nam

e o

r B

inB

ase

ID

10

280

8

10

280

9

10

282

1

144

Sig

nal

In

ten

sity

at

6 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

45

02

67

59

77

8

30

8

33

2

35

88

13

34

36

9

45

7

87

3

48

1

52

5

33

8

37

9

13

03

12

05

36

2

36

6

36

11

17

23

51

82

47

7

53

5

flas

k 5

32

33

26

55

28

6

22

1

23

2

66

01

22

37

36

8

16

1

21

1

31

3

10

32

24

4

26

9

96

1

15

56

16

7

10

7

18

57

12

95

96

7

20

1

32

0

flas

k 4

43

38

36

23

55

1

34

0

37

9

72

81

26

47

55

4

30

8

55

1

69

1

83

6

46

1

53

5

19

33

67

47

44

9

28

5

40

45

12

10

13

12

40

6

57

8

flas

k 3

29

35

27

30

30

0

32

3

22

2

37

87

17

67

35

9

21

2

19

1

50

9

43

1

40

8

33

8

88

9

19

76

19

9

32

3

24

49

14

60

18

62

18

9

42

4

flas

k 2

45

03

34

40

43

8

27

8

18

7

68

69

29

34

61

5

45

7

76

3

35

5

75

2

31

4

27

2

16

78

18

96

21

3

28

3

23

97

25

29

21

61

51

1

27

2

flas

k 1

78

77

53

19

79

3

77

5

10

73

13

905

51

14

13

16

42

9

14

28

17

08

21

09

11

76

75

6

38

26

74

57

94

3

13

25

81

57

45

92

52

54

23

89

23

70

Mo

naz

ite

On

ly

flas

k 6

25

11

23

79

93

49

5

49

6

47

3

51

37

28

6

40

7

10

5

14

9

16

1

29

4

29

8

38

0

30

4

50

4

10

7

55

5

50

808

67

89

14

8

11

080

flas

k 5

18

79

24

80

24

5

17

45

15

72

28

23

13

10

93

8

19

9

30

3

29

9

89

9

17

53

57

9

32

1

33

9

78

36

57

97

5

15

61

17

265

16

4

30

1

flas

k 4

35

01

41

37

58

5

74

15

7

89

53

36

36

69

2

25

6

63

0

31

9

27

16

20

0

22

3

75

3

13

11

47

2

12

4

17

20

87

7

31

97

48

6

24

0

flas

k 3

20

78

19

84

14

1

60

7

64

2

76

1

12

04

90

4

56

5

13

0

27

7

27

0

91

5

40

2

39

0

43

6

85

0

97

71

0

14

447

87

46

15

3

48

14

flas

k 2

19

57

25

74

11

4

72

7

46

6

98

9

28

76

53

0

82

9

20

0

27

6

22

6

29

67

25

8

38

4

10

06

10

38

60

74

1

24

061

10

072

16

6

49

55

flas

k 1

37

98

27

84

10

9

89

5

84

4

80

4

29

88

88

1

72

8

22

9

22

4

17

7

14

36

74

7

24

7

11

04

22

65

87

59

5

61

019

69

238

19

8

10

692

Met

abo

lite

Nam

e o

r B

inB

ase

ID

1-d

eox

yer

yth

rito

l

2-d

eox

yer

yth

rito

l

2-h

yd

roxy

adip

ic a

cid

2-h

yd

roxy

glu

tari

c ac

id

2-i

sop

rop

ylm

alic

aci

d

3,4

-dih

yd

rox

yb

enzo

ic a

cid

3,6

-anh

ydro

-D-g

luco

se

3,6

-anh

ydro

-d-h

exo

se

3-d

eox

yh

exit

ol

3-h

yd

roxy

-3-m

eth

ylg

luta

ric

acid

3-h

yd

roxy

pro

pio

nic

aci

d

4-h

yd

roxy

ben

zoat

e

5-h

yd

roxy

met

hy

l-2

-fu

roic

aci

d

aco

nit

ic a

cid

adip

ic a

cid

alan

ine

alp

ha-

ket

og

luta

rate

azel

aic

acid

ben

zoic

aci

d

bet

a-g

enti

ob

iose

bu

tan

e-2,3

-dio

l

cap

ric

acid

cell

ob

iose

145

Sig

nal

In

ten

sity

at

6 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

28

8

36

2

13

03

16

08

36

2

49

28

75

5

44

7

18

45

45

0

47

4

26

16

27

4

68

0

49

168

75

14

31

8

11

91

39

3

10

983

34

9

37

2

52

80

flas

k 5

21

5

32

4

14

04

17

19

51

4

29

77

37

6

44

1

20

99

25

1

28

6

43

51

18

2

61

6

46

860

59

09

18

2

10

07

14

6

57

84

26

7

31

5

27

93

flas

k 4

42

6

54

7

27

49

21

32

75

7

22

49

59

0

46

9

25

18

23

8

64

0

33

34

37

9

11

32

58

642

19

25

50

8

23

00

80

4

13

216

42

9

48

0

69

03

flas

k 3

24

3

30

5

11

06

16

02

26

9

47

30

46

0

40

6

27

12

23

5

51

4

41

15

16

0

11

39

58

910

49

78

30

7

86

0

44

2

91

16

22

7

46

0

18

60

flas

k 2

40

5

22

8

13

20

19

95

12

11

26

98

25

7

57

3

28

20

29

3

82

8

48

74

23

9

14

58

73

282

80

52

22

8

84

3

27

8

78

01

36

6

31

1

58

91

flas

k 1

11

57

78

4

40

97

55

15

17

36

61

31

20

44

24

08

55

06

91

5

14

65

11

554

13

16

30

98

50

946

23

406

61

6

29

68

65

3

29

845

79

3

66

3

11

236

Mo

naz

ite

On

ly

flas

k 6

50

4

36

079

40

1

13

51

18

592

11

76

11

03

27

08

34

6

21

83

29

417

55

56

71

59

0

21

778

4

12

798

46

35

6

54

8

75

7

68

2

14

5

12

52

flas

k 5

67

9

10

463

55

5

81

1

69

91

71

2

30

47

41

954

10

16

11

60

60

5

58

1

85

10

71

55

754

5

20

601

51

79

6

15

7

14

07

47

1

14

8

78

91

flas

k 4

30

8

37

6

73

3

12

99

42

9

13

53

29

4

63

9

24

37

13

9

49

0

73

3

13

7

60

0

58

200

86

75

13

7

11

06

46

8

32

96

16

7

10

6

21

41

flas

k 3

60

9

35

369

44

5

75

5

86

85

30

7

15

62

59

74

55

8

15

29

20

04

20

65

81

73

8

23

411

3

63

963

66

36

7

30

2

14

50

50

9

19

9

71

53

flas

k 2

42

3

17

148

31

6

28

21

10

054

78

8

55

65

13

37

37

7

18

93

37

80

72

78

80

12

09

11

791

18

22

277

97

65

6

66

9

85

9

11

6

30

1

54

66

flas

k 1

44

2

47

533

41

5

52

7

11

301

10

40

15

71

11

096

64

9

14

13

56

66

26

94

89

79

9

17

974

2

46

485

40

23

7

36

1

14

63

79

6

10

4

34

40

Met

abo

lite

Nam

e o

r B

inB

ase

ID

citr

amal

ic a

cid

citr

ic a

cid

deh

ydro

abie

tic

acid

dih

yd

rox

yac

eto

ne

ery

thri

tol

ery

thro

nic

aci

d

fru

cto

se

fum

aric

aci

d

gal

acti

no

l

glu

con

ic a

cid

glu

cose

glu

cose

-1-p

ho

sph

ate

glu

tari

c ac

id

gly

ceri

c ac

id

gly

cero

l

gly

cero

l-3

-gal

acto

sid

e

gly

cero

l-al

ph

a-ph

osp

hat

e

gly

coli

c ac

id

his

tid

ine

hy

dro

xy

lam

ine

iso

citr

ic a

cid

iso

thre

on

ic a

cid

lact

ic a

cid

146

Sig

nal

In

ten

sity

at

6 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

67

7

63

6

31

68

46

0

83

3

79

9

50

8

45

4

28

8

34

2

31

5

14

9

47

7

22

139

12

509

4

10

817

25

281

2

21

73

24

7

44

32

8

41

3

39

70

flas

k 5

23

0

24

0

21

33

35

9

31

1

56

8

35

1

42

6

59

7

37

8

43

0

28

6

42

2

14

072

74

497

43

70

22

203

7

14

62

20

3

15

9

26

1

26

9

35

51

flas

k 4

39

4

76

1

36

31

83

9

92

9

48

8

37

9

57

4

36

3

41

8

41

0

28

9

50

0

19

674

13

330

0

95

69

31

716

4

32

95

30

8

59

0

92

9

76

9

90

23

flas

k 3

35

6

22

2

12

40

40

3

95

1

60

2

25

1

80

1

57

1

47

3

26

3

65

50

9

14

877

90

526

55

80

28

467

4

12

48

29

4

39

0

29

4

25

3

65

90

flas

k 2

45

1

11

7

49

26

71

3

12

45

42

8

38

9

79

4

43

8

39

4

35

3

28

8

42

0

14

442

94

023

71

47

30

977

1

13

88

26

5

36

8

10

35

54

0

81

72

flas

k 1

15

49

29

30

52

73

23

05

13

81

24

36

12

51

40

78

23

80

20

62

14

84

13

81

13

53

50

376

37

945

6

17

237

26

658

0

55

06

10

64

11

20

76

5

78

4

99

86

Mo

naz

ite

On

ly

flas

k 6

33

16

88

9

43

4

23

02

41

673

67

6

15

801

11

514

20

7

17

5

81

5

10

3

12

5

44

74

19

760

11

14

47

4

32

6

17

2

44

29

88

12

2

68

51

flas

k 5

12

0

56

2

36

66

18

1

16

969

24

4

32

494

53

4

80

33

9

91

11

4

10

8

49

50

28

061

36

66

86

6

44

9

11

2

57

81

01

13

8

17

553

flas

k 4

14

6

59

3

10

90

30

8

83

7

27

7

33

9

44

8

17

5

45

2

34

4

58

29

7

11

294

65

868

35

91

23

11

11

16

0

18

7

56

9

34

2

28

58

flas

k 3

13

8

21

87

19

8

26

08

31

549

35

9

28

367

34

65

19

5

18

3

78

9

68

18

8

51

52

27

508

87

8

34

0

44

1

86

16

9

28

74

16

9

62

99

flas

k 2

93

8

63

2

26

90

27

75

87

727

34

01

14

639

36

00

81

30

9

80

7

11

6

60

5

29

06

22

701

22

41

52

6

35

0

10

79

85

7

11

402

51

8

37

756

flas

k 1

37

64

21

47

10

03

39

75

41

357

42

0

33

499

97

53

25

5

12

3

16

72

72

18

7

53

54

21

294

13

74

12

3

48

1

14

0

29

5

39

15

15

3

63

17

Met

abo

lite

Nam

e o

r B

inB

ase

ID

lact

ito

l

lact

ulo

se

lau

ric

acid

lev

og

luco

san

lyx

ito

l

lyx

ose

mal

ic a

cid

mal

tose

mal

totr

iose

my

o-i

no

sito

l

nic

oti

nic

aci

d

ole

ic a

cid

ox

alic

aci

d

pal

mit

ic a

cid

p-c

reso

l

pel

arg

on

ic a

cid

ph

osp

hat

e

pro

pan

e-1

,3-d

iol

pu

tres

cin

e

py

ruv

ic a

cid

rib

ito

l

rib

on

ic a

cid

rib

ose

147

Sig

nal

In

ten

sity

at

6 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

45

4

58

62

19

02

95

1

12

865

5

98

8

21

3

13

011

64

26

1

25

7

13

94

46

4

44

7

21

0

16

14

27

8

19

87

59

6

20

31

71

04

51

78

43

22

67

4

flas

k 5

56

8

10

72

17

69

55

4

11

780

8

10

01

24

4

14

408

22

18

2

22

1

17

40

15

0

40

1

21

1

82

9

30

3

17

92

51

4

89

8

55

98

37

18

18

15

17

1

flas

k 4

10

74

19

1

22

06

14

52

10

728

2

76

9

94

12

337

88

27

7

38

7

12

38

44

1

81

2

28

9

14

13

26

5

21

665

39

8

13

94

92

30

60

36

39

67

54

7

flas

k 3

95

3

57

94

17

18

98

2

77

744

55

3

24

5

13

770

62

22

2

20

9

78

3

32

0

64

8

22

2

14

16

26

1

21

57

62

5

15

09

67

50

47

63

19

09

34

6

flas

k 2

11

60

81

53

24

23

11

67

77

034

13

67

80

13

041

73

19

2

36

3

91

8

78

1

54

0

10

4

27

26

34

0

26

492

60

2

89

5

55

90

46

77

20

91

30

9

flas

k 1

12

79

11

442

47

50

85

9

26

263

3

79

05

42

9

68

577

3

12

88

12

51

41

62

13

53

13

81

88

7

16

43

12

88

63

27

98

0

33

78

20

093

14

969

10

126

17

54

Mo

naz

ite

On

ly

flas

k 6

67

31

12

20

3

32

274

8

22

216

42

627

10

4

10

621

75

17

49

45

1

21

9

21

93

51

74

51

39

96

15

9

21

71

10

86

27

6

17

16

95

9

60

1

16

328

6

flas

k 5

82

29

97

44

9

13

29

27

583

10

364

7

39

10

358

09

18

0

27

3

19

9

13

16

17

2

68

16

47

11

2

92

05

15

19

20

6

20

35

11

59

68

3

25

8

flas

k 4

17

5

10

03

89

5

15

27

86

240

13

09

18

9

16

939

05

14

8

31

2

15

72

20

5

46

3

11

9

86

1

18

7

20

730

52

6

11

78

42

13

33

28

16

03

18

6

flas

k 3

74

39

687

42

1

12

60

42

950

64

089

62

13

206

95

80

5

23

4

34

5

12

33

15

75

59

17

87

19

0

16

00

29

9

50

0

18

02

11

16

52

4

10

025

flas

k 2

91

94

18

79

7

37

764

5

12

281

34

482

20

5

36

079

27

51

28

6

19

0

23

50

24

96

10

6

14

17

64

7

33

50

24

89

25

0

15

85

84

7

16

44

33

85

flas

k 1

51

30

808

35

1

14

93

35

214

99

002

12

3

12

034

11

10

71

23

9

36

7

30

02

50

34

60

18

44

26

6

14

85

67

5

29

0

15

23

97

2

49

0

26

556

Met

abo

lite

Nam

e o

r B

inB

ase

ID

rib

ose

-5-p

ho

sph

ate

s(-)

-wil

lard

iin

e

shik

imic

aci

d

sorb

ito

l

stea

ric

acid

succ

inic

aci

d

sucr

ose

sulf

uri

c ac

id

tag

ato

se

thre

ito

l

tran

s-4

-hyd

rox

y-L

-pro

lin

e

tyro

sol

UD

P-g

lucu

ron

ic a

cid

ura

cil

xy

lito

l

xy

lon

ola

cto

ne

xy

lose

xy

lulo

se

39

47

62

91

99

148

Sig

nal

In

ten

sity

at

6 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

16

08

77

5

13

37

43

42

16

86

95

4

32

76

16

31

39

3

27

8

29

1

47

7

23

96

53

54

40

62

43

66

26

06

71

8

53

31

25

96

61

9

31

51

50

8

flas

k 5

75

4

14

02

63

3

70

2

30

22

91

3

26

67

75

8

56

8

21

9

26

9

29

5

14

29

38

14

26

09

30

08

10

51

61

6

34

65

20

20

44

3

21

39

26

1

flas

k 4

17

92

67

74

21

40

33

19

22

68

10

46

33

26

45

7

43

7

43

7

36

7

53

5

24

32

58

95

61

06

50

72

16

48

93

7

53

72

42

99

73

4

37

95

13

7

flas

k 3

92

0

12

828

12

89

15

89

22

42

61

02

30

33

95

1

32

8

31

3

33

3

47

3

16

79

51

97

35

13

37

77

31

88

62

5

37

17

18

34

53

0

25

24

28

7

flas

k 2

86

9

21

32

15

20

10

07

11

93

67

4

26

18

10

17

42

8

28

8

42

5

27

0

18

68

30

01

20

81

23

30

21

14

90

0

39

41

19

95

46

2

24

46

18

2

flas

k 1

37

80

68

22

55

99

12

897

63

27

90

71

67

01

51

33

24

36

16

61

10

36

12

60

51

89

13

765

89

12

92

58

54

13

22

40

14

941

74

19

17

26

92

11

84

0

Mo

naz

ite

On

ly

flas

k 6

29

8

13

81

47

8

25

1

10

47

20

3

94

9

47

7

67

6

73

24

15

2

44

8

38

9

24

61

68

8

20

40

27

9

91

2

55

4

44

1

14

9

66

9

13

9

flas

k 5

40

2

43

0

32

6

86

3

35

7

63

3

10

26

53

7

24

4

12

02

11

7

26

7

54

4

18

90

83

4

17

02

42

2

11

2

13

02

66

4

60

70

2

12

0

flas

k 4

72

6

43

0

16

2

21

81

18

06

14

50

15

25

11

47

27

7

47

7

20

0

19

6

12

25

25

68

14

98

13

98

10

97

68

8

18

41

10

45

19

1

17

45

19

6

flas

k 3

31

4

12

0

20

5

27

8

79

2

19

3

51

9

35

9

35

9

78

7

12

6

27

1

77

7

18

13

93

2

20

53

54

3

33

0

11

20

28

8

55

10

03

10

8

flas

k 2

35

5

33

1

27

0

64

9

47

7

33

4

44

35

30

9

25

78

11

80

97

1

98

03

57

7

17

54

11

01

28

77

27

7

78

0

88

7

45

1

17

7

72

5

10

85

flas

k 1

24

7

49

4

27

8

24

9

87

2

26

0

79

4

50

8

42

0

11

94

98

25

5

49

8

17

36

74

8

18

45

31

4

69

3

59

5

48

9

53

53

5

15

4

Met

abo

lite

Nam

e o

r B

inB

ase

ID

13

7

16

8

25

7

65

7

80

9

89

2

10

64

11

73

16

73

16

81

16

90

17

15

18

70

18

72

18

75

18

78

19

13

20

44

20

61

20

81

20

95

20

97

28

21

149

Sig

nal

In

ten

sity

at

6 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

26

928

58

89

45

7

42

0

62

104

45

4

28

8

10

26

42

0

58

62

65

7

20

10

68

7

92

1

42

6

59

57

11

20

79

2

16

256

33

2

37

87

15

06

14

89

flas

k 5

15

915

42

65

59

3

18

4

34

553

42

6

31

1

74

2

39

1

60

51

26

1

29

70

37

0

52

0

52

2

37

20

47

2

47

2

97

30

29

9

23

58

66

4

83

6

flas

k 4

28

146

58

17

49

2

49

6

61

289

57

4

28

5

11

71

74

2

64

11

38

7

30

45

40

2

16

44

19

21

64

38

14

95

93

3

18

623

39

0

43

96

56

6

15

66

flas

k 3

18

689

48

64

79

0

26

1

44

723

26

6

34

9

70

3

36

4

38

26

37

7

25

63

42

9

86

3

23

2

47

43

10

02

65

1

12

425

37

7

26

45

35

9

13

41

flas

k 2

18

668

54

45

43

3

39

4

38

637

79

4

32

4

40

0

46

7

48

56

41

2

24

72

44

1

12

04

11

70

29

60

98

3

49

3

10

550

30

6

20

52

13

54

12

06

flas

k 1

75

844

15

874

14

75

85

9

13

941

7

17

17

10

92

15

31

15

21

14

540

17

36

45

08

18

57

20

06

74

75

11

619

34

90

39

01

36

723

17

64

10

630

19

88

38

36

Mo

naz

ite

On

ly

flas

k 6

43

56

79

1

17

7

63

1

95

99

12

357

54

74

76

0

84

36

66

5

20

02

83

7

57

9

14

1

98

11

17

29

0

18

5

37

58

25

0

80

6

27

40

29

1

flas

k 5

57

78

11

22

17

6

74

14

419

34

9

99

26

53

11

1

87

1

40

82

60

5

26

8

28

3

12

6

10

47

34

9

46

6

49

00

15

6

10

88

13

15

15

9

flas

k 4

14

136

44

86

27

9

20

7

29

474

44

8

13

7

37

1

34

4

43

22

45

6

13

78

14

8

25

6

34

2

24

17

72

9

10

63

82

45

53

9

16

46

16

03

90

2

flas

k 3

50

43

15

15

30

4

93

8

12

503

33

72

21

76

63

4

22

97

79

8

15

044

62

5

12

25

21

3

61

11

63

26

8

29

8

43

69

15

8

10

26

94

73

33

1

flas

k 2

42

86

99

1

38

7

36

5

29

658

51

61

88

0

51

2

36

53

15

41

31

95

51

5

74

0

21

4

68

90

0

55

2

32

0

32

81

11

55

10

31

46

49

40

3

flas

k 1

48

23

90

8

38

4

13

26

10

413

12

761

18

56

40

5

88

28

61

6

10

444

65

7

19

65

51

67

87

6

25

4

21

6

41

93

20

7

73

1

87

26

28

1

Met

abo

lite

Nam

e o

r B

inB

ase

ID

29

44

30

83

31

73

32

47

34

42

37

81

45

41

45

43

47

13

47

32

47

95

47

97

48

19

49

37

49

76

53

46

55

76

61

04

63

30

66

46

93

20

14

694

16

561

150

Sig

nal

In

ten

sity

at

6 D

ays

K2H

PO

4 a

nd

Mo

naz

ite

flas

k 6

14

35

29

45

24

0

32

26

45

7

58

9

53

5

72

8

77

5

44

64

38

31

24

71

71

4

37

2

57

5

43

3

24

4

13

98

91

0

19

43

30

5

42

6

11

98

flas

k 5

17

38

13

54

27

2

15

62

30

3

54

9

32

0

33

4

35

7

30

50

23

79

67

5

77

7

19

4

50

1

23

8

19

4

99

4

46

2

19

01

23

0

24

0

51

2

flas

k 4

27

33

24

60

32

8

17

65

37

5

59

3

57

8

55

4

55

1

21

90

40

06

21

63

11

95

38

7

10

31

60

5

38

7

18

78

84

7

36

78

55

1

47

2

98

8

flas

k 3

16

84

77

5

23

8

19

74

35

4

96

9

42

4

36

4

74

4

33

27

27

74

11

55

49

1

30

5

37

7

26

6

30

5

15

19

64

1

22

89

26

3

27

6

10

72

flas

k 2

28

77

14

55

24

1

25

76

44

1

87

9

27

2

37

9

66

9

40

26

26

98

19

07

13

28

25

4

70

3

34

8

14

0

13

20

60

4

11

57

38

7

40

0

55

3

flas

k 1

27

72

48

72

93

3

68

50

19

41

16

24

17

64

17

08

14

47

11

703

10

172

38

64

30

89

10

36

13

35

59

73

10

36

26

13

19

97

71

11

11

57

93

3

17

92

Mo

naz

ite

On

ly

flas

k 6

14

50

10

19

19

815

34

1

54

77

35

32

87

96

60

8

52

68

22

84

2

59

4

22

9

19

2

30

42

48

848

31

1

42

6

10

76

70

1

18

2

14

399

26

5

flas

k 5

28

3

12

22

24

5

84

6

15

9

28

598

30

1

18

6

11

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151

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152

Sig

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153

Sig

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154

Appendix 3:

Heatmap showing average levels of all detected metabolites during monazite bioleaching

155

Appendix 3. Heatmap showing average levels of all detected metabolites during monazite

bioleaching. Rows represent different conditions and time points. Columns represent different

metabolites. Metabolites are ordered based on hierarchical clustering, with the clustering

dendrogram displayed at the bottom of the heatmap and metabolite names at the top. Heatmap

colors indicate standard deviations below (blue) and above (yellow) the overall mean level for

each metabolite. Note: figure covers two pages.

157

Appendix 4:

Novel ANAS Dehalococcoides genes with product predictions beyond "hypothetical

protein".

158

Appendix 4. Novel ANAS Dehalococcoides genes with product predictions beyond

"hypothetical protein".

a Genes on contigs identified as Dhc by SS but not by TF are highlighted in grey.

Contig Name

JGI IMG

Gene Object ID JGI Predicted Product

ANASMEC_C725 2014734531 Integral membrane protein TIGR01906

ANASMEC_C818 2014734798 Signal transduction histidine kinase

ANASMEC_C818 2014734801 Uncharacterized conserved protein

ANASMEC_C818 2014734803 Site-specific recombinases, DNA invertase Pin

homologs


homologs


homologs

ANASMEC_C818 2014734808 Adenine-specific DNA methylase

ANASMEC_C818 2014734809 Predicted transcriptional regulators

ANASMEC_C818 2014734832 phage/plasmid primase, P4 family, C-terminal

domain

ANASMEC_C818 2014734837 Restriction endonuclease

ANASMEC_C818 2014734838 methionine adenosyltransferase (EC 2.5.1.6)


ANASMEC_C818 2014734840 DNA modification methylase

ANASMEC_C818 2014734844 Phage terminase-like protein, large subunit


ANASMEC_C818 2014734846 Phage portal protein, HK97 family

ANASMEC_C818 2014734847 Protease subunit of ATP-dependent Clp proteases

ANASMEC_C818 2014734848 phage major capsid protein, HK97 family

ANASMEC_C818 2014734851 Bacteriophage head-tail adaptor

ANASMEC_C818 2014734852 phage protein, HK97 gp10 family

ANASMEC_C818 2014734858 Phage-related protein

ANASMEC_C818 2014734863 toxin secretion/phage lysis holin

ANASMEC_C818 2014734864 Negative regulator of beta-lactamase expression


homologs


homologs



homologs

ANASMEC_C4102 2014746224 Recombinase

159

Contig Name

JGI IMG



homologs


homologs

ANASMEC_C5086 2014749816 Sigma-70, region 4.

ANASMEC_C5086 2014749817 Negative regulator of beta-lactamase expression

ANASMEC_C5086 2014749818 toxin secretion/phage lysis holin

ANASMEC_C5086 2014749826 phage major tail protein, phi13 family

ANASMEC_C5086 2014749828 phage protein, HK97 gp10 family

ANASMEC_C5086 2014749829 phage head-tail adaptor, putative, SPP1 family

ANASMEC_C5086 2014749833 phage major capsid protein, HK97 family

ANASMEC_C5086 2014749834 Protease subunit of ATP-dependent Clp proteases

ANASMEC_C5086 2014749835 phage portal protein, HK97 family


ANASMEC_C5086 2014749840 DNA-methyltransferase (dcm)

ANASMEC_C5086 2014749841 DNA modification methylase

ANASMEC_C5086 2014749844 HNH endonuclease

ANASMEC_C5086 2014749846 Superfamily II DNA/RNA helicases, SNF2 family

ANASMEC_C5086 2014749847 VRR-NUC domain.

ANASMEC_C5086 2014749848 Predicted P-loop ATPase and inactivated derivatives

ANASMEC_C5086 2014749852 Uncharacterized phage-encoded protein

ANASMEC_C5086 2014749853 DNA polymerase I - 3'-5' exonuclease and

polymerase domains

ANASMEC_C5086 2014749861 Helix-turn-helix.

ANASMEC_C5086 2014749862 Predicted transcriptional regulator

ANASMEC_C5086 2014749863 Superfamily II DNA/RNA helicases, SNF2 family

ANASMEC_C5086 2014749864 Adenine specific DNA methylase Mod

ANASMEC_C5086 2014749865 DNA or RNA helicases of superfamily II

ANASMEC_C5086 2014749866 exonuclease SbcD

ANASMEC_C5086 2014749867 ATPase involved in DNA repair

ANASMEC_C5086 2014749869 ABC-type Mn/Zn transport systems, ATPase

component


ANASMEC_C6240 2014753777 PAS domain S-box

ANASMEC_C6240 2014753778 Reductive dehalogenase

ANASMEC_C6240 2014753782 Fe-S oxidoreductase

ANASMEC_C6240 2014753783 Transcriptional regulator, MarR family



160

Contig Name

JGI IMG


ANASMEC_C6240 2014753788 Predicted ATPases of PP-loop superfamily

ANASMEC_C6240 2014753791 ABC-type Fe3+-hydroxamate transport system,

periplasmic component

ANASMEC_C6240 2014753792 ABC-type Fe3+-siderophore transport system,

permease component

ANASMEC_C6240 2014753793 ABC-type cobalamin/Fe3+-siderophores transport

systems, ATPase components

ANASMEC_C6240 2014753794 Cobalamin biosynthesis protein CobN and related

Mg-chelatases

ANASMEC_C6240 2014753795 hydrogenobyrinic acid a,c-diamide cobaltochelatase

(EC 6.6.1.2)




permease component



ANASMEC_C6240 2014753799 Percorrin isomerase

ANASMEC_C6240 2014753800 ABC-type multidrug transport system, ATPase

component

ANASMEC_C6240 2014753801 cobalamin biosynthesis protein CbiD

ANASMEC_C6240 2014753802 precorrin-6y C5,15-methyltransferase

(decarboxylating), CbiE subunit/precorrin-6Y

C5,15-methyltransferase (decarboxylating), CbiT

subunit

ANASMEC_C6240 2014753803 precorrin-2 C20-methyltransferase

ANASMEC_C6240 2014753804 precorrin-4 C11-methyltransferase

ANASMEC_C6240 2014753805 precorrin-3B C17-methyltransferase

ANASMEC_C6240 2014753806 ABC-type polysaccharide/polyol phosphate export

systems, permease component



ANASMEC_C6240 2014753808 Predicted amidohydrolase




permease component



161

Contig Name

JGI IMG


ANASMEC_C6240 2014753812 Mg-chelatase subunit ChlI

ANASMEC_C6240 2014753813 Arylsulfatase regulator (Fe-S oxidoreductase)

ANASMEC_C6240 2014753814 Precorrin isomerase

ANASMEC_C6240 2014753815 Predicted amidohydrolase

ANASMEC_C6240 2014753817 ABC-type metal ion transport system, periplasmic

component/surface adhesion

ANASMEC_C6240 2014753819 Putative GTPases (G3E family)

ANASMEC_C6240 2014753821 Fe2+/Zn2+ uptake regulation proteins


ANASMEC_C6240 2014753826 ferric uptake regulator, Fur family

ANASMEC_C6240 2014753827 rubrerythrin




ANASMEC_C6240 2014753832 Response regulator containing a CheY-like receiver

domain and an HTH DNA-binding domain

ANASMEC_C6240 2014753834 VTC domain

ANASMEC_C6240 2014753837 Response regulators consisting of a CheY-like

receiver domain and a winged-helix DNA-binding

domain


ANASMEC_C6240 2014753846 NUDIX domain

ANASMEC_C6240 2014753847 Predicted phosphoesterase or phosphohydrolase

ANASMEC_C6240 2014753850 ADP-ribosylglycohydrolase

ANASMEC_C6240 2014753851 Uridine kinase

ANASMEC_C6240 2014753852 Uncharacterized protein with protein kinase and

helix-hairpin-helix DNA-binding domains

ANASMEC_C6240 2014753854 Uncharacterized protein encoded in toxicity

protection region of plasmid R478, contains von

Willebrand factor (vWF) domain



domain




domain


ANASMEC_C6240 2014753862 transcriptional regulator/antitoxin, MazE

162

Contig Name

JGI IMG


ANASMEC_C6240 2014753863 transcriptional modulator of MazE/toxin, MazF

ANASMEC_C6240 2014753864 Uncharacterized protein conserved in bacteria


ANASMEC_C6240 2014753871 Nucleotidyltransferase/DNA polymerase involved in

DNA repair

ANASMEC_C6240 2014753873 DNA polymerase III, alpha subunit

ANASMEC_C6240 2014753874 DNA polymerase III, alpha subunit

ANASMEC_C6240 2014753877 DNA binding domain, excisionase family



homologs



domain



domain





ANASMEC_C9422 2014767434 FMN-binding domain


homologs


ANASMEC_C9422 2014767439 Helix-turn-helix

ANASMEC_C9422 2014767445 Preprotein translocase subunit Sec63

ANASMEC_C9422 2014767446 Predicted ATPase involved in replication control,

Cdc46/Mcm family

ANASMEC_C9422 2014767450 SpoVT / AbrB like domain

ANASMEC_C9422 2014767462 Subtilisin-like serine proteases

ANASMEC_C9422 2014767467 Site-specific recombinase XerD


ANASMEC_C9422 2014767471 MTH538 TIR-like domain (DUF1863).



ANASMEC_C9422 2014767477 DNA polymerase III beta subunit family protein

ANASMEC_C9422 2014767481 Eco57I restriction endonuclease

ANASMEC_C9422 2014767482 Superfamily II DNA and RNA helicases

163

Contig Name

JGI IMG


ANASMEC_C9422 2014767484 Predicted hydrolase of the metallo-beta-lactamase

superfamily

ANASMEC_C9422 2014767486 Type I restriction-modification system

methyltransferase subunit





ANASMEC_C9422 2014767637 Predicted transcriptional regulator with C-terminal

CBS domains



ANASMEC_C10029 2014770452 Growth regulator

ANASMEC_C10029 2014770454 Nucleotidyltransferase domain

ANASMEC_C10029 2014770456 Type III restriction enzyme, res subunit

ANASMEC_C10029 2014770458 Adenine specific DNA methylase Mod

ANASMEC_C10029 2014770462 Superfamily II helicase

ANASMCE_C10442 2014772673 ABC-type multidrug transport system, ATPase and

permease components

ANASMCE_C10442 2014772674 Putative secretion activating protein

ANASMCE_C10442 2014772675 Deoxyribodipyrimidine photo-lyase type II (EC

4.1.99.3)

ANASMCE_C10442 2014772676 Dihydroorotate dehydrogenase

ANASMCE_C10442 2014772677 GAF domain-containing protein

ANASMCE_C10442 2014772678 diguanylate cyclase (GGDEF) domain

ANASMCE_C10442 2014772679 Putative threonine efflux protein

ANASMCE_C10442 2014772680 Mg2+ and Co2+ transporters

ANASMCE_C10442 2014772681 Permeases of the drug/metabolite transporter (DMT)

superfamily

ANASMCE_C10442 2014772682 Predicted integral membrane protein

ANASMCE_C10442 2014772683 Uncharacterized protein conserved in bacteria

ANASMCE_C10442 2014772684 Pyruvate/2-oxoglutarate dehydrogenase complex,

dihydrolipoamide dehydrogenase (E3) component,

and related enzymes

ANASMCE_C10442 2014772685 Uncharacterized conserved protein

ANASMCE_C10442 2014772686 Glycosyl transferase family 2.

ANASMCE_C10442 2014772687 Outer membrane cobalamin receptor protein

ANASMCE_C10442 2014772688 Outer membrane cobalamin receptor protein

ANASMCE_C10442 2014772689 Sugar phosphate permease

164

Contig Name

JGI IMG


ANASMCE_C10769 2014773969 SOS-response transcriptional repressors (RecA-

mediated autopeptidases)

ANASMCE_C10769 2014773980 VRR-NUC domain

ANASMCE_C10769 2014773981 Site-specific DNA methylase

ANASMEC_C10784 2014774099 Transcriptional regulators

ANASMEC_C10784 2014774101 Uncharacterized Fe-S protein

ANASMEC_C10784 2014774103 Transcriptional regulators


ANASMEC_C10784 2014774108 addiction module toxin, RelE/StbE family

FYHO20111_b1 2014778994 dihydrodipicolinate reductase (EC 1.3.1.26)

165

Appendix 5:

Genes for hydrogenase components identified in the ANAS metagenome contigs.

166

Ap

pen

dix

5. G

enes

for

hydro

gen

ase

com

ponen

ts i

den

tifi

ed i

n t

he

AN

AS

met

agen

om

e co

nti

gs

JGI

Pre

dic

ted P

roduct

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Hydro

gen

ase

4 m

embra

ne

com

ponen

t (E

)

Ni,

Fe-

hydro

gen

ase

III

larg

e su

bunit

Ni,

Fe-

hydro

gen

ase

III

com

ponen

t G

Hydro

gen

ase

4 m

embra

ne

com

ponen

t (E

)

F420

-non-r

educi

ng h

ydro

gen

ase

subunit

G

F420

-non-r

educi

ng h

ydro

gen

ase

subunit

A (

EC

:1.1

2.1

.2)

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

bet

a su

bu

nit

hydro

gen

ases

, F

e-only

(E

C:1

.6.5

.3)

hydro

gen

ase

(NiF

e) s

mal

l su

bu

nit

(hydA

) (E

C:1

.12.9

9.6

)

Ni,

Fe-

hydro

gen

ase

I la

rge

sub

un

it (

EC

:1.1

2.7

.2,

EC

:1.1

2.9

9.6

)

Fe-

S-c

lust

er-c

onta

inin

g h

yd

rog

enas

e co

mp

on

ents

1 (

EC

:1.2

.7.-

)

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 2

ech h

ydro

gen

ase

subunit

A (

EC

:1.6

.99.5

, E

C:1

.6.5

.3)

JGI

IMG

Gen

e O

bje

ct I

D

2014756582

2014759808

2014759810

2014737892

2014737897

2014737898

2014737900

2014766382

2014766383

2014767525

2014767574

2014767610

2014767611

2014767618

2014769806

2014774036

Conti

g N

ame

AN

AS

ME

C_C

7062

AN

AS

ME

C_C

7752

AN

AS

ME

C_C

7752

AN

AS

ME

C_C

1689

AN

AS

ME

C_C

1691

AN

AS

ME

C_C

1691

AN

AS

ME

C_C

1691

AN

AS

ME

C_C

9125

AN

AS

ME

C_C

9125

AN

AS

ME

C_C

9422

AN

AS

ME

C_C

9422

AN

AS

ME

C_C

9422

AN

AS

ME

C_C

9422

AN

AS

ME

C_C

9422

AN

AS

ME

C_C

9983

AN

AS

ME

C_C

10782

Tax

a

(TF

Conti

g C

lass

)

Clo

stri

dia

ceae

Clo

stri

dia

ceae

Clo

stri

dia

ceae

Deh

alo

cocc

oid

es

Deh

alo

cocc

oid

es

Deh

alo

cocc

oid

es

Deh

alo

cocc

oid

es

Deh

alo

cocc

oid

es

Deh

alo

cocc

oid

es

Deh

alo

cocc

oid

es

Deh

alo

cocc

oid

es

Deh

alo

cocc

oid

es

Deh

alo

cocc

oid

es

Deh

alo

cocc

oid

es

Deh

alo

cocc

oid

es

Deh

alo

cocc

oid

es

167

JGI

Pre

dic

ted P

roduct

ech h

ydro

gen

ase

subunit

B

ech h

ydro

gen

ase

subunit

C

ech h

ydro

gen

ase

subunit

E

ech h

ydro

gen

ase

subunit

E

Hydro

gen

ase

4 m

embra

ne

com

ponen

t (E

)

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

del

ta s

ub

unit

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

del

ta s

ub

unit

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Ni,

Fe-

hydro

gen

ase

I sm

all

subunit

Ni,

Fe-

hydro

gen

ase

I sm

all

subunit

Ni,

Fe-

hydro

gen

ase

I la

rge

subunit

Ni,

Fe-

hydro

gen

ase

I la

rge

subunit

Ni/

Fe-

hydro

gen

ase,

b-t

ype

cyto

chro

me

subunit

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

ech h

ydro

gen

ase

subunit

A

ech h

ydro

gen

ase

subunit

B (

EC

:1.6

.5.3

)

JGI

IMG

Gen

e O

bje

ct I

D

2014774037

2014774039

2014774044

2014774045

2014734315

2014735861

2014735882

2014737255

2014746021

2014746022

2014746023

2014746024

2014746025

2014747692

2014747699

2014748557

2014750566

2014750568

Conti

g N

ame

AN

AS

ME

C_C

10782

AN

AS

ME

C_C

10782

AN

AS

ME

C_C

10782

AN

AS

ME

C_C

10782

AN

AS

ME

C_C

650

AN

AS

ME

C_C

1084

AN

AS

ME

C_C

1087

AN

AS

ME

C_C

1513

AN

AS

ME

C_C

4055

AN

AS

ME

C_C

4055

AN

AS

ME

C_C

4055

AN

AS

ME

C_C

4056

AN

AS

ME

C_C

4056

AN

AS

ME

C_C

4501

AN

AS

ME

C_C

4501

AN

AS

ME

C_C

4688

AN

AS

ME

C_C

5298

AN

AS

ME

C_C

5298

Tax

a

(TF

Conti

g C

lass

)

Deh

alo

cocc

oid

es

Deh

alo

cocc

oid

es

Deh

alo

cocc

oid

es

Deh

alo

cocc

oid

es

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

168

JGI

Pre

dic

ted P

roduct

ech h

ydro

gen

ase

subunit

C (

EC

:1.6

.5.3

)

ech h

ydro

gen

ase

subunit

E (

EC

:1.6

.5.3

, E

C:1

.6.5

.3)

ech h

ydro

gen

ase

subunit

F (

EC

:1.6

.5.3

)

Mem

bra

ne

bound h

yd

rog

enas

e su

bunit

mbhM

(E

C:1

.6.5

.3)

Mem

bra

ne

bound h

yd

rog

enas

e su

bunit

mbhM

Ni,

Fe-

hydro

gen

ase

III

smal

l su

bunit

ech h

ydro

gen

ase

subunit

E (

EC

:1.6

.5.3

)

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 2

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

hydro

gen

ases

, F

e-only

(E

C:1

.12.7

.2)

Ni,

Fe-

hydro

gen

ase

III

smal

l su

bunit

Ni,

Fe-

hydro

gen

ase

III

larg

e su

bunit

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehaP

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehaO

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehaO

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehaN

(E

C:1

.6.5

.3)

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehaJ

(E

C:1

.6.5

.3)

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehaH

JGI

IMG

Gen

e O

bje

ct I

D

2014750569

2014750571

2014750572

2014752890

2014752891

2014752892

2014752895

2014752898

2014759038

2014763480

2014770923

2014770925

2014745729

2014745730

2014745731

2014745732

2014745736

2014745737

Conti

g N

ame

AN

AS

ME

C_C

5298

AN

AS

ME

C_C

5299

AN

AS

ME

C_C

5299

AN

AS

ME

C_C

5961

AN

AS

ME

C_C

5961

AN

AS

ME

C_C

5961

AN

AS

ME

C_C

5961

AN

AS

ME

C_C

5962

AN

AS

ME

C_C

7530

AN

AS

ME

C_C

8446

AN

AS

ME

C_C

10097

AN

AS

ME

C_C

10097

AN

AS

ME

C_C

3966

AN

AS

ME

C_C

3966

AN

AS

ME

C_C

3966

AN

AS

ME

C_C

3966

AN

AS

ME

C_C

3966

AN

AS

ME

C_C

3966

Tax

a

(TF

Conti

g C

lass

)

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Des

ulf

ovi

bri

o

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

169

JGI

Pre

dic

ted P

roduct

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehaH

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehaG

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehaF

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehaE

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehaC

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehaB

F420

-non-r

educi

ng h

ydro

gen

ase

subunit

D

coen

zym

e F

42

0-r

edu

cing

hy

dro

gen

ase,

alp

ha

sub

un

it (

EC

1.1

2.9

8.1

)

(EC

:1.1

2.9

8.1

)

coen

zym

e F

42

0-r

edu

cing

hy

dro

gen

ase,

del

ta s

ubu

nit

(E

C 1

.12

.98

.1)

coen

zym

e F

42

0-r

edu

cing

hy

dro

gen

ase,

gam

ma

sub

un

it (

EC

1.1

2.9

8.1

)

(EC

:1.1

2.9

8.1

)

coen

zym

e F

42

0-r

edu

cing

hy

dro

gen

ase,

bet

a su

bu

nit

(E

C 1

.12

.98

.1)

(EC

:1.1

2.9

8.1

)

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehbA

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehbD

F420

-non-r

educi

ng h

ydro

gen

ase

subunit

D

F420

-non-r

educi

ng h

ydro

gen

ase

subunit

A

F420

-non-r

educi

ng h

ydro

gen

ase

subunit

G (

EC

:1.1

2.9

8.1

)

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehbQ

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

bet

a su

bu

nit

JGI

IMG

Gen

e O

bje

ct I

D

2014745738

2014745739

2014745740

2014745741

2014745743

2014745744

2014746595

2014748304

2014748305

2014748306

2014748307

2014748427

2014748430

2014751448

2014752722

2014752723

2014756258

2014768131

Conti

g N

ame

AN

AS

ME

C_C

3966

AN

AS

ME

C_C

3966

AN

AS

ME

C_C

3966

AN

AS

ME

C_C

3966

AN

AS

ME

C_C

3966

AN

AS

ME

C_C

3966

AN

AS

ME

C_C

4198

AN

AS

ME

C_C

4653

AN

AS

ME

C_C

4653

AN

AS

ME

C_C

4653

AN

AS

ME

C_C

4653

AN

AS

ME

C_C

4655

AN

AS

ME

C_C

4655

AN

AS

ME

C_C

5543

AN

AS

ME

C_C

5907

AN

AS

ME

C_C

5907

AN

AS

ME

C_C

7038

AN

AS

ME

C_C

9544

Tax

a

(TF

Conti

g C

lass

)

Met

hanoba

cter

ium

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

170

JGI

Pre

dic

ted P

roduct

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

bet

a su

bu

nit

Co

enzy

me

F4

20

-red

uci

ng

hy

dro

gen

ase,

gam

ma

subu

nit

(E

C:1

.12

.98

.1)

F420

-non-r

educi

ng h

ydro

gen

ase

subunit

A

Fe-

S-c

lust

er-c

onta

inin

g h

yd

rog

enas

e co

mp

on

ents

2 (

EC

:1.2

.1.2

)

Fe-

S-c

lust

er-c

onta

inin

g h

yd

rog

enas

e co

mp

on

ents

2 (

EC

:1.2

.1.2

)

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 2

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehbK

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehbL

Ni,

Fe-

hydro

gen

ase

III

smal

l su

bunit

(E

C:1

.6.5

.3)

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehbN

(E

C:1

.6.5

.3)

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehbO

(E

C:1

.6.5

.3)

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehbP

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

hydro

gen

ases

, F

e-only

(E

C:1

.6.5

.3)

Hydro

gen

ase

4 m

embra

ne

com

ponen

t (E

)

Ni,

Fe-

hydro

gen

ase

III

larg

e su

bunit

Ni,

Fe-

hydro

gen

ase

III

smal

l su

bunit

JGI

IMG

Gen

e O

bje

ct I

D

2014768132

2014768166

2014768167

2014771049

2014771073

2014771074

2014772216

2014772217

2014772218

2014772219

2014772220

2014772221

2014732339

2014732343

2014744373

2014758594

2014758596

2014758597

Conti

g N

ame

AN

AS

ME

C_C

9544

AN

AS

ME

C_C

9545

AN

AS

ME

C_C

9545

AN

AS

ME

C_C

10127

AN

AS

ME

C_C

10129

AN

AS

ME

C_C

10129

AN

AS

ME

C_C

10352

AN

AS

ME

C_C

10352

AN

AS

ME

C_C

10352

AN

AS

ME

C_C

10352

AN

AS

ME

C_C

10352

AN

AS

ME

C_C

10352

AN

AS

ME

C_C

77

AN

AS

ME

C_C

77

AN

AS

ME

C_C

3551

AN

AS

ME

C_C

7420

AN

AS

ME

C_C

7420

AN

AS

ME

C_C

7420

Tax

a

(TF

Conti

g C

lass

)

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Met

hanobact

eriu

m

Spir

och

aete

s

Spir

och

aete

s

Spir

och

aete

s

Spir

och

aete

s

Spir

och

aete

s

Spir

och

aete

s

171

JGI

Pre

dic

ted P

roduct

hydro

gen

ases

, F

e-only

(E

C:1

.6.5

.3)

Iron o

nly

hyd

rogen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Iro

n o

nly

hy

dro

gen

ase

larg

e su

bu

nit

, C

-ter

min

al d

om

ain (

EC

:1.1

2.7

.2)

hydro

gen

ases

, F

e-only

(E

C:1

.6.5

.3)

Mem

bra

ne

bound h

yd

rog

enas

e su

bunit

mbhH

(E

C:1

.6.5

.3)

Mem

bra

ne

bound h

yd

rog

enas

e su

bunit

mbhJ

Ni,

Fe-

hydro

gen

ase

III

com

ponen

t G

(E

C:1

.6.5

.3)

Mem

bra

ne

bound h

yd

rog

enas

e su

bunit

mbhL

(E

C:1

.6.5

.3)

Ni,

Fe-

hydro

gen

ase

III

larg

e su

bunit

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Mem

bra

ne

bound h

yd

rog

enas

e su

bunit

mbhD

Mem

bra

ne

bound h

yd

rog

enas

e su

bunit

mbhE

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 2

Co

enzy

me

F4

20

-red

uci

ng

hy

dro

gen

ase,

gam

ma

subu

nit

(E

C:1

.12

.2.1

)

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

alp

ha

sub

unit

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

del

ta s

ub

unit

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

alp

ha

sub

unit

JGI

IMG

Gen

e O

bje

ct I

D

2014761181

2014764872

2014769527

2014770160

2014745306

2014745308

2014745309

2014745310

2014745311

2014751345

2014753093

2014753094

2014753408

2014753733

2014753734

2014740617

2014762786

2014753264

Conti

g N

ame

AN

AS

ME

C_C

7814

AN

AS

ME

C_C

8778

AN

AS

ME

C_C

9969

AN

AS

ME

C_C

10002

AN

AS

ME

C_C

3841

AN

AS

ME

C_C

3841

AN

AS

ME

C_C

3841

AN

AS

ME

C_C

3841

AN

AS

ME

C_C

3841

AN

AS

ME

C_C

5524

AN

AS

ME

C_C

6017

AN

AS

ME

C_C

6017

AN

AS

ME

C_C

6125

AN

AS

ME

C_C

6229

AN

AS

ME

C_C

6229

AN

AS

ME

C_C

238

8

AN

AS

ME

C_C

8232

AN

AS

ME

C_C

6076

Tax

a

(TF

Conti

g C

lass

)

Spir

och

aete

s

Spir

och

aete

s

Spir

och

aete

s

Spir

och

aete

s

Syner

gis

tete

s

Syner

gis

tete

s

Syner

gis

tete

s

Syner

gis

tete

s

Syner

gis

tete

s

Syner

gis

tete

s

Syner

gis

tete

s

Syner

gis

tete

s

Syner

gis

tete

s

Syner

gis

tete

s

Syner

gis

tete

s

un

kno

wn

Del

ta-

pro

teo

bac

teri

um

un

kno

wn

Del

ta-

pro

teo

bac

teri

um

unid

enti

fied

Cla

ss 6

172

JGI

Pre

dic

ted P

roduct

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

gam

ma

subunit

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

gam

ma

subunit

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

del

ta s

ub

unit

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

del

ta s

ub

unit

Fe-

S-c

lust

er-c

onta

inin

g h

yd

rog

enas

e co

mp

on

ents

2 (

EC

:1.2

.1.2

)

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

alp

ha

sub

unit

Co

enzy

me

F4

20

-red

uci

ng

hy

dro

gen

ase,

gam

ma

subu

nit

(E

C:1

.12

.98

.1)

Co

enzy

me

F4

20 h

yd

rog

enas

e/d

ehy

dro

gen

ase,

bet

a su

bun

it N

ter

min

us.

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

del

ta s

ub

unit

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

del

ta s

ub

unit

Fe-

S-c

lust

er-c

onta

inin

g h

yd

rog

enas

e co

mp

on

ents

1 (

EC

:1.2

.1.2

)

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

alp

ha

sub

unit

hyd

rogen

ase

(NiF

e) s

mal

l su

bu

nit

(hydA

)

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

del

ta s

ub

unit

Ni,

Fe-

hydro

gen

ase

III

smal

l su

bunit

Ni,

Fe-

hydro

gen

ase

III

larg

e su

bunit

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

JGI

IMG

Gen

e O

bje

ct I

D

2014753265

2014753266

2014753267

2014753268

2014753271

2014759312

2014759313

2014763577

2014763578

2014763580

2014763583

2014764214

2014741466

2014741467

2014758628

2014759102

2014759103

2014761270

Conti

g N

ame

AN

AS

ME

C_C

6076

AN

AS

ME

C_C

6076

AN

AS

ME

C_C

6076

AN

AS

ME

C_C

6076

AN

AS

ME

C_C

6076

AN

AS

ME

C_C

7617

AN

AS

ME

C_C

7617

AN

AS

ME

C_C

8475

AN

AS

ME

C_C

8475

AN

AS

ME

C_C

8475

AN

AS

ME

C_C

8475

AN

AS

ME

C_C

8652

AN

AS

ME

C_C

2675

AN

AS

ME

C_C

2675

AN

AS

ME

C_C

7432

AN

AS

ME

C_C

7550

AN

AS

ME

C_C

7550

AN

AS

ME

C_C

7820

Tax

a

(TF

Conti

g C

lass

)

unid

enti

fied

Cla

ss 6

unid

enti

fied

Cla

ss 6

unid

enti

fied

Cla

ss 6

unid

enti

fied

Cla

ss 6

unid

enti

fied

Cla

ss 6

unid

enti

fied

Cla

ss 6

unid

enti

fied

Cla

ss 6

unid

enti

fied

Cla

ss 6

unid

enti

fied

Cla

ss 6

unid

enti

fied

Cla

ss 6

unid

enti

fied

Cla

ss 6

unid

enti

fied

Cla

ss 6

unid

enti

fied

Cla

ss 9

unid

enti

fied

Cla

ss 9

unid

enti

fied

Cla

ss 9

unid

enti

fied

Cla

ss 9

unid

enti

fied

Cla

ss 9

unid

enti

fied

Cla

ss 9

173

JGI

Pre

dic

ted P

roduct

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 2

Coen

zym

e F

420-r

edu

cing h

ydro

gen

ase,

del

ta s

ub

unit

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Mem

bra

ne

bound h

yd

rog

enas

e su

bunit

mbhJ

Co

enzy

me

F4

20

-red

uci

ng

hy

dro

gen

ase,

alp

ha

sub

un

it (

EC

:1.1

2.1

.2)

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Ni,

Fe-

hy

dro

gen

ase

I la

rge

subu

nit

(E

C:1

.12

.99

.6,

EC

:1.1

2.5

.1,

EC

:1.1

2.5

.1)

hydro

gen

ases

, F

e-only

(E

C:1

.12.7

.2, E

C:1

.6.5

.3)

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Ni,

Fe-

hydro

gen

ase

III

smal

l su

bunit

Ni,

Fe-

hydro

gen

ase

III

larg

e su

bunit

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

bet

a su

bu

nit

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Ni,

Fe-

hydro

gen

ase

I sm

all

subunit

JGI

IMG

Gen

e O

bje

ct I

D

2014761457

2014763265

2014732173

2014732382

2014733276

2014733911

2014733912

2014734234

2014735094

2014736156

2014736461

2014736703

2014737258

2014737894

2014737895

2014738154

2014738247

2014738467

Conti

g N

ame

AN

AS

ME

C_C

7870

AN

AS

ME

C_C

8392

AN

AS

ME

C_C

25

AN

AS

ME

C_C

86

AN

AS

ME

C_C

341

AN

AS

ME

C_C

527

AN

AS

ME

C_C

528

AN

AS

ME

C_C

627

AN

AS

ME

C_C

883

AN

AS

ME

C_C

1189

AN

AS

ME

C_C

1283

AN

AS

ME

C_C

1362

AN

AS

ME

C_C

1514

AN

AS

ME

C_C

1690

AN

AS

ME

C_C

1690

AN

AS

ME

C_C

1735

AN

AS

ME

C_C

1775

AN

AS

ME

C_C

1853

Tax

a

(TF

Conti

g C

lass

)

uncl

assi

fied

uncl

assi

fied

174

JGI

Pre

dic

ted P

roduct

Ni,

Fe-

hydro

gen

ase

I la

rge

subunit

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 2

F420

-non-r

educi

ng h

ydro

gen

ase

subunit

A

Mem

bra

ne

bound h

yd

rog

enas

e su

bunit

mbhC

Mem

bra

ne

bound h

yd

rog

enas

e su

bunit

mbhD

Mem

bra

ne

bound h

yd

rog

enas

e su

bunit

mbhE

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

alp

ha

sub

unit

ech h

ydro

gen

ase

subunit

E

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

hydro

gen

ases

, F

e-only

Iro

n h

ydro

gen

ase

smal

l su

bu

nit

./T

AT

(tw

in-a

rgin

ine

tran

slo

cati

on

)

pat

hw

ay s

ign

al s

equ

ence

. (E

C:1

.12

.7.2

)

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Hy

dro

gen

ase

4 m

embra

ne

com

ponen

t (E

)

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

alp

ha

sub

unit

Ni,

Fe-

hydro

gen

ase

III

smal

l su

bunit

JGI

IMG

Gen

e O

bje

ct I

D

2014738468

2014738794

2014739384

2014740019

2014740750

2014740751

2014740752

2014741247

2014742389

2014743057

2014743150

2014744681

2014744682

2014744683

2014745388

2014745528

2014745841

2014746481

Conti

g N

ame

AN

AS

ME

C_C

1853

AN

AS

ME

C_C

1941

AN

AS

ME

C_C

2075

AN

AS

ME

C_C

2214

AN

AS

ME

C_C

2429

AN

AS

ME

C_C

2429

AN

AS

ME

C_C

2429

AN

AS

ME

C_C

2599

AN

AS

ME

C_C

2945

AN

AS

ME

C_C

3132

AN

AS

ME

C_C

3166

AN

AS

ME

C_C

3625

AN

AS

ME

C_C

3625

AN

AS

ME

C_C

3625

AN

AS

ME

C_C

3861

AN

AS

ME

C_C

3914

AN

AS

ME

C_C

4001

AN

AS

ME

C_C

4172

Tax

a

(TF

Conti

g C

lass

)

175

JGI

Pre

dic

ted P

roduct

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Ni,

Fe-

hydro

gen

ase

I la

rge

subunit

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehbH

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

del

ta s

ub

unit

Fe-

S-c

lust

er-c

onta

inin

g h

yd

rog

enas

e co

mp

on

ents

1 (

EC

:1.2

.1.2

)

F420

-non-r

educi

ng h

ydro

gen

ase

subunit

A

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

gam

ma

subunit

F420

-non-r

educi

ng h

ydro

gen

ase

subunit

D

Mem

bra

ne

bound h

yd

rog

enas

e su

bunit

mbhF

Mem

bra

ne

bound h

yd

rog

enas

e su

bunit

mbhD

Mem

bra

ne

bound h

yd

rog

enas

e su

bunit

mbhC

Mem

bra

ne

bound h

yd

rog

enas

e su

bunit

mbhB

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 2

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

(EC

:1.2

.1.2

) M

embra

ne

bound h

yd

rog

enas

e su

bunit

mbhJ

Ni,

Fe-

hydro

gen

ase

III

com

ponen

t G

(E

C:1

.6.5

.3)

Mem

bra

ne

bound h

yd

rog

enas

e su

bunit

mbhL

JGI

IMG

Gen

e O

bje

ct I

D

2014746664

2014748921

2014749641

2014749988

2014750888

2014751039

2014751040

2014751041

2014751251

2014751253

2014751254

2014751255

2014752009

2014752392

2014752737

2014753100

2014753102

2014753103

Conti

g N

ame

AN

AS

ME

C_C

4206

AN

AS

ME

C_C

4809

AN

AS

ME

C_C

5040

AN

AS

ME

C_C

5109

AN

AS

ME

C_

C5384

AN

AS

ME

C_C

5418

AN

AS

ME

C_C

5418

AN

AS

ME

C_C

5418

AN

AS

ME

C_C

5488

AN

AS

ME

C_C

5488

AN

AS

ME

C_C

5488

AN

AS

ME

C_C

5488

AN

AS

ME

C_C

5706

AN

AS

ME

C_C

5845

AN

AS

ME

C_C

5913

AN

AS

ME

C_C

6018

AN

AS

ME

C_C

6018

AN

AS

ME

C_C

6018

Tax

a

(TF

Conti

g C

lass

)

176

JGI

Pre

dic

ted P

roduct

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Co

enzy

me

F4

20

-red

uci

ng

hy

dro

gen

ase,

gam

ma

subu

nit

(E

C:1

.12

.2.1

)

Co

enzy

me

F4

20

-red

uci

ng

hy

dro

gen

ase,

alp

ha

sub

un

it (

EC

:1.1

2.1

.2)

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 2

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Ni,

Fe-

hydro

gen

ase

III

larg

e su

bunit

coen

zym

e F

42

0-r

edu

cing

hy

dro

gen

ase,

bet

a su

bu

nit

(E

C 1

.12

.98

.1)

coen

zym

e F

42

0-r

edu

cing

hy

dro

gen

ase,

gam

ma

sub

un

it (

EC

1.1

2.9

8.1

)

coen

zym

e F

42

0-r

edu

cing

hy

dro

gen

ase,

alp

ha

sub

un

it (

EC

1.1

2.9

8.1

)

coen

zym

e F

42

0-r

edu

cing

hy

dro

gen

ase,

alp

ha

sub

un

it (

EC

1.1

2.9

8.1

)

Fe-

S-c

lust

er-c

onta

inin

g h

yd

rog

enas

e co

mp

on

ents

1 (

EC

:1.2

.7.-

)

ech h

ydro

gen

ase

subunit

B

hy

dro

gen

ase

(NiF

e) s

mal

l su

bu

nit

(h

yd

A)

(EC

:1.1

2.7

.2,

EC

:1.1

2.9

9.6

)

Ni,

Fe-

hydro

gen

ase

I la

rge

subunit

Ni,

Fe-

hydro

gen

ase

I la

rge

subunit

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

alp

ha

sub

unit

JGI

IMG

Gen

e O

bje

ct I

D

2014754483

2014755821

2014755822

2014755955

2014756330

2014757935

2014758973

2014759518

2014761350

2014761351

2014761352

2014761353

2014762362

2014762816

2014763313

2014763315

2014763316

2014763706

Conti

g N

ame

AN

AS

ME

C_C

6459

AN

AS

ME

C_C

6917

AN

AS

ME

C_C

6917

AN

AS

ME

C_C

6950

AN

AS

ME

C_C

7056

AN

AS

ME

C_C

7311

AN

AS

ME

C_C

7505

AN

AS

ME

C_C

7681

AN

AS

ME

C_C

7849

AN

AS

ME

C_C

7849

AN

AS

ME

C_C

7850

AN

AS

ME

C_C

7850

AN

AS

ME

C_C

8085

AN

AS

ME

C_C

8241

AN

AS

ME

C_C

8406

AN

AS

ME

C_C

8406

AN

AS

ME

C_C

8406

AN

AS

ME

C_C

8505

Tax

a

(TF

Conti

g C

lass

)

177

JGI

Pre

dic

ted P

roduct

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

gam

ma

subunit

Hydro

gen

ase

4 m

embra

ne

com

ponen

t (E

)

ech h

ydro

gen

ase

subunit

E (

EC

:1.6

.5.3

)

ech h

ydro

gen

ase

subunit

D

ech h

ydro

gen

ase

subunit

C

ech h

ydro

gen

ase

subunit

B

Iron h

ydro

gen

ase

smal

l su

bunit

.

Ni,

Fe-

hydro

gen

ase

III

larg

e su

bunit

Ni,

Fe-

hydro

gen

ase

III

larg

e su

bunit

Ni,

Fe-

hydro

gen

ase

III

smal

l su

bunit

Co

enzy

me

F4

20

-red

uci

ng

hy

dro

gen

ase,

alp

ha

sub

un

it (

EC

:1.1

2.1

.2)

Mem

bra

ne

bound h

yd

rog

enas

e su

bunit

mbhL

Mem

bra

ne

bound h

yd

rog

enas

e su

bunit

mbhM

Mem

bra

ne

bound h

yd

rog

enas

e su

bunit

mbhN

F420

-non-r

educi

ng h

ydro

gen

ase

subunit

D

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehaN

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehaO

(E

C:1

.6.5

.3)

Ni,

Fe-

hydro

gen

ase

I sm

all

subunit

JGI

IMG

Gen

e O

bje

ct I

D

2014764213

2014764376

2014765406

2014765407

2014765408

2014765409

2014765524

2014765702

2014765703

2014765704

2014765793

2014765834

2014765835

2014765837

2014767808

2014769256

2014769257

2014769374

Conti

g N

ame

AN

AS

ME

C_C

8651

AN

AS

ME

C_C

8694

AN

AS

ME

C_C

8895

AN

AS

ME

C_C

8895

AN

AS

ME

C_C

8895

AN

AS

ME

C_C

8895

AN

AS

ME

C_C

8944

AN

AS

ME

C_C

9000

AN

AS

ME

C_C

9000

AN

AS

ME

C_C

9000

AN

AS

ME

C_C

9032

AN

AS

ME

C_C

9045

AN

AS

ME

C_C

9045

AN

AS

ME

C_C

9045

AN

AS

ME

C_C

9478

AN

AS

ME

C_C

9903

AN

AS

ME

C_C

9903

AN

AS

ME

C_C

9936

Tax

a

(TF

Conti

g C

lass

)

178

JGI

Pre

dic

ted P

roduct

Ni,

Fe-

hydro

gen

ase

I la

rge

subunit

(E

C:1

.12.9

9.6

)

Ni,

Fe-

hydro

gen

ase

I la

rge

subunit

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 2

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 2

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Ni,

Fe-

hydro

gen

ase

I la

rge

subunit

Ni,

Fe-

hydro

gen

ase

I la

rge

subunit

Ni,

Fe-

hydro

gen

ase

I sm

all

subunit

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

gam

ma

subunit

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

alp

ha

sub

unit

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

alp

ha

sub

unit

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

JGI

IMG

Gen

e O

bje

ct I

D

2014769375

2014772737

2014773281

2014773484

2014773633

2014773740

2014774777

2014775047

2014775687

2014776383

2014776384

2014776620

2014776768

2014778033

2014778151

2014778482

2014779184

2014779243

Conti

g N

ame

AN

AS

ME

C_C

993

6

AN

AS

ME

C_C

10452

AN

AS

ME

C_C

10611

AN

AS

ME

C_C

10649

AN

AS

ME

C_C

10704

AN

AS

ME

C_C

10743

AN

AS

ME

C_F

YH

O2833_b1

AN

AS

ME

C_F

YH

O4035_g1

AN

AS

ME

C_F

YH

O6120_g1

AN

AS

ME

C_F

YH

O9267_b1

AN

AS

ME

C_F

YH

O9267_g1

AN

AS

ME

C_F

YH

O10722_g1

AN

AS

ME

C_F

YH

O11347_g1

AN

AS

ME

C_F

YH

O16482_g1

AN

AS

ME

C_F

YH

O1699

5_b1

AN

AS

ME

C_F

YH

O18538_g1

AN

AS

ME

C_F

YH

O20884_b1

AN

AS

ME

C_F

YH

O21096_g1

Tax

a

(TF

Conti

g C

lass

)

179

JGI

Pre

dic

ted P

roduct

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

bet

a su

bu

nit

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 2

Ni,

Fe-

hydro

gen

ase

I sm

all

subunit

Ni,

Fe-

hydro

gen

ase

I la

rge

subunit

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

ech h

ydro

gen

ase

subunit

C

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

gam

ma

subunit

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

alp

ha

sub

unit

F420

-non-r

educi

ng h

ydro

gen

ase

subunit

A

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Co

enzy

me

F4

20

-red

uci

ng

hy

dro

gen

ase,

gam

ma

subu

nit

(E

C:1

.12

.2.1

,

EC

:1.1

2.1

.2)

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

alp

ha

sub

unit

Ni,

Fe-

hydro

gen

ase

III

smal

l su

bunit

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

del

ta s

ub

unit

JGI

IMG

Gen

e O

bje

ct I

D

2014779248

2014779943

2014780903

2014781259

2014781278

2014781310

2014782820

2014782841

2014783150

2014783268

2014783309

2014785350

2014786065

2014786359

2014786360

2014787077

2014787100

2014787482

Conti

g N

ame

AN

AS

ME

C_F

YH

O21118_b1

AN

AS

ME

C_F

YH

O24152_g1

AN

AS

ME

C_F

YH

O28140_g1

AN

AS

ME

C_F

YH

O29406_g1

AN

AS

ME

C_F

YH

O29496_g1

AN

AS

ME

C_F

YH

O29612_b1

AN

AS

ME

C_F

YH

O40291_g1

AN

AS

ME

C_F

YH

O40769_b1

AN

AS

ME

C_F

YH

O42060_b1

AN

AS

ME

C_F

YH

O42412_g1

AN

AS

ME

C_F

YH

O42621_g1

AN

AS

ME

C_F

YH

O52982_g1

AN

AS

ME

C_F

YH

O56076_g1

AN

AS

ME

C_F

YH

O57762_b1

AN

AS

ME

C_F

YH

O577

62_b1

AN

AS

ME

C_F

YH

O60390_g1

AN

AS

ME

C_F

YH

O60505_g1

AN

AS

ME

C_F

YH

O62192_b1

Tax

a

(TF

Conti

g C

lass

)

180

JGI

Pre

dic

ted P

roduct

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Mem

bra

ne

bound h

yd

rog

enas

e su

bunit

mbhH

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

del

ta s

ub

unit

Coen

zym

e F

420

-red

uci

ng h

ydro

gen

ase,

del

ta s

ub

unit

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehaE

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehaF

mem

bra

ne-

bound h

yd

rog

enas

e su

bunit

ehaJ

ech h

ydro

gen

ase

subunit

A

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

coen

zym

e F

42

0-r

edu

cing

hy

dro

gen

ase,

alp

ha

sub

un

it (

EC

1.1

2.9

8.1

)

F420

-non-r

educi

ng h

ydro

gen

ase

subunit

D

Fe-

S-c

lust

er-c

onta

inin

g h

ydro

gen

ase

com

ponen

ts 1

JGI

IMG

Gen

e O

bje

ct I

D

2014787675

2014788107

2014788638

2014788846

2014789187

2014789360

2014789526

2014789825

2014790391

2014790392

2014790394

2014790395

2014790397

2014791062

2014792104

2014792247

2014792282

2014793123

Conti

g N

ame

AN

AS

ME

C_F

YH

O63046_g1

AN

AS

ME

C_F

YH

O65027_g1

AN

AS

ME

C_F

YH

O67404_b1

AN

AS

ME

C_F

YH

O68348_b1

AN

AS

ME

C_F

YH

O69689_b1

AN

AS

ME

C_F

YH

O70452_g1

AN

AS

ME

C_F

YH

O70995_g1

AN

AS

ME

C_F

YH

O72306_b1

AN

AS

ME

C_F

YH

O74637_b1

AN

AS

ME

C_F

YH

O74637_b1

AN

AS

ME

C_F

YH

O74651_b1

AN

AS

ME

C_F

YH

O74651_b1

AN

AS

ME

C_F

YH

O74651_g1

AN

AS

ME

C_F

YH

O77655_g1

AN

AS

ME

C_F

YH

O82056_g1

AN

AS

ME

C_F

YH

O82556_g1

AN

AS

ME

C_F

YH

O82696_g1

AN

AS

ME

C_

GC

AX

03

49

1_

c1

_1

000

_10

0_1

Tax

a

(TF

Conti

g C

lass

)

181

JGI

Pre

dic

ted P

roduct

Iron o

nly

hydro

gen

ase

larg

e su

bunit

, C

-ter

min

al d

om

ain

ech h

ydro

gen

ase

subunit

A

Ni,

Fe-

hydro

gen

ase

III

smal

l su

bunit

JGI

IMG

Gen

e O

bje

ct I

D

2014793925

2014795068

2014795140

Conti

g N

ame

AN

AS

ME

C_

GC

AX

09804_c1

_1

00

0_

10

0_

1

AN

AS

ME

C_

GC

AX

18540_c1

_1

00

0_

10

0_

1

AN

AS

ME

C_

GC

AX

20496_c1

_1

00

0_

10

0_

2

Tax

a

(TF

Conti

g C

lass

)

182

Appendix 6:

Cobalamin biosynthesis genes identified in the ANAS metagenome contigs.

183

Appendix 6. Cobalamin biosynthesis genes identified in the ANAS metagenome contigs.

Taxa

(TF Contig Class) Contig Name

JGI IMG

Gene Object ID

Gene

Name

Clostridiaceae ANASMEC_C2155 2014739789 cbiC

Clostridiaceae ANASMEC_C2155 2014739790 cbiC

Clostridiaceae ANASMEC_C2155 2014739792 cobA

Clostridiaceae ANASMEC_C2155 2014739793 cbiP

Clostridiaceae ANASMEC_C2155 2014739795 cbiB

Clostridiaceae ANASMEC_C2155 2014739797 cobU

Clostridiaceae ANASMEC_C2155 2014739798 cobS

Clostridiaceae ANASMEC_C2155 2014739799 cobU

Clostridiaceae ANASMEC_C2155 2014739800 cobT

Clostridiaceae ANASMEC_C2155 2014739801 cbiA

Clostridiaceae ANASMEC_C2155 2014739802 cbiJ/E/T

Clostridiaceae ANASMEC_C2155 2014739803 cbiH

Clostridiaceae ANASMEC_C2155 2014739804 cbiG

Clostridiaceae ANASMEC_C2155 2014739805 cbiF

Clostridiaceae ANASMEC_C2155 2014739806 cbiL

Clostridiaceae ANASMEC_C2155 2014739807 cbiD

Clostridiaceae ANASMEC_C2155 2014739808 cbiK

Dehalococcoides ANASMEC_C2180 2014739915 cbiP

Dehalococcoides ANASMEC_C2636 2014741361 cobA

Dehalococcoides ANASMEC_C6240 2014753794 cobN

Dehalococcoides ANASMEC_C6240 2014753795 cobN

Dehalococcoides ANASMEC_C6240 2014753799 cbiX/C

Dehalococcoides ANASMEC_C6240 2014753801 cbiD

Dehalococcoides ANASMEC_C6240 2014753802 cbiE/T

Dehalococcoides ANASMEC_C6240 2014753803 cbiL

Dehalococcoides ANASMEC_C6240 2014753804 cbiF

Dehalococcoides ANASMEC_C6240 2014753805 cbiG/H

Dehalococcoides ANASMEC_C6240 2014753814 cbiC

Dehalococcoides ANASMEC_C6240 2014753861 cbiE

Dehalococcoides ANASMEC_C9125 2014766420 cbiB


Dehalococcoides ANASMEC_C9125 2014766424 cobT

Dehalococcoides ANASMEC_C9125 2014766425 cobS

Dehalococcoides ANASMEC_C9125 2014766426 cobC

Dehalococcoides ANASMEC_C9125 2014766427 cobU



184

Taxa


JGI IMG

Gene Object ID

Gene

Name



Dehalococcoides ANASMEC_C9422 2014767593 cbiA



Desulfovibrio ANASMEC_C10219 2014771567 cbiP

Desulfovibrio ANASMEC_C10280 2014771809 cbiH

Desulfovibrio ANASMEC_C10425 2014772542 cbiK

Desulfovibrio ANASMEC_C1452 2014737023 cobT

Desulfovibrio ANASMEC_C2682 2014741500 cbiK

Desulfovibrio ANASMEC_C5098 2014749951 cbiL

Desulfovibrio ANASMEC_C5922 2014752770 cbiA

Desulfovibrio ANASMEC_C6044 2014753178 cbiB

Desulfovibrio ANASMEC_C614 2014734182 cbiF

Desulfovibrio ANASMEC_C614 2014734183 cbiF

Desulfovibrio ANASMEC_C615 2014734184 cbiE

Desulfovibrio ANASMEC_C615 2014734185 cbiD

Desulfovibrio ANASMEC_C7938 2014761871 cbiG

Desulfovibrio ANASMEC_C8971 2014765623 cbiA

Methanobacteriacea ANASMEC_C10286 2014771933 cbiT

Methanobacteriacea ANASMEC_C10466 2014772804 cbiF

Methanobacteriacea ANASMEC_C10466 2014772805 cbiF

Methanobacteriacea ANASMEC_C124 2014732527 cbiJ

Methanobacteriacea ANASMEC_C126 2014732536 cbiP

Methanobacteriacea ANASMEC_C1527 2014737393 cbiE

Methanobacteriacea ANASMEC_C4198 2014746601 cobU

Methanobacteriacea ANASMEC_C4638 2014748160 cbiC

Methanobacteriacea ANASMEC_C4638 2014748181 cobN





Methanobacteriacea ANASMEC_C4654 2014748350 cbiE





Methanobacteriacea ANASMEC_C7444 2014758745 cbiD

Methanobacteriacea ANASMEC_C7444 2014758746 cbiD

185

Taxa


JGI IMG

Gene Object ID

Gene

Name

Methanobacteriacea ANASMEC_C9971 2014769572 cbiL

Methanobacteriacea ANASMEC_C9972 2014769627 cbiH

Methanobacteriacea ANASMEC_C9972 2014769634 cbiG

Methanobacteriacea ANASMEC_C9972 2014769635 cbiG

Methanobacteriacea ANASMEC_C9972 2014769636 cbiB

Methanobacteriacea ANASMEC_C9974 2014769689 cbiA



Methanospirillum ANASMEC_C3080 2014742893 cbiE

Methanospirillum ANASMEC_C3080 2014742895 cbiF

Methanospirillum ANASMEC_C3080 2014742896 cbiG

Methanospirillum ANASMEC_C3081 2014742897 cbiH

Methanospirillum ANASMEC_C3081 2014742898 cbiC

Methanospirillum ANASMEC_C3081 2014742899 cbiD

Methanospirillum ANASMEC_C3081 2014742900 cbiE

Methanospirillum ANASMEC_C4547 2014747827 cbiP

Methanospirillum ANASMEC_C5014 2014749563 cbiA

Methanospirillum ANASMEC_C5014 2014749564 cbiA

Methanospirillum ANASMEC_C6921 2014755836 cobS

Methanospirillum ANASMEC_C8670 2014764303 cbiB

Methanospirillum ANASMEC_C8670 2014764304 cbiB

Synergistetes ANASMEC_C10090 2014770870 cobT

Synergistetes ANASMEC_C6473 2014754522 cbiD

Synergistetes ANASMEC_C6473 2014754523 cbiE

Synergistetes ANASMEC_C6473 2014754524 cbiE

Synergistetes ANASMEC_C6473 2014754525 cbiF

Synergistetes ANASMEC_C6475 2014754530 cobS

Synergistetes ANASMEC_C6475 2014754532 cobU

Synergistetes ANASMEC_C726 2014734551 cobT

Synergistetes ANASMEC_C726 2014734552 cobU

unknown Delta-

proteobacterium ANASMEC_C7396 2014758181 cibK

unidentified Class 6 ANASMEC_C9945 2014769400 cobA

unidentified Class 6 ANASMEC_C9946 2014769403 cobS

unidentified Class 6 ANASMEC_C9946 2014769404 cobS

unidentified Class 6 ANASMEC_C9946 2014769406 cobU

unidentified Class 9 ANASMEC_C2876 2014742219 cobA

unclassified ANASMEC_C2768 2014741815 cbiL

unclassified ANASMEC_C2768 2014741816 cbiL

186

Taxa


JGI IMG

Gene Object ID

Gene

Name

unclassified ANASMEC_C2768 2014741817 cibT

unclassified ANASMEC_C2768 2014741818 cibE

unclassified ANASMEC_C2768 2014741819 cbiD

unclassified ANASMEC_C2768 2014741820 cbiC

unclassified ANASMEC_C2768 2014741821 cbiA

unclassified ANASMEC_C2768 2014741822 cbiP

ANASMEC_C202 2014732832 cbiG

ANASMEC_C727 2014734554 cbiB

ANASMEC_C728 2014734556 cbiP

ANASMEC_C1628 2014737706 cbiA



ANASMEC_C2767 2014741814 cbiF

ANASMEC_C2834 2014741992 cobS

ANASMEC_C3069 2014742870 cbiH






ANASMEC_C3520 2014744222 cobA

ANASMEC_C4447 2014747522 cbiK

ANASMEC_C4867 2014749135 cobN



ANASMEC_C4972 2014749454 cbiL


ANASMEC_C5703 2014751998 cbiE

ANASMEC_C5703 2014751999 cbiE

ANASMEC_C5921 2014752768 cbiC


ANASMEC_C6089 2014753304 cbiD






ANASMEC_C7395 2014758176 cbiK

ANASMEC_C7395 2014758177 cbiL

187

Taxa


JGI IMG

Gene Object ID

Gene

Name

ANASMEC_C7713 2014759650 cobU















ANASMEC_FYHO897_b1 2014776303 cbiP

ANASMEC_FYHO3513_b1 2014774922 cbiK

ANASMEC_FYHO5065_b1 2014775389 cobS

ANASMEC_FYHO7312_g1 2014775985 cbiK

ANASMEC_FYHO8764_g1 2014776259 cbiF

ANASMEC_FYHO10859_b1 2014776666 cobN

ANASMEC_FYHO10859_g1 2014776668 cobN

ANASMEC_FYHO11194_b1 2014776741 cbiE

ANASMEC_FYHO11194_g1 2014776742 cbiB

ANASMEC_FYHO11194_g1 2014776743 cbiA

ANASMEC_FYHO11245_g1 2014776755 cobU

ANASMEC_FYHO13996_b1 2014777397 cbiB

ANASMEC_FYHO21893_g1 2014779438 cobA

ANASMEC_FYHO23079_b1 2014779767 cbiF

ANASMEC_FYHO24439_b1 2014780009 cbiC

ANASMEC_FYHO24439_g1 2014780010 cbiP


ANASMEC_FYHO27856_b1 2014780805 cbiD

ANASMEC_FYHO30996_b1 2014781682 cbiG

ANASMEC_FYHO30996_g1 2014781684 cbiX


ANASMEC_FYHO45647_g1 2014783570 cbiP

ANASMEC_FYHO55308_g1 2014785885 cobA

ANASMEC_FYHO55308_g1 2014785886 cbiT

188

Taxa


JGI IMG

Gene Object ID

Gene

Name

ANASMEC_FYHO55674_g1 2014785970 cobU


ANASMEC_FYHO64873_g3 2014788076 cbiH



ANASMEC_FYHO71871_b1 2014789709 cbiL

ANASMEC_FYHO72545_b1 2014789888 cbiA


ANASMEC_FYHO76378_b1 2014790734 cobA

ANASMEC_FYHO81740_g1 2014792002 cobS

ANASMEC_GCAX02227_c1_1000_100_1 2014792982 cbiH

ANASMEC_GCAX02227_c1_1000_100_1 2014792983 cbiJ

ANASMEC_GCAX04797_c1_1000_100_1 2014793287 cbiA

ANASMEC_GCAX10475_c1_1000_100_1 2014794041 cobU

ANASMEC_GCAX11080_c1_1000_100_1 2014794138 cbiP

ANASMEC_GCAX11638_c1_1000_100_1 2014794222 cbiL

189

Appendix 7:

Bacterial and archaeal sequenced genomes lacking genes for methylene tetrahydrofolate

reductase (MTHFR)

190

Appendix 7. Bacterial and archaeal sequenced genomes lacking genes for methylene

tetrahydrofolate reductase (MTHFR)

Bacteria and Archaea Lacking MTHFR Genes

Acholeplasma_laidlawii_PG_8A

Aciduliprofundum_boonei_T469

Aciduliprofundum_MAR08_339

Actinobacillus_succinogenes_130Z

Aeropyrum_pernix_K1

Aminobacterium_colombiense_DSM_12261

Anaerococcus_prevotii_DSM_20548

Anaplasma_centrale_Israel

Anaplasma_marginale_Florida

Anaplasma_marginale_Maries

Anaplasma_phagocytophilum_HZ

Arthrobacter_arilaitensis_Re117

Aster_yellows_witches_broom_phytoplasma_AYWB

Atopobium_parvulum_DSM_20469

bacterium_BT_1

Bartonella_bacilliformis_KC583

Bartonella_clarridgeiae_73

Bartonella_grahamii_as4aup

Bartonella_henselae_Houston_1

Bartonella_quintana_RM_11

Bartonella_quintana_Toulouse

Bartonella_tribocorum_CIP_105476

Bdellovibrio_bacteriovorus_HD100

Bdellovibrio_bacteriovorus_Tiberius

Borrelia_afzelii_HLJ01

Borrelia_afzelii_PKo

Borrelia_afzelii_PKo

Borrelia_bissettii_DN127

Borrelia_burgdorferi_B31

Borrelia_burgdorferi_JD1

Borrelia_burgdorferi_N40

Borrelia_burgdorferi_ZS7

Borrelia_crocidurae_Achema

Borrelia_duttonii_Ly

Borrelia_garinii_BgVir

Borrelia_garinii_NMJW1

Borrelia_garinii_PBi

191


Borrelia_hermsii_DAH

Borrelia_recurrentis_A1

Borrelia_turicatae_91E135

Buchnera_aphidicola__Cinara_tujafilina_

Caldisericum_exile_AZM16c01

Campylobacter_hominis_ATCC_BAA_381

Campylobacter_lari_RM2100

Candidatus_Amoebophilus_asiaticus_5a2

Candidatus_Arthromitus_SFB_mouse_Japan

Candidatus_Arthromitus_SFB_mouse_Yit

Candidatus_Arthromitus_SFB_rat_Yit

Candidatus_Cloacamonas_acidaminovorans

Candidatus_Hamiltonella_defensa_5AT__Acyrthosiphon_pisum_

Candidatus_Kinetoplastibacterium_blastocrithidii__ex_Strigomonas_culicis_

Candidatus_Kinetoplastibacterium_crithidii__ex_Angomonas_deanei_ATCC_30255_

Candidatus_Liberibacter_asiaticus_psy62

Candidatus_Liberibacter_solanacearum_CLso_ZC1

Candidatus_Midichloria_mitochondrii_IricVA

Candidatus_Moranella_endobia_PCIT

Candidatus_Mycoplasma_haemolamae_Purdue

Candidatus_Pelagibacter_IMCC9063

Candidatus_Phytoplasma_australiense

Candidatus_Phytoplasma_mali

Candidatus_Protochlamydia_amoebophila_UWE25

Candidatus_Rickettsia_amblyommii_GAT_30V

Candidatus_Riesia_pediculicola_USDA

Candidatus_Sulcia_muelleri_CARI

Candidatus_Sulcia_muelleri_DMIN

Candidatus_Sulcia_muelleri_GWSS

Candidatus_Sulcia_muelleri_SMDSEM

Capnocytophaga_canimorsus_Cc5

Cardinium_endosymbiont_cEper1_of_Encarsia_pergandiella

Chlamydia_muridarum_Nigg

Chlamydia_psittaci_01DC12

Chlamydia_psittaci_84_55

Chlamydia_psittaci_GR9

Chlamydia_psittaci_M56

Chlamydia_psittaci_MN

Chlamydia_psittaci_VS225

Chlamydia_psittaci_WC

192


Chlamydia_psittaci_WS_RT_E30

Chlamydia_trachomatis_434_Bu

Chlamydia_trachomatis_A_HAR_13

Chlamydia_trachomatis_A2497

Chlamydia_trachomatis_A2497

Chlamydia_trachomatis_B_Jali20_OT

Chlamydia_trachomatis_B_TZ1A828_OT

Chlamydia_trachomatis_D_EC

Chlamydia_trachomatis_D_LC

Chlamydia_trachomatis_D_UW_3_CX

Chlamydia_trachomatis_E_11023

Chlamydia_trachomatis_E_150

Chlamydia_trachomatis_E_SW3

Chlamydia_trachomatis_F_SW4

Chlamydia_trachomatis_F_SW5

Chlamydia_trachomatis_G_11074




Chlamydia_trachomatis_L2b_UCH_1_proctitis

Chlamydia_trachomatis_L2c

Chlamydia_trachomatis_Sweden2

Chlamydophila_abortus_S26_3

Chlamydophila_caviae_GPIC

Chlamydophila_felis_Fe_C_56

Chlamydophila_pecorum_E58

Chlamydophila_pneumoniae_AR39

Chlamydophila_pneumoniae_CWL029

Chlamydophila_pneumoniae_J138

Chlamydophila_pneumoniae_LPCoLN

Chlamydophila_pneumoniae_TW_183

Chlamydophila_psittaci_01DC11



Chlamydophila_psittaci_6BC

Chlamydophila_psittaci_6BC

Chlamydophila_psittaci_C19_98

Chlamydophila_psittaci_CP3

Chlamydophila_psittaci_Mat116

Chlamydophila_psittaci_NJ1

193


Chlamydophila_psittaci_RD1

Clostridiales_genomosp__BVAB3_UPII9_5

Cryptobacterium_curtum_DSM_15641

cyanobacterium_UCYN_A

Dehalococcoides_BAV1

Dehalococcoides_CBDB1

Dehalococcoides_ethenogenes_195

Dehalococcoides_GT

Dehalococcoides_VS

Desulfurococcus_fermentans_DSM_16532

Desulfurococcus_kamchatkensis_1221n

Desulfurococcus_mucosus_DSM_2162

Eggerthella_lenta_DSM_2243

Eggerthella_YY7918

Ehrlichia_canis_Jake

Ehrlichia_chaffeensis_Arkansas

Ehrlichia_ruminantium_Gardel

Ehrlichia_ruminantium_Welgevonden

Ehrlichia_ruminantium_Welgevonden

Enterococcus_faecalis_62

Enterococcus_faecalis_D32

Enterococcus_faecalis_OG1RF

Enterococcus_faecalis_Symbioflor_1

Enterococcus_faecalis_V583

Enterococcus_faecium_Aus0004

Enterococcus_faecium_DO

Enterococcus_faecium_NRRL_B_2354

Enterococcus_hirae_ATCC_9790

Erysipelothrix_rhusiopathiae_Fujisawa

Fervidicoccus_fontis_Kam940

Filifactor_alocis_ATCC_35896

Finegoldia_magna_ATCC_29328

Flavobacterium_psychrophilum_JIP02_86

Francisella_cf__novicida_3523

Francisella_cf__novicida_Fx1

Francisella_noatunensis_orientalis_Toba_04

Francisella_novicida_U112

Francisella_tularensis_FSC198

Francisella_tularensis_holarctica_F92

Francisella_tularensis_holarctica_FSC200

194


Francisella_tularensis_holarctica_FTNF002_00

Francisella_tularensis_holarctica_LVS

Francisella_tularensis_holarctica_OSU18

Francisella_tularensis_mediasiatica_FSC147

Francisella_tularensis_NE061598

Francisella_tularensis_SCHU_S4

Francisella_tularensis_TI0902

Francisella_tularensis_TIGB03

Francisella_tularensis_WY96_3418

Haemophilus_ducreyi_35000HP

Halobacterium_NRC_1

Halobacterium_salinarum_R1

Helicobacter_acinonychis_Sheeba

Helicobacter_bizzozeronii_CIII_1

Helicobacter_cetorum_MIT_00_7128

Helicobacter_cetorum_MIT_99_5656

Helicobacter_felis_ATCC_49179

Helicobacter_mustelae_12198

Helicobacter_pylori

Helicobacter_pylori_2017



Helicobacter_pylori_35A




Helicobacter_pylori_Aklavik117

Helicobacter_pylori_Aklavik86

Helicobacter_pylori_B38

Helicobacter_pylori_B8

Helicobacter_pylori_Cuz20

Helicobacter_pylori_ELS37

Helicobacter_pylori_F16




Helicobacter_pylori_G27

Helicobacter_pylori_Gambia94_24

Helicobacter_pylori_HPAG1

Helicobacter_pylori_HUP_B14

195


Helicobacter_pylori_India7

Helicobacter_pylori_J99

Helicobacter_pylori_Lithuania75

Helicobacter_pylori_P12

Helicobacter_pylori_PeCan18

Helicobacter_pylori_PeCan4

Helicobacter_pylori_Puno120

Helicobacter_pylori_Puno135

Helicobacter_pylori_Rif1

Helicobacter_pylori_Rif2

Helicobacter_pylori_Sat464

Helicobacter_pylori_Shi112




Helicobacter_pylori_SJM180

Helicobacter_pylori_SNT49

Helicobacter_pylori_SouthAfrica7

Helicobacter_pylori_v225d

Helicobacter_pylori_XZ274

Idiomarina_loihiensis_L2TR

Ignisphaera_aggregans_DSM_17230

Kosmotoga_olearia_TBF_19_5_1

Kytococcus_sedentarius_DSM_20547

Lactobacillus_brevis_ATCC_367

Lactobacillus_gasseri_ATCC_33323

Lactobacillus_johnsonii_DPC_6026

Lactobacillus_johnsonii_FI9785

Lactobacillus_johnsonii_NCC_533

Lactobacillus_reuteri_SD2112

Lactobacillus_ruminis_ATCC_27782

Lactobacillus_sakei_23K

Lactococcus_garvieae_ATCC_49156

Lactococcus_garvieae_Lg2

Lawsonia_intracellularis_N343

Lawsonia_intracellularis_PHE_MN1_00

Legionella_longbeachae_NSW150

Melissococcus_plutonius_ATCC_35311

Mesoplasma_florum_L1

Micavibrio_aeruginosavorus_ARL_13

196


Micrococcus_luteus_NCTC_2665

Moraxella_catarrhalis_RH4

Mycoplasma_agalactiae

Mycoplasma_agalactiae_PG2

Mycoplasma_arthritidis_158L3_1

Mycoplasma_bovis_HB0801

Mycoplasma_bovis_Hubei_1

Mycoplasma_bovis_PG45

Mycoplasma_capricolum_ATCC_27343

Mycoplasma_conjunctivae_HRC_581

Mycoplasma_crocodyli_MP145

Mycoplasma_cynos_C142

Mycoplasma_fermentans_JER

Mycoplasma_fermentans_M64

Mycoplasma_gallisepticum_CA06_2006_052_5_2P

Mycoplasma_gallisepticum_F

Mycoplasma_gallisepticum_NC06_2006_080_5_2P

Mycoplasma_gallisepticum_NC08_2008_031_4_3P

Mycoplasma_gallisepticum_NC95_13295_2_2P

Mycoplasma_gallisepticum_NC96_1596_4_2P

Mycoplasma_gallisepticum_NY01_2001_047_5_1P

Mycoplasma_gallisepticum_R_high_

Mycoplasma_gallisepticum_R_low_

Mycoplasma_gallisepticum_VA94_7994_1_7P

Mycoplasma_gallisepticum_WI01_2001_043_13_2P

Mycoplasma_genitalium_G37

Mycoplasma_genitalium_M2288




Mycoplasma_haemocanis_Illinois

Mycoplasma_haemofelis_Langford_1

Mycoplasma_haemofelis_Ohio2

Mycoplasma_hominis_ATCC_23114

Mycoplasma_hyopneumoniae_168



Mycoplasma_hyopneumoniae_J

Mycoplasma_hyorhinis_GDL_1

Mycoplasma_hyorhinis_HUB_1

197


Mycoplasma_hyorhinis_MCLD

Mycoplasma_hyorhinis_SK76

Mycoplasma_leachii_99_014_6

Mycoplasma_leachii_PG50

Mycoplasma_mobile_163K

Mycoplasma_mycoides_capri_LC_95010

Mycoplasma_mycoides_SC_PG1

Mycoplasma_penetrans_HF_2

Mycoplasma_pneumoniae_309

Mycoplasma_pneumoniae_FH

Mycoplasma_pneumoniae_M129

Mycoplasma_pulmonis_UAB_CTIP

Mycoplasma_putrefaciens_KS1

Mycoplasma_suis_Illinois

Mycoplasma_suis_KI3806

Mycoplasma_synoviae_53

Mycoplasma_wenyonii_Massachusetts

Nanoarchaeum_equitans_Kin4_M

Neorickettsia_risticii_Illinois

Neorickettsia_sennetsu_Miyayama

Oenococcus_oeni_PSU_1

Olsenella_uli_DSM_7084

Onion_yellows_phytoplasma_OY_M

Orientia_tsutsugamushi_Boryong

Orientia_tsutsugamushi_Ikeda

Parachlamydia_acanthamoebae_UV7

Pediococcus_pentosaceus_ATCC_25745

Porphyromonas_asaccharolytica_DSM_20707

Porphyromonas_gingivalis_ATCC_33277

Porphyromonas_gingivalis_TDC60

Porphyromonas_gingivalis_W83

Prevotella_denticola_F0289

Prevotella_intermedia_17

Propionibacterium_acnes_266

Propionibacterium_acnes_6609

Propionibacterium_acnes_ATCC_11828

Propionibacterium_acnes_C1

Propionibacterium_acnes_KPA171202

Propionibacterium_acnes_SK137

Propionibacterium_acnes_TypeIA2_P_acn33

198


Pyrococcus_yayanosii_CH1

Rickettsia_africae_ESF_5

Rickettsia_akari_Hartford

Rickettsia_australis_Cutlack

Rickettsia_bellii_OSU_85_389

Rickettsia_bellii_RML369_C

Rickettsia_canadensis_CA410

Rickettsia_canadensis_McKiel

Rickettsia_conorii_Malish_7

Rickettsia_felis_URRWXCal2

Rickettsia_heilongjiangensis_054

Rickettsia_japonica_YH

Rickettsia_massiliae_AZT80

Rickettsia_massiliae_MTU5

Rickettsia_montanensis_OSU_85_930

Rickettsia_parkeri_Portsmouth

Rickettsia_peacockii_Rustic

Rickettsia_philipii_364D

Rickettsia_prowazekii_BuV67_CWPP

Rickettsia_prowazekii_Chernikova

Rickettsia_prowazekii_Dachau

Rickettsia_prowazekii_GvV257

Rickettsia_prowazekii_Katsinyian

Rickettsia_prowazekii_Madrid_E

Rickettsia_prowazekii_Rp22

Rickettsia_prowazekii_RpGvF24

Rickettsia_rhipicephali_3_7_female6_CWPP

Rickettsia_rickettsii__Sheila_Smith_

Rickettsia_rickettsii_Arizona

Rickettsia_rickettsii_Brazil

Rickettsia_rickettsii_Colombia

Rickettsia_rickettsii_Hauke

Rickettsia_rickettsii_Hino

Rickettsia_rickettsii_Hlp_2

Rickettsia_rickettsii_Iowa

Rickettsia_slovaca_13_B

Rickettsia_slovaca_D_CWPP

Rickettsia_typhi_B9991CWPP

Rickettsia_typhi_TH1527

Rickettsia_typhi_Wilmington

199


secondary_endosymbiont_of_Ctenarytaina_eucalypti

secondary_endosymbiont_of_Heteropsylla_cubana_Thao2000

Serratia_symbiotica__Cinara_cedri_

Simkania_negevensis_Z

Staphylothermus_marinus_F1

Streptobacillus_moniliformis_DSM_12112

Streptococcus_dysgalactiae_equisimilis_AC_2713

Streptococcus_dysgalactiae_equisimilis_ATCC_12394

Streptococcus_dysgalactiae_equisimilis_GGS_124

Streptococcus_dysgalactiae_equisimilis_RE378

Streptococcus_equi_4047

Streptococcus_equi_zooepidemicus

Streptococcus_equi_zooepidemicus_ATCC_35246

Streptococcus_equi_zooepidemicus_MGCS10565

Streptococcus_intermedius_JTH08

Streptococcus_parauberis_KCTC_11537

Streptococcus_pyogenes_A20

Streptococcus_pyogenes_Alab49

Streptococcus_pyogenes_M1_GAS

Streptococcus_pyogenes_Manfredo

Streptococcus_pyogenes_MGAS10270











Streptococcus_pyogenes_NZ131

Streptococcus_pyogenes_SSI_1

Streptococcus_uberis_0140J

Taylorella_asinigenitalis_MCE3

Taylorella_equigenitalis_ATCC_35865

Taylorella_equigenitalis_MCE9

Tetragenococcus_halophilus

Thermococcus_4557

Thermococcus_AM4

200


Thermococcus_barophilus_MP

Thermococcus_CL1

Thermococcus_gammatolerans_EJ3

Thermococcus_onnurineus_NA1

Thermococcus_sibiricus_MM_739

Thermosphaera_aggregans_DSM_11486

Treponema_denticola_ATCC_35405

Tropheryma_whipplei_TW08_27

Tropheryma_whipplei_Twist

Ureaplasma_parvum_serovar_3_ATCC_27815

Ureaplasma_parvum_serovar_3_ATCC_700970

Ureaplasma_urealyticum_serovar_10_ATCC_33699

Waddlia_chondrophila_WSU_86_1044

Weeksella_virosa_DSM_16922

Wigglesworthia_glossinidia_endosymbiont_of_Glossina_brevipalpis

Wigglesworthia_glossinidia_endosymbiont_of_Glossina_morsitans__Yale_colony_

Wolbachia_endosymbiont_of_Culex_quinquefasciatus_Pel

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