Natural Science, 2014, 6, 323-337 Published Online March 2014 in SciRes. http://www.scirp.org/journal/ns http://dx.doi.org/10.4236/ns.2014.65034

How to cite this paper: Romão-Dumaresq, A.S., et al. (2014) Towards a Comprehensive Search of Putative Chitinases Se-quences in Environmental Metagenomic Databases. Natural Science, 6, 323-337. http://dx.doi.org/10.4236/ns.2014.65034

Towards a Comprehensive Search of Putative Chitinases Sequences in Environmental Metagenomic Databases Aline S. Romão-Dumaresq1, Adriana M. Fróes1, Rafael R. C. Cuadrat1, Floriano P. Silva Jr.2,3, Alberto M. R. Dávila1,3* 1Laboratório de Biologia Computacional e Sistemas, Instituto Oswaldo Cruz (IOC), FIOCRUZ, Rio de Janeiro, Brazil 2Laboratório de Bioquímica de Proteínas e Peptídeos, Instituto Oswaldo Cruz (IOC), FIOCRUZ, Rio de Janeiro, Brazil 3Pólo de Biologia Computacional e Sistemas, Instituto Oswaldo Cruz (IOC), FIOCRUZ, Rio de Janeiro, Brazil Email: *davila@fiocruz.br Received 26 October 2013; revised 26 November 2013; accepted 6 December 2013

Copyright © 2014 by authors and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/

Abstract Chitinases catalyze the hydrolysis of chitin, a linear homopolymer of β-(1,4)-linked N-acetylglu- cosamine. The broad range of applications of chitinolytic enzymes makes their identification and study very promising. Metagenomic approaches offer access to functional genes in uncultured representatives of the microbiota and hold great potential in the discovery of novel enzymes, but tools to extensively explore these data are still scarce. In this study, we develop a chitinase mining pipeline to facilitate the comprehensive search of these enzymes in environmental metagenomic databases and also to explore phylogenetic relationships among the retrieved sequences. In order to perform the analyses, UniprotKB fungal and bacterial chitinases sequences belonging to the glycoside hydrolases (GH) family-18, 19 and 20 were used to generate 15 reference datasets, which were then used to generate high quality seed alignments with the MAFFT program. Profile Hidden Markov Models (pHMMs) were built from each seed alignment using the hmmbuild pro- gram of HMMER v3.0 package. The best-hit sequences returned by hmmsearch against two envi- ronmental metagenomic databases (Community Cyberinfrastructure for Advanced Microbial Eco- logy Research and Analysis—CAMERA and Integrated Microbial Genomes—IMG/M) were retrieved and further analyzed. The NJ trees generated for each chitinase dataset showed some variability in the catalytic domain region of the metagenomic sequences and revealed common sequence pat- terns among all the trees. The scanning of the retrieved metagenomic sequences for chitinase con- served domains/signatures using both the InterPro and the RPS-BLAST tools confirmed the effi- cacy and sensitivity of our pHMM-based approach in detecting putative chitinases sequences.

*Corresponding author.

http://www.scirp.org/journal/nshttp://dx.doi.org/10.4236/ns.2014.65034http://dx.doi.org/10.4236/ns.2014.65034http://www.scirp.orgmailto:davila@fiocruz.brhttp://creativecommons.org/licenses/by/4.0/

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These analyses provide insight into the potential reservoir of novel molecules in metagenomic databases while supporting the chitinase mining pipeline developed in this work. By using our chitinase mining pipeline, a larger number of previously unannotated metagenomic chitinase se-quences can be classified, enabling further studies on these enzymes.

Keywords Chitinase; Metagenome; pHMM; Sequence Search

1. Introduction Enzymes are catalysts that support the development of environmental-friendly industrial processes. At present, most of the industrial enzymes of major importance are of microbial origin, so the search for novel of these cat- alysts is a key step towards the development of innovative bioprocesses. Chitinases are enzymes responsible for the hydrolysis of chitin, a linear homopolymer of β-(1,4)-linked N-acetylglucosamine, which is the second most abundant biopolymer in nature. A set of different enzymes are needed to drive the complete hydrolysis of chitin to free N-acetylglucosamine (GlcNAc), involving diverse mode of actions known to be synergistic and consecu- tive [1] [2]. The endochitinases (EC 3.2.1.14) randomly cleave the chitin chain at internal sites, whilst the exo-chitinases (EC 3.2.1.52) catalyze either the successive removal of sugar unit from the non-reducing end or the hydrolysis of terminal non-reducing sugar [3] [4].

Based on amino acid sequence similarities these chitinolytic enzymes are classified into glycoside hydrolases (GH) family 18, 19 and 20 [5] [6]. GH family-18 and 20 are thought to have a common evolutionary ancestry, since they possess significant similarity in their tertiary structure, catalytic residues and mechanism. GH family- 18 exhibit considerable variability in evolutionary terms and comprises chitinases from bacteria, fungi, viruses, insect and plants [7]. GH family-19 contains plant, bacteria and some Streptomyces chitinases, and GH family- 20 includes the β-N-acetylhexosaminidases from bacteria, fungi, Streptomyces and humans [4] [7]. These enzymes have widespread applications, such as in bioremediation [8], biological control [9]-[11], production of chitooli-gosaccharides [12]-[14], preparation of single-cell protein [15] and isolation of protoplasts from fungi [16].

The low discovery rate of novel natural products from culturable microorganisms [17] coupled with the fact that only a small portion (estimated less than 1%) of the microbial community is capable of growing under ar- tificial conditions [18] [19] has brought about the need to explore metagenomic approaches to speed up the find- ing of new biomolecules potentially useful in biotechnology [20]. To date, a great number of environmental me- tagenomic studies were performed, such as the extensive studies on the Sargasso Sea [21] and the Global Ocean Expedition [22] [23], and as a result, a huge amount of sequence data has been generated but has not been en-tirely explored. Different projects have been implemented to provide an open infrastructure for metagenomic sequence data storage and analysis, as CAMERA (“Community Cyberinfrastructure for Advanced Microbial Ecology Research & Analysis”) [24], MG-RAST (“Metagenomic Rapid Annotation using Subsystem Technol-ogy”) [25], and IMG/M (“Integrated Microbial Genomes”) [26]. The current challenge is to fully exploit the metagenomic sequence information using appropriate data-management and data-analysis methods.

Typical metagenomic analyses rely on similarity search against some databases, followed by annotation of the output. The most frequently used similarity search tool is BLAST [27], but as it requires significant computa- tional capacity for large datasets, faster searching tools have been developed, such as Pattern-Hunter [28] [29] and BLAT [30]. However, comprehensive searches on specific genes or gene families require more sensitive tools to be used. Therefore, methods are needed to find subtler similarities between sequences and to assign put-ative structure and functional characterization to new proteins [31]. Pipelines based on Hidden Markov Model (HMM) [32] are very promising since this is a statistical representation of a protein family conservation pattern extracted from multiple alignment of sequences, which has been demonstrated to be very effective in detecting distantly related homologues [33]-[35].

The aim of this work was to develop and validate a data mining strategy based on profile HMM (pHMM) in order to be able to broadly explore environmental metagenomic databases for putative chitinase sequences. The results confirmed the efficacy of our pipeline in detecting chitinase sequences and highlighted the power of pHMM-based strategies to identify remote homologues.

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2. Methodology 2.1. Collection of Chitinase Reference Sequences Fungal and bacterial curated amino acid sequences of chitinases belonging to the glycoside hydrolase (GH) fam- ilies 18, 19 and 20 were retrieved from the UniprotKB version 2011-06 database (http://www.uniprot.org) on July 2011. A total of 170, 13 and 46 sequences were collected for GH family-18, GH family-19 and GH family- 20, respectively. GH family-18 sequences UniprotKB IDs were: P04067, P36912, P80036, F3Y8V4, D6ESW9, F3NDC4, O83008, Q6T6I1, P07254, A8G807, Q9ALZ0, Q8KKF5, Q9L5D5, Q43919, Q25BN2, Q8GHI4, P32823, A7M6A0, Q9WX41, Q9AMP1, C3LU56, D2YR61, D2YAB4, Q48373, Q5MYT4, Q9RCG5, Q56077, Q845S2, O30678, Q09IY6, Q6BCF8, A5YRG4, B7UB89, P20533, Q48494, Q9KHB3, C6IW88, B1VBB0, A6FD95, P96168, A6CVZ0, Q9CE95, Q7PC52, Q9Z493, Q59143, Q59924, Q9KY99, Q59141, D0VV10, D0VV09, Q81A65, D5TUL7, P11797, A6B8H6, A7LHM6, B2TQ75, B8DGV4, C1IAI6, D0ELI3, D0WTF8, D1RSJ9, D3YGV3, E3YUT8, F3RZA6, O50076, Q0MRC3, Q1EM71, Q547S1, Q5WKC0, Q8KWS2, Q99PX0, Q9KED7, Q9REI6, O69311, D5ZUF3, D6EQC0, O86826, Q9S5K1, Q05638, Q09WI7, A0Q8N1, F4BBA4, E2MRS9, B2SEL0, P36909, Q6A4C3, Q700B8, Q75ZW9, Q7PC51, Q8KVU8, Q9L8G0, Q9Z9M8, Q9ZIX2, Q8RQP6, B1W0A0, D6ANP5, A4GZI8, B5H9B1, D5ZXC4, P11220, P27050, Q9Z9M7, E3FMX3, Q099U8, Q1CZN0, Q092X1, C6J4E8, E8U3R7, D6EPZ7, D9XVU0, D9XI74, B5I3A2, A7UGE4, Q12735, Q9UV45, Q9UV49, A6YNL9, Q99006, P48827, Q9C1T8, Q9C1T7, Q9C1T6, O59928, Q9C1U0, Q65YQ7, Q9C1T4, Q9C1T9, O14456, Q9Y841, A9LI60, Q8J042, Q5MNU1, A6Y9S8, P32470, Q870C0, Q873X9, Q06HA3, Q3YLC5, Q9HGU5, Q92222, Q9HEW6, Q9P4Q1, Q5YLC0, A6YJX1, Q4FCX2, Q92270, Q7Z8C9, Q8J1Y3, Q96VR2, E5KCK8, A5JV26, A3RLY3, A5X8W3, Q96UW2, A2VEC4, Q8NJQ4, D6N0Y7, D6N0Y8, F6MIV5, E5LEW9, A2SW11, E9F7R6, P29026, P29027, P29025, P54197, P40954, P40953, P29029, P46876. GH family-19 sequences UniprotKB IDs were: Q9WXI9, Q59I46, Q9LBM0, Q8GI53, Q9S6T0, Q8CK55, B3XZQ2, O50152, Q9Z4P2, Q5J1K1, Q9RHU4, Q9RHU5, Q25BT4. GH family-20 sequences UniprotKB IDs were: Q9F9B4, Q75V90, A7M7B5, Q9LC82, Q7WUL4, Q9L448, Q9ZN69, Q9WXH9, D2KW09, P49008, A1XNE6, P49007, Q8VUM1, Q9R6Y9, Q9FAC5, Q9ZH38, Q7PC48, Q7PC49, Q54468, P49610, Q9ACN7, O85361, Q83WL6, Q9RHV6, Q84FS9, P96155, D9ISD9, D9ISE0, P13670, Q60081, Q04786, C8VMN3, Q8J2T0, A2SW08, P43077, Q309C3, P13723, Q643Y1, Q9URR8, E3NYM0, P87258, Q0ZLH7, P78738, P78739, Q8NIN7, Q8NIN6. The great sequence diversity found in the GH family-18 required the partitioning of it into nine subsets of bacterial sequences and three subsets of fungal sequences. This division was carried out taking into account both the existing chitinase subfamilies and a Neighbor-Joining guide tree topology. The re- trieved sequences were then used to generate 15 multi-fasta chitinase reference sets (with 12 GH family-18, one GH family-19 and two GH family-20 sets).

2.2. Environmental Metagenomic Databases Two environmental metagenomic databases were selected to test our chitinase mining strategy. The first one was CAMERA v2.0 [36], available at http://camera.calit2.net/, which contains 84 unannotated metagenomic da- tasets with 135,704,056,943 nucleotide sequences. Six-frame translation of the nucleotide sequences was per- formed using the EMBOSS Transeq tool available at http://www.ebi.ac.uk/Tools/st/ and a total of 75 Gb of se- quences were generated. The second database was IMG/M [26], available at http://img.jgi.doe.gov/cgi-bin/m/main.cgi/, which includes 364 automatically annotated metagenomic datasets containing 119,059,610 amino acid sequences, making a total of 20 Gb. Database sequences were downloaded to a local server by June 2011.

2.3. Construction of Profiles HMM and Search for Putative Chitinase Homologues First, multiple sequence alignments were generated for each chitinase reference set (seed alignments) using the default settings (“-auto”) of MAFFT v6.717b program [37] [38]. Alignment visualizations were carried out in Jalview version 2 [39]. The quality of each seed alignment was controlled by manual checking and, in a few cases, manual editing was necessary. Profile HMMs (pHMMs) were then built from each seed alignment using the hmmbuild program of HMMER v3.0 package (http://hmmer.janelia.org/). The 15 pHMMs generated were used to perform sequence database searches with the hmmsearch program also of the HMMER v3.0 package and an e-value threshold of 1.0E−05 against the two environmental databases CAMERA and IMG/M.

http://www.uniprot.org/http://camera.calit2.net/http://www.ebi.ac.uk/Tools/st/http://img.jgi.doe.gov/cgi-bin/m/main.cgi/http://hmmer.janelia.org/

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2.4. Mining Strategy Validation The resulting sequence database searches (described in detail in Section 2.3) were used to extract the best-hit sequences of each metagenomic dataset, that is, the hits which presented the lowest e-value parameter among all the sequences of a metagenomic project. Best-hit sequences were retrieved in a fasta format using fastacmd pro-gram of BLAST package [27] [40] and then scanned for the occurrence of chitinase conserved domains/ signa-tures using both InterPro v4.7 (http://www.ebi.ac.uk/interpro/) and RPS-BLAST v.2.2.21 resources, with a e- value threshold of 1.0E−05. InterPro v4.7 combines predictive models and protein signatures from 10 member databases (Gene3D, PANTHER, Pfam, PIRSF, PRINTS, ProDom, PROSITE, SMART, SUPERFAMILY and TIGRFAMs) [41] and RPS-BLAST v2.2.21 integrates seven conserved domain databases (CDD v2.25, Pfam v.24.0, Smart v.5.1, COG v1.0, KOG, TigrFam v9.0 and Prk v.5.0). These conserved domain and protein sig- nature databases were downloaded from EBI and NCBI on October 2010. InterPro and RPS-BLAST search re-sults were parsed into spreadsheets using an in-house ruby script, and the frequency of the different chitinase conserved domain/signatures was calculated.

2.5. Phylogenetic Analysis of Putative Chitinase Sequences Best-hit sequences (described in detail in section 2.4) were selected to perform phylogenetic reconstructions us-ing the Neighbor-Joining (NJ) algorithm from MEGA 5.05 [42], p-distance model and 1000 bootstrap tests. Catalytic domain amino acid sequences from the chitinase reference sets and the selected best hit sequences were concatenated to generate a multiple sequence alignment using MAFFT v6.717b [37], which was used as query to build the NJ trees with MEGA 5.05.

3. Results The construction of chitinase-reference sequence sets was a key step in the success of the mining strategy ap- plied in this work. The collection and grouping of chitinase sequences on subsets allowed the generation of 15 chitinase groups covering all the three chitinase GH families, in which 9 were fungal GH family-18, three were bacterial GH family-18, one was bacterial GH family-19, one was fungal GH family-20 and one was bacterial GH family-20 (Figure 1). The use of these chitinase-reference subsets enabled the production of high quality multiple sequence alignments and, consequently, the properly construction of chitinase pHMMs.

The hmmsearch analysis performed against CAMERA and IMG/M metagenomic environmental databases retrieved a total of 708, 104 and 256 best-hit sequences putative of GH family-18, 19 and 20, respectively. The scanning of these sequences using a RPS-BLAST search revealed the presence of chitinase conserved domains in 74.6%, 97.1% and 97.7% of the GH family-18, GH family-19 and GH family-20 sequences, respectively (Figures 2(a)-(c)). Only a small portion of the sequences presented hits with conserved domains other than the chitinase ones (4.8% of GH family-18 and 0.8% of GH family-20). No hits sequences were 20.6% of GH fami-ly-18, whilst just 2.9% of GH family-19 and 1.6% of GH family-20 (Figures 2(a)-(c)). The InterPro search in-ferred the occurrence of chitinase signatures in 81.7%, 89.4% and 98.8% of the metagenomic sequences belong- ing to GH family-18, 19 and 20, respectively (Figures 2(d)-(f)). Compared to the RPS-BLAST search, the In-terPro analysis revealed a higher percentage of sequences hosting protein signatures other than the chitinase ones (10.3% of GH family-18, 8.7% of GH family-19 and 0.4% of GH family-20) and a smaller percentage of sequences presenting no hits against the databases examined (8.0% of GH family-18, 1.9% of GH family 19 and 0.8% of GH family 20) (Figures 2(d)-(f)).

A large difference in diversity among all the three chitinase GH families was revealed in the RPS-BLAST and the InterPro analysis. That is, GH family-19 and GH family-20 presented no more than 12 types of conserved do- mains, and most of the sequences shared the same conserved domain hits (Tables 1 and 2). In contrast, GH fam- ily-18 displayed up to 34 different sorts of conserved domains and there was not a predominant set of conserved domains to the majority of the sequences (at most, half of the sequences shared the same conserved domain hits) (Tables 1 and 2). In addition, the scanning of IMG/M sequences has showed that some sequences annotated as hypothetical protein exhibited chitinase conserved domain hits, showing the sensitivity of our mining pipeline.

The phylogenetic analysis generated NJ trees corresponding to each chitinase dataset. All datasets showed some variability in the amino acid sequence of the catalytic domain region, except for the two active site resi- dues (aspartate and glutamate in GH family-18 and 20, and two glutamates in the case of GH family-19), which

http://www.ebi.ac.uk/interpro/

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Figure 1. Workflow of the methodology applied in this study. The first step was to generate fungal and bacterial chitinase reference sets for the glycoside hydrolase (GH) families 18, 19 and 20. Fifteen subsets were created, in which 9 were fungal GH family-18, 3 were bacterial GH family-18, one was bacterial GH family-19, one was fungal GH family-20 and one was bacterial GH family-20. The second stage consisted of the generation of profile Hidden Markov Models (pHMM) for each chitinase reference sequence subset, followed by a sequence database search against CAMERA and IMG/M. The best-hit sequences of each metagenomic project were retrieved and used in the last step of our analysis. The validation of the mining strategy was carried out by performing both an InterPro and a RPS-BLAST search against protein signatures, conserved do-mains and motifs databases. The phylogenetic analysis of the metagenomic sequences together with the chitinase reference sequences generated NJ trees for each chitinase subset. were conserved in almost all sequences examined (data not shown). In addition, the NJ tree analysis also re- vealed two common sequence patterns, that is, all the trees presented metagenomic sequences phylogenetically related to characterized chitinases; and all these trees also displayed metagenomic sequences which did not cluster with any characterized chitinase (Figures 3-6). Interestingly, some metagenomic sequences annotated as

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Figure 2. Pie charts representing the percentage of metagenomic sequences (the hmmsearch best hits sequences) which ex-hibited chitinase-related domain and/or signatures after RPS-BLAST ((a), (b), (c)) and InterPro ((d), (e), (f)) searches against different conserved domain databases. The plots represent each GH family separately: GH family-18 results are presented in (a) and (d); GH family-19 in (b) and (e), and GH family-20 in (c) and (f). *Percentage of metagenomic sequences showing conserved domains other than the ones found in the representative chitinase sequences; **Percentage of metagenomic se-quences which did not find any hit in these searches against conserved domain databases. “hypothetical protein” in the IMG/M database were retrieved after running our mining pipeline and were grouped with chitinase GH family-18 reference sequences in the NJ phylogenetic analysis (Figure 4), indicating they are putative chitinase sequences.

4. Discussion The broad range of applications of chitinolytic enzymes makes their identification and study very promising. Metagenomic approaches offer access to functional genes in uncultured representatives of the microbiota and hold great potential in the discovery of novel enzymes, but tools to extensively explore these data are still scarce. This study aimed the development of a chitinase mining pipeline to facilitate the comprehensive search of these enzymes in metagenomic databases. The use of a pHMM-based strategy allowed sensitive and efficient detec- tion of putative chitinase sequences.

The generation of representative seed alignments and the selection of the homology detection method are key steps in sequence mining pipelines. The quality of an alignment is critical to its utility in different approaches, such as functional analysis, evolutionary studies and structure prediction [43]. For instance, the quality of a query and template sequence alignment is a major determinant of model quality in comparative modeling studies [44]. In fact, the higher an alignment quality, the higher the sensitivity in detecting homologous sequences [43]. However, the assignment of a high quality alignment depends on the relatedness of the sequences being aligned. Alignments of sequences sharing high levels of similarity, or about 50% identity, are generally unambiguous and easier to be automatically generated, but alignments of more distant sequences, as for some family of pro- teins (sharing 30% identity or less), usually will need to be manually checked for higher qualities. For most alignment methods, the quality increases significantly at about 20% identity [45]. The algorithm implemented in the MAFFT program is considered to be faster though still accurate compared to other methods, such as Clus- talW and T-Coffee [38], thus making this program to be considered one of the best global alignment tools cur- rently available [46] [47] and justifying the decision for using it in our mining pipeline. In this study we put some effort on properly generating chitinase reference sets representative of the different subgroups of se-quences belonging to the GH families-18, 19 and 20. Basically, well-characterized chitinase sequences were chosen and organized in subsets of at least five sequences. Seed alignments were generated and manually checked, and then used to build reliable pHMMs.

pHMMs are statistical models that use multiple alignments of homologous sequences to quantify amino acids frequencies and the position-specific probabilities for inserts and deletions along the alignment [32] [48]. They are broadly used for modeling conserved motifs of protein families since they contain more information about

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Table 1. Conserved domains hits recovered after a RPS-BLAST search using the metagenomic sequences (hmmsearch best hit sequences) against seven conserved domain databases (CDD, COG, KOG, Pfam, Prk, SMART and TIGRfam).

Chitinase family Conserved domaina Percentage (%)b Best e-value hit

GH-18

Glycosyl hydrolases family 18 (pfam00704) 51.0 2.00E−88

Glycosyl hydrolase family 18 (smart00636) 48.3 1.00E−108

GH18_chitinase (cd06548) 46.2 1.00E−111

ChiA, Chitinase (COG3325 ) 42.2 1.00E−125

GH18_chitolectin_chitotriosidase (cd02872) 40.4 1.00E−161

Chitinase (KOG2806) 39.4 8.00E−97

GH18_chitinase-like (cd00598) 35.6 2.00E−35

GH18_plant_chitinase_class_V (cd02879) 30.1 4.00E−49

GH18_zymocin_alpha (cd02878) 24.4 8.00E−33

GH18_CFLE_spore_hydrolase (cd02874) 24.0 1.00E−94

GH18_IDGF (cd02873) 23.2 4.00E−60

GH18 domain of Chitinase D (ChiD) (cd02871) 20.6 1.00E−121

GH18_3CO4_chitinase (cd06545) 19.5 3.00E−61

Predicted glycosyl hydrolase (COG3858) 17.7 5.00E−80

GH18_EndoS-like (cd06542) 15.0 2.00E−40

Fibronectin type 3 domain (smart00060) 13.4 4.00E−12

Chitinase (COG3469) 11.7 1.00E−152

Fibronectin type III domain (pfam00041) 11.4 5.00E−12

GH-19

Glycoside hydrolase family 19 chitinase domain (cd00325) 96.2 8.00E−67

Glyco_hydro_19 (pfam00182) 96.2 2.00E−69

Predicted chitinase (KOG4742) 90.4 4.00E−47

Predicted chitinase (COG3179) 54.8 5.00E−45

Uncharacterized protein chitin-binding domain (COG3979) 17.3 6.00E−33

GH-20

Glycosyl hydrolase family 20, catalytic domain (pfam00728) 96.1 1.00E−133

Chb, N-acetyl-beta-hexosaminidase (COG3525) 94.1 1.00E−132

GH20_chitobiase-like (cd06563) 92.6 1.00E−179

Beta-N-acetylhexosaminidase (KOG2499) 91.0 7.00E−80

GH20_hexosaminidase (cd02742) 90.6 1.00E−109

GH20_SpHex_like (cd06568) 89.1 1.00E−156

GH20_HexA_HexB-like (cd06562) 88.7 1.00E−155

GH20_chitobiase-like_1 (cd06570) 88.3 1.00E−151

GH20_Sm-chitobiase-like (cd06569) 87.5 1.00E−140

GH20_DspB_LnbB-like (cd06564) 84.4 1.00E−110

GH20_GcnA-like (cd06565) 65.6 6.00E−91

Glyco_hydro_20b (pfam02838) 23.8 2.00E−46 aOnly the conserved domains hits found in more than 10% of the sequences analyzed were displayed in table; bPercentage of sequences which showed hit with that conserved domain.

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Table 2. Conserved domains hits recovered after an InterPro search using the metagenomic sequences (hmmsearch best hit sequences) against ten conserved domain databases (Gene3D, PANTHER, Pfam, PIRSF, PRINTS, ProDom, PROSITE, SMART, SUPERFAMILY and TIGRfams).

Chitinase family Motif/signaturea Percentage (%)b Best e-value hit

GH-18

G3DSA:3.20.20.80 - Glyco_hydro_cat 56.2 6.20E−110

SSF51445 - (Trans)glycosidases 55.2 1.60E−104

PF00704 - Glyco_hydro_18 51.1 1.80E−110

PTHR11177 - FAMILY NOT NAMED 38.8 0.00E+00

G3DSA:2.60.40.10 - no description 19.4 1.40E−47

SM00636 – no description 16.7 1.50E−166

SSF49265 – Fibronectin type III 16.1 2.50E−22

G3DSA:3.10.50.10 – no description 13.8 3.20E−31

SSF54556 – Chitinase insertion domain 13.8 5.90E−27

PF00041 – fn3 13.7 1.10E−14

SSF49299 – PKD domain 13.0 6.10E−25

GH-19

SSF53955 - Lysozyme-like 97.1 9.30E−69

PF00182 - Glyco_hydro_19 96.2 4.50E−66

PTHR22595 - Lytic enzyme 69.2 9.30E−147

G3DSA:3.30.20.10 – no description 55.8 1.20E−27

G3DSA:1.10.530.10 – no description 47.1 1.00E−56

PTHR22595:SF11 - Class I chitinase 27.9 2.40E−76

PTHR22595:SF17 - Lytic enzyme 17.3 3.50E−56

PTHR22595:SF8 – Secreted chitinase 11.5 9.30E−147

GH-20

SSF51445 - (Trans)glycosidases 96.1 7.80E−145

G3DSA:3.20.20.80 - no description 95.7 4.00E−162

PF00728 - Glyco_hydro_20 94.9 1.40E−127

PTHR22600 – family not named 87.1 2.50E−219

PR00738 - GLHYDRLASE20 82.8 7.90E−71

SSF55545 - beta-N-acetylhexosaminidase-like domain 53.9 1.10E−42

G3DSA:3.30.379.10 – no description 51.2 5.30E−44

PF02838 - Glyco_hydro_20b 35.2 3.70E−43 aOnly the conserved domains hits found in more than 10% of the sequences analyzed were displayed in table; bPercentage of sequences which showed hit with that conserved domain. the sequence family than a single sequence [32] [48] [49]. These pHMMs have been described as very efficient to detect conserved patterns in multiple sequences [35] [50] [51] and to perform better than simple profile- sequence methods such as PSI-BLAST [48] [49]. This higher sensitivity found with pHMMs is very promising when performing comprehensive searches to find remote homologues, as is such the case in our study. Two software packages are frequently used to build pHMMs and to perform profile-sequence searches, SAM [33] and HMMER [52], but the last one has been reported as more suitable for large sequence dataset searches [53] and then was used in the analyses of the present work.

The scanning for the presence of chitinase conserved domains and motifs/signatures in the best hit sequences (the ones retrieved after the hmmsearch analysis) was carried out in order to evaluate the performance of our chitinase mining pipeline on detecting true putative chitinase sequences. Many annotation pipelines use searches against conserved domain databases since these regions are evolutionarily conserved units in proteins [54]. The recognition of a conserved domain footprint in a protein sequence usually indicates its cellular or molecular function [55] and provides more reliable protein classification than sequence similarity analysis. The RPS-Blast and InterPro searches performed in this work found high percentages of chitinase-related domains and motifs in

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Figure 3. Phylogenetic tree of fungal chitinases subset-3 (GH family-18) using the Neighbor-Joining (NJ) algorithm from MEGA 5.05, p-distance model and 1000 bootstrap tests. The “□” symbol indicates CAMERA metagenomic sequences; “Δ” indicates IMG/M metagenomic sequences; “♦” indicates UniprotKB chitinase reference sequences and “●” indicates the outgroup sequences. the best hit metagenomic sequences, validating our chitinase mining pipeline. The presence of best hit metage- nomic sequences showing no hits to any conserved domain may represent putative novel chitinases that possibly would not be identified using sequence-sequence similarity searches. Furthermore, some IMG/M metagenomic sequences annotated as hypothetical proteins resulted in hits with chitinase conserved domains in our analysis, indicating that our pipeline may have high sensitivity and it is able to detect remote homologues.

The results obtained in the RPS-Blast and InterPro analyses emphasized the large differences in diversity among the three chitinases GH families-18, 19 and 20. As described in previous reports, GH family-18 holds higher variability in evolutionary terms and contains the greatest number protein members [4] [7]. The diversity observed in the GH family-18, 19 and 20 was also assessed in the phylogenetic reconstructions for the metage- nomic and the chitinase reference sequences. Indeed, interpreting phylogenetic relationships among sequences is particularly important since it allows to infer gene function [56], genetic variability and protein evolution. Phy-logeny-based classification systems have been used before to identify enzymes in metagenomic sequence data-sets [57] [58]. Based on the phylogenetic relationships observed in the NJ trees generated in this study, two common sequence patterns were identified, one including metagenomic sequences phylogenetically related to characterized chitinases—which may help to understand their origin and classification; and the other comprising metagenomic sequences which did not cluster with any characterized chitinase—suggesting a great reservoir of putative new chitinases to be exploited in these metagenomic databases. Our results reinforced the sensitivity and efficiency of our mining pipeline in detecting putative chitinase sequences from metagenomic databases.

5. Conclusion Traditional sequence search pipelines frequently are not able to extensively exploit metagenomic databases. The current flood of sequence data from metagenomic studies and the wide range of applications of chitinases brought about the need to develop a new data search pipeline. The chitinase mining pipeline developed in this work was based on the generation of high quality seed alignments from reliable chitinase reference sets, which

Endochitinase_Saccharomyces_cerevisiae (sp|P29029|) CAM_READ_0279363247 Chitinase_1_Candida_albicans_CHT1 (sp|P46876|) Chitinase_2_Candida_albicans_CHT2 (sp|P40953|) Chitinase_3_Candida_albicans_CHT3 (sp|P40954|) Chitinase_1_Rhizopus_niveus_CHI1 (sp|P29025|) Chitinase_1_Rhizopus_oligosporus_CHI1 (sp|P29026|) Chitinase_2_Rhizopus_oligosporus_CHI2 (sp|P29027|) Endochitinase_2_Coccidioides_posadasii_CTS2 (sp|P54197|) CAM_READ_0220365223 SAM_READ_00076986 Endochitinase_precursor_Air_microbial_communities_Singapore NCBI_PEP_211960849/_DESCRIPTION_glycosyl_hydrolase_family_18 HumanDistalGut_READ_00079297 Chitinase_family_Atta_columbica_fungus_garden_and_dump Chitinase_Sediment_microbial_communities_from_Lake_Washington Chitinase_Atta_texana_internal_waste_dump Chitinase_family_Soil_microbial_communities_from_FACE_and_OTC_sites Chitinase_family_Soil_microbial_communities_from_FACE_and_OTC_sites Glycosyl_hydrolases_family_18_Dendroctonus_frontalis_Fungal_community Chitinase_family_Apterostigma_dentigerum_fungus_garden Chitinase_family_Cyphomyrmex_longiscapus_fungus_garden Beta-xylan_endohydrolase_isoenzyme_X-I_Hordeum_vulgare (tr|P93185|) Endo-14-beta-xylanase_Claviceps_purpurea_xyl2 (tr|O74717|) Xylanase_III_Trichoderma_reesei_xyn3 (tr|Q9P973|) Endo-14-beta-D-xylan_xylanohydrolase_P_chrysogenum (tr|Q6PRW6|)

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Figure 4. Phylogenetic tree of endo-β-N-acetylglucosaminidase (GH family-18) using the Neighbor-Joining (NJ) algorithm from MEGA 5.05, p-distance model and 1000 bootstrap tests. The “□” symbol indicates CAMERA metagenomic sequences; “Δ” indicates IMG/M metagenomic sequences; “♦” indicates UniprotKB chitinase reference sequences and “●” indicates the outgroup sequences. were then used on the construction of chitinase pHMMs. The searches using these pHMMs were able to retrieve high percentages of putative chitinase sequences, which were confirmed in silico by a scanning for chitinase conserved domains and motif/signatures and in NJ phylogenetic reconstructions. The results confirmed the effi- cacy of our pipeline in detecting chitinase sequences and highlighted the sensitivity of pHMM-based strategies to identify remote homologues. These analyses provide insight into the potential reservoir of novel molecules in

Chitinase_Sediment_microbial_communities_from_Lake_Washington Chitinase_Soil_microbial_communities_from_FACE_and_OTC_sites Chitinase_Sludge/US_Virion Glycosyl_hydrolases_family_18_Coastal_water_and_sediment_microbial_communities_from_Arctic Chitinase_Sediment_microbial_communities_from_Lake_Washington Chitinase_family_Soil_microbial_communities_from_FACE_and_OTC_sites Chitinase_Sediment_microbial_communities_from_Lake_Washington JGI_SLUDGE_AUS_READ_1434047643 Chitinase_Sludge/Australian Chitinase_Methylotrophic_community_from_Lake_Washington Chitinase_Methylotrophic_community_from_Lake_Washington HumanDistalGut_READ_00079297 Chitinase_Atta_texana_internal_waste_dump Predicted_glycosyl_hydrolase_Microbial_community_from_Yellowstone_Hot_Springs Chitinase_family_Atta_texana_internal_waste_dump WASECA_FRM_SOIL_READ_1557330502 Chitinase_Soil_microbial_communities_from_Minnesota_Farm Chitinase_VLU Chitinase_Soil_microbial_community_from_switchgrass_rhizosphere Chitinase_Apterostigma_dentigerum_fungus_garden Chitinase_Atta_columbica_fungus_garden Chitinase_Fungus-growing_Termite_Worker Chitinase_Atta_cephalotes_fungus_garden Chitinase_Bison_Hot_Spring_Pool_Yellowstone BisonMetagenome_READ_00199686 Chitinase_Bison_Hot_Spring_Pool_Yellowstone JGI_SCAF_2004129902 Endo-beta-N-acetylglucosaminidase_Hindgut_microbiome_of_Nasutitermes_sp. CAM_READ_0100067807 Glycosyl_hydrolases_family_18_K9gut Glycosyl_hydrolases_family_18_Mixed_alcohol_bioreactor Glycosyl_hydrolases_family_18_Atta_columbica_fungus_garden_and_dump Glycosyl_hydrolases_family_18_Poplar_biomass_decaying_microbial_community TwinStudy_READ_09385162 HumanGut_CONTIG_00189686 Glycosyl_hydrolases_family_18_Cyphomyrmex_longiscapus_fungus_garden Endo-beta-N-acetylglucosaminidase_Flavobacterium_sp._strain_SK1022 (sp|P80036|) CAM_READ_0274750873 Glycosyl_hydrolases_family_18_Atta_columbica_fungus_garden_and_dump Glycosyl_hydrolases_family_18_Soil_microbial_communities_from_FACE_and_OTC_sites Glycosyl_hydrolases_family_18_Atta_columbica_fungus_garden Secreted_endo-beta-N-acetylglucosaminidase_Streptomyces_griseoaurantiacus (tr|F3NDC4|) Endo-beta-N-acetylglucosaminidase_H_Streptomyces_plicatus (sp|P04067|) Secreted_endo-beta-N-acetylglucosaminidase_Streptomyces_lividans_TK24 (tr|D6ESW9|) Hypothetical_protein_Aquatic_dechlorinating_community_(KB-1) NCBI_PEP_149233387 Endo-beta-N-acetylglucosaminidase_F2_Flavobacterium_meningosepticum (sp|P36912|) Secreted_endo-beta-N-acetylglucosaminidase_EndoS_Melissococcus_plutonius (tr|F3Y8V4|) Hypothetical_protein_Dendroctonus_frontalis_Fungal_community Hypothetical_protein_Dendroctonus_ponderosae_beetle_community Secreted_xylanase_Xanthomonas_oryzae_pv._oryzae (tr|Q9AM28|) Xylanase_glycosyl_hydrolase_family_10_Clostridium_acetobutylicum (tr|Q97TI5|) Glycosyl_hydrolase_family_10_xylanase_Flavobacterium_sp. (tr|C0M1B6|) Endo-14-beta-xylanase_A_Bacillus_halodurans_xynA (sp|P07528|) GH10_xylanase_Clostridium_cellulolyticum_xyn10A (tr|Q0PRN5|) Xylanase_A_Streptomyces_thermocyaneoviolaceus_xynA (tr|Q9RMM5|)

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Figure 5. Phylogenetic tree of bacterial chitinases (GH family-19) using the Neighbor-Joining (NJ) algorithm from MEGA 5.05, p-distance model and 1000 bootstrap tests. The “□” symbol indicates CAMERA metagenomic sequences; “Δ” indicates IMG/M metagenomic sequences; “♦” indicates UniprotKB chitinase reference sequences and “●” indicates the outgroup sequences.

Uncharacterized_protein_contain_chitin-binding_Cyphomyrmex_longiscapus_fungus_garden Uncharacterized_protein_contain_chitin-binding_Atta_cephalotes_fungus_garden BISONN_Uncharacterized_protein_contain_chitin-binding_Bison_Hot_Spring_Pool_Yellowstone Uncharacterized_protein_contain_chitin-binding_Fungus-growing_Termite_Worker Uncharacterized_protein_contain_chitin-binding_Atta_columbica_fungus_garden Uncharacterized_protein_contain_chitin-binding_Atta_columbica_fungus_garden BisonMetagenome_READ_00017044_library_id_BXBH Uncharacterized_protein_contain_chitin-binding_domain_Bison_Hot_Spring_Pool_Yellowstone Uncharacterized_protein_contain_chitin-binding_domain_Dendroctonus_ponderosae_fungus Uncharacterized_protein_contain_chitin-binding_domain_type_Dendroctonus_ponderosae_fungus Uncharacterized_protein_contain_chitin-binding_domain_Acromyrmex_echinatior_fungus_garden Chitinase_class_I._Sediment_microbial_communities_from_Lake_Washington Uncharacterized_protein_contain_chitin-binding_Methylotrophic_community_from_Lake_Washington Uncharacterized_protein_contain_chitin-binding_Methylotrophic_community_from_Lake_Washington Uncharacterized_protein_contain_chitin-binding_Apterostigma_dentigerum_fungus_garden Uncharacterized_protein_contain_chitin-binding_Endophytic_microbiome_from_Rice CAM_READ_0071982861_library_id_CAM_LIB_A00002 Chitinase_Vibrio_orientalis_(tr|C9QJ20|) Chitinase_Vibrio_vulnificus_(tr|E8VQ40|) Chitinase_Vibrio_proteolyticus_(tr|Q25BT4|) Chitinase_class_I_Xyleborus_affinis_beetle_metagenome NCBI_NT_188040707_NCBI_GI_188040707 Uncharacterized_protein_contain_chitin-binding_Guerrero_Negro_salt_ponds_hypersaline_mat ALVINELLA_READ_1878700170_library_id_ALVINELLA_LIB_20041130 NCBI_READ_alv_lsb_408_g04.y01.scf CAM_READ_0214391205_library_id_CAM_LIB_BBAY02-4F-01-676 CAM_READ_0238266111_library_id_CAM_LIB SynechococcusWH7803_READ_00322968 Chitinase_class_I_Compost_Minireactor_Metagenome NCBI_PEP_88778030/90-433_Reinekea_blandensis_MED297 Chitinase_class_I_Dendroctonus_frontalis_Fungal_community Chitinase_B_Burkholderia_gladioli_(tr|Q9LBM0|) Chitinase_B_Burkholderia_gladioli_(tr|F2LM34|) CAM_READ_0262530305_library_id_CAM_LIB_000107 Chitinase_Polysphondylium_pallidum_(tr|D3BFR3|) Chitinase_I_Bacillus_circulans_(tr|Q59I46|) Chitinase_class_I_Atta_columbica_fungus_garden_and_dump Family_19_chitinase_Chitiniphilus_shinanonensis_(tr|F8WSX8|) Chi35_protein_Streptomyces_thermoviolaceus_(tr|Q9RHU5|) Chitinase_class_I_Atta_texana_internal_waste_dump Chitinase_A_Streptomyces_cyaneus_(tr|B3XZQ2|) Chitinase_Streptomyces_olivaceoviridis_(tr|Q9Z4P2|) Chitinase_Streptomyces_coelicolor_(tr|Q9S6T0|) Chitinase_Streptomyces_bingchenggensis_(tr|D7BYX7|) Predicted_chitinase_Sediment_microbial_communities_from_Lake_Washington Family19_chitinase_Nocardiopsis_prasina_(tr|Q8GI53|) Chitinase_Streptomyces_sp._(tr|G2NLC6|) Chitinase_C_Streptomyces_griseus_(tr|O50152|) CAM_READ_0071648843_6_library_id_CAM_LIB_A00001 Bacterioplankton_READ_01002885_2_sample_id_1312147078918440203 PML_READ_00716426_1_accession_PML_READ_00716426 Lytic_enzyme_Hindgut_microbiome_of_Nasutitermes_sp. Predicted_chitinase_Sludge/US_Virion JGI_SLUDGE_US_READ_1404905792_4_library_id_JGI_LIB_SLUDGE_US Predicted_chitinase_Sludge/US_Jazz_Assembly Predicted_chitinase_Sludge/US_Phrap_Assembly Predicted_chitinase_Sediment_microbial_communities_from_Lake_Washington Predicted_chitinase_Methylotrophic_community_from_Lake_Washington Predicted_chitinase_Air_microbial_communities_Singapore_indoor_air_filters Predicted_chitinase_Air_microbial_communities_Singapore_indoor_air_filters Predicted_chitinase_simMC_Simulated_Medium_Complexity_Metagenome Predicted_chitinase_Fungus-growing_Termite_Fungus_Garden SAM_READ_00010894_2/111-388_library_id_HSAB Predicted_chitinase_Soil_microbial_communities_from_FACE_and_OTC_sites Predicted_chitinase_Soil_microbial_communities_from_FACE_and_OTC_sites OCTOPUS_READ_1647171229_4_library_id_JGI_LIB_OCTOPUS_20031004 Predicted_chitinase_Microbial_community_from_Yellowstone_Hot_Springs Predicted_chitinase_Viral_community_from_bovine_rumen Predicted_chitinase_Methylotrophic_community_from_Lake_Washington HumanDistalGut_READ_00098616_3/42-354_library_id_T24143 Predicted_chitinase_Human_Gut_Community_Subject_7 Predicted_chitinase_Sediment_microbial_communities_from_Lake_Washington WASECA_FRM_SOIL_READ_1557419369_library_id_WASECA_FRM_SOIL_LIB_20010901 Predicted_chitinase_Soil_microbial_communities_from_Minnesota_Farm Predicted_chitinase_Poplar_biomass_decaying_microbial_community CellCapture_READ_00593848_library_id_CELLCAPTURE_LIB_MDA Predicted_chitinase_Oak_Ridge_Pristine_Groundwater_FRC_FW301 BISONS__Predicted_chitinase_Bison_Hot_Spring_Pool_Yellowstone Predicted_chitinase_Soil_microbial_community_from_switchgrass_rhizosphere Predicted_chitinase_Dendroctonus_ponderosae_beetle_community Chitinase_class_I_Xyleborus_affinis_microbiome_from_Bern_Switzerland Predicted_chitinase_Dendroctonus_ponderosae_beetle_community Predicted_chitinase_Coastal_water_and_sediment_microbial_communities_from_Arctic Sludge/Australian_Phrap_Assembly GH10_xylanase_Clostridium_cellulolyticum_strain_ATCC_35319_(tr|Q0PRN5|) Xylanase_A_Streptomyces_thermocyaneoviolaceus_(tr|Q9RMM5|)

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Figure 6. Phylogenetic tree of fungal chitinases (GH family-20) using the Neighbor-Joining (NJ) al-gorithm from MEGA 5.05, p-distance model and 1000 bootstrap tests. The “□” symbol indicates CAMERA metagenomic sequences; “Δ” indicates IMG/M metagenomic sequences; “♦” indicates UniprotKB chitinase reference sequences and “●” indicates the outgroup sequences.

N-acetyl-beta-hexosaminidase_Air_microbial_communities_Singapore_indoor_air_filters Glycosyl_hydrolase_family_20_catalytic_domain_Dendroctonus_frontalis_Bacterial_community SAM_READ_00017585_library_id_HSAB_NCBI_project_ID_37809 N-acetyl-beta-hexosaminidase_Atta_texana_internal_waste_dump N-acetyl-beta-hexosaminidase_Atta_texana_internal_waste_dump N-acetyl-beta-hexosaminidase_Uranium_Contaminated_Groundwater beta-N-acetylhexosaminidase_Simulated_Medium_Complexity_Metagenome N-acetyl-beta-hexosaminidase_Atta_columbica_fungus_garden_and_dump N-acetyl-beta-hexosaminidase_Methylotrophic_community_from_Lake_Washington_sediment N-acetyl-beta-hexosaminidase_Poplar_biomass_decaying_microbial_community N-acetyl-beta-hexosaminidase_Soil_microbial_communities_from_Minnesota_Farm WASECA_FRM_SOIL_READ_1557375600_library_id_WASECA_FRM_SOIL N-acetyl-beta-hexosaminidase_Atta_columbica_fungus_garden_and_dump N-acetyl-beta-hexosaminidase_Hindgut_microbiome_of_Nasutitermes_sp. JGI_SCAF_2004121036_1_NCBI_project_ID_19107_host_name_Nasutitermes_sp ANASMEC_N-acetyl-beta-hexosaminidase_ANAS_dechlorinating_bioreactor beta-N-acetylhexosaminidase_Wastewater_Terephthalate-degrading_communities_from_Bioreactor N-acetyl-beta-hexosaminidase_Atta_texana_internal_waste_dump NCBI_READ_alv_lsb_014_a11.y01.scf_5_NCBI_project_ID_17241 N-acetyl-beta-hexosaminidase_Mixed_alcohol N-acetyl-beta-hexosaminidase_Aquatic_dechlorinating_community N-acetyl-beta-hexosaminidase_Groundwater_dechlorinating_microbial_community_Kitchener_Ontario N-acetyl-beta-hexosaminidase_Saline_water_microbial_communities_from_Great_Salt_Lake N-acetyl-beta-hexosaminidase_Thermophilic_enrichment_culture_SG0.5JP CAM_READ_0072285831_3_library_id_CAM_LIB_A00002 N-acetyl-beta-hexosaminidase_Sediment_microbial_communities_from_Lake_Washington NCBI_READ_1594414298_2/9-259_jgi_project_id_3634300 N-acetyl-beta-hexosaminidase_Air_microbial_communities_Singapore_indoor_air_filters N-acetyl-beta-hexosaminidase_Sludge/US_Phrap_Assembly JGI_SLUDGE_US_READ_1404894340_6_library_id_JGI_LIB_SLUDGE_US N-acetyl-beta-hexosaminidase_Sludge/US_Jazz_Assembly N-acetyl-beta-hexosaminidase_Sludge/Australian_Phrap_Assembly NCBI_NT_188131206_5_NCBI_project_ID_29621_NCBI_GI_188131206 N-acetyl-beta-hexosaminidase_Microbial_community_from_Yellowstone_Hot_Springs N-acetyl-beta-hexosaminidase_Sediment_microbial_communities_from_Lake_Washington beta-N-acetylhexosaminidase_Simulated_Low_Complexity_Metagenome N-acetyl-beta-hexosaminidase_Thermophilic_enrichment_culture N-acetyl-beta-hexosaminidase_Methylotrophic_community_from_Lake_Washington_sediment N-acetyl-beta-hexosaminidase_Methylotrophic_community_from_Lake_Washington_sediment N-acetyl-beta-hexosaminidase_Microbial_community_from_Yellowstone_Hot_Springs N-acetyl-beta-hexosaminidase_Anammox_bioreactor_Anammoxoglobus_propionicus NCBI_PEP_90324090_Photobacterium_profundum_hypothetical_protein BisonMetagenome_READ_00151130_library_id_BXBC N-acetyl-beta-hexosaminidase_Fungus-growing_Termite_Fungus_Garden N-acetyl-beta-hexosaminidase_Dendroctonus_ponderosae_fungus_gallery N-acetyl-beta-hexosaminidase_Fungus-growing_Termite_Worker N-acetyl-beta-hexosaminidase_Dendroctonus_ponderosae_beetle_community N-acetyl-beta-hexosaminidase_Xyleborus_affinis_beetle_metagenome Glycosyl_hydrolase_family_20_catalytic_domain_Dendroctonus_frontalis_Fungal_community N-acetyl-beta-hexosaminidase_Acromyrmex_echinatior_fungus_garden N-acetyl-beta-hexosaminidase_Atta_columbica_fungus_garden N-acetyl-beta-hexosaminidase_Endophytic_microbiome_from_Rice N-acetyl-beta-hexosaminidase_Apterostigma_dentigerum_fungus_garden N-acetyl-beta-hexosaminidase_Cyphomyrmex_longiscapus_fungus_garden N-acetyl-beta-hexosaminidase_Atta_cephalotes_fungus_garden N-acetyl-beta-hexosaminidase_Atta_columbica_fungus_garden Hexosaminidase_A_(alpha_polypeptide)_VLU N-acetyl-beta-D-glucosaminidase_Trichoderma_hamatum_(tr|G1EIS2|) N-acetyl-beta-D-glucosaminidase_Trichoderma_atroviride_(tr|Q0ZLH7|) Exochitinase_Trichoderma_harzianum_(tr|P78738|) Beta-hexosaminidase_Candida_albicans_(sp|P43077|) Beta-N-acetylhexosaminidase_Penicillium_oxalicum_(tr|E3NYM0|) Beta-N-acetylglucosaminidase_Aspergillus_oryzae_(tr|Q8J2T0|) Chitobiase_Coccidioides_posadasii_(tr|Q309C3|) N-acetylglucosaminidase_OS_Neotyphodium_sp._(tr|Q643Y1|) N-acetyl-beta-hexosaminidase_Human_Gut_Community N-acetyl-beta-hexosaminidase_Human_Gut_Community N-acetyl-beta-hexosaminidase_Bison_Hot_Spring_Pool_Yellowstone N-acetyl-beta-hexosaminidase_Microbial_community_from_Yellowstone N-acetyl-beta-hexosaminidase_Bison_Hot_Spring_Pool_Yellowstone N-acetyl-beta-hexosaminidase_Microbial_community_from_Yellowstone_Hot_Springs N-acetyl-beta-hexosaminidase_Sediment_and_Water_microbial_communities N-acetyl-beta-hexosaminidase_Guerrero_Negro_salt_ponds_hypersaline N-acetyl-beta-hexosaminidase_Sediment_and_Water_microbial_communities N-acetyl-beta-hexosaminidase_Bison_Hot_Spring_Pool_Yellowstone N-acetyl-beta-hexosaminidase_Bison_Hot_Spring_Pool_Yellowstone Endo-14-beta-xylanase_Thermoascus_aurantiacus_(sp|P23360|) Endo-14-beta-xylanase_Aspergillus_oryzae_(sp|O94163|) Endo-14-beta-xylanase_Emericella_nidulans_(sp|Q00177|)

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metagenomic databases while supporting the in silico chitinase mining pipeline developed in this work and identifying phylogenetic relationships among the chitinase sequences. By using our chitinase mining pipeline, a larger number of previously unannotated metagenomic chitinase sequences can be classified, enabling further exploration of these enzymes.

Acknowledgements This research was supported by CAPES/PNPD.

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Technology, 26, 473-483. http://dx.doi.org/10.1016/S0141-0229(00)00134-4 [5] Henrissat, B. (1991) A Classification of Glycosyl Hydrolases Based on Amino Acid Sequence Similarities. Biochemi-

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Towards a Comprehensive Search of Putative Chitinases Sequences in Environmental Metagenomic DatabasesAbstractKeywords1. Introduction2. Methodology2.1. Collection of Chitinase Reference Sequences2.2. Environmental Metagenomic Databases2.3. Construction of Profiles HMM and Search for Putative Chitinase Homologues2.4. Mining Strategy Validation2.5. Phylogenetic Analysis of Putative Chitinase Sequences

3. Results4. Discussion5. ConclusionAcknowledgementsReferences