Supplementary appendix

S1. Specimen collection, storage and the work flows for performing DNA extraction, next

generation DNA sequencing, sequence analysis and quality control of DNA reads and qPCR

to determine the microbial load, were performed as previously described by our group.

(Malone et al., 2017)

Subjects and sample collection

Individuals presenting to a tertiary referral hospital (Liverpool Hospital High Risk Foot

Service and Liverpool Hospital Emergency Department) with a newly infected diabetic foot

ulcer occurring below the malleolus (Lipsky et al., 2012) were recruited consecutively over a

twelve-month study period between January 2015 and December 2015. A 3mm (width) x

10mm (depth) tissue punch biopsy was obtained from the edge of each DFU after debriding

and cleansing the wound with NaCl 09%. Patients who had received any systemic or topical

antimicrobials antimicrobial therapy two weeks prior to enrolment were excluded. Ethics

approval for this study was granted by the South West Sydney Local Health District Research

and Ethics Committee (HREC/14/LPOOL/487, SSA/14/LPOOL/489). The study

methodology was designed in guidance by STROME-ID and our molecular surveillance data

are reported in keeping with this (Field et al., 2014).

Tissue processing workflow

DNA Extraction

5 – 10 mg of human chronic DFU biopsy samples were defrosted on ice prior to DNA

extraction. Genomic DNA was extracted using Mo Bio PowerBiofilm DNA isolation kit (Mo

Bio Cat# 24000-50) following the manufacturers instructions.

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Next generation DNA sequencing to determine bacterial diversity

Genomic DNA was extracted from 5-10 mg of DFU biopsy material using Mo Bio

PowerBiofilm DNA isolation kit (Mo Bio Cat# 24000-50) following the manufacturer’s

instructions. DNA sequencing was carried out by a commercial laboratory (Australian Centre

for Ecogenomics, Brisbane, Australia) targeting the V3-V4 region of the 16S rRNA gene

using eubacterial universal primers 515F and 806R (Caporaso et al., 2012). Preparation of

the16S library was performed using the workflow outlined by the manufacturer (Iluumina

Inc. Part # 15044223 Rev. B). In the 1st stage, PCR products were amplified according to the

specified workflow with an alteration in polymerase used to substitute Q5 Hot Start High-

Fidelity 2X Master Mix (New England Biolabs, Ipswich, Massachusetts, United States).

Resulting PCR amplicons were purified using Agencourt AMPure XP beads (Beckman

Coulter). Purified DNA was indexed with unique 8bp barcodes using the Illumina Nextera

XT 384 sample Index Kit A-D (Illumina FC-131-1002) in standard PCR conditions with Q5

Hot Start High-Fidelity 2X Master Mix. Indexed amplicons were pooled together in

equimolar concentrations and sequenced on the Illumina MiSeq platform using paired end

sequencing with V3 300bp chemistry.

Sequence analysis and quality control

Reads in FASTQ format were imported to CLC genomics workbench version 8.5.1 using the

microbial genome finishing module (CLC bio, Qiagen Aarhus, Denmark), for sequence

quality control and analysis. Workflows for sequence quality control and operational

taxonomic units (OTU) clustering were based on previously reported wound microbiome

analysis (Gardner et al., 2013). OTUs were defined as molecular proxies for describing

organisms based on their phylogenetic relationships to other organisms, and were reported at

either the genera or species level identification where possible.

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Sequence and quality control measures were performed using CLC genomic software. Reads

were paired, merged and fixed trimmed at set averages of greater than 230 base pairs. OTUs

were clustered, chimeric sequences removed and OTUs aligned using SILVA (Quast et al.,

2013) at 97% similarity to identify microorganisms at the genus level (species level where

possible). OTUs were defined as molecular proxies for describing organisms based on their

phylogenetic relationships to other organisms, (Gardner et al., 2013). Where OTUs of interest

such as Staphylocci which were only clustered at the genera level, each genomic sequence

was manually reviewed for read length and a base pair >300 were utilised for analysis and

further referenced for speciation using NCBI Mega BLASTtn (Morgulis et al., 2008). This

resolved a proportion of Staphylocci cases which speciation was possible, but overall species

determination was limited. To classify microorganisms based on their residing origin at the

genera level (i.e. skin, gut, environment, oral), microorganisms were manually referenced

against Bergey’s manual of bacteriology (Holt and Krieg, 1994) and manual of systemic

bacteriology (Whitman et al., 2012).

Two sets of descriptive data were reported based on the relative abundance OTUs contributed

to each individual wound (OTUs contributing 1% - 10% - these were considered major

contributors, the second data set reports OTUs contributing ≥10% - these were considered

dominant contributors) (Rhoads et al., 2012). Next, OTUs were aligned using MUSCLE

(Edgar, 2004) to reconstruct a phylogenetic tree, and then subsampled allowing the

estimation of the alpha and beta diversity. This included both community richness

(Rarefaction) and community diversity (Shannon Weaver Index). Rarefaction curves allow

the estimation of the number of unique microbial taxa within a sample and the Shannon

Weaver Index is a measure of diversity that includes the number of unique microbial taxa and

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their relative evenness within each sample. Thus, a higher Shannon Weaver Index correlates

to a greater diversity.

16s rRNA quantitative real-time PCR to determine microbial load

We utilised real-time quantitative PCR (qPCR) using the 16s rRNA eubacterial universal

primers 341F 5’-CCTACGGGAGGCAGCAG-3’ and 534R 5’-ATTACCGCGGCTGCTGG-

3’ to amplify a 194bp amplicon of 16s rRNA gene of all bacteria to determine the microbial

load in DFUs as previously reported (Hu et al., 2015; Jacombs et al., 2012). The total number

of bacteria was expressed as per mg of tissue normalised to the average number of copies of

the 18s gene in a mg of human tissue. The primer pair used in 18s rRNA gene real-time PCR

was 18s rRNA_756F 5’-GGTGGTGCCCTTCCGTCA-3’ and 18s rRNA_877R 5’-

CGATGCGGCGGCGTTATT-3’ to amplify a 122bp amplicon. 16s rRNA copy number per

mg tissue were normalised to human 18s rRNA copy number per mg tissue.

Real-time PCR was carried out in 25 µl reaction mix containing 1X Brilliant II Sybr Green

qPCR Master mix (Agilent Technologies, Sanat Clara, US), 400nM forward and reverse

primer and 100ng DNA template was analysed on the Mx3000P system (Agilent

Technologies, Santa Clara, US) with the following cycling conditions: activation of Taq

polymerase at 95oC for 10 min, followed by 40 cycles of denaturation at 95oC for 15 sec,

annealing at 56oC for 30 sec and extension at 72oC for 30 sec.

Each qPCR was run with standard samples of known concentrations (copies/µl). Ten-fold

serial dilutions of the quantified 16s rRNA gene and ten-fold serial dilutions of 18s rRNA

gene PCR amplicon solution were kept in aliquots at -20oC and used as external standards of

known concentration (copies/µl) in real-time PCR reaction. The standard samples were

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ranged 102–106 copies/µl which used to construct a standard curve for each qPCR run. The

calibration curve was created by plotting the threshold cycle (Ct) corresponding to each

standard vs the value of their corresponding gene concentration (copies/µl). The copy number

of 16s rRNA gene (copies/µl) was normalised against copy number of human 18s rRNA gene

(copies/µl) in each wound sample.

Culture-dependent Bacteriological Enumeration and Identification

Culture-dependent analysis of tissue cultures was performed by a hospital pathology service

(Sydney South West Pathology Service) using methods previously described.(Oates et al.,

2014) Briefly, tissue samples were weighed and homogenized using a sterile tissue pulper in

3 ml of sterile saline. A 1:10 dilution of homogenized tissue was made and two sets of plates

were inoculated, one for the neat crushed tissue and one for the 1:10 dilution. Plates were

streaked for isolation onto four quadrants of recommended agars and grown under

appropriate atmospheres to isolate clinically relevant organisms (both aerobe and anaerobe)

per standardized methods. The number of microorganisms were quantified by colony forming

units (CFU), and reported as either 106 CFU/g of tissue or <106 CFU/g of tissue for each

isolate.

References for methods section detailed only in supplemental:

Caporaso, J. G., Lauber, C. L., Walters, W. A., Berg-Lyons, D., Huntley, J., Fierer, N., Knight, R. (2012). Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. The ISME Journal, 6(8), 1621-1624. doi:10.1038/ismej.2012.8

Edgar, R. C. (2004). MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics, 5. doi:10.1186/1471-2105-5-113

Field, N., Cohen, T., Struelens, M. J., Palm, D., Cookson, B., Glynn, J. R., Abubakar, I. (2014). Strengthening the Reporting of Molecular Epidemiology for Infectious Diseases (STROME-ID): an extension of the STROBE statement. The Lancet Infectious Diseases, 14(4), 341-352. doi:10.1016/S1473-3099(13)70324-4

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Gardner, S. E., Hillis, S. L., Heilmann, K., Segre, J. A., & Grice, E. A. (2013). The Neuropathic Diabetic Foot Ulcer Microbiome Is Associated With Clinical Factors. Diabetes, 62(3), 923-930. doi:10.2337/db12-0771

Gardner, S. E., Hillis, S. L., Heilmann, K., Segre, J. A., & Grice, E. A. (2013). The neuropathic diabetic foot ulcer microbiome is associated with clinical factors. Diabetes, 62. doi:10.2337/db12-0771

Hu, H., Jacombs, A., Vickery, K., Merten, S. L., Pennington, D. G., & Deva, A. K. (2015). Chronic Biofilm Infection in Breast Implants Is Associated with an Increased T-Cell Lymphocytic Infiltrate: Implications for Breast Implant–Associated Lymphoma. Plastic and Reconstructive Surgery, 135(2), 319-329. doi:10.1097/prs.0000000000000886

Holt, J.G. & Krieg, N.R. (eds., 1994). Bergey's Manual of Determinative Bacteriology, 9th ed., The Williams & Wilkins Co., Baltimore.

Jacombs, A., Allan, J., Hu, H., Valente, P. M., Wessels, W. L. F., Deva, A. K., & Vickery, K. (2012). Prevention of Biofilm-Induced Capsular Contracture With Antibiotic-Impregnated Mesh in a Porcine Model. Aesthetic Surgery Journal, 32(7), 886-891.

Lipsky, B. A., Berendt, A. R., Cornia, P. B., Pile, J. C., Peters, E. J. G., Armstrong, D. G., Senneville, E. (2012). 2012 Infectious Diseases Society of America Clinical Practice Guideline for the Diagnosis and Treatment of Diabetic Foot Infections. Clinical Infectious Diseases, 54 (12), e132-e173. doi:10.1093/cid/cis346

Morgulis, A., Coulouris, G., Raytselis, Y., Madden, T. L., Agarwala, R., & Schäffer, A. A. (2008). Database indexing for production MegaBLAST searches. Bioinformatics, 24(16), 1757-1764. doi:10.1093/bioinformatics/btn322

Oates, A., Bowling, F. L., Boulton, A. J. M., Bowler, P. G., Metcalf, D. G., & McBain, A. J. (2014). The Visualization of Biofilms in Chronic Diabetic Foot Wounds Using Routine Diagnostic Microscopy Methods. Journal of Diabetes Research, 2014, 8. doi:10.1155/2014/153586

Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., Glöckner, F. O. (2013). The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Research, 41(Database issue), D590-D596. doi:10.1093/nar/gks1219

Rhoads, D. D., Cox, S. B., Rees, E. J., Sun, Y., & Wolcott, R. D. (2012). Clinical identification of bacteria in human chronic wound infections: culturing vs. 16S ribosomal DNA sequencing. BMC Infectious Diseases, 12, 321-321. doi:10.1186/1471-2334-12-321

Whitman, W.B., Goodfellow, M., Kämpfer, P., Busse, H.-J., Trujillo, M.E., Ludwig, W. & Suzuki, K.-i. (eds., 2012). Bergey’s Manual of Systematic Bacteriology, 2nd ed., vol. 5, parts A and B, Springer-Verlag, New York, NY.

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S2. Microorganisms contributing between 1-10% in each sample (representing major contributors) (Rhoads, Cox, et al., 2012). * Refers to the

species level identification of Staphylococcus genus level data.

Genera/Species Samples Average abundance % SD Range % Aerotolerance

Corynebacterium spp. 13 35 2 1 to 8 Aerobe

Anaerococcus spp. 10 4 26 1 to 8 Facultative

Staphlycoccus spp.: - 10 29 16 1 to 6 Facultative

*Staphylococcus epidermidis 5 28 09 2 to 4 Facultative

*Staphylococcus xylosus 3 1.3 06 1 to 2 Facultative

*Staphylococcus aureus 1 1 0 1 Facultative

*Staphylococcus simulans 1 1 0 1 Facultative

Finegoldia spp. 9 44 26 15 to 8 Anaerobe

Acinetobacter spp. 9 38 2 2 to 85 Aerobe

Propionibacterium spp. 8 25 16 1 to 5 Facultative

Cyanobacteria_Subsectionl 7 49 25 2 to 9 N/A

Cenarchaeum 7 44 25 1 to 8 N/A

Streptococcus spp. 6 36 28 1 to 75 Facultative

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Pseudomonas aeruginosa 6 4 29 1 to 76 Aerobe

Proteobacteria_ARKDMS-49 6 64 17 4 to 8 N/A

Porphymonas spp. 6 4 34 1 to 9 Anaerobe

Peptoniphilus spp. 6 49 36 1 to 85 Anaerobe

Rhodothermaceae spp. 5 47 27 2 to 8 N/A

Veillonella spp. 5 16 04 1 to 2 Anaerobe

Proteobacteria_E01-9C-26 marine 5 6.4 31 1 to 9 N/A

Elizabethkingia meniingoseptica 5 4.3 21 2 to 75 Aerobe

Candidatus Hepatobacter penaei 5 3.7 23 2 to 65 Anaerobe

Aerococcus spp. 5 2.9 15 15 to 5 Aerobe

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S3. Residing niche of sampled microorganisms identifies skin, environment, gut and oral microbes colonizing DFUs.194

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S4. Analysis of variance between Staphylocci spp., relative abundance in DFUs based on the

duration. In DFUs < six weeks Staphyloccci spp., were present as the dominant taxa (High

frequency). The average relative abundance of Staphyloccci in DFUs > six-weeks is far less

and this is because DFUs of longer duration are typically polymicrobial.

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S5. PCoA Bray-curtis plot demonstrates how similar/dissimilar the community structure of

DFUs less than 6 weeks.

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S6. Relative abundance (%) of obligate anaerobes at the individual samples level identifies great heterogeneity in thirty-nine patients with infected DFUs. Black bars represent DFUs <6 weeks and grey bars represent DFUs >6 weeks.

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S7. Relative abundance of species of differing aerotolerance in neuropathic (n=25) and neuroischemic (n=16) infected diabetic foot ulcers.227

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