Classifying individual bacterial species comprising complex, polymicrobial patient specimens remains a challenge for culture-based and molecular microbiology techniques in common clinical use. We therefore adapted practices from metagenomics research to rapidly catalog the bacterial composition of clinical specimens directly from patients, without need for prior culture. We have combined a semiconductor deep sequencing protocol that produces reads spanning 16S ribosomal RNA gene variable regions 1 and 2 (~360 bp) with a de-noising pipeline that significantly improves the fraction of error-free sequences. The resulting sequences can be used to perform accurate genus- or species-level taxonomic assignment. We explore the microbial composition of challenging, heterogeneous clinical specimens by deep sequencing, culture-based strain typing, and Sanger sequencing of bulk PCR product. We report that deep sequencing can catalog bacterial species in mixed specimens from which usable data cannot be obtained by conventional clinical methods. Deep sequencing a collection of sputum samples from cystic fibrosis (CF) patients reveals well-described CF pathogens in specimens where they were not detected by standard clinical culture methods, especially for low-prevalence or fastidious bacteria. We also found that sputa submitted for CF diagnostic workup can be divided into a limited number of groups based on the phylogenetic composition of the airway microbiota, suggesting that metagenomic profiling may prove useful as a clinical diagnostic strategy in the future. The described method is sufficiently rapid (theoretically compatible with same-day turnaround times) and inexpensive for routine clinical use.
References
[1]
Gill SR, Pop M, Deboy RT, Eckburg PB, Turnbaugh PJ, et al. (2006) Metagenomic analysis of the human distal gut microbiome. Science 312: 1355–1359.
[2]
Gajer P, Brotman RM, Bai G, Sakamoto J, Schutte UM, et al. (2012) Temporal dynamics of the human vaginal microbiota. Sci Transl Med 4: 132ra152.
[3]
Rhoads DD, Wolcott RD, Sun Y, Dowd SE (2012) Comparison of culture and molecular identification of bacteria in chronic wounds. Int J Mol Sci 13: 2535–2550.
[4]
Blumberg R, Powrie F (2012) Microbiota, disease, and back to health: a metastable journey. Sci Transl Med 4: 137rv137.
[5]
Schlaberg R, Simmon KE, Fisher MA (2012) A systematic approach for discovering novel, clinically relevant bacteria. Emerg Infect Dis 18: 422–430.
[6]
Petti CA, Polage CR, Schreckenberger P (2005) The role of 16S rRNA gene sequencing in identification of microorganisms misidentified by conventional methods. J Clin Microbiol 43: 6123–6125.
[7]
Clarridge JE, 3rd (2004) Impact of 16S rRNA gene sequence analysis for identification of bacteria on clinical microbiology and infectious diseases. Clin Microbiol Rev 17: : 840–862, table of contents.
[8]
Drancourt M, Bollet C, Carlioz A, Martelin R, Gayral JP, et al. (2000) 16S ribosomal DNA sequence analysis of a large collection of environmental and clinical unidentifiable bacterial isolates. J Clin Microbiol 38: 3623–3630.
[9]
Olsen GJ, Lane DJ, Giovannoni SJ, Pace NR, Stahl DA (1986) Microbial ecology and evolution: a ribosomal RNA approach. Annu Rev Microbiol 40: 337–365.
[10]
Fournier PE, Raoult D (2011) Prospects for the future using genomics and proteomics in clinical microbiology. Annu Rev Microbiol 65: 169–188.
[11]
Shendure J, Ji H (2008) Next-generation DNA sequencing. Nat Biotechnol 26: 1135–1145.
[12]
Baker GC, Smith JJ, Cowan DA (2003) Review and re-analysis of domain-specific 16S primers. J Microbiol Methods 55: 541–555.
[13]
Wu GD, Lewis JD, Hoffmann C, Chen YY, Knight R, et al. (2010) Sampling and pyrosequencing methods for characterizing bacterial communities in the human gut using 16S sequence tags. BMC Microbiol 10: 206.
[14]
Nasidze I, Quinque D, Li J, Li M, Tang K, et al. (2009) Comparative analysis of human saliva microbiome diversity by barcoded pyrosequencing and cloning approaches. Anal Biochem 391: 64–68.
[15]
Sundquist A, Bigdeli S, Jalili R, Druzin ML, Waller S, et al. (2007) Bacterial flora-typing with targeted, chip-based Pyrosequencing. BMC Microbiol 7: 108.
[16]
Huys G, Vanhoutte T, Joossens M, Mahious AS, De Brandt E, et al. (2008) Coamplification of eukaryotic DNA with 16S rRNA gene-based PCR primers: possible consequences for population fingerprinting of complex microbial communities. Curr Microbiol 56: 553–557.
[17]
Kinde I, Wu J, Papadopoulos N, Kinzler KW, Vogelstein B (2011) Detection and quantification of rare mutations with massively parallel sequencing. Proc Natl Acad Sci U S A 108: 9530–9535.
[18]
Meier A, Persing DH, Finken M, Bottger EC (1993) Elimination of contaminating DNA within polymerase chain reaction reagents: implications for a general approach to detection of uncultured pathogens. J Clin Microbiol 31: 646–652.
[19]
Spangler R, Goddard NL, Thaler DS (2009) Optimizing Taq polymerase concentration for improved signal-to-noise in the broad range detection of low abundance bacteria. PLoS One 4: e7010.
[20]
Pearson WR (2000) Flexible sequence similarity searching with the FASTA3 program package. Methods Mol Biol 132: 185–219.
[21]
Bragg L, Stone G, Imelfort M, Hugenholtz P, Tyson GW (2012) Fast, accurate error-correction of amplicon pyrosequences using Acacia. Nat Methods 9: 425–426.
[22]
Reeder J, Knight R (2010) Rapidly denoising pyrosequencing amplicon reads by exploiting rank-abundance distributions. Nat Methods 7: 668–669.
[23]
Edgar RC (2010) Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26: 2460–2461.
[24]
Edgar RC (2004) MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32: 1792–1797.
[25]
Cole JR, Wang Q, Cardenas E, Fish J, Chai B, et al. (2009) The Ribosomal Database Project: improved alignments and new tools for rRNA analysis. Nucleic Acids Res 37: D141–145.
[26]
Matsen FA, Kodner RB, Armbrust EV (2010) pplacer: linear time maximum-likelihood and Bayesian phylogenetic placement of sequences onto a fixed reference tree. BMC Bioinformatics 11: 538.
[27]
Matsen FA, Hoffman NG, Gallagher A, Stamatakis A (2012) A format for phylogenetic placements. PLoS One 7: e31009.
[28]
Nawrocki EP, Kolbe DL, Eddy SR (2009) Infernal 1.0: inference of RNA alignments. Bioinformatics 25: 1335–1337.
[29]
Price MN, Dehal PS, Arkin AP (2010) FastTree 2–approximately maximum-likelihood trees for large alignments. PLoS One 5: e9490.
[30]
Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, et al. (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25: 3389–3402.
[31]
Matsen FA, Evans S (2011) Edge principal components and squash clustering: using the special structure of phylogenetic placement data for sample comparison. arXiv
[32]
Sukumaran J, Holder MT (2010) DendroPy: a Python library for phylogenetic computing. Bioinformatics 26: 1569–1571.
Loman NJ, Misra RV, Dallman TJ, Constantinidou C, Gharbia SE, et al. (2012) Performance comparison of benchtop high-throughput sequencing platforms. Nat Biotechnol 30: 434–439.
[35]
Quail M, Smith ME, Coupland P, Otto TD, Harris SR, et al. (2012) A tale of three next generation sequencing platforms: comparison of Ion torrent, pacific biosciences and illumina MiSeq sequencers. BMC Genomics 13: 341.
[36]
Lam HY, Clark MJ, Chen R, Natsoulis G, O'Huallachain M, et al. (2012) Performance comparison of whole-genome sequencing platforms. Nat Biotechnol 30: 78–82.
[37]
Quince C, Lanzen A, Curtis TP, Davenport RJ, Hall N, et al. (2009) Accurate determination of microbial diversity from 454 pyrosequencing data. Nat Methods 6: 639–641.
[38]
Quince C, Lanzen A, Davenport RJ, Turnbaugh PJ (2011) Removing noise from pyrosequenced amplicons. BMC Bioinformatics 12: 38.
[39]
Vandamme P, Coenye T (2004) Taxonomy of the genus Cupriavidus: a tale of lost and found. Int J Syst Evol Microbiol 54: 2285–2289.
[40]
Barrionuevo MR, Vullo DL (2012) Bacterial swimming, swarming and chemotactic response to heavy metal presence: which could be the influence on wastewater biotreatment efficiency? World J Microbiol Biotechnol 28: 2813–2825.
[41]
Boutros N, Gonullu N, Casetta A, Guibert M, Ingrand D, et al. (2002) Ralstonia pickettii traced in blood culture bottles. J Clin Microbiol 40: 2666–2667.
[42]
Kampfer P, Glaeser S, Lodders N, Busse HJ, Falsen E (2012) Herminiimonas contaminans sp. nov., isolated as a contaminant of biopharmaceuticals. Int J Syst Evol Microbiol
[43]
Suzuki MT, Giovannoni SJ (1996) Bias caused by template annealing in the amplification of mixtures of 16S rRNA genes by PCR. Appl Environ Microbiol 62: 625–630.
[44]
Al Masalma M, Lonjon M, Richet H, Dufour H, Roche PH, et al. (2012) Metagenomic analysis of brain abscesses identifies specific bacterial associations. Clin Infect Dis 54: 202–210.
[45]
Conrad D, Haynes M, Salamon P, Rainey PB, Youle M, et al. (2012) Cystic Fibrosis Therapy: A Community Ecology Perspective. Am J Respir Cell Mol Biol
[46]
Ashelford KE, Chuzhanova NA, Fry JC, Jones AJ, Weightman AJ (2005) At least 1 in 20 16S rRNA sequence records currently held in public repositories is estimated to contain substantial anomalies. Appl Environ Microbiol 71: 7724–7736.
[47]
Sibley CD, Grinwis ME, Field TR, Eshaghurshan CS, Faria MM, et al. (2011) Culture enriched molecular profiling of the cystic fibrosis airway microbiome. PLoS One 6: e22702.
[48]
Manzella JP, Kellogg JA, Parsey KS (1995) Corynebacterium pseudodiphtheriticum: a respiratory tract pathogen in adults. Clin Infect Dis 20: 37–40.
[49]
Didelot X, Bowden R, Wilson DJ, Peto TE, Crook DW (2012) Transforming clinical microbiology with bacterial genome sequencing. Nat Rev Genet 13: 601–612.
[50]
Whiteley AS, Jenkins S, Waite I, Kresoje N, Payne H, et al. (2012) Microbial 16S rRNA Ion Tag and community metagenome sequencing using the Ion Torrent (PGM) Platform. J Microbiol Methods 91: 80–88.
[51]
Hongoh Y, Yuzawa H, Ohkuma M, Kudo T (2003) Evaluation of primers and PCR conditions for the analysis of 16S rRNA genes from a natural environment. FEMS Microbiol Lett 221: 299–304.
[52]
Claesson MJ, Wang Q, O'Sullivan O, Greene-Diniz R, Cole JR, et al. (2010) Comparison of two next-generation sequencing technologies for resolving highly complex microbiota composition using tandem variable 16S rRNA gene regions. Nucleic Acids Res 38: e200.
[53]
Guss AM, Roeselers G, Newton IL, Young CR, Klepac-Ceraj V, et al. (2011) Phylogenetic and metabolic diversity of bacteria associated with cystic fibrosis. ISME J 5: 20–29.
[54]
Harris JK, De Groote MA, Sagel SD, Zemanick ET, Kapsner R, et al. (2007) Molecular identification of bacteria in bronchoalveolar lavage fluid from children with cystic fibrosis. Proc Natl Acad Sci U S A 104: 20529–20533.
[55]
Rogers GB, Carroll MP, Bruce KD (2009) Studying bacterial infections through culture-independent approaches. J Med Microbiol 58: 1401–1418.
[56]
van Belkum A, Renders NH, Smith S, Overbeek SE, Verbrugh HA (2000) Comparison of conventional and molecular methods for the detection of bacterial pathogens in sputum samples from cystic fibrosis patients. FEMS Immunol Med Microbiol 27: 51–57.
[57]
Whitby PW, Dick HL, Campbell PW 3rd, Tullis DE, Matlow A, et al. (1998) Comparison of culture and PCR for detection of Burkholderia cepacia in sputum samples of patients with cystic fibrosis. J Clin Microbiol 36: 1642–1645.
[58]
Zemanick ET, Sagel SD, Harris JK (2011) The airway microbiome in cystic fibrosis and implications for treatment. Curr Opin Pediatr 23: 319–324.
[59]
Frank JA, Reich CI, Sharma S, Weisbaum JS, Wilson BA, et al. (2008) Critical evaluation of two primers commonly used for amplification of bacterial 16S rRNA genes. Appl Environ Microbiol 74: 2461–2470.
[60]
Delhaes L, Monchy S, Frealle E, Hubans C, Salleron J, et al. (2012) The airway microbiota in cystic fibrosis: a complex fungal and bacterial community–implications for therapeutic management. PLoS One 7: e36313.
[61]
Duan K, Dammel C, Stein J, Rabin H, Surette MG (2003) Modulation of Pseudomonas aeruginosa gene expression by host microflora through interspecies communication. Mol Microbiol 50: 1477–1491.
[62]
Zhao J, Schloss PD, Kalikin LM, Carmody LA, Foster BK, et al. (2012) Decade-long bacterial community dynamics in cystic fibrosis airways. Proc Natl Acad Sci U S A 109: 5809–5814.
[63]
Tunney MM, Field TR, Moriarty TF, Patrick S, Doering G, et al. (2008) Detection of anaerobic bacteria in high numbers in sputum from patients with cystic fibrosis. Am J Respir Crit Care Med 177: 995–1001.
[64]
Junemann S, Prior K, Szczepanowski R, Harks I, Ehmke B, et al. (2012) Bacterial community shift in treated periodontitis patients revealed by ion torrent 16S rRNA gene amplicon sequencing. PLoS One 7: e41606.
[65]
Wang GC, Wang Y (1996) The frequency of chimeric molecules as a consequence of PCR co-amplification of 16S rRNA genes from different bacterial species. Microbiology 142 (Pt 5) 1107–1114.
[66]
Haas BJ, Gevers D, Earl AM, Feldgarden M, Ward DV, et al. (2011) Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons. Genome Res 21: 494–504.
