Metagenomics of two severe foodborne outbreaks provides diagnostic signatures and signs of coinfection not attainable by traditional methods

Applied and Environmental Microbiology

Volumn 83, Issue 3, 2017, Pages

  Huang, Andrew D ^a   Luo, Chengwei ^b   Pena Gonzalez, Angela ^c   Weigand, Michael R ^a,b   Tarr, Cheryl L ^a   Konstantinidis, Konstantinos T ^b,c  

^a CENTERS FOR DISEASE CONTROL AND PREVENTION   (United States)

^b Georgia Institute of Technology   (United States)

^c GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Diagnostics; Diarrhea; Human gut; Metagenomics; Salmonella

Indexed keywords

DIAGNOSIS; DNA SEQUENCES; ESCHERICHIA COLI; PATHOGENS; PLASMA DIAGNOSTICS; SALMONELLA;

DIARRHEA; DISEASE SURVEILLANCE; FOOD-BORNE PATHOGENS; HUMAN GUTS; METAGENOMICS; MICROBIAL COMMUNITIES; SALMONELLA ENTERICA; STAPHYLOCOCCUS AUREUS;

FOOD MICROBIOLOGY;

ABUNDANCE; BACTERIUM; BIOINFORMATICS; DETECTION METHOD; DIARRHEAL DISEASE; DIGESTIVE SYSTEM; DISEASE INCIDENCE; DNA; GENETIC ANALYSIS; GENOMICS; MICROBIAL COMMUNITY; PATHOGEN; PEST OUTBREAK; PUBLIC HEALTH;

ALABAMA; COLORADO; UNITED STATES;

ESCHERICHIA COLI; SALMONELLA; SALMONELLA ENTERICA SUBSP. ENTERICA SEROVAR HEIDELBERG; STAPHYLOCOCCUS AUREUS;

ALABAMA; COLORADO; EPIDEMIC; ESCHERICHIA COLI; FECES; FOOD POISONING; HUMAN; INTESTINE FLORA; ISOLATION AND PURIFICATION; METAGENOMICS; MICROBIOLOGY; MIXED INFECTION; SALMONELLA ENTERICA; SALMONELLOSIS; STAPHYLOCOCCUS AUREUS;

ALABAMA; COINFECTION; COLORADO; DISEASE OUTBREAKS; ESCHERICHIA COLI; FECES; FOODBORNE DISEASES; GASTROINTESTINAL MICROBIOME; HUMANS; METAGENOMICS; SALMONELLA ENTERICA; SALMONELLA INFECTIONS; STAPHYLOCOCCUS AUREUS;

EID: 85010207128     PISSN: 00992240     EISSN: 10985336     Source Type: Journal    
DOI: 10.1128/AEM.02577-16     Document Type: Article

References (56)

1. Cronquist AB, Mody RK, Atkinson R, Besser J, Tobin D'Angelo M, Hurd S, Robinson T, Nicholson C, Mahon BE. 2012. Impacts of cultureindependent diagnostic practices on public health surveillance for bacterial enteric pathogens. Clin Infect Dis 54(Suppl 5):S432-S439. https://doi.org/10.1093/cid/cis267
2. Amann RI, Ludwig W, Schleifer KH. 1995. Phylogenetic identification and in situ detection of individual microbial cells without cultivation. Microbiol Rev 59:143-169
3. Eckburg PB, Bik EM, Bernstein CN, Purdom E, Dethlefsen L, Sargent M, Gill SR, Nelson KE, Relman DA. 2005. Diversity of the human intestinal microbial flora. Science 308:1635-1638. https://doi.org/10.1126/science.1110591
4. Hold GL, Pryde SE, Russell VJ, Furrie E, Flint HJ. 2002. Assessment of microbial diversity in human colonic samples by 16S rDNA sequence analysis. FEMS Microbiol Ecol 39:33-39. https://doi.org/10.1111/j.1574-6941.2002.tb00904.x
5. Scallan E, Hoekstra RM, Angulo FJ, Tauxe RV, Widdowson MA, Roy SL. 2011. Foodborne illness acquired in the United States-major pathogens. Emerg Infect Dis 17:7-15. https://doi.org/10.3201/eid1701.P11101
6. Acinas SG, Sarma-Rupavtarm R, Klepac-Ceraj V, Polz MF. 2005. PCRinduced sequence artifacts and bias: insights from comparison of two 16S rRNA clone libraries constructed from the same sample. Appl Environ Microbiol 71:8966-8969. https://doi.org/10.1128/AEM.71.12.8966-8969.2005
7. Loman NJ, Constantinidou C, Christner M, Rohde H, Chan JZ, Quick J, Weir JC, Quince C, Smith GP, Betley JR, Aepfelbacher M, Pallen MJ. 2013. A culture-independent sequence-based metagenomics approach to the investigation of an outbreak of Shiga-toxigenic Escherichia coli O104:H4. JAMA 309:1502-1510. https://doi.org/10.1001/jama.2013.3231
8. Mellmann A, Harmsen D, Cummings CA, Zentz EB, Leopold SR, Rico A, Prior K, Szczepanowski R, Ji Y, Zhang W, McLaughlin SF, Henkhaus JK, Leopold B, Bielaszewska M, Prager R, Brzoska PM, Moore RL, Guenther S, Rothberg JM, Karch H. 2011. Prospective genomic characterization of the German enterohemorrhagic Escherichia coli O104:H4 outbreak by rapid next generation sequencing technology. PLoS One 6:e22751. https://doi.org/10.1371/journal.pone.0022751
9. Tranter HS. 1990. Foodborne staphylococcal illness. Lancet 336: 1044-1046. https://doi.org/10.1016/0140-6736(90)92500-H
10. Baird-Parker AC. 1990. Foodborne salmonellosis. Lancet 336:1231-1235. https://doi.org/10.1016/0140-6736(90)92844-8
11. Rodriguez RL, Konstantinidis KT. 2014. Estimating coverage in metagenomic data sets and why it matters. ISME J 8:2349-2351. https://doi.org/10.1038/ismej.2014.76
12. Rodriguez RL-M, Konstantinidis KT. 2014. Bypassing cultivation to identify bacterial species. Microbe Mag 9:111-118. https://doi.org/10.1128/microbe.9.111.1
13. Peng Y, Leung HC, Yiu SM, Chin FY. 2012. IDBA-UD: a de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth. Bioinformatics 28:1420-1428. https://doi.org/10.1093/bioinformatics/bts174
14. Haider B, Ahn T-H, Bushnell B, Chai J, Copeland A, Pan C. 2014. Omega: an overlap-graph de novo assembler for metagenomics. Bioinformatics 30:2717-2722. https://doi.org/10.1093/bioinformatics/btu395
15. Luo C, Knight R, Siljander H, Knip M, Xavier RJ, Gevers D. 2015. Con-Strains identifies microbial strains in metagenomic datasets. Nat Biotechnol 33:1045-1052. https://doi.org/10.1038/nbt.3319
16. Human Microbiome Project Consortium. 2012. A framework for human microbiome research. Nature 486:215-221. https://doi.org/10.1038/nature11209
17. Pusz P, Bok E, Mazurek J, Stosik M, Baldy-Chudzik K. 2014. Type 1 fimbriae in commensal Escherichia coli derived from healthy humans. Acta Biochim Pol 61:389-392
18. 2 specifically exploits the NLR cochaperone activity of SGT1 to subvert immunity. PLoS Pathog 9:e1003518. https://doi.org/10.1371/journal.ppat.1003518
19. Moran GJ, Krishnadasan A, Gorwitz RJ, Fosheim GE, McDougal LK, Carey RB, Talan DA, EMERGEncy ID Net Study Group. 2006. Methicillin-resistant S. aureus infections among patients in the emergency department. N Engl J Med 355:666-674. https://doi.org/10.1056/NEJMoa055356
20. Singh P, Teal TK, Marsh TL, Tiedje JM, Mosci R, Jernigan K, Zell A, Newton DW, Salimnia H, Lephart P, Sundin D, Khalife W, Britton RA, Rudrik JT, Manning SD. 2015. Intestinal microbial communities associated with acute enteric infections and disease recovery. Microbiome 3:1-12. https://doi.org/10.1186/s40168-014-0066-1
21. Greenblum S, Turnbaugh PJ, Borenstein E. 2012. Metagenomic systems biology of the human gut microbiome reveals topological shifts associated with obesity and inflammatory bowel disease. Proc Natl Acad Sci U S A 109:594-599. https://doi.org/10.1073/pnas.1116053109
22. Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan A, Ley RE, Sogin ML, Jones WJ, Roe BA, Affourtit JP, Egholm M, Henrissat B, Heath AC, Knight R, Gordon JI. 2009. A core gut microbiome in obese and lean twins. Nature 457:480-484. https://doi.org/10.1038/nature07540
23. Schloissnig S, Arumugam M, Sunagawa S, Mitreva M, Tap J, Zhu A, Waller A, Mende DR, Kultima JR, Martin J, Kota K, Sunyaev SR, Weinstock GM, Bork P. 2013. Genomic variation landscape of the human gut microbiome. Nature 493:45-50. https://doi.org/10.1038/nature11711
24. Pop M, Walker AW, Paulson J, Lindsay B, Antonio M, Hossain MA, Oundo J, Tamboura B, Mai V, Astrovskaya I, Corrada Bravo H, Rance R, Stares M, Levine MM, Panchalingam S, Kotloff K, Ikumapayi UN, Ebruke C, Adeyemi M, Ahmed D, Ahmed F, Alam MT, Amin R, Siddiqui S, Ochieng JB, Ouma E, Juma J, Mailu E, Omore R, Morris JG, Breiman RF, Saha D, Parkhill J, Nataro JP, Stine OC. 2014. Diarrhea in young children from low-income countries leads to large-scale alterations in intestinal microbiota composition. Genome Biol 15:R76. https://doi.org/10.1186/gb-2014-15-6-r76
25. Carroll IM, Ringel-Kulka T, Siddle JP, Ringel Y. 2012. Alterations in composition and diversity of the intestinal microbiota in patients with diarrhea-predominant irritable bowel syndrome. Neurogastroenterol Motil 24:521-530, e248. https://doi.org/10.1111/j.1365-2982.2012 .01891.x
26. David LA, Weil A, Ryan ET, Calderwood SB, Harris JB, Chowdhury F, Begum Y, Qadri F, LaRocque RC, Turnbaugh PJ. 2015. Gut microbial succession follows acute secretory diarrhea in humans. mBio 6:e00381-15. https://doi.org/10.1128/mBio.00381-15
27. Konstantinidis KT, Tiedje JM. 2007. Prokaryotic taxonomy and phylogeny in the genomic era: advancements and challenges ahead. Curr Opin Microbiol 10:504-509. https://doi.org/10.1016/j.mib.2007.08.006
28. Cox MP, Peterson DA, Biggs PJ. 2010. SolexaQA: at-a-glance quality assessment of Illumina second-generation sequencing data. BMC Bioinformatics 11:485. https://doi.org/10.1186/1471-2105-11-485
29. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, Lesin VM, Nikolenko SI, Pham S, Prjibelski AD, Pyshkin AV, Sirotkin AV, Vyahhi N, Tesler G, Alekseyev MA, Pevzner PA. 2012. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol 19:455-477. https://doi.org/10.1089/cmb.2012.0021
30. Treangen TJ, Ondov BD, Koren S, Phillippy AM. 2014. The Harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes. Genome Biol 15:524. https://doi.org/10.1186/s13059-014-0524-x
31. Stamatakis A. 2014. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30:1312-1313. https://doi.org/10.1093/bioinformatics/btu033
32. Rambaut A. 2011. FigTree. Molecular evolution, phylogenetics and epidemiology. http://tree.bio.ed.ac.uk/software/figtree/
33. Rotmistrovsky K, Agarwala R. 2011. BMTagger: Best Match Tagger for removing human reads from metagenomics datasets. ftp://ftp.ncbi.nlm.nih.gov/pub/agarwala/bmtagger/
34. Luo C, Tsementzi D, Kyrpides NC, Konstantinidis KT. 2012. Individual genome assembly from complex community short-read metagenomic datasets. ISME J 6:898-901. https://doi.org/10.1038/ismej.2011.147
35. Langmead B, Salzberg SL. 2012. Fast gapped-read alignment with Bowtie 2. Nat Methods 9:357-359. https://doi.org/10.1038/nmeth.1923
36. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, 1000 Genome Project Data Processing Subgroup. 2009 The Sequence Alignment/Map format and SAMtools. Bioinformatics 25:2078-2079. https://doi.org/10.1093/bioinformatics/btp352
37. Kang DD, Froula J, Egan R, Wang Z. 2015. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ 3:e1165. https://doi.org/10.7717/peerj.1165
38. Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. 2015. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res 25:1043-1055. https://doi.org/10.1101/gr.186072.114
39. Kent WJ. 2002. BLAT-the BLAST-like alignment tool. Genome Res 12: 656-664. https://doi.org/10.1101/gr.229202
40. Segata N, Waldron L, Ballarini A, Narasimhan V, Jousson O, Huttenhower C. 2012. Metagenomic microbial community profiling using unique clade-specific marker genes. Nat Methods 9:811-814. https://doi.org/10.1038/nmeth.2066
41. Su X, Pan W, Song B, Xu J, Ning K. 2014. Parallel-META 2.0: enhanced metagenomic data analysis with functional annotation, high performance computing and advanced visualization. PLoS One 9:e89323. https://doi.org/10.1371/journal.pone.0089323
42. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Pena AG, Goodrich JK, Gordon JI, Huttley GA, Kelley ST, Knights D, Koenig JE, Ley RE, Lozupone CA, McDonald D, Muegge BD, Pirrung M, Reeder J, Sevinsky JR, Turnbaugh PJ, Walters WA, Widmann J, Yatsunenko T, Zaneveld J, Knight R. 2010. QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7:335-336. https://doi.org/10.1038/nmeth.f.303
43. Edgar RC. 2010. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26:2460-2461. https://doi.org/10.1093/bioinformatics/btq461
44. Wang Q, Garrity GM, Tiedje JM, Cole JR. 2007. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 73:5261-5267. https://doi.org/10.1128/AEM.00062-07
45. Anders S, Huber W. 2010. Differential expression analysis for sequence count data. Genome Biol 11:R106. https://doi.org/10.1186/gb-2010-11-10-r106
46. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. 1990. Basic local alignment search tool. J Mol Biol 215:403-410. https://doi.org/10.1016/S0022-2836(05)80360-2
47. Konstantinidis KT, DeLong EF. 2008. Genomic patterns of recombination, clonal divergence and environment in marine microbial populations. ISME J 2:1052-1065. https://doi.org/10.1038/ismej.2008.62
48. Borodovsky M, Lomsadze A. 2014. Gene identification in prokaryotic genomes, phages, metagenomes, and EST sequences with GeneMarkS suite. Curr Protoc Bioinformatics Chapter 4:Unit 4.5-1-4.5-17
49. Suzek BE, Huang H, McGarvey P, Mazumder R, Wu CH. 2007. UniRef: comprehensive and non-redundant UniProt reference clusters. Bioinformatics 23:1282-1288. https://doi.org/10.1093/bioinformatics/btm098
50. Chen L, Yang J, Yu J, Yao Z, Sun L, Shen Y, Jin Q. 2005. VFDB: a reference database for bacterial virulence factors. Nucleic Acids Res 33: D325-D328
51. Luo C, Walk ST, Gordon DM, Feldgarden M, Tiedje JM, Konstantinidis KT. 2011. Genome sequencing of environmental Escherichia coli expands understanding of the ecology and speciation of the model bacterial species. Proc Natl Acad Sci U S A 108:7200-7205. https://doi.org/10.1073/pnas.1015622108
52. Zhou Z, McCann A, Weill FX, Blin C, Nair S, Wain J, Dougan G, Achtman M. 2014. Transient Darwinian selection in Salmonella enterica serovar Paratyphi A during 450 years of global spread of enteric fever. Proc Natl Acad Sci U S A 111:12199-12204. https://doi.org/10.1073/pnas .1411012111
53. Edgar RC. 2004. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 32:1792-1797. https://doi.org/10.1093/nar/gkh340
54. Talavera G, Castresana J. 2007. Improvement of phylogenies after removing divergent and ambiguously aligned blocks from protein sequence alignments. Syst Biol 56:564-577. https://doi.org/10.1080/10635150701472164
55. Price MN, Dehal PS, Arkin AP. 2010. FastTree 2-approximately maximum-likelihood trees for large alignments. PLoS One 5:e9490. https://doi.org/10.1371/journal.pone.0009490
56. Human Microbiome Project Consortium. 2012. Structure, function and diversity of the healthy human microbiome. Nature 486:207-214. https://doi.org/10.1038/nature11234