Skip to main content

Abstract

Two decades after the first bacterial genome sequencing by Fleischmann et al. in 1995, bacterial genomics gained an important role both in the identification and antimicrobial susceptibility testing of bacterial pathogens. Continuous advances in high throughput sequencing (Next Generation Sequencing, NGS) technologies have empowered today’s clinical microbiology laboratory with vast potential in pathogen detection, identification and characterisation. Bacterial whole-genome sequencing (WGS) is the most promising aspect of these technologies. Most clinical microbiology laboratories are not currently ready to adopt and implement WGS in their routine, mostly because of costs, time to results and data interpretation issues and it is currently applied in specific niches, such as molecular epidemiology and outbreak investigations, as well as identification and susceptibility testing of difficult-to-grow yet clinically important pathogens, such as Mycobacterium tuberculosis. In this chapter, the application of WGS in the routine clinical microbiology laboratories for identification and susceptibility testing of common and fastidious bacteria will be discussed with specific emphasis on mycobacteria as an example of utilisation of NGS technologies on clinically important slow-growing pathogens.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 119.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 159.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Rossen JWA, Friedrich AW, Moran-Gilad J (2018) Practical issues in implementing whole-genome-sequencing in routine diagnostic microbiology. Clin Microbiol Infect 24:355–360

    Article  CAS  PubMed  Google Scholar 

  2. Judge K, Harris SR, Reuter S, Parkhill J, Peacock SJ (2015) Early insights into the potential of the Oxford Nanopore MinION for the detection of antimicrobial resistance genes. J Antimicrob Chemother 70:2775–2778

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Reuter S, Ellington MJ, Cartwright EJP et al (2014) Europe PMC Funders Group. Rapid bacterial whole-genome sequencing to enhance diagnostic and public health microbiology. JAMA Intern Med 173:1397–1404

    Article  Google Scholar 

  4. Köser CU, Fraser LJ, Ioannou A et al (2014) Rapid single-colony whole-genome sequencing of bacterial pathogens. J Antimicrob Chemother 69:1275–1281

    Article  PubMed  CAS  Google Scholar 

  5. Cummings CA, Bormann Chung CA, Fang R et al (2010) Accurate, rapid and high-throughput detection of strain-specific polymorphisms in Bacillus anthracis and Yersinia pestis by next-generation sequencing. Investig Genet 1:1–14

    Article  CAS  Google Scholar 

  6. Bertelli C, Greub G (2013) Rapid bacterial genome sequencing: methods and applications in clinical microbiology. Clin Microbiol Infect 19:803–813

    Article  CAS  PubMed  Google Scholar 

  7. Hasman H, Saputra D, Sicheritz-Ponten T, Lund O, Svendsen CA, Frimodt-Moller N, Aarestrup FM (2014) Rapid whole-genome sequencing for detection and characterization of microorganisms directly from clinical samples. J Clin Microbiol 52:139–146

    Article  PubMed  PubMed Central  Google Scholar 

  8. Adey A, Morrison HG, Asan et al (2010) Rapid, low-input, low-bias construction of shotgun fragment libraries by high-density in vitro transposition. Genome Biol 11:R119

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Besser J, Carleton HA, Gerner-Smidt P, Lindsey RL, Trees E (2018) Next-generation sequencing technologies and their application to the study and control of bacterial infections. Clin Microbiol Infect 24:335–341

    Article  CAS  PubMed  Google Scholar 

  10. Gargis AS, Kalman L, Berry MW et al (2013) Assuring the quality of next-generation sequencing in clinical laboratory practice. Nat Biotechnol 30(11):1033–1036. https://doi.org/10.1038/nbt.2403.Assuring

  11. Roy S, Coldren C, Karunamurthy A et al (2018) Standards and guidelines for validating next-generation sequencing bioinformatics pipelines: a joint recommendation of the Association for Molecular Pathology and the College of American Pathologists. J Mol Diagn 20:4–27

    Article  CAS  PubMed  Google Scholar 

  12. Gargis AS, Kalman L, Bick DP et al (2015) Good laboratory practice for clinical next-generation sequencing informatics pipelines. Nat Biotechnol 33:689–693

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Lefterova MI, Suarez CJ, Banaei N, Pinsky BA (2015) Next-generation sequencing for infectious disease diagnosis and management: a report of the Association for Molecular Pathology. J Mol Diagn 17:623–634

    Article  CAS  PubMed  Google Scholar 

  14. Pont-Kingdon G, Gedge F, Wooderchak-Donahue W, Schrijver I, Weck KE, Kant JA, Oglesbee D, Bayrak-Toydemir P, Lyon E (2012) Design and analytical validation of clinical DNA sequencing assays. Arch Pathol Lab Med 136:41–46

    Article  CAS  PubMed  Google Scholar 

  15. Gargis A, Kalman L, Lubin IM (2016) Assuring the quality of next-generation sequencing in clinical laboratory practice. J Clin Microbiol 54:2857–2865

    Article  PubMed  PubMed Central  Google Scholar 

  16. Rehm HL, Bale SJ, Bayrak-toydemir P, Jonathan S, Brown KK, Deignan JL, Friez MJ, Birgit H (2013) ACMG clinical laboratory standards for next-generation sequencing. Genet Med 15:733–747

    Article  PubMed  PubMed Central  Google Scholar 

  17. Moran-Gilad J, Sintchenko V, Pedersen SK, Wolfgang WJ, Pettengill J, Strain E, Hendriksen RS (2015) Proficiency testing for bacterial whole genome sequencing: an end-user survey of current capabilities, requirements and priorities. BMC Infect Dis 15:1–10

    Article  Google Scholar 

  18. Long SW, Williams D, Valson C, Cantu CC, Cernoch P, Musser JM, Olsen RJ (2013) A genomic day in the life of a clinical microbiology laboratory. J Clin Microbiol 51:1272–1277

    Article  PubMed  PubMed Central  Google Scholar 

  19. Anson LW, Chau K, Sanderson N et al (2018) DNA extraction from primary liquid blood cultures for bloodstream infection diagnosis using whole genome sequencing. J Med Microbiol 67:347–357

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Clark SA, Doyle R, Lucidarme J, Borrow R, Breuer J (2018) Targeted DNA enrichment and whole genome sequencing of Neisseria meningitidis directly from clinical specimens. Int J Med Microbiol 308:256–262

    Article  CAS  PubMed  Google Scholar 

  21. Wilson MR, Naccache SN, Samayoa E et al (2014) Actionable diagnosis of neuroleptospirosis by next-generation sequencing. N Engl J Med 370:2408–2417

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Seth-Smith HMB, Harris SR, Skilton RJ et al (2013) Whole-genome sequences of chlamydia trachomatis directly from clinical samples without culture. Genome Res 23:855–866

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Christiansen MT, Brown AC, Kundu S et al (2014) Whole-genome enrichment and sequencing of chlamydia trachomatis directly from clinical samples. BMC Infect Dis 14:1–11

    Article  CAS  Google Scholar 

  24. Andersson P, Klein M, Lilliebridge RA, Giffard PM (2013) Sequences of multiple bacterial genomes and a chlamydia trachomatis genotype from direct sequencing of DNA derived from a vaginal swab diagnostic specimen. Clin Microbiol Infect 19:E405–E408

    Article  CAS  PubMed  Google Scholar 

  25. Joseph SJ, Li B, Ghonasgi T, Haase CP, Qin ZS, Dean D, Read TD (2014) Direct amplification, sequencing and profiling of chlamydia trachomatis strains in single and mixed infection clinical samples. PLoS One. https://doi.org/10.1371/journal.pone.0099290

  26. Wołkowicz T (2017) The utility and perspectives of NGS-based methods in BSL-3 and BSL-4 laboratory – sequencing and analysis strategies. Brief Funct Genomics 17(6):471–476.

    Google Scholar 

  27. Mitchell SL, Mattei LM, Alby K (2017) Whole genome characterization of a naturally occurring vancomycin-dependent Enterococcus faecium from a patient with bacteremia. Infect Genet Evol 52:96–99

    Article  CAS  PubMed  Google Scholar 

  28. Stoesser N, Batty EM, Eyre DW, Morgan M, Wyllie DH, Del Ojo EC, Johnson JR, Walker AS, Peto TEA, Crook DW (2013) Predicting antimicrobial susceptibilities for Escherichia coli and Klebsiella pneumoniae isolates using whole genomic sequence data. J Antimicrob Chemother 68:2234–2244

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Sadouki Z, Day MR, Doumith M, Chattaway MA, Dallman TJ, Hopkins KL, Elson R, Woodford N, Godbole G, Jenkins C (2017) Comparison of phenotypic and WGS-derived antimicrobial resistance profiles of Shigella sonnei isolated from cases of diarrhoeal disease in England and Wales, 2015. J Antimicrob Chemother 72:2496–2502

    Article  CAS  PubMed  Google Scholar 

  30. Shelburne SA, Kim J, Munita JM et al (2017) Whole-genome sequencing accurately identifies resistance to extended-spectrum β-lactams for major gram-negative bacterial pathogens. Clin Infect Dis 65:738–745

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Bradley P, Gordon NC, Walker TM et al (2015) Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis. Nat Commun. https://doi.org/10.1038/ncomms10063

  32. Jaillard M, van Belkum A, Cady KC et al (2017) Correlation between phenotypic antibiotic susceptibility and the resistome in Pseudomonas aeruginosa. Int J Antimicrob Agents 50:210–218

    Article  CAS  PubMed  Google Scholar 

  33. Zankari E, Hasman H, Kaas RS, Seyfarth AM, Agersø Y, Lund O, Larsen MV, Aarestrup FM (2013) Genotyping using whole-genome sequencing is a realistic alternative to surveillance based on phenotypic antimicrobial susceptibility testing. J Antimicrob Chemother 68:771–777

    Article  CAS  PubMed  Google Scholar 

  34. Zankari E, Hasman H, Cosentino S, Vestergaard M, Rasmussen S, Lund O, Aarestrup FM, Larsen MV (2012) Identification of acquired antimicrobial resistance genes. J Antimicrob Chemother 67:2640–2644

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Neuert S, Nair S, Day MR et al (2018) Prediction of phenotypic antimicrobial resistance profiles from whole genome sequences of non-typhoidal Salmonella enterica. Front Microbiol 9:1–11

    Article  Google Scholar 

  36. Gordon NC, Price JR, Cole K et al (2014) Prediction of staphylococcus aureus antimicrobial resistance by whole-genome sequencing. J Clin Microbiol 52:1182–1191

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Tyson GH, McDermott PF, Li C et al (2015) WGS accurately predicts antimicrobial resistance in Escherichia coli. J Antimicrob Chemother 70:2763–2769

    Article  CAS  PubMed  Google Scholar 

  38. Mcdermott PF, Tyson GH, Kabera C, Chen Y, Li C, Folster JP, Ayers SL, Lam C, Tate HP (2016) Whole-genome sequencing for detecting antimicrobial resistance in. Antimicrob Agents Chemother 60:5515–5520

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Holden MTG, Hsu L, Kurt K et al (2013) A genomic portrait of the emerfences, evolution, and global spread of methicillin-resistant Staphylococcus aureus. Genome Res 23:653–664

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Eyre DW, Golubchik T, Gordon NC et al (2012) A pilot study of rapid benchtop sequencing of Staphylococcus aureus and Clostridium difficile for outbreak detection and surveillance. BMJ Open 2:1–9

    Article  Google Scholar 

  41. Hazen TH, Zhao L, Boutin MA, Stancil A, Robinson G, Harris AD, Rasko DA, Johnson JK (2014) Comparative genomics of an IncA/C multidrug resistance plasmid from Escherichia coli and Klebsiella isolates from intensive care unit patients and the utility of whole-genome sequencing in health care settings. Antimicrob Agents Chemother 58:4814–4825

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Kos VN, Déraspe M, McLaughlin RE, Whiteaker JD, Roy PH, Alm RA, Corbeil J, Gardner H (2015) The resistome of Pseudomonas seudomonas aeruginosa in relationship to phenotypic susceptibility. Antimicrob Agents Chemother 59:427–436

    Article  PubMed  CAS  Google Scholar 

  43. Luo Y, Luo R, Ding H, Ren X, Luo H, Zhang Y, Ye L, Cui S (2017) Characterization of carbapenem-resistant Escherichia coli isolates through the whole-genome sequencing analysis. Microb Drug Resist 24(2). https://doi.org/10.1089/mdr.2017.0079

  44. Ellington MJ, Ekelund O, Aarestrup FM et al (2017) The role of whole genome sequencing in antimicrobial susceptibility testing of bacteria: report from the EUCAST subcommittee. Clin Microbiol Infect 23:2–22

    Article  CAS  PubMed  Google Scholar 

  45. Xavier BB, Das AJ, Cochrane G, De Ganck S, Kumar-Singh S, Aarestrup FM, Goossens H, Malhotra-Kumar S (2016) Consolidating and exploring antibiotic resistance gene data resources. J Clin Microbiol 54:851–859

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. McArthur AG, Tsang KK (2017) Antimicrobial resistance surveillance in the genomic age. Ann N Y Acad Sci 1388:78–91

    Article  PubMed  Google Scholar 

  47. Rowe W, Baker KS, Verner-Jeffreys D, Baker-Austin C, Ryan JJ, Maskell D, Pearce G (2015) Search engine for antimicrobial resistance: a cloud compatible pipeline and web interface for rapidly detecting antimicrobial resistance genes directly from sequence data. PLoS One. https://doi.org/10.1371/journal.pone.0133492

  48. Gupta SK, Padmanabhan BR, Diene SM, Lopez-Rojas R, Kempf M, Landraud L, Rolain JM (2014) ARG-annot, a new bioinformatic tool to discover antibiotic resistance genes in bacterial genomes. Antimicrob Agents Chemother 58:212–220

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  49. de Man TJB, Limbago BM (2016) SSTAR, a stand-alone easy-to-use antimicrobial resistance gene predictor. mSphere 1:1–10

    Google Scholar 

  50. Davis JJ, Boisvert S, Brettin T et al (2016) Antimicrobial resistance prediction in PATRIC and RAST. Sci Rep 6:1–12

    Article  CAS  Google Scholar 

  51. Brittnacher MJ, Heltshe SL, Hayden HS, Radey MC, Weiss EJ, Damman CJ, Zisman TL, Suskind DL, Miller SI (2016) GUTSS: an alignment-free sequence comparison method for use in human intestinal microbiome and fecal microbiota transplantation analysis. PLoS One 11:1–16

    Article  CAS  Google Scholar 

  52. Jia B, Raphenya AR, Alcock B et al (2017) CARD 2017: expansion and model-centric curation of the comprehensive antibiotic resistance database. Nucleic Acids Res 45:D566–D573

    Article  CAS  PubMed  Google Scholar 

  53. Lakin SM, Dean C, Noyes NR et al (2017) MEGARes: an antimicrobial resistance database for high throughput sequencing. Nucleic Acids Res 45:D574–D580

    Article  CAS  PubMed  Google Scholar 

  54. Galagan JE (2014) Genomic insights into tuberculosis. Nat Rev Genet 15:307–320

    Article  CAS  PubMed  Google Scholar 

  55. WHO (2017) Global tunerculosis report 2017. WHO, Geneva

    Google Scholar 

  56. Lange C, Chesov D, Heyckendorf J, Leung CC, Udwadia Z, Dheda K (2018) Drug-resistant tuberculosis: an update on disease burden, diagnosis and treatment. Respirology. https://doi.org/10.1111/resp.13304

  57. McNerney R, Zignol M, Clark TG (2018) Use of whole genome sequencing in surveillance of drug resistant tuberculosis. Expert Rev Anti-Infect Ther 16:433–442

    Article  CAS  PubMed  Google Scholar 

  58. Piersimoni C, Olivieri A, Benacchio L, Scarparo C (2006) MINIREVIEW current perspectives on drug susceptibility testing of Mycobacterium tuberculosis complex : the automated nonradiometric systems. Society 44:20–28

    CAS  Google Scholar 

  59. Lange C, Abubakar I, Alffenaar JWC et al (2014) Management of patients with multidrugresistant/extensively drug-resistant tuberculosis in Europe: a TBNET consensus statement. Eur Respir J 44:23–63

    Article  PubMed  PubMed Central  Google Scholar 

  60. Domínguez J, Boettger EC, Cirillo D et al (2016) Clinical implications of molecular drug resistance testing for Mycobacterium tuberculosis: a TBNET/RESIST-TB consensus statement. Int J Tuberc Lung Dis 20:24–42

    Article  PubMed  Google Scholar 

  61. Feliciano CS, Namburete EI, Rodrigues Plaça J, Peronni K, Dippenaar A, Warren RM, Silva WA, Bollela VR (2018) Accuracy of whole genome sequencing versus phenotypic (MGIT) and commercial molecular tests for detection of drug-resistant Mycobacterium tuberculosis isolated from patients in Brazil and Mozambique. Tuberculosis 110:59–67

    Article  CAS  PubMed  Google Scholar 

  62. Hameed HMA, Islam MM, Chhotaray C et al (2018) Molecular targets related drug resistance mechanisms in MDR-, XDR-, and TDR-Mycobacterium tuberculosis strains. Front Cell Infect Microbiol 8:114

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  63. Gillespie S (2002) Evolution of drug resistance in Mycobacterium tuberculosis: clinical and molecular perspective. Antimicrob Agents Chemother 46:267–274

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Miotto P, Tessema B, Tagliani E et al (2017) A standardised method for interpreting the association between mutations and phenotypic drug resistance in Mycobacterium tuberculosis. Eur Respir J 50(6):1701354. https://doi.org/10.1183/13993003.01354-2017

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Walker TM, Kohl TA, Omar SV et al (2015) Whole-genome sequencing for prediction of Mycobacterium tuberculosis drug susceptibility and resistance: a retrospective cohort study. Lancet Infect Dis 15:1193–1202

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Witney AA, Gould KA, Arnold A et al (2015) Clinical application of whole-genome sequencing to inform treatment for multidrug-resistant tuberculosis cases. J Clin Microbiol 53:1473–1483

    Article  PubMed  PubMed Central  Google Scholar 

  67. Pankhurst LJ, del Ojo EC, Votintseva AA et al (2016) Rapid, comprehensive, and affordable mycobacterial diagnosis with whole-genome sequencing: a prospective study. Lancet Respir Med 4:49–58

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Manson AL, Cohen KA, Abeel T, Desjardins CA, Cho N, Gabrielian A, Gomez J, Jodals AM, Joloba M (2017) HHS Public Access 49:395–402

    CAS  Google Scholar 

  69. Coll F, Phelan J, Hill-Cawthorne GA et al (2018) Genome-wide analysis of multi- and extensively drug-resistant Mycobacterium tuberculosis. Nat Genet 50:307–316

    Article  PubMed  Google Scholar 

  70. Bryant JM, Schürch AC, van Deutekom H et al (2013) Inferring patient to patient transmission of Mycobacterium tuberculosis from whole genome sequencing data. BMC Infect Dis 13:1–12

    Article  Google Scholar 

  71. Glynn JR, Guerra-Assunção JA, Houben RMGJ et al (2015) Whole genome sequencing shows a low proportion of tuberculosis disease is attributable to known close contacts in rural Malawi. PLoS One 10:1–12

    Article  CAS  Google Scholar 

  72. Guthrie JL, Delli Pizzi A, Roth D, Kong C, Jorgensen D, Rodrigues M, Tang P, Cook VJ, Johnston J, Gardy JL (2018) Genotyping and whole genome sequencing to identify tuberculosis transmission to Pediatric patients in British Columbia, Canada, 2005–2014. J Infect Dis. https://doi.org/10.1093/infdis/jiy278

  73. Holden KL, Bradley CW, Curran ET, Pollard C, Smith G, Holden E, Glynn P, Garvey MI (2018) Unmasking leading to a healthcare worker Mycobacterium tuberculosis transmission. J Hosp Infect:1–7

    Google Scholar 

  74. Gardy JL, Johnston JC, Sui SJH et al (2011) Whole-genome sequencing and social-network analysis of a tuberculosis outbreak. N Engl J Med 364:730–739

    Article  CAS  PubMed  Google Scholar 

  75. Casali N, Nikolayevskyy V, Balabanova Y et al (2014) Europe PMC Funders Group. Evolution and transmission of drug resistant tuberculosis in a Russian population. Nat Genet 46:279–286

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Zeng X, Kwok JS-L, Yang KY, Leung KS-S, Shi M, Yang Z, Yam W-C, Tsui SK-W (2018) Whole genome sequencing data of 1110 Mycobacterium tuberculosis isolates identifies insertions and deletions associated with drug resistance. BMC Genomics 19:365

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  77. Zhang H, Li D, Zhao L et al (2013) Genome sequencing of 161 Mycobacterium tuberculosis isolates from China identifies genes and intergenic regions associated with drug resistance. Nat Genet 45:1255–1260

    Article  CAS  PubMed  Google Scholar 

  78. Zignol M, Cabibbe AM, Dean AS et al (2018) Genetic sequencing for surveillance of drug resistance in tuberculosis in highly endemic countries: a multi-country population-based surveillance study. Lancet Infect Dis 18:675–683

    Article  PubMed  PubMed Central  Google Scholar 

  79. Quan TP, Bawa Z, Foster D et al (2017) Evaluation of whole genome sequencing for mycobacterial species identification and drug susceptibility testing in a clinical setting: a large-scale prospective assessment of performance against line-probe assays and phenotyping. J Clin Microbiol 56:JCM.01480-17

    Article  Google Scholar 

  80. Coll F, McNerney R, Preston MD et al (2015) Rapid determination of anti-tuberculosis drug resistance from whole-genome sequences. Genome Med 7:1–10

    Article  CAS  Google Scholar 

  81. Chatterjee A, Nilgiriwala K, Saranath D, Rodrigues C, Mistry N (2017) Whole genome sequencing of clinical strains of Mycobacterium tuberculosis from Mumbai, India: a potential tool for determining drug-resistance and strain lineage. Tuberculosis 107:63–72

    Article  CAS  PubMed  Google Scholar 

  82. Votintseva AA, Pankhurst LJ, Anson LW et al (2015) Mycobacterial DNA extraction for whole-genome sequencing from early positive liquid (MGIT) cultures. J Clin Microbiol 53:1137–1143

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Brown AC, Bryant JM, Einer-Jensen K et al (2015) Rapid whole-genome sequencing of mycobacterium tuberculosis isolates directly from clinical samples. J Clin Microbiol 53:2230–2237

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Cohen T, van Helden PD, Wilson D, Colijn C, McLaughlin MM, Abubakar I, Warren RM (2012) Mixed-strain Mycobacterium tuberculosis infections and the implications for tuberculosis treatment and control. Clin Microbiol Rev 25:708–719

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. McIvor A, Koornhof H, Kana BD (2017) Relapse, re-infection and mixed infections in tuberculosis disease. Pathog Dis 75:1–16

    Article  CAS  Google Scholar 

  86. Macedo R, Nunes A, Portugal I, Duarte S, Vieira L, Gomes JP (2018) Dissecting whole-genome sequencing-based online tools for predicting resistance in Mycobacterium tuberculosis: can we use them for clinical decision guidance? Tuberculosis 110:44–51

    Article  CAS  PubMed  Google Scholar 

  87. Feuerriegel S, Schleusener V, Beckert P, Kohl TA, Miotto P, Cirillo DM, Cabibbe AM, Niemann S, Fellenberg K (2015) PhyResSE: a web tool delineating Mycobacterium tuberculosis antibiotic resistance and lineage from whole-genome sequencing data. J Clin Microbiol 53:1908–1914

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Sekizuka T, Yamashita A, Murase Y, Iwamoto T, Mitarai S, Kato S, Kuroda M (2015) TGS-TB: Total genotyping solution for Mycobacterium tuberculosis using short-read whole-genome sequencing. PLoS One 10:1–12

    Article  CAS  Google Scholar 

  89. van Beek J, Haanperä M, Smit PW, Mentula S, Soini H (2018) Evaluation of whole genome sequencing and software tools for drug susceptibility testing of Mycobacterium tuberculosis. Clin Microbiol Infect 25(1):82–86. https://doi.org/10.1016/j.cmi.2018.03.041

    Article  CAS  PubMed  Google Scholar 

  90. Cirillo DM, Miotto P, Tortoli E (2017) Evolution of phenotypic and molecular drug susceptibility testing. Adv Exp Med Biol 1019:221–246. https://doi.org/10.1007/978-3-319-64371-7_12

    Article  CAS  PubMed  Google Scholar 

  91. Gcebe N, Rutten VPMG, Van Pittius NG, Naicker B, Michel AL (2018) Mycobacterium komaniense sp. Nov., a rapidly growing nontuberculous Mycobacterium species detected in South Africa. Int J Syst Evol Microbiol 68(5). https://doi.org/10.1099/ijsem.0.002707

  92. Griffith DE, Aksamit T, Brown-Elliott BA et al (2007) An official ATS/IDSA statement: diagnosis, treatment, and prevention of nontuberculous mycobacterial diseases. Am J Respir Crit Care Med 175:367–416

    Article  CAS  PubMed  Google Scholar 

  93. Prevots DR, Marras TK (2015) Epidemiology of human pulmonary infection with non- tuberculous mycobacteria: a review. Clin Chest Med 36:13–34

    Article  PubMed  Google Scholar 

  94. van Ingen J (2015) Microbiological diagnosis of nontuberculous mycobacterial pulmonary disease. Clin Chest Med 36:43–54

    Article  PubMed  Google Scholar 

  95. Somoskovi A, Salfinger M (2014) Nontuberculous mycobacteria in respiratory infections: advances in diagnosis and identification. Clin Lab Med 34:271–295

    Article  PubMed  Google Scholar 

  96. Tortoli E (2014) Microbiological features and clinical relevance of new species of the genus Mycobacterium. Clin Microbiol Rev 27:727–752

    Article  PubMed  PubMed Central  Google Scholar 

  97. Koh W-J (2017) Nontuberculous mycobacteria—overview. Microbiol Spectr 5(1). https://doi.org/10.1128/microbiolspec.tnmi7-0024-2016

  98. Olaru ID, Patel H, Kranzer K, Perera N (2018) Turnaround time of whole genome sequencing for mycobacterial identification and drug susceptibility testing in routine practice. Clin Microbiol Infect 24:659.e5–659.e7

    Article  CAS  Google Scholar 

  99. Shea J, Halse TA, Lapierre P, Shudt M, Kohlerschmidt D, Van Roey P, Limberger R, Taylor J, Escuyer V, Musser KA (2017) Comprehensive whole-genome sequencing and reporting of drug resistance profiles on clinical cases of Mycobacterium tuberculosis in New York. J Clin Microbiol 55:1871–1882

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Votintseva AA, Bradley P, Pankhurst L et al (2017) Same-day diagnostic and surveillance data for tuberculosis via whole-genome sequencing of direct respiratory samples. J Clin Microbiol 55:1285–1298

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Cabibbe AM, Trovato A, De Filippo MR et al (2018) Early View Countrywide implementation of whole genome sequencing : an opportunity to improve tuberculosis management, surveillance and contact tracing in low incidence countries. Eur Respir J. https://doi.org/10.1183/13993003.00387-2018

  102. Stefani MMA, Avanzi C, Bührer-Sékula S et al (2017) Whole genome sequencing distinguishes between relapse and reinfection in recurrent leprosy cases. PLoS Negl Trop Dis 11:1–13

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Sophia Vourli or Spyridon Pournaras .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Vourli, S., Kontos, F., Pournaras, S. (2021). WGS for Bacterial Identification and Susceptibility Testing in the Clinical Lab. In: Moran-Gilad, J., Yagel, Y. (eds) Application and Integration of Omics-powered Diagnostics in Clinical and Public Health Microbiology . Springer, Cham. https://doi.org/10.1007/978-3-030-62155-1_3

Download citation

Publish with us

Policies and ethics