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Metagenomic Next-Generation Sequencing for Pathogen Detection and Identification

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Advanced Techniques in Diagnostic Microbiology

Abstract

The development of mNGS assays for pathogen detection has allowed for the diagnosis of infections from rare and unexpected pathogens in several clinical cases. The broad nature of these assays allows for unbiased detection with potential for simultaneous genomic characterization, allowing for detailed epidemiologic investigations and identification of pathogenic or resistance determinants. Assay performance and validation remain challenging, with the need for specialized bioinformatics tools along with translating new and unfamiliar sequencing-based protocols to the clinical laboratory. Despite the challenges involved, mNGS for pathogen detection promises to deliver insights into patient diagnoses and disease manifestations for many clinical syndromes and is poised to enhance the ability of physicians to provide infectious disease diagnosis in the near future.

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References

  1. Wylie TN, Wylie KM, Herter BN, Storch GA. Enhanced virome sequencing using targeted sequence capture. Genome Res. 2015;25:1910–20.

    Article  CAS  Google Scholar 

  2. Briese T, Kapoor A, Mishra N, et al. Virome capture sequencing enables sensitive viral diagnostics and comprehensive virome analysis. MBio. 2015;6:e01491–15.

    Article  CAS  Google Scholar 

  3. Depledge DP, Palser AL, Watson SJ, et al. Specific capture and whole-genome sequencing of viruses from clinical samples. PLoS One. 2011;6:e27805.

    Article  CAS  Google Scholar 

  4. Salipante SJ, Sengupta DJ, Rosenthal C, et al. Rapid 16S rRNA next-generation sequencing of polymicrobial clinical samples for diagnosis of complex bacterial infections. PLoS One. 2013;8:e65226.

    Article  CAS  Google Scholar 

  5. Mao DP, Zhou Q, Chen CY, Quan ZX. Coverage evaluation of universal bacterial primers using the metagenomic datasets. BMC Microbiol. 2012;12:66.

    Article  CAS  Google Scholar 

  6. Thézé J, Li T, du Plessis L, et al. Genomic epidemiology reconstructs the introduction and spread of Zika virus in Central America and Mexico. Cell Host and Microbe. 2018; 23(6):855–864.

    Article  Google Scholar 

  7. Wilson MR, Naccache SN, Samayoa E, et al. Actionable diagnosis of neuroleptospirosis by next-generation sequencing. N Engl J Med. 2014;370:2408–17.

    Article  Google Scholar 

  8. Hall RJ, Wang J, Todd AK, et al. Evaluation of rapid and simple techniques for the enrichment of viruses prior to metagenomic virus discovery. J Virol Methods. 2014;195:194–204.

    Article  CAS  Google Scholar 

  9. Li L, Deng X, Mee ET, et al. Comparing viral metagenomics methods using a highly multiplexed human viral pathogens reagent. J Virol Methods. 2015;213:139–46.

    Article  CAS  Google Scholar 

  10. He S, Wurtzel O, Singh K, et al. Validation of two ribosomal RNA removal methods for microbial metatranscriptomics. Nat Methods. 2010;7:807–12.

    Article  CAS  Google Scholar 

  11. Feehery GR, Yigit E, Oyola SO, et al. A method for selectively enriching microbial DNA from contaminating vertebrate host DNA. PLoS One. 2013;8:e76096.

    Article  CAS  Google Scholar 

  12. Oyola SO, Gu Y, Manske M, et al. Efficient depletion of host DNA contamination in malaria clinical sequencing. J Clin Microbiol. 2013;51:745–51.

    Article  CAS  Google Scholar 

  13. Horz HP, Scheer S, Vianna ME, Conrads G. New methods for selective isolation of bacterial DNA from human clinical specimens. Anaerobe. 2010;16:47–53.

    Article  CAS  Google Scholar 

  14. Hasan MR, Rawat A, Tang P, et al. Depletion of human DNA in spiked clinical specimens for improvement of sensitivity of pathogen detection by next-generation sequencing. J Clin Microbiol. 2016;54:919–27.

    Article  CAS  Google Scholar 

  15. Gu W, Crawford ED, O’Donovan BD, et al. Depletion of abundant sequences by hybridization (DASH): using Cas9 to remove unwanted high-abundance species in sequencing libraries and molecular counting applications. Genome Biol. 2016;17:41.

    Article  CAS  Google Scholar 

  16. Strong MJ, Xu G, Morici L, et al. Microbial contamination in next generation sequencing: implications for sequence-based analysis of clinical samples. PLoS Pathog. 2014;10:e1004437.

    Article  Google Scholar 

  17. Naccache SN, Greninger AL, Lee D, et al. The perils of pathogen discovery: origin of a novel parvovirus-like hybrid genome traced to nucleic acid extraction spin columns. J Virol. 2013;87:11966–77.

    Article  CAS  Google Scholar 

  18. Simmonds P, Prescott LE, Loque C, et al. TT virus—part of the normal human flora? J Infect Dis. 1999;180:1748–50.

    Article  CAS  Google Scholar 

  19. Santini M, Kutlesa M, Zarkovic K, et al. Influenza A 2009 H1N1 encephalitis in adults with viral RNA in cerebrospinal fluid. Scand J Infect Dis. 2012;44:992–6.

    Article  Google Scholar 

  20. Plentz A, Jilg W, Kochanowski B, et al. Detection of herpesvirus DNA in cerebrospinal fluid and correlation with clinical symptoms. Infection. 2008;36:158–62.

    Article  CAS  Google Scholar 

  21. Santee CA, Nagalingam NA, Farugi AA, et al. Nasopharyngeal microbiota composition of children is related to the frequency of upper respiratory infection and acute sinusitis. Microbiome. 2016;4:34.

    Article  Google Scholar 

  22. Talaulikar K, Gray JX, Shadbolt B, et al. A comparative study of the quality of DNA obtained from fresh frozen and formalin-fixed decalcified paraffin-embedded bone marrow trephine biopsy specimens using two different methods. J Clin Pathol. 2008;61:119–23.

    Article  CAS  Google Scholar 

  23. Turashvili G, Yang W, McKinney S, et al. Nucleic acid quantity and quality from paraffin blocks: defining optimal fixation, processing and DNA/RNA extraction techniques. Exp Mol Pathol. 2012;92:33–43.

    Article  CAS  Google Scholar 

  24. Head SR, Komori HK, LaMere SA, et al. Library construction for next-generation sequencing: overviews and challenges. Biotechniques 2014;56:61–64, 66, 68–77.

    Google Scholar 

  25. Nelson MC, Morrison HG, Benjamino J, et al. Analysis, optimization and verification of Illumina-generated 16S rRNA gene amplicon surveys. PLoS One. 2014;9:e94249.

    Article  Google Scholar 

  26. Buschmann T, Bystrykh LV. Levenshtein error-correcting barcodes for multiplexed DNA sequencing. BMC Bioinformatics. 2013;14:272.

    Article  Google Scholar 

  27. Bystrykh LV. Generalized DNA barcode design based on Hamming codes. PLoS One. 2012;7:e36852.

    Article  CAS  Google Scholar 

  28. Lefterova MI, Suarez CJ, Banaei N, Pinsky BA. Next-generation sequencing for infectious disease diagnosis and management: a report of the Association for Molecular Pathology. J Mol Diagn. 2015;17:623–34.

    Article  CAS  Google Scholar 

  29. Liu L, Li Y, Li S, et al. Comparison of next-generation sequencing systems. J Biomed Biotechnol. 2012;2012:251364.

    PubMed  PubMed Central  Google Scholar 

  30. Rhoads A, Au KF. PacBio sequencing and its applications. Genomics Proteomics Bioinformatics. 2015;13:278–89.

    Article  Google Scholar 

  31. Lu H, Giordano F, Ning Z. Oxford Nanopore MinION sequencing and genome assembly. Genomics Proteomics Bioinformatics. 2016;14:265–79.

    Article  Google Scholar 

  32. Naccache SN, Federman S, Veeraraghavan N, et al. A cloud-compatible bioinformatics pipeline for ultrarapid pathogen identification from next-generation sequencing of clinical samples. Genome Res. 2014;24:1190–2.

    Article  Google Scholar 

  33. Kilianski A, Carcel P, Yao S, et al. Pathosphere.org: pathogen detection and characterization through a web-based, open source informatics platform. BMC Bioinformatics. 2015;16:416.

    Article  Google Scholar 

  34. Flygare S, Simmon K, Miller C, et al. Taxonomer: an interactive metagenomics analysis portal for universal pathogen detection and host mRNA expression profiling. Genome Biol. 2016;17:111.

    Article  Google Scholar 

  35. Correia D, Doppelt-Azeroual O, Denis JB, et al. MetaGen Sense: a web-application for analysis and exploration of high throughput sequencing metagenomics data. F1000Res. 2015;4:86.

    Article  Google Scholar 

  36. Ondov BD, Bergman NH, Philippy AM. Interactive metagenomics visualization in a web browser. BMC Bioinformatics. 2011;12:385.

    Article  Google Scholar 

  37. Jia B, Raphenya AR, Alcock B, et al. CARD 2017: expansion and model-centric curation of the comprehensive antibiotic resistance database. Nucleic Acids Res. 2017;45:D566–73.

    Article  CAS  Google Scholar 

  38. Beerenwinkel N, Daumer M, Oette M, et al. Geno2pheno: estimating phenotypic drug resistance from HIV-1 genotypes. Nucleic Acids Res. 2003;31:3850–5.

    Article  CAS  Google Scholar 

  39. Kalaghatgi P, Sikorski AM, Knops E, et al. Geno2pheno[HCV] – a web-based interpretation system to support hepatitis C treatment decisions in the era of direct-acting antiviral agents. PLoS One. 2016;11:e0155869.

    Article  Google Scholar 

  40. Schwartz S, Friedberg I, Ivanov IV, et al. A metagenomics study of diet-dependent interaction between gut microbiota and host in infants reveals differences in immune response. Genome Biol. 2012;13:r32.

    Article  CAS  Google Scholar 

  41. Bouquet J, Soloski MJ, Swei A, et al. Longitudinal transcriptome analysis reveals a sustained differential gene expression signature in patients treated for acute Lyme disease. MBio. 2016;7:e00100–16.

    Article  CAS  Google Scholar 

  42. Bouquet J, Gardy JL, Brown S, et al. RNA-seq analysis of gene expression, viral pathogen, and B-cell/T-cell receptor signatures in complex chronic disease. Clin Infect Dis. 2017;64:476–81.

    Article  Google Scholar 

  43. Schlaberg R, Chiu CY, Miller S, Procop GW, Weinstock G. Validation of metagenomics next-generation sequencing tests for universal pathogen detection. Arch Pathol Lab Med. 2017;141:776–86.

    Article  Google Scholar 

  44. Yao K, Honarmand S, Espinosa A, et al. Detection of human herpesvirus-6 in cerebrospinal fluid of patients with encephalitis. Ann Neurol. 2009;65:257–67.

    Article  CAS  Google Scholar 

  45. Gargis AS, Kalman L, Lubin IM. Assuring the quality of next-generation sequencing in clinical microbiology and public health laboratories. J Clin Microbiol. 2016;54:2857–65.

    Article  Google Scholar 

  46. Jennings LJ, Arcila ME, Corless C, et al. Guidelines for validation of next-generation sequencing-based oncology panels: a joint consensus recommendation of the Association for Molecular Pathology and College of American pathologists. J Mol Diagn. 2017;19:341–65.

    Article  Google Scholar 

  47. Mongkolrattanothai K, Naccache SNm Bender JM, et al. Neurobrucellosis: Unexpected answer from metagenomics next-generation sequencing. J Pediatric Infect Dis Soc. 2017;6:393–8.

    PubMed  Google Scholar 

  48. Murkey JA, Chew KW, Carlson M, et al. Hepatitis E virus-associated meningoencephalitis in a lung transplant recipient diagnosed by clinical metagenomic sequencing. Open Forum Infect Dis. 2017;4:ofx121.

    Article  Google Scholar 

  49. Wilson MR, Shanbhag NM, Reid MJ, et al. Diagnosing Balamuthia mandrillaris encephalitis with metagenomic deep sequencing. Ann Neurol. 2015;78:722–30.

    Article  CAS  Google Scholar 

  50. Chiu CY, Coffey LL, Murkey J, et al. Fatal human case of mosquito-borne St. Louis encephalitis virus infection diagnosed by metagenomic sequencing, California, 2016. Emerging Infect Dis. 2017;23:1694–8.

    Article  CAS  Google Scholar 

  51. Fukui Y, Aoki K, Okuma S, et al. Metagenomic analysis for detecting pathogens in culture-negative infective endocarditis. J Infect Chemother. 2015;21:882–4.

    Article  CAS  Google Scholar 

  52. Grard G, Fair JN, Slikas E, et al. A novel rhabdovirus associated with acute hemorrhagic fever in central Africa. PLoS Pathog. 2012;8:e1002924.

    Article  Google Scholar 

  53. Naccache SN, Peggs KS, Mattes FM, et al. Diagnosis of neuroinvasive astrovirus infection in an immunocompromised adult with encephalitis by unbiased next-generation sequencing. Clin Infect Dis. 2015;60:919–23.

    Article  Google Scholar 

  54. Doan T, Acharya NR, Pinsky BA, et al. Metagenomic DNA sequencing for the diagnosis of intraocular infections. Opthalmology. 2017;S0161–6420:30858–8.

    Google Scholar 

  55. Graf EH, Simmon KE, Tardif KD, et al. Unbiased detection of respiratory viruses by use of RNA sequencing-based metagenomics: a systematic comparison to a commercial PCR panel. J Clin Microbiol. 2016;54:1000–7.

    Article  CAS  Google Scholar 

  56. Sardi SI, Somasekar S, Naccache SN, et al. Coinfections of Zika and Chikungunya viruses in Bahia, Brazil, identified by metagenomic next-generation sequencing. J Clin Microbiol. 2016;54:2348–53.

    Article  CAS  Google Scholar 

  57. Wylie KM, Mihindukulasuriya KA, Sodergren, et al. Sequence analysis of the human virome in febrile and afebrile children. PloS ONE. 2012;7(6):e27735.

    Article  CAS  Google Scholar 

  58. Zhou Y, Wylie KM, El Feghaly RE, et al. Metagenomic approach for identification of the pathogens associated with diarrhea in stool specimens. J Clin Microbiol. 2016;54:368–75.

    Article  CAS  Google Scholar 

  59. Somasekar S, Lee D, Rule J, et al. Viral surveillance in serum samples from patients with acute liver failure by metagenomic next-generation sequencing. Clin Infect Dis. 2017;54:2348–53.

    Google Scholar 

  60. Greninger AL, Chen EC, Sittler T, et al. A metagenomic analysis of pandemic influenza A (2009 H1N1) infection in patients from North America. PLoS One. 2010;5:e13381.

    Article  Google Scholar 

  61. Ma Y, Madupu R, Karaoz U, et al. Human papillomavirus community in healthy persons, defined by metagenomics analysis of human microbiome project shotgun sequencing data sets. J Virol. 2014;88:4786–97.

    Article  Google Scholar 

  62. Lewandowska DW, Schreiber PW, Schuurmamns MM, et al. Metagenomic sequencing complements routine diagnostics in identifying viral pathogens in lung transplant recipients with unknown etiology of respiratory infection. PLoS One. 2017;12:e0177340.

    Article  Google Scholar 

  63. Greninger AL, Naccache SN, Messacar K, et al. A novel outbreak enterovirus D68 strain associated with acute flaccid myelitis cases in the USA (2012-14): a retrospective cohort study. Lancet Infect Dis. 2015;15:671–82.

    Article  Google Scholar 

  64. Greninger AL, Naccache SN, Federman S, et al. Rapid metagenomic identification of viral pathogens in clinical samples by real-time nanopore sequencing analysis. Genome Med. 2015;7:99.

    Article  Google Scholar 

  65. Gire SK, Goba A, Andersen KG, et al. Genomic surveillance elucidates Ebola virus origin and transmission during the 2014 outbreak. Science. 2014;345:1369–72.

    Article  CAS  Google Scholar 

  66. Metsky HC, Matranga CB, Wohl S, et al. Zika virus evolution and spread in the Americas. Nature. 2017;546:411–5.

    Article  CAS  Google Scholar 

  67. Naccache SN, Theze J, Sardi SI, et al. Distinct Zika virus lineage in Salvador, Bahia, Brazil. Emerg Infect Dis. 2016;22:1788–92.

    Article  Google Scholar 

  68. Feigelman R, Kahlert CR, Baty F, et al. Sputum DNA sequencing in cystic fibrosis: non-invasive access to the lung microbiome and to pathogen details. Microbiome. 2017;5:20.

    Article  Google Scholar 

  69. Ward DV, Scholz M, Zolfo M, et al. Metagenomic sequencing with strain-level resolution implicates uropathogenic E. coli in necrotizing enterocolitis and mortality in preterm infants. Cell Rep. 2016;14:2912–24.

    Article  CAS  Google Scholar 

  70. Schmidt K, Mwaigwisya S, Crossman LC, et al. Identification of bacterial pathogens and antimicrobial resistance directly from clinical urines by nanopore-based metagenomic sequencing. J Antimicrob Chemother. 2017;72:104–14.

    Article  CAS  Google Scholar 

  71. Deurenberg RH, Bathoorn E, Chlebowicz MA, et al. Application of next generation sequencing in clinical microbiology and infection prevention. J Biotechnol. 2017;243:16–24.

    Article  CAS  Google Scholar 

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Authors and Affiliations

  1. Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA, USA

    Steve Miller & Charles Chiu

  2. Department of Medicine, University of California San Francisco, San Francisco, CA, USA

    Charles Chiu

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  1. Steve Miller
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Correspondence to Steve Miller .

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Editors and Affiliations

  1. Departments of Laboratory Medicine and Internal Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Yi-Wei Tang

  2. Department of Pathology, Microbiology and Immunology and Medicine, Vanderbilt University Medical Center, Nashville, TN, USA

    Charles W. Stratton

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Miller, S., Chiu, C. (2018). Metagenomic Next-Generation Sequencing for Pathogen Detection and Identification. In: Tang, YW., Stratton, C. (eds) Advanced Techniques in Diagnostic Microbiology. Springer, Cham. https://doi.org/10.1007/978-3-319-95111-9_25

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