Third generation sequencing technologies applied to diagnostic microbiology: benefits and challenges in applications and data analysis

Expert Review of Molecular Diagnostics

Volumn 16, Issue 9, 2016, Pages 1011-1023

  Lavezzo, Enrico ^a   Barzon, Luisa ^a   Toppo, Stefano ^a   Palù, Giorgio ^a  

^a UNIVERSITY OF PADOVA   (Italy)

Author keywords

diagnostics of infectious diseases; host pathogen interaction; Metagenomics; metatranscriptomics; next generation sequencing technologies; nucleotide modification detection; outbreak monitoring; pathogen discovery; single molecule sequencing; third generation sequencing technologies

Indexed keywords

DISEASE SURVEILLANCE; EPIDEMIC; EPIGENETICS; GENETIC ANALYSIS; GENOMICS; GENOTYPING TECHNIQUE; HUMAN; INFECTION; METAGENOMICS; METATRANSCRIPTOMICS; MICROBIOLOGY; NEXT GENERATION SEQUENCING; NONHUMAN; PATHOGENESIS; REVIEW; SEQUENCE ANALYSIS; THIRD GENERATION SEQUENCING; WHOLE GENOME SEQUENCING; GENETICS; HIGH THROUGHPUT SEQUENCING; MICROBIOLOGICAL EXAMINATION; PROCEDURES;

GENOTYPING TECHNIQUES; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; INFECTION; MICROBIOLOGICAL TECHNIQUES;

EID: 84984972166     PISSN: 14737159     EISSN: 17448352     Source Type: Journal    
DOI: 10.1080/14737159.2016.1217158     Document Type: Review

References (173)

1. M.Margulies, M.Egholm, W.E.Altman, et al. Genome sequencing in microfabricated high-density picolitre reactors. Nature. 2005;437(7057):376–380.
2. D.R.Bentley, S.Balasubramanian, H.P.Swerdlow, et al. Accurate whole human genome sequencing using reversible terminator chemistry. Nature. 2008;456(7218):53–59.
3. A.Valouev, J.Ichikawa, T.Tonthat, et al. A high-resolution, nucleosome position map of C. elegans reveals a lack of universal sequence-dictated positioning. Genome Res. 2008;18(7):1051–1063.
4. J.M.Rothberg, W.Hinz, T.M.Rearick, et al. An integrated semiconductor device enabling non-optical genome sequencing. Nature. 2011;475(7356):348–352.
5. M.L.Metzker Sequencing technologies - the next generation. Nat Rev Genet. 2010;11(1):31–46.• This paper, together with reference n. 7, comprehensively describe the basic principles and technical details of next generation sequencing technologies.
6. B.P.Hodkinson, E.A.Grice. Next-generation sequencing:a review of technologies and tools for wound microbiome research. Adv Wound Care (New Rochelle). 2015;4(1):50–58.
7. E.R.Mardis. Next-generation sequencing platforms. Annu Rev Anal Chem (Palo Alto Calif). 2013;6:287–303.• This paper, together with reference n. 5, comprehensively describe the basic principles and technical details of next generation sequencing technologies.
8. A.Wirawan, R.S.Harris, Y.Liu, et al. HECTOR:a parallel multistage homopolymer spectrum based error corrector for 454 sequencing data. BMC Bioinformatics. 2014;15:131.
9. M.H.Schulz, D.Weese, M.Holtgrewe, et al. Fiona:a parallel and automatic strategy for read error correction. Bioinformatics. 2014;30(17):i356–i363.
10. A.Allam, P.Kalnis, V.Solovyev. Karect:accurate correction of substitution, insertion and deletion errors for next-generation sequencing data. Bioinformatics. 2015;31(21):3421–3428.
11. J.R.Miller, A.L.Delcher, S.Koren, et al. Aggressive assembly of pyrosequencing reads with mates. Bioinformatics. 2008;24(24):2818–2824.
12. D.R.Zerbino, E.Birney. Velvet:algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 2008;18(5):821–829.
13. R.B.Luo, B.H.Liu, Y.L.Xie, et al. Erratum:SOAPdenovo2:an empirically improved memory-efficient short-read de novo assembler. Gigascience. 2015;4:30.
14. H.Li, R.Durbin. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25(14):1754–1760.
15. B.Langmead, C.Trapnell, M.Pop, et al. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 2009;10(3):R25.
16. A.McKenna, M.Hanna, E.Banks, et al. The genome analysis toolkit:a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 2010;20(9):1297–1303.
17. D.C.Koboldt, Q.Zhang, D.E.Larson, et al. VarScan 2:somatic mutation and copy number alteration discovery in cancer by exome sequencing. Genome Res. 2012;22(3):568–576.
18. T.J.Carver, K.M.Rutherford, M.Berriman, et al. ACT:the Artemis comparison tool. Bioinformatics. 2005;21(16):3422–3423.
19. I.Milne, M.Bayer, L.Cardle, et al. Tablet–next generation sequence assembly visualization. Bioinformatics. 2010;26(3):401–402.
20. J.Eid, A.Fehr, J.Gray, et al. Real-time DNA sequencing from single polymerase molecules. Science. 2009;323(5910):133–138.
21. M.J.Levene, J.Korlach, S.W.Turner, et al. Zero-mode waveguides for single-molecule analysis at high concentrations. Science. 2003;299(5607):682–686.
22. T.Hackl, R.Hedrich, J.Schultz, et al. Proovread:large-scale high-accuracy PacBio correction through iterative short read consensus. Bioinformatics. 2014;30(21):3004–3011.
23. K.J.Travers, C.-S.Chin, D.R.Rank, et al. A flexible and efficient template format for circular consensus sequencing and SNP detection. Nucleic Acids Res. 2010;38(15):e159.
24. S.Koren, G.P.Harhay, T.P.Smith, et al. Reducing assembly complexity of microbial genomes with single-molecule sequencing. Genome Biol. 2013;14(9):R101.• This paper demonstrates how third generation sequencing platforms can be applied to obtain full-length, finished-grade bacterial genomes.
25. H.Bayley, P.S.Cremer. Stochastic sensors inspired by biology. Nature. 2001;413(6852):226–230.
26. Y.Feng, Y.Zhang, C.Ying, et al. Nanopore-based fourth-generation DNA sequencing technology. Genomics Proteomics Bioinformatics. 2015;13(1):4–16.
27. D.Branton, D.W.Deamer, A.Marziali, et al. The potential and challenges of nanopore sequencing. Nat Biotechnol. 2008;26(10):1146–1153.
28. J.Clarke, H.-C.Wu, L.Jayasinghe, et al. Continuous base identification for single-molecule nanopore DNA sequencing. Nat Nanotechnol. 2009;4(4):265–270.
29. T.Laver, J.Harrison, P.A.O’Neill, et al. Assessing the performance of the Oxford Nanopore Technologies MinION. Biomol Detect Quantif. 2015;3:1–8.
30. C.L.Ip, M.Loose, J.R.Tyson, et al. MinION analysis and reference consortium:phase 1 data release and analysis. F1000Res. 2015;4:1075.
31. T.Hoenen, A.Groseth, K.Rosenke, et al. Nanopore sequencing as a rapidly deployable Ebola outbreak tool. Emerg Infect Dis. 2016;22(2):331–334.
32. N.J.Loman, J.Quick, J.T.Simpson. A complete bacterial genome assembled de novo using only nanopore sequencing data. Nat Methods. 2015;12(8):733–735.
33. E.A.Manrao, I.M.Derrington, M.Pavlenok, et al. Nucleotide discrimination with DNA immobilized in the MspA nanopore. PLoS One. 2011;6(10):e25723.
34. T.Z.Butler, M.Pavlenok, I.M.Derrington, et al. Single-molecule DNA detection with an engineered MspA protein nanopore. Proc Natl Acad Sci U S A. 2008;105(52):20647–20652.
35. I.M.Derrington, T.Z.Butler, M.D.Collins, et al. Nanopore DNA sequencing with MspA. Proc Natl Acad Sci U S A. 2010;107(37):16060–16065.
36. E.A.Manrao, I.M.Derrington, A.H.Laszlo, et al. Reading DNA at single-nucleotide resolution with a mutant MspA nanopore and phi29 DNA polymerase. Nature Biotechnology. 2012;30(4):349–353.
37. D.Wendell, P.Jing, J.Geng, et al. Translocation of double-stranded DNA through membrane-adapted phi29 motor protein nanopores. Nature Nanotechnology. 2009;4(11):765–772.
38. F.Haque, S.Y.Wang, C.Stites, et al. Single pore translocation of folded, double-stranded, and tetra-stranded DNA through channel of bacteriophage phi29 DNA packaging motor. Biomaterials. 2015;53:744–752.
39. B.M.Venkatesan, R.Bashir. Nanopore sensors for nucleic acid analysis. Nat Nanotechnol. 2011;6(10):615–624.
40. J.B.Heng, C.Ho, T.Kim, et al. Sizing DNA using a nanometer-diameter pore. Biophys J. 2004;87(4):2905–2911.
41. S.Garaj, W.Hubbard, A.Reina, et al. Graphene as a subnanometre trans-electrode membrane. Nature. 2010;467(7312):190–193.
42. S.Liu, B.Lu, Q.Zhao, et al. Boron nitride nanopores:highly sensitive DNA single-molecule detectors. Adv Mater. 2013;25(33):4549–4554.
43. J.Menestrina, C.Yang, M.Schiel, et al. Charged particles modulate local ionic concentrations and cause formation of positive peaks in resistive-pulse-based detection. J Phys Chem C. 2014;118(5):2391–2398.
44. S.Kumar, C.Tao, M.Chien, et al. PEG-labeled nucleotides and nanopore detection for single molecule DNA sequencing by synthesis. Sci Rep. 2012;2:684.
45. C.W.Fuller, S.Kumar, M.Porel, et al. Real-time single-molecule electronic DNA sequencing by synthesis using polymer-tagged nucleotides on a nanopore array. Proc Natl Acad Sci U S A. 2016;113:5233–5238.
46. B.Goldberg, H.Sichtig, C.Geyer, et al. Making the leap from research laboratory to clinic:challenges and opportunities for next-generation sequencing in infectious disease diagnostics. MBio. 2015;6(6):e01888-15.
47. Y.Zhou, C.-A.D.Burnham, T.Hink, et al. Phenotypic and genotypic analysis of Clostridium difficile isolates:a single-center study. J Clin Microbiol. 2014;52(12):4260–4266.
48. A.Roetzer, R.Diel, T.A.Kohl, et al. Whole genome sequencing versus traditional genotyping for investigation of a Mycobacterium tuberculosis outbreak:a longitudinal molecular epidemiological study. PLoS Med. 2013;10(2):e1001387.
49. P.K.G.Ching, V.C.De Los Reyes, M.N.Sucaldito, et al. Outbreak of henipavirus infection, Philippines, 2014. Emerg Infect Dis. 2015;21(2):328–331.
50. J.R.Miller, S.Koren, G.Sutton. Assembly algorithms for next-generation sequencing data. Genomics. 2010;95(6):315–327.
51. S.Koren, A.M.Phillippy. One chromosome, one contig:complete microbial genomes from long-read sequencing and assembly. Curr Opin Microbiol. 2015;23:110–120.
52. E.Lavezzo, S.Toppo, E.Franchin, et al. Genomic comparative analysis and gene function prediction in infectious diseases:application to the investigation of a meningitis outbreak. BMC Infect Dis. 2013;13:554.
53. F.Finotello, E.Lavezzo, P.Fontana, et al. Comparative analysis of algorithms for whole-genome assembly of pyrosequencing data. Brief Bioinform. 2012;13(3):269–280.
54. Y.-C.Liao, S.-H.Lin, -H.-H.Lin. Completing bacterial genome assemblies:strategy and performance comparisons. Sci Rep. 2015;5:8747.
55. M.Choi, U.I.Scholl, W.Ji, et al. Genetic diagnosis by whole exome capture and massively parallel DNA sequencing. Proc Natl Acad Sci U S A. 2009;106(45):19096–19101.
56. S.Bashiardes, R.Veile, C.Helms, et al. Direct genomic selection. Nat Methods. 2005;2(1):63–69.
57. M.R.Wilson, S.N.Naccache, E.Samayoa, et al. Actionable diagnosis of neuroleptospirosis by next-generation sequencing. N Engl J Med. 2014;370(25):2408–2417.• This paper highlights the potential of applying NGS approaches in diagnostics of unsuspected pathogens.
58. H.Feng, M.Shuda, Y.Chang, et al. Clonal integration of a polyomavirus in human Merkel cell carcinoma. Science. 2008;319(5866):1096–1100.•• One of the most successful applications of next generation sequencing, the discovery of new, unknown pathogens as the etiological agents of diseases.
59. J.R.Brown, S.Morfopoulou, J.Hubb, et al. Astrovirus VA1/HMO-C:an increasingly recognized neurotropic pathogen in immunocompromised patients. Clin Infect Dis. 2015;60(6):881–888.
60. A.J.Westermann, S.A.Gorski, J.Vogel. Dual RNA-seq of pathogen and host. Nat Rev Microbiol. 2012;10(9):618–630.
61. A.J.Westermann, K.U.Förstner, F.Amman, et al. Dual RNA-seq unveils noncoding RNA functions in host-pathogen interactions. Nature. 2016;529(7587):496–501.•• This paper shows how next generation sequencing can be applied to investigate the complex network of interactions between host and pathogens.
62. Y.-J.Choi, M.T.Aliota, G.F.Mayhew, et al. Dual RNA-seq of parasite and host reveals gene expression dynamics during filarial worm-mosquito interactions. PLoS Negl Trop Dis. 2014;8(5):e2905.
63. B.Haider, T.-H.Ahn, B.Bushnell, et al. Omega:an overlap-graph de novo assembler for metagenomics. Bioinformatics. 2014;30(19):2717–2722.
64. D.Li, C.-M.Liu, R.Luo, et al. MEGAHIT:an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics. 2015;31(10):1674–1676.
65. H.C.M.Leung, S.-M.Yiu, F.Y.L.Chin. IDBA-MTP:a hybrid metatranscriptomic assembler based on protein information. J Comput Biol. 2015;22(5):367–376.
66. Afiahayati, K.Sato, Y.Sakakibara. MetaVelvet-SL:an extension of the Velvet assembler to a de novo metagenomic assembler utilizing supervised learning. DNA Res. 2015;22(1):69–77.
67. J.Laserson, V.Jojic, D.Koller. Genovo:de novo assembly for metagenomes. J Comput Biol. 2011;18(3):429–443.
68. S.Picelli, O.R.Faridani, A.K.Björklund, et al. Full-length RNA-seq from single cells using Smart-seq2. Nat Protoc. 2014;9(1):171–181.
69. S.Picelli, Å.K.Björklund, O.R.Faridani, et al. Smart-seq2 for sensitive full-length transcriptome profiling in single cells. Nat Methods. 2013;10(11):1096–1098.
70. M.Wu, A.J.Scott. Phylogenomic analysis of bacterial and archaeal sequences with AMPHORA2. Bioinformatics. 2012;28(7):1033–1034.
71. B.Liu, T.Gibbons, M.Ghodsi, et al. Accurate and fast estimation of taxonomic profiles from metagenomic shotgun sequences. BMC Genomics. 2011;12(Suppl 2):S4.
72. N.Segata, L.Waldron, A.Ballarini, et al. Metagenomic microbial community profiling using unique clade-specific marker genes. Nat Methods. 2012;9(8):811–814.
73. M.Scholz, D.V.Ward, E.Pasolli, et al. Strain-level microbial epidemiology and population genomics from shotgun metagenomics. Nat Methods. 2016;13(5):435–438.
74. K.R.Patil, L.Roune, A.C.McHardy. The PhyloPythiaS web server for taxonomic assignment of metagenome sequences. PLoS One. 2012;7(6):e38581.
75. A.Brady, S.Salzberg. PhymmBL expanded:confidence scores, custom databases, parallelization and more. Nat Methods. 2011;8(5):367.
76. G.L.Rosen, E.R.Reichenberger, A.M.Rosenfeld. NBC:the Naive Bayes classification tool webserver for taxonomic classification of metagenomic reads. Bioinformatics. 2011;27(1):127–129.
77. H.Noguchi, J.Park, T.Takagi. MetaGene:prokaryotic gene finding from environmental genome shotgun sequences. Nucleic Acids Res. 2006;34(19):5623–5630.
78. H.Noguchi, T.Taniguchi, T.Itoh. MetaGeneAnnotator:detecting species-specific patterns of ribosomal binding site for precise gene prediction in anonymous prokaryotic and phage genomes. DNA Res. 2008;15(6):387–396.
79. K.J.Hoff, T.Lingner, P.Meinicke, et al. Orphelia:predicting genes in metagenomic sequencing reads. Nucleic Acids Res. 2009;37(Web Server):W101–W105.
80. M.Rho, H.Tang, Y.Ye. FragGeneScan:predicting genes in short and error-prone reads. Nucleic Acids Res. 2010;38(20):e191.
81. D.R.Kelley, B.Liu, A.L.Delcher, et al. Gene prediction with Glimmer for metagenomic sequences augmented by classification and clustering. Nucleic Acids Res. 2012;40(1):e9.
82. W.Zhu, A.Lomsadze, M.Borodovsky. Ab initio gene identification in metagenomic sequences. Nucleic Acids Res. 2010;38(12):e132.
83. V.M.Markowitz, I.M.Chen, K.Chu, et al. IMG/M:the integrated metagenome data management and comparative analysis system. Nucleic Acids Res. 2012;40(Database issue):D123–D129.
84. J.Goll, D.B.Rusch, D.M.Tanenbaum, et al. METAREP:JCVI metagenomics reports–an open source tool for high-performance comparative metagenomics. Bioinformatics. 2010;26(20):2631–2632.
85. R.Seshadri, S.A.Kravitz, L.Smarr, et al. CAMERA:a community resource for metagenomics. PLoS Biol. 2007;5(3):e75.
86. F.Meyer, D.Paarmann, M.D’Souza, et al. The metagenomics RAST server - a public resource for the automatic phylogenetic and functional analysis of metagenomes. BMC Bioinformatics. 2008;9:386.
87. R.Overbeek, T.Begley, R.M.Butler, et al. The subsystems approach to genome annotation and its use in the project to annotate 1000 genomes. Nucleic Acids Research. 2005;33(17):5691–5702.
88. M.Kanehisa, Y.Sato, M.Kawashima, et al. KEGG as a reference resource for gene and protein annotation. Nucleic Acids Research. 2016;44(D1):D457–D462.
89. R.Caspi, T.Altman, R.Billington, et al. The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Res. 2014;42(D1):D459–D471.
90. J.Huerta-Cepas, D.Szklarczyk, K.Forslund, et al. eggNOG 4.5:a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences. Nucleic Acids Res. 2016;44(D1):D286–D293.
91. A.Fabregat, K.Sidiropoulos, P.Garapati, et al. The reactome pathway knowledgebase. Nucleic Acids Res. 2016;44(D1):D481–D487.
92. R.D.Finn, P.Coggill, R.Y.Eberhardt, et al. The Pfam protein families database:towards a more sustainable future. Nucleic Acids Res. 2016;44(D1):D279–D285.
93. P.D.Thomas, M.J.Campbell, A.Kejariwal, et al. PANTHER:a library of protein families and subfamilies indexed by function. Genome Res. 2003;13(9):2129–2141.
94. E.Lavezzo, M.Falda, P.Fontana, et al. Enhancing protein function prediction with taxonomic constraints - the Argot2.5 web server. Methods. 2016;93:15–23.
95. M.Falda, S.Toppo, A.Pescarolo, et al. Argot2:a large scale function prediction tool relying on semantic similarity of weighted Gene Ontology terms. BMC Bioinformatics. 2012;13:S14.
96. P.Radivojac, W.T.Clark, T.R.Oron, et al. A large-scale evaluation of computational protein function prediction. Nat Methods. 2013;10(3):221–227.
97. C.R.Woese, O.Kandler, M.L.Wheelis. Towards a natural system of organisms:proposal for the domains Archaea, Bacteria, and Eucarya. Proc Natl Acad Sci U S A. 1990;87(12):4576–4579.
98. M.C.J.Maiden, J.A.Bygraves, E.Feil, et al. Multilocus sequence typing:a portable approach to the identification of clones within populations of pathogenic microorganisms. Proc Natl Acad Sci USA. 1998;95(6):3140–3145.
99. M.C.J.Maiden. Multilocus sequence typing of bacteria. Annu Rev Microbiol. 2006;60:561–588.
100. G.Vergnaud, C.Pourcel. Multiple locus variable number of tandem repeats analysis. Methods Mol Biol. 2009;551:141–158.
101. L.Fallico, D.Couvin, M.Peracchi, et al. Four year longitudinal study of Mycobacterium tuberculosis complex isolates in a region of North-Eastern Italy. Infect Genet Evol. 2014;26:58–64.
102. A.Vahidnia, W.Bekers, H.Bliekendaal, et al. High throughput multiplex-PCR for direct detection and diagnosis of dermatophyte species, Candida albicans and Candida parapsilosis in clinical specimen. J Microbiol Methods. 2015;113:38–40.
103. C.L.Taira, T.S.Okay, A.F.Delgado, et al. A multiplex nested PCR for the detection and identification of Candida species in blood samples of critically ill paediatric patients. BMC Infect Dis. 2014;14:406.
104. D.Duò, C.Ghimenti, P.Migliora, et al. Identification and characterization of human papillomavirus DNA sequences in Italian breast cancer patients by PCR and line probe assay reverse hybridization. Mol Med Rep. 2008;1(5):673–677.
105. M.I.Micalessi, G.A.Boulet, A.Vorsters, et al. A real-time PCR approach based on SPF10 primers and the INNO-LiPA HPV Genotyping Extra assay for the detection and typing of human papillomavirus. J Virol Methods. 2013;187(1):166–171.
106. T.D.Lieberman, K.B.Flett, I.Yelin, et al. Genetic variation of a bacterial pathogen within individuals with cystic fibrosis provides a record of selective pressures. Nat Genet. 2014;46(1):82–87.•• This paper demonstrates the feasibility of using next generation sequencing for the characterization of pathogen evolution within the patient in the course of infection.
107. E.S.Snitkin, A.M.Zelazny, P.J.Thomas, et al. Tracking a hospital outbreak of carbapenem-resistant Klebsiella pneumoniae with whole-genome sequencing. Sci Transl Med. 2012;4(148):148ra116.
108. J.L.Gardy, J.C.Johnston, S.J.Ho Sui, et al. Whole-genome sequencing and social-network analysis of a tuberculosis outbreak. N Engl J Med. 2011;364(8):730–739.
109. E.R.Robinson, T.M.Walker, M.J.Pallen. Genomics and outbreak investigation:from sequence to consequence. Genome Med. 2013;5(4):36.
110. N.A.Kuzmina, P.Lemey, I.V.Kuzmin, et al. The phylogeography and spatiotemporal spread of south-central skunk rabies virus. PLoS One. 2013;8(12):e82348.
111. P.Lemey, A.Rambaut, T.Bedford, et al. Unifying viral genetics and human transportation data to predict the global transmission dynamics of human influenza H3N2. PLoS Pathog. 2014;10(2):e1003932.• This paper shows how NGS data, combined with information on global human movement patterns, can be exploited to predict the spread of viruses.
112. O.G.Pybus, M.A.Suchard, P.Lemey, et al. Unifying the spatial epidemiology and molecular evolution of emerging epidemics. Proc Natl Acad Sci U S A. 2012;109(37):15066–15071.
113. D.G.Streicker, P.Lemey, A.Velasco-Villa, et al. Rates of viral evolution are linked to host geography in bat rabies. PLoS Pathog. 2012;8(5):e1002720.
114. C.Talbi, P.Lemey, M.A.Suchard, et al. Phylodynamics and human-mediated dispersal of a zoonotic virus. PLoS Pathog. 2010;6(10):e1001166.
115. N.R.Faria, A.Rambaut, M.A.Suchard, et al. HIV epidemiology. The early spread and epidemic ignition of HIV-1 in human populations. Science. 2014;346(6205):56–61.
116. N.J.Croucher, S.R.Harris, C.Fraser, et al. Rapid pneumococcal evolution in response to clinical interventions. Science. 2011;331(6016):430–434.
117. N.J.Croucher, J.A.Finkelstein, S.I.Pelton, et al. Population genomics of post-vaccine changes in pneumococcal epidemiology. Nat Genet. 2013;45(6):656–663.
118. L.Barzon, E.Lavezzo, V.Militello, et al. Applications of next-generation sequencing technologies to diagnostic virology. Int J Mol Sci. 2011;12(11):7861–7884.
119. X.Didelot, R.Bowden, D.J.Wilson, et al. Transforming clinical microbiology with bacterial genome sequencing. Nat Rev Genet. 2012;13(9):601–612.
120. S.D.Brown, S.Nagaraju, S.Utturkar, et al. Comparison of single-molecule sequencing and hybrid approaches for finishing the genome of Clostridium autoethanogenum and analysis of CRISPR systems in industrial relevant Clostridia. Biotechnol Biofuels. 2014;7:40.
121. A.Bashir, A.A.Klammer, W.P.Robins, et al. A hybrid approach for the automated finishing of bacterial genomes. Nat Biotechnol. 2012;30(7):701–707.
122. M.Pal, M.K.Swarnkar, R.Thakur, et al. Complete genome sequence of Paenibacillus sp. strain IHBB 10380 using PacBio single-molecule real-time sequencing technology. Genome Announc. 2015;3(2):e00356-15.
123. A.J.Abrams, D.L.Trees, R.A.Nicholas. Complete genome sequences of three Neisseria gonorrhoeae laboratory reference strains, determined using PacBio single-molecule real-time technology. Genome Announc. 2015;3(5):e01052-15.
124. K.Berlin, S.Koren, C.-S.Chin, et al. Assembling large genomes with single-molecule sequencing and locality-sensitive hashing. Nat Biotechnol. 2015;33(6):623–630.
125. F.J.Ribeiro, D.Przybylski, S.Yin, et al. Finished bacterial genomes from shotgun sequence data. Genome Res. 2012;22(11):2270–2277.
126. M.Boetzer, W.Pirovano. SSPACE-LongRead:scaffolding bacterial draft genomes using long read sequence information. BMC Bioinformatics. 2014;15:211.
127. S.Koren, M.C.Schatz, B.P.Walenz, et al. Hybrid error correction and de novo assembly of single-molecule sequencing reads. Nat Biotechnol. 2012;30(7):693–700.
128. A.Bankevich, S.Nurk, D.Antipov, et al. SPAdes:a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19(5):455–477.
129. K.F.Au, J.G.Underwood, L.Lee, et al. Improving PacBio long read accuracy by short read alignment. PLoS One. 2012;7(10):e46679.
130. C.-S.Chin, D.H.Alexander, P.Marks, et al. Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data. Nat Methods. 2013;10(6):563–569.•• The successful employment of third generation sequencing data for the complete assembly of microbial genomes.
131. A.Ritz, A.Bashir, S.Sindi, et al. Characterization of structural variants with single molecule and hybrid sequencing approaches. Bioinformatics. 2014;30(24):3458–3466.
132. A.Patel, R.Schwab, Y.-T.Liu, et al. Amplification and thrifty single-molecule sequencing of recurrent somatic structural variations. Genome Res. 2014;24(2):318–328.
133. A.Piccirillo, E.Lavezzo, G.Niero, et al. Full genome sequence-based comparative study of wild-type and vaccine strains of infectious Laryngotracheitis virus from Italy. PLoS One. 2016;11(2):e0149529.
134. S.-W.Lee, P.F.Markham, M.J.C.Coppo, et al. Attenuated vaccines can recombine to form virulent field viruses. Science. 2012;337(6091):188–188.
135. X.Zhang, K.W.Davenport, W.Gu, et al. Improving genome assemblies by sequencing PCR products with PacBio. Biotechniques. 2012;53(1):61–62.
136. E.Domingo, J.Sheldon, C.Perales. Viral quasispecies evolution. Microbiol Mol Biol Rev. 2012;76(2):159–216.
137. J.Gregori, C.Perales, F.Rodriguez-Frias, et al. Viral quasispecies complexity measures. Virology. 2016;493:227–237.
138. M.C.F.Prosperi, M.Salemi. QuRe:software for viral quasispecies reconstruction from next-generation sequencing data. Bioinformatics. 2012;28(1):132–133.
139. L.Z.Hong, S.Hong, H.T.Wong, et al. BAsE-Seq:a method for obtaining long viral haplotypes from short sequence reads. Genome Biol. 2014;15(11):517.
140. F.Di Giallonardo, A.Töpfer, M.Rey, et al. Full-length haplotype reconstruction to infer the structure of heterogeneous virus populations. Nucleic Acids Research. 2014;42(14):e115.
141. W.-T.Poh, E.Xia, K.Chin-Inmanu, et al. Viral quasispecies inference from 454 pyrosequencing. BMC Bioinformatics. 2013;14:355.
142. M.Schirmer, W.T.Sloan, C.Quince. Benchmarking of viral haplotype reconstruction programmes:an overview of the capacities and limitations of currently available programmes. Brief Bioinform. 2014;15(3):431–442.
143. M.C.F.Prosperi, L.Yin, D.J.Nolan, et al. Empirical validation of viral quasispecies assembly algorithms:state-of-the-art and challenges. Sci Rep-UK. 2013;3:2837.
144. T.W.Laver, R.C.Caswell, K.A.Moore, et al. Pitfalls of haplotype phasing from amplicon-based long-read sequencing. Sci Rep. 2016;6:21746.
145. R.Ammar, T.A.Paton, D.Torti, et al. Long read nanopore sequencing for detection of HLA and CYP2D6 variants and haplotypes. F1000Res. 2015;4:17.• Example of application of long reads for SNP phasing and haplotype reconstruction.
146. H.Rohde, J.Qin, Y.Cui, et al. Open-source genomic analysis of Shiga-toxin-producing E. coli O104:H4. N Engl J Med. 2011;365(8):718–724.
147. C.U.Köser, M.T.G.Holden, M.J.Ellington, et al. Rapid whole-genome sequencing for investigation of a neonatal MRSA outbreak. N Engl J Med. 2012;366(24):2267–2275.
148. T.M.Walker, C.L.C.Ip, R.H.Harrell, et al. Whole-genome sequencing to delineate Mycobacterium tuberculosis outbreaks:a retrospective observational study. Lancet Infect Dis. 2013;13(2):137–146.
149. S.R.Harris, E.J.P.Cartwright, M.E.Török, et al. Whole-genome sequencing for analysis of an outbreak of meticillin-resistant Staphylococcus aureus:a descriptive study. Lancet Infect Dis. 2013;13(2):130–136.
150. J.Quick, N.J.Loman, S.Duraffour, et al. Real-time, portable genome sequencing for Ebola surveillance. Nature. 2016;530(7589):228–232.•• This paper shows the feasibility of using third generation sequencing for pathogen detection also in remote areas with no infrastructures.
151. J.R.Kugelman, M.R.Wiley, S.Mate, et al. Monitoring of Ebola virus Makona evolution through establishment of advanced genomic capability in Liberia. Emerg Infect Dis. 2015;21(7):1135–1143.
152. S.K.Gire, A.Goba, K.G.Andersen, et al. Genomic surveillance elucidates Ebola virus origin and transmission during the 2014 outbreak. Science. 2014;345(6202):1369–1372.
153. A.L.Greninger, S.N.Naccache, S.Federman, et al. Rapid metagenomic identification of viral pathogens in clinical samples by real-time nanopore sequencing analysis. Genome Med. 2015;7(1):99.
154. A.Rhoads, K.F.Au. PacBio sequencing and its applications. Genomics Proteomics Bioinformatics. 2015;13(5):278–289.
155. N.R.Faria, S.Azevedo Rdo, M.U.G.Kraemer, et al. Zika virus in the Americas:early epidemiological and genetic findings. Science. 2016;352(6283):345–349.
156. G.Calvet, R.S.Aguiar, A.S.O.Melo, et al. Detection and sequencing of Zika virus from amniotic fluid of fetuses with microcephaly in Brazil:a case study. Lancet Infect Dis. 2016;16:653–660.
157. R.W.Driggers, C.-Y.Ho, E.M.Korhonen, et al. Zika virus infection with prolonged maternal viremia and fetal brain abnormalities. N Engl J Med. 2016;374:2142–2151.
158. J.Mlakar, M.Korva, N.Tul, et al. Zika virus associated with microcephaly. N Engl J Med. 2016;374(10):951–958.
159. K.Judge, S.R.Harris, S.Reuter, et al. Early insights into the potential of the Oxford Nanopore MinION for the detection of antimicrobial resistance genes. J Antimicrob Chemoth. 2015;70(10):2775–2778.
160. V.Militello, E.Lavezzo, G.Costanzi, et al. Accurate human papillomavirus genotyping by 454 pyrosequencing. Clin Microbiol Infec. 2013;19(10):E428–E434.
161. L.Barzon, V.Militello, E.Lavezzo, et al. Human papillomavirus genotyping by 454 next generation sequencing technology. J Clin Virol. 2011;52(2):93–97.• Important application of NGS in viral genotyping:the possibility to detect the simultaneous infection by multiple types in shown in HPV.
162. N.P.AmbulosJr, L.M.Schumaker, T.J.Mathias, et al. Next-generation sequencing-based HPV genotyping assay validated in formalin-fixed, paraffin-embedded oropharyngeal and cervical cancer specimens. J Biomol Tech. 2016;27:46–52. jbt.16-2702-004.
163. T.L.Meiring, A.T.Salimo, B.Coetzee, et al. Next-generation sequencing of cervical DNA detects human papillomavirus types not detected by commercial kits. Virol J. 2012;9:164.
164. E.Lavezzo, G.Masi, S.Toppo, et al. Characterization of intra-type variants of oncogenic human papillomaviruses by next-generation deep sequencing of the E6/E7 region. Viruses. 2016;8(3):79.
165. I.D.Vilfan, Y.-C.Tsai, T.A.Clark, et al. Analysis of RNA base modification and structural rearrangement by single-molecule real-time detection of reverse transcription. J Nanobiotechnology. 2013;11:8.• Third generation sequencing platforms can be applied to detect base modifications.
166. G.Fang, D.Munera, D.I.Friedman, et al. Genome-wide mapping of methylated adenine residues in pathogenic Escherichia coli using single-molecule real-time sequencing (vol 30, pg 1232, 2012). Nature Biotechnology. 2013;31(6):566.
167. J.G.Powers, V.J.Weigman, J.Shu, et al. Efficient and accurate whole genome assembly and methylome profiling of E. coli. BMC Genomics. 2013;14:675.
168. K.T.Mou, U.K.Muppirala, A.J.Severin, et al. A comparative analysis of methylome profiles of Campylobacter jejuni sheep abortion isolate and gastroenteric strains using PacBio data. Front Microbiol. 2015;5:782.
169. J.Shim, Y.Kim, G.I.Humphreys, et al. Nanopore-based assay for detection of methylation in double-stranded DNA fragments. ACS Nano. 2015;9(1):290–300.
170. J.-C.Lagier, S.Edouard, I.Pagnier, et al. Current and past strategies for bacterial culture in clinical microbiology. Clin Microbiol Rev. 2015;28(1):208–236.
171. E.Afshinnekoo, C.Meydan, S.Chowdhury, et al. Geospatial resolution of human and bacterial diversity with city-scale metagenomics. Cell Syst. 2015;1(1):97-97.e3.
172. E.Afshinnekoo, C.Meydan, S.Chowdhury, et al. Geospatial resolution of human and bacterial diversity with city-scale metagenomics. Cell Syst. 2015;1(1):72–87.
173. J.Ackelsberg, J.Rakeman, S.Hughes, et al. Lack of evidence for plague or anthrax on the New York City subway. Cell Syst. 2015;1(1):4–5.