Understanding and overcoming the pitfalls and biases of next-generation sequencing (NGS) methods for use in the routine clinical microbiological diagnostic laboratory

被引:168
作者
Boers, Stefan A. [1 ]
Jansen, Ruud [2 ]
Hays, John P. [1 ]
机构
[1] Erasmus Univ, Med Ctr Rotterdam, Erasmus MC, Dept Med Microbiol & Infect Dis, Rotterdam, Netherlands
[2] Reg Lab Publ Hlth Kennemerland, Dept Mol Biol, Haarlem, Netherlands
关键词
Routine clinical microbiological diagnostics; Microbiota analysis; Pitfalls and biases; 16S rRNA gene; (Shotgun) metagenomics; Next-generation sequencing; RIBOSOMAL-RNA GENES; GUT MICROBIOME; PCR; IDENTIFICATION; OUTBREAK; EXTRACTION; CULTURE; MARKER; CONTAMINATION; AMPLIFICATION;
D O I
10.1007/s10096-019-03520-3
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
Recent advancements in next-generation sequencing (NGS) have provided the foundation for modern studies into the composition of microbial communities. The use of these NGS methods allows for the detection and identification of (difficult-to-culture') microorganisms using a culture-independent strategy. In the field of routine clinical diagnostics however, the application of NGS is currently limited to microbial strain typing for epidemiological purposes only, even though the implementation of NGS for microbial community analysis may yield clinically important information. This lack of NGS implementation is due to many different factors, including issues relating to NGS method standardization and result reproducibility. In this review article, the authors provide a general introduction to the most widely used NGS methods currently available (i.e., targeted amplicon sequencing and shotgun metagenomics) and the strengths and weaknesses of each method is discussed. The focus of the publication then shifts toward 16S rRNA gene NGS methods, which are currently the most cost-effective and widely used NGS methods for research purposes, and are therefore more likely to be successfully implemented into routine clinical diagnostics in the short term. In this respect, the experimental pitfalls and biases created at each step of the 16S rRNA gene NGS workflow are explained, as well as their potential solutions. Finally, a novel diagnostic microbiota profiling platform (MYcrobiota') is introduced, which was developed by the authors by taking into consideration the pitfalls, biases, and solutions explained in this article. The development of the MYcrobiota, and future NGS methodologies, will help pave the way toward the successful implementation of NGS methodologies into routine clinical diagnostics.
引用
收藏
页码:1059 / 1070
页数:12
相关论文
共 111 条
  • [1] Low gut microbiota diversity in early infancy precedes asthma at school age
    Abrahamsson, T. R.
    Jakobsson, H. E.
    Andersson, A. F.
    Bjorksten, B.
    Engstrand, L.
    Jenmalm, M. C.
    [J]. CLINICAL AND EXPERIMENTAL ALLERGY, 2014, 44 (06) : 842 - 850
  • [2] The rpoB gene as a tool for clinical microbiologists
    Adekambi, Toidi
    Drancourt, Michel
    Raoult, Didier
    [J]. TRENDS IN MICROBIOLOGY, 2009, 17 (01) : 37 - 45
  • [3] Early infancy microbial and metabolic alterations affect risk of childhood asthma
    Arrieta, Marie-Claire
    Stiemsma, Leah T.
    Dimitriu, Pedro A.
    Thorson, Lisa
    Russell, Shannon
    Yurist-Doutsch, Sophie
    Kuzeljevic, Boris
    Gold, Matthew J.
    Britton, Heidi M.
    Lefebvre, Diana L.
    Subbarao, Padmaja
    Mandhane, Piush
    Becker, Allan
    McNagny, Kelly M.
    Sears, Malcolm R.
    Kollmann, Tobias
    Mohn, William W.
    Turvey, Stuart E.
    Finlay, B. Brett
    [J]. SCIENCE TRANSLATIONAL MEDICINE, 2015, 7 (307)
  • [4] At least 1 in 20 16S rRNA sequence records currently held in public repositories is estimated to contain substantial anomalies
    Ashelford, KE
    Chuzhanova, NA
    Fry, JC
    Jones, AJ
    Weightman, AJ
    [J]. APPLIED AND ENVIRONMENTAL MICROBIOLOGY, 2005, 71 (12) : 7724 - 7736
  • [5] Freezing fecal samples prior to DNA extraction affects the Firmicutes to Bacteroidetes ratio determined by downstream quantitative PCR analysis
    Bahl, Martin Iain
    Bergstrom, Anders
    Licht, Tine Rask
    [J]. FEMS MICROBIOLOGY LETTERS, 2012, 329 (02) : 193 - 197
  • [6] Role of the Gut Microbiome in Obesity and Diabetes Mellitus
    Barlow, Gillian M.
    Yu, Allen
    Mathur, Ruchi
    [J]. NUTRITION IN CLINICAL PRACTICE, 2015, 30 (06) : 787 - 797
  • [7] Use of Metatranscriptomics in Microbiome Research
    Bashiardes, Stavros
    Zilberman-Schapira, Gili
    Elinav, Eran
    [J]. BIOINFORMATICS AND BIOLOGY INSIGHTS, 2016, 10 : 19 - 25
  • [8] A Modified RNA-Seq Approach for Whole Genome Sequencing of RNA Viruses from Faecal and Blood Samples
    Batty, Elizabeth M.
    Wong, T. H. Nicholas
    Trebes, Amy
    Argoud, Karene
    Attar, Moustafa
    Buck, David
    Ip, Camilla L. C.
    Golubchik, Tanya
    Cule, Madeleine
    Bowden, Rory
    Manganis, Charis
    Klenerman, Paul
    Barnes, Eleanor
    Walker, A. Sarah
    Wyllie, David H.
    Wilson, Daniel J.
    Dingle, Kate E.
    Peto, Tim E. A.
    Crook, Derrick W.
    Piazza, Paolo
    [J]. PLOS ONE, 2013, 8 (06):
  • [9] Species-level resolution of 16S rRNA gene amplicons sequenced through the MinION™ portable nanopore sequencer
    Benitez-Paez, Alfonso
    Portune, Kevin J.
    Sanz, Yolanda
    [J]. GIGASCIENCE, 2016, 5
  • [10] Are Oligotypes Meaningful Ecological and Phylogenetic Units? A Case Study of Microcystis in Freshwater Lakes
    Berry, Michelle A.
    White, Jeffrey D.
    Davis, Timothy W.
    Jain, Sunit
    Johengen, Thomas H.
    Dick, Gregory J.
    Sarnelle, Orlando
    Denef, Vincent J.
    [J]. FRONTIERS IN MICROBIOLOGY, 2017, 8