Best practices for analysing microbiomes

被引:1146
作者
Knight, Rob [1 ,4 ,6 ]
Vrbanac, Alison [2 ]
Taylor, Bryn C. [2 ]
Aksenov, Alexander [3 ]
Callewaert, Chris [4 ,5 ]
Debelius, Justine [4 ]
Gonzalez, Antonio [4 ]
Kosciolek, Tomasz [4 ]
McCall, Laura-Isobel [3 ]
McDonald, Daniel [4 ]
Melnik, Alexey V. [3 ]
Morton, James T. [4 ,6 ]
Navas, Jose [6 ]
Quinn, Robert A. [3 ]
Sanders, Jon G. [4 ]
Swafford, Austin D. [1 ]
Thompson, Luke R. [7 ,8 ,9 ]
Tripathi, Anupriya [10 ]
Xu, Zhenjiang Z. [4 ]
Zaneveld, Jesse R. [11 ]
Zhu, Qiyun [4 ]
Caporaso, J. Gregory [12 ]
Dorrestein, Pieter C. [1 ,3 ,4 ]
机构
[1] Univ Calif San Diego, Ctr Microbiome Innovat, La Jolla, CA 92093 USA
[2] Univ Calif San Diego, Biomed Sci Grad Program, La Jolla, CA 92093 USA
[3] Univ Calif San Diego, Skaggs Sch Pharm & Pharmaceut Sci, La Jolla, CA 92093 USA
[4] Univ Calif San Diego, Sch Med, Dept Pediat, La Jolla, CA 92093 USA
[5] Univ Ghent, Ctr Microbial Ecol & Technol, Ghent, Belgium
[6] Univ Calif San Diego, Dept Comp Sci & Engn, La Jolla, CA 92093 USA
[7] Univ Southern Mississippi, Dept Biol Sci, Hattiesburg, MS USA
[8] Univ Southern Mississippi, Northern Gulf Inst, Hattiesburg, MS USA
[9] NOAA, Atlantic Oceanog & Meteorol Lab, Southwest Fisheries Sci Ctr, Natl Marine Fisheries Serv, La Jolla, CA USA
[10] Univ Calif San Diego, Div Biol Sci, La Jolla, CA 92093 USA
[11] Univ Washington Bothell, Sch Sci Technol Engn & Math, Div Biol Sci, Bothell, WA USA
[12] No Arizona Univ, Pathogen & Microbiome Inst, Flagstaff, AZ USA
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
GUT MICROBIOTA; COMMUNITY VARIATION; MASS-SPECTROMETRY; SYSTEMS BIOLOGY; GENE-EXPRESSION; RARE BIOSPHERE; DIVERSITY; BACTERIAL; METAGENOME; GENOMES;
D O I
10.1038/s41579-018-0029-9
中图分类号
Q93 [微生物学];
学科分类号
071005 ; 100705 ;
摘要
Complex microbial communities shape the dynamics of various environments, ranging from the mammalian gastrointestinal tract to the soil. Advances in DNA sequencing technologies and data analysis have provided drastic improvements in microbiome analyses, for example, in taxonomic resolution, false discovery rate control and other properties, over earlier methods. In this Review, we discuss the best practices for performing a microbiome study, including experimental design, choice of molecular analysis technology, methods for data analysis and the integration of multiple omics data sets. We focus on recent findings that suggest that operational taxonomic unit-based analyses should be replaced with new methods that are based on exact sequence variants, methods for integrating metagenomic and metabolomic data, and issues surrounding compositional data analysis, where advances have been particularly rapid. We note that although some of these approaches are new, it is important to keep sight of the classic issues that arise during experimental design and relate to research reproducibility. We describe how keeping these issues in mind allows researchers to obtain more insight from their microbiome data sets.
引用
收藏
页码:410 / 422
页数:13
相关论文
共 165 条
[121]  
Scholz M, 2016, NAT METHODS, V13, P435, DOI [10.1038/NMETH.3802, 10.1038/nmeth.3802]
[122]   A Bayesian method for detecting pairwise associations in compositional data [J].
Schwager, Emma ;
Mallick, Himel ;
Ventz, Steffen ;
Huttenhower, Curtis .
PLOS COMPUTATIONAL BIOLOGY, 2017, 13 (11)
[123]  
Sczyrba A, 2017, NAT METHODS, V14, P1063, DOI [10.1038/NMETH.4458, 10.1038/nmeth.4458]
[124]  
Siddhartha Mandal Siddhartha Mandal, 2015, Microbial Ecology in Health and Disease, V26, P27663
[125]   A phylogenetic transform enhances analysis of compositional microbiota data [J].
Silverman, Justin D. ;
Washburne, Alex D. ;
Mukherjee, Sayan ;
David, Lawrence A. .
ELIFE, 2017, 6
[126]   Assessment of variation in microbial community amplicon sequencing by the Microbiome Quality Control (MBQC) project consortium [J].
Sinha, Rashmi ;
Abu-Ali, Galeb ;
Vogtmann, Emily ;
Fodor, Anthony A. ;
Ren, Boyu ;
Amir, Amnon ;
Schwager, Emma ;
Crabtree, Jonathan ;
Ma, Siyuan ;
Abnet, Christian C. ;
Knight, Rob ;
White, Owen ;
Huttenhower, Curtis .
NATURE BIOTECHNOLOGY, 2017, 35 (11) :1077-+
[127]   Influence of early life exposure, host genetics and diet on the mouse gut microbiome and metabolome [J].
Snijders, Antoine M. ;
Langley, Sasha A. ;
Kim, Young-Mo ;
Brislawn, Colin J. ;
Noecker, Cecilia ;
Zink, Erika M. ;
Fansler, Sarah J. ;
Casey, Cameron P. ;
Miller, Darla R. ;
Huang, Yurong ;
Karpen, Gary H. ;
Celniker, Susan E. ;
Brown, James B. ;
Borenstein, Elhanan ;
Jansson, Janet K. ;
Metz, Thomas O. ;
Mao, Jian-Hua .
NATURE MICROBIOLOGY, 2017, 2 (02)
[128]   Selection of primers for optimal taxonomic classification of environmental 16S rRNA gene sequences [J].
Soergel, David A. W. ;
Dey, Neelendu ;
Knight, Rob ;
Brenner, Steven E. .
ISME JOURNAL, 2012, 6 (07) :1440-1444
[129]   Preservation Methods Differ in Fecal Microbiome Stability, Affecting Suitability for Field Studies [J].
Song, Se Jin ;
Amir, Amnon ;
Metcalf, Jessica L. ;
Amato, Katherine R. ;
Xu, Zhenjiang Zech ;
Humphrey, Greg ;
Knight, Rob .
MSYSTEMS, 2016, 1 (03)
[130]   The role of adaptive immunity as an ecological filter on the gut microbiota in zebrafish [J].
Stagaman, Keaton ;
Burns, Adam R. ;
Guillemin, Karen ;
Bohannan, Brendan J. M. .
ISME JOURNAL, 2017, 11 (07) :1630-1639