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Assessment of variation in microbial community amplicon sequencing by the Microbiome Quality Control (MBQC) project consortium

by Vogtmann, Emily , Crabtree, Jonathan , Schwager, Emma , Fodor, Anthony A , Ma, Siyuan , Knight, Rob , Abnet, Christian C , Sinha, Rashmi , White, Owen , Abu-Ali, Galeb , Huttenhower, Curtis , Amir, Amnon , Ren, Boyu

in 45/23 / 49/22 / 631/158/855 / 631/326/2565/2134 / 692/308/174 / Agriculture / analysis / Bacteria - genetics / Baseline studies / Bioinformatics / Biomedical Engineering/Biotechnology / Biomedicine / Biotechnology / Chemostats / Communities / Consortia / Data processing / Deoxyribonucleic acid / DNA / DNA, Bacterial - chemistry / DNA, Bacterial - genetics / Experimental design / Gastrointestinal Microbiome - genetics / Health aspects / Humans / Intestinal microflora / Life Sciences / Methods / Microbial activity / Microbial colonies / Microbiological assay / Microbiomes / Microbiota / Microorganisms / Nucleic Acid Amplification Techniques - methods / Nucleic Acid Amplification Techniques - standards / Quality control / Reference Standards / Reproducibility / Research Design / Sequences

2017

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Assessment of variation in microbial community amplicon sequencing by the Microbiome Quality Control (MBQC) project consortium

2017

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2017

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Journal Article

Assessment of variation in microbial community amplicon sequencing by the Microbiome Quality Control (MBQC) project consortium

Vogtmann, Emily,

Crabtree, Jonathan,

Schwager, Emma,

Fodor, Anthony A,

Ma, Siyuan,

Knight, Rob,

Abnet, Christian C,

Sinha, Rashmi,

White, Owen,

Abu-Ali, Galeb,

Huttenhower, Curtis,

Amir, Amnon,

Ren, Boyu

2017

Overview

The Microbiome Quality Control project consortium reports outcomes of a baseline study (MBQC) that will guide future improvements in reproducibility of microbiome analyses. In order for human microbiome studies to translate into actionable outcomes for health, meta-analysis of reproducible data from population-scale cohorts is needed. Achieving sufficient reproducibility in microbiome research has proven challenging. We report a baseline investigation of variability in taxonomic profiling for the Microbiome Quality Control (MBQC) project baseline study (MBQC-base). Blinded specimen sets from human stool, chemostats, and artificial microbial communities were sequenced by 15 laboratories and analyzed using nine bioinformatics protocols. Variability depended most on biospecimen type and origin, followed by DNA extraction, sample handling environment, and bioinformatics. Analysis of artificial community specimens revealed differences in extraction efficiency and bioinformatic classification. These results may guide researchers in experimental design choices for gut microbiome studies.

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Publisher

Nature Publishing Group US,Nature Publishing Group

Subject

/ 49/22