Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences

Morgan G.I. Langille; Jesse Zaneveld; J. Gregory Caporaso; Daniel McDonald; Dan Knights; Joshua A. Reyes; Jose C. Clemente; Deron E. Burkepile; Rebecca L. Vega Thurber; Rob Knight; Robert G. Beiko; Curtis Huttenhower

doi:10.1038/nbt.2676

Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences

Morgan G.I. Langille, Jesse Zaneveld, J. Gregory Caporaso, Daniel McDonald, Dan Knights, Joshua A. Reyes, Jose C. Clemente, Deron E. Burkepile, Rebecca L. Vega Thurber, Rob Knight, Robert G. Beiko, Curtis Huttenhower

Medicine

Research output: Contribution to journal › Article › peer-review

7342 Citations (Scopus)

Abstract

Profiling phylogenetic marker genes, such as the 16S rRNA gene, is a key tool for studies of microbial communities but does not provide direct evidence of a community's functional capabilities. Here we describe PICRUSt (phylogenetic investigation of communities by reconstruction of unobserved states), a computational approach to predict the functional composition of a metagenome using marker gene data and a database of reference genomes. PICRUSt uses an extended ancestral-state reconstruction algorithm to predict which gene families are present and then combines gene families to estimate the composite metagenome. Using 16S information, PICRUSt recaptures key findings from the Human Microbiome Project and accurately predicts the abundance of gene families in host-associated and environmental communities, with quantifiable uncertainty. Our results demonstrate that phylogeny and function are sufficiently linked that this 'predictive metagenomic' approach should provide useful insights into the thousands of uncultivated microbial communities for which only marker gene surveys are currently available.

Original language	English
Pages (from-to)	814-821
Number of pages	8
Journal	Nature Biotechnology
Volume	31
Issue number	9
DOIs	https://doi.org/10.1038/nbt.2676
Publication status	Published - Sept 2013

Bibliographical note

Funding Information:
We would like to thank A. Robbins-Pianka and N. Segata, along with all members of the Knight, Beiko, Vega Thurber, Caporaso and Huttenhower laboratories, for their assistance during PICRUSt conception and development. This work was supported in part by the Canadian Institutes of Health Research (M.G.I.L., R.G.B.), the Canada Research Chairs program (R.G.B.), US National Science Foundation (NSF) OCE #1130786 (R.V.T., D.B.), the Howard Hughes Medical Institute (R.K.), US National Institutes of Health (NIH) P01DK078669, U01HG004866, R01HG004872 (R.K.), the Crohn’s and Colitis Foundation of America (R.K.), the Sloan Foundation (R.K.), NIH 1R01HG005969 (C.H.), NSF CAREER DBI-1053486 (C.H.) and ARO W911NF-11-1-0473 (C.H.).

ASJC Scopus Subject Areas

Biotechnology
Bioengineering
Applied Microbiology and Biotechnology
Molecular Medicine
Biomedical Engineering

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title = "Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences",

abstract = "Profiling phylogenetic marker genes, such as the 16S rRNA gene, is a key tool for studies of microbial communities but does not provide direct evidence of a community's functional capabilities. Here we describe PICRUSt (phylogenetic investigation of communities by reconstruction of unobserved states), a computational approach to predict the functional composition of a metagenome using marker gene data and a database of reference genomes. PICRUSt uses an extended ancestral-state reconstruction algorithm to predict which gene families are present and then combines gene families to estimate the composite metagenome. Using 16S information, PICRUSt recaptures key findings from the Human Microbiome Project and accurately predicts the abundance of gene families in host-associated and environmental communities, with quantifiable uncertainty. Our results demonstrate that phylogeny and function are sufficiently linked that this 'predictive metagenomic' approach should provide useful insights into the thousands of uncultivated microbial communities for which only marker gene surveys are currently available.",

author = "Langille, {Morgan G.I.} and Jesse Zaneveld and Caporaso, {J. Gregory} and Daniel McDonald and Dan Knights and Reyes, {Joshua A.} and Clemente, {Jose C.} and Burkepile, {Deron E.} and {Vega Thurber}, {Rebecca L.} and Rob Knight and Beiko, {Robert G.} and Curtis Huttenhower",

note = "Funding Information: We would like to thank A. Robbins-Pianka and N. Segata, along with all members of the Knight, Beiko, Vega Thurber, Caporaso and Huttenhower laboratories, for their assistance during PICRUSt conception and development. This work was supported in part by the Canadian Institutes of Health Research (M.G.I.L., R.G.B.), the Canada Research Chairs program (R.G.B.), US National Science Foundation (NSF) OCE #1130786 (R.V.T., D.B.), the Howard Hughes Medical Institute (R.K.), US National Institutes of Health (NIH) P01DK078669, U01HG004866, R01HG004872 (R.K.), the Crohn{\textquoteright}s and Colitis Foundation of America (R.K.), the Sloan Foundation (R.K.), NIH 1R01HG005969 (C.H.), NSF CAREER DBI-1053486 (C.H.) and ARO W911NF-11-1-0473 (C.H.).",

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AU - Knights, Dan

AU - Reyes, Joshua A.

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AU - Vega Thurber, Rebecca L.

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AU - Beiko, Robert G.

AU - Huttenhower, Curtis

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Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences

Abstract

Bibliographical note

ASJC Scopus Subject Areas

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