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

Morgan G I Langille, Jesse Zaneveld, James G 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

Research output: Contribution to journalArticle

2338 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 languageEnglish (US)
Pages (from-to)814-821
Number of pages8
JournalNature Biotechnology
Volume31
Issue number9
DOIs
StatePublished - Sep 2013

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rRNA Genes
Genes
Metagenome
Metagenomics
Microbiota
Phylogeny
Uncertainty
Genome
Databases
Composite materials
Chemical analysis

ASJC Scopus subject areas

  • Applied Microbiology and Biotechnology
  • Biotechnology
  • Molecular Medicine
  • Bioengineering
  • Biomedical Engineering

Cite this

Langille, M. G. I., Zaneveld, J., Caporaso, J. G., McDonald, D., Knights, D., Reyes, J. A., ... Huttenhower, C. (2013). Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nature Biotechnology, 31(9), 814-821. https://doi.org/10.1038/nbt.2676

Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. / Langille, Morgan G I; Zaneveld, Jesse; Caporaso, James G; McDonald, Daniel; Knights, Dan; Reyes, Joshua A.; Clemente, Jose C.; Burkepile, Deron E.; Vega Thurber, Rebecca L.; Knight, Rob; Beiko, Robert G.; Huttenhower, Curtis.

In: Nature Biotechnology, Vol. 31, No. 9, 09.2013, p. 814-821.

Research output: Contribution to journalArticle

Langille, MGI, Zaneveld, J, Caporaso, JG, McDonald, D, Knights, D, Reyes, JA, Clemente, JC, Burkepile, DE, Vega Thurber, RL, Knight, R, Beiko, RG & Huttenhower, C 2013, 'Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences', Nature Biotechnology, vol. 31, no. 9, pp. 814-821. https://doi.org/10.1038/nbt.2676
Langille, Morgan G I ; Zaneveld, Jesse ; Caporaso, James G ; McDonald, Daniel ; Knights, Dan ; Reyes, Joshua A. ; Clemente, Jose C. ; Burkepile, Deron E. ; Vega Thurber, Rebecca L. ; Knight, Rob ; Beiko, Robert G. ; Huttenhower, Curtis. / Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. In: Nature Biotechnology. 2013 ; Vol. 31, No. 9. pp. 814-821.
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