Genome-resolved metaproteomic characterization of preterm infant gut microbiota development reveals species-specific metabolic shifts and variabilities during early life

Weili Xiong, Christopher T. Brown, Michael J. Morowitz, Jillian F. Banfield, Robert L. Hettich

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

BACKGROUND: Establishment of the human gut microbiota begins at birth. This early-life microbiota development can impact host physiology during infancy and even across an entire life span. However, the functional stability and population structure of the gut microbiota during initial colonization remain poorly understood. Metaproteomics is an emerging technology for the large-scale characterization of metabolic functions in complex microbial communities (gut microbiota).

RESULTS: We applied a metagenome-informed metaproteomic approach to study the temporal and inter-individual differences of metabolic functions during microbial colonization of preterm human infants' gut. By analyzing 30 individual fecal samples, we identified up to 12,568 protein groups for each of four infants, including both human and microbial proteins. With genome-resolved matched metagenomics, proteins were confidently identified at the species/strain level. The maximum percentage of the proteome detected for the abundant organisms was ~45%. A time-dependent increase in the relative abundance of microbial versus human proteins suggested increasing microbial colonization during the first few weeks of early life. We observed remarkable variations and temporal shifts in the relative protein abundances of each organism in these preterm gut communities. Given the dissimilarity of the communities, only 81 microbial EggNOG orthologous groups and 57 human proteins were observed across all samples. These conserved microbial proteins were involved in carbohydrate, energy, amino acid and nucleotide metabolism while conserved human proteins were related to immune response and mucosal maturation. We identified seven proteome clusters for the communities and showed infant gut proteome profiles were unstable across time and not individual-specific. Applying a gut-specific metabolic module (GMM) analysis, we found that gut communities varied primarily in the contribution of nutrient (carbohydrates, lipids, and amino acids) utilization and short-chain fatty acid production.

CONCLUSIONS: Overall, this study reports species-specific proteome profiles and metabolic functions of human gut microbiota during early colonization. In particular, our work contributes to reveal microbiota-associated shifts and variations in the metabolism of three major nutrient sources and short-chain fatty acid during colonization of preterm infant gut.

Original languageEnglish
Pages (from-to)72
Number of pages1
JournalMicrobiome
Volume5
Issue number1
DOIs
StatePublished - Jul 10 2017

Funding

This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). Research support was provided by NIH grant 1R01-GM-103600. Oak Ridge National Laboratory is managed by UT-Battelle, LLC, for the U.S. Department of Energy.

FundersFunder number
Chemical Sciences Division, Oak Ridge National Laboratory, Bethel Valley RdR01 GM103600
National Institutes of Health
U.S. Department of Energy
National Institute of General Medical SciencesR01GM103600

    Keywords

    • Genome resolved
    • Human infant gut
    • Metaproteomics
    • Microbial metabolic functions
    • Shotgun proteomics

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