Strains, functions and dynamics in the expanded Human Microbiome Project
Open accessAbstract
The characterization of baseline microbial and functional diversity in the human microbiome has enabled studies of microbiome-related disease, diversity, biogeography, and molecular function. The National Institutes of Health Human Microbiome Project has provided one of the broadest such characterizations so far. Here we introduce a second wave of data from the study, comprising 1,631 new metagenomes (2,355 total) targeting diverse body sites with multiple time points in 265 individuals. We applied updated profiling and assembly methods to provide new characterizations of microbiome personalization. Strain identification revealed subspecies clades specific to body sites; it also quantified species with phylogenetic diversity under-represented in isolate genomes. Body-wide functional profiling classified pathways into universal, human-enriched, and body site-enriched subsets. Finally, temporal analysis decomposed microbial variation into rapidly variable, moderately variable, and stable subsets. This study furthers our knowledge of baseline human microbial diversity and enables an understanding of personalized microbiome function and dynamics.
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Comparative genomic analyses usually test for correlations between traits.
“Comparative genomic analyses usually test for correlations between traits.”
From A phylogenetic approach to comparative genomics (2025) · cites this paper as [77]
The Methods section, “Association testing between microbiome features and phenotypic covariates” (page unavailable), describes testing associations between microbial or pathway abundances and subject metadata. This supports the idea that the paper tests associations, but it does not establish that comparative genomic analyses usually test correlations between traits. (LLM, conf=0.77)
Experimental — accuracy not yet measuredWhile the inherited genome is essentially stable for the lifetime of the host, the microbiome is immensely diverse, dynamic, and responsive to external input, enhancing its potential as a target for therapeutic intervention.
“While our inherited genome is essentially stable for the lifetime of the host, the microbiome is immensely diverse (Mosca et al., 2016;Pasolli et al., 2019), dynamic (Lloyd-Price et al., 2017), and responsive to external input, enhancing its potential as a target for therapeutic intervention”
From The Microbiota-Gut-Brain Axis (2019) · cites this paper as Lloyd-Price et al., 2017
The environment has more influence on the gut microbiome than the pathological condition in human progeria.
“Despite the low number of samples, these results suggest that the environment has more influence on the gut microbiome than the pathological condition, which is in accordance with recent findings 22,23 .”
From Healthspan and lifespan extension by fecal microbiota transplantation into progeroid mice (2019) · cites this paper as [23]
Most bacterial taxa detected in pancreatic tumor tissue are also commonly found in the gut microbiome.
“Most of the bacterial communities found in the tumoral milieu are present commonly in the gut microbiome (Human Microbiome Project, 2012b; Lloyd-Price et al., 2017)”
From Tumor Microbiome Diversity and Composition Influence Pancreatic Cancer Outcomes (2019) · cites this paper as Lloyd-Price et al., 2017
HMP1 studies established typical ranges, for some populations, of microbial membership and enzymatic repertoires across the body, combinations of metabolic functions that were either prevalent or strain-specific, and some host factors such as race or ethnicity that determine this variation.
“Studies of both a baseline adult population21–23 and ‘demonstration’ populations with specific disease states established typical ranges (for some populations) of microbial membership and enzymatic repertoires across the body, combinations of metabolic functions that were either prevalent or strain-specific, and some of the host factors (such as race or ethnicity) that determine this variation.”
From The Integrative Human Microbiome Project (2019) · cites this paper as [23]
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Wilbert, S. A., Welch, J. L. M., & Borisy, G. G. (2019) · Cell Reports · doi:10.1016/j.celrep.2020.02.097 · Cited by 194 · see citing works
Key features and guidelines for the application of microbial alpha diversity metrics
Cassol, I., Ibañez, M., & Bustamante, J. P. (2025) · Scientific Reports · doi:10.1038/s41598-024-77864-y · Cited by 194 · see citing works
Nickols, W. A., Kuntz, T. M., Shen, J., Maharjan, S., Mallick, H., Franzosa, E. A., Thompson, K. N., Nearing, J. T., & Huttenhower, C. (2026) · Nature Methods · doi:10.1038/s41592-025-02923-9 · Cited by 192 · see citing works
Self-citation
- Authors
- Lloyd-Price, J., Mahurkar, A., Rahnavard, G., Crabtree, J., Orvis, J., Hall, A. B., Brady, A., Creasy, H. H., McCracken, C., Giglio, M. G., McDonald, D., Franzosa, E. A., Knight, R., White, O., & Huttenhower, C.
- Affiliations
- University of Maryland, Baltimore (US)
- Broad Institute (US)
- University of California San Diego (US)
- Corresponding author
- Huttenhower, Curtis
- ORCID
- Venue
- Nature
- Published
- 2017-09-20
- Volume
- 550
- Issue
- 7674
- Pages
- 61-66
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC5831082
- OpenAlex
- W2756958651
- Cited by
- 1,267
- References
- 70
- Citations by year
- 2026: 91 · 2025: 126 · 2024: 150 · 2023: 108 · 2022: 165 · 2021: 195 · 2020: 160 · 2019: 168 · 2018: 91 · 2017: 10 · 2014: 1
- FWCI
- 47.89
- Type
- journal article
- Language
- en
- Update notices
- erratum (2017-10-12)
- Open access
- hybrid
- doi.org
- Locations
- Nature (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- Funders
- National Institutes of Health
- National Human Genome Research Institute (U54HG004969, U54HG003079, U01HG004866, U01HG006537, R01HG004872, U54HG004968, U54HG004973)
- National Institute of Allergy and Infectious Diseases (U54AI084844)
- National Institute of Diabetes and Digestive and Kidney Diseases (U54DK102557, P30DK043351)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
- Keywords
- human microbiome, metagenomics, Human Microbiome Project, microbial diversity, strain identification, phylogenetic diversity, functional profiling, pathway enrichment, temporal dynamics
- MeSH terms
- Humans, National Institutes of Health (U.S.), Organ Specificity, Phylogeny, Time Factors, United States, Metagenome, Molecular Sequence Annotation, Spatio-Temporal Analysis, Microbiota, Datasets as Topic
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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