Evidence map›Paper›PMID 27279224›Full record

ArticleNature2016

Universality of human microbial dynamics.

Amir Bashan, Travis E Gibson, Jonathan Friedman, Vincent J Carey, Scott T Weiss, Elizabeth L Hohmann, Yang-Yu Liu

Abstract read
In one paragraph

Article in Nature, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 137 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
137citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

137 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  16. Review
  17. Quantifying compositional variability in microbial communities with FAVA.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  18. Mechanisms promoting biodiversity in ecosystems.Quantitative biology (Beijing, China) · 2025
    Review
  19. Review
  20. Article

77 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Amir BashanChanning Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA.
Travis E GibsonChanning Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA.
Jonathan FriedmanPhysics of Living Systems, Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.
Vincent J CareyChanning Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA.
Scott T WeissChanning Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA.
Elizabeth L HohmannInfectious Disease Division, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA.
Yang-Yu LiuChanning Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA.

Funding

RANDOMIZED CONTROLLED TRIAL: VDAART CONTINUATION STUDY - DCC - LEADR01HL091528 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI LITONJUA, AUGUSTO A, WEISS, SCOTT T · 2014 to 2018
$9.1M
NHLBI NIH HHS R01 HL091528
6 · The paper itself

Abstract

Human-associated microbial communities have a crucial role in determining our health and well-being, and this has led to the continuing development of microbiome-based therapies such as faecal microbiota transplantation. These microbial communities are very complex, dynamic and highly personalized ecosystems, exhibiting a high degree of inter-individual variability in both species assemblages and abundance profiles. It is not known whether the underlying ecological dynamics of these communities, which can be parameterized by growth rates, and intra- and inter-species interactions in population dynamics models, are largely host-independent (that is, universal) or host-specific. If the inter-individual variability reflects host-specific dynamics due to differences in host lifestyle, physiology or genetics, then generic microbiome manipulations may have unintended consequences, rendering them ineffective or even detrimental. Alternatively, microbial ecosystems of different subjects may exhibit universal dynamics, with the inter-individual variability mainly originating from differences in the sets of colonizing species. Here we develop a new computational method to characterize human microbial dynamics. By applying this method to cross-sectional data from two large-scale metagenomic studies--the Human Microbiome Project and the Student Microbiome Project--we show that gut and mouth microbiomes display pronounced universal dynamics, whereas communities associated with certain skin sites are probably shaped by differences in the host environment. Notably, the universality of gut microbial dynamics is not observed in subjects with recurrent Clostridium difficile infection but is observed in the same set of subjects after faecal microbiota transplantation. These results fundamentally improve our understanding of the processes that shape human microbial ecosystems, and pave the way to designing general microbiome-based therapies.

Indexed as

EcosystemClostridioides difficileClostridium InfectionsComputer SimulationCross-Sectional StudiesDatasets as TopicEnvironmentFecal Microbiota TransplantationGastrointestinal MicrobiomeHealthy VolunteersHumansIntestinesMetagenomicsMicrobiotaMouthOrgan Specificity

Identifiers

PMID27279224
PMCPMC4902290

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.