Evidence map›Paper›PMID 38383538›Full record

ArticleNature communications2024

Quantifying the adaptive landscape of commensal gut bacteria using high-resolution lineage tracking.

Daniel P G H Wong, Benjamin H Good

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–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

15 citing papers in PubMed.

  1. Review
  2. Article
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  6. Review
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  11. Review
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  14. Article
  15. Within-host evolution of the gut microbiome.Current opinion in microbiology · 2023
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Daniel P G H WongDepartment of Applied Physics, Stanford University, Stanford, CA, 94305, USA.
Benjamin H GoodDepartment of Applied Physics, Stanford University, Stanford, CA, 94305, USA. bhgood@stanford.edu.ORCID 0000-0002-7757-3347

Funding

Quantitative approaches for mapping the real-time evolution of the gut microbiotaR35GM146949 · NIGMS · STANFORD UNIVERSITY · PI Benjamin H Good · 2022 to 2026
$2.0M
NIGMS NIH HHS R35 GM146949
6 · The paper itself

Abstract

Gut microbiota can adapt to their host environment by rapidly acquiring new mutations. However, the dynamics of this process are difficult to characterize in dominant gut species in their complex in vivo environment. Here we show that the fine-scale dynamics of genome-wide transposon libraries can enable quantitative inferences of these in vivo evolutionary forces. By analyzing >400,000 lineages across four human Bacteroides strains in gnotobiotic mice, we observed positive selection on thousands of cryptic variants - most of which were unrelated to their original gene knockouts. The spectrum of fitness benefits varied between species, and displayed diverse tradeoffs over time and in different dietary conditions, enabling inferences of their underlying function. These results suggest that within-host adaptations arise from an intense competition between numerous contending variants, which can strongly influence their emergent evolutionary tradeoffs.

Indexed as

BacteroidesGastrointestinal MicrobiomeAnimalsBacteriaBiological EvolutionHumansMice

Identifiers

PMID38383538
PMCPMC10881964

What OpenQuestion holds

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LicenceCC BY
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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.