Evidence map›Paper›PMID 38105970›Full record

ArticlebioRxiv : the preprint server for biology2023

An evolution-based framework for describing human gut bacteria.

Benjamin A Doran, Robert Y Chen, Hannah Giba, Vivek Behera, Bidisha Barat, Anitha Sundararajan, Huaiying Lin, Ashley Sidebottom, Eric G Pamer, Arjun S Raman

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Benjamin A DoranDuchossois Family Institute, University of Chicago, Chicago, IL, 60637.ORCID 0000-0003-4713-5562
Robert Y ChenDepartment of Psychiatry, University of Washington, Seattle, WA, 98195.
Hannah GibaDuchossois Family Institute, University of Chicago, Chicago, IL, 60637.
Vivek BeheraDepartment of Medicine, University of Chicago, Chicago, IL, 60637.
Bidisha BaratDuchossois Family Institute, University of Chicago, Chicago, IL, 60637.
Anitha SundararajanDuchossois Family Institute, University of Chicago, Chicago, IL, 60637.
Huaiying LinDuchossois Family Institute, University of Chicago, Chicago, IL, 60637.
Ashley SidebottomDuchossois Family Institute, University of Chicago, Chicago, IL, 60637.
Eric G PamerDuchossois Family Institute, University of Chicago, Chicago, IL, 60637.
Arjun S RamanDuchossois Family Institute, University of Chicago, Chicago, IL, 60637.ORCID 0000-0002-0070-1953

Funding

Using co-evolution to understand the emergence of bacterial phenotype from proteome variationR35GM146702 · NIGMS · UNIVERSITY OF CHICAGO · PI Arjun Raman · 2022 to 2026
$2.0M
NIGMS NIH HHS R35 GM146702
6 · The paper itself

Abstract

The human gut microbiome contains many bacterial strains of the same species ('strain-level variants'). Describing strains in a biologically meaningful way rather than purely taxonomically is an important goal but challenging due to the genetic complexity of strain-level variation. Here, we measured patterns of co-evolution across >7,000 strains spanning the bacterial tree-of-life. Using these patterns as a prior for studying hundreds of gut commensal strains that we isolated, sequenced, and metabolically profiled revealed widespread structure beneath the phylogenetic level of species. Defining strains by their co-evolutionary signatures enabled predicting their metabolic phenotypes and engineering consortia from strain genome content alone. Our findings demonstrate a biologically relevant organization to strain-level variation and motivate a new schema for describing bacterial strains based on their evolutionary history.

Identifiers

PMID38105970
PMCPMC10723311

What OpenQuestion holds

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LicenceCC BY-ND
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Registered trials

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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.