Evidence map›Paper›PMID 42244647›Full record

ArticlebioRxiv : the preprint server for biology2026

A single-strain dropout screen reveals mechanistic links between microbial ecology and metabolism.

Xianfeng Zeng, Xiandong Meng, Allison M Weakley, Steven Higginbottom, Eugenell Mae Lopez, Ashley V Cabrera, Ira J Gray, Brian C DeFelice, Masahiko Terasaki, Aishan Zhao and 4 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. 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

14 authors.

Xianfeng ZengDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0001-9593-3388
Xiandong MengDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.
Allison M WeakleyChEM-H Institute, Stanford University, Stanford, CA 94305, USA.
Steven HigginbottomChEM-H Institute, Stanford University, Stanford, CA 94305, USA.
Eugenell Mae LopezChEM-H Institute, Stanford University, Stanford, CA 94305, USA.
Ashley V CabreraChEM-H Institute, Stanford University, Stanford, CA 94305, USA.
Ira J GrayChan Zuckerberg Biohub, San Francisco, CA 94158, USA.
Brian C DeFeliceChan Zuckerberg Biohub, San Francisco, CA 94158, USA.
Masahiko TerasakiDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.
Aishan ZhaoDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-9010-7981
Kerrigan R HallDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.
Mikhail LeviaChEM-H Institute, Stanford University, Stanford, CA 94305, USA.
Jeanette ArreolaChEM-H Institute, Stanford University, Stanford, CA 94305, USA.
Michael A FischbachDepartment of Bioengineering, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0003-3079-8247

Funding

Dietary and Microbial Reprogramming of Intestinal Microbiota-Produced MetabolitesR01DK101674 · NIDDK · STANFORD UNIVERSITY · PI FISCHBACH, MICHAEL ANDREW, MEYER, TIMOTHY W · 2014 to 2024
$6.5M
NIDDK NIH HHS R01 DK101674
6 · The paper itself

Abstract

The complexity of the gut microbiome has made it challenging to define the role of individual species in community-level function. Here, we constructed 56 single-strain dropout variants of a defined 118-member community and used each one to colonize a group of germ-free mice. In many cases, removing a single strain triggered a large reordering of a small group of species, which in turn altered the community's metabolic output.

Identifiers

PMID42244647
PMCPMC13232234

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.