Evidence map›Paper›PMID 36909644›Full record

ArticlebioRxiv : the preprint server for biology2023

Microbial community-scale metabolic modeling predicts personalized short chain fatty acid production profiles in the human gut.

Nick Quinn-Bohmann, Tomasz Wilmanski, Katherine Ramos Sarmiento, Lisa Levy, Johanna W Lampe, Thomas Gurry, Noa Rappaport, Erin M Ostrem, Ophelia S Venturelli, Christian Diener and 1 more

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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

5 · Who and what money

Authors and funding

11 authors.

Nick Quinn-BohmannInstitute for Systems Biology, Seattle, WA 98109, USA.
Tomasz WilmanskiInstitute for Systems Biology, Seattle, WA 98109, USA.ORCID 0000-0003-1059-073X
Katherine Ramos SarmientoInstitute for Systems Biology, Seattle, WA 98109, USA.
Lisa LevyFred Hutchinson Cancer Center, Seattle, WA 98109, USA.
Johanna W LampeFred Hutchinson Cancer Center, Seattle, WA 98109, USA.ORCID 0000-0003-2717-3780
Thomas GurryPharmaceutical Biochemistry Group, School of Pharmaceutical Sciences, University of Geneva, Switzerland.ORCID 0000-0002-8639-1860
Noa RappaportCenter for Phenomic Health, Buck Institute for Research on Aging, Novato, CA 94945, USA.ORCID 0000-0001-8643-2055
Erin M OstremDepartment of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA.
Ophelia S VenturelliDepartment of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA.ORCID 0000-0003-2200-1963
Christian DienerInstitute for Systems Biology, Seattle, WA 98109, USA.ORCID 0000-0002-7476-0868
Sean M GibbonsInstitute for Systems Biology, Seattle, WA 98109, USA.ORCID 0000-0002-8724-7916

Funding

Translational Bioimaging Core Shared ResourceP30CA015704 · NCI · FRED HUTCHINSON CANCER RESEARCH CENTER · PI Eric Collisson · 1985 to 2026
$296.4M
Systems BiologyU19AG023122 · NIA · TRANSLATIONAL GENOMICS RESEARCH INST · PI FRED H GAGE · 2004 to 2026
$102.6M
PILOT STUDY--CLINICAL NUTRITION RESEARCHP30DK035816 · NIDDK · UNIVERSITY OF WASHINGTON · PI Ellen A Schur · 1986 to 2026
$30.4M
Institutional Training in the Genomic SciencesT32HG002760 · NHGRI · UNIVERSITY OF WISCONSIN-MADISON · PI Qiongshi Lu · 2003 to 2026
$17.7M
CyberGut: towards personalized human-microbiome metabolic modeling for precision health and nutritionR01DK133468 · NIDDK · INSTITUTE FOR SYSTEMS BIOLOGY · PI Sean Michael Gibbons · 2022 to 2026
$3.6M
NCI NIH HHS P30 CA015704NHGRI NIH HHS T32 HG002760NIA NIH HHS U19 AG023122NIDDK NIH HHS P30 DK035816NIDDK NIH HHS R01 DK133468
6 · The paper itself

Abstract

Microbially-derived short chain fatty acids (SCFAs) in the human gut are tightly coupled to host metabolism, immune regulation, and integrity of the intestinal epithelium. However, the production of SCFAs can vary widely between individuals consuming the same diet, with lower levels often associated with disease. A systems-scale mechanistic understanding of this heterogeneity is lacking. We present a microbial community-scale metabolic modeling (MCMM) approach to predict individual-specific SCFA production profiles. We assess the quantitative accuracy of our MCMMs using

Indexed as

flux balance analysisgut microbiomemetabolic modelprecision nutritionshort chain fatty acids

Identifiers

PMID36909644
PMCPMC10002715

What OpenQuestion holds

Textfull text, public
LicenceCC BY
reference markers read3
measurements read48
Read underepoch 390

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.