Evidence map›Paper›PMID 29694888›Full record

ArticleCell reports2018

Gut Microbiota-Derived Tryptophan Metabolites Modulate Inflammatory Response in Hepatocytes and Macrophages.

Smitha Krishnan, Yufang Ding, Nima Saedi, Maria Choi, Gautham V Sridharan, David H Sherr, Martin L Yarmush, Robert C Alaniz, Arul Jayaraman, Kyongbum Lee

Erratum issuedOpen access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 355 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
355citing papers in PubMed, 1 pooled it
23.2field-weighted citation impact, top 1% of its field
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

355 citing papers in PubMed, 1 synthesis or guideline pooled it, 669 citations in OpenAlex.

  1. Pooled it
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  5. The Hallmarks of Aging: From Molecular Mechanisms to Clinical Translation.International journal of molecular sciences · 2026
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295 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 5 institutions in 1 country.

Smitha KrishnanDepartment of Chemical and Biological Engineering, Tufts University, Medford, MA 02155, USA.
Yufang DingDepartment of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA.
Nima SaediCenter for Engineering in Medicine, Massachusetts General Hospital, Boston, MA 02114, USA.
Maria ChoiDepartment of Chemical and Biological Engineering, Tufts University, Medford, MA 02155, USA.
Gautham V SridharanDepartment of Chemical and Biological Engineering, Tufts University, Medford, MA 02155, USA.
David H SherrDepartment of Environmental Health, Boston University School of Public Health, Boston, MA 02118, USA.
Martin L YarmushCenter for Engineering in Medicine, Massachusetts General Hospital, Boston, MA 02114, USA.
Robert C AlanizDepartment of Microbial Pathogenesis and Immunology, College of Medicine, Texas Health Science Center, Texas A&M University, College Station, TX, USA.
Arul JayaramanDepartment of Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA; Department of Microbial Pathogenesis and Immunology, College of Medicine, Texas Health Science Center, Texas A&M University, College Station, TX, USA; Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX 77843, USA. Electronic address: arulj@tamu.edu.
Kyongbum LeeDepartment of Chemical and Biological Engineering, Tufts University, Medford, MA 02155, USA. Electronic address: kyongbum.lee@tufts.edu.
Tufts University · USMassachusetts General Hospital · USTexas A&M Health Science Center · USBoston University · USTexas A&M University · US

Funding

Computational Metabolomics of Gut Microbiota MetabolitesR21GM106251 · NIGMS · TUFTS UNIVERSITY MEDFORD · PI LEE, KYONGBUM · 2014 to 2015
$404k
A Machine-Learning Based Software Widget for Resolving Metabolite IdentitiesR03CA211839 · NCI · TUFTS UNIVERSITY MEDFORD · PI LEE, KYONGBUM · 2016 to 2016
$148k
NCI NIH HHS R03 CA211839NIGMS NIH HHS R21 GM106251
6 · The paper itself

Abstract

The gut microbiota plays a significant role in the progression of fatty liver disease; however, the mediators and their mechanisms remain to be elucidated. Comparing metabolite profile differences between germ-free and conventionally raised mice against differences between mice fed a low- and high-fat diet (HFD), we identified tryptamine and indole-3-acetate (I3A) as metabolites that depend on the microbiota and are depleted under a HFD. Both metabolites reduced fatty-acid- and LPS-stimulated production of pro-inflammatory cytokines in macrophages and inhibited the migration of cells toward a chemokine, with I3A exhibiting greater potency. In hepatocytes, I3A attenuated inflammatory responses under lipid loading and reduced the expression of fatty acid synthase and sterol regulatory element-binding protein-1c. These effects were abrogated in the presence of an aryl-hydrocarbon receptor (AhR) antagonist, indicating that the effects are AhR dependent. Our results suggest that gut microbiota could influence inflammatory responses in the liver through metabolites engaging host receptors.

Indexed as

HepatocytesIndoleacetic AcidsMacrophagesTryptaminesTryptophanAnimalsCytokinesDietary FatsFatty Acid Synthase, Type IGastrointestinal MicrobiomeHep G2 CellsHumansInflammationMaleMiceRAW 264.7 CellsCytokinesDietary FatsFatty Acid Synthase, Type Iindoleacetic acidIndoleacetic AcidsReceptors, Aryl HydrocarbonSrebf1 protein, mouseSterol Regulatory Element Binding Protein 1tryptamineTryptaminesTryptophanaryl hydrocarbon receptorgut microbiotaindole-3-acetateinflammationmetabolomicsnonalcoholic fatty liver disease

Identifiers

PMID29694888
PMCPMC6392449
OpenAlexW2802744456

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.