Evidence map›Paper›PMID 38961185›Full record

ReviewNature metabolism2024

Emerging tools and best practices for studying gut microbial community metabolism.

Cecilia Noecker, Peter J Turnbaugh

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature metabolism, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Microbial metabolism of host-derived antioxidants.Current opinion in chemical biology · 2025
    Review
  6. Article
  7. 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.

Cecilia NoeckerDepartment of Biological Sciences, Minnesota State University, Mankato, Mankato, MN, USA.ORCID http://orcid.org/0000-0003-1417-2383
Peter J TurnbaughDepartment of Microbiology & Immunology, University of California, San Francisco, San Francisco, CA, USA. peter.turnbaugh@ucsf.edu.ORCID http://orcid.org/0000-0002-0888-2875

Funding

Predicting and preventing drug metabolism by the human gut microbiomeR01HL122593 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Peter James Turnbaugh · 2016 to 2026
$5.7M
Systems-level analysis of the metabolism and ecology of genetically intractable gut bacteriaF32GM140808 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI NOECKER, CECILIA · 2021 to 2022
$134k
U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI) R01HL122593U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS) F32GM140808
6 · The paper itself

Abstract

The human gut microbiome vastly extends the set of metabolic reactions catalysed by our own cells, with far-reaching consequences for host health and disease. However, our knowledge of gut microbial metabolism relies on a handful of model organisms, limiting our ability to interpret and predict the metabolism of complex microbial communities. In this Perspective, we discuss emerging tools for analysing and modelling the metabolism of gut microorganisms and for linking microorganisms, pathways and metabolites at the ecosystem level, highlighting promising best practices for researchers. Continued progress in this area will also require infrastructure development to facilitate cross-disciplinary synthesis of scientific findings. Collectively, these efforts can enable a broader and deeper understanding of the workings of the gut ecosystem and open new possibilities for microbiome manipulation and therapy.

Indexed as

Gastrointestinal MicrobiomeAnimalsHumans

Identifiers

What OpenQuestion holds

Textmetadata
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.