Evidence map›Paper›PMID 39604625›Full record

ReviewNature microbiology2024

A framework for understanding collective microbiome metabolism.

Matthias Huelsmann, Olga T Schubert, Martin Ackermann

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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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

3 authors.

Matthias HuelsmannDepartment of Environmental Systems Science, Swiss Federal Institute of Technology Zurich (ETH Zurich), Zurich, Switzerland. matthias.huelsmann@alumni.ethz.ch.ORCID http://orcid.org/0000-0003-1955-0953
Olga T SchubertDepartment of Environmental Systems Science, Swiss Federal Institute of Technology Zurich (ETH Zurich), Zurich, Switzerland.ORCID http://orcid.org/0000-0002-2613-0714
Martin AckermannDepartment of Environmental Systems Science, Swiss Federal Institute of Technology Zurich (ETH Zurich), Zurich, Switzerland.ORCID http://orcid.org/0000-0003-0087-4819

Funding

EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 Marie Skłodowska-Curie Actions (H2020 Excellent Science - Marie Skłodowska-Curie Actions) 101023360Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation) 180575Simons Foundation 542389Simons Foundation 542395
6 · The paper itself

Abstract

Microbiome metabolism underlies numerous vital ecosystem functions. Individual microbiome members often perform partial catabolism of substrates or do not express all of the metabolic functions required for growth. Microbiome members can complement each other by exchanging metabolic intermediates and cellular building blocks to achieve a collective metabolism. We currently lack a mechanistic framework to explain why microbiome members adopt partial metabolism and how metabolic functions are distributed among them. Here we argue that natural selection for proteome efficiency-that is, performing essential metabolic fluxes at a minimal protein investment-explains partial metabolism of microbiome members, which underpins the collective metabolism of microbiomes. Using the carbon cycle as an example, we discuss motifs of collective metabolism, the conditions under which these motifs increase the proteome efficiency of individuals and the metabolic interactions they result in. In summary, we propose a mechanistic framework for how collective metabolic functions emerge from selection on individuals.

Indexed as

BacteriaMicrobiotaBacterial ProteinsCarbon CycleHumansMetabolic Networks and PathwaysProteomeSelection, GeneticBacterial ProteinsProteome

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.