Evidence map›Paper›PMID 42039569›Full record

ArticlebioRxiv : the preprint server for biology2026

Metabolic inequality in microbial communities.

Emmi A Mueller, Jay T Lennon

Abstract readPreprint
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

2 authors.

Emmi A MuellerDepartment of Biology, Indiana University, Bloomington, IN 47405, USA.
Jay T LennonDepartment of Biology, Indiana University, Bloomington, IN 47405, USA.ORCID 0000-0003-3126-6111

Funding

Cell dormancy and virus entrapmentR35GM161372 · NIGMS · TRUSTEES OF INDIANA UNIVERSITY · PI Jay T Lennon · 2026 to 2026
$429k
NIGMS NIH HHS R35 GM161372
6 · The paper itself

Abstract

How metabolic activity is partitioned among individuals determines the scaling of cellular physiology to higher levels of biological organization. Yet the mechanisms that generate this heterogeneity and shape its distribution remain largely unresolved. We quantified single-cell metabolism in microbial communities spanning aquatic, terrestrial, and host-associated ecosystems. Across more than one million cells, metabolic activity followed a long-tailed distribution best described by a lognormal model, with a small subset of individuals contributing disproportionately to community metabolism. In some cases, the most active 20% of cells accounted for over 90% of metabolic output, but this pattern became less pronounced in more productive environments. To assess the consequences of metabolic inequality, we developed a stochastic simulation model linking single-cell activity to community respiration via enzyme kinetics. Because respiration responds nonlinearly to enzyme activity, variation among cells does not translate proportionally into ecosystem-level fluxes. As a result, ignoring metabolic heterogeneity can bias estimates of community respiration by up to 60%. Our findings reveal a general pattern of metabolic inequality in microbial communities that holds across a wide range of habitats. Accounting for this structure is critical for understanding how microorganisms regulate ecosystem processes and for improving predictions of large-scale biogeochemical dynamics.

Indexed as

ecologymetabolic theoryphenotypic heterogeneityproductivityscaling

Identifiers

PMID42039569
PMCPMC13105025

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.