Evidence map›Paper›PMID 42818693›Full record

ArticlebioRxiv : the preprint server for biology2026

The ecological context of enzymatic variation.

Joseph A Landsittel, Addison Howe, Seppe Kuehn, Kiseok K Lee, Madhav Mani

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

5 authors.

Joseph A LandsittelDepartment of Engineering Science and Applied Mathematics, Northwestern University, Evanston, Illinois 60208 USA.ORCID 0000-0001-6586-4924
Addison HoweDepartment of Engineering Science and Applied Mathematics, Northwestern University, Evanston, Illinois 60208 USA.ORCID 0009-0007-3330-9927
Seppe KuehnDepartment of Ecology & Evolution, University of Chicago, 1101 East 57th Street, Chicago, IL 60637.ORCID 0000-0002-4130-6845
Kiseok K LeeDepartment of Chemical & Biomolecular Engineering, University of Delaware, 150 Academy Street, Newark, DE 19716.ORCID 0000-0002-3298-7116
Madhav ManiDeparment of Mathematics, Imperial College London, London, UK SW72AZ.ORCID 0000-0002-5812-4167

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Among the challenges in understanding microbial ecosystems is the presence of physics at vastly different scales. Reactions, catalyzed by enzymes but regulated at the level of the cell, propel the flux of carbon and nitrogen through our atmosphere. Compounding this is the presence of pervasive enzyme sequence variation; this variation has been shown to contain coevolving modes of amino acids which encode the enzyme's evolutionary history. In this work, we take steps towards bridging the gap between the enzymatic variation present in an ecosystem and its subsequent activity. We employ the reduction of nitrate by NarG as a model system, which acts as an essential step in the nitrogen cycle by mediating both the return of di-nitrogen to the atmosphere and the assimilation of nitrate into biomass. Considering both metagenomic reconstructions as well as functional data from soil nitrate reducers, we find that sequence variants of enzymes obey predictable responses to environmental fluctuations. That is, while prior community-level metagenomic studies have characterized the response of bacterial strains to the environment, our study provides an enzyme variant level sequence-to-response map. Further, we demonstrate that a simple statistical model can predict the organismal phenotype from variant sequence; in soil samples not originally seen by that model, the prediction of a variant's reduction rate correlates with how much cells with that variant grow in abundance.

Identifiers

PMID42818693
PMCPMC13622635

What OpenQuestion holds

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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.