Evidence map›Paper›PMID 41387544›Full record

ArticleScientific reports2025

Data-driven analysis reveals distinct genomic and environmental contributions to bacterial growth curves.

Jiarun Gong, Bei-Wen Ying

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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.

Jiarun GongSchool of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8572, Japan.
Bei-Wen YingSchool of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8572, Japan. ying.beiwen.gf@u.tsukuba.ac.jp.

Funding

Japan Society for the Promotion of Science 25K02259
6 · The paper itself

Abstract

Bacterial growth dynamics, typically represented by growth curves, are fundamental yet complex features of living populations. Traditional analyses focusing on specific parameters often overlook the full temporal patterns of growth. Here, we systematically investigated how genomic and environmental factors shape bacterial growth dynamics by analyzing 870 growth curves from five Escherichia coli strains with varying genome sizes cultured in 29 chemically defined media. Using dynamic time warping, clustering, and gradient boosting decision trees, we found that environmental components, especially glucose, primarily determine overall growth curve patterns, while genome size governs detailed growth parameters such as lag time, growth rate, and carrying capacity. Notably, finer clustering revealed increased genomic influence and decreased environmental impact, suggesting a hierarchical interaction where the environment modulates broad growth behavior and the genome fine-tunes specific growth responses. These findings provide insights into the coordinated roles of genome and environment in bacterial population dynamics, advancing our understanding of microbial growth regulation.

Indexed as

Escherichia coliGenome, BacterialCulture MediaEnvironmentGenomicsCulture MediaBacterial growth dynamicsDynamic time warpingGenome-environment interactionMachine learning in biologyTime series data mining

Identifiers

PMID41387544
PMCPMC12816573

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.