Growth rate structures the dynamics of bacterial trait evolution

Bacterial species span orders of magnitude in growth rate, yet how its evolution is embedded within the broader evolutionary dynamics of other bacterial traits remains poorly understood.

By Hao, Konno, Zhang +1Oct 23, 2026

Score████░░░░░░4.3

Caveats

Preprint; not yet peer reviewed.

VerdictWorth a reader's time today.

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Abstract

Bacterial species span orders of magnitude in growth rate, yet how its evolution is embedded within the broader evolutionary dynamics of other bacterial traits remains poorly understood. We integrated experimentally measured growth rates for 283 bacterial species with 11 genomic, metabolic, ecological and environmental traits, and used multivariate Ornstein-Uhlenbeck models to characterize how growth rate and associated traits coevolve across evolutionary time. Growth rate was best explained by models assuming distinct slow- and fast-growing evolutionary regimes, and evolved toward adaptive optima more rapidly than any other trait examined over longer evolutionary timescales, both when modelled independently and jointly with other traits. Coevolution between growth rate and associated traits was primarily structured by growth-rate regimes, suggesting growth rate serves as a pacemaker of evolution. At instantaneous timescales, six of the eight traits coevolving with growth rate showed unidirectional coupling, including all four environmental traits, with the direction varying among traits. In contrast, ribosomal RNA operon copy number and GC percentage exhibited reciprocal coupling with growth rate. These findings recast bacterial growth strategy from a correlate of trait variation to a major organizing axis shaping bacterial trait evolution across distinct evolutionary timescales.

C. Hao, N. Konno, Y. Zhang, F. He

The editor's rubric

Heuristic review

Leverage3 / 5: A method or resource many groups across the field will adopt within a year.; 24% of this desk’s rubric
Magnitude3 / 5: Large gain: roughly 2x, or a clear new state of the art on a hard, unsaturated problem.; 16% of this desk’s rubric
Evidence3 / 5: Solid: multiple benchmarks or cohorts, ablations, fair baselines, released code or data.; 20% of this desk’s rubric
Novelty2 / 5: A new combination of known ideas.; 20% of this desk’s rubric
Trajectory3 / 5: A clear path to scale.; 10% of this desk’s rubric
Stakes2 / 5: Benefits a professional community (practitioners, clinicians, engineers).; 10% of this desk’s rubric

Dimension	Level	Weight	What that level means
Leverage	███░░ 3	24%	A method or resource many groups across the field will adopt within a year.
Magnitude	███░░ 3	16%	Large gain: roughly 2x, or a clear new state of the art on a hard, unsaturated problem.
Evidence	███░░ 3	20%	Solid: multiple benchmarks or cohorts, ablations, fair baselines, released code or data.
Novelty	██░░░ 2	20%	A new combination of known ideas.
Trajectory	███░░ 3	10%	A clear path to scale.
Stakes	██░░░ 2	10%	Benefits a professional community (practitioners, clinicians, engineers).

Editor’s rationale

Heuristic triage from title and abstract text only, not a reading of the paper. Cues found: breadth (many tasks); gains (orders of magnitude); verification (multiple benchmarks, independent replication); scale (orders of magnitude).

How the score was computed

rank-2026-10-18

Score████░░░░░░4.3

Score = 10 × (75% × adjusted merit / 10 + 15% × attention + 10% × freshness)

Desks place stronger verdicts first, then use this score to order work within the same verdict.

Merit: 5.4 / 10; Weighted rubric, evidence-gated.
Adjusted merit: 4.6 / 10; Shrunk toward the desk prior by editor confidence (40%).
Attention: 0%; Citations, upvotes, points, mentions.
Freshness: 88%; Half-life decay since publication.

No attention signals recorded yet.

The record

Reviewed by heuristic-v7 on Oct 24, 2026, 05:48 UTC. Paper type: empirical.
Categories: evolutionary biology
BRIEF, No.4 in the Biology edition of October 24, 2026.