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Precise, High-throughput Analysis of Bacterial Growth
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Genomic traits associated with copiotrophy decouple from maximum growth rate predictions along temperature gradients.

J L Weissman1,2, Alexandra Walling1,2, Hugh Ducklow3

  • 1Institute for Advanced Computational Science, Stony Brook University, Stony Brook, NY  11794, United States.

The ISME Journal
|June 9, 2026
PubMed
Summary

Maximum growth rate is not always indicative of microbial growth optimization. Temperature confounds genomic studies, suggesting growth optimization may be more ecologically relevant than maximum growth rate itself.

Keywords:
CopiotrophyGenomicsMaximum Growth RateMicrobial GrowthOptimal Growth Temperature

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Area of Science:

  • Microbial Ecology
  • Genomics
  • Biogeochemistry

Background:

  • Maximum growth rate is a common metric for microbial functional variation, estimated using genomic and metagenomic data.
  • Temperature influences reaction kinetics and can confound studies linking genomic signatures of growth optimization to environmental conditions.
  • Microbial growth optimization does not always correlate with rapid growth, especially across environmental temperature gradients.

Purpose of the Study:

  • To investigate the confounding effect of temperature on the relationship between genomic indicators of microbial growth optimization and maximum growth rate.
  • To determine if genomic signatures of growth optimization are better predictors of microbial ecological roles and functional content than growth rates.
  • To propose a revised definition of copiotrophy.

Main Methods:

  • Analysis of genomic and metagenomic data to estimate microbial growth optimization.
  • Comparison of growth optimization signals across diverse environmental temperatures, particularly oceanic gradients.
  • Statistical analysis to identify relationships between growth optimization, optimal growth temperature, and maximum growth rate.

Main Results:

  • A negative relationship was observed between genomic growth optimization and optimal growth temperature across environments.
  • Genomic signatures of growth optimization were decoupled from maximum growth rate, especially along temperature gradients.
  • Genomic growth optimization signals proved to be better predictors of microbial ecological roles and functional genomic content than growth rates.

Conclusions:

  • Temperature acts as a significant confounder in studies of microbial growth optimization, potentially decoupling it from maximum growth rate.
  • Genomic indicators of growth optimization offer a more robust understanding of microbial ecological roles than maximum growth rate alone.
  • Copiotrophy should be redefined as growth exceeding a thermodynamic baseline maximum, rather than relative to a static rate.