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Positive relationship between substrate-induced respiration rate and translationally active bacterial counts in soil

  • Nina Rose Camillone
  • , Mary Ann Victoria Bruns
  • , Raúl Román
  • , Daniel Wasner
  • , Estelle Couradeau

Research output: Contribution to journalArticlepeer-review

Abstract

Soil microorganisms perform biogeochemical processes fundamental to soil functions. Bulk respiration, or microbial metabolic emission of CO2, is the classic indicator of soil biological activity. However, among the millions of microbes per gram of soil, only 0.1%–2.0% are metabolically active at any given time. Understanding the relationship between bulk soil respiration and microbial activity is complicated by microbes potentially awakening from quiescent states during incubation test periods. Here, we investigated this relationship through parallel measurements of substrate-induced respiration and translationally active cell counts using bioorthogonal non-canonical amino acid tagging (BONCAT). After a 6-h incubation of agricultural soil with glucose, galactose, or only water, active cell counts were positively correlated with respiration rates. As hypothesized, active cell numbers increased rapidly compared to total cell numbers after a 6-h incubation with glucose, suggesting newly activated cells. Additionally, carbon-amended soils respired more than water-only soils with similar active cell counts. This suggested that cells in carbon-rich environments were turning over freshly added carbon faster or metabolizing it less efficiently than those exposed to native substrates only. This study distinguishes for the first time microbial activation in the soil matrix using a translation signal, providing evidence that respiration rates reflect active cell numbers and varied metabolic responses, decoupled from cell growth upon soil wetting and carbon addition. We propose BONCAT as a useful tool to gain mechanistic insights into microbial activation and recommend combining it with tracking substrate incorporation and phylogenetics.

Original languageEnglish (US)
Pages (from-to)1-15
Number of pages15
JournalmSystems
Volume11
Issue number2
DOIs
StatePublished - Feb 17 2026

All Science Journal Classification (ASJC) codes

  • Microbiology
  • Ecology, Evolution, Behavior and Systematics
  • Physiology
  • Biochemistry
  • Modeling and Simulation
  • Molecular Biology
  • Genetics
  • Computer Science Applications

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