A novel method to simultaneously estimate bacterial respiration and growth from oxygen dynamics.

Bacterial growth and respiration are fundamental metabolic processes that drive energy transformation and allocation within organisms and impact carbon sequestration at the ecosystem scale. However, these traits are usually measured independently; bacterial growth is quantified with endpoint biomass measurements, while respiration is determined by monitoring oxygen or carbon dioxide. Because the two physiological traits are collected at different temporal and volumetric scales (hours-to-days for growth versus minutes-to-hours for respiration), reconciling them is challenging and often introduces scale-mismatch bias, obscuring causal links between metabolism and environmental drivers. In this study, we develop a novel method for quantifying the rates of bacterial growth and respiration from a single dissolved-oxygen time series. Our approach introduces a model that couples exponential biomass growth with biomass-specific respiration, enabling simultaneous inference of growth rate and respiration rate from each oxygen trajectory. We applied our high-throughput method to 15 bacterial taxa isolated from natural environments. Our approach yielded growth estimates in close agreement with measurements based on popular methods using optical density or flow cytometry ([Formula: see text] > 0.9) with no evidence of taxon-specific bias. We also tested our approach in quantifying the effects of temperature on respiration, growth, and carbon use-efficiency in