Abstract
Developing mathematical models to accurately predict microbial growth dynamics remains a key challenge in ecology, evolution, biotechnology, and public health. To reproduce and grow, microbes need to take up essential nutrients from the environment, and mathematical models classically assume that the nutrient uptake rate is a saturating function of the nutrient concentration. In nature, microbes experience different levels of nutrient availability at all environmental scales, yet parameters shaping the nutrient uptake function are commonly estimated for a single initial nutrient concentration. This hampers the models from accurately capturing microbial dynamics when the environmental conditions change. To address this problem, we conduct growth experiments for a range of micro-organisms, including human fungal pathogens, baker’s yeast, and common coliform bacteria, and uncover the following patterns. We observed that the maximal nutrient uptake rate and biomass yield were both decreasing functions of initial nutrient concentration. While a functional form for the relationship between biomass yield and initial nutrient concentration has been previously derived from first metabolic principles, here we also derive the form of the relationship between maximal nutrient uptake rate and initial nutrient concentration. Incorporating these two functions into a model of microbial growth allows for variable growth parameters and enables us to substantially improve predictions for microbial dynamics in a range of initial nutrient concentrations, compared to keeping growth parameters fixed.
Highlights
Microbial communities shape the biogeochemistry of the planet [1, 2], the functioning of the ecosystem [3, 4], and the health of macro-organisms [5, 6]
Our ability to predict microbial population dynamics is of key importance for the fields of ecology, evolution, biotechnology, and public health
Understanding and predicting microbial population dynamics is a key challenge for the fields of ecology, evolution, public health, and biotechnology
Summary
Microbial communities shape the biogeochemistry of the planet [1, 2], the functioning of the ecosystem [3, 4], and the health of macro-organisms [5, 6]. Ecological models aimed at predicting microbial population densities and frequencies within a community, often treat metabolism as a black box [8, 22, 23], while others incorporate an intermediate level of metabolic detail [13, 24, 25] Regardless of their metabolic complexity, mathematical models generally assume that nutrient uptake is a saturating function of nutrient concentration. The parameters shaping such a function can subsequently be estimated by fitting a numerical solution of the mathematical model describing microbial population growth and/or nutrient uptake over time to empirically obtained data, typically for a selected initial nutrient concentration This does not accurately reflect reality as in nature microbes regularly face changes in nutrient availability at all environmental scales [26]. Bacteria are known to experience changes in the ambient nutrient abundance, where periods of nutrient excess are followed by periods of its scarcity [30], or changes in the nutrient type [31]
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