Predicting microbial growth dynamics in response to nutrient availability

PLoS Comput Biol. 2021 Mar 18;17(3):e1008817. doi: 10.1371/journal.pcbi.1008817. eCollection 2021 Mar.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biotechnology
  • Candida* / cytology
  • Candida* / growth & development
  • Candida* / physiology
  • Cell Proliferation / physiology
  • Computational Biology
  • Ecology
  • Enterobacteriaceae* / cytology
  • Enterobacteriaceae* / growth & development
  • Enterobacteriaceae* / physiology
  • Models, Biological*
  • Saccharomyces cerevisiae* / cytology
  • Saccharomyces cerevisiae* / growth & development
  • Saccharomyces cerevisiae* / physiology

Grants and funding

OAN, AJ, LB and IG were funded by an ERC Consolidator grant (MathModExp 647292) to IG, RJL was funded by a Leverhulme grant (RPG-2019-238) to IG, REB was funded by an EPSRC Healthcare Technology Impact Fellowship (EP/N033671/1) The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.