ArticlePLoS computational biology2021
Predicting microbial growth dynamics in response to nutrient availability.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Inferring bacterial cell size dynamics across media conditions.Scientific reports · 2026Article
- Solution towards low yield biosurfactant production from bacteria, a novel approach using microalgae-bacteria consortium.Microbial cell factories · 2025Article
- Linking Cell Size, VEnvironmental microbiology reports · 2025Article
- Improved maximum growth rate prediction from microbial genomes by integrating phylogenetic information.Nature communications · 2025Article
- A comparative assesment of biostimulants in microbiome-based ecorestoration of polycyclic aromatic hydrocarbon polluted soil.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2025Article
- Lactose-assimilating yeasts with high fatty acid accumulation uncovered by untargeted bioprospecting.Applied and environmental microbiology · 2025Article
- Competition for resources can reshape the evolutionary properties of spatial structure.PLoS computational biology · 2024Article
- Bacterial cell size modulation along the growth curve across nutrient conditions.bioRxiv : the preprint server for biology · 2024Article
- Autoencoder neural networks enable low dimensional structure analyses of microbial growth dynamics.Nature communications · 2023Article
- Metabolic efficiency reshapes the seminal relationship between pathogen growth rate and virulence.Ecology letters · 2023Article
- Phosphate Solubilizing MicroorganismBiology · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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