Pareto Suboptimal Resource Allocation and Microbial Growth
Abstract
Microbial growth has often been analyzed under the assumption that microorganisms have evolved to optimize phenotypic characteristics of interest, such as growth rate and growth yield. This assumption has been useful, for example, for the genome-scale modeling of metabolism and the study of the allocation of cellular resources to physiological processes. In many experimental situations of interest, however, microorganisms are found to be suboptimal with respect to phenotypic characteristics that are thought to be favorable in that situation. Whereas a strong theoretical framework exists to mathematically relate cellular resource allocation strategies to Pareto optimality of microbial growth and other biological processes, much less is known about the consequences of Pareto suboptimality. We extend the framework to the latter case and show that a given Pareto suboptimal phenotype can be explained by a range of underlying resource allocation strategies, each corresponding to a different growth physiology and biomass composition. We test the predictions with the help of a coarse-grained model of microbial growth and published experimental data, which relate Pareto suboptimal rate-yield phenotypes of Escherichia coli and the microalga Tisochrysis lutea to the macromolecular composition of the cells (storage metabolite and total protein contents). Changing the focus from Pareto optimality to suboptimality provides interesting leads to exploring the diversity of growth strategies that can support a given phenotype. This change of perspective is of practical interest, because some of the growth physiologies within this range may be important for biotechnological applications. Author summary Many methods for the analysis of metabolism and growth are based on the assumption that, under the pressure of natural selection, microorganisms have evolved towards phenotypes that are optimal with respect to ecologically important characteristics. In mathematical terms, this assumption can be formulated as Pareto optimality of microbial growth and related to underlying resource allocation strategies that shape cellular physiology. Based on the observation that this assumption is often not satisfied in practice, we investigate the consequences of adopting the opposite assumption, namely that microbial growth and cellular resource allocation are suboptimal. We extend an existing mathematical framework to the case of Pareto suboptimality, which allows us to make predictions on the diversity of the macromolecular composition of microbial cells. These predictions are shown to correspond with experimental data on growth rate, growth yield, and macromolecular composition of the model bacterium Escherichia coli and the microalga Tisochrysis lutea . Our results thus associate suboptimality with observed metabolic diversity in microorganisms.
Related
- RBApy: Extending resource allocation modeling to eukaryotes in complex environments
- Effects of plant density and nitrogen fertilization on purple basil growth, biomass allocation, and organ-specific essential oil content and yield
- Resource Availability Shaped the Female‐Biased Floral Sex Allocation With Plant Size in Andromonoecious Capparis spinosa in Desert
- Increased nutrient diversity can induce loss of microbial diversity through enhanced resource uptake
- Dynamic allocation of MurJ coordinates bacterial growth and division
BibTeX
@misc{baldazzi2026pareto,
title = {{Pareto Suboptimal Resource Allocation and Microbial Growth}},
author = {Valentina Baldazzi and Francis Mairet and Tomas Gedeon and Hidde de Jong},
howpublished = {HAL},
year = {2026},
month = sep,
doi = {10.64898/2026.09.08.749853},
url = {https://hal.inrae.fr/hal-05761385v1},
note = {CC BY-ND 4.0},
}
RIS
TY - UNPB
TI - Pareto Suboptimal Resource Allocation and Microbial Growth
AU - Valentina Baldazzi
AU - Francis Mairet
AU - Tomas Gedeon
AU - Hidde de Jong
PY - 2026
DA - 2026/09/07
PB - HAL
DO - 10.64898/2026.09.08.749853
UR - https://hal.inrae.fr/hal-05761385v1
AB - Microbial growth has often been analyzed under the assumption that microorganisms have evolved to optimize phenotypic characteristics of interest, such as growth rate and growth yield. This assumption has been useful, for example, for the genome-scale modeling of metabolism and the study of the allocation of cellular resources to physiological processes. In many experimental situations of interest, however, microorganisms are found to be suboptimal with respect to phenotypic characteristics that are thought to be favorable in that situation. Whereas a strong theoretical framework exists to mathematically relate cellular resource allocation strategies to Pareto optimality of microbial growth and other biological processes, much less is known about the consequences of Pareto suboptimality. We extend the framework to the latter case and show that a given Pareto suboptimal phenotype can be explained by a range of underlying resource allocation strategies, each corresponding to a different growth physiology and biomass composition. We test the predictions with the help of a coarse-grained model of microbial growth and published experimental data, which relate Pareto suboptimal rate-yield phenotypes of Escherichia coli and the microalga Tisochrysis lutea to the macromolecular composition of the cells (storage metabolite and total protein contents). Changing the focus from Pareto optimality to suboptimality provides interesting leads to exploring the diversity of growth strategies that can support a given phenotype. This change of perspective is of practical interest, because some of the growth physiologies within this range may be important for biotechnological applications. Author summary Many methods for the analysis of metabolism and growth are based on the assumption that, under the pressure of natural selection, microorganisms have evolved towards phenotypes that are optimal with respect to ecologically important characteristics. In mathematical terms, this assumption can be formulated as Pareto optimality of microbial growth and related to underlying resource allocation strategies that shape cellular physiology. Based on the observation that this assumption is often not satisfied in practice, we investigate the consequences of adopting the opposite assumption, namely that microbial growth and cellular resource allocation are suboptimal. We extend an existing mathematical framework to the case of Pareto suboptimality, which allows us to make predictions on the diversity of the macromolecular composition of microbial cells. These predictions are shown to correspond with experimental data on growth rate, growth yield, and macromolecular composition of the model bacterium Escherichia coli and the microalga Tisochrysis lutea . Our results thus associate suboptimality with observed metabolic diversity in microorganisms.
ER -