Biological Sciences

Events and seminars

EngBio Seminar - A general theoretical framework to study holistic models of growing cells

Hugo Dourado (Heinrich Heine University, Dusseldorf)

14th March 2024 at 9:30am [Download iCalendar / .ics file]

C.H Waddington Building, Seminar room 1.08

Mathematical models are an important tool for understanding and predicting the complex behavior of biological cells. For unicellular organisms, this behavior is driven by natural selection through fitness maximization under nonlinear physical constraints that cannot be fully captured in most current modeling frameworks, which rely on simplified linear optimizations and phenomenological assumptions about cell biomass composition. Importantly, the critical trade-off between cell resource investments in reactants and catalysts of biochemical reactions can only be fully captured by models that incorporate nonlinear kinetic rate laws. When these kinetic models also account for the necessary production of proteins to catalyze their biochemical reactions, the limited cell density, and the dilution of all components by growth, they become holistic models capable of explaining the entire cell composition and behavior as a result of a nonlinear optimization problem. While this problem cannot be solved efficiently numerically for large models with thousands of reactions, we present here an alternative analytical approach to study holistic cell models of any size, leading to fundamental quantitative principles relevant to all cells at steady state growth. These analytical principles can be used as tools to independently predict the composition and behavior of cellular subsystems. We show how these predictions are in good agreement with experimental measurements of E. coli enzyme and metabolite composition at steady state growth, and ribosome allocation at different steady state growth rates for both E. coli and S. cerevisiae. We also present our recent result on the necessary analytical conditions for optimal dynamic allocation of cell resources in changing environments, and show how it predicts the same qualitative behavior observed experimentally for ribosome allocation and specific growth rate in E. coli.More information: Centre for Engineering Biology

Host Andrea Weisse (SBS/Informatics)

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