Optimality principles of cellular resource allocation: enzyme/substrate relationship and growth laws

Hugo Dourado (Heinrich-Heine-Universität Düsseldorf)

28-Apr-2022, 15:30-16:00 (24 months ago)

Abstract: Much recent progress has been made to understand the impact of proteome allocation on bacterial growth; much less is known about the relationship between the abundances of the enzymes and their substrates, which jointly determine metabolic fluxes. Here, we suggest an optimal relationship between the concentrations of enzymes and their substrates as a consequence of the optimal biomass allocation: for a cellular reaction network composed of effectively irreversible reactions, maximal reaction flux is achieved when the dry mass allocated to each substrate is equal to the dry mass of the unsaturated (or “free”) enzymes waiting to consume it. Calculations based on this optimality principle successfully predict the quantitative relationship between the observed enzyme and metabolite abundances in E. coli, parameterized only by dissociation constants ($K_m$). This optimal relationship is also shown to explain the emergence of linear “growth laws” of proteome allocation under carbon limitation; these can be seen as approximations to the optimal enzyme/substrate relationship, including the existence of aparent protein “offsets” at zero growth. The apparent offsets relate directly to the levels of substrate saturation of catalytic proteins, explaining also how the “under-utilization” of enzymes results from a trade-off between biomass allocation to enzymes and to metabolites.

algebraic geometrydynamical systemsprobability

Audience: researchers in the topic

( video )


Seminar on the Mathematics of Reaction Networks

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This seminar series focuses on progress in mathematical theory for the study of reaction networks, mainly in biology and chemistry. The scope is broad and accommodates works arising from dynamical systems, stochastics, algebra, topology and beyond.

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The organizers.

Organizers: Daniele Cappelletti*, Stefan Müller*, Tung Nguyen*, Polly Yu*
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