Evolution of enzyme levels in metabolic pathways: A theoretical approach. Part 1. (7th April 2022)

• Record Type: Journal Article
• Authors: Coton, Charlotte; Talbot, Grégoire; Le Louarn, Maud; Dillmann, Christine; de Vienne, Dominique
• Is Part Of: Journal of theoretical biology. Volume 538(2022)
• Publication Date: 2022-04-07
• Subjects: Adaptive landscape -- Enzyme concentration -- Co-regulation -- Evolutionary equilibrium -- Selective neutrality; Biology -- Periodicals; Biological Science Disciplines -- Periodicals; Biology -- Periodicals; Biologie -- Périodiques; Theoretische biologie; Biology; Periodicals; 571.05
• DOI: 10.1016/j.jtbi.2022.111015
• Languages: English
• ISSNs: 0022-5193

Abstract

Highlights: Modeling evolution of enzyme concentrations under selection for increased flux. Competition for cell resources and/or co-regulations shape the adaptive landscape. Evolutionary equilibria and ranges of neutral variation depend on the constraints. The equilibria depend on the initial concentrations when there is co-regulation. Abstract: The central role of metabolism in cell functioning and adaptation has given rise to countless studies on the evolution of enzyme-coding genes and network topology. However, very few studies have addressed the question of how enzyme concentrations change in response to positive selective pressure on the flux, considered a proxy of fitness. In particular, the way cellular constraints, such as resource limitations and co-regulation, affect the adaptive landscape of a pathway under selection has never been analyzed theoretically. To fill this gap, we developed a model of the evolution of enzyme concentrations that combines metabolic control theory and an adaptive dynamics approach, and integrates possible dependencies between enzyme concentrations. We determined the evolutionary equilibria of enzyme concentrations and their range of neutral variation, and showed that they differ with the properties of the enzymes, the constraints applied to the system and the initial enzyme concentrations. Simulations of long-term evolution confirmed all analytical and numerical predictions, even though we relaxed the simplifying assumptions used in the analytical treatment.