The population genetics of alleles affecting enzyme activity

The genotype-phenotype relationship and evolutionary genetics in the light of the Metabolic Control Analysis

Metabolic control analysis has long been used as a systemic model of the genotype-phenotype (GP) relationship. By considering kinetic parameters and enzyme concentrations as reflecting the genotype level and metabolic fluxes or pools as phenotypes related to fitness, MCA has given a biological basis to the relationship between these two levels. The non-linear and concave relationship between enzymes and fluxes can account for common genetic effects that reductionist approaches have been powerless to explain, such as the dominance of active alleles over less active alleles, the various types of epistasis and heterosis, and reveals the structural links between these genetic effects. The summation property of the flux control coefficients accounts for the L-shaped distribution of Quantitative Trait Locus (QTL) effects, irrespective of other possible causes. Metabolic models of response to selection results in evolutionary scenarios that are markedly different from those derived from the classical infinitesimal model of quantitative genetics. In particular, evolution towards selective neutrality appears to be a consequence of the diminishing return of the flux-enzyme relationship. In this paper, we survey the historical and recent achievements of MCA in genetics, quantitative genetics and evolution, focusing on epistasis and the evolution of flux in relation to enzyme concentrations.

An extension to the metabolic control theory taking into account correlations between enzyme concentrations

The classical metabolic control theory [Kacser, H. & Burns, J.A. (1973) Symp. Soc. Exp. Biol.27, 65-104; Heinrich, R. & Rapoport, T. (1974) Eur. J. Biochem.42, 89-95.] does not take into account experimental evidence for correlations between enzyme concentrations in the cell. We investigated the implications of two causes of linear correlations: competition between enzymes, which is a mere physical adaptation of the cell to the limitation of resources and space, and regulatory correlations, which result from the existence of regulatory networks. These correlations generate redistribution of enzyme concentrations when the concentration of an enzyme varies; this may dramatically alter the flux and metabolite concentration curves. In particular, negative correlations cause the flux to have a maximum value for a defined distribution of enzyme concentrations. Redistribution coefficients of enzyme concentrations allowed us to calculate the 'combined response coefficient' that quantifies the response of flux or metabolite concentration to a perturbation of enzyme concentration.

From metabolism to polymorphism in bacterial populations: a theoretical study

Stable polymorphisms are commonly observed in experimental bacterial populations grown in homogeneous media. Evidence is accumulating that metabolic interactions might be the main mechanism underlying the emergence and maintenance of such polymorphisms. To date, however, attempts to model the evolution of bacterial polymorphism have not considered metabolism as a possible component of polymorphism maintenance. Here, we propose a simulation approach to model the evolution of selected polymorphisms in a bacterial population. Using recent knowledge of the relationship between bacterial fitness and metabolism, we build a simple metabolic model and test the effect of resource competition on polymorphism. Without making an a priori hypothesis on fitness functions, we show that stable polymorphic situations could be observed under high nutrient competition, and we propose a functional, metabolism-based explanation to the debated issue of polymorphism maintenance.

Fluxes and metabolic pools as model traits for quantitative genetics. I. The L-shaped distribution of gene effects

The fluxes through metabolic pathways can be considered as model quantitative traits, whose QTL are the polymorphic loci controlling the activity or quantity of the enzymes. Relying on metabolic control theory, we investigated the relationships between the variations of enzyme activity along metabolic pathways and the variations of the flux in a population with biallelic QTL. Two kinds of variations were taken into account, the variation of the average enzyme activity across the loci, and the variation of the activity of each enzyme of the pathway among the individuals of the population. We proposed analytical approximations for the flux mean and variance in the population as well as for the additive and dominance variances of the individual QTL. Monte Carlo simulations based on these approximations showed that an L-shaped distribution of the contributions of individual QTL to the flux variance (R(2)) is consistently expected in an F(2) progeny. This result could partly account for the classically observed L-shaped distribution of QTL effects for quantitative traits. The high correlation we found between R(2) value and flux control coefficients variance suggests that such a distribution is an intrinsic property of metabolic pathways due to the summation property of control coefficients.