Reconstructing the genotype-to-fitness map for the bacterial chemotaxis network and its emergent behavioural phenotypes.
The signal-transduction network responsible for chemotaxis in Escherichia coli has been characterised in extraordinary detail. Yet, relatively little is known about eco-evolutionary aspects of chemotaxis, such as how the network has been shaped by selection and to what extent natural populations may fine-tune their chemotactic behaviour to the ecological conditions. To address these questions, we here develop an evolutionary-systems-biology model of the chemotaxis network of E. coli, which we apply to estimate the resource accumulation rate (here used as a proxy for fitness) of wildtype and a large number of potential mutant genotypes. Mutant genotypes differ from the wildtype in the concentrations of one or more constituent proteins of the chemotaxis signalling network or in one or more of its kinetic parameters. To guarantee model consistency across the genotype space, we explicitly incorporated biochemical constraints that underly observed phenotypic trade-offs. The model was validated by reconstructing the phenotypic properties of several known mutant genotypes. We also characterised differences in the fitness distribution between genotypes, and reconstructed adaptive walks in genotype space for populations exposed to different environmental conditions. We found that the local fitness landscape is rugged, due to non-additive interactions between mutations. When selection has a consistent direction, just a few adaptive mutations are required to reach a local peak, and different local peaks can be reached by adaptive walks starting from the same initial genotype. However, when the direction of selection is fluctuating, evolutionary paths are much longer and genotype space is explored further. Longer adaptive walks were also observed when evolution was started from a low-fitness genotype such as a CheZ knockout mutant. In line with empirical observations, the initial ΔcheZ mutant did not respond to a step-down stimulus, but a dynamic response similar to the wildtype was recovered following the fixation of compensatory mutations.
Groningen Institute for Evolutionary Life Sciences, University of Groningen, 9700 CC Groningen, The Netherlands. Electronic address: j.a.nakauma.gonzalez@rug.nl.
Alberto
A
Nakauma
Groningen Institute for Evolutionary Life Sciences, University of Groningen, 9700 CC Groningen, The Netherlands.
G Sander
GS
van Doorn
D000222:Adaptation, Physiological / Q000235:genetics; D002633:Chemotaxis / Q000235:genetics; D004926:Escherichia coli / Q000235:genetics*; D005838:Genotype; D000072236:Methyl-Accepting Chemotaxis Proteins / Q000235:genetics; D008957:Models, Genetic; D009154:Mutation; D010641:Phenotype; D060066:Protein Interaction Maps / Q000235:genetics; D012641:Selection, Genetic; D049490:Systems Biology / Q000379:methods*
D000072236:Methyl-Accepting Chemotaxis Proteins; C000607605:cheZ protein, E coli
Compensatory mutations; Complex traits; Evolutionary systems biology; Fitness landscape; Network evolution