Nonlinear Fitness Landscape of a Molecular Pathway

Genes are regulated because their expression involves a fitness cost to the organism. The production of proteins by transcription and translation is a well-known cost factor, but the enzymatic activity of the proteins produced can also reduce fitness, depending on the internal state and the environment of the cell. Here, we map the fitness costs of a key metabolic network, the lactose utilization pathway in Escherichia coli. We measure the growth of several regulatory lac operon mutants in different environments inducing expression of the lac genes. We find a strikingly nonlinear fitness landscape, which depends on the production rate and on the activity rate of the lac proteins. A simple fitness model of the lac pathway, based on elementary biophysical processes, predicts the growth rate of all observed strains. The nonlinearity of fitness is explained by a feedback loop: production and activity of the lac proteins reduce growth, but growth also affects the density of these molecules. This nonlinearity has important consequences for molecular function and evolution. It generates a cliff in the fitness landscape, beyond which populations cannot maintain growth. In viable populations, there is an expression barrier of the lac genes, which cannot be exceeded in any stationary growth process. Furthermore, the nonlinearity determines how the fitness of operon mutants depends on the inducer environment. We argue that fitness nonlinearities, expression barriers, and gene–environment interactions are generic features of fitness landscapes for metabolic pathways, and we discuss their implications for the evolution of regulation

Rate and effects of spontaneous mutations that affect fitness in mutator Escherichia coli

Knowledge of the mutational parameters that affect the evolution of organisms is of key importance in understanding the evolution of several characteristics of many natural populations, including recombination and mutation rates. In this study, we estimated the rate and mean effect of spontaneous mutations that affect fitness in a mutator strain of Escherichia coli and review some of the estimation methods associated with mutation accumulation (MA) experiments. We performed an MA experiment where we followed the evolution of 50 independent mutator lines that were subjected to repeated bottlenecks of a single individual for approximately 1150 generations. From the decline in mean fitness and the increase in variance between lines, we estimated a minimum mutation rate to deleterious mutations of 0.005 (±0.001 with 95% confidence) and a maximum mean fitness effect per deleterious mutation of 0.03 (±0.01 with 95% confidence). We also show that any beneficial mutations that occur during the MA experiment have a small effect on the estimate of the rate and effect of deleterious mutations, unless their rate is extremely large. Extrapolating our results to the wild-type mutation rate, we find that our estimate of the mutational effects is slightly larger and the inferred deleterious mutation rate slightly lower than previous estimates obtained for non-mutator E. coli