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Mungan, M.

Publications and source records attributed to Mungan, M..

3 recordsLinked to original sources

Biphasic adaptive evolution of antimicrobial resistance

The evolutionary adaptation of an organism to a stressful environment often comes at the cost of reduced fitness. For example, resistance to antimicrobial drugs frequently reduces growth rate in the drug-free environment. This cost can be compensated without loss in resistance by mutations at secondary sites when the organism evolves again in the stress-free environment. Here we analytically and numerically study evolution on a simple model fitness landscape to show that compensatory evolution can occur even in the presence of the stress and without the need for mutations at secondary sites. Fitness in the model depends on two phenotypes - the null-fitness defined as the fitness in the absence of stress, and the resistance level to the stress. Mutations universally exhibit antagonistic pleiotropy between the two phenotypes, that is they increase resistance while decreasing the null-fitness. Initial adaptation in this model occurs in a smooth region of the landscape with a rapid accumulation of stress resistance mutations and a concurrent decrease in the null-fitness. This is followed by a second, slower phase exhibiting partial recovery of the null-fitness. The second phase occurs on the rugged part of the landscape and involves the exchange of high-cost resistance mutations for low-cost ones. This process, which we call exchange compensation, is the result of changing epistatic interactions in the genotype as evolution progresses. The model provides general lessons about the tempo and mode of evolution under universal antagonistic pleiotropy with specific implications for drug resistance evolution.

evolutionary biology↗

Collective β-lactam resistance in Escherichia coli due to β-lactamase release upon cell death

Collective antibiotic resistance occurs when populations of bacteria survive antibiotic treatments that are lethal to individual bacteria, which affects the efficacy of drug therapies. An important mechanism of collective resistance against widely used {beta}-lactams is the production of drug-degrading {beta}-lactamases. Here, we integrate experiments with mathematical modeling to understand the collective survival of Escherichia coli challenged with cefotaxime. At near-lethal cefotaxime concentrations, we observe complex dynamics, involving initial biomass growth due to filamentation, followed by death, and subsequently growth recovery. We show that production of AmpC, a chromosomal {beta}-lactamase, is responsible for cefotaxime degradation, allowing the resumption of cell division in surviving filaments. The detoxification of the environment proceeds through CTX hydrolysis by AmpC in the periplasm of intact cells, as well as extracellularly after cell lysis. Our model predicts the recovery time from molecular parameters, and quantifies the relative roles of periplasmic and extracellular degradation for two strains of E. coli that differ in the degree of privatization of AmpC hydrolysis. Our findings suggest that {beta}-lactam survival of bacterial infections depends on a combination of intra- and extracellular {beta}-lactamase activity, which will likely vary among isolates.

microbiology↗

A Driven Disordered Systems Approach to Biological Evolution in Changing Environments

Biological evolution of a population is governed by the fitness landscape, which is a map from genotype to fitness. However, a fitness landscape depends on the organisms environment, and evolution in changing environments is still poorly understood. We study a particular model of antibiotic resistance evolution in bacteria where the antibiotic concentration is an environmental parameter and the fitness landscapes incorporate tradeoffs between adaptation to low and high antibiotic concentration. With evolutionary dynamics that follow fitness gradients, the evolution of the system under slowly changing antibiotic concentration resembles the athermal dynamics of disordered physical systems under quasistatic external drives. Specifically, our model can be described as a system with interacting hysteretic elements, and it exhibits effects such as hysteresis loops and memory formation under antibiotic concentration cycling. Using methods familiar from studies in this field, we derive a number of analytical and numerical results. Our approach provides a general framework for studying motifs of evolutionary dynamics in biological systems in a changing environment.

evolutionary biology↗