Biology subjects

de Visser, A.

Publications and source records attributed to de Visser, A..

3 recordsLinked to original sources

bioRxiv2022

Race to survival during antibiotic breakdown determines the minimal surviving population size

A common strategy used by bacteria to resist antibiotics is enzymatic degradation or modification. Such a collective mechanism also enhances the survival of nearby cells, an effect that increases with the number of bacteria that are present. Collective resistance is of clinical significance, yet a quantitative understanding at the population level is lacking. Here we develop a general theoretical framework of collective resistance under antibiotic degradation. Our modeling reveals that population survival crucially depends on the ratio of timescales of two processes: the rates of population death and antibiotic removal. However, it is insensitive to molecular, biological and kinetic details of the underlying processes that give rise to these timescales. Another important aspect for this race to survival is the degree of cooperativity, which is related to the permeability of the cell wall for antibiotics and enzymes. These observations motivate a coarse-grained, phenomenological model and simple experimental assay to measure the dose-dependent minimal surviving population size. From this model, two dimensionless parameters can be estimated, representing the populations race to survival and single-cell resistance. Our simple model may serve as reference for more complex situations, such as heterogeneous bacterial communities.

microbiology↗

bioRxiv2022

The fitness landscape of TEM-1 β-lactamase is stratified and inverted by sublethal concentrations of cefotaxime

Adaptive evolutionary processes are constrained by the availability of mutations which cause a fitness benefit - a concept that may be illustrated by fitness landscapes which map the relationship of genotype space with fitness. Experimentally derived landscapes have demonstrated a predictability to evolution by identifying limited mutational routes that evolution by natural selection may take between low and high-fitness genotypes. However, such studies often utilise indirect measures to determine fitness. We estimated the competitive fitness of each mutant relative to all of its single-mutation neighbours to describe the fitness landscape of three mutations in a {beta}-lactamase enzyme at sub-lethal concentrations of the antibiotic cefotaxime in a structured and unstructured environment. We found that in the unstructured environment the antibiotic selected for higher-resistance types - but with an equivalent fitness for subsets of mutants, despite substantial variation in resistance - resulting in a stratified fitness landscape. In contrast, in a structured environment with low antibiotic concentration, antibiotic-susceptible genotypes had a relative fitness advantage, which was associated with antibiotic-induced filamentation. These results cast doubt that highly resistant genotypes have a unique selective advantage in environments with sub-inhibitory concentrations of antibiotics, and demonstrate that direct fitness measures are required for meaningful predictions of the accessibility of evolutionary routes. ImportanceThe evolution of antibiotic resistant bacterial populations underpins the ongoing antibiotic-resistance crisis. We aim to understand how antibiotic-degrading enzymes can evolve to cause increased resistance, how this process is constrained and whether it can be predictable. To this end we performed competition experiments with a combinatorially-complete set of mutants of a {beta}-lactamase gene subject to sub-inhibitory concentrations of the antibiotic cefotaxime. While some mutants confer their hosts with high resistance to cefotaxime, in competition these mutants do not always confer a selective advantage. Similarly, we identified conditions involving spatial structure where mutations causing high resistance result in a selective disadvantage. Together, this work suggests that the relationship between resistance level and fitness at sub-inhibitory concentrations is complex; predicting the evolution of antibiotic resistance requires knowledge of the conditions that select for resistant genotypes and the selective advantage evolved types have over their predecessors.

evolutionary biology↗

bioRxiv2021

Stochastic effects on the establishment of mutants resistant to β-lactam antibiotics

For antibiotic resistance to arise, new resistant mutants must establish in a bacterial population before they can spread via natural selection. Comprehending the stochastic factors that influence mutant establishment is crucial for a quantitative understanding of antibiotic resistance emergence. Here, we quantify the single-cell establishment probability of four Escherichia coli strains expressing {beta}-lactamase alleles with different activity against the antibiotic cefotaxime, as a function of antibiotic concentration in both unstructured (liquid) and structured (agar) environments. We show that concentrations well below the minimum inhibitory concentration (MIC) can substantially hamper establishment, particularly for highly resistant mutants. While the pattern of establishment suppression is comparable in both tested environments, we find greater variability in establishment probability on agar. Using a simple branching model, we investigate possible sources of this stochasticity, including environment-dependent lineage variability. Lastly, we use the single-cell establishment probability to predict each strains MIC in the absence of social interactions. We observe substantially higher measured than predicted MIC values, particularly for highly resistant strains, which indicates cooperative effects among resistant cells at large cell numbers, such as in standard MIC assays.

evolutionary biology↗