Substrate geometry affects population dynamics in a bacterial biofilm.

Biofilms inhabit a range of environments, such as dental plaques or soil micropores, often characterized by noneven surfaces. However, the impact of surface irregularities on the population dynamics of biofilms remains elusive, as most experiments are conducted on flat surfaces. Here, we show that the shape of the surface on which a biofilm grows influences genetic drift and selection within the biofilm. We culture Escherichia coli biofilms in microwells with a corrugated bottom surface and observe the emergence of clonal sectors whose size corresponds to that of the corrugations, despite no physical barrier separating different areas of the biofilm. The sectors are remarkably stable and do not invade each other; we attribute this stability to the characteristics of the velocity field within the biofilm, which hinders mixing and clonal expansion. A microscopically detailed computer model fully reproduces these findings and highlights the role of mechanical interactions such as adhesion and friction in microbial evolution. The model also predicts clonal expansion to be limited even for clones with a significant growth advantage-a finding which we confirm experimentally using a mixture of antibiotic-sensitive and antibiotic-resistant mutants in the presence of sublethal concentrations of the antibiotic rifampicin. The strong suppression of selection contrasts sharply with the behavior seen in range expansion experiments in bacterial colonies grown on agar. Our results show that biofilm population dynamics can be affected by patterning the surface and demonstrate how a better understanding of the physics of bacterial growth can be used to control microbial evolution.

Phenotypic delay in the evolution of bacterial antibiotic resistance: Mechanistic models and their implications.

Phenotypic delay-the time delay between genetic mutation and expression of the corresponding phenotype-is generally neglected in evolutionary models, yet recent work suggests that it may be more common than previously assumed. Here, we use computer simulations and theory to investigate the significance of phenotypic delay for the evolution of bacterial resistance to antibiotics. We consider three mechanisms which could potentially cause phenotypic delay: effective polyploidy, dilution of antibiotic-sensitive molecules and accumulation of resistance-enhancing molecules. We find that the accumulation of resistant molecules is relevant only within a narrow parameter range, but both the dilution of sensitive molecules and effective polyploidy can cause phenotypic delay over a wide range of parameters. We further investigate whether these mechanisms could affect population survival under drug treatment and thereby explain observed discrepancies in mutation rates estimated by Luria-Delbrück fluctuation tests. While the effective polyploidy mechanism does not affect population survival, the dilution of sensitive molecules leads both to decreased probability of survival under drug treatment and underestimation of mutation rates in fluctuation tests. The dilution mechanism also changes the shape of the Luria-Delbrück distribution of mutant numbers, and we show that this modified distribution provides an improved fit to previously published experimental data.

A Roadblock-and-Kill Mechanism of Action Model for the DNA-Targeting Antibiotic Ciprofloxacin.

Fluoroquinolones, antibiotics that cause DNA damage by inhibiting DNA topoisomerases, are clinically important, but their mechanism of action is not yet fully understood. In particular, the dynamical response of bacterial cells to fluoroquinolone exposure has hardly been investigated, although the SOS response, triggered by DNA damage, is often thought to play a key role. Here, we investigated the growth inhibition of the bacterium Escherichia coli by the fluoroquinolone ciprofloxacin at low concentrations. We measured the long-term and short-term dynamical response of the growth rate and DNA production rate to ciprofloxacin at both the population and single-cell levels. We show that, despite the molecular complexity of DNA metabolism, a simple roadblock-and-kill model focusing on replication fork blockage and DNA damage by ciprofloxacin-poisoned DNA topoisomerase II (gyrase) quantitatively reproduces long-term growth rates in the presence of ciprofloxacin. The model also predicts dynamical changes in the DNA production rate in wild-type E. coli and in a recombination-deficient mutant following a step-up of ciprofloxacin. Our work highlights that bacterial cells show a delayed growth rate response following fluoroquinolone exposure. Most importantly, our model explains why the response is delayed: it takes many doubling times to fragment the DNA sufficiently to inhibit gene expression. We also show that the dynamical response is controlled by the timescale of DNA replication and gyrase binding/unbinding to the DNA rather than by the SOS response, challenging the accepted view. Our work highlights the importance of including detailed biophysical processes in biochemical-systems models to quantitatively predict the bacterial response to antibiotics.

Substrate cross-feeding affects the speed and trajectory of molecular evolution within a synthetic microbial assemblage.

BACKGROUND: Substrate cross-feeding occurs when one organism partially consumes a primary substrate into one or more metabolites while other organisms then consume the metabolites. While pervasive within microbial communities, our knowledge about the effects of substrate cross-feeding on microbial evolution remains limited. To address this knowledge gap, we experimentally evolved isogenic nitrite (NO2-) cross-feeding microbial strains together for 700 generations, identified genetic changes that were acquired over the evolution experiment, and compared the results with an isogenic completely denitrifying strain that was evolved alone for 700 generations. We further investigated how the magnitude of interdependence between the nitrite cross-feeding strains affects the main outcomes. Our main objective was to quantify how substrate cross-feeding and the magnitude of interdependence affect the speed and trajectory of molecular evolution. RESULTS: We found that each nitrite (NO2-) cross-feeding strain acquired fewer genetic changes than did the completely denitrifying strain. In contrast, pairs of nitrite cross-feeding strains together acquired more genetic changes than did the completely denitrifying strain. Moreover, nitrite cross-feeding promoted population diversification, as pairs of nitrite cross-feeding strains acquired a more varied set of genetic changes than did the completely denitrifying strain. These outcomes likely occurred because nitrite cross-feeding enabled the co-existence of two distinct microbial strains, thus increasing the amount of genetic variation for selection to act upon. Finally, the nitrite cross-feeding strains acquired different types of genetic changes than did the completely denitrifying strain, indicating that nitrite cross-feeding modulates the trajectory of molecular evolution. CONCLUSIONS: Our results demonstrate that substrate cross-feeding can affect both the speed and trajectory of molecular evolution within microbial populations. Substrate cross-feeding can therefore have potentially important effects on the life histories of microorganisms.

Metabolite toxicity determines the pace of molecular evolution within microbial populations.

BACKGROUND: The production of toxic metabolites has shaped the spatial and temporal arrangement of metabolic processes within microbial cells. While diverse solutions to mitigate metabolite toxicity have evolved, less is known about how evolution itself is affected by metabolite toxicity. We hypothesized that the pace of molecular evolution should increase as metabolite toxicity increases. At least two mechanisms could cause this. First, metabolite toxicity could increase the mutation rate. Second, metabolite toxicity could increase the number of available mutations with large beneficial effects that selection could act upon (e.g., mutations that provide tolerance to toxicity), which consequently would increase the rate at which those mutations increase in frequency. RESULTS: We tested this hypothesis by experimentally evolving the bacterium Pseudomonas stutzeri under denitrifying conditions. The metabolite nitrite accumulates during denitrification and has pH-dependent toxic effects, which allowed us to evolve P. stutzeri at different magnitudes of nitrite toxicity. We demonstrate that increased nitrite toxicity results in an increased pace of molecular evolution. We further demonstrate that this increase is generally due to an increased number of available mutations with large beneficial effects and not to an increased mutation rate. CONCLUSIONS: Our results demonstrate that the production of toxic metabolites can have important impacts on the evolutionary processes of microbial cells. Given the ubiquity of toxic metabolites, they could also have implications for understanding the evolutionary histories of biological organisms.

Segregating metabolic processes into different microbial cells accelerates the consumption of inhibitory substrates.

Different microbial cell types typically specialize at performing different metabolic processes. A canonical example is substrate cross-feeding, where one cell type consumes a primary substrate into an intermediate and another cell type consumes the intermediate. While substrate cross-feeding is widely observed, its consequences on ecosystem processes is often unclear. How does substrate cross-feeding affect the rate or extent of substrate consumption? We hypothesized that substrate cross-feeding eliminates competition between different enzymes and reduces the accumulation of growth-inhibiting intermediates, thus accelerating substrate consumption. We tested this hypothesis using isogenic mutants of the bacterium Pseudomonas stutzeri that either completely consume nitrate to dinitrogen gas or cross-feed the intermediate nitrite. We demonstrate that nitrite cross-feeding eliminates inter-enzyme competition and, in turn, reduces nitrite accumulation. We further demonstrate that nitrite cross-feeding accelerates substrate consumption, but only when nitrite has growth-inhibiting effects. Knowledge about inter-enzyme competition and the inhibitory effects of intermediates could therefore be important for deciding how to best segregate different metabolic processes into different microbial cell types to optimize a desired biotransformation.

Metabolic specialization and the assembly of microbial communities.

Metabolic specialization is a general biological principle that shapes the assembly of microbial communities. Individual cell types rarely metabolize a wide range of substrates within their environment. Instead, different cell types often specialize at metabolizing only subsets of the available substrates. What is the advantage of metabolizing subsets of the available substrates rather than all of them? In this perspective piece, we argue that biochemical conflicts between different metabolic processes can promote metabolic specialization and that a better understanding of these conflicts is therefore important for revealing the general principles and rules that govern the assembly of microbial communities. We first discuss three types of biochemical conflicts that could promote metabolic specialization. Next, we demonstrate how knowledge about the consequences of biochemical conflicts can be used to predict whether different metabolic processes are likely to be performed by the same cell type or by different cell types. We then discuss the major challenges in identifying and assessing biochemical conflicts between different metabolic processes and propose several approaches for their measurement. Finally, we argue that a deeper understanding of the biochemical causes of metabolic specialization could serve as a foundation for the field of synthetic ecology, where the objective would be to rationally engineer the assembly of a microbial community to perform a desired biotransformation.