The Innate Growth Bistability and Fitness Landscapes of Antibiotic-Resistant Bacteria

Introduction Understanding how bacteria harboring antibiotic resistance grow in the presence of antibiotics is critical for predicting the spread and evolution of drug resistance. Because drugs inhibit cell growth and a cell’s growth state globally influences its gene expression, the expression of drug resistance is subject to an innate, growth-mediated feedback, leading to complex behaviors that affect both the characterization and the prevention of antibiotic resistance. We characterized the consequences of this feedback for the growth of antibiotic-resistant bacteria. Fitness landscape and growth bistability. (A) This fitness landscape describes the fitness, or growth rates, of bacterial strains exposed to antibiotics (colored lines indicate the fitness of four example strains). Fitness drops abruptly at high drug concentrations. The shaded area shows a broad region of growth bistability, throughout which we observe that genetically identical cells possessing drug resistance are split into subpopulations of growing and nongrowing cells in response to antibiotics (B, top). Methods We studied the growth of Escherichia coli strains expressing resistance to translation-inhibiting antibiotics, by using both bulk and single-cell techniques. The growth of each strain was quantified in a broad range of drug concentrations by using time-lapse microscopy (to track the responses of individual cells to antibiotics inside a microfluidic chemostat) and by the enrichment of batch cultures for nongrowing cells. We formulated a quantitative phenomenological model to predict the growth rates of drug-resistant strains in the presence of drugs, based on the well-characterized biochemistry of drug and drug-resistance interactions and on bacterial growth laws that dictate relations between cell growth and gene expression. We tested the model predictions for various drugs and resistance mechanisms by constructing strains that constitutively express varying degrees of drug resistance. Results In strains expressing a moderate degree of drug resistance, growth rates dropped abruptly above a critical drug concentration, the minimum inhibitory concentration (MIC), whose value increased linearly with the basal level of resistance expression (see figure below, panel A). Cells exhibited growth bistability over a broad range of drug concentrations below the MIC: Isogenic cells expressing drug resistance coexisted in growing and nongrowing states in a homogeneous environment (panel B). Our model accurately predicted the range of drug concentrations in which growth bistability occurred, as well as the growth rates of the growing subpopulation, without any ad hoc fitting parameters. These findings reveal a plateau-like fitness landscape (panel A), which can be used to study the evolution of drug resistance in environments with varying drug concentrations. Discussion The broad occurrence of growth bistability in drug-resistant bacteria challenges the common notions and measures of drug efficacy and resistance. And because growth bistability can arise without complex regulation when gene expression is coupled to the state of cell growth, similar physiological links may underlie the growth bistability implicated in causing bacterial persistence. The availability of quantitative, predictive models will facilitate the formulation of strategies to limit the efficacy and evolvability of drug resistance. Keeping Quiet Many bacteria overcome antibiotic treatment by expressing proteins that confer antibiotic resistance, for instance, efflux pumps. But when a strain that expresses these antibiotic resistance proteins encounters an environment containing the corresponding drug, the resistance against the drug may paradoxically become silenced in many cells. In this case, a fraction of a population of genetically identical cells will grow in the presence of antibiotics while other subpopulations fail to grow at all. Deris et al. (10.1126/science.1237435) show that this bistable response arises from a built-in global feedback originating in antibiotic-mediated inhibition of growth, which reduces the expression of proteins that protect against growth inhibition. The resulting populations of dormant cells can exceed 50%, among otherwise identical resistance-expressing cells. This is important for antimicrobial treatment strategies because many bacterial cells may remain vulnerable to an antibiotic even when they apparently display strong resistance to it. Identical bacteria can have low-level resistance to low concentrations of drugs that can flip subpopulations into dormancy. To predict the emergence of antibiotic resistance, quantitative relations must be established between the fitness of drug-resistant organisms and the molecular mechanisms conferring resistance. These relations are often unknown and may depend on the state of bacterial growth. To bridge this gap, we have investigated Escherichia coli strains expressing resistance to translation-inhibiting antibiotics. We show that resistance expression and drug inhibition are linked in a positive feedback loop arising from an innate, global effect of drug-inhibited growth on gene expression. A quantitative model of bacterial growth based on this innate feedback accurately predicts the rich phenomena observed: a plateau-shaped fitness landscape, with an abrupt drop in the growth rates of cultures at a threshold drug concentration, and the coexistence of growing and nongrowing populations, that is, growth bistability, below the threshold.