Antibiotic resistance is generally associated with a fitness deficit resulting from the burden of producing and maintaining resistance machinery. This additional cost suggests that resistant bacteria will be outcompeted by susceptible bacteria in conditions without antibiotics. However, in practice, this process is slow in part because of regulation that minimizes expression of these genes in the absence of antibiotics. This suggests that if it were possible to turn on their expression, the cost would increase, thereby accelerating removal of resistant strains. Experimental and theoretical studies have shown that environmental chemicals can change the fitness cost associated with resistance and therefore have a significant impact on population dynamics. The multiple antibiotic resistance activator (MarA) is a clinically important regulator in Escherichia coli that activates downstream genes to increase resistance against multiple classes of antibiotics. Salicylate is an inducer of MarA that can be found in the environment and derepresses marA's expression. In this study, we sought to unravel the interplay between salicylate and the fitness cost of MarA-mediated antibiotic resistance. Using salicylate as an inducer of MarA, we found that a wide spectrum of concentrations can increase burden in resistant strains compared to susceptible strains. Induction resulted in rapid exclusion of resistant bacteria from mixed populations of antibiotic-resistant and susceptible cells. A mathematical model captures the process and predicts its effect in various environmental conditions. Our work provides a quantitative understanding of salicylate exposure on the fitness of different MarA variants and suggests that salicylate can lead to selection against MarA-mediated resistant strains. More generally, our findings show that natural inducers may serve to bias population membership and could impact antibiotic resistance and other important phenotypes.

A classical and well-established mechanism that enables cells to adapt to new and adverse conditions is the acquisition of beneficial genetic mutations. Much less is known about epigenetic mechanisms that allow cells to develop novel and adaptive phenotypes without altering their genetic blueprint. It has been recently proposed that histone modifications, such as heterochromatin-defining H3K9 methylation (H3K9me), normally reserved to maintain genome integrity, can be redistributed across the genome to establish new and potentially adaptive phenotypes. To uncover the dynamics of this process, we developed a precision engineered genetic approach to trigger H3K9me redistribution on demand in fission yeast. This enabled us to trace genome-scale RNA and chromatin changes over time prior to and during adaptation in long-term continuous cultures. Establishing adaptive H3K9me occurs over remarkably slow time-scales relative to the initiating stress. During this time, we captured dynamic H3K9me redistribution events ultimately leading to cells converging on an optimal adaptive solution. Upon removal of stress, cells relax to new transcriptional and chromatin states rather than revert to their initial (ground) state, establishing a tunable memory for a future adaptive epigenetic response. Collectively, our tools uncover the slow kinetics of epigenetic adaptation that allow cells to search for and heritably encode adaptive solutions, with implications for drug resistance and response to infection.

Antibiotic resistance is generally associated with a fitness deficit resulting from the burden of producing and maintaining resistance machinery. This additional cost suggests that resistant bacteria will be outcompeted by susceptible bacteria in conditions without antibiotics. However, in practice this process is slow due in part to regulation that minimizes expression of these genes in the absence of antibiotics. This suggests that if it were possible to turn on their expression, the cost would increase, thereby accelerating removal of resistant strains. Experimental and theoretical studies have shown that environmental chemicals can change the fitness cost associated with resistance and therefore have a significant impact on population dynamics. MarA (multiple antibiotic resistance activator) is a clinically important regulator in Escherichia coli which activates downstream genes to increase resistance against multiple classes of antibiotics. Salicylate is an inducer of MarA which can be found in the environment and de-represses marA's expression. In this study, we sought to unravel the interplay between salicylate and the fitness cost of MarA-mediated antibiotic resistance. Using salicylate as a natural inducer of MarA, we found that a wide spectrum of concentrations can increase burden in resistant strains compared to susceptible strains. Induction resulted in rapid exclusion of resistant bacteria from mixed populations of antibiotic resistant and susceptible cells. A mathematical model captures the process and predicts its effect in various environmental conditions. Our work provides a quantitative understanding of salicylate exposure on the fitness of different MarA variants, and suggests that salicylate can lead to selection against MarA-mediated resistant strains. More generally, our findings show that natural inducers may serve to bias population membership and could impact antibiotic resistance and other important phenotypes.

A synthetic gene circuit enables programming of many stable states in mammalian cells