Antimicrobial resistance is a major threat worldwide that requires a strong investment in fundamental studies. Resistance, as well as transient tolerance (persistence) to antibiotics, involve a network of intracellular stress responses: e.g., the stringent response, the SOS response, and the RpoS-regulated general stress response. We and others have shown that these stress responses are induced by antibiotic (AB) doses below the minimum inhibitory concentration (sub-MIC) and that they can accelerate acquisition of heritable AB resistance through increased mutagenesis and horizontal gene transfer (HGT). Although low concentrations of antibiotics do not kill bacteria, they can have a major impact on bacterial populations. In particular, it was shown that AB concentrations as low as hundred-fold below the MIC can lead to mutations and the selection of AB resistant cells. Most of the studies describing how bacteria acquire resistance or become persisters are based on experiments dealing with populations of cells. Such measurements yield average quantities for the whole population but they cannot provide a distribution of responses, nor can they follow the temporal evolution of individuals within the population. By contrast, there is mounting evidence that cells within a given population can display widely heterogeneous responses to an AB stress. This project aims at describing precisely individual cell fate during stress responses to low doses of antibiotics, and understanding the emergence of antibiotic resistance on the level of a single cell. We propose to address the profile of induction of four stress responses at the single-cell level: SOS, stringent response, RpoS general stress response and oxidative stress response, in response to three ABs from different families (fluoroquinolones, aminoglycosides, ß-lactams). To this end, we will use a microfluidic platform to culture bacteria, while submitting them to controlled AB stresses to assess heterogeneity and growth on chip. We will develop the theoretical description of bacterial growth dynamics taking into account the AB stress through mathematical modelling relating large-scale heterogeneity to the variability on the scale of individual cells. We will then isolate and extract cells that show phenotypic diversity. The large statistics will allow us to get access to rare events. The extracted cells will be subjected to analysis (NGS, dPCR) in order to detect horizontal gene transfers, mutations or changes of protein expression that can explain the behavior of these cells. This will first require the development of technological tools to genotype the small number of bacterial cells that can be recovered from the microchannel. The second step will be to explore different conditions that lead to the emergence of antibiotic resistance in order to gain insight into the underlying mechanisms and devise strategies to counter them. The impact of this project will be threefold: (i) Concerning the fundamental biological knowledge it will bring, (ii) the technological and quantitative developments that accompany it, and (iii) in understanding the emergence of resistance mechanisms and their implications for the development of new therapeutic strategies.