TY - GEN AB - This text provides additional information about the model, a derivation of the analytic results in Eq (4), and details about simulations of an additional parameter set. AU - Lukacisinova, Marta AU - Novak, Sebastian AU - Paixao, Tiago ID - 9849 TI - Modelling and simulation details ER - TY - GEN AB - In this text, we discuss how a cost of resistance and the possibility of lethal mutations impact our model. AU - Lukacisinova, Marta AU - Novak, Sebastian AU - Paixao, Tiago ID - 9850 TI - Extensions of the model ER - TY - GEN AB - Based on the intuitive derivation of the dynamics of SIM allele frequency pM in the main text, we present a heuristic prediction for the long-term SIM allele frequencies with χ > 1 stresses and compare it to numerical simulations. AU - Lukacisinova, Marta AU - Novak, Sebastian AU - Paixao, Tiago ID - 9851 TI - Heuristic prediction for multiple stresses ER - TY - GEN AB - We show how different combination strategies affect the fraction of individuals that are multi-resistant. AU - Lukacisinova, Marta AU - Novak, Sebastian AU - Paixao, Tiago ID - 9852 TI - Resistance frequencies for different combination strategies ER - TY - THES AB - Antibiotics have diverse effects on bacteria, including massive changes in bacterial gene expression. Whereas the gene expression changes under many antibiotics have been measured, the temporal organization of these responses and their dependence on the bacterial growth rate are unclear. As described in Chapter 1, we quantified the temporal gene expression changes in the bacterium Escherichia coli in response to the sudden exposure to antibiotics using a fluorescent reporter library and a robotic system. Our data show temporally structured gene expression responses, with response times for individual genes ranging from tens of minutes to several hours. We observed that many stress response genes were activated in response to antibiotics. As certain stress responses cross-protect bacteria from other stressors, we then asked whether cellular responses to antibiotics have a similar protective role in Chapter 2. Indeed, we found that the trimethoprim-induced acid stress response protects bacteria from subsequent acid stress. We combined microfluidics with time-lapse imaging to monitor survival, intracellular pH, and acid stress response in single cells. This approach revealed that the variable expression of the acid resistance operon gadBC strongly correlates with single-cell survival time. Cells with higher gadBC expression following trimethoprim maintain higher intracellular pH and survive the acid stress longer. Overall, we provide a way to identify single-cell cross-protection between antibiotics and environmental stressors from temporal gene expression data, and show how antibiotics can increase bacterial fitness in changing environments. While gene expression changes to antibiotics show a clear temporal structure at the population-level, it is unclear whether this clear temporal order is followed by every single cell. Using dual-reporter strains described in Chapter 3, we measured gene expression dynamics of promoter pairs in the same cells using microfluidics and microscopy. Chapter 4 shows that the oxidative stress response and the DNA stress response showed little timing variability and a clear temporal order under the antibiotic nitrofurantoin. In contrast, the acid stress response under trimethoprim ran independently from all other activated response programs including the DNA stress response, which showed particularly high timing variability in this stress condition. In summary, this approach provides insight into the temporal organization of gene expression programs at the single-cell level and suggests dependencies between response programs and the underlying variability-introducing mechanisms. Altogether, this work advances our understanding of the diverse effects that antibiotics have on bacteria. These results were obtained by taking into account gene expression dynamics, which allowed us to identify general principles, molecular mechanisms, and dependencies between genes. Our findings may have implications for infectious disease treatments, and microbial communities in the human body and in nature. AU - Mitosch, Karin ID - 818 SN - 2663-337X TI - Timing, variability and cross-protection in bacteria – insights from dynamic gene expression responses to antibiotics ER -