Igoshin, Oleg A.2014-10-142014-10-142013-122013-11-26December 2Tiwari, Abhinav. "Uncovering Mechanisms of Bistability and Ultrasensitivity in Bacterial Stress Response." (2013) Diss., Rice University. <a href="https://hdl.handle.net/1911/77560">https://hdl.handle.net/1911/77560</a>.https://hdl.handle.net/1911/77560Bacteria have evolved optimized biochemical and genetic networks to sense diverse stimuli and implement appropriate dynamic responses. Despite the remarkable progress in experimental approaches and the increasingly common use of mathematical modeling, very few examples exist of general design principles that relate a network’s structure to its response. To improve this understanding we develop biochemically accurate models of networks that contain well-conserved regulatory modules, which allows us to make both specific and biologically-relevant predictions. First, we analyze the mycobacterial stress-response network which consists of the MprA/MprB two-component system and the alternative sigma factor Sig E. This network contains multiple positive feedback loops which may give rise to bistability, thereby making it a good candidate for controlling the mycobacterial persistence switch. We find that neither the positive autoregulation in the two-component system nor the Sig E-mediated feedback is sufficient to induce bistability. Nonetheless, including the post-translational regulation of SigE by RseA increases system’s effective cooperativity resulting in bistability. We predict that overexpression or deletion of RseA, the key element controlling the ultrasensitive response, can eliminate bistability. Second, we investigate how dynamical properties of a network with positive autoregulation are affected by additive or multiplicative coupling with another positive or negative feedback. We find that a network’s bistability range is positively correlated with its maximum open-loop gain and that both the quantities depend on the sign of feedback loops and the type of feedback coupling. Moreover, we show that addition of a positive feedback can decrease, whereas addition of a negative feedback can increase the bistability range. Third, we examine the mechanism of pulsing in Bacillus subtilis stress-response sigma factor Sig B. We determine that the concentration of anti-sigma factor RsbW must lie in an optimal range for pulsing. We also observe that pulsing occurs only above a phosphatase threshold, beyond which the amount of RsbW is insufficient to fully sequester its binding partners Sig B and anti-anti-sigma factor RsbV. Furthermore, we compare our simulation results with experimental data to show that the network encodes phosphatase burst size into Sig B pulses. We predict that genetic perturbations which disrupt the fine-tuning of RsbW concentration will curb pulsing.application/pdfengCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.MultiplicativeBimodalityLogarithmic gainOpen-loop gainDecoupling approximationRobustnessPulsingThresholdTwo-component systemSigma factorFeedback loopsBistabilityUltrasensitivityStress-responseMolecular titrationProtein sequestrationCouplingAdditiveThesis2014-10-14