Limits and trade-offs of feedback control

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PROJECT SUMMARY Negative feedback control is essential to make biological systems stable to internal and external perturbations, just as homes need thermostats to maintain a fixed room temperature. In cells feedback is used to regulate everything from gene expression to chromosome replication, and its failure causes a range of disorders. But our understanding of feedback in biology is very incomplete. Most theoretical approaches use mathematical frameworks that are poorly suited to describe cells because they ignore a main source of perturbations: chemical reactions involve molecules in low numbers and since each individual reaction is probabilistic, fluctuations in concentrations arise spontaneously. Unlike man-made machines, where the control systems (e.g. thermostats) are fundamentally different from the processes they control (temperature fluctuations), the chemical control systems in cells are similar to the chemical processes they control. This makes it difficult for cells to suppress perturbations, and also makes it difficult for researchers to analyze control. Experimentally, very few systems allow both accurate measurements of concentrations in single cells and systematic modifications of the control system to analyze how they affect the system. Individual analyses can also focus so closely on the specific details of one specific system that general guiding principles are overlooked or misinterpreted. We propose to address these problems by developing new mathematical approaches and systematically applying our novel experimental assays to central model system: bacterial plasmids. Our preliminary theory demonstrates hard limits on the ability of negative feedback to suppress fluctuations in cells. It also suggests creative and counter-intuitive mechanisms that minimize these problems. Remarkably, we have found examples of these in plasmids that we know are under strong selection to suppress noise. We have also developed three types of experimental platforms to quantitatively address fluctuations and control in cells in general and for plasmids in particular: Accurate and independently validated single-molecule counting assays, high-throughput cell tracking platforms allowing us to follow a billion cell divisions with microscopy, and assays for highly accurate genotype-to-phenotype mapping for a million parallel lineages and control mutants. In addition to the importance of fundamentally understanding fluctuations and feedback control, bacterial plasmids are also very relevant medically, since they cause the majority of multidrug resistance cases in hospitals, a problem that leads to millions of serious illnesses and tens of thousands of deaths annually in the US alone. They are also key tools in biotechnology, where the fluctuation suppression properties we study are a significant nuisance. The unmatched experimental tractability of plasmids allows us to systematically vary control properties and rigorously test the mathematical descriptions experimentally, leading to a deeper understanding of feedback mechanisms and also an increase in useful knowledge about plasmid behavior.