Insights from Phosphorylation Profiling of an Autoregulated Two-Component System

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Connecting biophysical and biochemical parameters determined in vitro to understanding and predicting physiological behavior is an important challenge. Bacterial two-component systems have long served as models for investigating fundamental properties of signal transduction. While understanding regulatory mechanisms has benefited greatly from mathematic modeling, a major obstacle to this approach is the lack of quantitative analyses of two-component systems in their native environments, particularly in vivo parameters for histidine kinase and phosphatase activities. Measurement of cellular phosphorylation levels combined with mathematic modeling has enabled a phosphorylation profiling approach to investigate whether protein expression levels of the archetype PhoB/PhoR two-component system are optimized to the phosphorylation output profile and how the positive autoregulatory scheme enables wild-type cells to achieve optimal expression levels of PhoB/PhoR in dynamic environments. The PhoB/PhoR system responds to phosphate (Pi) limitation, and different Pi conditions were discovered to have conflicting requirements for optimal protein expression levels. Experimental evidence established that wild-type cells achieve different optimal expression levels via autoregulation under respective Pi conditions. The fitness optimum balances costs of protein production with benefits, which are correlated with the phosphorylation output. Laboratory evolution experiments revealed that cells with different non-optimal levels of PhoB/PhoR all rapidly evolve toward optimal expression levels by acquisition of diverse mutations, demonstrating strong selective pressure for evolutionary tuning of protein expression levels. However, positive autoregulation comes at the cost of delaying the output response. Analysis of promoter architecture and mathematic modeling suggests that a PhoB repressor site within the phoBR promoter provides negative feedback that enables acceleration of the response, counterbalancing the delay imposed by positive autoregulation. Thus system architecture appears to be exquisitely evolved to provide protein activities, levels and timing of expression integrated for optimal response output under dynamic and diverse conditions.