Crosstalk, Network Dynamics, and the Evolution of Signaling
Rowland, Michael A.
University of Kansas
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Cells have developed networks of interacting proteins to process information about their environment and respond appropriately to stimuli. Reversible post-translational modifications alter the functionality of these proteins, transmitting information through the cell. Bacteria primarily utilize Two-Component Signaling (TCS) networks, in which a sensor Histidine Kinase (HK) activates a Response Regulator (RR), which typically acts as a transcription factor. TCS pathways are insulated from one another, each responding to a unique stimulus. In contrast, metazoan signaling networks are extremely complex, to the point that individual pathways are no longer discernible from the web of interactions. Cellular decisions are no longer binary; the overall state of the network determines the response to inputs. In this work, we use mathematical modeling to explore the dynamics that give rise to the dichotomy in network complexity and the evolutionary pressures and benefits of crosstalk, or the lack thereof. We find that proteins can act as competitive inhibitors of each other when competing for a shared enzyme. For example, the phosphorylation of one protein would monopolize a phosphatase, decreasing the concentration of phosphatase available to competing substrates. Consequently, the other substrates would see an increase in their own phosphorylation, indicating the potential for crosstalk mediated by any shared enzyme. The shared competitive inhibition of enzymes by different substrates has a more drastic effect in bacterial TCS pathways. HKs are typically bifunctional, acting as both kinase and phosphatase for their RRs. These dynamics results in a situation in which the introduction of crosstalk to TCS networks would always decrease system efficiency. While the enzymes typical of metazoan networks do not have the same enzymatic constraints as TCS networks, the fact that they can evolve crosstalk does not explain the benefits that have driven such complexity. The extensive crosstalk present in metazoans has likely evolved due to the constraints multicellularity has placed on intracellular communication. Because of the complexity of the network, the expression of different signaling components in various cell types results in a high level of diversity in responses to stimuli. Ultimately, our work demonstrates that the cellular context must be considered in interpreting network connectivity.
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