Metabolic Supply and Demand Constrain Optimal Regulatory Strategies: Structural Evidence from the E coli Small Molecule Regulatory Network
Conference on Constraint-Based Reconstruction and Analysis (COBRA)
2018
5th Conference on Constraint-Based Reconstruction and Analysis (COBRA 2018)
Poster Session
Poster Session
Sunday, October 14, 2018 - 6:00pm to 7:00pm
Balancing supply and demand is a life or death-or-task for bacteria. In resource-limited envrionments, they must be able to precisely coordinate metabolic flux distributions to balance the demands required for optimal growth without wasting costly metabolites. To this end, they have evolved complex, layered regulatory systems which respond to changing external contexts. While the structure and function of hierarchical regulatory mechanisms (transcription and translation) have been characterized extensively, regulation at the metabolic level remains less well understood. To address this, we reconstructed a genome-scale small-molecule regulatory network (SMRN) for E coli to understand the role small-molecule regulation plays in balancing supply and demand. Structural analysis of our SMRN revealed a dense network of interactions with layers of organization. We found that at the local level, SMR interactions are organized into well-understood feedforward loop motifs that provide specific input-output relationships between fluxes through relatively distanct metabolic reactions. Functionalization of these motifs demonstrates that the SMRN has the capacity to influence supply and demand balancing in two ways: by coordinating signals within the core metabolism and effecting tertiary fluxes based on these signals; and by directly balancing fluxes of metabolites which are essential for biomass production. We explore the constraints under which this regulatory system is likely to be active to show that it can work synergistically with transcriptional regulation and that protein degradation rate is the dominant factor which determines the optimal balance of control burden across these layers of regulation.