Brauer Hall, room 12
Dr. Amir Akbari, Postdoctoral Associate
Department of Bioengineering
University of California, San Diego
A constraint-based model for quantitative characterization of the metabolome
Biological networks define the physiological traits and biochemical properties of cells. Flux distributions, metabolite concentrations, and macromolecular levels determine their functional states. While biological networks exhibit certain universal features across vastly diverse species, their flux and concentration states can drastically change from species to spices, strain to strain, or in response to environmental stresses in a specific cell. The robustness and evolvability of biological networks result from long-term adaptations of species in the face of an uncertain environment to remain highly functional, whereas variabilities in flux and concentration states are induced by short-term processes serving regulatory or homeostatic purposes. Understanding these two dichotomous aspects of living systems and their interplay throughout the evolutionary history of life could help answer some of the fundamental questions of cellular biochemistry.
Current mathematical frameworks for predicting the flux state (Flux-Balance Analysis) and macromolecular composition (Metabolism-Expression Model) of the cell do not rely on thermodynamic constraints to determine the spontaneous direction of reactions. These predictions may be biologically infeasible as a result. Imposing thermodynamic constraints requires accurate estimations of intracellular metabolite concentrations. These concentrations are constrained within physiologically possible ranges to enable an organism to grow in extreme conditions and adapt to its environment. In this talk, I will present a new generation of constraint-based models that can accurately estimate intracellular concentration ranges, showing results for a subnetwork of the Escherichia coli core metabolism (~70 metabolites and ~70 reactions), obeying fundamental biophysical constraints, including charge balance, osmotic balance, buffer capacity, ionic strength, reaction spontaneity, membrane potential, and metal-ion/hydrogen binding. I will talk about the scope and limitations of the model and discuss insights into the energetic evolution of transport systems that can be drawn from this framework.
Organizer / Host: Dr. Tang