Cells Take Sub-Optimal Metabolic Approaches to Maximize Survival Chances

There are few times in life when one should aim for suboptimal performance, but new research at Rice University in Texas suggests scientists who study metabolism and its role in evolution should look for signs of just that. A study published online on April 3, 2015 in an open-access article in BMC Systems Biology details a computational method called corsoFBA. FBA stands for flux balance analysis and the program predicts internal cell flux -- the rate at which cells process and store energy -- at what researchers call suboptimal growth. The ultimate goal of the study is to discover how organisms, including humans, adapt to changing environments, including the body's response during exercise. The method allows researchers to model how metabolic pathways, chains of chemical reactions in the cells of all living beings, will react in the presence or absence of certain conditions, like the availability of oxygen or the acidity of the environment. It does so by measuring how a cell spends its fixed energetic resources -- its protein cost -- to preserve flux in more than one pathway. The work springs from the mind and talents of a Rice graduate student André Schultz who spent years training his body for absolutely optimal performance. Schultz is a former member of the Brazilian national swim team who trained alongside U.S. Olympic legend Michael Phelps at the University of Michigan. As an undergraduate there, Schultz divided his time between competitive swimming and academics, particularly his love for mathematics. At Rice, where he is a student of bioengineering in the laboratory of co-author Amina Qutub, Ph.D., Schultz turned his attention to biophysics, specifically mathematical models of metabolic pathways.
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