Designing Novel Cellulase Systems Through Agent Based Modeling and Global Sensitivity Analysis

Wednesday, October 19, 2011: 12:30 PM
M100 I (Minneapolis Convention Center)
Advait Apte, Biological Systems Engineering, Virginia Tech, Blacksburg, VA, Ryan S. Senger, Biological Systems Engineering Department, Virginia Tech, Blacksburg, VA and Stephen S. Fong, Department of Chemical and Life Science Engineering, Virginia Commonwealth University, Richmond, VA

The efficiency of enzymatic digestion of lignocellulosic substrates is an important area of research for liquid biofuels produced through fermentation.  Given the large research activity in this area, fewer research efforts have been directed towards directly comparing the different cellulolytic enzymatic systems available to microorganisms of interest. Specifically, these are (i) cellulase enzymes supported by a cellulosome and (ii) secreted cellulases.  There is a growing need to assess the competing mechanisms of these enzyme systems, independent of the underlying organisms, to compare their efficiency in hydrolyzing cellulose. In this study, we have used agent based modeling (ABM) to build a computational model of complexed (cellulosome) and non-complexed (secreted enzyme) cellulose hydrolysis.  Statistical analyses show that complexed cellulose hydrolysis involving an extracellular cellulosome is advantageous to non-complexed cellulose hydrolysis.  Additional simulations carried-out to measure the specific role of different cellulases suggest positive correlation between the concentration of endoglucanases and efficiency of cellulose hydrolysis.  These simulations were further supplemented by a global sensitivity analysis of the system.  From these results, we have derived a series of rules for metabolic engineers and synthetic biologists to facilitate choosing effective cellulase systems or designing new ones based on the lignocellulosic substrate available.

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