Computational Tools for the Analysis and Redesign of Microbial Production Systems
by Prof. Costas D. Maranas
Details at http://www.castdiv.org/WebCAST.htm <http://www.castdiv.org/WebCAST.htm>
Deadline to Register- 10 May 2006
DATE: Friday, 12 May 2006, 10am-12noon Pacific [1pm-3pm Eastern]
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Abstract
In this talk we will describe how optimization-based computational tools can be used to guide strain redesign leading to targeted overproductions. For example, production of bio-ethanol or complex molecules such as terpenes. Using as a starting point stoichiometric models of microbial metabolism, we will first explore how optimization can be used to pinpoint which new functionalities to add to the microbial host to endow it with new capabilities extracted from a generated database of more than 5,700 reactions. Building on this computational infrastructure, we will then present an integrated framework for identifying optimal microbial strain redesign strategies allowing for (i) additions, (ii) deletions and (iii) modulations (i.e., activations or inhibitions) of targeted reactions in the metabolic network. Finally we will explore how optimization can be used to analyze the topological properties of metabolic networks, identify pathway gaps and suggest ways of filling them. Th!
e developed computational tools will be highlighted using a number of design case-studies and the predictions will be contrasted with experimental results.
Biographical Sketch
Costas D. Maranas (b. 1967), Donald B. Broughton Professor, Department of Chemical Engineering, The Pennsylvania State University, BS, Chemical Engineering, Aristotle University, Greece, (1990); MA, Chemical Engineering, Princeton University (1992); Ph.D. in Chemical Engineering, Princeton University (1995); Allan P. Colburn Award for Excellence in Publication (2002), Editorial Board for Biophysical Journal, Computers & Chemical Engineering, Journal of Global Optimization and Metabolic Engineering; Reviewer for NSF, NIH and DOE; Research interests: Modeling and optimization of directed evolution protocols for protein engineering, analysis and optimization of metabolic and signaling networks, optimal design of biological circuits and synthetic biology, inference of gene regulatory networks, real options based optimization of product and R&D pipelines, optimization theory and algorithms.
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