THE IMPORTANCE OF COMPARTMENTALIZATION IN METABOLIC FLUX MODELS: YEAST AS AN ECOSYSTEM OF ORGANELLES

• Published in: Genome Informatics 2009 Vol. 22; pp. 41 - 55
• Main Authors: KLITGORD, NIELS, SEGRÈ, DANIEL
• Format: Book Chapter Journal Article
• Language: English
• Published: Japan IMPERIAL COLLEGE PRESS 01.01.2010
• Subjects: Cell Compartmentation - physiology; Ecosystem; Metabolic Networks and Pathways; Models, Biological; Organelles - metabolism; Saccharomyces cerevisiae - genetics; Saccharomyces cerevisiae - growth & development; Saccharomyces cerevisiae - metabolism; Saccharomyces cerevisiae Proteins - metabolism; metabolic network models; microbial communities; flux balance analysis; compartments; constraint-based models
• ISBN: 9781848165694; 9781908977991; 1848165692; 190897799X; 1848165781; 9781848165786
• ISSN: 0919-9454
• DOI: 10.1142/9781848165786_0005

Understanding the evolution and dynamics of metabolism in microbial ecosystems is an ongoing challenge in microbiology. A promising approach towards this goal is the extension of genome-scale flux balance models of metabolism to multiple interacting species. However, since the detailed distribution of metabolic functions among ecosystem members is often unknown, it is important to investigate how compartmentalization of metabolites and reactions affects flux balance predictions. Here, as a first step in this direction, we address the importance of compartmentalization in the well characterized metabolic model of the yeast Saccharomyces cerevisiae, which we treat as an "ecosystem of organelles". In addition to addressing the impact that the removal of compartmentalization has on model predictions, we show that by systematically constraining some individual fluxes in a de-compartmentalized version of the model we can significantly reduce the flux prediction errors induced by the removal of compartments. We expect that our analysis will help predict and understand metabolic functions in complex microbial communities. In addition, further study of yeast as an ecosystem of organelles might provide novel insight on the evolution of endosymbiosis and multicellularity.