Steve G. Oliver, Cambridge Systems Biology Centre (CSBC),"Design Rules and Evolutionary Imperatives for a Simple Eukaryote"
Feb 23 2010, 11:00 am
Distinguished Lecture Series Guest Speaker:
Steve G. Oliver
Director, Cambridge Systems Biology Centre (CSBC)
Professor of Systems Biology
University of Cambridge
Date & Time:Tuesday February 23, 2010, 11:00AM
Location:U.A. Whitaker 1103
Construction of a model of the eukaryotic cell with both predictive and explanatory power is a key goal of systems biology. Using a top-down approach, we have identified the cellular components that control growth rate in Saccharomyces cerevisiae under a range of different nutrient conditions and growth rates. We find that, for some controllers of growth rate (most notably the proteasome), the nature of the control they exert changes according to conditions. At fast growth rates the concentrations of the most abundant growth-rate-regulated protein complexes (such as the ribosome, proteasome, and COPI vesicle) become the limiting factors to further growth. We also find that at the very fastest growth rates, some of the key regulators of the cell cycle impose a barrier that prevents growth exceeding a maximum rate (1¼max). A reduction in the copy number of these genes lowers this barrier and allows faster growth rates to be achieved. While this suggests sub-optimal design, the identity of the haploproficient genes indicates that the imperative of conserving genome integrity results in yeast growing at slower than optimal rates. We find that both haploinsufficient and haploproficient genes are highly conserved in yeast evolution. Moreover, the genomic location of some haploinsufficient genes is also highly conserved and has not been disturbed by major evolutionary upheavals such as whole-genome duplication (WGD). The impact of many of the significant controllers of growth rate is, itself, a function of growth rate, even to the extent that the sign of the control they exert changes at the fastest growth rates. In other cases, control changes according to the environemtal context. This context dependency makes it difficult to define "design rules" for biological systems and the prospects for using Robot Scientists to assist in the elucidation of such rules will be discussed.
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