Quantitative Analysis of Constructive Stochastic Designs in Biological Systems

By Michael Samoilov, QB3/LBL

June 23, 2009

CNLS Conference room.

It has been long understood and, in recent years, conclusively shown that molecular noise arising due to the stochastic occurrence and discrete nature of individual chemical reactions is ubiquitous in natural biological processes. By analogy with artificially engineered systems, these random processes are still often assumed to be destructive – that is, undesirable and targeted for suppression by organisms at large. However, natural systems are not constrained by many practical engineering design limitations. With ongoing improvements in experimental techniques, increasing number of in situ mechanisms has been shown to actively employ innate molecular number fluctuations to enable diverse physiological functions. Quantitative analysis of these natural constructive stochastic designs can help us better understand evolutionary priorities of organisms involved as well as aid the development of novel optimized solutions in bioengineering applications.

This talk will discuss some of our efforts in modeling and computational analysis of processes that fall within the chemical master equation (CME) framework. Specific points include advantages provided by constructive discrete-stochastic mechanisms over alternative continuous-deterministic solutions – as given by classical chemical kinetics (CCK) – in several natural settings (viruses, microbes, metazoans); characteristics of CME processes that can lead to behavioral deviations from CCK predictions; as well as applications of this analysis to concrete biomedical problems of temperature control in uropathogenic E. coli fimbriation.

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