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Michael S Samoilov

Publications and source records attributed to Michael S Samoilov.

2 recordsLinked to original sources

From fluctuations to phenotypes: the physiology of noise.

There are fundamental physical reasons why biochemical processes might be subject to noise and stochastic fluctuations. Indeed, it has long been understood that random molecular-scale mechanisms, such as those that drive genetic mutation, lie at the heart of population-scale evolutionary dynamics. What we can now appreciate is how stochastic fluctuations inherent in biochemical processes contribute to cellular and organismal phenotypes. Advancements in techniques for empirically measuring single cells and in corresponding theoretical methods have enabled the rigorous design and interpretation of experiments that provide incontrovertible proof that there are important endogenous sources of stochasticity that drive biological processes at the scale of individual organisms. Recently, some studies have progressed beyond merely ascertaining the presence of noise in biological systems; they trace its role in cellular physiology as it is passed through and processed by the biomolecular pathways-from the underlying origins of stochastic fluctuations in random biomolecular interactions to their ultimate manifestations in characteristic species phenotypes. These emerging results suggest new biological network design principles that account for a constructive role played by noise in defining the structure, function, and fitness of biological systems. They further show that stochastic mechanisms open novel classes of regulatory, signaling, and organizational choices that can serve as efficient and effective biological solutions to problems that are more complex, less robust, or otherwise suboptimal to deal with in the context of purely deterministic systems. Research in Drosophila melanogaster eye color-vision development and Bacillus subtilis competence induction has elegantly traced the role of noise in vital physiological processes from fluctuations to phenotypes, and is used here to highlight these developments.

Animals↗

Deviant effects in molecular reaction pathways.

In biological networks, any manifestations of behaviors substantially 'deviant' from the predictions of continuous-deterministic classical chemical kinetics (CCK) are typically ascribed to systems with complex dynamics and/or a small number of molecules. Here we show that in certain cases such restrictions are not obligatory for CCK to be largely incorrect. By systematically identifying properties that may cause significant divergences between CCK and the more accurate discrete-stochastic chemical master equation (CME) system descriptions, we comprehensively characterize potential CCK failure patterns in biological settings, including consequences of the assertion that CCK is closer to the 'mode' rather than the 'average' of stochastic reaction dynamics, as generally perceived. We demonstrate that mechanisms underlying such nonclassical effects can be very simple, are common in cellular networks and result in often unintuitive system behaviors. This highlights the importance of deviant effects in biotechnologically or biomedically relevant applications, and suggests some approaches to diagnosing them in situ.

Biotechnology↗