Oleg Igoshin

Bionote:

Oleg Igoshin specializes in computational systems biology, focusing on dynamical properties and evolutionary design principles of biochemical networks, gene-regulatory networks in bacterial stress response and differentiation, and pattern formation in bacterial biofilms. Research in Igoshin’s Cellular Systems Dynamics Laboratory uses methods of nonlinear dynamics, biophysics, statistics, and bioinformatics to expose emergent properties of biological systems on intercellular and intracellular scales. Igoshin’s computational and theoretical methods complement the experimental approaches of collaborators with leading academic and medical researchers across the U.S., Europe, and Australia. Igoshin joined Rice in 2007. From 2012 to present, he has been instrumental in establishing and growing the doctoral program in Systems, Synthetic, and Physical Biology (SSPB). He has also been a senior investigator with Rice’s Center for Theoretical Biological Physics since 2013. Prof. Igoshin has been an Associate Editor of PLOS Computational Biology since 2016 and mSystems since 2022.

Understanding Trade-offs in Biological Information Processing

Abstract

High accuracy of major biological processes relies on the ability of the participating enzymatic molecules to preferentially select the correct substrate from a pool of chemically similar substrates by activating the so-called proofreading mechanisms. While the importance of such mechanisms is widely accepted, it is still unclear how evolution has optimized biological systems with respect to their characteristic properties. We developed a comprehensive master-equation theoretical framework that allowed us to quantitatively investigate the trade-offs between the three properties of enzymatic systems: error, speed, and energy dissipation. Within this framework, we analyzed the speed and accuracy of several fundamental biological processes, including DNA replication, transcription, tRNA charging, and tRNA selection during the translation. The results indicate that the speed-accuracy trade-off is not always observed contrary to typical assumptions. However, when the trade-off is present, the biological systems tend to optimize the speed rather than the accuracy of the processes, as long as the error level is tolerable. When systems function in a regime where no speed-accuracy trade-off is observed, constraints due to energy dissipation in the proofreading play a key role. Our theory demonstrates a universal Pareto front in error-dissipation trade-off and shows how naturally selected kinetic parameters position their system close to this boundary. Our findings, therefore, provide a new system-level picture of how complex biological processes are able to function so fast with high accuracy and low dissipation.

Master-equation Theoretical Framework to Quantitatively Investigate Error, Speed, and Energy Dissipation in the Enzymatic Systems

Abstract

We will discuss forward and backward master equations for enzymatic control mechanisms and how these approaches can be used to compute speed, error, and energy dissipation rate.