Understanding mitochondria and the utility of optimization as a canonical framework for identifying and modeling mitochondrial pathways.

Abstract

The goal of this paper is to provide an overview of our current understanding of mitochondrial function as a framework to motivate the hypothesis that mitochondrial behavior is governed by optimization principles that are constrained by the laws of the physical and biological sciences. Then, mathematical optimization tools can generally be useful to model some of these processes under reasonable assumptions and limitations. We are specifically interested in optimizations via variational methods, which are briefly summarized. Within such an optimization framework, we suggest that the numerous mechanical instigators of cell and intracellular functioning can be modeled utilizing some of the principles of mechanics that govern engineered systems, as well as by the frequently observed feedback and feedforward mechanisms that coordinate the multitude of processes within cells. These mechanical aspects would need to be coupled to governing biochemical rules. Of course, biological systems are significantly more complex than engineered systems, and require considerably more experimentation to ascertain and characterize parameters and subsequent behavior. That complexity requires well-defined limitations and assumptions for any derived models. Optimality is being motivated as a framework to help us understand how cellular decisions are made, especially those that transition between physiological behaviors and dysfunctions along pathophysiological pathways. We elaborate on our interpretation of optimality and cellular decision making within the body of this paper, as we revisit these ideas in the numerous different contexts of mitochondrial functions.