A MULTIDIMENSIONAL LANDSCAPE MODEL FOR DETERMINING CELLULAR NETWORK THERMODYNAMICS
Joseph B. Hubbard, Michael W. Halter, Anne L. Plant
The distribution of phenotypic responses within an isogenic population of cells reflects the thermodynamics of a stationary state that results from coordinated intracellular reactions. The distribution of phenotypes is the result of both deterministic and stochastic characteristics of biochemical networks. A network can be characterized by a multidimensional potential landscape and a diffusion matrix of the dynamic fluctuations between N-number of intracellular network variables. These steady state and dynamic features contribute to the heat associated with maintaining a nonequilibrium steady state. The Boltzmann H-function defines the rate of free energy dissipation of a system and provides a framework for determining the heat associated with the nonequilibrium steady state. Normal mode analysis can be used to simplify the many-bodied problem by rotation of the diffusion matrix and corresponding landscape to identify degrees of freedom associated with complex clusters of network variables and the dynamics of their fluctuations. This experimentally accessible analysis allows evaluation of the relative thermodynamic contributions from network components, which provides insight into the composition of the network and the appropriate interpretation of the presence and concentration of each network component. We conjecture that there is an upper limit to the rate of dissipative heat produced by a biological system, and we also show that the dissipative heat has a lower bound. The magnitudes of the landscape gradients and the dynamic correlated fluctuations of network variables determine the relative importance of network components to network stability and adaptability.
, Halter, M.
and Plant, A.
A MULTIDIMENSIONAL LANDSCAPE MODEL FOR DETERMINING CELLULAR NETWORK THERMODYNAMICS, Proceedings of the National Academy of Sciences, [online], https://doi.org/10.1101/682690
(Accessed September 29, 2023)