Universality of Thermodynamic Constants Governing Biological Growth Rates

Ross Corkrey,Tom Mcmeekin,David Ratkowsky,June Olley,Tom Ross,Vladimir N Uversky

doi:10.1371/journal.pone.0032003

Abstract

BackgroundMathematical models exist that quantify the effect of temperature on poikilotherm growth rate. One family of such models assumes a single rate-limiting ‘master reaction’ using terms describing the temperature-dependent denaturation of the reaction's enzyme. We consider whether such a model can describe growth in each domain of life.Methodology/Principal FindingsA new model based on this assumption and using a hierarchical Bayesian approach fits simultaneously 95 data sets for temperature-related growth rates of diverse microorganisms from all three domains of life, Bacteria, Archaea and Eukarya. Remarkably, the model produces credible estimates of fundamental thermodynamic parameters describing protein thermal stability predicted over 20 years ago.Conclusions/SignificanceThe analysis lends support to the concept of universal thermodynamic limits to microbial growth rate dictated by protein thermal stability that in turn govern biological rates. This suggests that the thermal stability of proteins is a unifying property in the evolution and adaptation of life on earth. The fundamental nature of this conclusion has importance for many fields of study including microbiology, protein chemistry, thermal biology, and ecological theory including, for example, the influence of the vast microbial biomass and activity in the biosphere that is poorly described in current climate models.

Highlights

Temperature governs the rate of chemical reactions including those controlling the development and decline of life on earth from individual cells to complex populations
The fundamental nature of this conclusion has importance for many fields of study including microbiology, protein chemistry, thermal biology, and ecological theory including, for example, the influence of the vast microbial biomass and activity in the biosphere that is poorly described in current climate models
We were able to do this by utilizing the Markov Chain Monte Carlo (MCMC) methods to greatly simplify the computation involved with a Bayesian framework, and a hierarchical model that permits those parameters that are less well informed to ‘borrow strength’ from elsewhere in the model and so improve estimation

Summary

Introduction

Temperature governs the rate of chemical reactions including those controlling the development and decline of life on earth from individual cells to complex populations. Models to describe the effect of temperature on biological systems reliably are becoming increasingly important One such family of models [1,2] assumes a single rate-limiting, enzyme-catalyzed ‘master reaction’ using an Arrhenius form modified by terms that describe the temperature-dependent denaturation of that enzyme. Mathematical models exist that quantify the effect of temperature on poikilotherm growth rate One family of such models assumes a single rate-limiting ‘master reaction’ using terms describing the temperature-dependent denaturation of the reaction’s enzyme. We consider whether such a model can describe growth in each domain of life

Methods

Results

Conclusion