A general theory for temperature dependence in biology

Author:

Arroyo José Ignacio12,Díez Beatriz345ORCID,Kempes Christopher P.2,West Geoffrey B.2,Marquet Pablo A.12678

Affiliation:

1. Departamento de Ecología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, CP 8331150 Santiago, Chile

2. The Santa Fe Institute, Santa Fe, NM 87501

3. Departamento de Genética Molecular y Microbiología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, CP 8331150 Santiago, Chile

4. Center for Climate and Resilience Research, FONDAP (Fondo de Financiamiento de Centros de Investigación en Áreas Prioritarias), University of Chile, CP 8370449 Santiago, Chile

5. Center for Genome Regulation, FONDAP, Faculty of Science, University of Chile, CP 7800003 Santiago, Chile

6. Instituto de Ecología y Biodiversidad, CP 7800003 Santiago, Chile

7. Centro de Cambio Global Universidad Católica, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, CP 8331150 Santiago, Chile

8. Instituto de Sistemas Complejos de Valparaíso, CP 2340000 Valparaíso, Chile

Abstract

At present, there is no simple, first principles–based, and general model for quantitatively describing the full range of observed biological temperature responses. Here we derive a general theory for temperature dependence in biology based on Eyring–Evans–Polanyi’s theory for chemical reaction rates. Assuming only that the conformational entropy of molecules changes with temperature, we derive a theory for the temperature dependence of enzyme reaction rates which takes the form of an exponential function modified by a power law and that describes the characteristic asymmetric curved temperature response. Based on a few additional principles, our model can be used to predict the temperature response above the enzyme level, thus spanning quantum to classical scales. Our theory provides an analytical description for the shape of temperature response curves and demonstrates its generality by showing the convergence of all temperature dependence responses onto universal relationships—a universal data collapse—under appropriate normalization and by identifying a general optimal temperature, around 25 C, characterizing all temperature response curves. The model provides a good fit to empirical data for a wide variety of biological rates, times, and steady-state quantities, from molecular to ecological scales and across multiple taxonomic groups (from viruses to mammals). This theory provides a simple framework to understand and predict the impact of temperature on biological quantities based on the first principles of thermodynamics, bridging quantum to classical scales.

Funder

Agencia Nacional de Investigación y Desarrollo

ANID-FONDECYT

AFB

NSF

BASAL funds for centers of excellence from ANID-Chile

Publisher

Proceedings of the National Academy of Sciences

Subject

Multidisciplinary

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