New model predicts how temperature affects life from quantum to classical scale

Every biological process is highly dependent on temperature. This applies to the very small, the very large, and every scale in between, from molecules to ecosystems and in every environment.

A general theory explaining how life depends on temperature is lacking — until recently. In a paper published in the Proceedings of the National Academy of Sciences, researchers led by Jose Ignacio Arroyo, a Santa Fe Institute Postdoctoral Fellow, introduce a simple framework that strictly predicts how temperature affects living things, at all scales.

“This is very basic,” says SFI External Professor Pablo Marquet, an ecologist at the Pontifica Universidad Catolica de Chile, in Santiago. Marquet, Ph.D. thesis advisor, is also working on the model. “You can apply this to almost any process that is affected by temperature. We hope this will be an important contribution.”

Marquet noted that such a theory could help researchers make accurate predictions in a variety of areas, including biological responses to climate change, the spread of infectious diseases, and food production.

Previous attempts to generalize the effect of temperature on biology did not have the “big picture” implications built into the new model, Marquet said. Biologists and ecologists often use the Arrhenius equation, for example, to describe how temperature affects the rate of chemical reactions. That approach succeeds in approximating how temperature affects some biological processes, but cannot fully explain many others, including metabolism and growth rates.

Arroyo initially set out to develop a general mathematical model to predict the behavior of any variable in biology. He soon realized, however, that temperature was a kind of universal predictor and could guide the development of new models. He started with a chemical theory explaining enzyme kinetics, but with a few additions and assumptions, he extended the model from the quantum-molecular level to a larger macroscopic scale.

Importantly, this model incorporates three elements that were lacking in previous attempts. First, like its chemical equivalent, it is derived from the first principle. Second, the core of the model is a simple single equation with only a few parameters. (Most existing models require a large number of assumptions and parameters.) Third, “it is universal in the sense that it can explain patterns and behavior for any microorganism or taxa in any environment,” he said. All temperature responses for different processes, taxa, and scales collapse to the same general functional form.

“I think our ability to systematize temperature responses has the potential to reveal new pools in biological processes to resolve various controversies,” said SFI Professor Chris Kempes who, together with SFI Professor Geoffrey West, helped the team bridge quantum-to-classical scales.

The PNAS paper describes the predictions of the new model that are in line with empirical observations of a variety of phenomena, including insect metabolic rates, relative germination of alfalfa, bacterial growth rates, and fruit fly mortality rates.

In future publications, Arroyo said, the group plans to derive new predictions from these models — many of which are planned for first publication. “The paper got too big,” he said.

Reference:

1. José Ignacio Arroyo, Beatriz Díez, Christopher P. Kempes, Geoffrey B. West, Pablo A. Marquet. A general theory for temperature dependence in biology. Proceedings of the National Academy of Sciences, 2022; 119 (30) DOI: 10.1073/pnas.2119872119

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