Modeling and Exploiting Microbial Temperature Response

Abstract

Temperature is an important parameter in bioprocesses, influencing the structure and functionality of almost every biomolecule, as well as affecting metabolic reaction rates. In industrial biotechnology, the temperature is usually tightly controlled at an optimum value. Smart variation of the temperature to optimize the performance of a bioprocess brings about multiple complex and interconnected metabolic changes and is so far only rarely applied. Mathematical descriptions and models facilitate a reduction in complexity, as well as an understanding, of these interconnections. Starting in the 19th century with the “primal” temperature model of Svante Arrhenius, a variety of models have evolved over time to describe growth and enzymatic reaction rates as functions of temperature. Data-driven empirical approaches, as well as complex mechanistic models based on thermodynamic knowledge of biomolecular behavior at different temperatures, have been developed. Even though underlying biological mechanisms and mathematical models have been well-described, temperature as a control variable is only scarcely applied in bioprocess engineering, and as a conclusion, an exploitation strategy merging both in context has not yet been established. In this review, the most important models for physiological, biochemical, and physical properties governed by temperature are presented and discussed, along with application perspectives. As such, this review provides a toolset for future exploitation perspectives of temperature in bioprocess engineering.

Cell size, genome size, and maximum growth rate are near‐independent dimensions of ecological variation across bacteria and archaea

“…Considering soil respiration and decomposition rates, meta-analysis showed Q10 around 4-6 at 0°C declining to 2 at around 25°C and continuing around 2 out to 50°C (Hamdi et al, 2013). A review of theoretical equations for temperature response (Noll et al, 2020) considered 19 models that are variations on Arrhenius (linear response of ln growth or metabolic rate to reciprocal of absolute temperature) from 1946 up to the present. Several of these equations have growth rates declining above some optimal temperature.…”

A general theory for temperature-dependence in biology

“…Temperature affects reaction rates of enzymes, which regulate processes that manifest at all levels of biological organization from molecules to ecosystems [1-7]. The classic Arrhenius equation [8-9] for the temperature dependence of chemical reaction rates ( k ), has become the standard mathematical description of temperature responses used by biologists and ecologists, as epitomized, for example, by the Metabolic Theory of Ecology (MTE), [7] and is given by where k B is Boltzmann’s constant, T is absolute temperature, E is an effective activation energy for the process of interest, and a is an overall normalization constant characteristic of the process.…”

“…Temperature dependence models and the Eyring-Evans-Polanyi (EEP) theory. Temperature affects reaction rates of enzymes, which regulate processes that manifest at all levels of biological organization from molecules to ecosystems [1][2][3][4][5][6][7]. The classic Arrhenius equation [8][9] for the temperature dependence of chemical reaction rates (k), has become the standard mathematical description of temperature responses used by biologists and ecologists, as epitomized, for example, by the Metabolic Theory of Ecology (MTE), [7] and is given by…”

“… Abstract Temperature affects all biological rates and has far reaching consequences from bioengineering [1] to predicting ecological shifts under a changing climate [2-3], and more recently, to pandemic spread [4]. Temperature response in biological systems is characteristically asymmetric and nonlinear, with an exponential phase of increase followed by a concave up-ward or downward phase [5].…”

“…with many parameters). Moreover, their theoretical framework does not include how parameters vary, nor their applicability across multiple scales and taxa, or whether they exhibit universality [1][2][3][4][5][6][7]. Here, we derive a new mechanistic, yet simple, model for the temperature dependence of biological rates based on the Eyring-Evans-Polanyi theory governing chemical reaction rates, which is applicable across all scales from the micro to the macro.…”