Constructing universal Phenomenology for biological cellular systems: An idiosyncratic review on evolutionary dimensional reduction

TL;DR

This paper reviews the potential for a macroscopic phenomenological theory of biological systems, emphasizing evolutionary dimensional reduction and proposing a framework linking phenotypic variability, robustness, and evolution.

Contribution

It introduces the concept of an evolutionary fluctuation-response relationship and provides a distribution theory explaining trait constraints in biological evolution.

Findings

Traits are constrained within a lower-dimensional space due to evolutionary pressures.

Experimental evidence supports the dimensional reduction hypothesis.

Potential for a macroscopic theory of biological robustness and irreversibility is discussed.

Abstract

Possibility to establish macroscopic phenomenological theory for biological systems, akin to the akin to the well-established framework of thermodynamics, is briefly reviewed. We introduce the concept of an evolutionary fluctuation-response relationship, which highlights the need for a tight correlation between the variance in phenotypic traits caused by genetic mutations and by internal noise. We provide a distribution theory that allows us to derive these relationships, which suggests that the changes in traits resulting from adaptation and evolution are considerably constrained within a lower-dimensional space. We explore the reasons behind this dimensional reduction, focusing on the constraints posed by the requirements for steady growth and robustness achieved through the evolutionary process. We draw support from recent laboratory and numerical experiments to substantiate our claims. Universality of evolutionary dimensional reduction is presented, whereas potential theoretical formulations for it are discussed. We conclude by briefly considering the prospects of establishing a macroscopic framework that characterizes biological robustness and irreversibility in cell differentiation, as well as an ideal cell model.