Macroscopic Theory for Evolving Biological Systems Akin to Thermodynamics

A linear reciprocal relationship between robustness and plasticity in homeostatic biological networks

In physics of living systems, a search for relationships of a few macroscopic variables that emerge from many microscopic elements is a central issue. We evolved gene regulatory networks so that the expression of core genes (partial system) is insensitive to environmental changes. Then, we found the expression levels of the remaining genes autonomously increase to provide a plastic (sensitive) response. A feedforward structure from the non-core to core genes evolved autonomously. Negative proportionality was observed between the average changes in core and non-core genes, reflecting reciprocity between the macroscopic robustness of homeostatic genes and plasticity of regulator genes. The proportion coefficient between those genes is represented by their number ratio, as in the "lever principle", whereas the decrease in the ratio results in a transition from perfect to partial adaptation, in which only a portion of the core genes exhibits robustness against environmental changes. This reciprocity between robustness and plasticity was satisfied throughout the evolutionary course, imposing an evolutionary constraint. This result suggests a simple macroscopic law for the adaptation characteristic in evolved complex biological networks.

An Alternative Approach for Assessing Biogenicity

The search for signs of life in the ancient rock record, extreme terrestrial environments, and other planetary bodies requires a well-established, universal, and unambiguous test of biogenicity. This is notably true for cellular remnants of microbial life, since their relatively simple morphologies resemble various abiogenic microstructures that occur in nature. Although lists of qualitative biogenicity criteria have been devised, debates regarding the biogenicity of many ancient microfossils persist to this day. We propose here an alternative quantitative approach for assessing the biogenicity of putative microfossils. In this theoretical approach, different hypotheses-involving biology or not and depending on the geologic setting-are put forward to explain the observed objects. These hypotheses correspond to specific types of microstructures/systems. Using test samples, the morphology and/or chemistry of these systems are then characterized at the scale of populations. Morphologic parameters include, for example, circularity, aspect ratio, and solidity, while chemical parameters could include elementary ratios (e.g., N/C ratio), isotopic enrichments (e.g., δ13C), or chirality (e.g., molar proportion of stereoisomers), among others. Statistic trends distinguishing the different systems are then searched for empirically. The trends found are translated into "decision spaces" where the different systems are quantitatively discriminated and where the potential microfossil population can be located as a single point. This approach, which is formulated here on a theoretical level, will solve several problems associated with the classical qualitative criteria of biogenicity. Most importantly, it could be applied to reveal the existence of cellular life on other planets, for which characteristics of morphology and chemical composition are difficult to predict.

Toward understanding of evolutionary constraints: experimental and theoretical approaches

Although organisms have diversified remarkably through evolution, they do not exhibit unlimited variability. During evolution, the phenotypic changes do not occur at random; instead, they are directional and restricted by the constraints imposed on them. Despite the perceived importance of characterizing the unevenness of these changes, studies on evolutionary constraints have been primarily qualitative in nature. In this review, we focus on the recent studies of evolutionary constraints, which are based on the quantification of high-dimensional phenotypic and genotypic data. Furthermore, we present a theoretical analysis that enables us to predict evolutionary constraints on the basis of phenotypic fluctuation, modeled on the fluctuation-response relationship in statistical physics. The review lays emphasis on the tight interactions between experimental and theoretical analyses in evolutionary biology that will contribute to a better understanding of evolutionary constraints.

Physical Constraints on Epistasis

Living systems evolve one mutation at a time, but a single mutation can alter the effect of subsequent mutations. The underlying mechanistic determinants of such epistasis are unclear. Here, we demonstrate that the physical dynamics of a biological system can generically constrain epistasis. We analyze models and experimental data on proteins and regulatory networks. In each, we find that if the long-time physical dynamics is dominated by a slow, collective mode, then the dimensionality of mutational effects is reduced. Consequently, epistatic coefficients for different combinations of mutations are no longer independent, even if individually strong. Such epistasis can be summarized as resulting from a global nonlinearity applied to an underlying linear trait, that is, as global epistasis. This constraint, in turn, reduces the ruggedness of the sequence-to-function map. By providing a generic mechanistic origin for experimentally observed global epistasis, our work suggests that slow collective physical modes can make biological systems evolvable.

Dimensional Reduction in Evolving Spin-Glass Model: Correlation of Phenotypic Responses to Environmental and Mutational Changes

The evolution of high-dimensional phenotypes is investigated using a statistical physics model consisting of interacting spins, in which phenotypes, genotypes, and environments are represented by spin configurations, interaction matrices, and external fields, respectively. We found that phenotypic changes upon diverse environmental change and genetic variation are highly correlated across all spins, consistent with recent experimental observations of biological systems. The dimension reduction in phenotypic changes is shown to be a result of the evolution of the robustness to thermal noise, achieved at the replica symmetric phase.