Darwin’s agential materials: evolutionary implications of multiscale competency in developmental biology

Abstract

A critical aspect of evolution is the layer of developmental physiology that operates between the genotype and the anatomical phenotype. While much work has addressed the evolution of developmental mechanisms and the evolvability of specific genetic architectures with emergent complexity, one aspect has not been sufficiently explored: the implications of morphogenetic problem-solving competencies for the evolutionary process itself. The cells that evolution works with are not passive components: rather, they have numerous capabilities for behavior because they derive from ancestral unicellular organisms with rich repertoires. In multicellular organisms, these capabilities must be tamed, and can be exploited, by the evolutionary process. Specifically, biological structures have a multiscale competency architecture where cells, tissues, and organs exhibit regulative plasticity—the ability to adjust to perturbations such as external injury or internal modifications and still accomplish specific adaptive tasks across metabolic, transcriptional, physiological, and anatomical problem spaces. Here, I review examples illustrating how physiological circuits guiding cellular collective behavior impart computational properties to the agential material that serves as substrate for the evolutionary process. I then explore the ways in which the collective intelligence of cells during morphogenesis affect evolution, providing a new perspective on the evolutionary search process. This key feature of the physiological software of life helps explain the remarkable speed and robustness of biological evolution, and sheds new light on the relationship between genomes and functional anatomical phenotypes.

Evolutionary Implications of Multi-Scale Intelligence

“…A fascinating body of work exists around the question of how neural and non-neural problem-solving capacities evolved, and how neuro-behavioral intelligence affects evolution [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31] . However, we and others have previously suggested that somatic competency pre-dates neural intelligence [32][33][34] , and has a bi-directional interaction with the evolutionary and developmental process 1,3,35 . Thus, here we address the second half of the evolution-intelligence spiral: how are evolutionary processes affected by the competency of the material?…”

“…Through a computational lens, such a competency transfer would also allow, as soon as the structural part of the genome is reliable enough, to re-purpose the system's competency to adapt to other, independent tasks, and thus may facilitate the in biology ubiquitous effect of polycomputing in related systems 123 . This all illustrates that an agential material 1,94 , or more precisely a substrate composed of competent parts, can have significant effects on the process of evolution and evolvability, especially for morphogenesis tasks. We thus conclude that, if competent parts are available, evolution prefers exploiting competency over direct encoding -if the environment requires competency at all (see discussion in section III C).…”

“…The quality of each individual in an evolutionary population of NCAs ( 10) is evaluated via a phenotypic fitness score, quantifying the deviation of the assumed cell types from a target pattern. Based on the fitness scores of a particular generation of NCAs, the genotypes of potentially betteradapted successor generations are successively sampled by the EA, closing the loop (1) and forming the largest scale in our system, an evolutionary lineage (11). Eventually, on a meta-scale (12), we compare the efficiency of the evolutionary process at different system parameters (I-III), i.e., at different competency-and noise levels, by analyzing the fitness trajectories of statistically independent lineages evaluated at the same system parameters.…”

“…We aim in this contribution to investigate the evolutionary implications of biologically inspired multi-scale competency architectures 1,94 . Thus, we compare two qualitatively different evolutionary processes both with the objective of morphogenetic pattern formation but whose genomes either (i) directly encode phenotypic features of a two-dimensional target pattern (cf.…”

“…This in turn suggests that the actual progress of evolution should be significantly impacted by the degree and kind of competency in the developmental architecture. Prior work has suggested a powerful feedback loop between the evolution of morphogenetic problem-solving and the effects of these competencies on the ability of evolutionary search to produce adaptive complexity 1,35,95 . Here, we construct and analyze a new model of evolving morphogenesis, to study how different competency architectures within and among cells impact evolutionary metrics such as rate, robustness to noise, and transferability to new environmental challenges.…”