Cellular Signaling Pathways as Plastic, Proto-cognitive Systems: Implications for Biomedicine

Abstract

Many aspects of health and disease are modeled using the abstraction of a “pathway” – a set of protein or other subcellular activities with specified functional linkages between them. This metaphor is a paradigmatic case of a deterministic, mechanistic framework that focuses biomedical intervention strategies on altering the members of this network or the up/down-regulation links between them – rewiring the molecular hardware. However, protein pathways and transcriptional networks share important properties with neural networks and related dynamical systems, which implies that they can exhibit interesting and unexpected capabilities such as trainability (memory) and information processing in a context-sensitive manner. Specifically, they may be amenable to manipulation via their history of stimuli (equivalent to experiences, in behavioral science). If true, this would enable a new class of biomedical interventions that targets aspects of the dynamic physiological “software” implemented by pathways and gene-regulatory networks. Here, we propose an expanded view of pathways from the perspective of basal cognition. We review clinical and laboratory data supporting the idea that a broader understanding of pathways (and how they process contextual information across scales) is a limiting factor for progress in many areas of physiology and neurobiology. We argue that a fuller understanding of the functionality and tractability of pathways must go beyond a focus on the mechanistic details of their structure, to encompass their physiological history and embedding within higher levels of organization in the organism, with numerous implications for data science addressing health and disease. Exploiting tools and concepts from behavioral and cognitive sciences is not just a philosophical stance on biochemical processes; at stake is a new roadmap for overcoming the limitations of today’s pharmacological strategies and for the inference of future therapeutic interventions impacting a wide range of disease states.

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

“…Because the inverse problem is not generally solvable, this view locks in a model of evolution limited to searching the genotype space (which may be extremely rugged, due to its nonlinear relationship to the phenotype space). It also limits workers in bioengineering and regenerative medicine to exclusively targeting the molecular hardware in hopes of improving system-level outcomes (which in turn results in the difficulties with drug discovery [ 160 ]).…”

“…Specific impacts of the above ideas will go far beyond evolutionary biology, for example, to applications in regenerative medicine which will increasingly exploit the decision-making capabilities of cells and tissues, in addition to traditional bottom-up molecular rewiring [ 160 ]. Beyond the life sciences, engineering is now heavily reliant on evolutionary approaches to design [ 287 – 289 ], and robust future robotics and AI architectures must mimic the multiscale competency architecture to achieve (and surpass) the functionality of natural systems.…”

Darwin’s Agential Materials: evolutionary implications of multi-scale competency in developmental biology

“…Because the inverse problem is not generally solvable, this view locks in a model of evolution limited to searching the genotype space (which may be extremely rugged, due to its nonlinear relationship to the phenotype space). It also limits workers in bioengineering and regenerative medicine to exclusively targeting the molecular hardware in hopes of improving system-level outcomes (which in turn results in the difficulties with drug discovery [156]).…”

“…Specific impacts of the above ideas will go far beyond evolutionary biology, for example to applications in regenerative medicine which will increasingly exploit the decision-making capabilities of cells and tissues, in addition to traditional bottom-up molecular rewiring [156]. Beyond the life sciences, engineering is now heavily reliant on evolutionary approaches to design [278][279][280], and robust future robotics and AI architectures must mimic the multiscale competency architecture in order to achieve (and surpass) the functionality of natural systems.…”

Stress Sharing as Cognitive Glue for Collective Intelligences: a computational model of stress as a coordinator for morphogenesis

“…Understanding how bodies navigate anatomical morphospace, including the nature and limits of reliability, the possible failure modes, and the optimal intervention strategies is crucial for advances in evolutionary developmental biology, the bioengineering of synthetic life forms, the biomedicine of birth defects and regenerative therapeutics, and adaptive robotics [24,25]. This specifically requires models of how the behaviors of individual cells scale up to adaptive responses at the level of the entire body.…”