Target morphology and cell memory: a model of regenerative pattern formation

Abstract

Despite the growing body of work on molecular components required for regenerative repair, we still lack a deep understanding of the ability of some animal species to regenerate their appropriate complex anatomical structure following damage. A key question is how regenerating systems know when to stop growth and remodeling – what mechanisms implement recognition of correct morphology that signals a stop condition? In this work, we review two conceptual models of pattern regeneration that implement a kind of pattern memory. In the first one, all cells communicate with each other and keep the value of the total signal received from the other cells. If a part of the pattern is amputated, the signal distribution changes. The difference fromthe original signal distribution stimulates cell proliferation and leads to pattern regeneration, in effect implementing an error minimization process that uses signaling memory to achieve pattern correction. In the second model, we consider a more complex pattern organization with different cell types. Each tissue contains a central (coordinator) cell that controls the tissue and communicates with the other central cells. Each of them keeps memory about the signals received from other central cells. The values of these signals depend on the mutual cell location, and the memory allows regeneration of the structure when it is modified. The purpose of these models is to suggest possible mechanisms of pattern regeneration operating on the basis of cell memory which are compatible with diverse molecular implementation mechanisms within specific organisms.

Neural control of body-plan axis in regenerating planaria

“…Crucially, this regenerating organism exhibits complex behaviors and properties functioning well beyond the level of a single cell. It can maintain body-plan homeostasis under normal circumstances, including body-wide allometric remodeling during growth and shrinkage depending on availability of food, while also detecting injury to precisely reproduce missing features, and stopping regeneration once the correct body structure (the target morphology ) has been restored [3, 4]. Therefore, a deep and functional understanding of regeneration requires, not only an account of single cell activities such as gene expression [5], but also of the regenerating organism as an intricate system exhibiting complex dynamics and coordination over multiple levels of scale.…”

Classical Sorting Algorithms as a Model of Morphogenesis: self-sorting arrays reveal unexpected competencies in a minimal model of basal intelligence

“…While biology does have important examples of global control and top-down signaling (reviewed in (McMillen et al, 2021;Pezzulo & Levin, 2016)), many biological outcomes result from the activities of distributed, local agents. This perspective is implemented in many examples (Bessonov et al, 2015;Dalle Nogare & Chitnis, 2020;Doursat et al, 2013;Glen et al, 2019;Newgreen et al, 2013;Pascalie et al, 2016;Thorne et al, 2007) of using agent-based modeling in biology (although the actual agency possessed by those components is typically assumed to be low).…”

Bistability of somatic pattern memories: stochastic outcomes in bioelectric circuits underlying regeneration

“…This is relevant to problems of regeneration and development because it suggests the use of techniques from cognitive science and computational neuroscience to understand the information flow that leads to cell group behaviours [15]. We conjectured [16][17][18] that anatomical homeostasis is a process that relies on pattern memory-biophysical properties stored in tissues that encode, to some rough level of detail, important aspects of the anatomy towards which cells will build (and which, once achieved, causes further activity to stop). Cognitive neuroscience studies neural circuits that implement memory and goal-directed behaviour.…”