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  • It is widely acknowledged that a

    2021-09-23

    It is widely acknowledged that a significant gap exists between the increasingly detailed knowledge of subcellular mechanisms and the ability to control large-scale anatomy. Radical advances in regenerative medicine require approaches aimed at taming the fundamental complexity of cellular regulation; one promising direction is the identification of master regulators – unique control nodes in regulatory processes that can be exploited to trigger coordinated patterning outcomes that are too complex to micromanage bottom-up. Due to their central role in decision-making processes for both neural and non-neural cells, bioelectric pathways provide a fertile ground to identify new control points for complex pattern regulation [1,2]. For example, because of the mean field nature of the electric potential, it could be possible to act on the scale of whole Bufalin without invoking a detailed molecular description [6,8,11,[32], [33], [34], [35], [36]], suggesting a tractable strategy to the control of global patterning outcomes. Conceptually, a practical understanding of the different levels of description is crucial in complex systems composed of many interacting units. Statistical Thermodynamics shows that instead of attempting a detailed molecular description of each individuality, a judicious use of average magnitudes can unveil the basic mechanisms characteristics of systems composed by a high number of individualities [6,7,31,33,35]. In a similar but much more complex way, cells are coupled together and their individual properties should then be influenced by ensemble-level magnitudes [[31], [32], [33],35,37]. This fact suggests that the identification and external modulation of appropriate average magnitudes can allow some control of the multicellular states that emerge from the combination of many single-cell states [7,[31], [32], [33], [34], [35]]. The progressive transcriptional dynamics involving proteins specified by the genome defines the molecular hardware utilized for single-cell behavior and cell-cell interactions in multicellular ensembles. However, classical epigenetics reveals remarkable plasticity of the patterning process [38]; phenomena of trophic memory in deer antler regeneration [39] and other examples of plasticity suggest that evolution has provided a way around the powerful inverse problem of knowing how to alter subcellular rules to achieve specific emergent large-scale outcomes. What aspects of cellular biophysics or chemistry can be re-written to change global outcomes [40,41]? Recent experiments with flatworms show that even without genomic editing [6,10,31], stable changes can be made to an organism's target morphology (the pattern to which it regenerates upon damage, and the pattern that – once achieved – causes further growth and remodeling to cease). The stable modification of an organism's regenerative target morphology by transient physiological stimuli suggests that critical parameters such as electric potentials may provide convenient control knobs for pattern (re)specification in therapeutic contexts. It is essential to understand the genome, which establishes the basic biological circuitry, as well as the physiological dynamics implemented by the circuits that guide patterning decisions. Neural networks and electronic devices are good examples showing that the control of electric potentials and currents allows efficient local modulation of the circuitry, which is needed to achieve full functionality [6,7]. It is well established that the ion channels that regulate the membrane potential are crucial to biological processes such as embryogenesis, regeneration, and tumorigenesis [5,8,9,11,14,15]. The problem for biomedicine is how to take control of these processes: the complex interplay between biochemical and bioelectrical networks is not still understood at the same level of description as are the basic genetic mechanisms. When attempting to modify multicellular states, the final outcome to be expected should depend on both the multiple characteristics of single-cell states and the intercellular connectivity. At this point, the problem to be solved is not only technical but also conceptual [6,7,31,32,34,36]. In this context, studying the interplay between biochemical and bioelectrical networks in model animals [6,10,31] and theoretical simulations [[32], [33], [34], [35], [36]] might contribute to develop new conceptual frameworks for predictive control in biomedical and bioengineering settings.