The patterns of Fig Fig emerge at the multicellular level

The patterns of Fig. 1, Fig. 2 emerge at the multicellular level; their dynamics can only be understood by integrating different magnitudes and feedback loops in networks incorporating the coupling between biochemical and bioelectrical signals (see Fig. 6, Fig. 8). Interestingly, this might also be the case of carcinogenesis and regenerative processes [5,15,89,119,[134], [135], [136]]. In this review, we have emphasized that the basic magnitudes introduced in the highly simplified schemes of Fig. 4, Fig. 5 do not work in isolation: they should be integrated, both at the single-cell (Fig. 4) and multicellular (Fig. 5) levels, into functional feedbacks (Fig. 6, Fig. 8) defined over different spatio-temporal scales [[32], [33], [34], [35], [36],117]. The classical chemically-oriented view is that genetic targets are activated by specific ion concentrations, disregarding thus the role of the electric potential as an important biological magnitude. In many cases, however, it does not matter which particular ion channels are used provided that the correct voltage window needed for a target morphological outcome is established; see e.g. the eye induction example of Fig. 1 as well as Ref. [89] on reprogramming Heme Colorimetric Assay Kit and tissue patterning via bioelectrical pathways. Moreover, extensive plant and animal data show that crucial transduction machinery can be influenced by membrane potentials; see e.g. the KRAS clustering mechanism described in Ref. [102] as well as the well-known cases of the voltage-sensitive phosphatases and voltage-gated calcium and potassium channels. The basic elements that modulate the cell electrical signals are the ion channels located on the membrane surface. Usually, these aqueous channels are regulated by the potential difference established through the membrane [13]. In addition, the voltage-gated gap junctions between neighboring cells and the external cellular microenvironment permit intercellular coupling and communication. We have attempted a preliminary, tentative description of the interplay between basic genetic mechanisms and cell electrical potentials using a system of coupled differential equations. The equations can simulate the bioelectric dynamics of the multicellular ensemble under different experimental conditions (Fig. 6, Fig. 7, Fig. 8). Given the generic depolarizing/polarizing nature of the channels considered, the results obtained should be of qualitative value [[32], [33], [34], [35], [36]]. Indeed, the map of cell electric potentials can influence the spatio-temporal distribution of signaling molecules such as serotonin [136] and it is then conceivable that polarized and depolarized cells may show different downstream genetic processes in a multicellular domain. Note that the membrane potential can also influence the insertion of specific ion channels in the cell membrane as well as other biomechanical effects [102]. Thus, transcriptional and post-translational mechanisms could be indirectly influenced by this bioelectrical magnitude. The theoretical results of Fig. 6 (model of Fig. 4, Fig. 5) and 8 (BETSE computational framework) suggest that externally acting on a small number of target ion channels could modify the polarization state of multicellular domains [[32], [33], [34], [35], [36]], in qualitative agreement with previous experimental results [54,55,100,101,136]. Weakly coupled network models suggest also that acting on a minimum number of key gap junctions could modulate intercellular communication [100,121]. In a similar but much more simplified way, the biomimetic nanochannels showing sensing and electrical rectification are the synthetic counterpart of the voltage-gated ion channels; they can also implement a variety of functionalities and control procedures in nanofluidic circuits [[137], [138], [139]]. Interestingly, the model predictions concerning the role of polarizing/ depolarizing channels and pumps on membrane potentials are falsifiable by acting directly on the channel protein transcription and post-translational gating, e.g. by optogenetics, channel blocking with specific molecules or ions, and changes in the external concentration of the particular ion that is transported through the channel (see Fig. 1 and Refs. [4, 6–9, 14, 15, 52–55, 64, 76, 81, 85, 86, 92]). Other experimental proposals which can clarify the extent to which voltage controls normal pattern formation consider the expression, spatial distribution, and post-translational activation and blocking of voltage-gated gap junctions (see Fig. 2 and Refs. [10, 31, 34, 35, 56, 62, 63, 104, 113, 114]). In addition, model predictions could also be tested in the case of channelopathies –defects in ion channel protein genes which give very specific patterning defects, providing thus loss-of-function data that clearly indicate the key regulators of “normal” pattern formation; see in particular Refs. [75, 76] for the case of craniofacial morphogenesis. By changing endogenous patterns, changes in gene expression and anatomy result [75,76], which suggests that these patterns are important here. Note also that the above experimental procedures do not rely on the external application of high electric fields: the bioelectrical states of the cells are modified within the physiological range of membrane potentials. In this sense, “non-physiological” perturbations would not be necessary.