Abstract:
Bioelectric signals possess the ability to robustly control and manipulate patterning during embryogenesis and tissue-level regeneration. Endogenous local and global electric fields function as a spatial \'pre-pattern\', controlling cell fates and tissue-scale anatomical boundaries; however, the mechanisms facilitating these robust multiscale outcomes are poorly characterized. Computational modeling addresses the need to predict in vitro patterning behavior and further elucidate the roles of cellular bioelectric signaling components in patterning outcomes. Here, we modified a previously designed image pattern recognition algorithm to distinguish unique spatial features of simulated non-excitable bioelectric patterns under distinct cell culture conditions. This algorithm was applied to comparisons between simulated patterns and experimental microscopy images of membrane potential (Vmem) across cultured human iPSC colonies. Furthermore, we extended the prediction to a novel co-culture condition in which cell sub-populations possessing different ionic fluxes were simulated; the defining spatial features were recapitulated in vitro with genetically modified colonies. These results collectively inform strategies for modeling multiscale spatial characteristics that emerge in multicellular systems, characterizing the molecular contributions to heterogeneity of membrane potential in non-excitable cells, and enabling downstream engineered bioelectrical tissue design.
摘要:
生物电信号具有在胚胎发生和组织水平再生期间强有力地控制和操纵模式的能力。内生局部和全局电场作为空间“预模式”,控制细胞命运和组织尺度解剖边界;然而,促进这些稳健的多尺度结果的机制特征不佳。计算模型解决了预测体外图案化行为的需求,并进一步阐明了细胞生物电信号传导成分在图案化结果中的作用。这里,我们修改了先前设计的图像模式识别算法,以区分不同细胞培养条件下模拟的非兴奋生物电模式的独特空间特征。该算法应用于跨培养的人iPSC集落的膜电位(Vmem)的模拟模式和实验显微镜图像之间的比较。此外,我们将预测扩展到一种新的共培养条件,其中模拟了具有不同离子通量的细胞亚群;定义的空间特征在体外用基因修饰的菌落进行了概括。这些结果共同为多细胞系统中出现的多尺度空间特征建模策略提供了信息。表征非兴奋细胞中膜电位异质性的分子贡献,并实现下游工程生物电组织设计。