Identification of Distinct, Quantitative Pattern Classes from Emergent Tissue-Scale hiPSC Bioelectric Properties

Area of Science:

• Biophysics
• Developmental Biology
• Regenerative Medicine

Background:

• Bioelectric signals and endogenous electric fields are crucial for controlling cell fates and anatomical boundaries during embryogenesis and regeneration.
• The precise mechanisms by which these bioelectric signals achieve robust multiscale patterning remain incompletely understood.
• Computational modeling offers a powerful approach to predict in vitro patterning and investigate the roles of cellular bioelectric components.

Purpose of the Study:

• To adapt and apply an image pattern recognition algorithm for analyzing simulated bioelectric patterns in non-excitable cells.
• To compare simulated bioelectric patterns with experimental microscopy data of membrane potential in human induced pluripotent stem cell (iPSC) colonies.
• To extend the computational model to predict patterning in novel co-culture conditions with varying ionic fluxes.

Main Methods:

• Modification of an existing image pattern recognition algorithm to identify unique spatial features in simulated bioelectric patterns.
• Application of the algorithm to analyze simulated membrane potential (Vmem) patterns under different cell culture conditions.
• Validation of the model by comparing simulated patterns with in vitro microscopy images of human iPSC colonies and genetically modified co-cultures.

Main Results:

• The modified algorithm successfully distinguished unique spatial features of simulated non-excitable bioelectric patterns.
• The algorithm accurately recapitulated experimentally observed spatial features of membrane potential in human iPSC colonies.
• The model's predictions were validated in a novel co-culture system, demonstrating its ability to handle complex ionic flux scenarios.

Conclusions:

• The study provides a validated computational framework for modeling multiscale spatial characteristics in multicellular systems.
• The findings contribute to understanding the molecular basis of membrane potential heterogeneity in non-excitable cells.
• This work enables improved strategies for engineered bioelectrical tissue design and regenerative medicine applications.