Mapping heterogeneity drivers in human PSC-derived limbal stem cell differentiation through single-cell multi-modal analysis
Understanding the molecular underpinnings of stem cell differentiation is pivotal for generating appropriate cell types in cell-based therapies. Differentiation of human pluripotent stem cells (PSC) into corneal limbal stem cells offers a promising avenue to regenerate the corneal epithelium. However, current differentiation strategies remain inconsistent in efficiency and yield heterogeneous cell populations that incompletely recapitulate the regenerative properties of donor-derived limbal stem cells. Here, we mapped the molecular landscape of cell states throughout the differentiation process. First, we construct PSC differentiation paths from single-cell RNA sequencing (scRNA-seq) data using the computational framework of optimal transport, identifying on- and off-track cell states toward the limbal stem cell state. Single cell Assay for Transposase-Accessible Chromatin sequencing (scATAC-seq) was performed to profile accessible genomic regions, and subsequently integrated with scRNA-seq data through gene regulatory network analysis to identify key drivers governing the diverse cell states. We showed that genomic enhancers play a major role in cell state determinations. Through this single-cell multi-modal approach, we identified potential transcription factors driving limbal epithelial lineage specification and off-track cell populations. Our findings provide a framework for rational optimization of PSC-derived limbal stem cell generation to advance the development of corneal cell therapies.