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Vattulainen, M.

Publications and source records attributed to Vattulainen, M..

3 recordsLinked to original sources

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.

molecular biology↗

Decoding murine corneal epithelial specification and homeostasis by single-cell spatial transcriptomics with scRNA-seq enrichment

Investigation of gene regulatory programs underlying corneal epithelial cell specification and homeostasis is essential for understanding how the cornea maintains vision. Here, we describe the use of true single-cell resolution spatial transcriptomics (ST), enriched with full-tissue single-cell RNAseq (SC), to improve spatial resolution and enhance cell cluster size up to 65-fold and per-cell transcriptomic depth up to 17-fold. This enabled cell type specification across the full differentiation trajectory from limbal stem cells (LSC) to superficial corneal epithelium and identification of an activated signature (Atf3, Zfp36, Gsta4 and Dapl1) marking differentiation-primed states across multiple cell types, including a major activated intermediate epithelium (AIE) population. Validation using ST data from murine corneas at different postnatal ages and multiple human SC datasets confirms a large AIE population, which spatial localization and transcriptomic profiling suggest is an active intermediate state distinct from quiescent wing cells. Sub-clustering further revealed early (Sox9, Hes1), proliferative (Mki67, Top2a) and mature (Ccdn1, Dapl1) transient amplifying cell subpopulations and four LSC subpopulations, including putative active (Atf3, Socs3, Zfp36), quiescent (Gpha2, Ifitm3, Cd63) and Apoe-specific. Direct ST-to-SC comparison revealed enhanced axonal processes and genes (Sema3f, Sema 4d, Pax6) and cell-cell adhesion and cell-matrix markers (Itgb4, Tns4, Tjp3) in ST data, suggesting cell dissociation from tissue in SC masks epithelial innervation, adhesion and barrier functions. Our findings identify and localize key transcriptional programs in situ, prompting a re-evaluation of epithelial states in scRNA-seq data.

cell biology↗

Deciphering the heterogeneity of differentiating hPSC-derived corneal limbal stem cells through single-cell RNA-sequencing

A comprehensive understanding of the human pluripotent stem cell (hPSC) differentiation process stands as a prerequisite for the development hPSC-based therapeutics. In this study, single-cell RNA-sequencing (scRNA-seq) was performed to decipher the heterogeneity during differentiation of three hPSC lines towards corneal limbal stem cells (LSCs). The scRNA-seq data revealed nine clusters encompassing the entire differentiation process, among which five followed the anticipated differentiation path of LSCs. The remaining four clusters were previously undescribed cell states that were annotated as either mesodermal-like or undifferentiated subpopulations, and their prevalence was hPSC line-dependent. Distinct cluster-specific marker genes identified in this study were confirmed by immunofluorescence analysis and employed to purify hPSC-derived LSCs, which effectively minimized the variation in the line-dependent differentiation efficiency. In summary, scRNA-seq offered molecular insights into the heterogeneity of hPSC-LSC differentiation, allowing a data-driven strategy for consistent and robust generation of LSCs, essential for future advancement toward clinical translation. HighlightsO_LIhPSCs to LSCs spans epithelial, mesodermal, and undifferentiated cell states. C_LIO_LIscRNA-seq reveals the cell line-dependent differentiation heterogeneity. C_LIO_LIITGA6 and AREG can be used to select pure LSC-like subpopulation. C_LI

cell biology↗