Biology subjects

Lima Cunha, D.

Publications and source records attributed to Lima Cunha, D..

4 recordsLinked to original sources

bioRxiv2026

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↗

bioRxiv2024

Prediction of Cell States and Key Transcription Factors of the Human Cornea through Integrated Single-Cell Omics Analyses

The cornea, a transparent tissue composed of multiple layers, allows light to enter the eye. Several single-cell RNA-seq analyses have been performed to explore the cell states and to understand the cellular composition of the human cornea. However, the inconsistences in cell state annotations between these studies complicate the application of these findings in corneal studies. To address this, we integrated single-cell RNA-seq data from four published studies and created a human corneal cell state meta-atlas. This meta-atlas was subsequently evaluated in two applications. First, we developed a machine learning pipeline cPredictor, using the human corneal cell state meta-atlas as input, to annotate corneal cell states. We demonstrated the accuracy of cPredictor and its ability to identify novel marker genes and rare cell states in the human cornea. Furthermore, cPredictor revealed the differences of the cell states between pluripotent stem cell-derived corneal organoids and the human cornea. Second, we integrated the single-cell RNA-seq based cell state meta-atlas with chromatin accessibility data, conducting motif-focused and gene regulatory network analyses. These approaches identified distinct transcription factors driving cell states of the human cornea. The novel marker genes and transcription factors were validated by immunohistochemistry. Overall, this study offers a reliable and accessible reference for profiling corneal cell states, which facilitates future research in cornea development, disease and regeneration. Significance statementThis study creates a human corneal cell state meta-atlas that provides a common nomenclature of cells in the human cornea, through integrating multiple single-cell RNA-seq analyses. Using this meta-atlas, we developed a machine learning pipeline, cPredictor, to accurately annotate cell states in corneal studies using single-cell RNA-seq. Additionally, we identified distinct transcription factors driving cell states through integrating the atlas with chromatin accessibility data. This meta-atlas and the computational tool cPredictor enable future research in cornea development, disease, and regeneration.

cell biology↗

bioRxiv2023

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↗

bioRxiv2022

Restoration of functional PAX6 in aniridia patient iPSC-derived ocular tissue models using repurposed nonsense suppression drugs

Aniridia is a rare, pan-ocular disease causing severe sight loss, with only symptomatic intervention offered to patients. Approximately 40% of aniridia patients present with heterozygous nonsense variants in PAX6, resulting in haploinsufficiency. Translational readthrough inducing compounds (TRIDs) have the ability to weaken the recognition of in-frame premature stop codons (PTCs), permitting full-length protein to be translated. We have established induced pluripotent stem cell (iPSC)-derived 3D optic cups and 2D limbal epithelial stem cell (LESC) models from an aniridia patient with a prevalent PAX6 nonsense mutation. Both in vitro models show reduced PAX6 protein levels, mimicking the disease. Repurposed TRIDs amlexanox and 2,6-diaminopurine (DAP), and positive control compounds ataluren and G418 were tested for their efficiency. Amlexanox was identified as the most promising TRID, increasing full-length PAX6 levels in both models, and rescuing the disease phenotype through normalization of VSX2 and cell proliferation in the optic cups and reduction of ABCG2 protein and SOX10 expression in LESC. This study highlights the significance of patient iPSC-derived cells as a new model system for aniridia and proposes amlexanox as a new putative treatment for nonsense-mediated aniridia.

genetics↗