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Londono-Vallejo, J.-A.

Publications and source records attributed to Londono-Vallejo, J.-A..

3 recordsLinked to original sources

autoFISH - a modular toolbox for sequential smFISH experiments

Fluorescence in situ hybridization (FISH) allows for spatial and quantitative profiling of gene expression by visualizing individual RNA molecules. Here, we introduce automated FISH (autoFISH), a comprehensive toolbox to conduct automated single molecule FISH (smFISH) experiments that is both cost-effective and versatile. This includes detailed plans for constructing the necessary equipment, open-source software for control, reliable experimental protocols, and analysis workflows based on our FISH-quant analysis package. Validation experiments with both cell lines and tissue samples confirmed the systems robustness. We demonstrate standard and amplified smFISH, along with a modified protocol for tissue clearing that enhances nuclear retention while preserving background reduction efficiency.

molecular biology↗

DNA damage-induced PARP/ALC1 activation leads to Epithelial-to-Mesenchymal transition stimulating homologous recombination.

Epithelial-to-mesenchymal transition (EMT) allows cancer cells to metastasize while acquiring resistance to apoptosis and to chemotherapeutic agents with significant implications in patients prognosis and survival. Despite its clinical relevance, the mechanisms initiating EMT during cancer progression remain poorly understood. We demonstrate that DNA damage triggers EMT by activating PARP and the PARP-dependent chromatin remodeler ALC1 (CHD1L). We show that this activation directly facilitates the access to chromatin of EMT transcriptional factors (TFs) which then initiate cell reprogramming. We also show that EMT-TFs bind to the RAD51 promoter to stimulate its expression and to promote DNA repair by recombination. Importantly, a clinically relevant PARP inhibitor totally reversed or prevented EMT in response to DNA damage while resensitizing tumor cells to other genotoxic agents. Overall, our observations shed light on the intricate relationship between EMT, DNA damage response and PARP inhibitors, providing valuable insights for future therapeutic strategies in cancer treatment.

cancer biology↗

A point cloud segmentation framework for image-based spatial transcriptomics

Recent progress in image-based spatial RNA profiling enables to spatially resolve tens to hundreds of distinct RNA species with high spatial resolution. It hence presents new avenues for comprehending tissue organization. In this context, the ability to assign detected RNA transcripts to individual cells is crucial for downstream analyses, such as in-situ cell type calling. Yet, accurate cell segmentation can be challenging in tissue data, in particular in the absence of a high-quality membrane marker. To address this issue, we introduce ComSeg, a segmentation algorithm that operates directly on single RNA positions and that does not come with implicit or explicit priors on cell shape. ComSeg is thus applicable in complex tissues with arbitrary cell shapes. Through comprehensive evaluations on simulated datasets, we show that ComSeg outperforms existing state-of-the-art methods for in-situ single-cell RNA profiling and cell type calling. On experimental data, our method also demonstrates proficiency in estimating RNA profiles that align with established scRNA-seq datasets. Importantly, ComSeg exhibits a particular efficiency in handling complex tissue, positioning it as a valuable tool for the community.

bioinformatics↗