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Zuccato, C.

Publications and source records attributed to Zuccato, C..

3 recordsLinked to original sources

Structure-function dissection of huntingtin exon 1 identifies a PRD-driven modifier of neuronal toxicity in Huntington's disease

The Huntingtin gene (HTT) contains a conserved, yet expandable CAG repeat within exon 1. While the pathogenic expansion in Huntingtons Disease (HD) is well studied, the role of surrounding domains remains unclear. Using genome-edited mini-organoids and neurons, we dissected HTT exon 1 and found species-specific toxicity: the human variant caused more severe deficits than the mouse. Swapping the proline-rich domain (PRD) - the most divergent region - revealed its key role: the mouse PRD mitigated, while the human PRD worsened neuronal phenotypes. Omics profiling showed that pathogenic human exon 1 induced broad protein dysregulation, largely reversed by mouse PRD replacement. Bioinformatics implicated the actin cytoskeleton and transcriptional coactivator MKL2/MRTFB. We validated MKL2/MRTFB dysregulation in HD models and showed that restoring its expression rescued neuronal abnormalities. These findings highlight the PRDs contribution to HD toxicity and point to MKL2/MRTFB and the cytoskeleton as candidate mediators.

neuroscience↗

Precision single-cell profiling of Circulating Tumour Cells: novel markers and data-driven characterization by CTCeek

Circulating tumour cells (CTCs) represent a minimally invasive method for monitoring cancer evolution in patients. CTCs are nowadays commonly isolated using antibodies against EPCAM protein. A key limitation regards the extent of EPCAM-negative CTCs, such as those that undergo EMT or whose tumour of origin is EPCAM-low or negative. We studied 3,302 RNA single-cell transcriptomes reported as CTCs in public repositories. Using copy number variation and cell type-specific markers, we discriminated bona fide CTCs from contaminating blood cells, often mislabelled as CTCs. The integration of bona fide CTCs and PBMCs, from multiple datasets, allowed us to identify novel markers, such as CLDN4, CLDN7, EFNA1 and TACSTD2 for epithelial CTCs, KCNK15 and LY6K for epithelial B CTCs, and ITGB4 for both epithelial B and mesenchymal CTCs. We revealed PODXL, AXL, CAV1, and TGM2 as markers of mesenchymal CTCs, which might be undetectable using anti-EPCAM antibodies, and TM4SF1 as universal marker, expressed in all CTC subclasses. Additionally, we found platelets to be physically associated with the epithelial A, but not with the epithelial B or the mesenchymal subtypes. Finally, we developed and implemented CTCeek, the first web-based and public reference tool that automatically annotates bona fide CTCs from scRNA-sequencing profiles.

cancer biology↗

Brain regional identity and cell type specificity landscape of human cortical organoid models

In vitro models of corticogenesis using mouse and human pluripotent stem cells (PSC) have greatly improved our understanding of human brain development and disease. Among these, 3D cortical organoid systems are able to recapitulate some aspects of in vivo cytoarchitecture of the developing cortex. Here, we tested three cortical organoid protocols for brain regional identity, cell type-specificity and neuronal maturation. Overall all protocols gave rise to organoids that displayed a time-dependent expression of neuronal maturation genes such as those involved in the establishment of synapses and neuronal function. We showed that three months old cortical organoids showed a pattern of gene expression that resembled late human embryonic cortex. Comparatively, directed differentiation methods without WNT activation gave rise to the highest degree of cortical regional identity in brain organoids. Whereas, default "intrinsic" brain organoid differentiation produced the broadest range of cell types such as neurons, astrocytes and hematopoietic-lineage derived microglia cells of the brain. These results suggest that cortical organoid models produce diverse outcomes in terms of brain regional identity and cell type specificity and emphasize the importance of selecting the correct model for the right application.

neuroscience↗