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Taglietti, V.

Publications and source records attributed to Taglietti, V..

3 recordsLinked to original sources

Distinct extracellular matrix states uncouple collagen accumulation from pathological fibrosis in Duchenne muscular dystrophy

Fibrosis severity is routinely inferred from collagen abundance, although whether collagen quantity determines pathological fibrosis remains unclear. In Duchenne muscular dystrophy (DMD), chronic muscle injury and inflammation drive extracellular matrix accumulation, making these processes difficult to disentangle. We exploit sarcospan overexpression in mdx mice, a model of DMD (mdxTG), which improves membrane integrity and muscle function despite persistent matrix remodeling. mdxTG muscle accumulates more collagen than mdx yet lacks its dense macrophage-rich scars. Matrisome proteomics and spatial transcriptomics reveal compositionally and spatially distinct matrix states, while decellularized mdxTG matrix protects myotubes from membrane damage relative to mdx matrix. Despite these differences, both dystrophic matrices remain stiff and induce nuclear YAP in fibro-adipogenic progenitors. Verteporfin suppresses collagen production and reduces fibrosis in vivo, while nuclear YAP is increased in FAPs from patients with DMD. Thus, collagen abundance alone does not define pathological fibrosis; matrix organization, biological activity, and mechanosignaling distinguish functionally distinct fibrotic states.

physiology↗

Cell-Hub: a graphical interface for end-to-end single-cell RNA sequencing analysis

Single-cell and single-nucleus RNA sequencing have become increasingly widespread, creating a significant demand for accessible analysis tools in research laboratories. Despite this need, the bioinformatics expertise required for such analyses remains rare. Cell-Hub addresses this gap by enabling single-cell data analysis for all researchers, regardless of computational background. Cell-Hub is a comprehensive, free, and open-source framework built on R/Shiny and distributed as a Docker image, integrating Seurat 5, CellChat 2, and Monocle 3 within a unified graphical interface. It supports all essential steps of single-cell RNA-seq analysis: data loading, quality control, normalization, clustering, multi-dataset integration, differential expression, and biomarker detection. Cell-Hub further incorporates ligand-receptor interaction inference powered by GaspouDB, a consolidated database of 11,563 mouse and 9,604 human interactions derived from CellChat, CellPhoneDB, CellTalkDB, and MultiNicheNet as well as trajectory inference via Monocle 3 and spatial transcriptomics analysis for 10X Visium datasets. All analyses produce publication-ready visualizations with flexible export options. By integrating these analytical frameworks into a single, intuitive interface requiring no programming expertise, Cell-Hub represents a significant step toward democratizing single- cell genomics for the broader research community.

bioinformatics↗

Structural bases for Nuclear Factor 1-X activation and DNA recognition. Prototypic insight into the NFI transcription factor family

Nuclear Factor I (NFI) proteins were first identified in adenovirus DNA replication and later as regulators of gene transcription, stem cell proliferation, and differentiation. They play key roles in development, cancer and congenital disorders. Within the NFI family, NFI-X is critical for neural stem cell biology, hematopoiesis, muscle development, muscular dystrophies and oncogenesis. Here, we present the first structural characterization of the NFI transcription factor, NFI-X, both alone and bound to its consensus palindromic DNA site. Our analyses reveal a novel, MH1-like fold within NFI-X DNA-binding domain (DBD) and identify crucial structural determinants for activity, such as a Zn{superscript 2} binding site, dimeric assembly, activation mechanism and DNA-binding specificity. Given the >95% sequence identity within the NFI DBDs, our structural data are prototypic for the entire family; a NFI Rosetta Stone that allows decoding a wealth of biochemical and functional data and provides a precise target for drug design in a wider disease context.

biochemistry↗