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Thuilliez, C.

Publications and source records attributed to Thuilliez, C..

2 recordsLinked to original sources

Molecular determinants of cardiac lymphatic dysfunction in a chronic pressure-overload model

Cardiac lymphatics have emerged as potential targets in cardiovascular diseases (CVDs). However, we recently reported that despite extensive lymphatic expansion during experimental cardiac pressure-overload, lymphatic drainage remained insufficient. To unravel the cellular and molecular mechanisms underlying lymphatic dysfunction in CVDs, we applied cardiac single-cell (sc) analyses in a murine heart failure model. Transaortic constriction (TAC), in C57BL/6J and BALB/c mice, was used to model chronic pressure-overload-induced cardiac hypertrophy and heart failure, respectively. Cardiac lymphatic (LEC) and blood vascular (BECs) endothelial cells were analyzed by scRNAseq (10XGenomics). Lymphatic targets were validated by immunohistochemistry and wholemount-imaging, and in vitro using human LEC cultures. We identified three distinct cardiac lymphatic subpopulations, capillary (LEC1), precollector (LEC2), and valvular (LEC3) clusters, and several BECs clusters, including venous BEC (vBEC). Chronic pressure-overload led to expansion of lymphatic capillaries and loss of valves in BALB/c, but not C75BL6/J. Analysis of differentially expressed genes (DEG) post-TAC revealed reduction only in BALB/c of lymphatic cell-junction components. In contrast, LEC expression of anchoring filaments, immune cell-adhesion molecules, and chemokines was preserved, or increased, indicating functional lymphatic-mediated immune cell uptake post-TAC. Interestingly, around 35% of DEGs identified in cardiac LECs post-TAC were similarly altered in interleukin (IL)-1{beta}-stimulated human LECs. In conclusion, loss of lymphatic valves and dysregulated lymphatic barrier properties may underly poor drainage capacity during pressure-overload, despite potent lymphangiogenesis and preserved LEC immune attraction. Further studies are needed to address how to restore lymphatic health to accelerate resolution of both inflammation and edema in CVDs.

cell biology↗

CellsFromSpace: A versatile tool for spatial transcriptomic data analysis with reference-free deconvolution and guided cell type/activity annotation

Spatial transcriptomics involves capturing the transcriptomic profiles of millions of cells within their spatial contexts, enabling the analysis of cell crosstalk in healthy and diseased organs. However, spatial transcriptomics also raises new computational challenges for analyzing multidimensional data associated with spatial coordinates. In this context, we introduce a novel framework called CellsFromSpace. This framework allows users to analyze various commercially available technologies without relying on a single-cell reference dataset. Based on the independent component analysis, CellsFromSpace decomposes spatial transcriptomic data into components that represent distinct cell types or activities. Here, we demonstrate that CellsFromSpace outperforms previous reference-free deconvolution tool in term of accuracy and speed, and successfully identify spatially distributed cells as well as rare diffuse cells on datasets from the Visium, Slide-seq, MERSCOPE, and COSMX technologies. The framework provides a user-friendly graphical interface that enables non-bioinformaticians to perform a full analysis and to annotate the components based on marker genes and spatial distributions. Additionally, CellsFromSpace offers the capability to reduce noise or artifacts by component selection and supports analyses on multiple datasets simultaneously. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=189 SRC="FIGDIR/small/555558v2_ufig1.gif" ALT="Figure 1"> View larger version (67K): org.highwire.dtl.DTLVardef@67f64eorg.highwire.dtl.DTLVardef@15ba940org.highwire.dtl.DTLVardef@c4d9a8org.highwire.dtl.DTLVardef@1ade390_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗