A Single-Cell Transcriptomic Atlas Characterizes Age-Related Changes of Murine Cranial Stem Cell Niches
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ABSTRACT:
PROVIDER: PRJNA984713 | ENA |
REPOSITORIES: ENA
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Project description:The bone tissue undergoes constant turnover, which relies on skeletal stem cells (SSCs) and/or mesenchymal stem cells (MSCs) and their niches. SSCs/MSCs and their perivascular niche within the bone marrow are well characterized in long bones. As for cranial bones, besides bone marrow, the suture mesenchyme has been identified as a unique niche for SSCs/MSCs of craniofacial bones. However, a comprehensive study of the two different cranial stem cell niches at single-cell resolution is still lacking. In addition, during the progression of aging, age-associated changes in cranial stem cell niches and resident cells remain uncovered. In this study, we investigated age-related changes in cranial stem cell niches via single-cell RNA sequencing (scRNA-seq).
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Project description:The craniofacial bones provide structural support for the skull and accommodate the vulnerable brain tissue with a protective cavity. The bone tissue undergoes constant turnover, which relies on skeletal stem cells (SSCs) and/or mesenchymal stem cells (MSCs) and their niches. SSCs/MSCs and their perivascular niche within the bone marrow are well characterized in long bones. As for cranial bones, besides bone marrow, the suture mesenchyme has been identified as a unique niche for SSCs/MSCs of craniofacial bones. However, a comprehensive study of the two different cranial stem cell niches at single-cell resolution is still lacking. In addition, during the progression of aging, age-associated changes in cranial stem cell niches and resident cells remain uncovered. In this study, we investigated age-related changes in cranial stem cell niches via single-cell RNA sequencing (scRNA-seq). The transcriptomic profiles and cellular compositions have been delineated, indicating alterations of the cranial bone marrow microenvironment influenced by inflammaging. Moreover, we identified a senescent mesenchymal cell subcluster and several age-related immune cell subclusters by reclustering and pseudotime trajectory analysis, which might be closely linked to inflammaging. Finally, differentially expressed genes (DEGs) and cell-cell communications were analyzed during aging, revealing potential regulatory factors. Overall, this work highlights the age-related changes in cranial stem cell niches, which deepens the current understanding of cranial bone and suture biology and may provide therapeutic targets for antiaging and regenerative medicine.
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Project description:Understanding kidney disease relies upon defining the complexity of cell types and states, their associated molecular profiles, and interactions within tissue neighborhoods. We applied multiple single-cell or -nucleus assays (>400,000 nuclei/cells) and spatial imaging technologies to a broad spectrum of healthy reference (45 donors) and diseased (48 patients) kidneys. This has provided a high resolution cellular atlas of 51 main cell types that include rare and novel cell populations. The multi-omic approach provides detailed transcriptomic profiles, epigenomic regulatory factors, and spatial localizations spanning the entire kidney. We further define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive or maladaptive repair, transitioning and degenerative states. Molecular signatures permitted localization of these states within injury neighborhoods using spatial transcriptomics, while large-scale 3D imaging analysis (~1.2 million neighborhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents the most comprehensive benchmark of cellular states, neighborhoods, outcome-associated signatures, and publicly available interactive visualizations.
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Project description:Understanding kidney disease relies upon defining the complexity of cell types and states, their associated molecular profiles, and interactions within tissue neighborhoods. We applied multiple single-cell or -nucleus assays (>400,000 nuclei/cells) and spatial imaging technologies to a broad spectrum of healthy reference (45 donors) and diseased (48 patients) kidneys. This has provided a high resolution cellular atlas of 51 main cell types that include rare and novel cell populations. The multi-omic approach provides detailed transcriptomic profiles, epigenomic regulatory factors, and spatial localizations spanning the entire kidney. We further define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive or maladaptive repair, transitioning and degenerative states. Molecular signatures permitted localization of these states within injury neighborhoods using spatial transcriptomics, while large-scale 3D imaging analysis (~1.2 million neighborhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents the most comprehensive benchmark of cellular states, neighborhoods, outcome-associated signatures, and publicly available interactive visualizations.
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