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Single-cell RNA sequencing reveals the ameliorative effects of Kai-Xin-San on depression via regulating neuroplasticity and inflammation in the hypothalamus of rats.
Kai-Xin-San (KXS) is widely used as a traditional Chinese herbal formula for treating depression, while its regulatory mechanisms on the hypothalamic microenvironment remain unclear. This study systematically elucidated the molecular mechanisms by which KXS alleviates chronic unpredictable mild stress (CUMS)-induced depression in rats through single-cell RNA sequencing (scRNA-seq) combined with behavioral and molecular biology experiments. Behavioral tests revealed that KXS significantly ameliorated depressive-like behaviors in CUMS-induced rats. The scRNA-seq analysis of 45,482 hypothalamic cells isolated from control rats, CUMS-induced rats, KXS-treated rats and fluoxetine-treated rats revealed nine major cell types. The transcriptional atlas of these cells revealed that CUMS reduced the numbers of astrocytes and adipocytes, while increasing the number of proinflammatory microglia and endothelial cells. KXS intervention restored astrocyte subpopulations (Astro_1), upregulated the protein expression of mitochondrial metabolism-related enzyme CPT1A, reduced the M1/M2 microglial polarization ratio, suppressed the protein expression of proinflammatory cytokines TNF-α and CXCL10, and elevated the protein expression of anti-inflammatory TGF-β. KXS remodeled hypothalamic intercellular communication networks, enhancing astrocyte-neuron interactions. The protein expression of neuronal nuclear antigen, microtubule-associated protein 2, synapsin, and postsynaptic density-95 in hypothalamus was significantly increased in KXS group, which reflected changes in the number of neurons and altered synaptic plasticity. Our study is the first to demonstrate that KXS can alleviate depression through the inhibition of proactivity, restoration of astrocytic mitochondrial metabolism, and reshaping of neuro-astrocyte interaction networks to enhance synaptic plasticity through scRNA-seq in hypothalamus. These results provide a theoretical foundation for the development of hypothalamic microenvironment-targeted antidepressant strategies.
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Microdissection of the gene expression codes driving nephrogenesis.
The kidney represents an excellent model system for learning the principles of organogenesis. It is intermediate in complexity, and employs many commonly used developmental processes. As such, kidney development has been the subject of intensive study, using a variety of techniques, including in situ hybridization, organ culture and gene targeting, revealing many critical genes and pathways. Nevertheless, proper organogenesis requires precise patterns of cell type specific differential gene expression, involving very large numbers of genes. This review is focused on the use of global profiling technologies to create an atlas of gene expression codes driving development of different mammalian kidney compartments. Such an atlas allows one to select a gene of interest, and to determine its expression level in each element of the developing kidney, or to select a structure of interest, such as the renal vesicle, and to examine its complete gene expression state. Novel component specific molecular markers are identified, and the changing waves of gene expression that drive nephrogenesis are defined. As the tools continue to improve for the purification of specific cell types and expression profiling of even individual cells it is possible to predict an atlas of gene expression during kidney development that extends to single cell resolution.
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Transcript-guided targeted cell enrichment for scalable single-nucleus RNA sequencing.
Large-scale single-cell atlases have revealed many aging- and disease-associated cell types, yet these populations are often underrepresented in heterogeneous tissues, limiting detailed molecular analyses. To address this, we developed EnrichSci-a scalable, microfluidics-free platform that combines hybridization chain reaction RNA fluorescence in situ hybridization (FISH) with combinatorial indexing to profile single-nucleus transcriptomes of target cell types with full gene-body coverage. Applied to oligodendrocytes in the aging mouse brain, EnrichSci uncovered aging-associated molecular dynamics across distinct oligodendrocyte subtypes, revealing both shared and subtype-specific gene expression changes. Additionally, we identified aging-associated exon-level signatures missed by conventional gene-level analyses, highlighting post-transcriptional regulation as a critical dimension of cell-state dynamics in aging. By coupling transcript-guided enrichment with a scalable sequencing workflow, EnrichSci provides a versatile approach to decode dynamic regulatory landscapes in diverse cell types from complex tissues.
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Single-Cell RNA Sequencing of Childhood Ependymoma Reveals Neoplastic Cell Subpopulations That Impact Molecular Classification and Etiology.
Ependymoma (EPN) is a brain tumor commonly presenting in childhood that remains fatal in most children. Intra-tumoral cellular heterogeneity in bulk-tumor samples significantly confounds our understanding of EPN biology, impeding development of effective therapy. We, therefore, use single-cell RNA sequencing, histology, and deconvolution to catalog cellular heterogeneity of the major childhood EPN subgroups. Analysis of PFA subgroup EPN reveals evidence of an undifferentiated progenitor subpopulation that either differentiates into subpopulations with ependymal cell characteristics or transitions into a mesenchymal subpopulation. Histological analysis reveals that progenitor and mesenchymal subpopulations co-localize in peri-necrotic zones. In conflict with current classification paradigms, relative PFA subpopulation proportions are shown to determine bulk-tumor-assigned subgroups. We provide an interactive online resource that facilitates exploration of the EPN single-cell dataset. This atlas of EPN cellular heterogeneity increases understanding of EPN biology.
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Benchmarking strategies for cross-species integration of single-cell RNA sequencing data.
The growing number of available single-cell gene expression datasets from different species creates opportunities to explore evolutionary relationships between cell types across species. Cross-species integration of single-cell RNA-sequencing data has been particularly informative in this context. However, in order to do so robustly it is essential to have rigorous benchmarking and appropriate guidelines to ensure that integration results truly reflect biology. Here, we benchmark 28 combinations of gene homology mapping methods and data integration algorithms in a variety of biological settings. We examine the capability of each strategy to perform species-mixing of known homologous cell types and to preserve biological heterogeneity using 9 established metrics. We also develop a new biology conservation metric to address the maintenance of cell type distinguishability. Overall, scANVI, scVI and SeuratV4 methods achieve a balance between species-mixing and biology conservation. For evolutionarily distant species, including in-paralogs is beneficial. SAMap outperforms when integrating whole-body atlases between species with challenging gene homology annotation. We provide our freely available cross-species integration and assessment pipeline to help analyse new data and develop new algorithms.
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Single-cell RNA sequencing reveals extensive fibrotic remodeling and pathogenic chondrocyte subpopulations in developmental dysplasia of the hip.
BACKGROUND: Developmental dysplasia of the hip (DDH) is a common pediatric orthopedic disorder that predisposes affected children to early-onset osteoarthritis (OA), yet the cellular heterogeneity and fibrotic remodeling of acetabular cartilage are poorly understood. METHODS: We performed single-cell RNA sequencing (scRNA-seq) on acetabular cartilage obtained from three children with DDH and two age-matched controls, thereby generating a transcriptomic atlas of 10,550 chondrocytes. RESULTS: Nine chondrocyte subpopulations were identified, including four previously unrecognized subsets (C1-C4). Compared with controls, DDH cartilage exhibited a marked shift toward fibrocartilage-like phenotypes, characterized by upregulation of fibrotic and matrix-remodeling genes, such as COL1A1, COL1A2, COL3A1, POSTN, MMP13, and MMP14, together with downregulation of key cartilage matrix genes, including COL2A1, ACAN, CHAD, and CNMD. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed enrichment of extracellular matrix (ECM) organization and related pathways. Pseudotime analysis demonstrated a trajectory toward fibrotic and proliferative states, and CellChat analysis identified enhanced collagen and TGF-β signaling among fibrotic subsets. These transcriptional findings were validated by polymerase chain reaction (PCR), immunohistochemistry (IHC), and histological staining. CONCLUSIONS: These findings reveal molecular remodeling of cartilage obtained from dislocated hips in DDH and identify fibrosis-associated chondrocyte subpopulations that may contribute to early degenerative changes.
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A multi-dataset single-cell meta-analysis of human keloid skin across Asian, Black and White populations reveals endothelial and mesenchymal programs linked to ethnic disparities.
INTRODUCTION: Keloid is a fibroproliferative scar with marked ethnic disparities, disproportionately affecting Asian and Black populations. Single-cell RNA sequencing (scRNA-seq) studies have mapped keloid pathology, but cross-study differences complicate generalization. We performed a meta-analysis to identify composition and transcriptional programs associated with keloid across ethnicities. METHODS: We aggregated human skin scRNA-seq datasets containing keloid and healthy samples with documented ethnicity (Asian, Black, White). After quality control and batch integration (scVI/scANVI), we annotated cell types and subtypes. Differential abundance was estimated with scCODA, Milo, and propeller. Pseudobulk differential expression was meta-analyzed using random-effects models. Ligand-receptor signaling was inferred with CellChat/NicheNet. RESULTS: The harmonized atlas comprised 112 donors, 147 samples, and 487,293 cells from 8 studies. Keloid demonstrated higher proportions of vascular endothelial cells and fibroblasts across all methods. Ethnicity-stratified analysis revealed endothelial expansion in Asian and Black relative to White populations, while fibroblast expansion was greater in White keloids. Endothelial subtyping showed increased post-capillary venules and arteriolar states. Fibroblast analysis revealed expansion of mesenchymal/ADAM12+ and pro-inflammatory populations. Meta-analysis implicated TGF-β/SMAD, integrin/FAK, and YAP/TAZ mechanotransduction pathways as candidate pathogenic programs warranting functional validation. CONCLUSION: Cross-study synthesis identifies shared and ethnicity-stratified endothelial and fibroblast programs in keloid. Expansion of post-capillary venules and ADAM12+ fibroblasts provides candidate therapeutic targets pending functional validation and a framework for understanding ethnic disparities in keloid formation.
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Single-Cell Transcriptomic Atlas of Gingival Mucosa in Type 2 Diabetes.
The oral gingival barrier is a constantly stimulated and dynamic environment where homeostasis is often disrupted, resulting in inflammatory periodontal diseases. Type 2 diabetes (T2D) has been reported to be associated with gingival barrier dysfunction, but the effect and underlying mechanism are inconclusive. Herein, we performed single-cell RNA sequencing (scRNA-seq) of gingiva from leptin receptor-deficient mice (db/db) to examine the gingival heterogeneity in the context of T2D. Periodontal health of control mice is characterized by populations of Krt14+-expressing epithelial cells and Col1a1+-fibroblasts mediating immune homeostasis primarily through the enrichment of innate lymphoid cells. The db/db gingiva exhibited decreased epithelial/stromal ratio and dysfunctional barrier. We further observed stromal, particularly fibroblast immune hyperresponsiveness, linked to the recruitment of myeloid-derived cells at the db/db gingiva. Both scRNA-seq and histological analysis suggested the inflammatory signaling between fibroblasts and neutrophils as a potential driver of diabetes-induced periodontal damage. Notably, the "immune-like" stromal cells were wired toward the induction of gingival IL-17A hyperresponsiveness in db/db mice. Our work reveals that the "immune-like" fibroblasts with transcriptional diversity are involved in the innate immune homeostasis at the diabetic gingiva. It highlights a potentially significant role of these cell types in its pathogenesis.
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Fibroblasts in the tumor microenvironment: heterogeneity and dynamic interactions in tumor progression revealed by spatial transcriptomics.
Cancer-associated fibroblasts (CAFs) constitute the most abundant and functionally versatile stromal component of the tumor microenvironment (TME), with their phenotype and spatial location jointly governing tumor growth, immune evasion, metastasis, and therapeutic resistance. While traditional single-cell RNA sequencing has unveiled CAF transcriptional heterogeneity, it forfeits crucial tissue-contextual information; the advent of high-resolution spatial transcriptomics (ST)—encompassing platforms such as 10xVisium, Slide-seq, Stereo-seq, and MERFISH—now overcomes this limitation by preserving native tissue architecture while simultaneously capturing whole-transcriptome data and single-cell spatial coordinates, enabling comprehensive mapping of CAF “spatial atlases.” Recent literature has consolidated CAFs into five functional subtypes: myofibroblastic CAFs (myCAFs), inflammatory CAFs (iCAFs), antigen-presenting CAFs (apCAFs), matrix-remodeling CAFs (matCAFs), and proliferative CAFs (pCAFs), each exhibiting spatial preferences and dynamic plasticity within tumor cores, hypoxic niches, invasive fronts, and tertiary lymphoid structures. Distinct subpopulations form sub-micron-scale interaction networks with SPP1+ macrophages, CXCL13+ CD8+ T cells, natural killer cells, or endothelial cells to orchestrate either immune exclusion or activation. Multi-cancer investigations in colorectal, pancreatic, hepatic, and lung malignancies demonstrate that peri-tumoral enrichment of POSTN+ myCAFs predicts immune exclusion and shortened survival, whereas therapeutic targeting of CAF-immune or CAF-cancer signaling axes—such as IL-34/CSF1R, TGF-β/LOXL2, and JAG1/NOTCH1—can reverse immunotherapy resistance. Looking forward, integrative multi-omics, subcellular-resolution in-vivo tracking, and AI-driven spatial interaction modeling will further decode CAF spatial phenotypes and expedite their incorporation into precision oncology frameworks.
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An atlas of transcriptional, chromatin accessibility, and surface marker changes in human mesoderm development.
Mesoderm is the developmental precursor to myriad human tissues including bone, heart, and skeletal muscle. Unravelling the molecular events through which these lineages become diversified from one another is integral to developmental biology and understanding changes in cellular fate. To this end, we developed an in vitro system to differentiate human pluripotent stem cells through primitive streak intermediates into paraxial mesoderm and its derivatives (somites, sclerotome, dermomyotome) and separately, into lateral mesoderm and its derivatives (cardiac mesoderm). Whole-population and single-cell analyses of these purified populations of human mesoderm lineages through RNA-seq, ATAC-seq, and high-throughput surface marker screens illustrated how transcriptional changes co-occur with changes in open chromatin and surface marker landscapes throughout human mesoderm development. This molecular atlas will facilitate study of human mesoderm development (which cannot be interrogated in vivo due to restrictions on human embryo studies) and provides a broad resource for the study of gene regulation in development at the single-cell level, knowledge that might one day be exploited for regenerative medicine.