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Single-cell RNA-seq analysis identifies the atlas of lymph fluid and reveals a sepsis-related T cell subset.
The lymphoid cycle serves as a sentinel of the immune response, yet the cell subtypes and immune properties within lymph fluid remain unclear. This study describes a comprehensive characterization of immune cells in rat lymph fluid using single-cell RNA sequencing, identifying a unique subset of CD4+ T cells (CD4_Icos) that suppresses inflammation in early sepsis. Trajectory analysis reveals that CD4+Icos+ T cells can differentiate into regulatory T cells (Tregs). Transferring CD4+Icos+ T cells alleviates CLP-induced organ injury, while CD4+ Icos-knockout (KO) mice show reduced Treg numbers, increased inflammation, and higher mortality. Further experiments identify Npas2 as an Icos-specific transcription factor regulating Icos expression and promoting the differentiation of CD4+Icos+ T cells. Clinical data show a negative correlation between ICOS expression in CD4+ T cells and clinical outcomes in septic patients. These findings highlight the protective role of CD4+ T cells in modulating immune responses and mitigating sepsis progression.
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Single-cell RNA-seq analysis decodes the kidney microenvironment induced by polystyrene microplastics in mice receiving a high-fat diet.
In recent years, the environmental health issue of microplastics has aroused an increasingly significant concern. Some studies suggested that exposure to polystyrene microplastics (PS-MPs) may lead to renal inflammation and oxidative stress in animals. However, little is known about the essential effects of PS-MPs with high-fat diet (HFD) on renal development and microenvironment. In this study, we provided the single-cell transcriptomic landscape of the kidney microenvironment induced by PS-MPs and HFD in mouse models by unbiased single-cell RNA sequencing (scRNA-seq). The kidney injury cell atlases in mice were evaluated after continued PS-MPs exposure, or HFD treated for 35 days. Results showed that PS-MPs plus HFD treatment aggravated the kidney injury and profibrotic microenvironment, reshaping mouse kidney cellular components. First, we found that PS-MPs plus HFD treatment acted on extracellular matrix organization of renal epithelial cells, specifically the proximal and distal convoluted tubule cells, to inhibit renal development and induce ROS-driven carcinogenesis. Second, PS-MPs plus HFD treatment induced activated PI3K-Akt, MAPK, and IL-17 signaling pathways in endothelial cells. Besides, PS-MPs plus HFD treatment markedly increased the proportions of CD8+ effector T cells and proliferating T cells. Notably, mononuclear phagocytes exhibited substantial remodeling and enriched in oxidative phosphorylation and chemical carcinogenesis pathways after PS-MPs plus HFD treatment, typified by alterations tissue-resident M2-like PF4+ macrophages. Multispectral immunofluorescence and immunohistochemistry identified PF4+ macrophages in clear cell renal cell carcinoma (ccRCC) and adjacent normal tissues, indicating that activate PF4+ macrophages might regulate the profibrotic and pro-tumorigenic microenvironment after renal injury. In conclusion, this study first systematically revealed molecular variation of renal cells and immune cells in mice kidney microenvironment induced by PS-MPs and HFD with the scRNA-seq approach, which provided a molecular basis for decoding the effects of PS-MPs on genitourinary injury and understanding their potential profibrotic and carcinogenesis in mammals.
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Single-cell integration and multi-modal profiling reveals phenotypes and spatial organization of neutrophils in colorectal cancer.
The immune composition of the tumor microenvironment has a major impact on the therapy response in patients with colorectal cancer. Here, we built an atlas with 4.27 million single cells from 1,670 patient samples and complemented it with single-cell profiles from 266 patients, including cells with low mRNA content, spatial transcriptomics from 3.7 million cells, and protein profiles from 0.7 million cells. The analysis of the atlas allows tumor classification into immune desert, B cell enriched, T cell enriched, and myeloid cell enriched immune phenotypes. Within the myeloid compartment, we identify consensus myeloid gene expression programs with four immunomodulatory programs, and uncover a subpopulation of neutrophils with antigen-presenting properties. Moreover, functional experiments using patient-derived organoids show KRAS-dependent pro-tumorigenic polarization of neutrophils. Further, spatial multimodal single-cell profiling reveals niches with IL-1 signaling-based neutrophil-fibroblast interaction. Finally, using an orthotopic mouse model, we show that cancer-derived signals modify neutrophil production in the bone marrow.
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Comprehensive cell atlas of the first-trimester developing human brain.
The adult human brain comprises more than a thousand distinct neuronal and glial cell types, a diversity that emerges during early brain development. To reveal the precise sequence of events during early brain development, we used single-cell RNA sequencing and spatial transcriptomics and uncovered cell states and trajectories in human brains at 5 to 14 postconceptional weeks (pcw). We identified 12 major classes that are organized as ~600 distinct cell states, which map to precise spatial anatomical domains at 5 pcw. We described detailed differentiation trajectories of the human forebrain and midbrain and found a large number of region-specific glioblasts that mature into distinct pre-astrocytes and pre-oligodendrocyte precursor cells. Our findings reveal the establishment of cell types during the first trimester of human brain development.
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A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain.
The mammalian brain consists of millions to billions of cells that are organized into many cell types with specific spatial distribution patterns and structural and functional properties1-3. Here we report a comprehensive and high-resolution transcriptomic and spatial cell-type atlas for the whole adult mouse brain. The cell-type atlas was created by combining a single-cell RNA-sequencing (scRNA-seq) dataset of around 7 million cells profiled (approximately 4.0 million cells passing quality control), and a spatial transcriptomic dataset of approximately 4.3 million cells using multiplexed error-robust fluorescence in situ hybridization (MERFISH). The atlas is hierarchically organized into 4 nested levels of classification: 34 classes, 338 subclasses, 1,201 supertypes and 5,322 clusters. We present an online platform, Allen Brain Cell Atlas, to visualize the mouse whole-brain cell-type atlas along with the single-cell RNA-sequencing and MERFISH datasets. We systematically analysed the neuronal and non-neuronal cell types across the brain and identified a high degree of correspondence between transcriptomic identity and spatial specificity for each cell type. The results reveal unique features of cell-type organization in different brain regions-in particular, a dichotomy between the dorsal and ventral parts of the brain. The dorsal part contains relatively fewer yet highly divergent neuronal types, whereas the ventral part contains more numerous neuronal types that are more closely related to each other. Our study also uncovered extraordinary diversity and heterogeneity in neurotransmitter and neuropeptide expression and co-expression patterns in different cell types. Finally, we found that transcription factors are major determinants of cell-type classification and identified a combinatorial transcription factor code that defines cell types across all parts of the brain. The whole mouse brain transcriptomic and spatial cell-type atlas establishes a benchmark reference atlas and a foundational resource for integrative investigations of cellular and circuit function, development and evolution of the mammalian brain.
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Single-cell RNA-seq reveals immune cell heterogeneity and increased Th17 cells in human fibrotic skin diseases.
BACKGROUND: Fibrotic skin disease represents a major global healthcare burden, characterized by fibroblast hyperproliferation and excessive accumulation of extracellular matrix components. The immune cells are postulated to exert a pivotal role in the development of fibrotic skin disease. Single-cell RNA sequencing has been used to explore the composition and functionality of immune cells present in fibrotic skin diseases. However, these studies detected the gene expression of all cells in fibrotic skin diseases and did not enrich immune cells. Thus, the precise immune cell atlas in fibrotic skin diseases remains unknown. In this study, we plan to investigate the intricate cellular landscape of immune cells in keloid, a paradigm of fibrotic skin diseases. METHODS: CD45+ immune cells were enriched by fluorescence-activated cell sorting. Single-cell RNA sequencing was used to analyze the cellular landscape of immune cells in keloid and normal scar tissues. Ki-67 staining, a scratch experiment, real-time PCR, and Western blotting were used to explore the effect of the Th17 cell supernatant on keloid fibroblasts. RESULTS: Our findings revealed the intricate cellular landscape of immune cells in fibrotic skin diseases. We found that the percentage of Th17 cells was significantly increased in keloids compared to normal scars. All the subclusters of macrophages and dendritic cells (DCs) showed similar proportions between keloid samples and normal scar samples. However, upregulated genes in keloid M1 macrophages, M2 macrophages, and cDC2 are associated with the MHC class II protein complex assembly and antigen assembly, indicating that macrophages and cDC2 are active in keloids. Functional studies suggested that the supernatant of Th17 cells could promote proliferation, collagen expression, and migration of keloid fibroblasts through interleukin 17A. Importantly, increased Th17 cells are also found in other fibrotic skin diseases, such as hypertrophic scars and scleroderma, suggesting this represents a broad mechanism for skin fibrosis. CONCLUSION: In summary, we built a single-cell atlas of fibrotic skin diseases in this study. In addition, we explored the function of Th17 cell-fibroblast interaction in skin fibrosis. These findings will help to understand fibrotic skin disease pathogenesis in depth and identify potential targets for fibrotic skin disease treatment.
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Ex vivo tissue perturbations coupled to single-cell RNA-seq reveal multilineage cell circuit dynamics in human lung fibrogenesis.
Pulmonary fibrosis develops as a consequence of failed regeneration after injury. Analyzing mechanisms of regeneration and fibrogenesis directly in human tissue has been hampered by the lack of organotypic models and analytical techniques. In this work, we coupled ex vivo cytokine and drug perturbations of human precision-cut lung slices (hPCLS) with single-cell RNA sequencing and induced a multilineage circuit of fibrogenic cell states in hPCLS. We showed that these cell states were highly similar to the in vivo cell circuit in a multicohort lung cell atlas from patients with pulmonary fibrosis. Using micro-CT-staged patient tissues, we characterized the appearance and interaction of myofibroblasts, an ectopic endothelial cell state, and basaloid epithelial cells in the thickened alveolar septum of early-stage lung fibrosis. Induction of these states in the hPCLS model provided evidence that the basaloid cell state was derived from alveolar type 2 cells, whereas the ectopic endothelial cell state emerged from capillary cell plasticity. Cell-cell communication routes in patients were largely conserved in hPCLS, and antifibrotic drug treatments showed highly cell type-specific effects. Our work provides an experimental framework for perturbational single-cell genomics directly in human lung tissue that enables analysis of tissue homeostasis, regeneration, and pathology. We further demonstrate that hPCLS offer an avenue for scalable, high-resolution drug testing to accelerate antifibrotic drug development and translation.
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Integrated analysis of single-cell RNA-seq and bulk RNA-seq to unravel the molecular mechanisms underlying the immune microenvironment in the development of intestinal-type gastric cancer.
Intestinal-type gastric cancer (IGC) is the most frequent type of gastric cancer in high-incidence populations. The early stages of IGC growth successively include nonatrophic gastritis (NAG), chronic atrophic gastritis (CAG) and intestinal metaplasia (IM). However, the mechanisms of IGC development through these stages remain unclear. For this study, single-cell RNA-seq data related to IGC were downloaded from the GEO database, and immune cells of the tumor microenvironment (TME) were annotated using R software. Changes in the proportion of immune cells and altered cell-to-cell interactions were explored at different disease stages using R software, with a focus on plasma cells. Additionally, IGC samples from the TCGA database were used for immune cell infiltration analysis, and a Cox proportional risk regression model was constructed to identify possible prognostic genes. The results indicated that for precancerous lesions, interactions between immune cells were mainly dominated by chemokines to stimulate the infiltration and activation of immune cells. In tumors, intercellular movement of upregulated molecules and amplified signals were associated with the tumor necrosis factor family and immunosuppression to escape immune surveillance and promote tumor growth. Regarding prognostic analysis, IGLC3, IGLV1-44, IGKV1-16, IGHV3-21, IGLV1-51, and IGLV3-19 were found to be novel biomarkers for IGC. Our analysis of the IGC single-cell atlas together with bulk transcriptome data contributes to understanding TME heterogeneity at the molecular level during IGC development and provides insights for elucidating the mechanism of IGC and discovering novel targets for precise therapy.
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T-cell exhaustion signatures characterize the immune landscape and predict HCC prognosis via integrating single-cell RNA-seq and bulk RNA-sequencing.
BACKGROUND: Hepatocellular carcinoma (HCC), the third most prevalent cause of cancer-related death, is a frequent primary liver cancer with a high rate of morbidity and mortality. T-cell depletion (TEX) is a progressive decline in T-cell function due to continuous stimulation of the TCR in the presence of sustained antigen exposure. Numerous studies have shown that TEX plays an essential role in the antitumor immune process and is significantly associated with patient prognosis. Hence, it is important to gain insight into the potential role of T cell depletion in the tumor microenvironment. The purpose of this study was to develop a trustworthy TEX-based signature using single-cell RNA-seq (scRNA-seq) and high-throughput RNA sequencing, opening up new avenues for evaluating the prognosis and immunotherapeutic response of HCC patients. METHODS: The International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) databases were used to download RNA-seq information for HCC patients. The 10x scRNA-seq. data of HCC were downloaded from GSE166635, and UMAP was used for clustering descending, and subgroup identification. TEX-related genes were identified by gene set variance analysis (GSVA) and weighted gene correlation network analysis (WGCNA). Afterward, we established a prognostic TEX signature using LASSO-Cox analysis. External validation was performed in the ICGC cohort. Immunotherapy response was assessed by the IMvigor210, GSE78220, GSE79671, and GSE91061cohorts. In addition, differences in mutational landscape and chemotherapy sensitivity between different risk groups were investigated. Finally, the differential expression of TEX genes was verified by qRT-PCR. RESULT: 11 TEX genes were thought to be highly predictive of the prognosis of HCC and substantially related to HCC prognosis. Patients in the low-risk group had a greater overall survival rate than those in the high-risk group, according to multivariate analysis, which also revealed that the model was an independent predictor of HCC. The predictive efficacy of columnar maps created from clinical features and risk scores was strong. CONCLUSION: TEX signature and column line plots showed good predictive performance, providing a new perspective for assessing pre-immune efficacy, which will be useful for future precision immuno-oncology studies.
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Spatiotemporal transcriptome atlas of human embryos after gastrulation.
The comprehensive spatiotemporal atlas of gene expression during early human embryonic development is critical for insights into embryogenesis1, organogenesis2 and disease origins3,4. Here, leveraging Stereo-seq technology, we generated spatial transcriptomic profiles across 77 sagittal sections of 13 whole-human embryos ranging from Carnegie stage 12 to 23, integrated with single-nucleus RNA sequencing to elucidate gene expression patterns within defined cellular contexts, revealing the cellular heterogeneity that drives organ-specific differentiation. Our study has established a regulatory profile for the development of 50 organs and 198 substructures, and identified potential tissue-identity regulators. Of note, it uncovered previously uncharacterized gene functions in cardiac and brain development. The atlas not only substantiates and refines the current understanding of human organ development but also highlights key organs susceptible to genetic disorders. Furthermore, we characterized the allelic gene expression within specific organs at different developmental stages. This work presents a comprehensive compilation of genome-wide gene expression profiles for each spatially defined cell population, which can be visualized as a spatial display of the embryonic transcriptional landscape. These results offer the most thorough delineation to data of the spatiotemporal transcriptomic dynamics of human organogenesis.