Браузер не даёт сохранять данные (например, приватный режим): закладки пропадут после закрытия вкладки.
Поиск статей PubMed
Ключевые слова, автор, журнал, годы — результаты из PubMed, аннотации с переводом на русский, закладки в браузере.
Найдено: 4 932
Страница 274 из 494-
The immunological paradox of tubal ectopic pregnancy: unraveling immune tolerance amidst inflammation via single-cell sequencing.
BACKGROUND: Tubal ectopic pregnancy (TEP) is a common and serious obstetric complication with unclear pathogenesis. This study aims to use single-cell RNA sequencing (scRNA-seq) to analyze immune cell composition and functional changes in implantation sites (IS) and non-implantation sites (NIS) of fallopian tube tissues from TEP patients, exploring potential pathogenesis. METHODS: We performed scRNA-seq on IS and NIS tubal tissues from TEP patients, constructing a high-resolution immune atlas. Differential expression and functional enrichment analysis were applied to reveal functional reprogramming in key immune subsets. RESULTS: We identified a total of 28 cell clusters encompassing 13 major cell types, and T/NK cells and macrophages as the predominant populations. Further subcluster analysis demonstrated CD4⁺ memory T cells (CD4⁺ Tm) enriched at the IS exhibited both pro-inflammatory and immune-tolerant function; CD8⁺ KLRC2⁺ effector T cells and CD8⁺ memory T cells (CD8⁺ Tm) were reduced in proportion and functionally impaired; monocyte numbers increased, contributing to chronic inflammation and abnormal angiogenesis; M1 macrophages decreased while M2 macrophages increased, promoting immune tolerance, angiogenesis, and extracellular matrix remodeling. Therefore, functional reprogramming and altered cellular composition of the TEP immune microenvironment underlie both transient ectopic embryo survival and tubal tissue damage. CONCLUSION: This study reveals the key roles of CD4⁺ Tm cells, CD8⁺ KLRC2⁺ Teff cells, CD8⁺ Tm cells, monocytes, and M1/M2 macrophages, offering insights into the pathogenesis of TEP and potential immunological interventions.
-
Spatial transcriptomics in health and disease.
The ability to localize hundreds of macromolecules to discrete locations, structures and cell types in a tissue is a powerful approach to understand the cellular and spatial organization of an organ. Spatially resolved transcriptomic technologies enable mapping of transcripts at single-cell or near single-cell resolution in a multiplex manner. The rapid development of spatial transcriptomic technologies has accelerated the pace of discovery in several fields, including nephrology. Its application to preclinical models and human samples has provided spatial information about new cell types discovered by single-cell sequencing and new insights into the cell-cell interactions within neighbourhoods, and has improved our understanding of the changes that occur in response to injury. Integration of spatial transcriptomic technologies with other omics methods, such as proteomics and spatial epigenetics, will further facilitate the generation of comprehensive molecular atlases, and provide insights into the dynamic relationships of molecular components in homeostasis and disease. This Review provides an overview of current and emerging spatial transcriptomic methods, their applications and remaining challenges for the field.
-
Genome-wide profiling of circular RNAs, alternative splicing, and R-loops in stem-differentiating xylem of Populus trichocarpa.
Circular RNAs (circRNAs) are a recently discovered type of non-coding RNA derived from pre-mRNAs. R-loops consist of a DNA:RNA hybrid and the associated single-stranded DNA. In Arabidopsis thaliana, circRNA:DNA R-loops regulate alternative splicing (AS) of SEPALLATA3 (SEP3). However, the occurrence and functions of circRNAs and R-loops in Populus trichocarpa are largely unexplored. Here, we performed circRNA-enriched sequencing in the stem-differentiating xylem (SDX) of P. trichocarpa and identified 2,742 distinct circRNAs, including circ-CESA4, circ-IRX7, and circ-GUX1, which are generated from genes involved in cellulose, and hemicellulose biosynthesis, respectively. To investigate the roles of circRNAs in modulating alternative splicing (AS), we detected 7,836 AS events using PacBio Iso-Seq and identified 634 circRNAs that overlapped with 699 AS events. Furthermore, using DNA:RNA hybrid immunoprecipitation followed by sequencing (DRIP-seq), we identified 8,932 R-loop peaks that overlapped with 181 circRNAs and 672 AS events. Notably, several SDX-related circRNAs overlapped with R-loop peaks, pointing to their possible roles in modulating AS in SDX. Indeed, overexpressing circ-IRX7 increased the levels of R-loop structures and decreased the frequency of intron retention in linear IRX7 transcripts. This study provides a valuable R-loop atlas resource and uncovers the interplay between circRNAs and AS in SDX of P. trichocarpa.
-
Systematic analysis of expression signatures of neuronal subpopulations in the VTA.
Gene expression profiling across various brain areas at the single-cell resolution enables the identification of molecular markers of neuronal subpopulations and comprehensive characterization of their functional roles. Despite the scientific importance and experimental versatility, systematic methods to analyze such data have not been established yet. To this end, we developed a statistical approach based on in situ hybridization data in the Allen Brain Atlas and thereby identified specific genes for each type of neuron in the ventral tegmental area (VTA). This approach also allowed us to demarcate subregions within the VTA comprising specific neuronal subpopulations. We further identified WW domain-containing oxidoreductase as a molecular marker of a population of VTA neurons that co-express tyrosine hydroxylase and vesicular glutamate transporter 2, and confirmed their region-specific distribution by immunohistochemistry. The results demonstrate the utility of our analytical approach for uncovering expression signatures representing specific cell types and neuronal subpopulations enriched in a given brain area.
-
HeLa nucleic acid contamination in the cancer genome atlas leads to the misidentification of human papillomavirus 18.
UNLABELLED: We searched The Cancer Genome Atlas (TCGA) database for viruses by comparing non-human reads present in transcriptome sequencing (RNA-Seq) and whole-exome sequencing (WXS) data to viral sequence databases. Human papillomavirus 18 (HPV18) is an etiologic agent of cervical cancer, and as expected, we found robust expression of HPV18 genes in cervical cancer samples. In agreement with previous studies, we also found HPV18 transcripts in non-cervical cancer samples, including those from the colon, rectum, and normal kidney. However, in each of these cases, HPV18 gene expression was low, and single-nucleotide variants and positions of genomic alignments matched the integrated portion of HPV18 present in HeLa cells. Chimeric reads that match a known virus-cell junction of HPV18 integrated in HeLa cells were also present in some samples. We hypothesize that HPV18 sequences in these non-cervical samples are due to nucleic acid contamination from HeLa cells. This finding highlights the problems that contamination presents in computational virus detection pipelines. IMPORTANCE: Viruses associated with cancer can be detected by searching tumor sequence databases. Several studies involving searches of the TCGA database have reported the presence of HPV18, a known cause of cervical cancer, in a small number of additional cancers, including those of the rectum, kidney, and colon. We have determined that the sequences related to HPV18 in non-cervical samples are due to nucleic acid contamination from HeLa cells. To our knowledge, this is the first report of the misidentification of viruses in next-generation sequencing data of tumors due to contamination with a cancer cell line. These results raise awareness of the difficulty of accurately identifying viruses in human sequence databases.
-
An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampus.
The hippocampus contains many unique cell types, which serve the structure's specialized functions, including learning, memory and cognition. These cells have distinct spatial organization, morphology, physiology, and connectivity, highlighting the importance of transcriptome-wide profiling strategies that retain cytoarchitectural organization. Here, we generated spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from adjacent tissue sections of the anterior human hippocampus in ten adult neurotypical donors to define molecular profiles for hippocampal cell types and spatial domains. Using non-negative matrix factorization (NMF) and label transfer, we integrated these data by defining gene expression patterns within the snRNA-seq data and inferring their expression in the SRT data. We identified NMF patterns that captured transcriptional variation across neuronal cell types and indicated that the response of excitatory and inhibitory postsynaptic specializations were prioritized in different SRT spatial domains. We used the NMF and label transfer approach to leverage existing rodent datasets, identifying patterns of activity-dependent transcription and subpopulations of dentate gyrus granule cells in our SRT dataset that may be predisposed to participate in learning and memory ensembles. Finally, we characterized the spatial organization of NMF patterns corresponding to non-cornu ammonis pyramidal neurons and identified snRNA-seq clusters mapping to distinct regions of the retrohippocampus, to three subiculum layers, and to a population of presubiculum neurons. To make this comprehensive molecular atlas accessible to the scientific community, both raw and processed data are freely available, including through interactive web applications.
-
A comprehensive single-cell atlas of three centenarian cohorts unveils unique natural killer cell signatures and enhanced mutual interactions among peripheral immune cells.
BACKGROUND: Centenarians are considered as an optimal population for studying healthy ageing. However, immune features associated with super longevity have only been investigated in a few small studies using a single research method. METHODS: In this study, single-cell RNA sequencing (scRNA-seq), mass cytometry, and flow cytometry analysis were used to analyse the immune feature of peripheral blood mononuclear cells (PBMCs) from 17 centenarians (CENs), 9 of their offsprings (COs), and 14 of their offsprings' spouses or neighbours (controls, CTs) from Lingao County of China. scRNA-seq data from the other two cohorts were downloaded from public databases. FINDINGS: Comprehensive analysis of 31 CENs, 17 COs, and 26 CTs from these three cohorts revealed decreased percentages of B cells and CD4+ T cells and an increased percentage of natural killer (NK) cells in PBMCs from CENs, compared with CTs. Moreover, NK cells from CENs exhibited relatively "young" signatures, including cell subset distribution and key membrane receptor expression. Enhanced RUNX3 expression in NK cells was observed in CENs, with reinforced interactions between NK and T cells, which promoted T cell function by modulating MHC-I, CD99 and MIF signalling. INTERPRETATION: CENs exhibit unique immunological features, especially NK cells with young protein expression signatures and immune functions. FUNDING: This study was funded by the Sanya Science and Technology Innovation Special Project (No. 2022KJCX02), National Natural Science Foundation of China (No. 32141005, 82270769), Specific Research Fund of the Innovation Platform for Academicians of Hainan Province, and National Key Research and Development Program of China (Nos. 2022YFC3602900, 2022YFC3602902, 2022YFC3602903).
-
Mechanistic insights into FEN1-mediated drug sensitivity and risk signature in colon cancer: An integrative bioinformatics study.
The overexpression of Flap endonuclease 1 (FEN1) has been implicated in drug resistance and prognosis across various cancer types. However, the precise role of FEN1 in colon cancer remains to be fully elucidated. In this study, we employed comprehensive datasets from The Cancer Genome Atlas, Gene Expression Omnibus, and Human Protein Atlas to examine FEN1 expression and assess its correlation with clinical pathology and prognosis in colon cancer. We utilized the pRRophetic algorithm to evaluate drug sensitivity and performed differential expression analysis to identify genes associated with FEN1-mediated drug sensitivity. Gene set enrichment analysis was conducted to further investigate these genes. Additionally, single-cell sequencing analysis was employed to explore the relationship between FEN1 expression and functional states. Cox regression analysis was implemented to construct a prognostic model, and a nomogram for prognosis was developed. Our analysis of The Cancer Genome Atlas and Gene Expression Omnibus datasets revealed a significant upregulation of FEN1 in colon cancer. However, while FEN1 expression showed no notable correlation with prognosis, it displayed associations with metastasis. Single-cell sequencing analysis further confirmed a positive correlation between FEN1 expression and colon cancer metastasis. Furthermore, we detected marked discrepancies in drug responsiveness between the High_FEN1 and Low_FEN1 groups, identifying 342 differentially expressed genes. Enrichment analysis showed significant suppression in processes related to DNA replication, spliceosome, and cell cycle pathways in the Low_FEN1 group, while the calcium signaling pathway, cAMP signaling pathway, and other pathways were activated. Of the 197 genes differentially expressed and strongly linked to FEN1 expression, 39 were significantly implicated in colon cancer prognosis. Finally, we constructed a risk signature consisting of 5 genes, which, when combined with drug treatment and pathological staging, significantly improved the prediction of colon cancer prognosis. This study offers novel insights into the interplay among FEN1 expression levels, colon cancer metastatic potential, and sensitivity to therapeutic agents. Furthermore, we successfully developed a multi-gene prognostic risk signature derived from FEN1.
-
Single-cell analysis of diquat-induced oxidative stress and its impact on organ-specific toxicity.
Diquat (DQ) is a commonly used herbicide, and its improper use can lead to multi-organ damage. The characteristics of multi-organ damage induced by DQ are not yet well understood. In this study, we conducted single-cell/single-nucleus RNA sequencing (scRNA-seq/snRNA-seq) on the lungs, liver, and kidneys of mice at consecutive time points (10 hours, 20 hours, and 36 hours) after DQ poisoning, as well as in a control group. In a multi-organ single-cell atlas comprising over 270,000 cells from mice, we found that DQ induces an oxidative stress microenvironment in endothelial and parenchymal cells, primarily characterized by activation of the oxidative phosphorylation pathway and an enhanced inflammatory response. This oxidative stress microenvironment prompted regulatory cell death in parenchymal and immune cells, releasing inflammatory factors and further exacerbating the oxidative environment. Additionally, metabolic reprogramming occurred in both parenchymal and immune cells under oxidative stress, leading to alterations in energy metabolism, reduced hepatic detoxification capabilities, and changes in the activation modes of immune cells, thereby intensifying tissue damage. Notably, no significant fibrosis was observed in the tissue damage caused by DQ, underscoring the importance of early intervention. Overall, using a mouse model, this study revealed the central role of the DQ-induced oxidative stress microenvironment in multi-organ damage and enhanced our understanding of the pathophysiology and complex molecular mechanisms underlying DQ-induced multi-organ injury.
-
Profiling of the TNBC Tumor Microenvironment's Functional Heterogeneity by CITE-seq to Guide Personalized Medicine.
UNLABELLED: Introduction / Objective: Triple-negative breast cancer (TNBC) is an aggressive subtype with few effective treatments and frequent resistance to immune checkpoint inhibitors. The heterogeneous and plastic tumor microenvironment (TME) is a dynamic, complex ecosystem. This study aims to deconstruct the TNBC immune ecosystem and generate a cellular atlas of its tumor microenvironment. METHODS: In this study, we apply three CITE-seq datasets from murine TNBC tumors, totaling 2,356 cells. After correcting for technical batch effects, we perform clustering to identify major cell types, followed by focused sub-clustering of tumor-associated macrophages (TAMs) and T cells to analysis their functional states and potential differentiation trajectories. RESULTS: Batch-corrected analysis resolves six primary cell populations within the TNBC microenvironment. TAMs segregate into three distinct subpopulations: a classical antigen-presenting subset, a metabolically active subset enriched for mitochondrial gene expression, and a unique subset with an erythroid-like gene signature consistent with active erythrophagocytosis. T-cell analysis reveals five major states. Furthermore, we identify several therapeutic targets. DISCUSSION: These findings reveal substantial functional diversity within key immune compartments of TNBC, particularly TAMs and T cells, including metabolically specialized and erythrophagocytic TAMs, as well as distinct T cells. Besides, we also identify several potential drug targets for targeted treatment. CONCLUSION: This work provides a detailed single-cell atlas of the TNBC tumor microenvironment and uncovers functional heterogeneity in its immune cells. The resulting map offers a foundation for precision medicine, facilitating patient stratification and the design of tailored therapies that target the specific cellular ecosystems driving TNBC progression.