Your browser does not allow saving data (e.g. private mode): bookmarks will be lost when the tab closes.
Search PubMed
Keywords, author, journal, years — results from PubMed, abstracts with Russian translation, bookmarks in your browser.
Found: 4 939
Page 364 of 494-
Single-cell RNA sequencing unveils unique transcriptomic signatures of endothelial cells and role of ENO1 in response to disturbed flow.
Flow patterns exert significant effects on vascular endothelial cells (ECs) to lead to the focal nature of atherosclerosis. Using a step flow chamber to investigate the effects of disturbed shear (DS) and pulsatile shear (PS) on ECs in the same flow channel, we conducted single-cell RNA sequencing analyses to explore the distinct transcriptomic profiles regulated by DS vs. PS. Integrated analysis identified eight cell clusters and demonstrated that DS induces EC transition from atheroprotective to proatherogenic phenotypes. Using an automated cell type annotation algorithm (SingleR), we showed that DS promoted endothelial-to-mesenchymal transition (EndMT) by inducing the transcriptional phenotypes for inflammation, hypoxia responses, transforming growth factor-beta (TGF-β) signaling, glycolysis, and fatty acid synthesis. Enolase 1 (ENO1), a key gene in glycolysis, was one of the top-ranked genes in the DS-induced EndMT cluster. Pseudotime trajectory analysis revealed that the kinetic expression of ENO1 was significantly associated with EndMT and that ENO1 silencing repressed the DS- and TGF-β-induced EC inflammation and EndMT. Consistent with these findings, ENO1 was highly expressed in ECs at the inner curvature of the mouse aortic arch (which is exposed to DS) and atherosclerotic lesions, suggesting its proatherogenic role in vivo. In summary, we present a comprehensive single-cell atlas of ECs in response to different flow patterns within the same flow channel. Among the DS-regulated genes, ENO1 plays an important role in DS-induced EC inflammation and EndMT. These results provide insights into how hemodynamic forces regulate vascular endothelium in health and disease.
-
Single-cell atlas reveals the immunosuppressive microenvironment and Treg cells landscapes in recurrent Glioblastoma.
Patients diagnosed with glioblastoma (GBM) have the most aggressive tumor progression and lethal recurrence. Research on the immune microenvironment landscape of tumor and cerebrospinal fluid (CSF) is limited. At the single-cell level, we aim to reveal the recurrent immune microenvironment of GBM and the potential CSF biomarkers and compare tumor locations. We collected four clinical samples from two patients: malignant samples from one recurrent GBM patient and non-malignant samples from a patient with brain tumor. We performed single-cell RNA sequencing (scRNA-seq) to reveal the immune landscape of recurrent GBM and CSF. T cells were enriched in the malignant tumors, while Treg cells were predominately found in malignant CSF, which indicated an inhibitory microenvironment in recurrent GBM. Moreover, macrophages and neutrophils were significantly enriched in malignant CSF. This indicates that they an important role in GBM progression. S100A9, extensively expressed in malignant CSF, is a promising biomarker for GBM diagnosis and recurrence. Our study reveals GBM's recurrent immune microenvironment after chemoradiotherapy and compares malignant and non-malignant CSF samples. We provide novel targets and confirm the promise of liquid CSF biopsy for patients with GBM.
-
Single-cell transcriptomic atlas reveals increased regeneration in diseased human inner ear balance organs.
Mammalian inner ear hair cell loss leads to permanent hearing and balance dysfunction. In contrast to the cochlea, vestibular hair cells of the murine utricle have some regenerative capacity. Whether human utricular hair cells regenerate in vivo remains unknown. Here we procured live, mature utricles from organ donors and vestibular schwannoma patients, and present a validated single-cell transcriptomic atlas at unprecedented resolution. We describe markers of 13 sensory and non-sensory cell types, with partial overlap and correlation between transcriptomes of human and mouse hair cells and supporting cells. We further uncover transcriptomes unique to hair cell precursors, which are unexpectedly 14-fold more abundant in vestibular schwannoma utricles, demonstrating the existence of ongoing regeneration in humans. Lastly, supporting cell-to-hair cell trajectory analysis revealed 5 distinct patterns of dynamic gene expression and associated pathways, including Wnt and IGF-1 signaling. Our dataset constitutes a foundational resource, accessible via a web-based interface, serving to advance knowledge of the normal and diseased human inner ear.
-
Single-cell transcriptome atlas unveils transcriptional regulation networks of banana root tips in response to Fusarium oxysporum infection.
Fusarium wilt caused by Fusarium oxysporum (Foc) is one of the most destructive diseases in global banana production. The response of root system to Foc infection through gene expression in multiple cell types is crucial for understanding the disease resistance mechanism in banana. Here, we reported a single-cell transcriptional landscape of banana root tips in response to Fusarium oxysporum f. sp. cubense tropical race 4 (Foc TR4) infection. We characterized 10 major cell types from 19 cell clusters. We explored differentiation trajectories of meristematic cells, root cap cells, and pericycle cells through pseudotime analysis, and identified pericycle cell as the dominant root cell type under Foc TR4 infection. Moreover, we identified 11 co-expression regulatory networks, of which eight were significantly associated with Foc TR4 response. Specifically, MaKAN4 was co-expressed with two Zn 2+-dependent genes (MaACA7 and MaADH3) in M5 module, which was associated with pericycle cell type and responded to Foc TR4 infection. Further analysis demonstrated that MaKAN4 protein could interact with the promoters of MaACA7 and MaADH3 to promote their expression levels, highlighting a crucial role of MaKAN4 in banana disease resistance by regulating the Zn 2+-dependent MaACA7/MaADH3 module. These findings provide a comprehensive view of cell fate determination in banana root tips and highlight novel insights into the regulatory mechanisms of major cell types in response to Foc TR4 infection, laying a useful foundation for developing disease-resistant banana cultivars.
-
Genome and Single-Cell Transcriptome Reveal the Evolution of Holoparasitic Plants: A Case Study of Cistanche deserticola.
The Orobanchaceae family, the largest group of parasitic plants, spans a complete spectrum from autotrophic to holoparasitic species. As a typical endangered holoparasitic species within this family, Cistanche deserticola is a parasitic plant that is widely harvested for traditional medicine in desertic regions, and of growing importance as a cash crop. However, the evolution of C. deserticola at the molecular and cellular level is poorly understood. Here, we constructed the first chromosome-level genome map of C. deserticola. Comparative genomic analyses demonstrated that the C. deserticola genome exhibited a substantial loss of genes related to photosynthesis and immunity (21.58% of the total genes) and contained 115 horizontally transferred genes. This suggested that the genomic evolution of holoparasitic plants was driven by the interplay between the acquisition of functional genes and the loss of genes specific to plant tissues or functions. Additionally, parasitism-related cells were identified using a high-resolution single-cell transcriptomic atlas, revealing stage-specific differentiation during the parasitic process. Early cells (cluster 11) highly expressed dopamine/tyrosine metabolism pathways genes (e.g., polyphenol oxidase), driving phenylethanoid glycoside biosynthesis. By contrast, mature cells (cluster 10) show high levels of gene expression relating to carbohydrate metabolism in association with nutrient acquisition. Connecting these insights, we developed a comprehensive C. deserticola database to integrate multi-omics and ecological data (http://60.30.67.246:7006/Home). This builds a robust molecular foundation for exploring pathways to parasitism in plants more broadly.
-
Distinct populations of crypt-associated fibroblasts act as signaling hubs to control colon homeostasis.
Despite recent progress in recognizing the importance of mesenchymal cells for the homeostasis of the intestinal system, the current picture of how these cells communicate with the associated epithelial layer remains unclear. To describe the relevant cell populations in an unbiased manner, we carried out a single-cell transcriptome analysis of the adult murine colon, producing a high-quality atlas of matched colonic epithelium and mesenchyme. We identify two crypt-associated colonic fibroblast populations that are demarcated by different strengths of platelet-derived growth factor receptor A (Pdgfra) expression. Crypt-bottom fibroblasts (CBFs), close to the intestinal stem cells, express low levels of Pdgfra and secrete canonical Wnt ligands, Wnt potentiators, and bone morphogenetic protein (Bmp) inhibitors. Crypt-top fibroblasts (CTFs) exhibit high Pdgfra levels and secrete noncanonical Wnts and Bmp ligands. While the Pdgfralow cells maintain intestinal stem cell proliferation, the Pdgfrahigh cells induce differentiation of the epithelial cells. Our findings enhance our understanding of the crosstalk between various colonic epithelial cells and their associated mesenchymal signaling hubs along the crypt axis-placing differential Pdgfra expression levels in the spotlight of intestinal fibroblast identity.
-
Single-cell sequencing reveals novel cellular heterogeneity in uterine leiomyomas.
STUDY QUESTION: What are the cellular composition and single-cell transcriptomic differences between myometrium and leiomyomas as defined by single-cell RNA sequencing? SUMMARY ANSWER: We discovered cellular heterogeneity in smooth muscle cells (SMCs), fibroblast and endothelial cell populations in both myometrium and leiomyoma tissues. WHAT IS KNOWN ALREADY: Previous studies have shown the presence of SMCs, fibroblasts, endothelial cells and immune cells in myometrium and leiomyomas. However, there is no information on the cellular heterogeneity in these tissues and the transcriptomic differences at the single-cell level between these tissues. STUDY DESIGN, SIZE, DURATION: We collected five leiomyoma and five myometrium samples from a total of eight patients undergoing hysterectomy. We then performed single-cell RNA sequencing to generate a cell atlas for both tissues. We utilized our single-cell sequencing data to define cell types, compare cell types by tissue type (leiomyoma versus myometrium) and determine the transcriptional changes at a single-cell resolution between leiomyomas and myometrium. Additionally, we performed MED12-variant analysis at the single-cell level to determine the genotype heterogeneity within leiomyomas. PARTICIPANTS/MATERIALS, SETTING, METHODS: We collected five MED12-variant positive leiomyomas and five myometrium samples from a total of eight patients. We then performed single-cell RNA sequencing on freshly isolated single-cell preparations. Histopathological assessment confirmed the identity of the samples. Sanger sequencing was performed to confirm the presence of the MED12 variant in leiomyomas. MAIN RESULTS AND ROLE OF CHANCE: Our data revealed previously unknown heterogeneity in the SMC, fibroblast cell and endothelial cell populations of myometrium and leiomyomas. We discovered the presence of two different lymphatic endothelial cell populations specific to uterine leiomyomas. We showed that both myometrium and MED12-variant leiomyomas are relatively similar in cellular composition but differ in cellular transcriptomic profiles. We found that fibroblasts influence the leiomyoma microenvironment through their interactions with endothelial cells, immune cells and SMCs. Variant analysis at the single-cell level revealed the presence of both MED12 variants as well as the wild-type MED12 allele in SMCs of leiomyomatous tissue. These results indicate genotype heterogeneity of cellular composition within leiomyomas. LARGE SCALE DATA: The datasets are available in the NCBI Gene Expression Omnibus (GEO) using GSE162122. LIMITATIONS, REASONS FOR CAUTION: Our study focused on MED12-variant positive leiomyomas for single-cell RNA sequencing analyses. Leiomyomas carrying other genetic rearrangements may differ in their cellular composition and transcriptomic profiles. WIDER IMPLICATIONS FOR THE FINDINGS: Our study provides a cellular atlas for myometrium and MED12-variant positive leiomyomas as defined by single-cell RNA sequencing. Our analysis provides significant insight into the differences between myometrium and leiomyomas at the single-cell level and reveals hitherto unknown genetic heterogeneity in multiple cell types within human leiomyomas. Our results will be important for future studies into the origin and growth of human leiomyomas. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by funding from the National Institute of Child Health and Human Development (HD098580 and HD088629). The authors declare no competing interests.
-
Integration of ATAC-seq and RNA-seq identifies human alpha cell and beta cell signature genes.
OBJECTIVE: Although glucagon-secreting α-cells and insulin-secreting β-cells have opposing functions in regulating plasma glucose levels, the two cell types share a common developmental origin and exhibit overlapping transcriptomes and epigenomes. Notably, destruction of β-cells can stimulate repopulation via transdifferentiation of α-cells, at least in mice, suggesting plasticity between these cell fates. Furthermore, dysfunction of both α- and β-cells contributes to the pathophysiology of type 1 and type 2 diabetes, and β-cell de-differentiation has been proposed to contribute to type 2 diabetes. Our objective was to delineate the molecular properties that maintain islet cell type specification yet allow for cellular plasticity. We hypothesized that correlating cell type-specific transcriptomes with an atlas of open chromatin will identify novel genes and transcriptional regulatory elements such as enhancers involved in α- and β-cell specification and plasticity. METHODS: We sorted human α- and β-cells and performed the "Assay for Transposase-Accessible Chromatin with high throughput sequencing" (ATAC-seq) and mRNA-seq, followed by integrative analysis to identify cell type-selective gene regulatory regions. RESULTS: We identified numerous transcripts with either α-cell- or β-cell-selective expression and discovered the cell type-selective open chromatin regions that correlate with these gene activation patterns. We confirmed cell type-selective expression on the protein level for two of the top hits from our screen. The "group specific protein" (GC; or vitamin D binding protein) was restricted to α-cells, while CHODL (chondrolectin) immunoreactivity was only present in β-cells. Furthermore, α-cell- and β-cell-selective ATAC-seq peaks were identified to overlap with known binding sites for islet transcription factors, as well as with single nucleotide polymorphisms (SNPs) previously identified as risk loci for type 2 diabetes. CONCLUSIONS: We have determined the genetic landscape of human α- and β-cells based on chromatin accessibility and transcript levels, which allowed for detection of novel α- and β-cell signature genes not previously known to be expressed in islets. Using fine-mapping of open chromatin, we have identified thousands of potential cis-regulatory elements that operate in an endocrine cell type-specific fashion.
-
Deeper insights into transcriptional features of cancer-associated fibroblasts: An integrated meta-analysis of single-cell and bulk RNA-sequencing data.
Cancer-associated fibroblasts (CAFs) have long been known as one of the most important players in tumor initiation and progression. Even so, there is an incomplete understanding of the identification of CAFs among tumor microenvironment cells as the list of CAF marker genes varies greatly in the literature, therefore it is imperative to find a better way to identify reliable markers of CAFs. To this end, we summarized a large number of single-cell RNA-sequencing data of multiple tumor types and corresponding normal tissues. As a result, for 9 different types of cancer, we identified CAF-specific gene expression signatures and found 10 protein markers that showed strongly positive staining of tumor stroma according to the analysis of IHC images from the Human Protein Atlas database. Our results give an insight into selecting the most appropriate combination of cancer-associated fibroblast markers. Furthermore, comparison of different approaches for studying differences between cancer-associated and normal fibroblasts (NFs) illustrates the superiority of transcriptome analysis of fibroblasts obtained from fresh tissue samples. Using single-cell RNA sequencing data, we identified common differences in gene expression patterns between normal and cancer-associated fibroblasts, which do not depend on the type of tumor.
-
Systematic reconstruction of molecular pathway signatures using scalable single-cell perturbation screens.
Recent advancements in functional genomics have provided an unprecedented ability to measure diverse molecular modalities, but predicting causal regulatory relationships from observational data remains challenging. Here, we leverage pooled genetic screens and single-cell sequencing (Perturb-seq) to systematically identify the targets of signalling regulators in diverse biological contexts. We demonstrate how Perturb-seq is compatible with recent and commercially available advances in combinatorial indexing and next-generation sequencing, and perform more than 1,500 perturbations split across six cell lines and five biological signalling contexts. We introduce an improved computational framework (Mixscale) to address cellular variation in perturbation efficiency, alongside optimized statistical methods to learn differentially expressed gene lists and conserved molecular signatures. Finally, we demonstrate how our Perturb-seq derived gene lists can be used to precisely infer changes in signalling pathway activation for in vivo and in situ samples. Our work enhances our understanding of signalling regulators and their targets, and lays a computational framework towards the data-driven inference of an 'atlas' of perturbation signatures.