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: 4 924
Page 216 of 493-
Hemocyte Nuclei Isolation from Adult Drosophila melanogaster for snRNA-seq.
In adult Drosophila, most of the hemocytes are macrophage-like cells (so called plasmatocytes), which serve various functions in organ homeostasis and immune defense. Ontogeny and functions are largely conserved between vertebrate and invertebrate macrophages. Hence, Drosophila offers a powerful genetic toolbox to study macrophage function and genetically modulate these cells. Technological advances in high-throughput sequencing approaches allowed to give an in-depth characterization of vertebrate macrophage populations and their heterogenous composition within different organs as well as changes in disease. Embryonic and larval hemocytes in Drosophila have been recently analyzed in single-cell RNA-sequencing (scRNA-seq) approaches during infection and steady state. These analyses revealed anatomical and functional Drosophila hemocyte subtypes dedicated to specific tasks. Only recently, the Fly Cell Atlas provided a whole transcriptomic single-cell atlas via single-nuclei RNA-sequencing (snRNA-seq) of adult Drosophila including many different tissues and cell types where hemocytes were also included. Yet, a specific protocol to isolate nuclei from adult hemocytes for snRNA-seq and study these cells in different experimental conditions was not available. In this chapter, we give a detailed protocol to purify hemocyte nuclei from adult Drosophila, which can be used in subsequent analyses such as snRNA-seq.
-
Multi-omics blood atlas reveals unique features of immune and platelet responses to SARS-CoV-2 Omicron breakthrough infection.
Although host responses to the ancestral SARS-CoV-2 strain are well described, those to the new Omicron variants are less resolved. We profiled the clinical phenomes, transcriptomes, proteomes, metabolomes, and immune repertoires of >1,000 blood cell or plasma specimens from SARS-CoV-2 Omicron patients. Using in-depth integrated multi-omics, we dissected the host response dynamics during multiple disease phases to reveal the molecular and cellular landscapes in the blood. Specifically, we detected enhanced interferon-mediated antiviral signatures of platelets in Omicron-infected patients, and platelets preferentially formed widespread aggregates with leukocytes to modulate immune cell functions. In addition, patients who were re-tested positive for viral RNA showed marked reductions in B cell receptor clones, antibody generation, and neutralizing capacity against Omicron. Finally, we developed a machine learning model that accurately predicted the probability of re-positivity in Omicron patients. Our study may inspire a paradigm shift in studying systemic diseases and emerging public health concerns.
-
PolyASite v3.0: a multi-species atlas of polyadenylation sites inferred from single-cell RNA-sequencing data.
The broadly used 10X Genomics technology for single-cell RNA sequencing (scRNA-seq) captures RNA 3' ends. Thus, some reads contain part of the non-templated polyadenosine tails, providing direct evidence for the sites of 3' end cleavage and polyadenylation on the respective RNAs. Taking advantage of this property, we recently developed the SCINPAS workflow to infer polyadenylation sites (PASs) from scRNA-seq data. Here, we used this workflow to construct version 3.0 (v3.0, https://polyasite.unibas.ch/) of the PolyASite Atlas from a big compendium of publicly available human, mouse and worm scRNA-seq datasets obtained from healthy tissues. As the resolution of scRNA-seq was too low for robust detection of cell-level differences in PAS usage, we aggregated samples based on their tissue-of-origin to construct tissue-level catalogs of PASs. These provide qualitatively new information about PAS usage, in comparison to the previous PAS catalogs that were based on bulk 3' end sequencing experiments primarily in cell lines. In the new version, we document stringency levels associated with each PAS so that users can balance sensitivity and specificity in their analysis. We also upgraded the integration with the UCSC Genome Browser and developed track hubs conveniently displaying pooled and tissue-specific expression of PASs.
-
An Atlas of Thyroid Hormone Responsive Genes in Adult Mouse Hypothalamus.
We present an atlas of genes that respond to thyroid hormone in the adult mouse mediobasal hypothalamus. Based on droplet-based single nuclei RNA-seq method and batch transcriptome analyses, the atlas lists putative target genes of the hormone nuclear receptors in 20 different types of neuronal and glial cells. The transcriptional regulation of these genes varies extensively across neuronal and glial cell types. However, while astrocytes appear to be highly sensitive to thyroid hormone stimulation, differentiated oligodendrocytes are relatively insensitive. This atlas is expected to promote future investigations into the molecular and cellular mechanisms that underlie the numerous functions of thyroid hormone in the hypothalamic circuits.
-
scPANDA: PAN-Blood Data Annotator with a 10-Million Single-Cell Atlas.
OBJECTIVES: Recent advancements in single-cell RNA sequencing (scRNA-seq) have revolutionized the study of cellular heterogeneity, particularly within the hematological system. However, accurately annotating cell types remains challenging due to the complexity of immune cells. To address this challenge, we develop a PAN-blood single-cell Data Annotator (scPANDA), which leverages a comprehensive 10-million-cell atlas to provide precise cell type annotation. METHODS: The atlas, constructed from data collected in 16 studies, incorporated rigorous quality control, preprocessing, and integration steps to ensure a high-quality reference for annotation. scPANDA utilizes a three-layer inference approach, progressively refining cell types from broad compartments to specific clusters. Iterative clustering and harmonization processes were employed to maintain cell type purity throughout the analysis. Furthermore, the performance of scPANDA was evaluated in three external datasets. RESULTS: The atlas was structured hierarchically, consisting of 16 compartments, 54 classes, 4,460 low-level clusters (pd_cc_cl_tfs), and 611 high-level clusters (pmid_cts). Robust performance of the tool was demonstrated in annotating diverse immune scRNA-seq datasets, analyzing immune-tumor coexisting clusters in renal cell carcinoma, and identifying conserved cell clusters across species. CONCLUSIONS: scPANDA exemplifies effective reference mapping with a large-scale atlas, enhancing the accuracy and reliability of blood cell type identification.
-
Infiltrating plasma cells maintain glioblastoma stem cells through IgG-Tumor binding.
Glioblastoma is a highly aggressive primary brain tumor with glioblastoma stem cells (GSCs) enforcing the intra-tumoral hierarchy. Plasma cells (PCs) are critical effectors of the B-lineage immune system, but their roles in glioblastoma remain largely unexplored. Here, we leverage single-cell RNA and B cell receptor sequencing of tumor-infiltrating B-lineage cells and reveal that PCs are aberrantly enriched in the glioblastoma-infiltrating B-lineage population, experience low level of somatic hypermutation, and are associated with poor prognosis. PCs secrete immunoglobulin G (IgG), which stimulates GSC proliferation via the IgG-FcγRIIA-AKT-mTOR axis. Disruption of IgG-FcγRIIA paracrine communication inhibits GSC proliferation and self-renewal. Glioblastoma-infiltrating PCs are recruited to GSC niches via CCL2-CCR2 chemokine program. GSCs further derive pro-proliferative signals from broadly utilized monoclonal antibody-based immune checkpoint inhibitors via FcγRIIA signaling. Our data generate an atlas of B-lineage cells in glioblastoma with a framework for combinatorial targeting of both tumor cell-intrinsic and microenvironmental dependencies.
-
A Pan-Cancer Single-Cell Atlas to Evaluate Tumor Identity, Cell Line Concordance, and Dependency Mapping.
Bulk RNA sequencing enables pan-cancer transcriptional analyses, but obscures cancer cell-specific programs due to admixture with nonmalignant cells, thereby limiting direct comparison between experimental models and primary tumors. Single-cell RNA sequencing (scRNA-seq) overcomes these limitations; however, the biological interpretability of public datasets is often compromised by variable data quality, inconsistent annotation, and atlas-scale aggregation strategies that prioritize data volume over biological coherence. We therefore developed a stringent integration framework that prioritizes representative malignant transcriptional states. Using Mahalanobis distance-based selection within batch-corrected latent space, we constructed a pan-cancer atlas comprising 135,424 high-quality malignant cells from 499 samples across 36 adult and pediatric cancers. Atlas-derived cancer signatures were used to determine tumor-cell line concordance and project ElasticNet models trained on DepMap CRISPR screens to infer cancer-specific gene dependencies. The scTumor Atlas establishes a scalable framework for tumor identity inference, cancer cell line benchmarking, and systematic identification of genetic vulnerabilities.
-
Cross-Tissue Transcriptomic Convergence Identifies a Leuko-Cyte-Shared, Myeloid-Enriched Inflammatory Program in Frailty and Osteoarthritis.
Frailty and osteoarthritis (OA) frequently coexist in older adults, yet the extent to which they share molecular programs across tissues remains unclear. We integrated bulk transcriptomics, peripheral immune and OA meniscal single-cell atlases, inferred cell-cell communication, and an in vitro myeloid-chondrocyte conditioned-medium model. Frailty-associated vastus lateralis and OA synovium shared a 16-gene program enriched for inflammatory and migratory processes, which was refined by protein-protein interaction analysis into a 15-gene hub module (Hub-15). Donor-aware pseudobulk analysis showed coordinated Hub-15 upregulation in CD8 T, natural killer, B, and monocyte/macrophage-like cells, with the highest scores in monocyte/macrophage populations. In the meniscal atlas, donor-level analysis of 7 normal and 6 OA donors identified a 20.5 percentage point lower proportion of inflammatory/stress cells and a 17.3 percentage point higher proportion of fibrochondrocyte-like cells in OA (both false discovery rate = 0.010), whereas state-specific Hub-15 differences were not significant after correction. Exploratory communication analysis nominated directionally consistent candidate myeloid-to-structural signaling axes, although none remained significant after multiple-testing correction. Conditioned medium from cytokine-primed THP-1 cells elicited inflammatory and matrix-catabolic responses in C28/I2 cells. These findings identify a cross-tissue, leukocyte-shared, and myeloid-enriched inflammatory program that converges across independent frailty and OA cohorts, providing a hypothesis-generating framework for future mechanistic testing.
-
Embryo-scale reverse genetics at single-cell resolution.
The maturation of single-cell transcriptomic technologies has facilitated the generation of comprehensive cellular atlases from whole embryos1-4. A majority of these data, however, has been collected from wild-type embryos without an appreciation for the latent variation that is present in development. Here we present the 'zebrafish single-cell atlas of perturbed embryos': single-cell transcriptomic data from 1,812 individually resolved developing zebrafish embryos, encompassing 19 timepoints, 23 genetic perturbations and a total of 3.2 million cells. The high degree of replication in our study (eight or more embryos per condition) enables us to estimate the variance in cell type abundance organism-wide and to detect perturbation-dependent deviance in cell type composition relative to wild-type embryos. Our approach is sensitive to rare cell types, resolving developmental trajectories and genetic dependencies in the cranial ganglia neurons, a cell population that comprises less than 1% of the embryo. Additionally, time-series profiling of individual mutants identified a group of brachyury-independent cells with strikingly similar transcriptomes to notochord sheath cells, leading to new hypotheses about early origins of the skull. We anticipate that standardized collection of high-resolution, organism-scale single-cell data from large numbers of individual embryos will enable mapping of the genetic dependencies of zebrafish cell types, while also addressing longstanding challenges in developmental genetics, including the cellular and transcriptional plasticity underlying phenotypic diversity across individuals.
-
Multimodal Nature of the Single-cell Primate Brain Atlas: Morphology, Transcriptome, Electrophysiology, and Connectivity.
Primates exhibit complex brain structures that augment cognitive function. The neocortex fulfills high-cognitive functions through billions of connected neurons. These neurons have distinct transcriptomic, morphological, and electrophysiological properties, and their connectivity principles vary. These features endow the primate brain atlas with a multimodal nature. The recent integration of next-generation sequencing with modified patch-clamp techniques is revolutionizing the way to census the primate neocortex, enabling a multimodal neuronal atlas to be established in great detail: (1) single-cell/single-nucleus RNA-seq technology establishes high-throughput transcriptomic references, covering all major transcriptomic cell types; (2) patch-seq links the morphological and electrophysiological features to the transcriptomic reference; (3) multicell patch-clamp delineates the principles of local connectivity. Here, we review the applications of these technologies in the primate neocortex and discuss the current advances and tentative gaps for a comprehensive understanding of the primate neocortex.