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Project description:Multi-modal Spatial Cellular Taxonomy of Human Hippocampus Reveals Region-Specific Activity and States
| PRJNA884110 | ENA
Project description:Juvenile dermatomyositis (JDM) is a rare autoimmune condition with insufficient biomarkers and treatments, in part, due to incomplete knowledge of the cell types mediating disease. We investigated immunophenotypes and cell-specific genes associated with disease activity using multiplexed RNA and protein single-cell sequencing applied to PBMCs from 4 treatment-naïve JDM (TN-JDM) subjects at baseline, 2, 4, and 6 months post-treatment and 4 subjects with inactive disease on treatment. Analysis of 55,564 cells revealed separate clustering of TN-JDM cells within monocyte, NK, CD8+ effector T and naïve B populations. The proportion of CD16+ monocytes was reduced in TN-JDM, and naïve B cells and CD4+ Tregs were expanded. Cell-type differential gene expression analysis and hierarchical clustering identified a pan-cell-type IFN gene signature over-expressed in TN-JDM in all cell types and correlated with disease activity most strongly in cytotoxic cell types. TN-JDM CD16+ monocytes expressed the highest IFN gene score and were highly skewed toward an inflammatory and antigen-presenting phenotype at both the transcriptomic and proteomic levels. A transitional B cell population with a distinct transcriptomic signature was expanded in TN-JDM and characterized by higher CD24 and CD5 proteins and less CD39, an immunoregulatory protein. This data provides new insights into JDM immune dysregulation at cellular resolution and serves as a novel resource for myositis investigators.
| S-EPMC9254730 | biostudies-literature
Project description:Biological systems are complex, encompassing intertwined spatial, molecular and functional features. However, methodological constraints limit the completeness of information that can be extracted. Here, we report the development of INSIHGT, a non-destructive, accessible three-dimensional (3D) spatial biology method utilizing superchaotropes and host-guest chemistry to achieve homogeneous, deep penetration of macromolecular probes up to centimeter scales, providing reliable semi-quantitative signals throughout the tissue volume. Diverse antigens, mRNAs, neurotransmitters, and post-translational modifications are well-preserved and simultaneously visualized. INSIHGT also allows multi-round, highly multiplexed 3D molecular probing and is compatible with downstream traditional histology and nucleic acid sequencing. With INSIHGT, we map undescribed podocyte-to-parietal epithelial cell microfilaments in mouse glomeruli and neurofilament-intensive inclusion bodies in the human cerebellum, and identify NPY-proximal cell types defined by spatial morpho-proteomics in mouse hypothalamus. We anticipate that INSIHGT can form the foundations for 3D spatial multi-omics technology development and holistic systems biology studies.
| S-EPMC11685604 | biostudies-literature
Project description:Juvenile dermatomyositis (JDM) is a rare autoimmune condition with insufficient biomarkers and treatments, in part, due to incomplete knowledge of the cell types mediating disease. We investigated immunophenotypes and cell-specific genes associated with disease activity using multiplexed RNA and protein single-cell sequencing applied to PBMCs from 4 treatment-naïve JDM (TN-JDM) subjects at baseline, 2, 4, and 6 months and 4 subjects with inactive disease.
2022-04-30 | GSE190684 | GEO
Project description:Training with long inter-session intervals, termed distributed training, has long been known to be superior to training with short intervals, termed massed training. In the present study we compared c-Fos expression after massed and distributed training protocols in the Morris water maze to outline possible differences in the learning-induced pattern of neural activation in the dorsal CA1 in the two training conditions. The results demonstrate that training and time lags between learning opportunities had an impact on the pattern of neuronal activity in the dorsal CA1. Mice trained with the distributed protocol showed sustained neuronal activity in the postero-distal component of the dorsal CA1. In parallel, in trained mice we found more active cells that tended to constitute spatially restricted clusters, whose degree increased with the increase in the time lags between learning trials. Moreover, activated cell assemblies demonstrated increased stability in their spatial organization after distributed as compared to massed training or control condition. Finally, using a machine learning algorithm we found that differences in the number of c-Fos positive cells and their location in the dorsal CA1 could be predictive of the training protocol used. These results suggest that the topographic organization and the spatial location of learning activated cell assemblies might be critical to promote the increased stability of the memory trace induced by distributed training.
| S-EPMC10432541 | biostudies-literature
Project description:The state and behaviour of a cell can be influenced by both genetic and environmental factors. In particular, tumour progression is determined by underlying genetic aberrations1-4 as well as the makeup of the tumour microenvironment5,6. Quantifying the contributions of these factors requires new technologies that can accurately measure the spatial location of genomic sequence together with phenotypic readouts. Here we developed slide-DNA-seq, a method for capturing spatially resolved DNA sequences from intact tissue sections. We demonstrate that this method accurately preserves local tumour architecture and enables the de novo discovery of distinct tumour clones and their copy number alterations. We then apply slide-DNA-seq to a mouse model of metastasis and a primary human cancer, revealing that clonal populations are confined to distinct spatial regions. Moreover, through integration with spatial transcriptomics, we uncover distinct sets of genes that are associated with clone-specific genetic aberrations, the local tumour microenvironment, or both. Together, this multi-modal spatial genomics approach provides a versatile platform for quantifying how cell-intrinsic and cell-extrinsic factors contribute to gene expression, protein abundance and other cellular phenotypes.
| S-EPMC9301586 | biostudies-literature
Project description:The ventral posterior hypothalamus (VPH) is an anatomically complex brain region implicated in arousal, reproduction, energy balance, and memory processing. However, neuronal cell type diversity within the VPH is poorly understood, an impediment to deconstructing the roles of distinct VPH circuits in physiology and behavior. To address this question, we employed a droplet-based single-cell RNA sequencing (scRNA-seq) approach to systematically classify molecularly distinct cell populations in the mouse VPH. Analysis of >16,000 single cells revealed 20 neuronal and 18 non-neuronal cell populations, defined by suites of discriminatory markers. We validated differentially expressed genes in selected neuronal populations through fluorescence in situ hybridization (FISH). Focusing on the mammillary bodies (MB), we discovered transcriptionally-distinct clusters that exhibit neuroanatomical parcellation within MB subdivisions and topographic projections to the thalamus. This single-cell transcriptomic atlas of VPH cell types provides a resource for interrogating the circuit-level mechanisms underlying the diverse functions of VPH circuits.
| S-EPMC7595735 | biostudies-literature
Project description:Signaling pathways can be activated through various cascades of genes depending on cell identity and biological context. Single-cell atlases now provide the opportunity to inspect such complexity in health and disease. Yet, existing reference tools for pathway scoring resume activity of each pathway to one unique common metric across cell types. Here, we present MAYA, a computational method that enables the automatic detection and scoring of the diverse modes of activation of biological pathways across cell populations. MAYA improves the granularity of pathway analysis by detecting subgroups of genes within reference pathways, each characteristic of a cell population and how it activates a pathway. Using multiple single-cell datasets, we demonstrate the biological relevance of identified modes of activation, the robustness of MAYA to noisy pathway lists and batch effect. MAYA can also predict cell types starting from lists of reference markers in a cluster-free manner. Finally, we show that MAYA reveals common modes of pathway activation in tumor cells across patients, opening the perspective to discover shared therapeutic vulnerabilities.
| S-EPMC10039856 | biostudies-literature
Project description:The skeletal system plays a pivotal role in the human body, and bone-related diseases present an urgent public health challenge. Understanding the bone microenvironment is essential for elucidating the mechanisms underlying bone homeostasis and developing innovative therapeutic strategies for bone diseases such as osteoporosis and osteoarthritis. In this study, we applied spatial and single-cell transcriptomic assays on bone tissue from human femur to comprehensively characterize the multi-dimensional cellular landscape of the human bone marrow microenvironment. We identified one niche related to bone formation and characterized cell-cell communication within bone marrow. Notably, we performed comprehensive dependency analysis, uncovering critical cellular relationships and molecular dependencies within the bone ecosystem. By mapping spatial distributions of gene expression, cellular composition, and pathway activities, we constructed a high-resolution atlas of the human bone microenvironment. This atlas not only delineates the intricate cellular architecture but also illuminates key molecular processes and dependencies governing bone metabolism.
2024-12-18 | GSE284089 | GEO
Project description:Hippocampal structural integrity is commonly quantified using volumetric measurements derived from brain magnetic resonance imaging (MRI). Previously reported associations with cognitive decline have not been consistent. We investigate hippocampal integrity using quantitative MRI techniques and its association with cognitive abilities in older age. Participants from the Lothian Birth Cohort 1936 underwent brain MRI at mean age 73 years. Longitudinal relaxation time (T1), magnetization transfer ratio (MTR), fractional anisotropy (FA) and mean diffusivity (MD) were measured in the hippocampus. General factors of fluid-type intelligence (g), cognitive processing speed (speed) and memory were obtained at age 73 years, as well as childhood IQ test results at age 11 years. Amongst 565 older adults, multivariate linear regression showed that, after correcting for ICV, gender and age 11 IQ, larger left hippocampal volume was significantly associated with better memory ability (β = .11, p = .003), but not with speed or g. Using quantitative MRI and after correcting for multiple testing, higher T1 and MD were significantly associated with lower scores of g (β range = -.11 to -.14, p < .001), speed (β range = -.15 to -.20, p < .001) and memory (β range = -.10 to -.12, p < .001). Higher MTR and FA in the hippocampus were also significantly associated with higher scores of g (β range = .17 to .18, p < .0001) and speed (β range = .10 to .15, p < .0001), but not memory. Quantitative multi-modal MRI assessments were more sensitive at detecting cognition-hippocampal integrity associations than volumetric measurements, resulting in stronger associations between MRI biomarkers and age-related cognition changes.
| S-EPMC3979658 | biostudies-literature