Project description:Spatially resolved gene expression was prepard by dissociated hman prostate tissue to single cells, and collected & prepped for RNA-seq using the Visium Spatial Gene Expression kit. 5000 cells were collected and sequenced at a depth of 50k cells/gene on a 2X150nt lane in a NovaSeq 6000. SpaceRanger alignment was performed to produce the RAW files
Project description:<p>Systemic lupus erythematosus (SLE) is a systemic autoimmune disease with a remarkable predominance in female, suggesting that steroid hormones may be involved in the pathogenesis. Herein, more than 70 kinds of steroids in urine were detected by gas chromatography/mass spectrometry (GC/MS) to reveal SLE-specific steroid alterations. Principle component analysis demonstrated that the steroid profile was obviously distinguished between SLE patients and controls. Lower level of total androgens was observed in patients, and 9 androgens (DHEA, testosterone, Etio, androsterone, βαβ-Diol, Epi-An, Epi-DHT, 16α-OH-DHEA, A-Diol) underwent significant decrease. Besides, SLE patients exhibited slightly higher level of total estrogens than controls, and 3 estrogens (17-Epi-E3, 17α-E2, E3) were remarkably increased. Furthermore, we identified the elevation of 2 sterols (Lan, Chol), and the reduction of 1 corticoid (11-DeoxyF) and 2 progestins (5α-DHP, 11β-OH-Prog) in patients. In this study, metabolic signature of urinary steroids associated with SLE was comprehensively defined by GC/MS for the first time, and steroid metabolism disorders were found in SLE patients, especially the conversion of androgens to estrogens. Our findings will provide new insights for a deeper understanding of the mechanism of steroid hormones in the pathogenesis of SLE, and help to unravel the reason of sexual disparity in SLE.</p>
Project description:We have developed an imaging-free framework to localize nucleic acids within a tissue by combining a compressed sensing tissue-sampling strategy based on multi-angle-sectioning and an associated image reconstruction algorithm. Initially, the tissue is cut into consecutive thin slices. Subsequently these are further sliced along an orthogonal plane at predefined orientations resulting in tissue strips that are subject to RNA sequencing. We implemented this framework to transform a single-cell RNA sequencing protocol into an imaging-free spatial transcriptomics technique. The method was validated by profiling the transcriptome of the Murine brain, and used to spatially profile the brain transcriptome of the Australian Central bearded dragon, Pogona vitticeps.
Project description:The project aims to elucidate mechanisms driving P. aeruginosa response to sex steroids hormones. An experiment involving Co-immunoprecipitation combined with Mass spectroscopy was performed to identify P. aeruginosa proteins binding to estradiol and /testosterone.
Project description:In breast cancer cells, some topologically associating domains (TADs) behave as hormonal gene regulation units, within which genes transcription is coordinately regulated in response to steroid hormones. Here we further described that responsive TADs contain 20-100 kb-long clusters of intermingled estrogen receptor (ER) and progesterone receptor (PR) binding sites, hereafter called Hormone-Control Regions (HCRs). In T47D cells, we identified more than 200 HCRs, which are frequently bound by unliganded ER and PR. These HCRs establish steady long-distance inter-TAD interactions between them and organize characteristic looping structures with promoters even in the absence of hormones in ER+-PR+ cells. This organization is dependent on the expression of the receptors and is further dynamically modulated in response to steroid hormones. HCRs function as platforms integrating different signals resulting in some cases in opposite transcriptional responses to estrogens or progestins. Altogether, these results suggest that steroid hormone receptors act not only as hormone-regulated sequence-specific transcription factors, but also as local and global genome organizers.
Project description:The recent development of spatial omics enables single-cell profiling of the transcriptome and the 3D organization of the genome in a spatially resolved manner. A spatial epigenomics method would expand the repertoire of spatial omics tools and accelerate our understanding of the spatial regulation of cellular processes and tissue functions. Here, we developed an imaging approach for spatially resolved profiling of epigenetic modifications in single cells
Project description:Development of specialized cell types and structures in the vertebrate heart is regulated by spatially-restricted molecular pathways. Disruptions in these pathways can cause severe congenital cardiac malformations or functional defects. To better understand these pathways and how they regulate cardiac development and function we used tomo-seq, combining high-throughput RNA sequencing with tissue sectioning, to establish a genome-wide expression dataset with high spatial resolution for the developing zebrafish heart. Analysis of the dataset revealed over 1100 genes differentially expressed in sub-compartments. Pacemaker cells in the sinoatrial region induce heart contractions, but little is known about the mechanisms underlying their development and function. Using our transcriptome map, we identified spatially restricted Wnt/β-catenin signaling activity in pacemaker cells, which was controlled by Islet-1 activity. Moreover, Wnt/β-catenin signaling at a specific developmental stage in the myocardium controls heart rate by regulating pacemaker cellular response to parasympathetic stimuli. Thus, this high-resolution transcriptome map incorporating all cell types in the embryonic heart can expose spatially-restricted molecular pathways critical for specific cardiac functions.
Project description:Understanding the spatial distribution of T cells is pivotal to decrypting immune dysfunction in cancer. Current spatially resolved transcriptomics fall short in directly annotating T cell receptors (TCRs), limiting the comprehension of anti-cancer immunity. We introduce a novel technology, Spatially Resolved T Cell Receptor Sequencing (SPTCR-seq), integrating target enrichment and long-read sequencing for highly sensitive TCR sequencing. This approach yields an on-target rate of ~85%, and via a bespoke computational pipeline, it provides meticulous spatial mapping, error correction, and UMI refinement. SPTCR-seq outperforms PCR-based methods, offering superior reconstruction of the complete TCR architecture, inclusive of V, D, J regions and the vital complementarity-determining region 3 (CDR3). Applying SPTCR-seq, we reveal local T cell diversity, clonal expansion, and transcriptional evolution across spatially distinct niches in glioblastoma, identifying critical involvement of NK and B cells in spatial T cell adaptation. SPTCR-seq, by bridging spatially resolved omics and TCR sequencing, stands as a robust tool for exploring T cell dysfunction in cancers and beyond.
Project description:To better understand how individual cells function within an anatomical space, we developed XYZeq, a novel scRNA-seq workflow that uses combinatorial indexing in microwells to encode spatial metadata into scRNA-seq libraries. We used XYZeq to profile heterotopic mouse liver and spleen tumor models to capture transcriptomes from tens of thousands of cells across a total of eight tissue slices.
Project description:We investigated spatiotemporal molecular patterns related to AD pathophsiology using spatially resolved transcriptome of the AD mouse model. The late change of gray matters of AD was commonly related to neuroinflammation, while the early change in the white matter of AD represented neuronal projection and ensheathment of axons before the amyloid plaques accumulation. Disease-associated microglia and astrocyte signatures were spatially differently enriched. Our results provide a key spatiotemporally heterogeneous molecular change particularly related to inflammation in AD.