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.
Project description:Deciphering the connectome, transcriptome and spatial-omics integrated multi-modal brain atlas and the underlying organization principles remains a great challenge. We developed a cost-effective Single-cell Projectome-transcriptome In situ Deciphering Sequencing (SPIDER-Seq) technique by combining viral barcoding tracing with single-cell sequencing and spatial-omics. This empowers us to delineate a comprehensive integrated single-cell spatial molecular, cellular and projectomic atlas of mouse prefrontal cortex (PFC). The projectomic and transcriptomic cell clusters display distinct modular organization principles, but are coordinately configured in the PFC. The projection neurons gradiently occupied different territories in the PFC aligning with their wiring patterns. Importantly, they show higher co-projection probability to the downstream nuclei with reciprocal circuit connections. Moreover, we integrated projectomic atlas with their distinct spectrum of neurotransmitter/neuropeptide and the receptors-related gene profiles and depicted PFC neural signal transmission network. By which, we uncovered potential mechanisms underlying the complexity and specificity of neural transmission. Finally, we predicted neuron projections with high accuracy by combining gene profiles and spatial information via machine learning. This study facilitates our understanding of brain multi-modal network and neural computation.
Project description:Multiple distinct cell types of the human lung and airways have been defined by single cell RNA sequencing (scRNAseq). Here we present a multi-omics spatial lung atlas to define novel cell types which we map back into the macro- and micro-anatomical tissue context to define functional tissue microenvironments. Firstly, we have generated single cell and nuclei RNA sequencing, VDJ-sequencing and Visium Spatial Transcriptomics data sets from 5 different locations of the human lung and airways. Secondly, we define additional cell types/states, as well as spatially map novel and known human airway cell types, such as adult lung chondrocytes, submucosal gland (SMG) duct cells, distinct pericyte and smooth muscle subtypes, immune-recruiting fibroblasts, peribronchial and perichondrial fibroblasts, peripheral nerve associated fibroblasts and Schwann cells. Finally, we define a survival niche for IgA-secreting plasma cells at the SMG, comprising the newly defined epithelial SMG-Duct cells, and B and T lineage immune cells. Using our transcriptomic data for cell-cell interaction analysis, we propose a signalling circuit that establishes and supports this niche. Overall, we provide a transcriptional and spatial lung atlas with multiple novel cell types that allows for the study of specific tissue microenvironments such as the newly defined gland-associated lymphoid niche (GALN).
Project description:The three major skin cancer types - squamous cell carcinoma (SCC), basal cell carcinoma (BCC), and melanoma - account for >70% of all cancer. Although these cancers all derive from the outer skin layer (epidermis), variability in cell type composition and interactions causes substantial cross-cancer differences in disease initiation and invasive and metastatic potential. A knowledgebase of cell type composition and cell-to-cell interactions within the three skin cancers is needed to aid the assessment of risks and prognosis upon patient presentation. Here we integrated six distinct yet complementary spatial single-cell technologies to build the largest cell atlas and interactome of SCC, BCC, and melanoma to date. First, we performed single-cell RNA sequencing (scRNAseq) on >50,000 cells from 11 paired healthy and SCC patient biopsies. GeoMx spatial proteomics data independently validated the presence of rare immune cell types defined by scRNAseq. Visium and CosMx transcriptomic analyses were performed for all three skin cancer types to map spatial neighbourhoods and construct a cell-to-cell interaction atlas. We independently validated two key LR interactions, PD1_PDL1 and IL34_CSF1R, using Opal Multiplex Polaris and RNAscope data. Downstream analysis of IL34_CSF1R signalling zones suggested enrichment of IL34-related antigen presenting pathways in melanoma. Overall, we present a valuable database and analysis approaches to reveal potential biomarkers of initiation and progression of the most lethal type (melanoma) and the most common types (SCC and BCC) of skin cancer.
Project description:Microfluidic deterministic barcoding of mRNAs and proteins in tissue slides followed by high throughput sequencing enables the construction of high-spatial-resolution multi-omics atlas at the genome scale. Applying it to mouse embryo tissues revealed major tissue (sub)types in early-stage organogenesis, brain micro-vasculatures, and the fine structure of an optical vesicle at the single-cell-layer resolution.
Project description:Comparative skin cancer atlas and interactome: A multi-modal spatial approach to uncovering the cells and interactions underlying skin cancer diversity
Project description:Liver fibrosis is a major cause of death worldwide. As a progressive step in chronic liver disease, fibrosis is almost always diagnosed too late with limited treatment options. Here, we uncover the spatial transcriptional landscape driving human liver fibrosis using single nuclei RNA and Assay for Transposase-Accessible Chromatin (ATAC) sequencing to deconvolute multi-cell spatial transcriptomic profiling in human liver cirrhosis.Through multi-modal data integration,we define molecular signatures driving cell state transitions in liver disease and define an impaired cellular response and directional trajectory from hepatocytes to cholangiocytes associated with disease remodelling.We identifypro-fibrogenic signatures in non-parenchymal cell subpopulations co-localised within the fibrotic niche and localise transitional cell states at the scar interface. This combined approach providesa spatial atlas of gene regulation and defines molecular signatures associated liver diseasefor targeted therapeutics or as early diagnostic markers of progressive liver disease. This is the 10X Visium data for the work.
Project description:The immune composition of the tumor microenvironment (TME) has a major impact on the therapeutic response and clinical outcome in patients with colorectal cancer (CRC). Here, we comprehensively characterize the TME at the single-cell level by first building a large-scale atlas that integrates 4.27 million single cells from 1,670 patient samples. We then complemented the atlas with single-cell profiles from four CRC cohorts with 266 patients, including cells with low mRNA content, spatial transcriptional profiles from 3.7 million cells, and protein profiles from 0.7 million cells. The analysis of the atlas allows refined tumor classification into four immune phenotypes: immune desert, B cell enriched, T cell enriched, and myeloid cell enriched subtypes. Within the myeloid compartment we uncover distinct subpopulations of neutrophils that acquire new functional properties in blood and in the TME, including anti-tumorigenic capabilities. Further, spatial multimodal single-cell profiling reveals that neutrophils are organized in clusters within distinct functional niches. Finally, using an orthotopic mouse model we show that cancer-derived systemic signals modify neutrophil production in the bone marrow, providing evidence for tumor-induced granulopoiesis. Our study provides a big data resource for the CRC and suggests novel therapeutic strategies targeting neutrophils.