Project description:In this study, we performed single cell RNA sequencing of isolated hematopoietic tissue (HPT) cells and hemocytes from the crayfish Pacifastacus leniusculus. Thereby, we could identify hitherto undescribed hemocyte types in the circulation, and show that the circulating cells are more diversified than previously recognized. In addition, we discovered cell populations in the HPT with clear precursor characteristics, but also cells involved in iron homeostasis, a previously undiscovered cell type and a finding that may have an impact to understand hematopoietic stem cell regulation in these and other animals. A limitation of the study is that it is done on the transcript-level, as Pacifastacus leniusculus is currently lacking a genomic reference. The sequencing depth is thus divided between a large number of features, compared to what would have been the case at the genome-level. There are, however, efforts currently underway to sequence and annotate the genome, which could potentially be used to re-analyze this data in the future and explore it further. In publications based on this data, the authors must acknowledge SciLifeLab and NGI with the following sentences: “Sequencing was performed by the SNP&SEQ Technology Platform in Uppsala. The facility is part of the National Genomics Infrastructure (NGI) Sweden and Science for Life Laboratory. The SNP&SEQ Platform is also supported by the Swedish Research Council and the Knut and Alice Wallenberg Foundation.”
Project description:We combined the Single-probe single cell MS(SCMS) experimental technique with a bioinformatics software package, SinCHet-MS (Single Cell Heterogeneity for Mass Spectrometry), to characterize changes of tumor heterogeneity, quantify cell subpopulations, and prioritize the metabolite biomarkers of each subpopulation.
Project description:We combined the Single-probe single cell MS(SCMS) experimental technique with a bioinformatics software package, SinCHet-MS (Single Cell Heterogeneity for Mass Spectrometry), to characterize changes of tumor heterogeneity, quantify cell subpopulations, and prioritize the metabolite biomarkers of each subpopulation.
Project description:Single-cell RNA-sequencing has emerged as a powerful technology to assess heterogeneity within defined cell populations. Here, we comprehensively study the heterogeneity of a previously described B220+CD117intCD19-NK1.1- uncommitted hematopoietic progenitor with combined lymphoid and myeloid potential (EPLM). Using staining for surface markers together with functional assays, we describe four subpopulations of this progenitor with distinct lineage developmental potentials. Amongst them, the Ly6D+SiglecH-CD11c- fraction was lymphoid restricted exhibiting strong B-cell potential, whereas the Ly6D-SiglecH-CD11c- fraction showed mixed lympho-myeloid potential. Single-cell RNA-sequencing of these subsets revealed that the latter population is composed of a mixture of cells with distinct lymphoid and myeloid genetic signatures and identified a subgroup as the potential precursor of Ly6D+SiglecH-CD11c-. We observed a B-cell priming gradient within the Ly6D+SiglecH-CD11c- subset and propose a herein newly identified subgroup as the direct precursor of the first B-cell committed stage. Our study demonstrates that the multipotency of B220+CD117intCD19-NK1.1- progenitors is a result of underlying heterogeneity at the single-cell level. Moreover, it highlights the validity of single-cell transcriptomics to resolve cellular heterogeneity and identify developmental relationships in hematopoietic progenitors.
Project description:Cervical cancer (CC) is the fourth leading cause of deaths in gynecological malignancies. Although the etiology of CC has been extensively investigated, the exact pathogenesis of CC remains incomplete. Recently, single-cell technologies demonstrated advantages in exploring intra-tumoral diversification among various tumor cells. However, single-cell transcriptome (scRNA-seq) analysis of CC cells and microenvironment has not been conducted. In this study, a total of 6 samples (3 CC and 3 adjacent normal tissues) were examined by scRNA-seq. Here, we performed single-cell RNA sequencing (scRNA-seq) to survey the transcriptomes of 57,669 cells derived from three CC tumors with paired normal adjacent non-tumor (NAT) samples. Single-cell transcriptomics analysis revealed extensive heterogeneity in malignant cells of human CCs, wherein epithelial subpopulation exhibited different genomic and transcriptomic signatures. We also identified cancer-associated fibroblasts (CAF) that may promote tumor progression of CC, and further distinguished inflammatory CAF (iCAF) and myofibroblastic CAF (myCAF). CD8+ T cell diversity revealed both proliferative (MKI67+) and non-cycling exhausted (PDCD1+) subpopulations at the end of the trajectory path. We used the epithelial signature genes derived from scRNA-seq to deconvolute bulk RNA-seq data of CC, identifying four different CC subtypes, namely hypoxia (S-H subtype), proliferation (S-P subtype), differentiation (S-D subtype), and immunoactive (S-I subtype) subtype. Our results lay the foundation for precision prognostic and therapeutic stratification of CC.
Project description:We aimed at identifying lymphangiogenic subpopulations by comparative analysis of single cell clones derived from a melanoma of a single patient. Selected clones were grafted into SCID mice, where they induced lymphangiogenesis and metastasized into sentinel nodes, whereas non-lymphangiogenic clones from the same patient did not metastasize. RNA isolated from primary SCID mouse tumors were used for transcriptome analysis. A total of 16 Samples were analysed, 4 per group. Parental pool MCM1(C), nonlymphangiogenic MCM1G(G), lymphangiogenic MCM1D(D1), lymphangiogenic and very metastatic MCM1DLN(D2).
Project description:The project aims at linking functionality to metabolic fluxes of mouse primary B cells, potentially correlating antibody secretion rates with metabolic differences in subpopulations of B cells. In previous experiments, subpopulations of primary B cells with different phenotypes were observed. Therefore, the next step is to further characterize these subpopulations of B cells via single-cell RNA sequencing so that we gain insight about cell characteristics and individual gene markers, and their potential biological role. Our hypothesis is that these cells present different expression profiles of key genes and/or are relevant in different immune-related pathways.