8 research outputs found
Single-cell RNA-sequencing uncovers transcriptional states and fate decisions in haematopoiesis.
The success of marker-based approaches for dissecting haematopoiesis in mouse and human is reliant on the presence of well-defined cell surface markers specific for diverse progenitor populations. An inherent problem with this approach is that the presence of specific cell surface markers does not directly reflect the transcriptional state of a cell. Here, we used a marker-free approach to computationally reconstruct the blood lineage tree in zebrafish and order cells along their differentiation trajectory, based on their global transcriptional differences. Within the population of transcriptionally similar stem and progenitor cells, our analysis reveals considerable cell-to-cell differences in their probability to transition to another committed state. Once fate decision is executed, the suppression of transcription of ribosomal genes and upregulation of lineage-specific factors coordinately controls lineage differentiation. Evolutionary analysis further demonstrates that this haematopoietic programme is highly conserved between zebrafish and higher vertebrates.The study was supported by Cancer Research UK grant number C45041/A14953 (to A.C. and E.A.), European Research Council project 677501 â ZF_Blood (to A.C.) and a core support grant from the Wellcome Trust and MRC to the Wellcome Trust â Medical Research Council Cambridge Stem Cell Institute. The authors would like to thank WTSI Cytometry Core Facility for their help with index cell sorting and the Core Sanger Web Team for hosting the cloud web application. The authors would also like to thank the CRUK Cambridge Institute Genomics Core Facility for their contribution in sequencing the data
CD4-Transgenic Zebrafish Reveal Tissue-Resident Th2- and Regulatory T Cell-like Populations and Diverse Mononuclear Phagocytes.
CD4+ T cells are at the nexus of the innate and adaptive arms of the immune system. However, little is known about the evolutionary history of CD4+ T cells, and it is unclear whether their differentiation into specialized subsets is conserved in early vertebrates. In this study, we have created transgenic zebrafish with vibrantly labeled CD4+ cells allowing us to scrutinize the development and specialization of teleost CD4+ leukocytes in vivo. We provide further evidence that CD4+ macrophages have an ancient origin and had already emerged in bony fish. We demonstrate the utility of this zebrafish resource for interrogating the complex behavior of immune cells at cellular resolution by the imaging of intimate contacts between teleost CD4+ T cells and mononuclear phagocytes. Most importantly, we reveal the conserved subspecialization of teleost CD4+ T cells in vivo. We demonstrate that the ancient and specialized tissues of the gills contain a resident population of il-4/13b-expressing Th2-like cells, which do not coexpress il-4/13a Additionally, we identify a contrasting population of regulatory T cell-like cells resident in the zebrafish gut mucosa, in marked similarity to that found in the intestine of mammals. Finally, we show that, as in mammals, zebrafish CD4+ T cells will infiltrate melanoma tumors and obtain a phenotype consistent with a type 2 immune microenvironment. We anticipate that this unique resource will prove invaluable for future investigation of T cell function in biomedical research, the development of vaccination and health management in aquaculture, and for further research into the evolution of adaptive immunity.European Research Council (Grant IDs: ERC-2011-StG-282059 (PROMINENT), 677501 (ZF_Blood)), Biotechnology and Biological Sciences Research Council (Grant ID: BB/L007401/1), Dowager Countess Eleanor Peel Trust (Grant ID: TH-PRCL.FID2228), Medical Research Council, Department for International Development (Career Development Award Fellowship MR/J009156/1), Medical Research Foundation (Grant ID: R/140419), Cancer Research UK (Grant ID: C45041/A14953), Wellcome Trust and Medical Research Council to the Wellcome TrustâMedical Research Council Cambridge Stem Cell Institute (core support grant)This is the final version of the article. It first appeared from The American Association of Immunologists via https://doi.org/10.4049/âjimmunol.160095
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Single-cell transcriptional analysis reveals ILC-like cells in zebrafish.
Innate lymphoid cells (ILCs) are important mediators of the immune response and homeostasis in barrier tissues of mammals. However, the existence and function of ILCs in other vertebrates are poorly understood. Here, we use single-cell RNA sequencing to generate a comprehensive atlas of zebrafish lymphocytes during tissue homeostasis and after immune challenge. We profiled 14,080 individual cells from the gut of wild-type zebrafish, as well as of rag1-deficient zebrafish that lack T and B cells, and discovered populations of ILC-like cells. We uncovered a rorc-positive subset of ILCs that could express cytokines associated with type 1, 2, and 3 responses upon immune challenge. Specifically, these ILC-like cells expressed il22 and tnfa after exposure to inactivated bacteria or il13 after exposure to helminth extract. Cytokine-producing ILC-like cells express a specific repertoire of novel immune-type receptors, likely involved in recognition of environmental cues. We identified additional novel markers of zebrafish ILCs and generated a cloud repository for their in-depth exploration.The study was supported by Cancer Research UK grant number C45041/A14953 (to A.C. and E.I.A.), European Research Council project 677501 â ZF_Blood (to A.C. and P.M.S.), EMBO Long-Term Fellowship ALTF-807-2015 (to P.P.H), ANR grant 17-CE15-0017-01 â ZF-ILC (to P.P.H) and ANR-16-CE20-0002-03 (to J.-P.L), H2020-MSCA-IF-2015 grant 708128 â ZF-ILC (to P.P.H), ANR-10-LABX-73 (âreviveâ to P. Herbomel) and a core support grant from the Wellcome Trust and MRC to the Wellcome Trust â Medical Research Council Cambridge Stem Cell Institute
GeneStoryTeller: a mobile app for quick and comprehensive information retrieval of human genes
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Single-cell and spatial transcriptomics analysis of non-small cell lung cancer
Acknowledgements: The authors are greatly thankful to the Papworth Hospital Research Tissue Bank for providing samples with data, and in particular to D. Rassl. The authors would like to thank L. Campos for the annotation of tumour histologies; A.M. Ranzoni, B. Myers and E. Panada for sample collection and processing; M. Nelson for computational support with initial clustering of scRNA-Seq and application of cell2location; Alessandro Di Tullio, GSK for insightful discussions; Cancer Research UK Cambridge Institute (CRUK CI) (Grant # CTRQQR-2021\100012) Genomics Core Facility for library preparation and sequencing services; Wellcome Sanger Institute (WSI) DNA pipelines for their contribution to sequencing the data; S. Leonard from New Pipeline Group (NPG) for pre-processing of sequencing data; the Cambridge NIHR BRC Cell Phenotyping Hub for support with cell sorting. We thank R. Möller, P. Rainer, and U. Tiemann for critically reading the manuscript. This study was conceived and funded by Open Targets (OTAR2060, A.C.); Core support grants from the Wellcome Trust and Wellcome Sanger Institute and both Wellcome and the MRC to the Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute (203151/Z/16/Z, A.C.); European Research Council (CONTEXT 101043559, A.C.); Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.Funder: Open Targets (OTAR2060); Core support grants from the Wellcome Trust and Wellcome Sanger Institute and both Wellcome and the MRC to the Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute (203151/Z/16/Z); European Research Council (CONTEXT 101043559); Cancer Research UK Cambridge Institute (CRUK CI) (Grant # CTRQQR-2021\100012).AbstractLung cancer is the second most frequently diagnosed cancer and the leading cause of cancer-related mortality worldwide. Tumour ecosystems feature diverse immune cell types. Myeloid cells, in particular, are prevalent and have a well-established role in promoting the disease. In our study, we profile approximately 900,000 cells from 25 treatment-naive patients with adenocarcinoma and squamous-cell carcinoma by single-cell and spatial transcriptomics. We note an inverse relationship between anti-inflammatory macrophages and NK cells/T cells, and with reduced NK cell cytotoxicity within the tumour. While we observe a similar cell type composition in both adenocarcinoma and squamous-cell carcinoma, we detect significant differences in the co-expression of various immune checkpoint inhibitors. Moreover, we reveal evidence of a transcriptional âreprogrammingâ of macrophages in tumours, shifting them towards cholesterol export and adopting a foetal-like transcriptional signature which promotes iron efflux. Our multi-omic resource offers a high-resolution molecular map of tumour-associated macrophages, enhancing our understanding of their role within the tumour microenvironment.</jats:p
Computerized Analysis of Digital Subtraction Angiography: A Tool for Quantitative In-vivo Vascular Imaging
The purpose of our study was to develop a user-independent computerized tool for the automated segmentation and quantitative assessment of in vivo-acquired digital subtraction angiography (DSA) images. Vessel enhancement was accomplished based on the concept of image structural tensor. The developed software was tested on a series of DSA images acquired from one animal and two human angiogenesis models. Its performance was evaluated against manually segmented images. A receiverâs operating characteristic curve was obtained for every image with regard to the different percentages of the image histogram. The area under the mean curve was 0.89 for the experimental angiogenesis model and 0.76 and 0.86 for the two clinical angiogenesis models. The coordinates of the operating point were 8.3% false positive rate and 92.8% true positive rate for the experimental model. Correspondingly for clinical angiogenesis models, the coordinates were 8.6% false positive rate and 89.2% true positive rate and 9.8% false positive rate and 93.8% true positive rate, respectively. A new user-friendly tool for the analysis of vascular networks in DSA images was developed that can be easily used in either experimental or clinical studies. Its main characteristics are robustness and fast and automatic execution