{"id":["DOI:10.1038/s41586-024-07944-6"],"title":["A spatial human thymus cell atlas mapped to a continuous tissue axis"],"publication_date":["2024-11-20"],"authors":{"ORCID:0000-0002-7034-0524":{"id":["ORCID:0000-0002-7034-0524"],"family_name":["Yayon"],"personal_name":["Nadav"],"affiliations":{"ROR:05cy4wa09":{"organization_name":["Wellcome Sanger Institute"]},"ROR:02catss52":{"organization_name":["European Bioinformatics Institute"]}}},"ORCID:0000-0001-6563-0829":{"id":["ORCID:0000-0001-6563-0829"],"family_name":["Kedlian"],"personal_name":["Veronika R."],"affiliations":{"ROR:05cy4wa09":{"organization_name":["Wellcome Sanger Institute"]},"ROR:05nz0zp31":{"organization_name":["Wellcome/MRC Cambridge Stem Cell Institute"]}}},"ORCID:0000-0001-7593-7533":{"id":["ORCID:0000-0001-7593-7533"],"family_name":["Boehme"],"personal_name":["Lena"],"affiliations":{"ROR:00cv9y106":{"organization_name":["Ghent 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Stem Cell Institute"]}}},"ORCID:0000-0001-8815-5485":{"id":["ORCID:0000-0001-8815-5485"],"family_name":["Van Nieuwerburgh"],"personal_name":["Filip"],"affiliations":{"ROR:00cv9y106":{"organization_name":["Ghent University"]}}},"ORCID:0000-0001-6055-277X":{"id":["ORCID:0000-0001-6055-277X"],"family_name":["Bayraktar"],"personal_name":["Omer"],"affiliations":{"ROR:05cy4wa09":{"organization_name":["Wellcome Sanger Institute"]}}},"AUTHTEMP:00067":{"id":["AUTHTEMP:00067"],"family_name":["Patel"],"personal_name":["Minal"],"affiliations":{"ROR:05cy4wa09":{"organization_name":["Wellcome Sanger Institute"]}}},"AUTHTEMP:00068":{"id":["AUTHTEMP:00068"],"family_name":["Davies"],"personal_name":["E. Graham"],"affiliations":{"ROR:00zn2c847":{"organization_name":["Great Ormond Street Hospital"]}}},"ORCID:0000-0002-3927-2084":{"id":["ORCID:0000-0002-3927-2084"],"family_name":["Haniffa"],"personal_name":["Muzlifah"],"affiliations":{"ROR:05cy4wa09":{"organization_name":["Wellcome Sanger Institute"]},"ROR:01kj2bm70":{"organization_name":["Newcastle University"]},"ROR:05p40t847":{"organization_name":["Newcastle upon Tyne Hospitals NHS Foundation Trust"]},"ROR:0187kwz08":{"organization_name":["National Institute for Health Research"]}},"HDBItheme":["BloodAndImmune"]},"ORCID:0000-0002-2859-9241":{"id":["ORCID:0000-0002-2859-9241"],"family_name":["Uhlmann"],"personal_name":["Virginie"],"affiliations":{"ROR:02catss52":{"organization_name":["European Bioinformatics Institute"]}}},"ORCID:0000-0002-8335-0262":{"id":["ORCID:0000-0002-8335-0262"],"family_name":["Notarangelo"],"personal_name":["Luigi D."],"affiliations":{"ROR:043z4tv69":{"organization_name":["National Institute of Allergy and Infectious Diseases"]}}},"ORCID:0000-0003-1495-9143":{"id":["ORCID:0000-0003-1495-9143"],"family_name":["Germain"],"personal_name":["Ronald N."],"affiliations":{"ROR:043z4tv69":{"organization_name":["National Institute of Allergy and Infectious Diseases"]}}},"ORCID:0000-0003-4379-8967":{"id":["ORCID:0000-0003-4379-8967"],"family_name":["Radtke"],"personal_name":["Andrea J."],"affiliations":{"ROR:043z4tv69":{"organization_name":["National Institute of Allergy and Infectious Diseases"]}}},"ORCID:0000-0001-9092-0852":{"id":["ORCID:0000-0001-9092-0852"],"family_name":["Marioni"],"personal_name":["John"],"affiliations":{"ROR:05cy4wa09":{"organization_name":["Wellcome Sanger Institute"]},"ROR:02catss52":{"organization_name":["European Bioinformatics Institute"]},"ROR:0068m0j38":{"organization_name":["Cancer Research UK Cambridge Center"]}}},"ORCID:0000-0002-5781-0288":{"id":["ORCID:0000-0002-5781-0288"],"family_name":["Taghon"],"personal_name":["Tom"],"affiliations":{"ROR:00cv9y106":{"organization_name":["Ghent University"]}}},"ORCID:0000-0002-6294-6366":{"id":["ORCID:0000-0002-6294-6366"],"family_name":["Teichmann"],"personal_name":["Sarah A."],"affiliations":{"ROR:05cy4wa09":{"organization_name":["Wellcome Sanger Institute"]},"ROR:013meh722":{"organization_name":["University of Cambridge"]}}}},"abstract":["T cells develop from circulating precursor cells, which enter the thymus and migrate through specialized subcompartments that support their maturation and selection1. In humans, this process starts in early fetal development and is highly active until thymic involution in adolescence. To map the microanatomical underpinnings of this process in pre- and early postnatal stages, we established a quantitative morphological framework for the thymus-the Cortico-Medullary Axis-and used it to perform a spatially resolved analysis. Here, by applying this framework to a curated multimodal single-cell atlas, spatial transcriptomics and high-resolution multiplex imaging data, we demonstrate establishment of the lobular cytokine network, canonical thymocyte trajectories and thymic epithelial cell distributions by the beginning of the the second trimester of fetal development. We pinpoint tissue niches of thymic epithelial cell progenitors and distinct subtypes associated with Hassall's corpuscles and identify divergence in the timing of medullary entry between CD4 and CD8 T cell lineages. These findings provide a basis for a detailed understanding of T lymphocyte development and are complemented with a holistic toolkit for cross-platform imaging data analysis, annotation and OrganAxis construction (TissueTag), which can be applied to any tissue."],"HDBItheme":["BloodAndImmune"],"datasets":{"EGA:EGAD00001015384":{"id":["EGA:EGAD00001015384"],"title":["A spatial human thymus cell atlas mapped to a continuous tissue axis"],"description":["T cells develop from circulating precursor cells, which enter the thymus and migrate through specialised sub-compartments that support their maturation and selection. In humans, this process starts in early fetal development and is highly active until thymic involution in adolescence. To map the micro-anatomical underpinnings of this process in pre- and early postnatal stages, we established a novel quantitative morphological framework for the thymus, the Cortico-Medullary Axis, and used it to perform a spatially resolved analysis. By applying this framework to a curated multimodal single-cell atlas, spatial transcriptomics, and high-resolution multiplex imaging data, we demonstrate establishment of the lobular cytokine network, canonical thymocyte trajectories and thymic epithelial cell distributions within the first trimester of fetal development. We pinpoint tissue niches of thymic epithelial cell progenitors and distinct subtypes associated with Hassall’s corpuscles and uncover divergence in the timing of medullary entry between CD4 vs. CD8 T cell lineages. These findings provide a basis for a detailed understanding of T lymphocyte development and are complemented with a holistic toolkit for cross-platform imaging data analysis, annotation, and Organ Axis construction (TissueTag), which can be applied to any tissue."],"authors":{},"tags":["sequencing","spatial","imaging"]},"GEO:GSE271304":{"id":["GEO:GSE271304"],"title":["Multimodal profiling of human postnatal thymocytes using CITE-seq"],"description":["T cell development in the human thymus has primarily been studied using antibody-based approaches, such as flow cytometry, which can create difficulties in translating phenotypic findings to scRNA-seq data. In order to bridge this gap and obtain paired surface protein and RNA information for individual cells, we carried out CITE-seq with a 143-plex customised antibody panel on human postnatal thymocytes. This was further combined with TCR-seq for TRA and TRB loci to gain insights into the V(D)J recombination progress in developing cells. Using information from all three modalities, we annotated over 30 different stages of human T cell development, which align with known surface marker profiles. This data was utilised in the context of the human thymus spatial atlas for high-resolution spatial mapping of developing T cells, which revealed differences in the migration and maturation kinetics of CD4 and CD8 lineage single positive thymocytes.\nThymocytes from 5 paediatric donors were stained with a TotalSeq-C panel containing antibodies against 143 surface markers and 7 isotype controls. Cells were sorted into CD3+ and CD3- subsets to enrich for immature stages and profiled using the 10X Genomics 5’ kit v2."],"authors":{"ORCID:0000-0001-7593-7533":{"id":["ORCID:0000-0001-7593-7533"],"family_name":["Boehme"],"personal_name":["Lena"],"affiliations":{"ROR:00cv9y106":{"organization_name":["Ghent University"]}}},"ORCID:0000-0001-8844-3700":{"id":["ORCID:0000-0001-8844-3700"],"family_name":["Van Hulle"],"personal_name":["Jolien"],"affiliations":{"ROR:00cv9y106":{"organization_name":["Ghent University"]}}},"ORCID:0000-0002-5781-0288":{"id":["ORCID:0000-0002-5781-0288"],"family_name":["Taghon"],"personal_name":["Tom"],"affiliations":{"ROR:00cv9y106":{"organization_name":["Ghent University"]}}}},"tags":["sequencing"]},"ENA:PRJEB77091":{"id":["ENA:PRJEB77091"],"title":["A spatial human thymus cell atlas mapped to a continuous tissue axis"],"description":["T cells develop from circulating precursor cells, which enter the thymus and migrate through specialised sub-compartments that support their maturation and selection. In humans, this process starts in early fetal development and is highly active until thymic involution in adolescence. To map the micro-anatomical underpinnings of this process in pre- and early postnatal stages, we established a novel quantitative morphological framework for the thymus, the Cortico-Medullary Axis, and used it to perform a spatially resolved analysis. By applying this framework to a curated multimodal single-cell atlas, spatial transcriptomics, and high-resolution multiplex imaging data, we demonstrate establishment of the lobular cytokine network, canonical thymocyte trajectories and thymic epithelial cell distributions within the first trimester of fetal development. We pinpoint tissue niches of thymic epithelial cell progenitors and distinct subtypes associated with Hassall’s corpuscles and uncover divergence in the timing of medullary entry between CD4 vs. CD8 T cell lineages. These findings provide a basis for a detailed understanding of T lymphocyte development and are complemented with a holistic toolkit for cross-platform imaging data analysis, annotation, and Organ Axis construction (TissueTag), which can be applied to any tissue."],"authors":{},"tags":["spatial","imaging","sequencing"]},"BioStudies:S-BIAD1257":{"id":["BioStudies:S-BIAD1257"],"title":["A spatial human thymus cell atlas mapped to a continuous tissue axis"],"description":["T cells develop from circulating precursor cells, which enter the thymus and migrate through specialised sub-compartments that support their maturation and selection. In humans, this process starts in early fetal development and is highly active until thymic involution in adolescence. To map the micro-anatomical underpinnings of this process in pre- and early postnatal stages, we established a novel quantitative morphological framework for the thymus, the Cortico-Medullary Axis, and used it to perform a spatially resolved analysis. By applying this framework to a curated multimodal single-cell atlas, spatial transcriptomics, and high-resolution multiplex imaging data, we demonstrate establishment of the lobular cytokine network, canonical thymocyte trajectories and thymic epithelial cell distributions within the first trimester of fetal development. We pinpoint tissue niches of thymic epithelial cell progenitors and distinct subtypes associated with Hassall’s corpuscles and uncover divergence in the timing of medullary entry between CD4 vs. CD8 T cell lineages. These findings provide a basis for a detailed understanding of T lymphocyte development and are complemented with a holistic toolkit for cross-platform imaging data analysis, annotation, and Organ Axis construction (TissueTag), which can be applied to any tissue."],"authors":{"ORCID:0000-0002-7034-0524":{"id":["ORCID:0000-0002-7034-0524"],"family_name":["Yayon"],"personal_name":["Nadav"],"affiliations":{"ROR:05cy4wa09":{"organization_name":["Wellcome Sanger Institute"]},"ROR:02catss52":{"organization_name":["European Bioinformatics Institute"]}}},"ORCID:0000-0002-6294-6366":{"id":["ORCID:0000-0002-6294-6366"],"family_name":["Teichmann"],"personal_name":["Sarah A."],"affiliations":{"ROR:05cy4wa09":{"organization_name":["Wellcome Sanger Institute"]},"ROR:013meh722":{"organization_name":["University of Cambridge"]}}},"ORCID:0000-0003-4379-8967":{"id":["ORCID:0000-0003-4379-8967"],"family_name":["Radtke"],"personal_name":["Andrea J."],"affiliations":{"ROR:043z4tv69":{"organization_name":["National Institute of Allergy and Infectious Diseases"]}}},"ORCID:0000-0003-1495-9143":{"id":["ORCID:0000-0003-1495-9143"],"family_name":["Germain"],"personal_name":["Ronald N."],"affiliations":{"ROR:043z4tv69":{"organization_name":["National Institute of Allergy and Infectious Diseases"]}}}},"tags":["spatial","imaging","sequencing"]}},"code":{"SWHID:swh:1:dir:344d7823ce84dcd2bb0cc24710662d767e801583":{"id":["SWHID:swh:1:dir:344d7823ce84dcd2bb0cc24710662d767e801583"],"title":["Human Thymus Spatial Atlas"],"description":["This repository holds all the computational components of the Human Thymus Spatial Atlas."],"authors":{"ORCID:0000-0002-7034-0524":{"id":["ORCID:0000-0002-7034-0524"],"family_name":["Yayon"],"personal_name":["Nadav"],"affiliations":{"ROR:05cy4wa09":{"organization_name":["Wellcome Sanger Institute"]},"ROR:02catss52":{"organization_name":["European Bioinformatics Institute"]}}}}},"SWHID:swh:1:dir:3f0e4eed83a1fc303963218b5dc3d407c7ec8f7e":{"id":["SWHID:swh:1:dir:3f0e4eed83a1fc303963218b5dc3d407c7ec8f7e"],"title":["TissueTag: Jupyter Image Annotator"],"description":["TissueTag consists of two major components:\n1) Jupyter-based image annotation tool:Utilising the Bokeh Python library (http://www.bokeh.pydata.org) empowered by Datashader (https://datashader.org/index.html) and holoviews (https://holoviews.org/index.html) for pyramidal image rendering.\nThis tool offers a streamlined annotation solution with subpixel resolution for quick interactive annotation of various image types (e.g., brightfield, fluorescence). TissueTag produces labelled images (e.g., cortex, medulla) and logs all tissue labels,\nand annotation resolution and colours for reproducibility.\n\n2) Mapping annotations to data: This component facilitates the migration of annotations to spots/cells based on overlap with annotated structures.\nIt also logs the minimum Euclidean distance of each spot/cell to the discrete annotations,\noffering continuous annotation. This contains spatial neighbourhood information,\nadding to the x-y coordinates of a given spot or cell,\nand is foundational for calculating a morphological axis (OrganAxis, see tutorials).\n\nNote: A labeled image is an integer array where each pixel value (0,1,2,…) corresponds to an annotated structure.\n\nAnnotator: Enables interactive annotation of predefined anatomical objects via convex shape filling while toggeling between reference and annotation image.\n\nWe envision this tool as a foundational starting point as its simplicity and transparent nature allows for many potential enhancements, additions and spinoffs.\nSo contributions and suggestions are highly appreciated!\n\nCurated online tutorial for OrganAxis (https://organ-axis-tutorial.readthedocs.io)."],"authors":{"ORCID:0000-0002-7034-0524":{"id":["ORCID:0000-0002-7034-0524"],"family_name":["Yayon"],"personal_name":["Nadav"],"affiliations":{"ROR:05cy4wa09":{"organization_name":["Wellcome Sanger Institute"]},"ROR:02catss52":{"organization_name":["European Bioinformatics Institute"]}}},"ORCID:0000-0002-8070-0378":{"id":["ORCID:0000-0002-8070-0378"],"family_name":["Amsalem"],"personal_name":["Oren"],"affiliations":{"ROR:04drvxt59":{"organization_name":["Beth Israel Deaconess Medical Center"]}}},"ORCID:0000-0002-8327-8096":{"id":["ORCID:0000-0002-8327-8096"],"family_name":["Yang"],"personal_name":["Andrian"],"affiliations":{"ROR:05nz0zp31":{"organization_name":["Wellcome/MRC Cambridge Stem Cell Institute"]},"ROR:02catss52":{"organization_name":["European Bioinformatics Institute"]}}},"ORCID:0000-0002-2586-9576":{"id":["ORCID:0000-0002-2586-9576"],"family_name":["Polański"],"personal_name":["Krzysztof"],"affiliations":{"ROR:05cy4wa09":{"organization_name":["Wellcome Sanger Institute"]}}}}}}}