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Bidanta S, Börner K, Herr BW, Nagy M, Gustilo KS, Bajema R, Maier L, Molontay R, Weber G. Functional Tissue Units in the Human Reference Atlas. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.16.562593. [PMID: 37905079 PMCID: PMC10614912 DOI: 10.1101/2023.10.16.562593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Functional tissue units (FTUs) form the basic building blocks of organs and are important for understanding and modeling the healthy physiological function of the organ and changes during disease states. In this first comprehensive catalog of FTUs, we document the definition, physical dimensions, vasculature, and cellular composition of 22 anatomically correct, nested functional tissue units (FTUs) in 10 healthy human organs. The catalog includes datasets, illustrations, an interactive online FTU explorer, and a large printable poster. All data and code are freely available. This is part of a larger ongoing international effort to construct a Human Reference Atlas (HRA) of all cells in the human body.
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Affiliation(s)
- Supriya Bidanta
- Department of Intelligent Systems Engineering, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN 47408, USA
| | - Katy Börner
- Department of Intelligent Systems Engineering, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN 47408, USA
| | - Bruce W Herr
- Department of Intelligent Systems Engineering, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN 47408, USA
| | - Marcell Nagy
- Department of Stochastics, Institute of Mathematics, Budapest University of Technology and Economics, Muegyetem rkp. 3., H-1111 Budapest, Hungary
| | - Katherine S Gustilo
- Department of Intelligent Systems Engineering, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN 47408, USA
| | - Rachel Bajema
- Department of Intelligent Systems Engineering, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN 47408, USA
| | - Libby Maier
- Department of Intelligent Systems Engineering, Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN 47408, USA
| | - Roland Molontay
- Department of Stochastics, Institute of Mathematics, Budapest University of Technology and Economics, Muegyetem rkp. 3., H-1111 Budapest, Hungary
| | - Griffin Weber
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
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Rinschen MM, Saez-Rodriguez J. The tissue proteome in the multi-omic landscape of kidney disease. Nat Rev Nephrol 2020; 17:205-219. [PMID: 33028957 DOI: 10.1038/s41581-020-00348-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/14/2020] [Indexed: 02/07/2023]
Abstract
Kidney research is entering an era of 'big data' and molecular omics data can provide comprehensive insights into the molecular footprints of cells. In contrast to transcriptomics, proteomics and metabolomics generate data that relate more directly to the pathological symptoms and clinical parameters observed in patients. Owing to its complexity, the proteome still holds many secrets, but has great potential for the identification of drug targets. Proteomics can provide information about protein synthesis, modification and degradation, as well as insight into the physical interactions between proteins, and between proteins and other biomolecules. Thus far, proteomics in nephrology has largely focused on the discovery and validation of biomarkers, but the systematic analysis of the nephroproteome can offer substantial additional insights, including the discovery of mechanisms that trigger and propagate kidney disease. Moreover, proteome acquisition might provide a diagnostic tool that complements the assessment of a kidney biopsy sample by a pathologist. Such applications are becoming increasingly feasible with the development of high-throughput and high-coverage technologies, such as versatile mass spectrometry-based techniques and protein arrays, and encourage further proteomics research in nephrology.
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Affiliation(s)
- Markus M Rinschen
- Department of Biomedicine, Aarhus University, Aarhus, Denmark. .,III. Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. .,Department II of Internal Medicine and Center for Molecular Medicine Cologne, University of Cologne, Cologne, Germany. .,Department of Chemistry, Scripps Center for Metabolomics and Mass Spectrometry, Scripps Research, La Jolla, CA, USA.
| | - Julio Saez-Rodriguez
- Institute for Computational Biomedicine, Faculty of Medicine, Heidelberg University, and Heidelberg University Hospital, Bioquant, Heidelberg, Germany.,Joint Research Center for Computational Biomedicine, RWTH Aachen University Hospital, Aachen, Germany.,Molecular Medicine Partnership Unit, European Molecular Biology Laboratory and Heidelberg University, Heidelberg, Germany
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