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Liu S, Ezran C, Wang MFZ, Li Z, Awayan K, Long JZ, De Vlaminck I, Wang S, Epelbaum J, Kuo CS, Terrien J, Krasnow MA, Ferrell JE. An organism-wide atlas of hormonal signaling based on the mouse lemur single-cell transcriptome. Nat Commun 2024; 15:2188. [PMID: 38467625 PMCID: PMC10928088 DOI: 10.1038/s41467-024-46070-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 02/07/2024] [Indexed: 03/13/2024] Open
Abstract
Hormones mediate long-range cell communication and play vital roles in physiology, metabolism, and health. Traditionally, endocrinologists have focused on one hormone or organ system at a time. Yet, hormone signaling by its very nature connects cells of different organs and involves crosstalk of different hormones. Here, we leverage the organism-wide single cell transcriptional atlas of a non-human primate, the mouse lemur (Microcebus murinus), to systematically map source and target cells for 84 classes of hormones. This work uncovers previously-uncharacterized sites of hormone regulation, and shows that the hormonal signaling network is densely connected, decentralized, and rich in feedback loops. Evolutionary comparisons of hormonal genes and their expression patterns show that mouse lemur better models human hormonal signaling than mouse, at both the genomic and transcriptomic levels, and reveal primate-specific rewiring of hormone-producing/target cells. This work complements the scale and resolution of classical endocrine studies and sheds light on primate hormone regulation.
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Affiliation(s)
- Shixuan Liu
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford, CA, USA
| | - Camille Ezran
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford, CA, USA
| | - Michael F Z Wang
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA
| | - Zhengda Li
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Kyle Awayan
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Jonathan Z Long
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Sarafan ChEM-H, Stanford, CA, USA
| | - Iwijn De Vlaminck
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA
| | - Sheng Wang
- Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA, USA
| | - Jacques Epelbaum
- Adaptive Mechanisms and Evolution (MECADEV), UMR 7179, National Center for Scientific Research, National Museum of Natural History, Brunoy, France
| | - Christin S Kuo
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Jérémy Terrien
- Adaptive Mechanisms and Evolution (MECADEV), UMR 7179, National Center for Scientific Research, National Museum of Natural History, Brunoy, France
| | - Mark A Krasnow
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford, CA, USA.
| | - James E Ferrell
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Biochemistry, Stanford University School of Medicine, Stanford, CA, USA.
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