Volume 13 Issue 7
Jul.  2023
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Baocai Xie, Dengfeng Gao, Biqiang Zhou, Shi Chen, Lianrong Wang. New discoveries in the field of metabolism by applying single-cell and spatial omics[J]. Journal of Pharmaceutical Analysis, 2023, 13(7): 711-725. doi: 10.1016/j.jpha.2023.06.002
Citation: Baocai Xie, Dengfeng Gao, Biqiang Zhou, Shi Chen, Lianrong Wang. New discoveries in the field of metabolism by applying single-cell and spatial omics[J]. Journal of Pharmaceutical Analysis, 2023, 13(7): 711-725. doi: 10.1016/j.jpha.2023.06.002

New discoveries in the field of metabolism by applying single-cell and spatial omics

doi: 10.1016/j.jpha.2023.06.002
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This work was supported by the National Key Research and Development Program of China (Program No.: 2019YFA0904300), Shenzhen Science and Technology Program (Program No.: JCYJ20220530150404009), and the Guangdong Basic and Applied Basic Research Foundation (Grant No.: 2022A1515110608).

  • Received Date: Oct. 30, 2022
  • Accepted Date: Jun. 02, 2023
  • Rev Recd Date: May 29, 2023
  • Publish Date: Jun. 04, 2023
  • Single-cell multi-Omics (SCM-Omics) and spatial multi-Omics (SM-Omics) technologies provide state-of-the-art methods for exploring the composition and function of cell types in tissues/organs. Since its emergence in 2009, single-cell RNA sequencing (scRNA-seq) has yielded many groundbreaking new discoveries. The combination of this method with the emergence and development of SM-Omics techniques has been a pioneering strategy in neuroscience, developmental biology, and cancer research, especially for assessing tumor heterogeneity and T-cell infiltration. In recent years, the application of these methods in the study of metabolic diseases has also increased. The emerging SCM-Omics and SM-Omics approaches allow the molecular and spatial analysis of cells to explore regulatory states and determine cell fate, and thus provide promising tools for unraveling heterogeneous metabolic processes and making them amenable to intervention. Here, we review the evolution of SCM-Omics and SM-Omics technologies, and describe the progress in the application of SCM-Omics and SM-Omics in metabolism-related diseases, including obesity, diabetes, nonalcoholic fatty liver disease (NAFLD) and cardiovascular disease (CVD). We also conclude that the application of SCM-Omics and SM-Omics approaches can help resolve the molecular mechanisms underlying the pathogenesis of metabolic diseases in the body and facilitate therapeutic measures for metabolism-related diseases. This review concludes with an overview of the current status of this emerging field and the outlook for its future.
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