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Akhtar J, Imran M, Wang G. Protocol for live-cell Förster resonance energy transfer imaging to reveal the bistable insulin response of single C2C12-derived myotubes. STAR Protoc 2024; 5:103109. [PMID: 38829736 PMCID: PMC11179099 DOI: 10.1016/j.xpro.2024.103109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 04/26/2024] [Accepted: 05/14/2024] [Indexed: 06/05/2024] Open
Abstract
Based on our hypothesis that myotubes exhibit a bistable response to insulin, here we present a protocol for finely measuring Akt phosphorylation in single myotubes under insulin stimulation. We describe steps to stably express a Förster resonance energy transfer (FRET)-based Akt biosensor in C2C12-derived myotubes and perform single-cell FRET imaging. This protocol highlights its potential for precision medicine in analyzing protein phosphorylation dynamics at the single-cell level. For complete details on the use and execution of this protocol, please refer to Akhtar et al.1.
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Affiliation(s)
- Javed Akhtar
- Futian Biomedical Innovation R&D Center, The Chinese University of Hong Kong, Shenzhen 518172, China; Biomedical Science and Engineering, School of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China; Ciechanover Institute of Precision and Regenerative Medicine, School of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China; Center for Endocrinology and Metabolic Diseases, Second Affiliated Hospital, The Chinese University of Hong Kong, Shenzhen 518172, China
| | - Muhammad Imran
- Department of Computer Science & IT, Institute of Southern Punjab, Multan, Pakistan
| | - Guanyu Wang
- Futian Biomedical Innovation R&D Center, The Chinese University of Hong Kong, Shenzhen 518172, China; Biomedical Science and Engineering, School of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China; Ciechanover Institute of Precision and Regenerative Medicine, School of Medicine, The Chinese University of Hong Kong, Shenzhen 518172, China; Center for Endocrinology and Metabolic Diseases, Second Affiliated Hospital, The Chinese University of Hong Kong, Shenzhen 518172, China.
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Jiang Z, Lu L, Liu Y, Zhang S, Li S, Wang G, Wang P, Chen L. SMAD7 and SERPINE1 as novel dynamic network biomarkers detect and regulate the tipping point of TGF-beta induced EMT. Sci Bull (Beijing) 2020; 65:842-853. [PMID: 36659203 DOI: 10.1016/j.scib.2020.01.013] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Revised: 10/21/2019] [Accepted: 11/18/2019] [Indexed: 01/21/2023]
Abstract
Epithelial-mesenchymal transition (EMT) is a complex nonlinear biological process that plays essential roles in fundamental biological processes such as embryogenesis, wounding healing, tissue regeneration, and cancer metastasis. A hallmark of EMT is the switch-like behavior during state transition, which is characteristic of phase transitions. Hence, detecting the tipping point just before mesenchymal state transition is critical for understanding molecular mechanism of EMT. Through dynamic network biomarkers (DNB) model, a DNB group with 37 genes was identified which can provide the early-warning signals of EMT. Particularly, we found that two DNB genes, i.e., SMAD7 and SERPINE1 promoted EMT by switching their regulatory network which was further validated by biological experiments. Survival analyses revealed that SMAD7 and SERPINE1 as DNB genes further acted as prognostic biomarkers for lung adenocarcinoma.
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Affiliation(s)
- Zhonglin Jiang
- Key Laboratory of Systems Biology, Center for Excellence in Molecular Cell Science, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Lina Lu
- Key Laboratory of Systems Biology, Center for Excellence in Molecular Cell Science, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China
| | - Yuwei Liu
- Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai 200241, China; Laboratory of Systems Biology, Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 200031, China
| | - Si Zhang
- Key Laboratory of Systems Biology, Center for Excellence in Molecular Cell Science, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Shuxian Li
- Key Laboratory of Systems Biology, Center for Excellence in Molecular Cell Science, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Guanyu Wang
- Guangdong Provincial Key Laboratory of Cell Microenviroment and Disease Research, Guangdong Provincial Key Laboratory of Computational Science and Material Design, Department of Biology, Southern University of Science and Technology, Shenzhen 518055, China.
| | - Peng Wang
- Bio-med Big Data Center, Key Laboratory of Computational Biology, CAS-MPG Partner Institute of Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China.
| | - Luonan Chen
- Key Laboratory of Systems Biology, Center for Excellence in Molecular Cell Science, Institute of Biochemistry and Cell Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai 200031, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China.
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