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Mehrotra P, Ikhapoh I, Lei P, Tseropoulos G, Zhang Y, Wang J, Liu S, Bronner ME, Andreadis ST. Wnt/BMP Mediated Metabolic Reprogramming Preserves Multipotency of Neural Crest-Like Stem Cells. Stem Cells 2023; 41:287-305. [PMID: 36617947 PMCID: PMC10020983 DOI: 10.1093/stmcls/sxad001] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [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: 07/05/2022] [Accepted: 12/27/2022] [Indexed: 01/10/2023]
Abstract
Neural crest-like stem cells resembling embryonic neural crest cells (NCs) can be derived from adult human tissues such as the epidermis. However, these cells lose their multipotency rapidly in culture limiting their expansion for clinical use. Here, we show that the multipotency of keratinocyte-derived NCs (KC-NCs) can be preserved by activating the Wnt and BMP signaling axis, promoting expression of key NC-specifier genes and ultimately enhancing their differentiation potential. We also show that transcriptional changes leading to multipotency are linked to metabolic reprogramming of KC-NCs to a highly glycolytic state. Specifically, KC-NCs treated with CHIR and BMP2 rely almost exclusively on glycolysis for their energy needs, as seen by increased lactate production, glucose uptake, and glycolytic enzyme activities. This was accompanied by mitochondrial depolarization and decreased mitochondrial ATP production. Interestingly, the glycolytic end-product lactate stabilized β-catenin and further augmented NC-gene expression. Taken together, our study shows that activation of the Wnt/BMP signaling coordinates the metabolic demands of neural crest-like stem cells governing decisions regarding multipotency and differentiation, with possible implications for regenerative medicine.
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Affiliation(s)
- Pihu Mehrotra
- Department of Chemical and Biological Engineering, University at Buffalo, Buffalo, NY, USA
| | - Izuagie Ikhapoh
- Department of Chemical and Biological Engineering, University at Buffalo, Buffalo, NY, USA
| | - Pedro Lei
- Department of Chemical and Biological Engineering, University at Buffalo, Buffalo, NY, USA
| | - Georgios Tseropoulos
- Department of Chemical and Biological Engineering, University at Buffalo, Buffalo, NY, USA
| | - Yali Zhang
- Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Jianmin Wang
- Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Song Liu
- Department of Biostatistics and Bioinformatics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Marianne E Bronner
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Stelios T Andreadis
- Department of Chemical and Biological Engineering, University at Buffalo, Buffalo, NY, USA
- Department of Biomedical Engineering, University at Buffalo, NY, Buffalo, NY, USA
- Center of Excellence in Bioinformatics and Life Sciences, University at Buffalo, Buffalo, NY, USA
- Center for Cell, Gene and Tissue Engineering (CGTE), University at Buffalo, Buffalo, NY, USA
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