| First Author | Cardot-Ruffino V | Year | 2020 |
| Journal | Sci Rep | Volume | 10 |
| Issue | 1 | Pages | 3880 |
| PubMed ID | 32127548 | Mgi Jnum | J:294598 |
| Mgi Id | MGI:6407356 | Doi | 10.1038/s41598-020-60272-3 |
| Citation | Cardot-Ruffino V, et al. (2020) Generation of a conditional Flpo/FRT mouse model expressing constitutively active TGFbeta in fibroblasts. Sci Rep 10(1):3880 |
| abstractText | Transforming growth factor (TGFbeta) is a secreted factor, which accumulates in tissues during many physio- and pathological processes such as embryonic development, wound healing, fibrosis and cancer. In order to analyze the effects of increased microenvironmental TGFbeta concentration in vivo, we developed a conditional transgenic mouse model (Flpo/Frt system) expressing bioactive TGFbeta in fibroblasts, a cell population present in the microenvironment of almost all tissues. To achieve this, we created the genetically-engineered [Fsp1-Flpo; (FSF)TGFbeta(CA)] mouse model. The Fsp1-Flpo allele consists in the Flpo recombinase under the control of the Fsp1 (fibroblast-specific promoter 1) promoter. The (FSF)TGFbeta(CA) allele consists in a transgene encoding a constitutively active mutant form of TGFbeta (TGFbeta(CA)) under the control of a Frt-STOP-Frt (FSF) cassette. The (FSF)TGFbeta(CA) allele was created to generate this model, and functionally validated by in vitro, ex vivo and in vivo techniques. [Fsp1-Flpo; (FSF)TGFbeta(CA)] animals do not present any obvious phenotype despite the correct expression of TGFbeta(CA) transgene in fibroblasts. This [Fsp1-Flpo; (FSF)TGFbeta(CA)] model is highly pertinent for future studies on the effect of increased microenvironmental bioactive TGFbeta concentrations in mice bearing Cre-dependent genetic alterations in other compartments (epithelial or immune compartments for instance). These dual recombinase system (DRS) approaches will enable scientists to study uncoupled spatiotemporal regulation of different genetic alterations within the same mouse, thus better replicating the complexity of human diseases. |
