RESUMO
Optogenetic genome engineering is a powerful technology for high-resolution spatiotemporal genetic manipulation, especially for in vivo studies. It is difficult to generate stable transgenic animals carrying a tightly regulated optogenetic system, as its long-term expression induces high background activity. Here, the generation of an enhanced photoactivatable Cre recombinase (ePA-Cre) transgenic mouse strain with stringent light responsiveness and high recombination efficiency is reported. Through serial optimization, ePA-Cre is developed to generate a transgenic mouse line that exhibits 175-fold induction upon illumination. Efficient light-dependent recombination is detected in embryos and various adult tissues of ePA-Cre mice crossed with the Ai14 tdTomato reporter. Importantly, no significant background Cre activity is detected in the tested tissues except the skin. Moreover, efficient light-inducible cell ablation is achieved in ePA-Cre mice crossed with Rosa26-LSL-DTA mice. In conclusion, ePA-Cre mice offer a tightly inducible, highly efficient, and spatiotemporal-specific genome engineering tool for multiple applications.
Assuntos
Camundongos Transgênicos , Camundongos , AnimaisRESUMO
As a potent insulinotrophic hormone, glucagon-like peptide 1 (GLP-1) is mainly secreted by intestinal L cells, which can effectively promote the release of insulin and thus reduce blood glucose. Therefore, GLP-1 and its analogs have a good prospect in the treatment of type 2 diabetes. In this study, we constructed mouse intestinal organoids that overexpress GLP-1 by optimizing the GLP-1 lentivirus infection method. We found that supernatants secreted by the GLP-1 overexpression organoids effectively enhanced glucose tolerance in wild-type and diabetic mouse. Thus, the GLP-1 overexpression organoids built in this study may provide a novel strategy for the treatment of type 2 diabetes.
Assuntos
Diabetes Mellitus Tipo 2 , Peptídeo 1 Semelhante ao Glucagon , Animais , Glicemia , Diabetes Mellitus Tipo 2/genética , Glucagon , Insulina , Camundongos , OrganoidesRESUMO
Spleen tyrosine kinase (SYK) is a critical immune signaling molecule and therapeutic target. We identified damaging monoallelic SYK variants in six patients with immune deficiency, multi-organ inflammatory disease such as colitis, arthritis and dermatitis, and diffuse large B cell lymphomas. The SYK variants increased phosphorylation and enhanced downstream signaling, indicating gain of function. A knock-in (SYK-Ser544Tyr) mouse model of a patient variant (p.Ser550Tyr) recapitulated aspects of the human disease that could be partially treated with a SYK inhibitor or transplantation of bone marrow from wild-type mice. Our studies demonstrate that SYK gain-of-function variants result in a potentially treatable form of inflammatory disease.
Assuntos
Artrite/genética , Colite/genética , Dermatite/genética , Linfoma Difuso de Grandes Células B/genética , Quinase Syk/genética , Adulto , Animais , Artrite/imunologia , Artrite/patologia , Artrite/terapia , Sequência de Bases , Transplante de Medula Óssea , Colite/imunologia , Colite/patologia , Colite/terapia , Dermatite/imunologia , Dermatite/patologia , Dermatite/terapia , Família , Feminino , Expressão Gênica , Técnicas de Introdução de Genes , Humanos , Lactente , Linfoma Difuso de Grandes Células B/imunologia , Linfoma Difuso de Grandes Células B/patologia , Linfoma Difuso de Grandes Células B/terapia , Masculino , Camundongos , Camundongos Knockout , Pessoa de Meia-Idade , Mutação , Linhagem , Inibidores de Proteínas Quinases/farmacologia , Quinase Syk/antagonistas & inibidores , Quinase Syk/deficiênciaRESUMO
The authors present a Recurrent Neural Network classifier model that segments the walking data recorded with instrumented footwear. The signals from 3 piezoresistive sensors, a 3-axis accelerometer, and Euler angles are used to generate temporal gait characteristics of a user. The model was tested using a data set collected from 28 adults containing 4198 steps. The mean errors for heel strikes and toe-offs were -5.9 ± 37.1 and 11.4 ± 47.4 milliseconds. These small errors show that the algorithm can be reliably used to segment the gait recordings and to use this segmentation to estimate temporal parameters of the subjects.
