A sensitive red/far-red photoswitch for controllable gene therapy in mouse models of metabolic diseases
Red light optogenetic systems are in high demand for the precise control of gene expression for gene- and cell-based therapies. Here, we report a red /far-red l ight- i nducible p hotoswitch (REDLIP) system based on the chimeric photosensory protein FnBphP (Fn-REDLIP) or PnBphP (Pn-REDLIP) and their...
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Veröffentlicht in: | Nature communications 2024-11, Vol.15 (1), p.10310-18, Article 10310 |
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Zusammenfassung: | Red light optogenetic systems are in high demand for the precise control of gene expression for gene- and cell-based therapies. Here, we report a
red
/far-red
l
ight-
i
nducible
p
hotoswitch (REDLIP) system based on the chimeric photosensory protein FnBphP (Fn-REDLIP) or PnBphP (Pn-REDLIP) and their interaction partner LDB3, which enables efficient dynamic regulation of gene expression with a timescale of seconds without exogenous administration of a chromophore in mammals. We use the REDLIP system to establish the REDLIP-mediated CRISPR-dCas9 (REDLIP
cas
) system, enabling optogenetic activation of endogenous target genes in mammalian cells and mice. The REDLIP system is small enough to support packaging into adeno-associated viruses (AAVs), facilitating its therapeutic application. Demonstrating its capacity to treat metabolic diseases, we show that an AAV-delivered Fn-REDLIP system achieved optogenetic control of insulin expression to effectively lower blood glucose levels in type 1 diabetes model mice and control an anti-obesity therapeutic protein (thymic stromal lymphopoietin, TSLP) to reduce body weight in obesity model mice. REDLIP is a compact and sensitive optogenetic tool for reversible and non-invasive control that can facilitate basic biological and biomedical research.
Red light optogenetic systems are in high demand for therapeutic applications. Here, the authors introduce REDLIP, a red-light-inducible system that enables rapid gene regulation without external chromophores, effectively modulating insulin and anti-obesity protein expression in disease models. |
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ISSN: | 2041-1723 2041-1723 |
DOI: | 10.1038/s41467-024-54781-2 |