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| Main Authors: | , , , , , , , , |
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| Format: | Artículo científico |
| Language: | en |
| Published: |
bioRxiv : the preprint server for biology
2025
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| Online Access: | https://pubmed.ncbi.nlm.nih.gov/40964392/ |
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Table of Contents:
- A programmable genetic platform for engineering noninvasive biosensors. Chacko, Asish N Dhanabalan, Kaamini M Wan, Jinyang Chien, Roy Anderson, Nolan T Xu, Binzhi Pham, Katie Tiwari, Ritu Mukherjee, Arnab Creating genetic sensors for noninvasive visualization of biological activities in deep, optically opaque tissues holds immense potential for basic research and the development of genetic and cell-based therapies. MRI stands out among deep-tissue imaging methods for its ability to generate high-resolution images without ionizing radiation. However, the adoption of MRI as a mainstream biomolecular technology has been hindered by the lack of adaptable methods to link molecular events with genetically encodable MRI contrast. To address this challenge, we introduce universal reporter circuit-based activatable sensors (URCAS), a highly programmable platform for the systematic creation of genetic sensors for MRI. In developing URCAS, we engineered protease-activatable MRI reporters using two distinct approaches: protein stabilization and subcellular trafficking. We established the applicability of URCAS in five diverse mammalian cell types and showcased its versatility by assembling a toolkit of genetic sensors for viral proteins, small-molecule drugs, logic gates, protein-protein interactions, and calcium, without requiring new customization for each target. Our findings suggest that URCAS provides a modular, programmable platform for streamlining the development of noninvasive, nonionizing, and genetically encoded sensors for biomedical research and in vivo diagnostics.