| Title | A programmable genetic platform for engineering noninvasive biosensors. |
| Publication Type | Journal Article |
| Year of Publication | 2025 |
| Authors | Chacko AN, Dhanabalan KM, Wan J, Chien R, Anderson NT, Xu B, Pham K, Tiwari R, Mukherjee A |
| Journal | bioRxiv |
| Date Published | 2025 Sep 11 |
| ISSN | 2692-8205 |
| Abstract | 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. |
| DOI | 10.1101/2025.09.07.674790 |
| Alternate Journal | bioRxiv |
| PubMed ID | 40964392 |
| PubMed Central ID | PMC12440030 |
| Grant List | R01 NS128278 / NS / NINDS NIH HHS / United States R35 GM133530 / GM / NIGMS NIH HHS / United States |
