A programmable genetic platform for engineering noninvasive biosensors.

Fuente: PubMed
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Autori principali: Chacko, Asish N, Dhanabalan, Kaamini M, Wan, Jinyang, Chien, Roy, Anderson, Nolan T, Xu, Binzhi, Pham, Katie, Tiwari, Ritu, Mukherjee, Arnab
Natura: Artículo científico
Lingua:en
Pubblicazione: bioRxiv : the preprint server for biology 2025
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author Chacko, Asish N
Dhanabalan, Kaamini M
Wan, Jinyang
Chien, Roy
Anderson, Nolan T
Xu, Binzhi
Pham, Katie
Tiwari, Ritu
Mukherjee, Arnab
author_facet Chacko, Asish N
Dhanabalan, Kaamini M
Wan, Jinyang
Chien, Roy
Anderson, Nolan T
Xu, Binzhi
Pham, Katie
Tiwari, Ritu
Mukherjee, Arnab
Chacko, Asish N
Dhanabalan, Kaamini M
Wan, Jinyang
Chien, Roy
Anderson, Nolan T
Xu, Binzhi
Pham, Katie
Tiwari, Ritu
Mukherjee, Arnab
collection PubMed - marine biology
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.
format Artículo científico
id pubmed_40964392
institution PubMed
language en
publishDate 2025
publisher bioRxiv : the preprint server for biology
record_format pubmed
spellingShingle 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
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.
title A programmable genetic platform for engineering noninvasive biosensors.
url https://pubmed.ncbi.nlm.nih.gov/40964392/