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Microbial biosensors are analytical devices that utilize living microbes to detect specific substances through measurable signals. These devices consist of two main components: biosensing organisms and signal-transducing elements. Biosensing organisms, such as Escherichia coli or Saccharomyces cerevisiae, are typically housed in multiwell plates connected to transducers, enabling rapid, real-time detection of target analytes.Signal Generation MechanismWhen a target analyte—such as...

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Preparation of Multifunctional Silk-Based Microcapsules Loaded with DNA Plasmids Encoding RNA Aptamers and Riboswitches
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A programmable genetic platform for engineering noninvasive biosensors.

Asish N Chacko1, Kaamini M Dhanabalan2, Jinyang Wan1

  • 1Department of Chemistry, University of California, Santa Barbara, CA 93106, USA.

Biorxiv : the Preprint Server for Biology
|September 18, 2025
PubMed
Summary
This summary is machine-generated.

Researchers developed universal reporter circuit-based activatable sensors (URCAS) for creating genetic MRI sensors. This platform enables noninvasive visualization of biological activities in deep tissues for research and diagnostics.

Keywords:
MRIaquaporinsbiosensorsprotease circuitsreporter genes

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Area of Science:

  • Biomedical Engineering
  • Molecular Imaging
  • Genetic Engineering

Background:

  • Noninvasive visualization of deep tissue biological activities is crucial for research and therapies.
  • Magnetic Resonance Imaging (MRI) offers high-resolution, radiation-free deep-tissue imaging but lacks adaptable genetic contrast methods.
  • Linking molecular events to genetically encoded MRI contrast is a significant challenge in biomolecular technology.

Purpose of the Study:

  • To introduce a programmable platform, universal reporter circuit-based activatable sensors (URCAS), for creating genetic sensors for MRI.
  • To engineer protease-activatable MRI reporters using protein stabilization and subcellular trafficking.
  • To demonstrate the versatility of URCAS for diverse biological targets without extensive customization.

Main Methods:

  • Developed the universal reporter circuit-based activatable sensors (URCAS) platform.
  • Engineered protease-activatable MRI reporters via protein stabilization and subcellular trafficking.
  • Tested URCAS applicability in five mammalian cell types and created sensors for various targets.

Main Results:

  • Successfully established URCAS applicability across five diverse mammalian cell types.
  • Demonstrated URCAS versatility by creating genetic sensors for viral proteins, drugs, logic gates, protein interactions, and calcium.
  • Showcased the ability to develop sensors without target-specific customization.

Conclusions:

  • URCAS provides a modular and programmable platform for developing genetic MRI sensors.
  • This platform streamlines the creation of noninvasive, nonionizing sensors for biomedical research.
  • URCAS holds potential for advancing in vivo diagnostics and cell-based therapies.