Evidence map›Paper›PMID 40964392›Full record

ArticlebioRxiv : the preprint server for biology2025

A programmable genetic platform for engineering noninvasive biosensors.

Asish N Chacko, Kaamini M Dhanabalan, Jinyang Wan, Roy Chien, Nolan T Anderson, Binzhi Xu, Katie Pham, Ritu Tiwari, Arnab Mukherjee

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Asish N ChackoDepartment of Chemistry, University of California, Santa Barbara, CA 93106, USA.
Kaamini M DhanabalanDepartment of Chemical Engineering, University of California, Santa Barbara, CA 93106, USA.
Jinyang WanDepartment of Chemistry, University of California, Santa Barbara, CA 93106, USA.
Roy ChienDepartment of Chemistry, University of California, Santa Barbara, CA 93106, USA.
Nolan T AndersonDepartment of Ecology, Evolution, and Marine Biology, University of California, Santa Barbara, CA 93106, USA.
Binzhi XuInterdisciplinary Program in Quantitative Biosciences, University of California, Santa Barbara, CA 93106, USA.
Katie PhamDepartment of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, CA 93106, USA.
Ritu TiwariDepartment of Diagnostic and Biomedical Sciences, School of Dentistry, University of Texas Health Science Center at Houston, TX 77054, USA.
Arnab MukherjeeDepartment of Chemistry, University of California, Santa Barbara, CA 93106, USA.

Funding

Metal-free, genetically encoded reporters for calcium recording with MRIR01NS128278 · NINDS · UNIVERSITY OF CALIFORNIA SANTA BARBARA · PI Tod Edward Kippin, Arnab Mukherjee · 2023 to 2026
$1.9M
Engineering fluorescence and magnetic resonance reporter genes for imaging biological function in hypoxic cells and in vivoR35GM133530 · NIGMS · UNIVERSITY OF CALIFORNIA SANTA BARBARA · PI MUKHERJEE, ARNAB · 2019 to 2023
$1.6M
NIGMS NIH HHS R35 GM133530NINDS NIH HHS R01 NS128278
6 · The paper itself

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.

Indexed as

aquaporinsbiosensorsMRIprotease circuitsreporter genes

Identifiers

PMID40964392
PMCPMC12440030

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.