Evidence map›Paper›PMID 42729385›Full record

ArticleBio-protocol2026

Engineering MRI-Based Programmable Genetic Sensors Using the MAPPER Platform.

Asish N Chacko, Yuxin He, Raymond E Borg, Thomas Tang, Arnab Mukherjee

Abstract read
In one paragraph

Article in Bio-protocol, 2026. 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

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Asish N ChackoDepartment of Chemistry and Biochemistry, University of California, Santa Barbara, CA, USA.
Yuxin HeDepartment of Chemistry and Biochemistry, University of California, Santa Barbara, CA, USA.
Raymond E BorgDepartment of Chemistry, University of Hawaii Maui College, Kahului, HI, USA.
Thomas TangDepartment of Chemistry and Biochemistry, University of California, Santa Barbara, CA, USA.
Arnab MukherjeeDepartment of Chemistry and Biochemistry, University of California, Santa Barbara, CA, 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

Genetically encodable reporters that produce signals detectable in deep tissues offer a powerful tool for noninvasive monitoring of molecular events in vivo. Although magnetic resonance imaging (MRI) is a standard technique for noninvasive clinical imaging, its wider application in detecting molecular activities has been constrained by the lack of programmable sensors. This limitation is in stark contrast to the widespread use of fluorescent reporter-derived sensors in cultured cells and in transparent specimens. To overcome this limitation, we recently developed the modular aquaporin-based protease-activatable probe for enhanced reporting (MAPPER) platform. This sensor engineering framework integrates a metal-free MRI reporter derived from human aquaporin-1 (hAqp1) with synthetic protease-based circuits. This integration facilitates the modular and scalable creation of a wide range of sensors by regulating protease activity through precise molecular events, such as protein-protein interactions, pharmacological inhibition, and second messenger signaling. In this paper, we present a detailed protocol for constructing and deploying sensors using the MAPPER paradigm. The protocol encompasses genetic design, lentiviral production, stable cell line generation, biochemical and microscopic validation of sensor function, diffusion-weighted MRI, and MR image analysis to quantify sensor signals in terms of the apparent diffusion coefficient. We describe two distinct MAPPER architectures: DD-MAPPER, which leverages protease-controlled protein degradation, and ER-MAPPER, which utilizes protease-controlled, subcellular trafficking. The MAPPER framework allows adaptation to various molecular targets without the need to redesign the core MRI reporter mechanism, making MAPPER a versatile platform for noninvasive biosensing in living cells and tissues. Key features • MAPPER enables programmable, protease-controlled switching of aquaporin-1-based diffusion weighted-MRI signals in genetically modified mammalian cells. • The protocol covers two complementary biosensor architectures (DD-MAPPER and ER-MAPPER) that exploit different post-translational regulatory mechanisms to modulate MRI signals. • Stable MAPPER cell lines are generated via lentiviral transduction, allowing long-term, selection-free biosensor expression across multiple mammalian cell types. • The sensor is fully modular; proteases and protease-based logic circuits can be substituted without altering the hAqp1 reporter, enabling rapid adaptation to new molecular targets.

Indexed as

AquaporinsDiffusion-weighted MRIMRINoninvasive biosensorsProtease circuitsReporter genes

Identifiers

PMID42729385
PMCPMC13561953

What OpenQuestion holds

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Registered trials

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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.