Evidence mapPaperPMID 39677763Full record

ArticlebioRxiv : the preprint server for biology2024

Two Novel Red-FRET ERK Biosensors in the 670-720nm Range.

Nicholaus L DeCuzzi, Jason Y Hu, Florene Xu, Brayant Rodriguez, Michael Pargett, John G Albeck

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In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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

6 authors.

Nicholaus L DeCuzziDepartment of Molecular and Cellular Biology, University of California, Davis.ORCID 0000-0002-2275-4933
Jason Y HuDepartment of Molecular and Cellular Biology, University of California, Davis.
Florene XuDepartment of Molecular and Cellular Biology, University of California, Davis.
Brayant RodriguezDepartment of Molecular and Cellular Biology, University of California, Davis.
Michael PargettDepartment of Molecular and Cellular Biology, University of California, Davis.ORCID 0000-0002-1403-7408
John G AlbeckDepartment of Molecular and Cellular Biology, University of California, Davis.ORCID 0000-0003-2688-8653

Funding

TRAINING IN COMPARATIVE LUNG BIOLOGY AND MEDICINET32HL007013 · UNIVERSITY OF CALIFORNIA DAVIS · 1985 to 2025
$1.6M
Control of gene expression by dynamic metabolic oscillationsR35GM139621 · UNIVERSITY OF CALIFORNIA AT DAVIS · 2025 to 2025
$374k
NHLBI NIH HHS R01 HL151983NHLBI NIH HHS T32 HL007013NIGMS NIH HHS R35 GM139621
6 · The paper itself

Abstract

Cell fate decisions are regulated by intricate signaling networks, with Extracellular signal-Regulated Kinase (ERK) being a central regulator. However, ERK is rarely the only signaling pathway involved, creating a need to study multiple signaling pathways simultaneously at the single-cell level. Many existing fluorescent biosensors for ERK and other pathways have significant spectral overlap, limiting their ability to be multiplexed. To address this limitation, we developed two novel red-FRET ERK biosensors, REKAR67 and REKAR76, which operate in the 670-720 nm range using miRFP670nano3 and miRFP720. REKAR67 and REKAR76 differ in fluorophore position, which impacts biosensor characteristics; REKAR67 displayed a higher dynamic range but greater signal variance than REKAR76. Mixed populations of REKAR67 or REKAR76 displayed similar Signal-to-Noise ratio (SNR), but in clonal cell populations, REKAR76 had a significantly higher SNR. Overall, our red-FRET ERK biosensors were highly consistent with existing ERK FRET biosensors and in reporting ERK activity and are spectrally compatible with CFP/YFP FRET and cpGFP -based biosensors. Both REKAR biosensors expand the available methods for measuring single-cell ERK activity.

Identifiers

PMID39677763
PMCPMC11642818

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.