Evidence map›Paper›PMID 38994966›Full record

ArticleCells2024

A Reliable System for Quantitative G-Protein Activation Imaging in Cancer Cells.

Elena Mandrou, Peter A Thomason, Peggy I Paschke, Nikki R Paul, Luke Tweedy, Robert H Insall

Abstract read
In one paragraph

Article in Cells, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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

6 authors.

Elena MandrouCRUK Scotland Institute, Garscube Campus, Glasgow G61 1BD, UK.ORCID 0000-0001-5258-9919
Peter A ThomasonCRUK Scotland Institute, Garscube Campus, Glasgow G61 1BD, UK.ORCID 0000-0003-3104-8392
Peggy I PaschkeCRUK Scotland Institute, Garscube Campus, Glasgow G61 1BD, UK.
Nikki R PaulCRUK Scotland Institute, Garscube Campus, Glasgow G61 1BD, UK.
Luke TweedySchool of Cancer Sciences, University of Glasgow, Glasgow G61 1QH, UK.
Robert H InsallCRUK Scotland Institute, Garscube Campus, Glasgow G61 1BD, UK.ORCID 0000-0003-4898-040X

Funding

MRC MR/X000702/1UKRI EP/T002123/1Wellcome Trust 221786/Z/20/Z
6 · The paper itself

Abstract

Fluorescence resonance energy transfer (FRET) biosensors have proven to be an indispensable tool in cell biology and, more specifically, in the study of G-protein signalling. The best method of measuring the activation status or FRET state of a biosensor is often fluorescence lifetime imaging microscopy (FLIM), as it does away with many disadvantages inherent to fluorescence intensity-based methods and is easily quantitated. Despite the significant potential, there is a lack of reliable FLIM-FRET biosensors, and the data processing and analysis workflows reported previously face reproducibility challenges. Here, we established a system in live primary mouse pancreatic ductal adenocarcinoma cells, where we can detect the activation of an mNeonGreen-Gαi3-mCherry-Gγ2 biosensor through the lysophosphatidic acid receptor (LPAR) with 2-photon time-correlated single-photon counting (TCSPC) FLIM. This combination gave a superior signal to the commonly used mTurquoise2-mVenus G-protein biosensor. This system has potential as a platform for drug screening, or to answer basic cell biology questions in the field of G-protein signalling.

Indexed as

Biosensing TechniquesFluorescence Resonance Energy TransferAnimalsCarcinoma, Pancreatic DuctalCell Line, TumorGTP-Binding ProteinsHumansMicePancreatic NeoplasmsReceptors, Lysophosphatidic AcidGTP-Binding ProteinsReceptors, Lysophosphatidic AcidFLIMfluorescence lifetimeFRETGPCRG-protein signallinglive cell imagingLPALPARPDAC

Identifiers

PMID38994966
PMCPMC11240385

What Socratic holds

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LicenceCC BY
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 Socratic graph.