Evidence map›Paper›PMID 21966401›Full record

ArticlePloS one2011

Determining signalling nodes for apoptosis by a genetic high-throughput screen.

Bevan Lin, Derek Huntley, Ghada Abuali, Sarah R Langley, George Sindelar, Enrico Petretto, Sarah Butcher, Stefan Grimm

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.4field-weighted citation impact, top 37% of its field
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

5 citing papers in PubMed, 8 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Bevan LinDivision of Experimental Medicine, Imperial College London, London, United Kingdom.
Derek Huntley
Ghada Abuali
Sarah R Langley
George Sindelar
Enrico Petretto
Sarah Butcher
Stefan Grimm
Imperial College London · GBMedical Research Council · GB

Funding

Department of HealthMedical Research Council MC_U120097112Wellcome TrustWellcome Trust P14515
6 · The paper itself

Abstract

backgroundWith the ever-increasing information emerging from the various sequencing and gene annotation projects, there is an urgent need to elucidate the cellular functions of the newly discovered genes. The genetically regulated cell suicide of apoptosis is especially suitable for such endeavours as it is governed by a vast number of factors. METHODOLOGY/PRINCIPAL

findingsWe have set up a high-throughput screen in 96-well microtiter plates for genes that induce apoptosis upon their individual transfection into human cells. Upon screening approximately 100,000 cDNA clones we determined 74 genes that initiate this cellular suicide programme. A thorough bioinformatics analysis of these genes revealed that 91% are novel apoptosis regulators. Careful sequence analysis and functional annotation showed that the apoptosis factors exhibit a distinct functional distribution that distinguishes the cell death process from other signalling pathways. While only a minority of classic signal transducers were determined, a substantial number of the genes fall into the transporter- and enzyme-category. The apoptosis factors are distributed throughout all cellular organelles and many signalling circuits, but one distinct signalling pathway connects at least some of the isolated genes. Comparisons with microarray data suggest that several genes are dysregulated in specific types of cancers and degenerative diseases. CONCLUSIONS/SIGNIFICANCE: Many unknown genes for cell death were revealed through our screen, supporting the enormous complexity of cell death regulation. Our results will serve as a repository for other researchers working with genomics data related to apoptosis or for those seeking to reveal novel signalling pathways for cell suicide.

Indexed as

ApoptosisGene Expression Regulation, NeoplasticSignal TransductionAnimalsComputational BiologyDNA, ComplementaryEnzyme-Linked Immunosorbent AssayGene Expression ProfilingGenomicsGreen Fluorescent ProteinsHEK293 CellsHumansMiceModels, GeneticOligonucleotide Array Sequence AnalysisRoboticsDNA, ComplementaryGreen Fluorescent Proteins

Identifiers

PMID21966401
PMCPMC3178610
OpenAlexW2088027382

What OpenQuestion holds

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LicenceCC BY
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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.