Evidence map›Paper›PMID 32699244›Full record

ArticleScientific reports2020

An improved method for high-throughput quantification of autophagy in mammalian cells.

Lennart Koepke, Benjamin Winter, Alexander Grenzner, Kerstin Regensburger, Susanne Engelhart, Johannes A van der Merwe, Stefan Krebs, Helmut Blum, Frank Kirchhoff, Konstantin M J Sparrer

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
3.3field-weighted citation impact, top 7% 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

26 citing papers in PubMed, 39 citations in OpenAlex.

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  14. [Establishment of a reporter system for estimating activation of human hepatic stellate cells based onBeijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · 2023
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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

10 authors at 2 institutions in 1 country.

Lennart Koepke *Institute of Molecular Virology, Ulm University Medical Center, 89081, Ulm, Germany.
Benjamin Winter *Institute of Molecular Virology, Ulm University Medical Center, 89081, Ulm, Germany.
Alexander GrenznerInstitute of Molecular Virology, Ulm University Medical Center, 89081, Ulm, Germany.
Kerstin RegensburgerInstitute of Molecular Virology, Ulm University Medical Center, 89081, Ulm, Germany.
Susanne EngelhartInstitute of Molecular Virology, Ulm University Medical Center, 89081, Ulm, Germany.
Johannes A van der MerweInstitute of Molecular Virology, Ulm University Medical Center, 89081, Ulm, Germany.
Stefan KrebsGene Center and Laboratory for Functional Genome Analysis, Ludwig-Maximilians-University, 81377, Munich, Germany.
Helmut BlumGene Center and Laboratory for Functional Genome Analysis, Ludwig-Maximilians-University, 81377, Munich, Germany.
Frank KirchhoffInstitute of Molecular Virology, Ulm University Medical Center, 89081, Ulm, Germany.
Konstantin M J SparrerInstitute of Molecular Virology, Ulm University Medical Center, 89081, Ulm, Germany. Konstantin.Sparrer@uni-ulm.de.
Universität Ulm · DELudwig-Maximilians-Universität München · DE

Funding

Marie Curie 794803
6 · The paper itself

Abstract

Autophagy is a cellular homeostatic pathway with functions ranging from cytoplasmic protein turnover to immune defense. Therapeutic modulation of autophagy has been demonstrated to positively impact the outcome of autophagy-dysregulated diseases such as cancer or microbial infections. However, currently available agents lack specificity, and new candidates for drug development or potential cellular targets need to be identified. Here, we present an improved method to robustly detect changes in autophagy in a high-throughput manner on a single cell level, allowing effective screening. This method quantifies eGFP-LC3B positive vesicles to accurately monitor autophagy. We have significantly streamlined the protocol and optimized it for rapid quantification of large numbers of cells in little time, while retaining accuracy and sensitivity. Z scores up to 0.91 without a loss of sensitivity demonstrate the robustness and aptness of this approach. Three exemplary applications outline the value of our protocols and cell lines: (I) Examining autophagy modulating compounds on four different cell types. (II) Monitoring of autophagy upon infection with e.g. measles or influenza A virus. (III) CRISPR/Cas9 screening for autophagy modulating factors in T cells. In summary, we offer ready-to-use protocols to generate sensitive autophagy reporter cells and quantify autophagy in high-throughput assays.

Indexed as

AnimalsAutophagyCell LineCell Line, TumorCRISPR-Cas SystemsHEK293 CellsHeLa CellsHigh-Throughput Screening AssaysHumansInfectionsJurkat CellsMammalsTHP-1 CellsT-Lymphocytes

Identifiers

PMID32699244
PMCPMC7376206
OpenAlexW3045310140

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.