Evidence map›Paper›PMID 36026492›Full record

ArticleAutophagy2023

Quantitative and temporal measurement of dynamic autophagy rates.

Nitin Sai Beesabathuni, Soyoon Park, Priya S Shah

Abstract read
In one paragraph

Article in Autophagy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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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

3 authors.

Nitin Sai BeesabathuniDepartment of Chemical Engineering, University of California, Davis, Davis, CA, USA.ORCID 0000-0002-5090-0176
Soyoon ParkDepartment of Microbiology and Molecular Genetics, University of California, Davis One Shields Ave, Davis, CA, USA.
Priya S ShahDepartment of Chemical Engineering, University of California, Davis, Davis, CA, USA.ORCID 0000-0001-7518-2839

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Macroautophagy/autophagy is a multistep degradative process that is essential for maintaining cellular homeostasis and is often dysregulated during disease. Systematically quantifying flux through this pathway is critical for gaining fundamental insights and effectively modulating this process. Established methods to quantify flux use steady-state measurements, which provide limited information about the perturbation and the cellular response. We present a theoretical and experimental framework to measure autophagic steps in the form of rates under non-steady-state conditions. We use this approach to measure temporal responses to rapamycin and wortmannin treatments, two commonly used autophagy modulators. We quantified changes in autophagy rates in as little as 10 min, which can establish direct mechanisms for autophagy perturbation before feedback begins. We identified concentration-dependent effects of rapamycin on the initial and temporal progression of autophagy rates. We also found variable recovery time from wortmannin's inhibition of autophagy, which is further accelerated by rapamycin. Furthermore, we applied this approach to study the effect of serum and glutamine starvation on autophagy. Serum starvation led to a rapid and transient increase in all the rates. Glutamine starvation led to a decrease in the rates on a longer timescale. In summary, this new approach enables the quantification of autophagy flux with high sensitivity and temporal resolution and facilitates a comprehensive understanding of this process.

Indexed as

AutophagyGlutamineHumansLysosomesSirolimusWortmanninGlutamineSirolimusWortmanninAutophagy fluxlive cell fluorescence microscopyrapamycinstarvationtemporal dynamicswortmannin

Identifiers

PMID36026492
PMCPMC10012960

What OpenQuestion holds

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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.