Evidence map›Paper›PMID 40332329›Full record

ArticleInternational journal of molecular sciences2025

NSP6 of SARS-CoV-2 Dually Regulates Autophagic-Lysosomal Degradation.

Haijiao Zhang, Jianying Chang, Ren Sheng

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Haijiao ZhangCollege of Life and Health Science, Northeastern University, Shenyang 110819, China.
Jianying ChangCollege of Life and Health Science, Northeastern University, Shenyang 110819, China.
Ren ShengCollege of Life and Health Science, Northeastern University, Shenyang 110819, China.ORCID 0000-0002-2293-8986

Funding

Fundamental Research Fund for the Central Universities, China N182005006Fundamental Research Fund for the Central Universities, China N2420001Liaoning Revitalization Talents Program XLYC1807239National Natural Science Foundation of China 31970721National Natural Science Foundation of China 81902830
6 · The paper itself

Abstract

The pandemic of coronavirus disease 2019 (COVID-19), brought about by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has significantly impacted public health and the economy. A fundamental aspect of addressing this virus lies in elucidating the mechanisms through which it induces disease. Our study reveals that Non-structural protein 6 (NSP6) of SARS-CoV-2 promotes the initiation of autophagy by activating Beclin1. In the later stage of autophagy, however, NSP6 causes a blockage in the autophagy-lysosome degradation via the inhibition of Mucolipin 1 (MLN1). The single nucleotide polymorphism (SNP) L37F in NSP6, which is associated with asymptomatic infection, similarly enhances the initiation of autophagy but displays a reduced ability to impede lysosome-dependent degradation. In summary, we demonstrated the dual-regulation mechanism of NSP6 in autophagy, which may be one of the reasons for targeting cellular autophagy to induce viral pathogenesis. This finding may provide promising new directions for future research and clinical interventions.

Indexed as

AutophagyCOVID-19LysosomesSARS-CoV-2Viral Nonstructural ProteinsAnimalsBeclin-1HumansPolymorphism, Single NucleotideTransient Receptor Potential ChannelsBeclin-1MCOLN1 protein, humanTransient Receptor Potential ChannelsViral Nonstructural Proteinsautophagy–lysosome degradationBeclin1COVID-19MLN1NSP6SARS-CoV-2

Identifiers

PMID40332329
PMCPMC12028300

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.