Evidence map›Paper›PMID 32511341›Full record

ArticlebioRxiv : the preprint server for biology2020

Network Analysis and Transcriptome Profiling Identify Autophagic and Mitochondrial Dysfunctions in SARS-CoV-2 Infection.

Komudi Singh, Yun-Ching Chen, Jennifer T Judy, Fayaz Seifuddin, Ilker Tunc, Mehdi Pirooznia

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed, 31 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Komudi SinghBioinformatics and Computational Biology Laboratory, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Yun-Ching ChenBioinformatics and Computational Biology Laboratory, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Jennifer T JudyBioinformatics and Computational Biology Laboratory, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Fayaz SeifuddinBioinformatics and Computational Biology Laboratory, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Ilker TuncBioinformatics and Computational Biology Laboratory, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Mehdi PiroozniaBioinformatics and Computational Biology Laboratory, National Heart Lung and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA.
National Institutes of Health · US

Funding

Bioinformatics CoreZICHL006228 · NHLBI · NATIONAL HEART, LUNG, AND BLOOD INSTITUTE · PI PIROOZNIA, MEHDI · 2017 to 2021
$6.6M
Intramural NIH HHS ZIC HL006228
6 · The paper itself

Abstract

Analyzing host transcriptional changes in response to SARS-CoV-2 infection will help delineate biological processes underlying viral pathogenesis. Comparison of expression profiles of lung cell lines A549 (infected with either SARS-CoV-2 (with ACE2 expression)) or Influenza A virus (IAV)) and Calu3 (infected with SARS-CoV-2 or MERS-CoV) revealed upregulation of the antiviral interferon signaling in all three viral infections. However, perturbations in inflammatory, mitochondrial, and autophagy processes were specifically observed in SARS-CoV-2 infected cells. Validation of findings from cell line data revealed perturbations in autophagy and mitochondrial processes in the infected human nasopharyngeal samples. Specifically, downregulation of mTOR expression, mitochondrial ribosomal, mitochondrial complex I, and lysosome acidification genes were concurrently observed in both infected cell lines and human datasets. Furthermore, SARS-CoV-2 infection impedes autophagic flux by upregulating GSK3B in lung cell lines, or by downregulating autophagy genes, SNAP29 and lysosome acidification genes in human samples, contributing to increased viral replication. Therefore, drugs targeting lysosome acidification or autophagic flux could be tested as intervention strategies. Additionally, downregulation of MTFP1 (in cell lines) or SOCS6 (in human samples) results in hyperfused mitochondria and impede proper interferon response. Coexpression networks analysis identifies correlated clusters of genes annotated to inflammation and mitochondrial processes that are misregulated in SARS-CoV-2 infected cells. Finally, comparison of age stratified human gene expression data revealed impaired upregulation of chemokines, interferon stimulated and tripartite motif genes that are critical for antiviral signaling. Together, this analysis has revealed specific aspects of autophagic and mitochondrial function that are uniquely perturbed in SARS-CoV-2 infection.

Indexed as

co-expression network analysisCOVID-19inflammationSARS-CoV-2transcriptomics

Identifiers

PMID32511341
PMCPMC7241104
OpenAlexW3025794751

What OpenQuestion holds

Textmetadata
LicenceCC0
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.