Evidence map›Paper›PMID 33796130›Full record

ArticleFrontiers in genetics2021

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

Komudi Singh, Yun-Ching Chen, Shahin Hassanzadeh, Kim Han, Jennifer T Judy, Fayaz Seifuddin, Ilker Tunc, Michael N Sack, Mehdi Pirooznia

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed, 1 pooled it
11.6field-weighted citation impact, top 1% 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

70 citing papers in PubMed, 1 synthesis or guideline pooled it, 90 citations in OpenAlex.

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  10. Interactions of SARS-CoV-2 with Human Target Cells-A Metabolic View.International journal of molecular sciences · 2024
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10 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 1 country.

Komudi SinghBioinformatics and Computational Biology Laboratory, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States.
Yun-Ching ChenBioinformatics and Computational Biology Laboratory, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States.
Shahin HassanzadehLaboratory of Mitochondrial Biology and Metabolism, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States.
Kim HanLaboratory of Mitochondrial Biology and Metabolism, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States.
Jennifer T JudyBioinformatics and Computational Biology Laboratory, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States.
Fayaz SeifuddinBioinformatics and Computational Biology Laboratory, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States.
Ilker TuncBioinformatics and Computational Biology Laboratory, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States.
Michael N SackLaboratory of Mitochondrial Biology and Metabolism, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States.
Mehdi PiroozniaBioinformatics and Computational Biology Laboratory, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, United States.
National Heart Lung and Blood Institute · USNational 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 cells' transcriptional response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection will help delineate biological processes underlying viral pathogenesis. First, analysis of expression profiles of lung cell lines A549 and Calu3 revealed upregulation of antiviral interferon signaling genes in response to all three SARS-CoV-2, MERS-CoV, or influenza A virus (IAV) infections. However, perturbations in expression of genes involved in inflammatory, mitochondrial, and autophagy processes were specifically observed in SARS-CoV-2-infected cells. Next, a validation study in infected human nasopharyngeal samples also revealed perturbations in autophagy and mitochondrial processes. Specifically, mTOR expression, mitochondrial ribosomal, mitochondrial complex I, lysosome acidification, and mitochondrial fission promoting genes were concurrently downregulated in both infected cell lines and human samples. SARS-CoV-2 infection impeded autophagic flux either 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. Finally, age-stratified SARS-CoV-2-positive human data revealed impaired upregulation of chemokines, interferon-stimulated genes, 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-infected host cells.

Indexed as

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

Identifiers

PMID33796130
PMCPMC8008150
OpenAlexW3136829303

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.