Targeted Down Regulation Of Core Mitochondrial Genes During SARS-CoV-2 Infection

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Abstract

Defects in mitochondrial oxidative phosphorylation (OXPHOS) have been reported in COVID-19 patients, but the timing and organs affected vary among reports. Here, we reveal the dynamics of COVID-19 through transcription profiles in nasopharyngeal and autopsy samples from patients and infected rodent models. While mitochondrial bioenergetics is repressed in the viral nasopharyngeal portal of entry, it is up regulated in autopsy lung tissues from deceased patients. In most disease stages and organs, discrete OXPHOS functions are blocked by the virus, and this is countered by the host broadly up regulating unblocked OXPHOS functions. No such rebound is seen in autopsy heart, results in severe repression of genes across all OXPHOS modules. Hence, targeted enhancement of mitochondrial gene expression may mitigate the pathogenesis of COVID-19.

One-Sentence Summary

Covid-19 is associated with targeted inhibition of mitochondrial gene transcription.

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  1. SciScore for 10.1101/2022.02.19.481089: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    EthicsField Sample Permit: Materials and Methods: EXPERIMENTAL MODEL AND SUBJECT DETAILS: Human nasopharyngeal swab sample collection for RNA-seq analysis: Patient specimens were processed as described in Butler et al.(1).
    Consent: All autopsies are performed with the consent of the next of kin and permission for retention and research use of tissue.
    IACUC: All animal experiment procedures, breeding and ethical use were performed in accordance with the guidelines set by the Institutional Animal Care and Use Committee.
    Sex as a biological variableVirus lines: SARS-CoV-2 Washington strain (isolate USA-WA1/2020, NR-52281) were provided by the Center for Disease Control and Prevention and obtained through BEI Resources, NIAID, NIH. Cell lines Vero E6 (African green monkey [Chlorocebus aethiops] kidney, CVCL_0574; female) were obtained from ATCC (https://www.atcc.org/).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line AuthenticationContamination: Cells were tested for the presence mycoplasma bi-weekly using MycoAlert Mycoplasma Detection Kit (lonza), They were not authenticated by an external service but were derived directly from ATCC.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    There also included 17 positive (Vero E6 cells) and 33 negative (buffer) controls.
    Vero E6
    suggested: RRID:CVCL_XD71)
    Changes in host protein levels are from published 24 hours post-infection CaCo-2 cells mass spectrometry-based proteomic data (28) (https://www.nature.com/articles/s41586-020-2332-7).
    CaCo-2
    suggested: None
    Experimental Models: Organisms/Strains
    SentencesResources
    Animals used in this study included female 16-week-old C57BL/6J (B6) (The Jackson Laboratory stock 000664) or 10-12-week-old BALB/cAnNHsd (BALB/c) (Envigo order code 047) mice, purchased directly from vendors.
    C57BL/6J
    suggested: None
    BALB/cAnNHsd
    suggested: None
    Analysis of COVID-19 murine tissue RNA-seq data: From the RNA-seq data the reads were aligned to the Mus musculus BALB/c or C57B/6 genome (v1.100) and the SARS-CoV-2 genome MA10 (MT952602) using the CLC Genomics Workbench v20.0 (https://digitalinsights.qiagen.com/) with the RNA-seq and Small RNA Analysis pipeline and the RNA-Seq Analysis module with all standard settings, the read counts then calculated.
    BALB/c
    suggested: None
    Software and Algorithms
    SentencesResources
    Virus lines: SARS-CoV-2 Washington strain (isolate USA-WA1/2020, NR-52281) were provided by the Center for Disease Control and Prevention and obtained through BEI Resources, NIAID, NIH. Cell lines Vero E6 (African green monkey [Chlorocebus aethiops] kidney, CVCL_0574; female) were obtained from ATCC (https://www.atcc.org/).
    https://www.atcc.org/
    suggested: (ATCC, RRID:SCR_001672)
    Libraries were pooled and sent to the WCM Genomics Core or HudsonAlpha for final quantification by Qubit fluorometer (ThermoFisher Scientific), TapeStation 2200 (Agilent), and qRT-PCR using the Kapa Biosystems Illumina library quantification kit.
    Agilent
    suggested: (Agilent Bravo NGS, RRID:SCR_019473)
    Final libraries were quantified using fluorescent-based assays including PicoGreen (Life Technologies) or Qubit Fluorometer (Invitrogen) and Fragment Analyzer (Advanced Analytics) and sequenced on a NovaSeq 6000 sequencer (v1 chemistry) with 2×150bp targeting 60M reads per sample.
    PicoGreen
    suggested: None
    Fastq files were generated using bcl2fastq (Illumina) and aligned to the Syrian golden hamster genome (MesAur 1.0, ensembl) using the RNA-seq Alignment application (Basespace, Illumina).
    bcl2fastq
    suggested: (bcl2fastq , RRID:SCR_015058)
    OrthoFinder was used to generate orthologous human ensembl gene ids and gene names (6).
    OrthoFinder
    suggested: (OrthoFinder, RRID:SCR_017118)
    After further filtering and quality control, R package edgeR (7) was used to calculate RPKM and Log2counts per million (CPM) matrices as well as perform differential expression analysis.
    edgeR
    suggested: (edgeR, RRID:SCR_012802)
    This workflow involved adapter trimming using Trim Galore!
    Trim Galore
    suggested: (Trim Galore, RRID:SCR_011847)
    (https://github.com/FelixKrueger/TrimGalore), read alignment with STAR (10), gene quantification with Salmon (11), duplicate read marking with Picard MarkDuplicates (https://github.com/broadinstitute/picard), and transcript quantification with StringTie (12).
    STAR
    suggested: (STAR, RRID:SCR_004463)
    Salmon
    suggested: (Salmon, RRID:SCR_017036)
    Picard
    suggested: (Picard, RRID:SCR_006525)
    StringTie
    suggested: (StringTie , RRID:SCR_016323)
    Other quality control measures included RSeQC, Qualimap, and dupRadar.
    RSeQC
    suggested: (RSeQC, RRID:SCR_005275)
    Qualimap
    suggested: (QualiMap, RRID:SCR_001209)
    FeatureCounts reads were normalized using variance-stabilizing transform (vst) in DESeq2 package in R for visualization purposes in log-scale (8).
    FeatureCounts
    suggested: (featureCounts, RRID:SCR_012919)
    Differential expression of genes was calculated by DESeq2.
    DESeq2
    suggested: (DESeq, RRID:SCR_000154)
    In addition, we manually activated the following essential pathways that are considered to be necessary for the model stability, since these essential pathways may not be properly activated based on RNA-seq data alone: ‘Oxidative Phosphorylation’, ‘Citric Acid Cycle’, ‘Glycolysis/Gluconeogenesis’, ‘CoA Biosynthesis’, ‘CoA Catabolism’, ‘NAD Metabolism’, ‘Fatty Acid Metabolism’, ‘Fatty acid activation’, ‘Fatty acid elongation’, ‘Fatty acid oxidation’, ‘ROS Detoxification’, and ‘Biomass and maintenance functions’.
    Biosynthesis’
    suggested: None
    Metabolism’
    suggested: None
    All modeling procedures were implemented within a Jupyter notebook 6.1.5 using Python 3.7.7 (18).
    Python
    suggested: (IPython, RRID:SCR_001658)
    Exploratory data analysis and differential expression analysis were performed using MetaOmGraph (22).
    MetaOmGraph
    suggested: None
    The murine RNA-seq data has been deposited in the NCBI BioProject database (https://www.ncbi.nlm.nih.gov/bioproject/) under the BioProject accession number PRJNA803057.
    NCBI BioProject
    suggested: (NCBI BioProject, RRID:SCR_004801)
    BioProject
    suggested: (NCBI BioProject, RRID:SCR_004801)
    We analyzed mitochondrial genes at both transcriptome and proteome levels and visualized the data using RStudio Desktop 1.3.1093 (32), ggplot2 version 3.3.2 and ggrepel version 0.8.2 ggrepel (33).
    RStudio
    suggested: (RStudio, RRID:SCR_000432)
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    ggrepel
    suggested: (ggrepel, RRID:SCR_017393)

    Results from OddPub: Thank you for sharing your data.


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    In the nasopharyngeal and heart, kidney, and liver samples, inhibition of OXPHOS and limitation of antioxidant defenses would result in increased mROS which stabilizes HIF-1α. This redirects metabolites away from the mitochondrion and toward glycolysis to generate lipid precursors. The imbalance in nDNA and mtDNA mitochondrial polypeptides also activates the UPRMT and UPRER, which activates the ISR resulting in bias of protein synthesis away from cellular maintenance and toward vial biogenesis. The human autopsy data confirms that, as viral titer declines, normal mitochondrial function resurges repairing tissue damage. However, if the virally-induced inhibition has been too severe, as in the case of the autopsy heart, kidney, and liver, then organ failure ensues resulting in death. While the early and late phases of COVID-19 modulation of bioenergetic gene transcription were established from the human nasopharyngeal and autopsy studies, the relationship between the initial viral protein inhibition of host mitochondrial proteins and the viral inhibition of bioenergetic gene transcription was not clear. To address this discrepancy, we analyzed the transcriptional effects of early hamster nasopharyngeal infection. This revealed that at peak lung viral titer, mitochondrial gene expression was not markedly impaired in the lung, heart, and kidney. Hence, the viral regulation of host mitochondrial transcription occurs after the initial viral protein inhibition of mitochondrial prote...

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.


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