Protein Arginylation Is Regulated during SARS-CoV-2 Infection

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Abstract

Background: In 2019, the world witnessed the onset of an unprecedented pandemic. By February 2022, the infection by SARS-CoV-2 has already been responsible for the death of more than 5 million people worldwide. Recently, we and other groups discovered that SARS-CoV-2 infection induces ER stress and activation of the unfolded protein response (UPR) pathway. Degradation of misfolded/unfolded proteins is an essential element of proteostasis and occurs mainly in lysosomes or proteasomes. The N-terminal arginylation of proteins is characterized as an inducer of ubiquitination and proteasomal degradation by the N-degron pathway. Results: The role of protein arginylation during SARS-CoV-2 infection was elucidated. Protein arginylation was studied in Vero CCL-81, macrophage-like THP1, and Calu-3 cells infected at different times. A reanalysis of in vivo and in vitro public omics data combined with immunoblotting was performed to measure levels of arginyl-tRNA-protein transferase (ATE1) and its substrates. Dysregulation of the N-degron pathway was specifically identified during coronavirus infections compared to other respiratory viruses. We demonstrated that during SARS-CoV-2 infection, there is an increase in ATE1 expression in Calu-3 and Vero CCL-81 cells. On the other hand, infected macrophages showed no enzyme regulation. ATE1 and protein arginylation was variant-dependent, as shown using P1 and P2 viral variants and HEK 293T cells transfection with the spike protein and receptor-binding domains (RBD). In addition, we report that ATE1 inhibitors, tannic acid and merbromine (MER) reduce viral load. This finding was confirmed in ATE1-silenced cells. Conclusions: We demonstrate that ATE1 is increased during SARS-CoV-2 infection and its inhibition has potential therapeutic value.

Article activity feed

  1. Aaron Smith

    Review 2: "Protein arginylation is regulated during SARS-CoV-2 infection"

    This preprint looks at how SARS-CoV-2 infection modulates arginylation, a modification that tags proteins for degradation, and finds a specific arginylation signature in some cell types. The reviewers found the claims potentially informative.

  2. Fangliang Zhang

    Review 1: "Protein arginylation is regulated during SARS-CoV-2 infection"

    This preprint looks at how SARS-CoV-2 infection modulates arginylation, a modification that tags proteins for degradation, and finds a specific arginylation signature in some cell types. The reviewers found the claims potentially informative.

  3. Strength of evidence

    Reviewers: Fangliang Zhang (University of Miami) | 📒📒📒◻️◻️ 
     Aaron Smith (University of Maryland) | 📒📒📒◻️◻️
    Hyunjoo Cha-Molstad (Korea Research Institute of Bioscience and Biotechnology)  |📙📙 ◻️◻️◻️

  4. SciScore for 10.1101/2021.11.02.466971: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    Data sources and curation: Previously published studies were used to verify the abundance of proteins that make up the N-end rule pathway in non-infected and SARS-CoV-2 infected groups: (i) Saccon et al42 (Calu-3, Caco-2, Huh7, and 293FT cell lines, proteomics); (ii) Nie et al43 (autopsy 7 organs, 19 patients, proteomics); (iii) Leng et al44 (lung tissue, 2 patients, proteomics); (iv) Qiu et al45 (lung tissue, 3 patients, proteomics); (v) Bojkova et
    Huh7
    suggested: None
    293FT
    suggested: ATCC Cat# PTA-5077, RRID:CVCL_6911)
    To verify modulation of the N-end rule pathway in other viral infections, including MERS-CoV/SARS-CoV/H1N1 influenza virus/Respiratory syncytial virus (RSV), data from the following studies were evaluated: (viii) Zhuravlev et al49 (MRC-5, A549, HEK293FT, and WI-38 VA-13 cell lines, H1N1 influenza virus, transcriptomics), (ix) Li et al50 (A549 and 293T cell lines, H1N1 influenza virus, transcriptomics), (x) Krishnamoorthy et al51 (comparative among coronaviruses, transcriptomics), (xi) Ampuero et al52 (time course of RSV infection in the lung, transcriptomics), (xii) Besteman et al53 (RSV infected neutrophils, transcriptomics), and (xiii) Dave et al54 (RSV infected alveolar cell, proteomics).
    MRC-5
    suggested: None
    HEK293FT
    suggested: RRID:CVCL_6911)
    VA-13
    suggested: RRID:CVCL_A5CQ)
    A549
    suggested: None
    293T
    suggested: None
    Kidney epithelial cell, African green monkey), Calu-3 (lung adenocarcinoma), Caco-2 (colorectal adenocarcinoma), and ACE2-A549 (lung carcinoma expressing ACE2 to gain cellular entry).
    Caco-2
    suggested: None
    ACE2-A549
    suggested: None
    Cell culture: Vero CCL-81 cells were cultured in DMEM medium supplemented with 10% fetal bovine serum (FBS), 100 U/ml penicillin-streptomycin, 4.5 g/L glucose, 2 mM L-glutamine, 1 mM sodium pyruvate, and 1.5 g/L NaHCO3
    Vero CCL-81
    suggested: None
    Calu-3 cells were cultured in DMEM medium supplemented with 20% FBS, 1% non-essential amino acids, 4.5 g/L glucose, 2 mM L - glutamine, 1 mM sodium pyruvate, 100 U/ml penicillin-streptomycin and 1.5 g/L NaHCO3.
    Calu-3
    suggested: None
    THP-1 cells were cultured in RPMI-1640 supplemented with 10% FBS, and 1% penicillin-streptomycin at 37 °C.
    THP-1
    suggested: None
    For comprehensive time course evaluation, Vero CCL-81 and Calu-3 cells were infected with SARS-CoV-2.
    Vero
    suggested: None
    Software and Algorithms
    SentencesResources
    Bioinformatics analysis: The tidyverse59, biostrings, and seqinr60 packages were used to map potentially arginylated proteins in the Homo sapiens and Chlorocebus sabaeus proteomes (downloaded in May 2021, https://www.uniprot.org/).
    https://www.uniprot.org/
    suggested: (Universal Protein Resource, RRID:SCR_002380)
    The String database v.
    String
    suggested: (STRING, RRID:SCR_005223)
    Single-cell RNA-seq re-analysis: Expression matrices were loaded into RStudio (v. 4.0.3) with the Seurat package66.
    Seurat
    suggested: (SEURAT, RRID:SCR_007322)
    The Metaboanalyst platform67 was used to evaluate differently regulated genes between cell clusters identified in the single-cell RNA-seq analysis. 4.
    Metaboanalyst
    suggested: (MetaboAnalyst, RRID:SCR_015539)
    (GraphPad Software, San Diego, USA).
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Immunoreactive bands were detected with the ChemiDoc XRS Imaging System equipment and protein quantification was performed using the ImageJ software.
    ImageJ
    suggested: (ImageJ, RRID:SCR_003070)
    Graphs were plotted using GraphPad Prism version 8.1 software.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.


    About SciScore

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