Proteomic deconvolution reveals distinct immune cell fractions in different body sites in SARS-Cov-2 positive individuals

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Abstract

Background

Severe acute respiratory syndrome coronavirus 2 ( SARS-CoV-2) continues to be a significant public health challenge globally. SARS-CoV-2 is a novel virus, and what constitutes immunological responses in different human body sites in infected individuals is yet to be presented. We set to determine the various immune cell fractions in gargle solution, bronchoalveolar lavage fluid, nasopharyngeal, and urine samples post-SARS-CoV-2 infection in humans.

Materials and methods

We downloaded proteomics data from ( https://www.ebi.ac.uk/pride/ ) with the following identifiers: PXD019423, n=3 (gargle solution), PXD018970, n=15 (urine), PXD022085, n=5 (Bronchoalveolar lavage fluid), PXD022889, n=18 (nasopharyngeal). MaxQuant was used for the peptide spectral matching using humans, and SARS-CoV-2 was downloaded from the UniProt database (Access date 9 th January 2022). The protein count matrix was extracted from the proteins group file and used as an input for the cibersort for the immune cells fraction determination.

Results

The body of individuals infected with the SARS-CoV-2 virus is characterized by different fractions of immune cells in Bronchoalveolar lavage fluid (BALF), nasopharyngeal, urine, and gargle solution. BALF has more abundant memory B cells, CD8, activated mast cells, and resting macrophages than urine, nasopharyngeal, and gargle solution. Our analysis also demonstrates that each body site comprises different immune cell fractions post-SARS-CoV-2 infection in humans.

Conclusion

Different body sites are characterized by different immune cells fractions in SARS-CoV-2 infected individuals. The findings in this study can inform public health policies and health professionals on treatment strategies and drive SARS-CoV-2 diagnosis procedures.

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  1. SciScore for 10.1101/2022.01.21.22269631: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    This study analyzed publicly available data downloaded from the Protein Identification Database, PRIDE (https://www.ebi.ac.uk/pride/) repository.
    PRIDE
    suggested: (Pride-asap, RRID:SCR_012052)
    https://www.ebi.ac.uk/pride/
    suggested: (Proteomics Identifications (PRIDE, RRID:SCR_003411)
    MaxQuant default parameter settings were used for the MS/MS database search, with carbamidomethylation of cysteine residues and acetylation of protein N-termini selected as fixed modification and oxidation of methionine as variable modification.
    MaxQuant
    suggested: (MaxQuant, RRID:SCR_014485)
    Reverse hits and common contaminants were removed using Bioconductor package ‘Differential Enrichment analysis of Proteomics data’ version 1.2.0 (19) before the downstream analysis.
    Bioconductor
    suggested: (Bioconductor, RRID:SCR_006442)

    Results from OddPub: Thank you for sharing your data.


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Study limitations include different sample preparation protocols, which can be a source of a possible confounder.

    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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