Transcriptomic dysregulations associated with SARS-CoV-2 infection in human nasopharyngeal and peripheral blood mononuclear cells

  1. Caroline Vilas Boas de Melo
  2. Maruf Ahmed Bhuiyan
  3. Winfred Nyoroka Gatua
  4. Stephen Kanyerezi
  5. Leonard Uzairue
  6. Priscilla Abechi
  7. Karan Kumar
  8. Jabale Rahmat
  9. Abdulazeez Giwa
  10. Gracious Mwandira
  11. Abisogun Mujib Olamilekan
  12. Tiffany Ezinne George
  13. Oluwapelumi John Adejinmi
  14. Monsurat Ademidun Ibironke
  15. Olayemi David Rotimi
  16. Dina Aly Mahmoud Aly Abo-Elenein
  17. Ridwanullah Abiodun Abubakar
  18. Mahmood Usman
  19. Ifeoluwa Adewunmi
  20. Oyewumi Akinpelu
  21. Olajide Emmanuel
  22. Khatendra Reang
  23. Akadiri Olalekan
  24. Sarah H. Carl

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Abstract

Introduction

Over 24 million people have been infected globally with the novel coronavirus, SARS-CoV-2, with more than 820,000 succumbing to the resulting COVID-19 disease as of the end of August 2020. The molecular mechanisms underlying the pathogenesis of the disease are not completely elucidated. Thus, we aim to understand host response to SARS-CoV-2 infection by comparing samples collected from two distinct compartments (infection site and blood), obtained from COVID-19 subjects and healthy controls.

Methods

We used two publicly available gene expression datasets generated via RNA sequencing in two different samples; nasopharyngeal swabs and peripheral blood mononuclear cells (PBMCs). We performed a differential gene expression analysis between COVID-19 subjects and healthy controls in the two datasets and then functionally profiled their differentially expressed genes (DEGs). The genes involved in innate immunity were also determined.

Results

We found a clear difference in the host response to SARS-CoV-2 infection between the two sample groups. In COVID-19 subjects, the nasopharyngeal sample group indicated upregulation of genes involved in cytokine activity and interferon signalling pathway, as well as downregulation of genes involved in oxidative phosphorylation and viral transcription. Host response in COVID-19 subjects for the PBMC group, involved upregulation of genes involved in the complement system and immunoglobulin mediated immune response. CXCL13, GABRE, IFITM3 were upregulated and HSPA1B was downregulated in COVID-19 subjects in both sample groups.

Conclusion

Our results indicate the host response to SARS-CoV-2 is compartmentalized and suggests potential biomarkers of response to SARS-CoV-2 infection.

Highlights

  • Transcriptomic profiling from publicly available RNA-seq count data revealed a site-specific immune response in COVID-19.

  • Host response was found cellular-mediated in nasopharyngeal samples and humoral-mediated in PBMCs samples.

  • CXCL13, GABRE and IFITM3 commonly upregulated and HSPA1B downregulated in both sample groups highlights the potential of these molecules as markers of response to SARS-CoV-2 infection.

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    SciScore for 10.1101/2020.09.09.289850: (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
    Gene expression data (RNA-Seq counts) of GSE152418 and GSE152075 datasets were downloaded from the NCBI Gene Expression Omnibus (GEO) database.
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)
    Differentially expressed gene (DEGs) analysis: DEGs analysis was performed on the control and disease samples in each nasopharyngeal and PBMC group using the DESeq2 package in R (Love et al., 2014).
    DESeq2
    suggested: (DESeq, RRID:SCR_000154)
    The DEGs were also searched for their involvement in innate immunity using the InnateDB database (Breuer et al., 2013). 2.3.
    InnateDB
    suggested: (InnateDB, RRID:SCR_006714)
    Functional analysis was plotted using Prism (GraphPad software, Inc).
    Prism
    suggested: (PRISM, RRID:SCR_005375)
    GraphPad
    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.
    • No funding statement was detected.
    • No protocol registration statement was detected.

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  2. Version published to 10.1101/2020.09.09.289850 on bioRxiv