Proinflammatory innate cytokines and metabolomic signatures shape the T cell response in active COVID-19

  1. Akshay Binayke
  2. Aymaan Zaheer
  3. Jyotsna Dandotiya
  4. Sonu K Gupta
  5. Shailendra Mani
  6. Manas Tripathi
  7. Upasna Madan
  8. Tripti Shrivastava
  9. Yashwant Kumar
  10. Anil K Pandey
  11. Deepak K Rathore
  12. Amit Awasthi

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Abstract

The underlying factors contributing to the evolution of SARS-CoV-2-specific T cell responses during COVID-19 infection remain unidentified. To address this, we characterized innate and adaptive immune responses with metabolomic profiling longitudinally at three different time points (0-3, 7-9, and 14-16 days post-COVID-19 positivity) from young mildly symptomatic active COVID-19 patients infected during the first wave in mid-2020. We observed that anti-RBD IgG and viral neutralization are significantly reduced against the Delta variant compared to the ancestral strain. In contrast, compared to the ancestral strain, T cell responses remain preserved against the delta and omicron variants. We determined innate immune responses during the early stage of active infection in response to TLR 3/7/8 mediated activation in PBMCs and serum metabolomic profiling. Correlation analysis indicated PBMCs-derived proinflammatory cytokines, IL-18, IL-1β, and IL-23, and the abundance of plasma metabolites involved in arginine biosynthesis were predictive of a robust SARS-CoV-2-specific Th1 response at a later stage (two weeks after PCR positivity). These observations may contribute to designing effective vaccines and adjuvants that promote innate immune responses and metabolites to induce long-lasting anti-SARS-CoV-2 specific T cells response.

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  1. Version published to 10.1101/2022.03.11.483930v3 on bioRxiv
  2. Version published to 10.1101/2022.03.11.483930v2 on bioRxiv
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    SciScore for 10.1101/2022.03.11.483930: (What is this?)

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

    Table 1: Rigor

    EthicsIACUC: Human Ethics: All the experiments were performed according to the suggested guidelines of the Institutional Ethics Committee (Human Research) of THSTI and ESIC Hospital,
    Consent: Human blood samples were collected from COVID-19 patients and healthy individuals after obtaining written informed consent.
    Sex as a biological variableThe clinical cohort was considerably young and consisted of 8 females and 13 males with a median age of 28 years (IQR: 25:34) (Table S1).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Study Design: To investigate the factors that contribute to the priming of a robust anti-SARS-CoV-2 T cell response, we longitudinally studied antibody and T cell immune responses at early time points of acute infection in young mildly symptomatic acute COVID-19 patients by collecting blood samples from RT-PCR positive COVID-19 patients on day 0-4 (indicated as “Visit 1 or V1”), day 7 (indicated as “Visit 2 or V2”) and day 14 (indicated as “Visit 3 or V3”) from the date of RT-PCR positive infection report.
    anti-SARS-CoV-2
    suggested: None
    V2”
    suggested: None
    Software and Algorithms
    SentencesResources
    Samples were acquired on a fluorescence-activated cell sorter (FACS) Symphony™ instrument (BD Biosciences) using BD FACSuite software version 1.0.6 and analyzed with FlowJo software version VX
    BD FACSuite
    suggested: None
    Functional profiles were deconvoluted by employing Boolean gating in FlowJo version XV followed by downstream representation using SPICE version 6.1 (https://niaid.github.io/spice/).
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    SPICE
    suggested: (SPICE, RRID:SCR_016603)
    Data Representation and Statistical Analysis: The statistical analysis and data representation was performed using GraphPad Prism 9.0 and FlowJo XV unless otherwise stated.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    All the statistical and functional analysis, including the PCA, heat map, pathway enrichment analysis, PLS-DA, analysis of variance (ANOVA), was done based on the observed peaks intensity using the online open-source software Metaboanalyst 5.0.
    Metaboanalyst
    suggested: (MetaboAnalyst, RRID:SCR_015539)
    Those metabolites belonging to V1 and V3 that significantly correlated (p<0.05, r>0.5) with the proinflammatory adaptive immune responses and/or TH1 skewed T cell immune responses and has pathway library of KEGG were selected for Pathway Analysis using the Metaboanalyst 5.0 software (45).
    KEGG
    suggested: (KEGG, RRID:SCR_012773)

    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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  4. Version published to 10.1101/2022.03.11.483930v1 on bioRxiv