Impact of an Immune Modulator Mycobacterium-w on Adaptive Natural Killer Cells and Protection Against COVID-19

  1. Sarita Rani Jaiswal
  2. Jaganath Arunachalam
  3. Ashraf Saifullah
  4. Rohit Lakhchaura
  5. Dhanir Tailor
  6. Anupama Mehta
  7. Gitali Bhagawati
  8. Hemamalini Aiyer
  9. Bakulesh Khamar
  10. Sanjay V. Malhotra
  11. Suparno Chakrabarti

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Abstract

The kinetics of NKG2C + adaptive natural killer (ANK) cells and NKG2A + inhibitory NK (iNK) cells with respect to the incidence of SARS-CoV-2 infection were studied for 6 months in a cohort of healthcare workers following the administration of the heat-killed Mycobacterium w (Mw group) in comparison to a control group. In both groups, corona virus disease 2019 (COVID-19) correlated with lower NKG2C + ANK cells at baseline. There was a significant upregulation of NKG2C expression and IFN-γ release in the Mw group (p=0.0009), particularly in those with a lower baseline NKG2C expression, along with the downregulation of iNK cells (p<0.0001). This translated to a significant reduction in the incidence and severity of COVID-19 in the Mw group (incidence risk ratio-0.15, p=0.0004). RNA-seq analysis at 6 months showed an upregulation of the ANK pathway genes and an enhanced ANK-mediated antibody-dependent cellular cytotoxicity (ADCC) signature. Thus, Mw was observed to have a salutary impact on the ANK cell profile and a long-term upregulation of ANK-ADCC pathways, which could have provided protection against COVID-19 in a non-immune high-risk population.

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  1. Version published to 10.3389/fimmu.2022.887230
  2. ScreenIT

    SciScore for 10.1101/2021.12.14.21267696: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: All subjects provided written informed consent for participating in the study.
    IRB: The study was approved by institutional ethics committee and registered with Clinical Trials Registry of India (CTRI/2020/10/028326).
    Sex as a biological variablenot detected.
    RandomizationSepsivac, Cadila Pharmaceuticals, India) intradermally in each arm on day 1 of the study (Mw group) and 50 randomly selected HCWs from the rest of the institution were enrolled in a Control group.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    For surface staining, 0.5 × 106 cells were washed with phosphate-buffered saline (PBS) and stained with the following antibodies which were used for phenotypic analysis: CD3(APC-H7, SK-7) CD16 (PE-Cy7, B73.1), CD56 (APC R700, NCAM16.2), CD57 (BV605, NK-1)
    CD16
    suggested: None
    CD56
    suggested: (Agilent Cat# TC67901, RRID:AB_579640)
    CD57
    suggested: (BioLegend Cat# 393304, RRID:AB_2728426)
    For intracellular staining, cells were stained for IFN-gamma using monoclonal antibodies for interferon-gamma (IFN-γ) (4S.B3) and perforin (Alexa647, DG9) (BD Biosciences) after fixation and permeabilization with appropriate buffer (BD Biosciences and e-biosciences, San Diego, CA, USA).
    IFN-γ
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    For surface staining, 0.5 × 106 cells were washed with phosphate-buffered saline (PBS) and stained with the following antibodies which were used for phenotypic analysis: CD3(APC-H7, SK-7) CD16 (PE-Cy7, B73.1), CD56 (APC R700, NCAM16.2), CD57 (BV605, NK-1)
    SK-7
    suggested: ATCC Cat# HB-8584, RRID:CVCL_L697)
    Software and Algorithms
    SentencesResources
    Flow Cytometry was performed using 10 colour flow cytometry (BD FACS Lyrics) and the flow cytometry data was analyzed using FlowJo software (v10.6.2, FlowJo).
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    GraphPad Prism (version 8.0 for Windows, GraphPad Software, La Jolla, CA, USA) was used for the statistical assessment (unpaired low-parametric Mann–Whitney or Kruskal–Wallis test and Spearman correlation).
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Recursive partitioning analysis was carried out using rpart package (https://cran.r-project.org/web/packages/rpart/index.html) in R (https://cran.r-project.org/) to generate optimal cut off for ANK cells at baseline.
    https://cran.r-project.org/
    suggested: (CRAN, RRID:SCR_003005)

    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: We detected the following sentences addressing limitations in the study:
    Thus, within the limitations of a small cohort, the findings are suggestive of a salutary effect of Mw on a favorable NKG2C+ANK profile and at the same time indicative of the fact that a favorable NKG2C+ANK profile might be protective against COVID-19. Another study had suggested that KLRC2 deletion might predispose to severe COVID-19(Vietzen et al., 2021). A third of the Mw cohort had KLRC2 deletion genotype and tended to have a slightly lower baseline NKG2C+ANK cells and tended to have a greater impact of Mw on the log2FC at day 60. It is possible that the adverse effect of KLRC2 genotype was mitigated by Mw. Unfortunately, KLRC2 genotype evaluation of the control group was not part of the study. Its evaluation could have shed some light on the predisposition of KLRC2 deletion genotype if any, independent of NKG2C expression, on COVID-19. The absence of any observation on the monocyte/macrophage pathway might be deemed as another limitation of the study, particularly when a NK-monocyte crosstalk might have been at play(Michel et al., 2012). Comparison of gene expression by RNAseq on NK and monocyte subsets pre- and post-Mw might help in better understanding of this phenomenon, which is a part of our ongoing project. The suggested mechanistic pathway as to how Mw might be favorably influencing ANK mediated protection against COVID-19 has been depicted in Figure 7. In conclusion, Mw did seem to offer protection against symptomatic COVID-19 in a high-risk population at the pea...

    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

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2021.12.14.21267696 on medRxiv