SARS-CoV-2 infection results in immune responses in the respiratory tract and peripheral blood that suggest mechanisms of disease severity

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1. Version published to 10.1038/s41467-022-30088-y

   May 19, 2022
2. 

   ScreenIT

   Sep 9, 2021

   SciScore for 10.1101/2021.09.01.21262715: (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

   Antibodies
   Sentences	Resources
   Phenotypic whole blood immune analyses: Fresh whole blood (200μl per stain) was used to measure CD4+CXCR5+ICOS+PD1+ follicular T cells (Tfh) and CD3-CD19+CD27hiCD38hi antibody-secreting B cell (ASC; plasmablast) populations as described15, 49 as well as activated HLA-DR+CD38+CD8+ and HLA-DR+CD38+CD4+ T cells, intermediate CD14+CD16+ and classical CD14+ monocytes, activated CD3-CD56+ NK cells, MAIT cells, [δ-T cells, as per the specific antibody panels (Supplementary Table 6; gating strategy is presented in Supplementary Fig.	CD3-CD19+CD27hiCD38hi antibody-secreting B suggested: None antibody-secreting su…

   SciScore for 10.1101/2021.09.01.21262715: (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

   Antibodies
   Sentences	Resources
   Phenotypic whole blood immune analyses: Fresh whole blood (200μl per stain) was used to measure CD4+CXCR5+ICOS+PD1+ follicular T cells (Tfh) and CD3-CD19+CD27hiCD38hi antibody-secreting B cell (ASC; plasmablast) populations as described15, 49 as well as activated HLA-DR+CD38+CD8+ and HLA-DR+CD38+CD4+ T cells, intermediate CD14+CD16+ and classical CD14+ monocytes, activated CD3-CD56+ NK cells, MAIT cells, [δ-T cells, as per the specific antibody panels (Supplementary Table 6; gating strategy is presented in Supplementary Fig.	CD3-CD19+CD27hiCD38hi antibody-secreting B suggested: None antibody-secreting suggested: (Félix A. Rey; Pasteur Institute Cat# C10, RRID:AB_2725800)
   SARS-CoV-2 RBD ELISA: RBD-specific ELISA for detection of IgM, IgG and IgA antibodies was performed as previously described31, 50, 51, using flat bottom Nunc MaxiSorp 96-well plates (Thermo Fisher Scientific) for antigen coating (2µg/ml), blocking with PBS (with w/v 1% BSA) and serial dilutions in PBS (with v/v 0.05% Tween and w/v 0.5% BSA).	IgM , IgG suggested: None IgA suggested: None antigen coating ( 2µg/ml) suggested: None
   The sVNT blocking ELISA assay (manufactured by GenScript, NJ, USA) was carried out essentially as described51, which detects circulating neutralizing SARS-CoV-2 antibodies that block the interaction between RBD and ACE2 on the cell surface receptor of the host.	ACE2 suggested: None
   Colour intensity was inversely dependent on the titre of anti-SARS-CoV-2 neutralizing antibodies.	anti-SARS-CoV-2 neutralizing antibodies . suggested: None
   Experimental Models: Cell Lines
   Sentences	Resources
   SARS-CoV-2 isolate CoV/Australia/VIC01/202053 was propagated in Vero cells and stored at -80°C.	Vero suggested: None
   Cytokine analysis: Patients’ plasma and respiratory samples were measured for IL-1β, IFN-α2, IFN-γ, TNF, MCP-1 (CCL2), IL-6, IL-8 (CXCL8), IL-10, IL-12p70, IL-17A, IL-18, IL-23 and IL-33 using the LEGENDplex™ Human Inflammation Panel 1 kit, as per manufacturer’s instructions (BioLegend, San Diego, CA, USA).	MCP-1 suggested: None
   Software and Algorithms
   Sentences	Resources
   Flow cytometry data were analyzed using FlowJo v10 software.	FlowJo suggested: (FlowJo, RRID:SCR_008520)
   Endpoint titres were determined by interpolation from a sigmodial curve fit (all R-squared values >0.95; GraphPad Prism 9) as the reciprocal dilution of plasma that produced >15% (for IgA and IgG) or >30% (for IgM) absorbance of the positive control at a 1:31.6 (IgG and IgM) or 1:10 dilution (IgA).	GraphPad suggested: (GraphPad Prism, RRID:SCR_002798)
   PLSDA: Partial least squares discriminant analysis (PLSDA), performed in Eigenvectors PLS toolbox in Matlab, was used in conjunction with Elastic-Net, described above, to identify and visualize signatures that distinguish categorical outcomes (COVID-19 diagnosis, NIH scores, drug therapies).	Matlab suggested: (MATLAB, RRID:SCR_001622)
   In R, data were subject to arcsinh transformation and clustering using FlowSOM 27.	FlowSOM suggested: (FlowSOM, RRID:SCR_016899)

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   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).

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   Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:

   There are limitations to the current study. Firstly, ETA samples were only collected from patients with severe disease requiring invasive oxygen support, therefore, it is unclear whether COVID-19 patients with milder symptoms had less robust immune responses in the respiratory tract. Additionally, most patients in the severe/critical group received dexamethasone, which could be an intercorrelating factor for the differences observed between severity groups. Moreover, while the non-COVID-19 controls provided insights onto the immune status in hospitalized individuals, the comparisons will benefit more if there were larger numbers of non-COVID patients with more homogenous diseases. Overall, innate and adaptive immune responses are generated in respiratory and blood samples of COVID-19 patients. While immunological features detected in the peripheral blood can be associated with robust immune responses and predict clinical outcomes, monitoring immune responses in the respiratory samples can be of a benefit prior to initiation of therapeutic interventions for COVID-19 patients.

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   Results from TrialIdentifier: No clinical trial numbers were referenced.

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   Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

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   Results from JetFighter: We did not find any issues relating to colormaps.

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   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.

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   Results from scite Reference Check: We found no unreliable references.

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3. 

   Version published to 10.1101/2021.09.01.21262715v1 on medRxiv

   Sep 7, 2021
4. 

   Version published to 10.21203/rs.3.rs-802084/v1 on Research Square

   Aug 26, 2021