Longitudinal characterization of circulating neutrophils uncovers phenotypes associated with severity in hospitalized COVID-19 patients

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1. Version published to 10.1016/j.xcrm.2022.100779

   Oct 1, 2022
2. 

   ScreenIT

   Oct 7, 2021

   SciScore for 10.1101/2021.10.04.463121: (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
   IgG subclass, isotype, and FcγR binding: SARS-CoV-2 and eCoV-specific antibody subclass/isotype levels were assessed using a 384-well based customized multiplexed Luminex assay, as previously described27.	IgG subclass , isotype suggested: None eCoV-specific suggested: None
   Unbound antibodies were washed away, and antigen-bound antibodies were detected by using a PE-coupled detection antibody for each subclass and isotype (IgG1, IgG2, IgG3, IgG4, IgA1, and IgM; Southern Biotech).	antigen-bound suggested: None IgA1 suggested: None
   PE median fluorescence intensity (MFI) is reported as a readout for …

   SciScore for 10.1101/2021.10.04.463121: (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
   IgG subclass, isotype, and FcγR binding: SARS-CoV-2 and eCoV-specific antibody subclass/isotype levels were assessed using a 384-well based customized multiplexed Luminex assay, as previously described27.	IgG subclass , isotype suggested: None eCoV-specific suggested: None
   Unbound antibodies were washed away, and antigen-bound antibodies were detected by using a PE-coupled detection antibody for each subclass and isotype (IgG1, IgG2, IgG3, IgG4, IgA1, and IgM; Southern Biotech).	antigen-bound suggested: None IgA1 suggested: None
   PE median fluorescence intensity (MFI) is reported as a readout for antigen-specific antibody titers.	antigen-specific suggested: None
   Antibody-dependent neutrophil phagocytosis (ADNP) assay: ADNP was conducted as previously described58.	Antibody-dependent neutrophil phagocytosis ( ADNP suggested: None
   Antibody-dependent neutrophil ROS release: A high-binding 96-well plate was coated with SARS-CoV-2 Spike protein (5ug/ml) and blocked with 5% BSA.	Antibody-dependent neutrophil ROS suggested: None
   Immunoglobulin Levels in Plasma, and Antibody-Dependent Neutrophil Phagocytosis Assay, Related to Figure 5.	Antibody-Dependent Neutrophil Phagocytosis Assay , suggested: None
   Experimental Models: Organisms/Strains
   Sentences	Resources
   Smart-Seq2 cDNA preparation: cDNA was prepared from bulk populations of 2×104 neutrophils per sample via the Smart-Seq2 protocol80 with some modifications to the reverse transcription step as previously described81.	Smart-Seq2 protocol80 suggested: None
   Software and Algorithms
   Sentences	Resources
   Cells were counted on a TC20™ Automated Cell Counter (Bio-Rad Laboratories, Inc., Cat# 1450102) with trypan blue staining for dead cell exclusion.	Bio-Rad Laboratories suggested: (Bio-Rad Laboratories, RRID:SCR_008426)
   Antibody-dependent neutrophil phagocytosis (ADNP) assay: ADNP was conducted as previously described58.	ADNP suggested: None
   Flow cytometry was performed with an IQue (Intellicyt) or LSRII(BD), and analysis was performed using IntelliCyt ForeCyt (v8.1) or FlowJo V10.7.1.	FlowJo suggested: (FlowJo, RRID:SCR_008520)
   GENCODE v35 with the appended SARS-CoV2 GTF was used for annotation.	GENCODE suggested: (GENCODE, RRID:SCR_014966)
   Raw FASTQ files were aligned to the custom genome FASTA in the Terra platform with the Broad Institute GTEx pipeline using STAR v2.5.3a, and expression quantification based on a collapsed annotation was performed using RSEM v1.3.0.	STAR suggested: (STAR, RRID:SCR_004463) RSEM suggested: (RSEM, RRID:SCR_013027)
   Gene set enrichment analysis: We performed gene set enrichment analysis using the fgsea package in R using the following pathway sets from MSigDB Release v7.2: H, C5 GO BP.	Gene set enrichment analysis suggested: (Gene Set Enrichment Analysis, RRID:SCR_003199)
   The GMT file containing all genes per pathway used in this analysis will be available on Zenodo, and the lists are included in Supplementary Table S1.	Zenodo suggested: (ZENODO, RRID:SCR_004129)
   Clustering Analysis for Single-cell Blood Neutrophils from Sepsis Patients: The gene expression matrix was imported into R using Seurat 4.0.4.	Seurat suggested: (SEURAT, RRID:SCR_007322)
   The full model included CIBERSORTx estimated cell type fractions, the immunoglobulin score, and the terms for Day, SeverityMax, and the Day:SeverityMax interaction term, while the reduced model did not include the interaction term, and we used the likelihood ratio test in DESeq2 to compare these models.	DESeq2 suggested: (DESeq, RRID:SCR_000154)
   Heatmaps of the protein markers per cluster were generated with the pheatmap package in R, with genes ordered according to p value.	pheatmap suggested: (pheatmap, RRID:SCR_016418)

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   Results from OddPub: Thank you for sharing your code and data.

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

   We acknowledge several limitations of our study. First, we performed bulk transcriptomics rather than single-cell RNA-sequencing, so the neutrophil state gene signatures reflect a mixture of true neutrophil subtypes. Second, our samples were enriched for neutrophils via magnetic bead negative selection, and high purity of all samples across the cohort could not be guaranteed; thus, we used estimated cell type proportions as covariates in all analyses, but the expression of contaminating cell type-specific genes and cytokines cannot be excluded. Third, our time course data was collected on Days 0, 3, and 7 of hospitalization, though patients may have been infected for varying amounts of time prior to enrollment, so this cannot be considered an exact time course. Fourth, we only collected longitudinal samples from hospitalized patients, so we were unable to study patients pre-hospitalization or patients who were infected but never hospitalized. Fifth, sample collection at later time points was biased towards sicker patients as they needed to stay in the hospital for a longer period of time. Sixth, we did not collect a validation cohort, so our findings will need to be validated in external cohorts with similar multimodal data structures. Seventh, our study relies on blood draws and thus only provides insights into circulating factors that play a role in COVID-19 disease pathology, yet the findings regarding type III interferons and the IgA-dominant humoral response strongly imp...

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   Results from TrialIdentifier: We found the following clinical trial numbers in your paper:
   

   Identifier	Status	Title
   NCT04594356	Active, not recruiting	Assessment of Netosis During COVID-19, Under Treatment With …

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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.
   • Thank you for including a protocol registration statement.

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

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3. 

   Version published to 10.1101/2021.10.04.463121 on bioRxiv

   Oct 5, 2021