Acute SARS-CoV-2 infection is associated with an increased abundance of bacterial pathogens, including Pseudomonas aeruginosa in the nose

  1. Nicholas S. Rhoades
  2. Amanda N. Pinski
  3. Alisha N. Monsibais
  4. Allen Jankeel
  5. Brianna M. Doratt
  6. Isaac R. Cinco
  7. Izabela Ibraim
  8. Ilhem Messaoudi

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Abstract

No abstract available

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  1. Version published to 10.1016/j.celrep.2021.109637
  2. ScreenIT

    SciScore for 10.1101/2021.05.20.445008: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The generated sequence variants were then aligned using MAFFT (41), and a phylogenetic tree was constructed using FastTree 2 (42).
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    FastTree
    suggested: (FastTree, RRID:SCR_015501)
    Taxonomy was assigned to sequence variants using q2-feature-classifier against the SILVA Database (release: 138) (43).
    SILVA
    suggested: (SILVA, RRID:SCR_006423)
    All statistical analyses were conducted using PRISM (V8) or the R package Vegan (46).
    PRISM
    suggested: (PRISM, RRID:SCR_005375)
    The LEfSe algorithm was used to identify differentially abundant taxa and pathways between groups with a logarithmic Linear discriminant analysis (LDA) score cutoff of 2 (47).
    LEfSe
    suggested: (LEfSe, RRID:SCR_014609)
    The ~300 bp amplicons were PCR-amplified and indexed with a unique molecular identifier. cDNA libraries were assessed for quality and quantity on the BioAnalyzer prior to single-end sequencing (x100bp) using the Illumina NovaSeq platform.
    BioAnalyzer
    suggested: (BioAnalyzer 2100, RRID:SCR_019715)
    RNA-Seq reads were demultiplexed, quality-filtered and trimmed for quality and adapter removal using Trim Galore (average Phred Score cut-off = 30, minimum length of 50 basepairs).
    Trim Galore
    suggested: (Trim Galore, RRID:SCR_011847)
    Tophat was used to align filtered reads to the reference genome Homo sapiens (GRCh38).
    Tophat
    suggested: (TopHat, RRID:SCR_013035)
    Statistical analysis with edgeR was used to determine differentially expressed genes (DEGs) meeting the following criteria: genes with median rpkm of ≥1, a false discovery rate (FDR) corrected p-value ≤ 0.05 and a log2fold change ≥ 1 compared to CoV-samples.
    edgeR
    suggested: (edgeR, RRID:SCR_012802)
    Functional enrichment of DEGs was performed using Metascape to identify relevant Gene Ontology (GO) biological process terms (49).
    Metascape
    suggested: (Metascape, RRID:SCR_016620)
    Heatmaps, bar graphs and volcano plots were generated using R package ggplot2.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    Samples were indexed, pooled and validated with 2100 Agilent BioAn.
    Agilent BioAn
    suggested: None
    Merged reads were aligned to SARS-CoV-2 Wuhan isolate NC_045512.2 with BWA-mem software version 0.7.17.
    BWA-mem
    suggested: (Sniffles, RRID:SCR_017619)

    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:
    This study had some limitations. The samples used in this study were initially collected for SARS-CoV-2 diagnosis and were therefore not processed in the typical fashion for either host transcriptomics or microbiome analysis. Nevertheless, we were able to obtain enough DNA and RNA for the studies shown here. Additionally, our study consisted of only 1 time point. A longitudinal study should be performed to gain much needed insight into the dynamic changes in microbial communities and host responses within the nasal cavity. Finally, analysis of samples from individuals with asymptomatic infection would provide additional valuable insight into determinants of disease.

    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 10.1101/2021.05.20.445008v1 on bioRxiv