Sleep and circadian rhythm disruption alters the lung transcriptome to predispose to viral infection

  1. Lewis Taylor
  2. Felix Von Lendenfeld
  3. Anna Ashton
  4. Harshmeena Sanghani
  5. Simona Di Pretoro
  6. Laura Usselmann
  7. Maria Veretennikova
  8. Robert Dallmann
  9. Jane A. McKeating
  10. Sridhar Vasudevan
  11. Aarti Jagannath

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Abstract

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  1. Version published to 10.1016/j.isci.2022.105877
  2. ScreenIT

    SciScore for 10.1101/2022.02.28.482377: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variableAnimals: All studies were conducted using male C57BL/6 mice over 8 weeks of age and, unless otherwise indicated, animals were group housed with ad libitum access to food and water under a 12:12 hour light/dark cycle (100 lux from white LED lamps).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Experimental Models: Organisms/Strains
    SentencesResources
    Animals: All studies were conducted using male C57BL/6 mice over 8 weeks of age and, unless otherwise indicated, animals were group housed with ad libitum access to food and water under a 12:12 hour light/dark cycle (100 lux from white LED lamps).
    C57BL/6
    suggested: None
    We first reduced the transcriptomic datasets to 10 circadian features, i. e., transcripts known to be highly rhythmic across murine organ systems (Arntl, Per2, Per3, Tef, Hlf, Dbp, Nr1d1, Nr1d2, Npas2, and Dtx4) 92.
    Npas2
    suggested: None
    Software and Algorithms
    SentencesResources
    Processing of RNA sequencing data: Raw RNA-Seq data processing (quality control, trimming, mapping to the genome, and read counting) was performed using tools embedded in Galaxy (v21.05) 81.
    Galaxy
    suggested: (Galaxy, RRID:SCR_006281)
    FastQC (v0.11.8) (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) was used for quality control of sequencing data.
    FastQC
    suggested: (FastQC, RRID:SCR_014583)
    For quality and adapter trimming, Trim Galore! (v0.6.3) (https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/) was employed to remove low-quality bases, short reads, and Illumina adapters.
    Trim Galore
    suggested: (Trim Galore, RRID:SCR_011847)
    High quality reads were then mapped to the Mus musculus (mm10) reference genome using HISAT2 (v2.1.0) 82, specifying the strand information as reverse.
    HISAT2
    suggested: (HISAT2, RRID:SCR_015530)
    MultiQC (v1.9) 84 was used to aggregate FastQC, HISAT2, and featureCounts results.
    MultiQC
    suggested: (MultiQC, RRID:SCR_014982)
    featureCounts
    suggested: (featureCounts, RRID:SCR_012919)
    Differential gene expression analysis: To identify differentially expressed genes in the SD and times series (ZT) datasets (adjusted p value < 0.05), the DESeq2 package (v1.32.0) 85 was used in R (v4.1.0).
    DESeq2
    suggested: (DESeq, RRID:SCR_000154)
    Heatmaps were drawn using the pheatmap function from the pheatmap package (v1.0.12).
    pheatmap
    suggested: (pheatmap, RRID:SCR_016418)
    Volcano plots were generated using the ggplot2 package (v.3.3.5).
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    To detect periodicity in the time series (ZT) data, the MetaCycle R package (v1.2.0) was used 86.
    MetaCycle
    suggested: None
    Functional enrichment analysis: Functional enrichment analysis of SD-associated genes and cycling genes was conducted using the clusterProfiler R package (v4.0.0) 87
    clusterProfiler
    suggested: (clusterProfiler, RRID:SCR_016884)
    Mm.eg.db (v3.13.0) as the Mus musculus genome annotation (GO BP parameters - pvalueCutoff = 0.01, qvalueCutoff = 0.05, pAdjustMethod = Benjamini–Hochberg correction and KEGG paramerters - pvalueCutoff = 0.05)
    KEGG
    suggested: (KEGG, RRID:SCR_012773)
    The network interaction between overrepresented GO BP pathways was visualized using the ClueGO application (v2.5.8) 88 and its plugin CluePedia (v1.5.8) 89 within the desktop version of the Cytoscape software (v3.8.2) 90.
    ClueGO
    suggested: (ClueGO, RRID:SCR_005748)
    Cytoscape
    suggested: (Cytoscape, RRID:SCR_003032)
    Singular value decomposition was applied to the 16 samples collected at times ZT2, ZT8, ZT14, and ZT20 to obtain the principal directions (using the svd function in MATLAB v2020b).
    MATLAB
    suggested: (MATLAB, RRID:SCR_001622)
    Statistical testing was performed in R, MATLAB, and GraphPad Prism 9 (v9.1.2).
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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

    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 10.1101/2022.02.28.482377 on bioRxiv