Niclosamide reverses SARS-CoV-2 control of lipophagy

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   ScreenIT

   Jul 16, 2021

   SciScore for 10.1101/2021.07.11.451951: (What is this?)

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

   Table 1: Rigor

   Ethics	not detected.
   Sex as a biological variable	The cells are female.
   Randomization	not detected.
   Blinding	The investigators were not blinded to the conditions.
   Power Analysis	not detected.
   Cell Line Authentication	Authentication: These cells have been authenticated.

   Table 2: Resources

   Experimental Models: Cell Lines
   Sentences	Resources
   EXPERIMENTAL MODEL AND SUBJECT DETAILS: Vero E6 cells: Vero clone E6 cells (ATCC: CRL-1586) were obtained from Dr. Pei-Yong Shi (University of Texas Medical Branch).	Vero E6 suggested: None Vero clone E6 suggested: None
   Software and Algorithms
   Sentences	Resources
   Data and code availability: The raw and processed data generated here have been deposited in publicly accessible databases; …

   SciScore for 10.1101/2021.07.11.451951: (What is this?)

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

   Table 1: Rigor

   Ethics	not detected.
   Sex as a biological variable	The cells are female.
   Randomization	not detected.
   Blinding	The investigators were not blinded to the conditions.
   Power Analysis	not detected.
   Cell Line Authentication	Authentication: These cells have been authenticated.

   Table 2: Resources

   Experimental Models: Cell Lines
   Sentences	Resources
   EXPERIMENTAL MODEL AND SUBJECT DETAILS: Vero E6 cells: Vero clone E6 cells (ATCC: CRL-1586) were obtained from Dr. Pei-Yong Shi (University of Texas Medical Branch).	Vero E6 suggested: None Vero clone E6 suggested: None
   Software and Algorithms
   Sentences	Resources
   Data and code availability: The raw and processed data generated here have been deposited in publicly accessible databases; the RNA sequencing data is available through NCBI’s GEO repository (Accession: GSE178157), and the lipidomics data is accessible via MetaboLights (Accession: MTBLS2943).	MetaboLights suggested: (MetaboLights, RRID:SCR_014663)
   Standard curve points were plotted in Microsoft Excel v.	Microsoft Excel suggested: (Microsoft Excel, RRID:SCR_016137)
   Mapping, expression, and pathway analyses: Bioinformatic processing was completed using Galaxy (https://galaxyproject.org, (Batut et al., 2018)).	Galaxy suggested: (Galaxy, RRID:SCR_006281)
   Quality control was performed with Cutadapt v 1.16 (Martin, 2011) and FastQC v 0.11.8 (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) to remove adapters, <20 nucleotide reads and low-quality reads.	Cutadapt suggested: (cutadapt, RRID:SCR_011841) FastQC suggested: (FastQC, RRID:SCR_014583)
   RNA STAR v2.7.7a (Dobin et al., 2013) was used to map samples to the Chlorocebus sabaeus genome and associated annotation (GenBank accession # GCA_015252025.1). featureCounts v 2.0.1 (Liao et al., 2014) was used with Infer Experiment v2.6.4.1 (Wang et al., 2012) to determine the strandedness of the samples, and sum reads for each gene.	STAR suggested: (STAR, RRID:SCR_004463) featureCounts suggested: (featureCounts, RRID:SCR_012919)
   Read counts for each sample were input into DESeq2 v 1.22.1 (Love et al., 2014) to call differential gene expression, analyzing the effect of time, drug, and virus on the samples.	DESeq2 suggested: (DESeq, RRID:SCR_000154)
   Resultant differential expression files were manually annotated using a combination of NCBI (O’Leary et al., 2016) and Ensembl (Yates et al., 2020) due to the poor annotation quality of the genome (https://www.ncbi.nlm.nih.gov/genome/annotation_euk/Chlorocebus_sabaeus/100/).	Ensembl suggested: (Ensembl, RRID:SCR_002344)
   Significantly regulated gene names were separately parsed out for each comparison and uploaded to ENRICHR (Kuleshov et al., 2016) for downstream gene ontology (GO (Harris et al., 2004)) and pathway analyses using Reactome (Fabregat et al., 2016), MSigDB (Liberzon et al., 2015), and KEGG (Ogata et al., 1999)) databases.	KEGG suggested: (KEGG, RRID:SCR_012773)
   Statistical P-values were obtained by application of the appropriate statistical tests using GraphPad Prism v.9.0.	GraphPad Prism suggested: (GraphPad Prism, RRID:SCR_002798)
   Lipidomics data was normalized to the total ion signal, glog transformed, autoscaled and analyzed with Metaboanalyst v.	Metaboanalyst suggested: (MetaboAnalyst, RRID:SCR_015539)

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   Results from OddPub: Thank you for sharing your data.

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

   Limitations: Although we used a C. sabaeus kidney epithelial cell line (Vero E6) and a SARS-CoV-2 strain isolated from a Floridian patient, we observed a similar (in direction and magnitude) transcriptomic response to other SARS-CoV-2 transcriptomic studies, despite differences in MOI and experimental sampling timepoints. These changes were consistent across another Vero E6 study noting cell stress and apoptosis (DeDiego et al., 2011), as well as other cell systems, including human lung cells (Wyler et al., 2021), cardiomyocytes (Sharma et al., 2020), adenocarcinomic human alveolar basal epithelial cells (Daamen et al., 2021), and bronchial epithelial cells (Yoshikawa et al., 2010), infected with different betacoronaviruses, suggesting the responses detected herein may represent a core set of host SARS-CoV viral response genes, and that these genes are not exclusive to our study system. Our work is limited to an in vitro model; however, it was recently shown in a multiomics study of COVID-19 patient samples that the lipidomic profile can effectively partition COVID-19 disease severity (Overmyer et al., 2021); implying that the biology captured in our culture model is relevant in vivo. While these observations highlight potential utility of niclosamide, these data alone do not support its indication in the clinic in the treatment of COVID-19.

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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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2. 

   Version published to 10.1101/2021.07.11.451951v1 on bioRxiv

   Jul 12, 2021