Reprogramming of the intestinal epithelial-immune cell interactome during SARS-CoV-2 infection
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Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) represents an unprecedented worldwide health problem. Although the primary site of infection is the lung, growing evidence points towards a crucial role of the intestinal epithelium. Yet, the exact effects of viral infection and the role of intestinal epithelial-immune cell interactions in mediating the inflammatory response are not known. In this work, we apply network biology approaches to single-cell RNA-seq data from SARS-CoV-2 infected human ileal and colonic organoids to investigate how altered intracellular pathways upon infection in intestinal enterocytes leads to modified epithelial-immune crosstalk. We point out specific epithelial-immune interactions which could help SARS-CoV-2 evade the immune response. By integrating our data with existing experimental data, we provide a set of epithelial ligands likely to drive the inflammatory response upon infection. Our integrated analysis of intra- and inter-cellular molecular networks contribute to finding potential drug targets, and suggest using existing anti-inflammatory therapies in the gut as promising drug repurposing strategies against COVID-19.
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SciScore for 10.1101/2021.08.09.455656: (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
Software and Algorithms Sentences Resources Source databases used to retrieve the ligand-receptor interactions through OmnipathR included six independent resources (CellPhoneDB, HPMR, Ramilowski 2015, Guide2Pharma, Kirouac 2010, Gene Ontology) (Ashburner et al., 2000; Ben-Shlomo et al., 2003; Kirouac et al., 2010; Pawson et al., 2014; Ramilowski et al., 2015; Vento-Tormo et al., 2018). CellPhoneDBsuggested: (CellPhoneDB, RRID:SCR_017054)Information on viral proteins and their interacting human binding partners was obtained from the SARS-CoV-2 collection of the IntAct database on 1st October 2020 (Hermjakob et al., 2004; Orchard et … SciScore for 10.1101/2021.08.09.455656: (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
Software and Algorithms Sentences Resources Source databases used to retrieve the ligand-receptor interactions through OmnipathR included six independent resources (CellPhoneDB, HPMR, Ramilowski 2015, Guide2Pharma, Kirouac 2010, Gene Ontology) (Ashburner et al., 2000; Ben-Shlomo et al., 2003; Kirouac et al., 2010; Pawson et al., 2014; Ramilowski et al., 2015; Vento-Tormo et al., 2018). CellPhoneDBsuggested: (CellPhoneDB, RRID:SCR_017054)Information on viral proteins and their interacting human binding partners was obtained from the SARS-CoV-2 collection of the IntAct database on 1st October 2020 (Hermjakob et al., 2004; Orchard et al., 2014). IntActsuggested: (IntAct, RRID:SCR_006944)ViralLink pipeline: Intracellular causal networks were inferred using the ViralLink pipeline, as described in (Treveil et al., 2021). ViralLinksuggested: NoneFor both ileal and colonic data, separate networks were generated using the viral miRNA and viral protein as perturbations, and subsequently joined using the “Merge” function within Cytoscape to generate the final intracellular network. Cytoscapesuggested: (Cytoscape, RRID:SCR_003032)Briefly, PROGENy is used to infer pathway activity from the log2 FC of the infected immature enterocytes 2 gene expression data (Schubert et al., 2018). PROGENysuggested: (PROGENY, RRID:SCR_006647)For the Reactome pathway enrichment analysis the IDs were converted to Entrez Gene ID within the ‘ReactomePA’ package. Entrez Genesuggested: (Entrez Gene, RRID:SCR_002473)Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:The methodology we used for our analysis has some limitations. When constructing the intracellular causal network, the effect of SARS-CoV-2 proteins towards human binding partners was always considered as inhibitory. However, this is not always the case. In the future, with increasingly available data, a more refined model could be generated. Furthermore, two different single cell transcriptomics datasets were used for colonic and ileal immune cell populations, due to the unavailability of both datasets from the same experiment. Similarly, IBD uninflamed data and healthy data were used for the ileum and colon respectively, as healthy control scRNAseq immune cell data for both tissues was not available at the time of the analysis. Finally, the a priori resources used to infer the intracellular and intercellular interaction networks may have some intrinsic limitations associated with them (Dimitrov et al., 2021) specific tools such as LIANA (LIgand-receptor ANalysis frAmework; https://github.com/saezlab/liana) could be used in the future to compare across several resources available, helping to choose the one(s) providing the best overall prediction. With our analysis, we provided a set of intestinal epithelial ligands and immune cell populations implicated in altered epithelial-immune interactions during SARS-CoV-2 infection, which could potentially drive the excessive inflammatory processes seen in severe COVID-19 patients. Further experimental validation will be key to valid...
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.
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