Footprint based analysis and causal network contextualisation in SARS-CoV-2 infected A549 cell line

We further used the transcriptome dataset from the GEO database with accession number GSE147507 (Blanco-Melo et al., 2020) to extract the series number 5 from the dataset, consisting of 2 conditions in triplicate, A549 cells treated with a mock and A549 infected with SARS-CoV-2, measured 24 hours after treatment. Phosphoproteomic data of mock-treated and SARS-CoV2 infected cells were extracted from (Stukalov et al., 2020). We then applied our pipeline described in M&M X. This work notably highlighted the activation of the MAP kinase family (MAPK1, MAPK3, MAPK7, MAPK11, MAPKAPK2) as a cellular response to SARS-CoV-2 infection, alongside EGFR, LYN, and ATM kinases (Figure 1). CARNIVAL highlighted widely studied signaling proteins such as PIK3CA, BRCA1, and RUNX1. In addition, genes involved in immune pathways, such as TICAM1, TBK1, IKBKE, and IRF3, are found in both our results and the curated pathogen-associated molecular patterns (PAMPs) and Interferon-1 pathways. A more intriguing result is the identification of relevant players in the Endoplasmic reticulum (ER) stress pathway, in particular ATF4, ATF6, and MBTPS1. A potential crosstalk between the ER stress pathway and immune pathways was discussed in our previous work (Ostaszewski et al., 2021). Our casual network supports this hypothesis and highlights interactions that may play a pivotal role in the mentioned crosstalk.