Temporal proteomic characterization of SARS-CoV-2 infected mouse lungs

Understanding of dynamic activations of pathophysiological processes in the infected lungs is important for effective treatment of SARS-CoV-2 infection. Time-course transcriptome analyses of infected lungs have been performed to address this issue. Since proteins actually execute the pathophysiological processes, however, the time-course transcriptome data provide limited information regarding their temporal transitions. Here, we present time-course proteomic profiling of lung tissues from K18-hACE2 transgenic mice using liquid chromatography-tandem mass spectrometry analysis at day 0, 1, 2, 5, and 7 after SARS-CoV-2 infection. Clustering analysis to identify early, intermediate, and late up-regulated proteins, analysis of pathways enriched by these proteins, and network analysis of early, intermediate, and late up-regulated pathways revealed detailed dynamic activations of molecular networks perturbed upon infection, and further proposed five markers that represented early-to-intermediate activation of nonsense-mediated decay (Smg6 and Upf1), intermediate-to-late activation of phagocytosis (Fcgr4 and Lamp2), and late activation of neutrophil extracellular trap formation (Padi4) that could be associated with severe pathological transitions. Immunohistochemistry analysis confirmed these temporal up-regulation patterns of the five markers identified from the time-course proteome data, and immunofluorescence analysis further confirmed that Padi4 was up-regulated predominantly in neutrophils at the late stage. Our temporal proteomic analysis suggests potential pathway and molecule markers that can be used to predict severe pathological transitions during the course of SARS-CoV-2 infection.