The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread to nearly every continent, registering over 1,250,000 deaths worldwide. The effects of SARS-CoV-2 on host targets remains largely limited, hampering our understanding of Coronavirus Disease 2019 (COVID-19) pathogenesis and the development of therapeutic strategies. The present study used a comprehensive untargeted metabolomic and lipidomic approach to capture the host response to SARS-CoV-2 infection. We found that several circulating lipids acted as potential biomarkers, such as phosphatidylcholine 14:0_22:6 (area under the curve (AUC) = 0.96), phosphatidylcholine 16:1_22:6 (AUC = 0.97), and phosphatidylethanolamine 18:1_20:4 (AUC = 0.94). Furthermore, triglycerides and free fatty acids, especially arachidonic acid (AUC = 0.99) and oleic acid (AUC = 0.98), were well correlated to the severity of the disease. An untargeted analysis of non-critical COVID-19 patients identified a strong alteration of lipids and a perturbation of phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, aminoacyl-tRNA degradation, arachidonic acid metabolism, and the tricarboxylic acid (TCA) cycle. The severity of the disease was characterized by the activation of gluconeogenesis and the metabolism of porphyrins, which play a crucial role in the progress of the infection. In addition, our study provided further evidence for considering phospholipase A2 (PLA2) activity as a potential key factor in the pathogenesis of COVID-19 and a possible therapeutic target. To date, the present study provides the largest untargeted metabolomics and lipidomics analysis of plasma from COVID-19 patients and control groups, identifying new mechanisms associated with the host response to COVID-19, potential plasma biomarkers, and therapeutic targets.
Knowledge of the host response to the novel coronavirus SARS-CoV-2 remains limited, hindering the understanding of COVID-19 pathogenesis and the development of therapeutic strategies. During the course of a viral infection, host cells release exosomes and other extracellular vesicles carrying viral and host components that can modulate the immune response. The present study used a shotgun proteomic approach to map the host circulating exosomes’ response to SARS-CoV-2 infection. We investigated how SARS-CoV-2 infection modulates exosome content, exosomes’ involvement in disease progression, and the potential use of plasma exosomes as biomarkers of disease severity. A proteomic analysis of patient-derived exosomes identified several molecules involved in the immune response, inflammation, and activation of the coagulation and complement pathways, which are the main mechanisms of COVID-19–associated tissue damage and multiple organ dysfunctions. In addition, several potential biomarkers—such as fibrinogen, fibronectin, complement C1r subcomponent and serum amyloid P-component—were shown to have a diagnostic feature presenting an area under the curve (AUC) of almost 1. Proteins correlating with disease severity were also detected. Moreover, for the first time, we identified the presence of SARS-CoV-2 RNA in the exosomal cargo, which suggests that the virus might use the endocytosis route to spread infection. Our findings indicate circulating exosomes’ significant contribution to several processes—such as inflammation, coagulation, and immunomodulation—during SARS-CoV-2 infection. The study’s data are available via ProteomeXchange with the identifier PXD021144.
SUMMARYNew theoretical molecular indices are defined. They contain information about the whole molecular structure in terms of size, shape, symmetry and atom distribution. These indices are calculated from the ( x , y , I) co-ordinates of a molecule within different weighting schemes in a straightforward manner and represent a very general approach to describe molecules, molecular fragments, macromolecules and molecular conformations in a unitary conceptual framework. Their interpretability is quite evident and is defined by the same mathematical properties as the algorithm used for their calculation. Examples on the total surface area, toxicity of PCDD and PCDF and reaction rate of catalysed reactions show a high modelling power of these indices.
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