Metabolic reprograming shapes neutrophil functions in severe COVID-19.

To better understand the mechanisms at the basis of neutrophil functions during SARS-CoV-2, we studied patients with severe COVID-19 pneumonia. They had high blood proportion of degranulated neutrophils and elevated plasma levels of myeloperoxidase (MPO), elastase, and MPO-DNA complexes, which are typical markers of neutrophil extracellular traps (NET). Their neutrophils display dysfunctional mitochondria, defective oxidative burst, increased glycolysis, glycogen accumulation in the cytoplasm, and increase glycogenolysis. Hypoxia-inducible factor 1α (ΗΙF-1α) is stabilized in such cells, and it controls the level of glycogen phosphorylase L (PYGL), a key enzyme in glycogenolysis. Inhibiting PYGL abolishes the ability of neutrophils to produce NET. Patients displayed significant increases of plasma levels of molecules involved in the regulation of neutrophils' function including CCL2, CXCL10, CCL20, IL-18, IL-3, IL-6, G-CSF, GM-CSF, IFN-γ. Our data suggest that metabolic remodelling is vital for the formation of NET and for boosting neutrophil inflammatory response, thus, suggesting that modulating ΗΙF-1α or PYGL could represent a novel approach for innovative therapies.

COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

Data and Text Mining Help Identify Key Proteins Involved in the Molecular Mechanisms Shared by SARS-CoV-2 and HIV-1.

Viruses can be spread from one person to another; therefore, they may cause disorders in many people, sometimes leading to epidemics and even pandemics. New, previously unstudied viruses and some specific mutant or recombinant variants of known viruses constantly appear. An example is a variant of coronaviruses (CoV) causing severe acute respiratory syndrome (SARS), named SARS-CoV-2. Some antiviral drugs, such as remdesivir as well as antiretroviral drugs including darunavir, lopinavir, and ritonavir are suggested to be effective in treating disorders caused by SARS-CoV-2. There are data on the utilization of antiretroviral drugs against SARS-CoV-2. Since there are many studies aimed at the identification of the molecular mechanisms of human immunodeficiency virus type 1 (HIV-1) infection and the development of novel therapeutic approaches against HIV-1, we used HIV-1 for our case study to identify possible molecular pathways shared by SARS-CoV-2 and HIV-1. We applied a text and data mining workflow and identified a list of 46 targets, which can be essential for the development of infections caused by SARS-CoV-2 and HIV-1. We show that SARS-CoV-2 and HIV-1 share some molecular pathways involved in inflammation, immune response, cell cycle regulation.

Kynurenic acid may underlie sex-specific immune responses to COVID-19.

Coronavirus disease 2019 (COVID-19) has poorer clinical outcomes in males than in females, and immune responses underlie these sex-related differences. Because immune responses are, in part, regulated by metabolites, we examined the serum metabolomes of COVID-19 patients. In male patients, kynurenic acid (KA) and a high KA-to-kynurenine (K) ratio (KA:K) positively correlated with age and with inflammatory cytokines and chemokines and negatively correlated with T cell responses. Males that clinically deteriorated had a higher KA:K than those that stabilized. KA inhibits glutamate release, and glutamate abundance was lower in patients that clinically deteriorated and correlated with immune responses. Analysis of data from the Genotype-Tissue Expression (GTEx) project revealed that the expression of the gene encoding the enzyme that produces KA, kynurenine aminotransferase, correlated with cytokine abundance and activation of immune responses in older males. This study reveals that KA has a sex-specific link to immune responses and clinical outcomes in COVID-19, suggesting a positive feedback between metabolites and immune responses in males.

Physiological and Pathological Inflammation Induced by Antibodies and Pentraxins.

Macrophages play a key role in induction of inflammatory responses. These inflammatory responses are mostly considered to be instigated by activation of pattern recognition receptors (PRRs) or cytokine receptors. However, recently it has become clear that also antibodies and pentraxins, which can both activate Fc receptors (FcRs), induce very powerful inflammatory responses by macrophages that can even be an order of magnitude greater than PRRs. While the physiological function of this antibody-dependent inflammation (ADI) is to counteract infections, undesired activation or over-activation of this mechanism will lead to pathology, as observed in a variety of disorders, including viral infections such as COVID-19, chronic inflammatory disorders such as Crohn's disease, and autoimmune diseases such as rheumatoid arthritis. In this review we discuss how physiological ADI provides host defense by inducing pathogen-specific immunity, and how erroneous activation of this mechanism leads to pathology. Moreover, we will provide an overview of the currently known signaling and metabolic pathways that underlie ADI, and how these can be targeted to counteract pathological inflammation.