ABSTRACT
Introduction: The variation in human blood serum metabolites resulting from an infection can assist in understanding mechanisms of pathogen action and body response and improve diagnosis. Aim: To map serum signatures of hospitalized symptomatic patients, positive or negative to SARS-CoV-2. Methods: Patients (n = 64) admitted to Anhembi Field Municipal Hospital, a hospital set up for initial care to patients with moderate symptoms, were analyzed being discriminated in positive (n = 32) or negative patients. Age and gender were matched to ensure homogeneity in the basal metabolic rates. Three Nuclear Magnetic Resonance (NMR) data set were recorded on Bruker AVANCE III 600 MHz spectrometer for serum samples analyzed in MetaboAnalyst 5.0 software platform. Results and discussion: The mean age of groups was 54.92 ±12.41 and 54.30 ±12.15, for positive and negative patients, divided in 16 female and 16 male. The ethnicity was 56.2% vs 46.8% caucasian, 34.3% mixed race in both groups, and 9.3% 12.5% vs black in positive and negative groups, respectively. BMI was 24 ±6.93 vs 33.5 ±7.85 in comparison to positive and negative patients, respectively. In both groups 50% of patients presented alveolar infiltrate. Although the groups were not paired by comorbidities, they were homogeneous ensuring that the metabolic variation is due to COVID-19 as similar percentage of patients with arterial hypertension, diabetes and dyslipidemia. Clinical symptoms were also remarkably similar between the groups in relation to: fever, dry cough, dyspnea and myalgia. The Partial Least Squares - Discriminant Analysis (PLS-DA) performed onto noesy1d data discriminated positively from negative patients. Also, it covered lower variance. Combining NMR techniques, it was possible to depict the main metabolites that distinguished the COVID-19 signatures. Alanine, glucose, cholesterol, and glutamine were increased, and lactate decreased in COVID-19. Conclusion: These results suggest NMR as an excellent tool to differentiate hospitalized patients with moderate symptoms as COVID-19 positive or negative. The Ethics Research Committee of the University of Campinas approved all of the experimental procedures, and all individuals signed the informed consent form.
ABSTRACT
Tumor necrosis factor (TNF) is a homotrimer that has two spatially distinct binding regions, three lectin-like domains (LLD) at the TIP of the protein and three basolaterally located receptor-binding sites, the latter of which are responsible for the inflammatory and cell death-inducing properties of the cytokine. Solnatide (a.k.a. TIP peptide, AP301) is a 17-mer cyclic peptide that mimics the LLD of human TNF which activates the amiloride-sensitive epithelial sodium channel (ENaC) and, as such, recapitulates the capacity of TNF to enhance alveolar fluid clearance, as demonstrated in numerous preclinical studies. TNF and solnatide interact with glycoproteins and these interactions are necessary for their trypanolytic and ENaC-activating activities. In view of the crucial role of ENaC in lung liquid clearance, solnatide is currently being evaluated as a novel therapeutic agent to treat pulmonary edema in patients with moderate-to-severe acute respiratory distress syndrome (ARDS), as well as severe COVID-19 patients with ARDS. To facilitate the description of the functional properties of solnatide in detail, as well as to further target-docking studies, we have analyzed its folding properties by NMR. In solution, solnatide populates a set of conformations characterized by a small hydrophobic core and two electrostatically charged poles. Using the structural information determined here and also that available for the ENaC protein, we propose a model to describe solnatide interaction with the C-terminal domain of the ENaCα subunit. This model may serve to guide future experiments to validate specific interactions with ENaCα and the design of new solnatide analogs with unexplored functionalities.