Biology subjects

Silva, B. M.

Publications and source records attributed to Silva, B. M..

3 recordsLinked to original sources

bioRxiv2022

Targeting C5aR1 signaling reduced neutrophil extracellular traps and ameliorates COVID-19 pathology

Patients with severe COVID-19 develop acute respiratory distress syndrome (ARDS) that may progress to cytokine storm syndrome, organ dysfunction, and death. Considering that complement component 5a (C5a), through its cellular receptor C5aR1, has potent proinflammatory actions, and plays immunopathological roles in inflammatory diseases, we investigated whether C5a/C5aR1 pathway could be involved in COVID-19 pathophysiology. C5a/C5aR1 signaling increased locally in the lung, especially in neutrophils of critically ill COVID-19 patients compared to patients with influenza infection, as well as in the lung tissue of K18-hACE2 Tg mice (Tg mice) infected with SARS-CoV-2. Genetic and pharmacological inhibition of C5aR1 signaling ameliorated lung immunopathology in Tg-infected mice. Mechanistically, we found that C5aR1 signaling drives neutrophil extracellular trap (NET)s-dependent immunopathology. These data confirm the immunopathological role of C5a/C5aR1 signaling in COVID-19 and indicate that antagonist of C5aR1 could be useful for COVID-19 treatment.

immunology↗

bioRxiv2022

Targeting Neutrophils Extracellular Traps (NETs) reduces multiple organ injury in a COVID-19 mouse model

COVID-19 is characterized by severe acute lung injury, which is associated with neutrophils infiltration and release of neutrophil extracellular traps (NETs). COVID-19 treatment options are scarce. Previous work has shown an increase in NETs release in the lung and plasma of COVID-19 patients suggesting that drugs that prevent NETs formation or release could be potential therapeutic approaches for COVID-19 treatment. Here, we report the efficacy of NET-degrading DNase I treatment in a murine model of COVID-19. DNase I decreased detectable levels of NETs, improved clinical disease, and reduced lung, heart, and kidney injuries in SARS-CoV-2-infected K18-hACE2 mice. Furthermore, our findings indicate a potential deleterious role for NETs lung tissue in vivo and lung epithelial (A549) cells in vitro, which might explain part of the pathophysiology of severe COVID-19. This deleterious effect was diminished by the treatment with DNase I. Together, our results support the role of NETs in COVID-19 immunopathology and highlight NETs disruption pharmacological approaches as a potential strategy to ameliorate COVID-19 clinical outcomes.

pharmacology and toxicology↗

bioRxiv2020

Workflow for Protein N-terminal Acetylation and C-terminal Amidation Application using CcpNmr Analysis v2.4 Platform and Aria2.3 Structure Calculation Software

Structural biology is a field that enables a better understanding of proteins from scratch. From the available techniques, solution NMR is one well established that provides structure, dynamics and protein-molecules interaction. In a NMR lab routine, from data acquisition until protein/mechanisms elucidation comes a process that can undergo months. During the past decades, different tools were developed for NMR data processing, peaks assignment, structure elucidation and data submission. Since many of these programs demand great computational skills, a few groups have tried to combine those programs and make them more friendly and useful, what can possibilite a faster process. Here we highlight CCPNMR2.4 analysis and ARIA2.3, responsible for peak assignment and structure calculation, respectively, and can work associated. Although being academic free and the possibility of working with a GUI interface, the common N-terminal acetylation and C-terminal amidation modifications are not implemented in a way that possibilities to work with them in combination, what results in a dilemma. This work brings visual data that evidences the low usability of CCPN and ARIA with N-terminal acetylated and C-terminal amidated proteins and propose a workflow to overcome this problem, which may improve the usage of both software in the mentioned versions and facilitate the lab users already used to these programs. As a proof of concept, we have chosen a N-terminal amidated peptide, L-Phenylseptin, whose structure has already been solved with other programs. Statistical data shows that no significant difference was found with the structure obtained with the new protocol. In conclusion, we exhibit a new protocol that can be used in combination with CCPNMR2.4 and ARIA2.3 for protein with the mentioned modifications and it successfully works and manipulates these molecules.

bioinformatics↗