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Rodrigues-Neto, J. F.

Publications and source records attributed to Rodrigues-Neto, J. F..

2 recordsLinked to original sources

A novel approach to identify cross-identity peptides between Epstein-Barr virus and central nervous system proteins in Guillain-Barre syndrome and multiple sclerosis

BackgroundGuillain-Barre Syndrome (GBS) and multiple sclerosis are autoimmune diseases associated with an immune system attack response against peripheral and central nervous system autoantigens, respectively. Given the potential of Epstein-Barr virus (EBV) as a risk factor for both multiple sclerosis and GBS, the present study aimed to identify crucial residues among potential EBV CD4+ T lymphocyte epitopes and nervous system proteins. MethodsPublic databases (Allele Frequency Net Database, Immune Epitope Database, Genevestigator and Protein Atlas) were used to select proteins abundant in the nervous system, EBV immunogenic proteins, and HLA haplotypes. Computational tools were employed for predicting HLA-binding peptides and immunogenicity. For this, we developed immuno-cross, a Python tool (https://github.com/evoMOL-Lab/immuno-cross) to compare residue identity among nonamers. ResultsWe found ten proteins from the nervous system and 28 from EBV, which were used for predicting the binding peptides of 21 common HLAs in the world population. A total of 1411 haplotypes were distributed among 51 pairs of HLAs. Simulations were performed to determine whether nonamers from the EBV and nervous system proteins targeted TCR-contact residues. Then, three selection criteria were used, based on the relevance of each contact in the TCR-peptide-MHC interaction. The primary contact has to be located at position P5, and the positions P2, P3, and P8 were weighed as secondary, and P4, P6, and P7 were considered tertiary. Nonamers of EBV proteins and myelin proteins were combined in pairs and compared based on predefined selection criteria. The Periaxin protein had the highest number of nonamers pairs among PNS proteins, with 35 pairs. Four nonamers pairs from APLP1, two from CNP, and two from MBP bind to alleles of the haplotype DR-15. ConclusionsThe new approach proposed herein revealed that peptides derived from nervous system and EBV proteins share identical residues at critical contact points, which supports molecular mimicry. These findings suggest cross-reactivity between them and that the nonamer pairs identified with this approach have the potential to be an autoantigen. Experimental studies are needed to validate these findings.

bioinformatics↗

Understanding SARS-CoV-2 Spike glycoprotein clusters and their impact on immunity of the population from Rio Grande do Norte, Brazil

SARS-CoV-2 genome underwent mutations since it started circulating intensively within the human populations. The aim of this study was to understand the fluctuation of the spike clusters concomitant to high rate of population immunity either due to natural infection and/or vaccination in a state of Brazil that had high rate of infection and vaccination coverage. A total of 1715 SARS-CoV-2 sequences from the state of Rio Grande do Norte, Brazil, were retrieved from GISAID and subjected to cluster analysis. Immunoinformatics were used to predict T- and B-cell epitopes, followed by simulation to estimate either pro- or anti-inflammatory responses and correlate with circulating variants. From March 2020 to June 2022, Rio Grande do Norte reported 579,931 COVID-19 cases with a 1.4% fatality rate across three major waves: May-Sept 2020, Feb-Aug 2021, and Jan-Mar 2022. Cluster 0 variants (wild type strain, Zeta) were prevalent in the first wave and Delta in the latter half of 2021, featuring fewer unique epitopes. Cluster 1 (Gamma [P1]) dominated the first half of 2021. Late 2021 had Clusters 2 (Omicron) and 3 (Omicron sublineages) with the most unique epitopes, while Cluster 4 (Delta sublineages) emerged in the second half of 2021 with fewer unique epitopes. Cluster 1 epitopes showed a high pro-inflammatory propensity, while others exhibited a balanced cytokine induction. The clustering method effectively identified Spike groups that may contribute to immune evasion and clinical presentation, and explain in part the clinical outcome. IMPORTANCEIdentification of epitopes of emerging or endemic pathogens is of importance to estimate population responses and predict clinical outcomes and contribute to vaccine improvement. In the case of SARS-CoV-2, the virus within 6 months of circulation transitioned from the wild-type to novel variants leading to distinct clinical outcomes. Immunoinformatics analysis of viral epitopes of isolates from the Brazilian state of Rio Grande do Norte was performed using a clustering method. This analysis aimed to clarify how the introduction of novel variants in a population characterized by high infection and/or vaccination rates resulted in immune evasion and distinct clinical disease. Our analysis showed that the epitope profiles of each variant explained the respective potential for cytokine production, including the variants that were more likely to cause cytokine storms. Finally, it serves as a mean to explain the multi-wave patterns observed during SARS-CoV-2 pandemics.

microbiology↗