Biology subjects

Oliveira, J. I. N.

Publications and source records attributed to Oliveira, J. I. N..

3 recordsLinked to original sources

bioRxiv2024

Prevalence of Key Spike Protein Mutations and Their Limited Effect on COVID-19 Clinical Manifestations in Sylhet, Bangladesh

SARS-CoV-2 is the virus responsible for the COVID-19 pandemic, which has spread rapidly around the world and had a significant impact on public health and the economy worldwide. This study investigated the correlation between SARS-CoV-2 spike protein mutations, clinical outcomes and patient demographics in the Sylhet region of Bangladesh. We looked at the full genome sequences of 37 SARS-CoV-2 samples that were collected between January and June 2020. Specifically, we looked at five major spike protein mutations: D614G, A570D, D1118H, A222V, and P681R. The D614G mutation was the most prevalent (94.6%), followed by A570D and D1118H (both 32.4%), A222V (29.7%), and P681R (13.5%). Despite their high prevalence, we found no statistically significant associations between these mutations and clinical outcomes or demographic variables, except for possible trends for the P681R mutation. We found that age played a decisive role in recovery from COVID-19, with older patients exhibiting slower recovery rates. In terms of predictors of outcome, gender differences were observed: clinical symptoms and viral genetic mutations were more influential for men, while age and disease progression were more important for women. Common nucleotide substitutions (A23403G, C3037T, and C14408T) associated with European strains were identified, suggesting possible routes of transmission. This study contributes to our understanding of the genetics, clinical manifestations and epidemiology of SARS-CoV-2 in the Sylhet region and emphasizes the need for continuous genomic surveillance and adaptive public health strategies.

microbiology↗

bioRxiv2023

Strain-specific evolution and host-specific regulation of transposable elements in the model plant symbiont Rhizophagus irregularis

Transposable elements (TEs) are repetitive DNA that can create variability in genome structure and regulation. The genome of Rhizophagus irregularis, a widely studied arbuscular mycorrhizal fungus (AMF), comprises approximately 50% repetitive sequences that include transposable elements. Despite their abundance, two-thirds of TEs remain unclassified, and their regulation among AMF life-stages remains unknown. Here, we aimed to improve our understanding of TE diversity and regulation in this model species by curating repeat datasets obtained from chromosome-level assemblies and by investigating their expression across multiple conditions. Our analyses uncovered new TE superfamilies and families in this model symbiont and revealed significant differences in how these sequences evolve both within and between R. irregularis strains. With this curated TE annotation, we also detected that the number of upregulated TE families in colonized roots is four times higher than in the extraradical mycelium, and their overall expression differs depending on the plant host. This work provides a fine-scale view of TE diversity and evolution in model plant symbionts and highlights their transcriptional dynamism and specificity during host-microbe interactions. We also provide Hidden Markov Model profiles of TE domains for future manual curation of uncharacterized sequences (https://github.com/jordana-olive/TE-manual-curation/tree/main).

genomics↗

bioRxiv2023

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↗