Mutations in glioblastoma proteins do not disrupt epitope presentation and recognition, maintaining a specific CD8 T cell immune response potential.

Antigen-specific cytotoxic CD8 T cells are extremely effective in controlling tumor growth and have been the focus of immunotherapy approaches. We leverage in silico tools to investigate whether the occurrence of mutations in proteins previously described as immunogenic and highly expressed by glioblastoma multiforme (GBM), such as Epidermal Growth Factor Receptor (EGFR), Isocitrate Dehydrogenase 1 (IDH1), Phosphatase and Tensin homolog (PTEN) and Tumor Protein 53 (TP53), may be contributing to the differential presentation of immunogenic epitopes. We recovered Class I MHC binding information from wild-type and mutated proteins using the Immune Epitope Database (IEDB). After that, we built peptide-MHC (pMHC-I) models in HLA-arena, followed by hierarchical clustering analysis based on electrostatic surface features from each complex. We identified point mutations that are determinants for the presentation of a set of peptides from TP53 protein. We point to structural features in the pMHC-I complexes of wild-type and mutated peptides, which may play a role in the recognition of CD8 T cells. To further explore these features, we performed 100 ns molecular dynamics simulations for the peptide pairs (wt/mut) selected. In pursuit of novel therapeutic targets for GBM treatment, we selected peptides where our predictive results indicated that mutations would not disrupt epitope presentation, thereby maintaining a specific CD8 T cell immune response. These peptides hold potential for future GBM interventions, including peptide-based or mRNA vaccine development applications.

Association between TNF-α and IFN-γ levels and severity of acute viral bronchiolitis.

Acute bronchiolitis caused by the respiratory syncytial virus triggers an inflammatory response with the production and release of several pro-inflammatory cytokines. Evidence suggests that their levels are associated with the severity of the infection. This systematic review and meta-analysis aim to assess whether the levels of TNF-α and IFN-γ are associated with the severity of acute viral bronchiolitis. We searched MEDLINE libraries (via PUBMED), EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL), Scientific Electronic Library Online (SciELO), Latin American Caribbean Health Sciences Literature (LILACS), Cumulative Index to Nursing and Allied Health Literature (CINAHL), Web of Science, and the gray literature through April 2020. Random effect models were used for general and subgroup analysis. In total, six studies were included with a total of 744 participants. The mean TNF-α levels between the severe group did not differ from the control group 0.14 (95% CI: -0.53 to 0.82, I2 = 91%, p < 0.01); the heterogeneity was high. The results remained insignificant when the analyses were performed including only studies with high quality 0.25 (95% CI: -0.46 to 0.96, I2 = 92%, p < 0.01) I2 = 95%, p = 0.815), when TNF-α was nasal 0.60 (95% CI: -0.49 to 1.69), I2 = 94%, p < 0.01), or serum -0.08 (95% CI: -0.48 to 0.31), I2 = 29%, p = 0.24). In the analysis of studies measuring IFN-γ, there was also no significance of -0.67 (95% CI: -1.56 to 0.22, I2 = 76%, p = 0.04). In conclusion, this meta-analysis suggests that the most severe patients do not have different mean TNF-α and IFN-γ values ​than patients with mild disease, but the heterogeneity of the studies was high. Supplemental data for this article is available online at https://doi.org/10.1080/08830185.2021.1889534.

Large-Scale Structure-Based Screening of Potential T Cell Cross-Reactivities Involving Peptide-Targets From BCG Vaccine and SARS-CoV-2.

Although not being the first viral pandemic to affect humankind, we are now for the first time faced with a pandemic caused by a coronavirus. The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has been responsible for the COVID-19 pandemic, which caused more than 4.5 million deaths worldwide. Despite unprecedented efforts, with vaccines being developed in a record time, SARS-CoV-2 continues to spread worldwide with new variants arising in different countries. Such persistent spread is in part enabled by public resistance to vaccination in some countries, and limited access to vaccines in other countries. The limited vaccination coverage, the continued risk for resistant variants, and the existence of natural reservoirs for coronaviruses, highlight the importance of developing additional therapeutic strategies against SARS-CoV-2 and other coronaviruses. At the beginning of the pandemic it was suggested that countries with Bacillus Calmette-Guérin (BCG) vaccination programs could be associated with a reduced number and/or severity of COVID-19 cases. Preliminary studies have provided evidence for this relationship and further investigation is being conducted in ongoing clinical trials. The protection against SARS-CoV-2 induced by BCG vaccination may be mediated by cross-reactive T cell lymphocytes, which recognize peptides displayed by class I Human Leukocyte Antigens (HLA-I) on the surface of infected cells. In order to identify potential targets of T cell cross-reactivity, we implemented an in silico strategy combining sequence-based and structure-based methods to screen over 13,5 million possible cross-reactive peptide pairs from BCG and SARS-CoV-2. Our study produced (i) a list of immunogenic BCG-derived peptides that may prime T cell cross-reactivity against SARS-CoV-2, (ii) a large dataset of modeled peptide-HLA structures for the screened targets, and (iii) new computational methods for structure-based screenings that can be used by others in future studies. Our study expands the list of BCG peptides potentially involved in T cell cross-reactivity with SARS-CoV-2-derived peptides, and identifies multiple high-density "neighborhoods" of cross-reactive peptides which could be driving heterologous immunity induced by BCG vaccination, therefore providing insights for future vaccine development efforts.

Novel frameshift variant of the CFTR gene: S511Lfs*2 from phenotype to molecular predictions.

Cystic fibrosis (CF) is a genetic disease caused by variants in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. There are over 2,000 different pathogenic and non-pathogenic variants described in association with a broad clinical heterogeneity. In this work, we identified a novel variant S511Lfs*2 in CFTR gene that has not been reported in patients with CF. The patient was a female genotyped with c.1000C>T (legacy name: R334W) variant (pathogenic, CF-causing) and the novel variant (S511Lfs*2). We verified the amino acid sequence, the protein structure, and predicted the pathogenicity employing computational analysis. Our findings showed that S511Lfs*2 is a frameshift variant and suggest that it is associated with severe CF phenotype, as it leads to a lack of CFTR protein synthesis, and consequently the loss of its functional activity.

DockTope: a Web-based tool for automated pMHC-I modelling.

The immune system is constantly challenged, being required to protect the organism against a wide variety of infectious pathogens and, at the same time, to avoid autoimmune disorders. One of the most important molecules involved in these events is the Major Histocompatibility Complex class I (MHC-I), responsible for binding and presenting small peptides from the intracellular environment to CD8(+) T cells. The study of peptide:MHC-I (pMHC-I) molecules at a structural level is crucial to understand the molecular mechanisms underlying immunologic responses. Unfortunately, there are few pMHC-I structures in the Protein Data Bank (PDB) (especially considering the total number of complexes that could be formed combining different peptides), and pMHC-I modelling tools are scarce. Here, we present DockTope, a free and reliable web-based tool for pMHC-I modelling, based on crystal structures from the PDB. DockTope is fully automated and allows any researcher to construct a pMHC-I complex in an efficient way. We have reproduced a dataset of 135 non-redundant pMHC-I structures from the PDB (Cα RMSD below 1 Å). Modelling of pMHC-I complexes is remarkably important, contributing to the knowledge of important events such as cross-reactivity, autoimmunity, cancer therapy, transplantation and rational vaccine design.

CrossTope: a curate repository of 3D structures of immunogenic peptide: MHC complexes.

The CrossTope is a highly curate repository of three-dimensional structures of peptide:major histocompatibility complex (MHC) class I complexes (pMHC-I). The complexes hosted by this databank were obtained in protein databases and by large-scale in silico construction of pMHC-I structures, using a new approach developed by our group. At this moment, the database contains 182 'non-redundant' pMHC-I complexes from two human and two murine alleles. A web server provides interface for database query. The user can download (i) structure coordinate files and (ii) topological and charges distribution maps images from the T-cell receptor-interacting surface of pMHC-I complexes. The retrieved structures and maps can be used to cluster similar epitopes in cross-reactivity approaches, to analyse viral escape mutations in a structural level or even to improve the immunogenicity of tumour antigens. Database URL: http://www.crosstope.com.br.

Immunogenic epitopes of Hantaviruses' N protein are restricted to conserved regions.

The Bunyaviridae virus family is composed by five genera, of which the Hantavirus genus is one of the most important representatives. Occasionally, these viruses can be transmitted to humans, giving rise to severe diseases that present high mortality rates. We analyzed the amino acid sequences of the nucleocapsid (N) proteins of 34 different hantaviruses to investigate the potential mechanisms involved in immunogenicity against hantaviruses. Immunogenic epitopes described in the literature through experimental analyses for Sin Nombre (SNV), Puumala (PUUV), and Hantaan (HTNV) viruses' species were retrieved. We identified and characterized the regions believed to be responsible for the induction of immune response in hosts. We found that N protein epitopes described in the literature for PUUV, SNV and HTNV viruses are all located in highly conserved regions of the protein. The high conservation of these regions suggests that a cross-reactive immune response among different hantaviruses can be induced.