Combining different bacteria in vaccine formulations enhances the chance for antiviral cross-reactive immunity: a detailed in silico analysis for influenza A virus.

Bacteria are well known to provide heterologous immunity against viral infections through various mechanisms including the induction of innate trained immunity and adaptive cross-reactive immunity. Cross-reactive immunity from bacteria to viruses is responsible for long-term protection and yet its role has been downplayed due the difficulty of determining antigen-specific responses. Here, we carried out a systematic evaluation of the potential cross-reactive immunity from selected bacteria known to induce heterologous immunity against various viruses causing recurrent respiratory infections. The bacteria selected in this work were Bacillus Calmette Guerin and those included in the poly-bacterial preparation MV130: Streptococcus pneumoniae, Staphylococcus aureus, Staphylococcus epidermidis, Klebisella pneumoniae, Branhamella catarrhalis and Haemophilus influenzae. The virus included influenza A and B viruses, human rhinovirus A, B and C, respiratory syncytial virus A and B and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Through BLAST searches, we first identified the shared peptidome space (identity ≥ 80%, in at least 8 residues) between bacteria and viruses, and subsequently predicted T and B cell epitopes within shared peptides. Interestingly, the potential epitope spaces shared between bacteria in MV130 and viruses are non-overlapping. Hence, combining diverse bacteria can enhance cross-reactive immunity. We next analyzed in detail the cross-reactive T and B cell epitopes between MV130 and influenza A virus. We found that MV130 contains numerous cross-reactive T cell epitopes with high population protection coverage and potentially neutralizing B cell epitopes recognizing hemagglutinin and matrix protein 2. These results contribute to explain the immune enhancing properties of MV130 observed in the clinic against respiratory viral infections.

Corrigendum: Combining different bacteria in vaccine formulations enhances the chance for antiviral cross-reactive immunity: a detailed in silico analysis for influenza A virus.

[This corrects the article DOI: 10.3389/fimmu.2023.1235053.].

Enhancing Regulatory T Cells to Treat Inflammatory and Autoimmune Diseases.

Regulatory T cells (Tregs) control immune responses and are essential to maintain immune homeostasis and self-tolerance. Hence, it is no coincidence that autoimmune and chronic inflammatory disorders are associated with defects in Tregs. These diseases have currently no cure and are treated with palliative drugs such as immunosuppressant and immunomodulatory agents. Thereby, there is a great interest in developing medical interventions against these diseases based on enhancing Treg cell function and numbers. Here, we give an overview of Treg cell ontogeny and function, paying particular attention to mucosal Tregs. We review some notable approaches to enhance immunomodulation by Tregs with therapeutic purposes including adoptive Treg cell transfer therapy and discuss relevant clinical trials for inflammatory bowel disease. We next introduce ways to expand mucosal Tregs in vivo using microbiota and dietary products that have been the focus of clinical trials in various autoimmune and chronic-inflammatory diseases.

Vaccine Design: An Introduction.

Vaccines are the most successful and cost-effective medical interventions available to fight infectious diseases. They consist of biological preparations that are capable of stimulating the immune system to confer protective immunity against a particular harmful pathogen/agent. Vaccine design and development have evolved through the years. Early vaccines were obtained with little implementation of technology and in the absence of fundamental knowledge, representing a pure feat of human ingenuity. In contrast, modern vaccine development takes advantage of advances in technology and in our enhanced understanding of the immune system and host-pathogen interactions. Moreover, vaccine design has found novel applications beyond the prophylactic arena and there is an increasing interest in designing vaccines to treat human ailments like cancer and chronic inflammatory diseases. In this chapter, we focus on prophylactic vaccines against infectious diseases, providing an overview on immunology principles underlying immunization and on how vaccines work and are designed.

EPIPOX: A Resource Facilitating Epitope-Vaccine Design Against Human Pathogenic Orthopoxviruses.

EPIPOX is a specialized online resource intended to facilitate the design of epitope-based vaccines against orthopoxviruses. EPIPOX is built upon a collection of T cell epitopes that are shared by eight pathogenic orthopoxviruses, including variola minor and major strains, monkeypox, cowpox, and vaccinia viruses. In EPIPOX, users can select T cell epitopes attending to the predicted binding to distinct major histocompatibility molecules (MHC) and according to various features that may have an impact on epitope immunogenicity. Among others, EPIPOX allows to discern epitopes by their structural location in the virion and the temporal expression of the counterpart antigens. Overall, the annotations in EPIPOX are optimized to facilitate the rational design of T cell epitope-based vaccines. In this chapter, we describe the main features of EPIPOX and exemplify its use, retrieving orthopoxvirus-specific T cell epitopes with features set to enhance their immunogenicity. EPIPOX is available for free public use at http://bio.med.ucm.es/epipox/ .

Prediction of TAP Transport of Peptides with Variable Length Using TAPREG.

CD8 T cells recognize short peptides, more frequently of nine residues, presented by class I major histocompatibility complex (MHC I) molecules in the cell surface of antigen-presenting cells. These epitope peptides are loaded onto MHC I molecules in the endoplasmic reticulum, where they are shuttled from the cytosol by the transporter associated with antigen processing (TAP) as such or as N-terminal extended precursors of up to 16 residues. In this chapter, we describe the use of TAPREG, a tool for predicting TAP binding affinity that has been enhanced to identify potential CD8 T cell epitope precursors transported by TAP. TAPREG is available for free public use at http://imed.med.ucm.es/Tools/tapreg/ .

Expression of the phagocytic receptors αMß2 and αXß2 is controlled by RIAM, VASP and Vinculin in neutrophil-differentiated HL-60 cells.

Activation of the integrin phagocytic receptors CR3 (αMß2, CD11b/CD18) and CR4 (αXß2, CD11c/CD18) requires Rap1 activation and RIAM function. RIAM controls integrin activation by recruiting Talin to ß2 subunits, enabling the Talin-Vinculin interaction, which in term bridges integrins to the actin-cytoskeleton. RIAM also recruits VASP to phagocytic cups and facilitates VASP phosphorylation and function promoting particle internalization. Using a CRISPR-Cas9 knockout approach, we have analyzed the requirement for RIAM, VASP and Vinculin expression in neutrophilic-HL-60 cells. All knockout cells displayed abolished phagocytosis that was accompanied by a significant and specific reduction in ITGAM (αM), ITGAX (αX) and ITGB2 (ß2) mRNA, as revealed by RT-qPCR. RIAM, VASP and Vinculin KOs presented reduced cellular F-actin content that correlated with αM expression, as treatment with the actin filament polymerizing and stabilizing drug jasplakinolide, partially restored αM expression. In general, the expression of αX was less responsive to jasplakinolide treatment than αM, indicating that regulatory mechanisms independent of F-actin content may be involved. The Serum Response Factor (SRF) was investigated as the potential transcription factor controlling αMß2 expression, since its coactivator MRTF-A requires actin polymerization to induce transcription. Immunofluorescent MRTF-A localization in parental cells was primarily nuclear, while in knockouts it exhibited a diffuse cytoplasmic pattern. Localization of FHL-2 (SRF corepressor) was mainly sub-membranous in parental HL-60 cells, but in knockouts the localization was disperse in the cytoplasm and the nucleus, suggesting RIAM, VASP and Vinculin are required to maintain FHL-2 close to cytoplasmic membranes, reducing its nuclear localization and inhibiting its corepressor activity. Finally, reexpression of VASP in the VASP knockout resulted in a complete reversion of the phenotype, as knock-ins restored αM expression. Taken together, our results suggest that RIAM, VASP and Vinculin, are necessary for the correct expression of αMß2 and αXß2 during neutrophilic differentiation in the human promyelocytic HL-60 cell line, and strongly point to an involvement of these proteins in the acquisition of a phagocytic phenotype.

Prediction of B cell epitopes in proteins using a novel sequence similarity-based method.

Prediction of B cell epitopes that can replace the antigen for antibody production and detection is of great interest for research and the biotech industry. Here, we developed a novel BLAST-based method to predict linear B cell epitopes. To that end, we generated a BLAST-formatted database upon a dataset of 62,730 known linear B cell epitope sequences and considered as a B cell epitope any peptide sequence producing ungapped BLAST hits to this database with identity ≥ 80% and length ≥ 8. We examined B cell epitope predictions by this method in tenfold cross-validations in which we considered various types of non-B cell epitopes, including 62,730 peptide sequences with verified negative B cell assays. As a result, we obtained values of accuracy, specificity and sensitivity of 72.54 ± 0.27%, 81.59 ± 0.37% and 63.49 ± 0.43%, respectively. In an independent dataset incorporating 503 B cell epitopes, this method reached accuracy, specificity and sensitivity of 74.85%, 99.20% and 50.50%, respectively, outperforming state-of-the-art methods to predict linear B cell epitopes. We implemented this BLAST-based approach to predict B cell epitopes at http://imath.med.ucm.es/bepiblast .

Resilience of Spike-Specific Immunity Induced by COVID-19 Vaccines against SARS-CoV-2 Variants.

The outbreak of SARS-CoV-2 leading to the declaration of the COVID-19 global pandemic has led to the urgent development and deployment of several COVID-19 vaccines. Many of these new vaccines, including those based on mRNA and adenoviruses, are aimed to generate neutralizing antibodies against the spike glycoprotein, which is known to bind to the receptor angiotensin converting enzyme 2 (ACE2) in host cells via the receptor-binding domain (RBD). Antibodies binding to this domain can block the interaction with the receptor and prevent viral entry into the cells. Additionally, these vaccines can also induce spike-specific T cells which could contribute to providing protection against the virus. However, the emergence of new SARS-CoV-2 variants can impair the immunity generated by COVID-19 vaccines if mutations occur in cognate epitopes, precluding immune recognition. Here, we evaluated the chance of five SARS-CoV-2 variants of concern (VOCs), Alpha, Beta, Gamma, Delta and Omicron, to escape spike-specific immunity induced by vaccines. To that end, we examined the impact of the SARS-CoV-2 variant mutations on residues located on experimentally verified spike-specific epitopes, deposited at the Immune Epitope Database, that are targeted by neutralizing antibodies or recognized by T cells. We found about 300 of such B cell epitopes, which were largely overlapping, and could be grouped into 54 B cell epitope clusters sharing ≥ 7 residues. Most of the B cell epitope clusters map in the RBD domain (39 out of 54) and 20%, 50%, 37%, 44% and 57% of the total are mutated in SARS-CoV-2 Alpha, Beta, Gamma, Delta and Omicron variants, respectively. We also found 234 experimentally verified CD8 and CD4 T cell epitopes that were distributed evenly throughout the spike protein. Interestingly, in each SARS-CoV-2 VOC, over 87% and 79% of CD8 and CD4 T cell epitopes, respectively, are not mutated. These observations suggest that SARS-CoV-2 VOCs-particularly the Omicron variant-may be prone to escape spike-specific antibody immunity, but not cellular immunity, elicited by COVID-19 vaccines.

Molecular Basis for Global Incidence of Pemphigoid Diseases and Differences in Phenotypes.

Pemphigoid (Pg) diseases are a group of potentially fatal autoimmune mucocutaneous diseases. They have different clinical phenotypes, involving only the skin or multiple mucous membranes. They occur globally and frequently affect the elderly. The common marker among all variants is the presence of autoantibodies targeting the dermal-epidermal or mucosal-submucosal junctions, or basement membrane zone (BMZ). Four target antigens in the BMZ were studied. These included BPAG1, BPAG2 and subunits of α6 and ß4 human integrins. Our objective was to find a molecular basis for the global incidence of Pg diseases and a mechanism that will explain the vast differences in clinical phenotypes and outcomes. All the variants of Pg that were analyzed had a statistically significant association with HLA-DQß1*03:01 in ten countries on four continents. This explains the reason for global incidence. Prediction models discovered multiple peptides in each of the four antigens that serve as T cell epitopes. These T cell epitopes were shown to bind to HLA-DQß1*03:01. In addition, structure modelling demonstrated the peptide-HLA complex bound to the T cell receptor. These autoreactive T cells would stimulate B cells to produce specific anti-BMZ autoantibodies. Anti-BMZ autoantibodies with different specificities will produce different phenotypes, which will account for involvement of different tissues and organs in different molecules. The contribution this study makes is that it provides a molecular basis of why a similar disease occurs in different racial groups. Furthermore, it provides the basis for the production of autoantibodies with different specificities, which resultantly produces different phenotypes.

A multi-step and multi-scale bioinformatic protocol to investigate potential SARS-CoV-2 vaccine targets.

The COVID-19 pandemic has highlighted the need to come out with quick interventional solutions that can now be obtained through the application of different bioinformatics software to actively improve the success rate. Technological advances in fields such as computer modeling and simulation are enriching the discovery, development, assessment and monitoring for better prevention, diagnosis, treatment and scientific evidence generation of specific therapeutic strategies. The combined use of both molecular prediction tools and computer simulation in the development or regulatory evaluation of a medical intervention, are making the difference to better predict the efficacy and safety of new vaccines. An integrated bioinformatics pipeline that merges the prediction power of different software that act at different scales for evaluating the elicited response of human immune system against every pathogen is proposed. As a working example, we applied this problem solving protocol to predict the cross-reactivity of pre-existing vaccination interventions against SARS-CoV-2.

Immune Tolerance in the Oral Mucosa.

The oral mucosa is a site of intense immune activity, where a large variety of immune cells meet to provide a first line of defense against pathogenic organisms. Interestingly, the oral mucosa is exposed to a plethora of antigens from food and commensal bacteria that must be tolerated. The mechanisms that enable this tolerance are not yet fully defined. Many works have focused on active immune mechanisms involving dendritic and regulatory T cells. However, epithelial cells also make a major contribution to tolerance by influencing both innate and adaptive immunity. Therefore, the tolerogenic mechanisms concurring in the oral mucosa are intertwined. Here, we review them systematically, paying special attention to the role of oral epithelial cells.

Activated gut-homing CD8+ T cells for coeliac disease diagnosis on a gluten-free diet.

BACKGROUND: The diagnosis of coeliac disease (CD) in individuals that have started a gluten-free diet (GFD) without an adequate previous diagnostic work-out is a challenge. Several immunological assays such as IFN-γ ELISPOT have been developed to avoid the need of prolonged gluten challenge to induce the intestinal damage. We aimed to evaluate the diagnostic accuracy of activated gut-homing CD8+ and TCRγδ+ T cells in blood after a 3-day gluten challenge and to compare it with the performance of IFN-γ ELISPOT in a HLA-DQ2.5 subsample. METHODS: A total of 22 CD patients and 48 non-CD subjects, all of them following a GFD, underwent a 3-day 10-g gluten challenge. The percentage of two T cell subsets (CD8+ CD103+ ß7hi CD38+/total CD8+ and TCRγδ+ CD103+ ß7hi CD38+/total TCRγδ+) in fresh peripheral blood drawn baseline and 6 days after the challenge was determined by flow cytometry. IFN-γ ELISPOT assays were also performed in HLA-DQ2.5 participants. ROC curve analysis was used to assess the diagnostic performance of the CD8+ T cell response and IFN-γ ELISPOT. RESULTS: Significant differences between the percentage of the two studied subsets of CD8+ and TCRγδ+ cells at days 0 and 6 were found only when considering CD patients (p < 10-3 vs. non-CD subjects). Measuring activated CD8+ T cells provided accurate CD diagnosis with 95% specificity and 97% sensitivity, offering similar results than IFN-γ ELISPOT. CONCLUSIONS: The results provide a highly accurate blood test for CD diagnosis in patients on a GFD of easy implementation in daily clinical practice.

BCEPS: A Web Server to Predict Linear B Cell Epitopes with Enhanced Immunogenicity and Cross-Reactivity.

Prediction of linear B cell epitopes is of interest for the production of antigen-specific antibodies and the design of peptide-based vaccines. Here, we present BCEPS, a web server for predicting linear B cell epitopes tailored to select epitopes that are immunogenic and capable of inducing cross-reactive antibodies with native antigens. BCEPS implements various machine learning models trained on a dataset including 555 linearized conformational B cell epitopes that were mined from antibody-antigen protein structures. The best performing model, based on a support vector machine, reached an accuracy of 75.38% ± 5.02. In an independent dataset consisting of B cell epitopes retrieved from the Immune Epitope Database (IEDB), this model achieved an accuracy of 67.05%. In BCEPS, predicted epitopes can be ranked according to properties such as flexibility, accessibility and hydrophilicity, and with regard to immunogenicity, as judged by their predicted presentation by MHC II molecules. BCEPS also detects if predicted epitopes are located in ectodomains of membrane proteins and if they possess N-glycosylation sites hindering antibody recognition. Finally, we exemplified the use of BCEPS in the SARS-CoV-2 Spike protein, showing that it can identify B cell epitopes targeted by neutralizing antibodies.

Characterization of Conserved and Promiscuous Human Rhinovirus CD4 T Cell Epitopes.

Human rhinovirus (RV) is the most common cause of upper respiratory infections and exacerbations of asthma. In this work, we selected 14 peptides (6 from RV A and 8 from RV C) encompassing potential CD4 T cell epitopes. Peptides were selected for being highly conserved in RV A and C serotypes and predicted to bind to multiple human leukocyte antigen class II (HLA II) molecules. We found positive T cell recall responses by interferon gamma (IFNγ)-ELISPOT assays to eight peptides, validating seven of them (three from RV A and four from RV C) as CD4 T cell epitopes through intracellular cytokine staining assays. Additionally, we verified their promiscuous binding to multiple HLA II molecules by quantitative binding assays. According to their experimental HLA II binding profile, the combination of all these seven epitopes could be recognized by >95% of the world population. We actually determined IFNγ responses to a pool encompassing these CD4 T cell epitopes by intracellular cytokine staining, finding positive responses in 29 out of 30 donors. The CD4 T cell epitopes identified in this study could be key to monitor RV infections and to develop peptide-based vaccines against most RV A and C serotypes.

Molecular design of the γδT cell receptor ectodomain encodes biologically fit ligand recognition in the absence of mechanosensing.

High-acuity αßT cell receptor (TCR) recognition of peptides bound to major histocompatibility complex molecules (pMHCs) requires mechanosensing, a process whereby piconewton (pN) bioforces exert physical load on αßTCR-pMHC bonds to dynamically alter their lifetimes and foster digital sensitivity cellular signaling. While mechanotransduction is operative for both αßTCRs and pre-TCRs within the αßT lineage, its role in γδT cells is unknown. Here, we show that the human DP10.7 γδTCR specific for the sulfoglycolipid sulfatide bound to CD1d only sustains a significant load and undergoes force-induced structural transitions when the binding interface-distal γδ constant domain (C) module is replaced with that of αß. The chimeric γδ-αßTCR also signals more robustly than does the wild-type (WT) γδTCR, as revealed by RNA-sequencing (RNA-seq) analysis of TCR-transduced Rag2-/- thymocytes, consistent with structural, single-molecule, and molecular dynamics studies reflective of γδTCRs as mediating recognition via a more canonical immunoglobulin-like receptor interaction. Absence of robust, force-related catch bonds, as well as γδTCR structural transitions, implies that γδT cells do not use mechanosensing for ligand recognition. This distinction is consonant with the fact that their innate-type ligands, including markers of cellular stress, are expressed at a high copy number relative to the sparse pMHC ligands of αßT cells arrayed on activating target cells. We posit that mechanosensing emerged over ∼200 million years of vertebrate evolution to fulfill indispensable adaptive immune recognition requirements for pMHC in the αßT cell lineage that are unnecessary for the γδT cell lineage mechanism of non-pMHC ligand detection.

Prediction of unconventional protein secretion by exosomes.

MOTIVATION: In eukaryotes, proteins targeted for secretion contain a signal peptide, which allows them to proceed through the conventional ER/Golgi-dependent pathway. However, an important number of proteins lacking a signal peptide can be secreted through unconventional routes, including that mediated by exosomes. Currently, no method is available to predict protein secretion via exosomes. RESULTS: Here, we first assembled a dataset including the sequences of 2992 proteins secreted by exosomes and 2961 proteins that are not secreted by exosomes. Subsequently, we trained different random forests models on feature vectors derived from the sequences in this dataset. In tenfold cross-validation, the best model was trained on dipeptide composition, reaching an accuracy of 69.88% ± 2.08 and an area under the curve (AUC) of 0.76 ± 0.03. In an independent dataset, this model reached an accuracy of 75.73% and an AUC of 0.840. After these results, we developed ExoPred, a web-based tool that uses random forests to predict protein secretion by exosomes. CONCLUSION: ExoPred is available for free public use at http://imath.med.ucm.es/exopred/ . Datasets are available at http://imath.med.ucm.es/exopred/datasets/ .

Deconvoluting the T Cell Response to SARS-CoV-2: Specificity Versus Chance and Cognate Cross-Reactivity.

SARS-CoV-2 infection takes a mild or clinically inapparent course in the majority of humans who contract this virus. After such individuals have cleared the virus, only the detection of SARS-CoV-2-specific immunological memory can reveal the exposure, and hopefully the establishment of immune protection. With most viral infections, the presence of specific serum antibodies has provided a reliable biomarker for the exposure to the virus of interest. SARS-CoV-2 infection, however, does not reliably induce a durable antibody response, especially in sub-clinically infected individuals. Consequently, it is plausible for a recently infected individual to yield a false negative result within only a few months after exposure. Immunodiagnostic attention has therefore shifted to studies of specific T cell memory to SARS-CoV-2. Most reports published so far agree that a T cell response is engaged during SARS-CoV-2 infection, but they also state that in 20-81% of SARS-CoV-2-unexposed individuals, T cells respond to SARS-CoV-2 antigens (mega peptide pools), allegedly due to T cell cross-reactivity with Common Cold coronaviruses (CCC), or other antigens. Here we show that, by introducing irrelevant mega peptide pools as negative controls to account for chance cross-reactivity, and by establishing the antigen dose-response characteristic of the T cells, one can clearly discern between cognate T cell memory induced by SARS-CoV-2 infection vs. cross-reactive T cell responses in individuals who have not been infected with SARS-CoV-2.

CERI, CEFX, and CPI: Largely Improved Positive Controls for Testing Antigen-Specific T Cell Function in PBMC Compared to CEF.

Monitoring antigen-specific T cell immunity relies on functional tests that require T cells and antigen presenting cells to be uncompromised. Drawing of blood, its storage and shipment from the clinical site to the test laboratory, and the subsequent isolation, cryopreservation and thawing of peripheral blood mononuclear cells (PBMCs) before the actual test is performed can introduce numerous variables that may jeopardize the results. Therefore, no T cell test is valid without assessing the functional fitness of the PBMC being utilized. This can only be accomplished through the inclusion of positive controls that actually evaluate the performance of the antigen-specific T cell and antigen presenting cell (APC) compartments. For Caucasians, CEF peptides have been commonly used to this extent. Moreover, CEF peptides only measure CD8 cell functionality. We introduce here universal CD8+ T cell positive controls without any racial bias, as well as positive controls for the CD4+ T cell and APC compartments. In summary, we offer new tools and strategies for the assessment of PBMC functional fitness required for reliable T cell immune monitoring.