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Background: The immunopeptidome is constantly monitored by T cells to detect foreign or aberrant HLA peptides. It is highly dynamic and reflects the current cellular state, enabling the immune system to recognize abnormal cellular conditions, such as those present in cancer cells. To precisely determine how changes in cellular processes, such as those induced by drug treatment, affect the immunopeptidome, quantitative immunopeptidomics approaches are essential. Methods: To meet this need, we developed a pulsed SILAC-based method for quantitative immunopeptidomics. Metabolic labeling with lysine, arginine, and leucine enabled isotopic labeling of nearly all HLA peptides across all allotypes (> 90% on average). We established a data analysis workflow that integrates the de novo sequencing-based tool Peptide-PRISM for comprehensive HLA peptide identification with MaxQuant for accurate quantification. Results: We employed this strategy to explore the modulation of the immunopeptidome upon MAPK pathway inhibition (MAPKi) and to investigate alterations associated with early cellular responses to inhibitor treatment and acquired resistance to MAPKi. Our analyses demonstrated significant changes in the immunopeptidome early during MAPKi treatment and in the resistant state. Moreover, we identified putative tumor-specific cryptic HLA peptides linked to these processes that might represent exploitable targets for cancer immunotherapy. Conclusions: We have developed a new mass spectrometric approach that allowed us to investigate the effects of common MAPK inhibitors on the immunopeptidome of melanoma cells. This finally led to the discovery of new potential targets for cancer immunotherapy. [ABSTRACT FROM AUTHOR]

Understanding the evolutionary patterns and geographic spread of SARS-CoV-2 variants, particularly Omicron, is essential for effective public health responses. This study focused on the genomic analysis of the Omicron variant in Cordoba, Argentina from 2021 to 2022. Phylogenetic analysis revealed the dominant presence of BA.1 and BA.2 lineages, with BA.5 emerging earlier than BA.4, aligning with observations from other regions. Haplotype network analysis showed significant genetic divergence within Omicron samples, forming distinct clusters. In comparison to global datasets, we identified mutations in the Omicron genomes (A27S, Y145D, and L212I) situated within the NTD region of the Spike protein. These mutations, while not widespread globally, showed higher prevalence in our region. Of particular interest were the Y145D and L212I substitutions, previously unreported in Argentina. In silico analysis revealed that both mutations impact the binding affinity of T-cell epitopes to HLA type I and II alleles. Notably, these alleles are among the most common in the Argentinian population, with some associated with protection against and others with susceptibility to SARS-CoV-2 infection. These findings strongly suggest that these prevalent mutations likely influence the immunogenicity of the Spike protein and contribute to immune evasion mechanisms. This study provides valuable insights into the genomic dynamics of the Omicron variant in Cordoba, Argentina and highlights unique mutations with potential implications for COVID-19 vaccines. [ABSTRACT FROM AUTHOR]

Recurrent pregnancy loss (RPL), defined as two or more pregnancy losses before the 24th week of gestation, affects 1%–3% of women worldwide. Approximately, 40% of RPL cases are secondary RPL (sRPL), where women have given birth before facing pregnancy losses. The underlying causes of RPL remain unclear, but immune‐related factors may play a role. Previously, a randomised controlled trial using immunoglobulin (IVIG) in sRPL women with a history of four pregnancy losses performed in our RPL unit did not show significant effects of IVIG treatment overall. Yet, some evidence suggests potential benefits for a subset of sRPL patients. In the cohort used for the randomised controlled trial, we examined the role of maternal HLA class II‐presented fetal HLA‐derived epitopes in sRPL using the predicted indirectly recognisable HLA epitopes (PIRCHE‐II) algorithm. In the placebo group, sRPL mothers with an anti‐HLA antibody response had higher PIRCHE‐II scores when having a live birth compared with sRPL women who experienced another pregnancy loss. This difference was not observed in the IVIG‐treated group. Furthermore, as a proxy for T‐cell memory, the number of overlapping peptides between the two paternal haplotypes in couples having live births without treatment displayed a larger number of overlapping peptides. This effect was primarily driven by class II‐derived peptides. These results suggest that specific combinations of sRPL mothers and fathers, particularly those with an anti‐HLA antibody response, may generate higher PIRCHE‐II scores, which could contribute to successful live births. Understanding these immune interactions may provide insights for personalised diagnostic and therapeutic strategies in sRPL. [ABSTRACT FROM AUTHOR]

With the development of novel vaccine strategies, T-cell epitope-based vaccines have become promising prophylactic and therapeutic tools against infectious diseases that cannot be controlled via traditional vaccines. T-cell epitope-based vaccines leverage specific immunogenic peptides to elicit protective T-cell responses against infectious pathogens. Compared to traditional vaccines, they provide superior efficacy and safety, minimizing the risk of adverse side effects. In this review, we summarized and compared the prediction and identification methods of T-cell epitopes. By integrating bioinformatic prediction and experimental validation, efficient and precise screening of T-cell epitopes can be achieved. Importantly, we delved into the development approaches to diverse T-cell epitope-based vaccines, comparing their merits and demerits, as well as discussing the prevalent challenges and perspectives in their applications. This review offers fresh perspectives for the formulation of safe and efficacious epitope-based vaccines for the devastating diseases against which no vaccines are currently available. [ABSTRACT FROM AUTHOR]

Simple Summary: Dengue fever is one of the major public health issues in tropical and subtropical regions. To prevent infection by the Dengue Virus, the World Health Organization has approved two dengue vaccines, Dengvaxia and TV003/TV005. But, unfortunately, the vaccines face challenges such as lower effectiveness and antibody-dependent enhancement (ADE). To address these concerns, we have designed a new vaccine, PSDV-2, with optimized B- and T-cell epitopes using an in silico approach. This design prioritizes high antigenicity and immunogenicity while minimizing risks such as allergenicity, toxicity, and ADE. In simulations, PSDV-2 bound strongly to immune receptors TLRs 4 and 2 and triggered a strong immune response. Although further testing is needed to confirm the effectiveness and safety of PSDV-2, our design offers a promising alternative option for dengue fever prevention, potentially contributing to an improvement in global health. Dengue virus poses a significant global health challenge, particularly in tropical and subtropical regions. Despite the urgent demand for vaccines in the control of the disease, the two approved vaccines, Dengvaxia and TV003/TV005, there are current questions regarding their effectiveness due to an increased risk of antibody-dependent enhancement (ADE) and reduced protection. These challenges have underscored the need for further development of improved vaccines for Dengue Virus. This study presents a new design using an in silico approach to generate a more effective dengue vaccine. Initially, our design process began with the collection of Dengue polyprotein sequences from 10 representative countries worldwide. And then conserved fragments of viral proteins were retrieved as the bases for epitope screening. The selection of epitopes was then carried out with criteria such as antigenicity, immunogenicity, and binding affinity with MHC molecules, while the exclusion criteria were according to their allergenicity, toxicity, and potential for antibody-dependent enhancement. We then constructed a core antigen with the selected epitopes and linked the outcomes with distinct adjuvant proteins, resulting in three candidate vaccines: PSDV-1, PSDV-2, and PSDV-3. Among these, PSDV-2 was selected for further validation due to its superior physicochemical and structural properties. Extensive simulations demonstrated that PSDV-2 exhibited strong binding to pattern recognition receptors, high stability, and robust immune induction, confirming its potential as a high-quality vaccine candidate. For its recombinant expression, a plasmid was subsequently designed. Our new vaccine design offers a promising additional option for Dengue virus protection. Further experimental validations will be conducted to confirm its protective efficacy and safety. [ABSTRACT FROM AUTHOR]

The E6 and E7 proteins of the high risk human papillomaviruses (HR HPVs) play a key role in the oncogenesis associated with papillomavirus infection. Data on the variability of these proteins are limited, and the factors affecting their variability are still poorly understood. We analyzed the variability of the currently known sequences of the HPV type 16 (HPV16) E6 and E7 proteins, taking into account their geographic origin and year of sample collection, as well as the direction of their evolution in the major geographic regions of the world. All sequences belonging to HPV16 genome fragments encoding the E6 and E7 oncoproteins were downloaded from the NCBI GenBank database on October 6, 2022. Samples were filtered according to the following parameters: the sequence has to include at least one of the two whole open reading frames, and given date of collection, and the country of origin. A total of 3651 full-genome nucleotide sequences encoding the E6 protein and 4578 full-genome nucleotide sequences encoding the E7 protein were sampled. The nucleotide sequences obtained after sampling and alignment were converted to amino acid sequences and analyzed using the MEGA11, R, RStudio, Jmodeltest 2.1.20, BEAST v1.10.4, Fastcov, and Biostrings software. The highest variability in the E6 protein was recorded for amino acid (AA) residues in the positions 17, 21, 32, 85, and 90. The most variable in E7 were aa positions 28, 29, 51, and 77. The samples were divided geographically into five heterogeneous groups as derived from Africa, Europe, America, South-West and South Asia, and South-East Asia. Unique amino acid substitutions (AA-substitutions) in the E6/E7 proteins of HPV16, presumably characteristic to certain ethnic groups, were identified for a number of countries. They weare mainly localized in the sites of known B- and T-cell epitopes and relatively rarely the domains critical for in structure and protein function. The revealed differences in AA-substitutions in different ethnic groups and their colocalization with the clusters of B- and T-cell epitopes suggested their possible relation to the geographical distribution of alleles and haplotypes of the major histocompatibility complex (HLA). This may lead to the recognition of a different set of B- and T-cell epitopes of the virus in different geographic areas, resulting in the regional differences in the direction of epitopic drift. Phylogenetic analysis of the nucleotide sequences encoding the E6 protein of HPV16 revealed a common ancestor, confirmed regional clustering of the E6 protein sequences sharing common AA-substitutions, and identified cases of reversion of individual AA-substitutions when the change of geographical localization. For the E7 protein, such analysis was not possible due to the high sequence homology. Covariance analysis of the pooled of E6 and E7 sequences revealed that there was no associations between amino acid residues in any aa position within E6 or E7 as well as aa positions of E6 and E7 proteins. The data presented here are important for the development of universal therapeutic vaccines against HPV of high carcinogenic risk. [ABSTRACT FROM AUTHOR]

BackgroundThe immunopeptidome is constantly monitored by T cells to detect foreign or aberrant HLA peptides. It is highly dynamic and reflects the current cellular state, enabling the immune system to recognize abnormal cellular conditions, such as those present in cancer cells. To precisely determine how changes in cellular processes, such as those induced by drug treatment, affect the immunopeptidome, quantitative immunopeptidomics approaches are essential.MethodsTo meet this need, we developed a pulsed SILAC-based method for quantitative immunopeptidomics. Metabolic labeling with lysine, arginine, and leucine enabled isotopic labeling of nearly all HLA peptides across all allotypes (> 90% on average). We established a data analysis workflow that integrates the de novo sequencing-based tool Peptide-PRISM for comprehensive HLA peptide identification with MaxQuant for accurate quantification.ResultsWe employed this strategy to explore the modulation of the immunopeptidome upon MAPK pathway inhibition (MAPKi) and to investigate alterations associated with early cellular responses to inhibitor treatment and acquired resistance to MAPKi. Our analyses demonstrated significant changes in the immunopeptidome early during MAPKi treatment and in the resistant state. Moreover, we identified putative tumor-specific cryptic HLA peptides linked to these processes that might represent exploitable targets for cancer immunotherapy.ConclusionsWe have developed a new mass spectrometric approach that allowed us to investigate the effects of common MAPK inhibitors on the immunopeptidome of melanoma cells. This finally led to the discovery of new potential targets for cancer immunotherapy.

Background: T-cell responses can be protective or detrimental during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection; however, the underlying mechanism is poorly understood. Methods: In this study, we screened 144 15-mer peptides spanning the SARS-CoV-2 spike, nucleocapsid (NP), M, ORF8, ORF10, and ORF3a proteins and 39 reported SARS-CoV-1 peptides in peripheral blood mononuclear cells (PBMCs) from nine laboratory-confirmed coronavirus disease 2019 (COVID-19) patients (five moderate and four severe cases) and nine healthy donors (HDs) collected before the COVID-19 pandemic. T-cell responses were monitored by IFN-γ and IL-17A production using ELISA, and the positive samples were sequenced for the T cell receptor (TCR) β chain. The positive T-cell responses to individual SARS-CoV-2 peptides were validated by flow cytometry. Results: COVID-19 patients with moderate disease produced more IFN-γ than HDs and patients with severe disease (moderate vs. HDs, p < 0.0001; moderate vs. severe, p < 0.0001) but less IL-17A than those with severe disease (p < 0.0001). A positive correlation was observed between IFN-γ production and T-cell clonal expansion in patients with moderate COVID-19 (r = 0.3370, p = 0.0214) but not in those with severe COVID-19 (r = −0.1700, p = 0.2480). Using flow cytometry, we identified that a conserved peptide of the M protein (Peptide-120, P120) was a dominant epitope recognized by CD8+ T cells in patients with moderate disease. Conclusion: Coordinated IFN-γ production and clonal expansion of SARS-CoV-2-specific T cells are associated with disease resolution in COVID-19. Our findings contribute to a better understanding of T-cell-mediated immunity in COVID-19 and may inform future strategies for managing and preventing severe outcomes of SARS-CoV-2 infection. [ABSTRACT FROM AUTHOR]

Introduction: This immunoinformatic study identified potential epitopes from the envelopment polyprotein (Gn/Gc) of Rift Valley fever virus (RVFV), a pathogenic virus causing severe fever in humans and livestock. Effective vaccination is crucial for controlling RVFV outbreaks. The identification of suitable epitopes is crucial for the development of safe and effective vaccines. Methodology: Protein sequences were obtained from the UniProt database, and evaluated through VaxiJen v2.0 to predict the B and T-cell epitopes within the RVFV glycoprotein. Gn/Gc protein sequences were analyzed with bioinformatics tools and algorithms. The predicted T- cell and B-cell epitopes were evaluated for antigenicity, allergenicity, and toxicity by the VaxiJen v2.0 system, AllerTop v2.0, and ToxinPred server, respectively. Results: We employed computational methods to screen the RVFV envelopment polyprotein encompassing N-terminal and C-terminal glycoprotein segments, to discover antigenic T- and B-cell epitopes. Our analysis unveiled multiple potential epitopes within the RVFV glycoprotein, specifically within the Gn/Gc protein sequences. Subsequently, we selected eleven cytotoxic T-lymphocytes (CTL) and four helper T-lymphocytes (HTL) for population coverage analysis, which collectively extended to cover 97.04% of the world's population, representing diverse ethnicities and regions. Notably, the CTL epitope VQADLTLMF exhibited binding affinity to numerous human leukocyte antigen (HLA) alleles. The identification of glycoprotein (Gn/Gc) epitopes through this immunoinformatic study bears significant implications for advancing the development of an effective RVFV vaccine. Conclusions: These findings provide valuable insights into the immunological aspects of the disease and may contribute towards the development of broad-spectrum antiviral therapies targeting other RNA viruses with similar polymerase enzymes. [ABSTRACT FROM AUTHOR]

Complications due to HCMV infection or reactivation remain a challenging clinical problem in immunocompromised patients, mainly due to insufficient or absent T‐cell functionality. Knowledge of viral targets is crucial to improve monitoring of high‐risk patients and optimise antiviral T‐cell therapy. To expand the epitope spectrum, genetically‐engineered dendritic cells (DCs) and fibroblasts were designed to secrete soluble (s)HLA‐A*11:01 and infected with an HCMV mutant lacking immune evasion molecules (US2‐6 + 11). More than 700 HLA‐A*11:01‐restricted epitopes, including more than 50 epitopes derived from a broad range of HCMV open‐reading‐frames (ORFs) were identified by mass spectrometry and screened for HLA‐A*11:01‐binding using established prediction tools. The immunogenicity of the 24 highest scoring new candidates was evaluated in vitro in healthy HLA‐A*11:01+/HCMV+ donors. Thus, four subdominant epitopes and one immunodominant epitope, derived from the anti‐apoptotic protein UL36 and ORFL101C (A11SAL), were identified. Their HLA‐A*11:01 complex stability was verified in vitro. In depth analyses revealed highly proliferative and cytotoxic memory T‐cell responses against A11SAL, with T‐cell responses comparable to the immunodominant HLA‐A*02:01‐restricted HCMVpp65NLV epitope. A11SAL‐specific T cells were also detectable in vivo in immunosuppressed transplant patients and shown to be effective in an in vitro HCMV‐infection model, suggesting their crucial role in inhibiting viral replication and improvement of patient's outcome. The developed in vitro pipeline is the first to utilise genetically‐engineered DCs to identify naturally presented immunodominant HCMV‐derived epitopes. It therefore offers advantages over in silico predictions, is transferable to other HLA alleles, and will significantly expand the repertoire of viral targets to improve therapeutic options. [ABSTRACT FROM AUTHOR]

Food allergies mediated by specific IgE (sIgE) have a significant socioeconomic impact on society. Evaluating the IgE cross-reactivity between allergens from different allergen sources can enable the better management of these potentially life-threatening adverse reactions to food proteins and enhance food safety. A novel banana fruit allergen, S-adenosyl-L-homocysteine hydrolase (SAHH), has been recently identified and its recombinant homolog was heterologously overproduced in E. coli. In this study, we performed a search in the NCBI (National Center for Biotechnology Information) for SAHH homologs in ryegrass, latex, and kiwifruit, all of which are commonly associated with pollen-latex-fruit syndrome. In addition, Western immunoblot analysis was utilized to identify the cross-reactive IgE to banana SAHH in the sera of patients with a latex allergy, kiwifruit allergy, and ryegrass allergy. ClustalOmega analysis showed more than 92% amino acid sequence identity among the banana SAHH homologs in ryegrass, latex, and kiwifruit. In addition to five B-cell epitopes, in silico analysis predicted eleven T-cell epitopes in banana SAHH, seventeen in kiwifruit SAHH, twelve in ryegrass SAHH, and eight in latex SAHH, which were related to the seven-allele HLA reference set (HLA-DRB1*03:01, HLA-DRB1*07:01, HLA-DRB1*15:01, HLA-DRB3*01:01, HLA-DRB3*02:02, HLA-DRB4*01:01, HLA-DRB5*01:01). Four T-cell epitopes were identical in banana and kiwifruit SAHH (positions 328, 278, 142, 341), as well as banana and ryegrass SAHH (positions 278, 142, 96, and 341). All four SAHHs shared two T-cell epitopes (positions 278 and 341). In line with the high amino acid sequence identity and B-cell epitope homology among the analyzed proteins, the cross-reactive IgE to banana SAHH was detected in three of three latex-allergic patients, five of six ryegrass-allergic patients, and two of three kiwifruit-allergic patients. Although banana SAHH has only been studied in a small group of allergic individuals, it is a novel cross-reactive food allergen that should be considered when testing for pollen-latex-fruit syndrome. [ABSTRACT FROM AUTHOR]

Introduction: Human leukocyte antigen (HLA)-DPB1 mismatches during hematopoietic stem cell transplantation (HSCT) with an unrelated donor result in an increased risk for the development of graft-versus-host disease (GvHD). The number of CD8+ T-cell epitopes available for indirect allorecognition as predicted by the PIRCHE algorithm has been shown to be associated with GvHD development. As a proof of principle, PIRCHE-I predictions for HLA-DPB1 mismatches were validated in vitro and in vivo. Methods: PIRCHE-I analysis was performed to identify HLA-DPB1-derived peptides that could theoretically bind to HLA-A*02:01. PIRCHE-I predictions for HLA-DPB1 mismatches were validated in vitro by investigating binding affinities of HLA-DPB1-derived peptides to the HLA-A*02:01 in a competition-based binding assay. To investigate the capacity of HLA-DPB1-derived peptides to elicit a T-cell response in vivo, mice were immunized with these peptides. T-cell alloreactivity was subsequently evaluated using an interferon-gamma ELISpot assay. Results: The PIRCHE-I algorithm identified five HLA-DPB1-derived peptides (RMCRHNYEL, YIYNREEFV, YIYNREELV, YIYNREEYA, and YIYNRQEYA) to be presented by HLA-A*02:01. Binding of these peptides to HLA-A*02:01 was confirmed in a competition-based peptide binding assay, all showing an IC50 value of 21 μm or lower. The peptides elicited an interferon-gamma response in vivo. Conclusion: Our results indicate that the PIRCHE-I algorithm can identify potential immunogenic HLA-DPB1-derived peptides present in recipients of an HLA-DPB1-mismatched donor. These combined in vitro and in vivo observations strengthen the validity of the PIRCHE-I algorithm to identify HLA-DPB1 mismatch-related GvHD development upon HSCT. [ABSTRACT FROM AUTHOR]

Abstract Background The clinical routine test of HBV-specific T cell reactivity is still limited due to the high polymorphisms of human leukocyte antigens (HLA) in patient cohort and the lack of universal detection kit, thus the clinical implication remains disputed. Methods A broad-spectrum peptide library, which consists of 103 functionally validated CD8+ T-cell epitopes spanning overall HBsAg, HBeAg, HBx and HBpol proteins and fits to the HLA polymorphisms of Chinese and Northeast Asian populations, was grouped into eight peptide pools and was used to establish an ELISpot assay for enumerating the reactive HBV-specific T cells in PBMCs. Totally 294 HBV-infected patients including 203 ones with chronic hepatitis B (CHB), 13 ones in acute resolved stage (R), 52 ones with liver cirrhosis (LC) and 26 ones with hepatocellular carcinoma (HCC) were detected, and 33 CHB patients were longitudinally monitored for 3 times with an interval of 3–5 months. Results The numbers of reactive HBV-specific T cells were significantly correlated with ALT level, HBsAg level, and disease stage (R, CHB, LC and HCC), and R patients displayed the strongest HBV-specific T cell reactivity while CHB patients showed the weakest one. For 203 CHB patients, the numbers of reactive HBV-specific T cells presented a significantly declined trend when the serum viral DNA load, HBsAg, HBeAg or ALT level gradually increased, but only a very low negative correlation coefficient was defined (r = − 0.21, − 0.21, − 0.27, − 0.079, respectively). Different Nucleotide Analogs (NUCs) did not bring difference on HBV-specific T cell reactivity in the same duration of treatment. NUCs/pegIFN-α combination led to much more reactive HBV-specific T cells than NUCs monotherapy. The dynamic numbers of reactive HBV-specific T cells were obviously increasing in most CHB patients undergoing routine treatment, and the longitudinal trend possess a high predictive power for the hepatitis progression 6 or 12 months later. Conclusion The presented method could be developed into an efficient reference method for the clinical evaluation of cellular immunity. The CHB patients presenting low reactivity of HBV-specific T cells have a worse prognosis for hepatitis progression and should be treated using pegIFN-α to improve host T-cell immunity.

Abstract Zika virus is an infectious virus, that belongs to Flaviviridae family, which is transferred to humans through mosquito vectors and severely threatens human health; but, apart from available resources, no effective and secure vaccine is present against Zika virus, to prevent such infections. In current study, we employed structural vaccinology approach to design an epitope-based vaccine against Zika virus, which is biocompatible, and secure and might trigger an adaptive and innate immune response by using computational approaches. We first retrieved the protein sequence from National Center for Biotechnology Information (NCBI) database and carried out for BLAST P. After BLAST P, predicted protein sequences were shortlisted and checked for allergic features and antigenic properties. Final sequence of Zika virus, with accession number (APO40588.1) was selected based on high antigenic score and non-allergenicity. Final protein sequence used various computational approaches including antigenicity testing, toxicity evaluation, allergenicity, and conservancy assessment to identify superior B-cell and T-cell epitopes. Two B-cell epitopes, five MHC-six MHC-II epitopes and I were used to construct an immunogenic multi-epitope-based vaccine by using suitable linkers. A 50S ribosomal protein was added at N terminal to improve the immunogenicity of vaccine. In molecular docking, strong interactions were presented between constructed vaccine and Toll-like receptor 9 (− 1100.6 kcal/mol), suggesting their possible relevance in the immunological response to vaccine. The molecular dynamics simulations ensure the dynamic and structural stability of constructed vaccine. The results of C-immune simulation revealed that constructed vaccine activate B and T lymphocytes which induce high level of antibodies and cytokines to combat Zika infection. The constructed vaccine is an effective biomarker with non-sensitization, nontoxicity; nonallergic, good immunogenicity, and antigenicity, however, experimental assays are required to verify the results of present study.

Background: The clinical routine test of HBV-specific T cell reactivity is still limited due to the high polymorphisms of human leukocyte antigens (HLA) in patient cohort and the lack of universal detection kit, thus the clinical implication remains disputed. Methods: A broad-spectrum peptide library, which consists of 103 functionally validated CD8+ T-cell epitopes spanning overall HBsAg, HBeAg, HBx and HBpol proteins and fits to the HLA polymorphisms of Chinese and Northeast Asian populations, was grouped into eight peptide pools and was used to establish an ELISpot assay for enumerating the reactive HBV-specific T cells in PBMCs. Totally 294 HBV-infected patients including 203 ones with chronic hepatitis B (CHB), 13 ones in acute resolved stage (R), 52 ones with liver cirrhosis (LC) and 26 ones with hepatocellular carcinoma (HCC) were detected, and 33 CHB patients were longitudinally monitored for 3 times with an interval of 3–5 months. Results: The numbers of reactive HBV-specific T cells were significantly correlated with ALT level, HBsAg level, and disease stage (R, CHB, LC and HCC), and R patients displayed the strongest HBV-specific T cell reactivity while CHB patients showed the weakest one. For 203 CHB patients, the numbers of reactive HBV-specific T cells presented a significantly declined trend when the serum viral DNA load, HBsAg, HBeAg or ALT level gradually increased, but only a very low negative correlation coefficient was defined (r = − 0.21, − 0.21, − 0.27, − 0.079, respectively). Different Nucleotide Analogs (NUCs) did not bring difference on HBV-specific T cell reactivity in the same duration of treatment. NUCs/pegIFN-α combination led to much more reactive HBV-specific T cells than NUCs monotherapy. The dynamic numbers of reactive HBV-specific T cells were obviously increasing in most CHB patients undergoing routine treatment, and the longitudinal trend possess a high predictive power for the hepatitis progression 6 or 12 months later. Conclusion: The presented method could be developed into an efficient reference method for the clinical evaluation of cellular immunity. The CHB patients presenting low reactivity of HBV-specific T cells have a worse prognosis for hepatitis progression and should be treated using pegIFN-α to improve host T-cell immunity. [ABSTRACT FROM AUTHOR]

Zika virus is an infectious virus, that belongs to Flaviviridae family, which is transferred to humans through mosquito vectors and severely threatens human health; but, apart from available resources, no effective and secure vaccine is present against Zika virus, to prevent such infections. In current study, we employed structural vaccinology approach to design an epitope-based vaccine against Zika virus, which is biocompatible, and secure and might trigger an adaptive and innate immune response by using computational approaches. We first retrieved the protein sequence from National Center for Biotechnology Information (NCBI) database and carried out for BLAST P. After BLAST P, predicted protein sequences were shortlisted and checked for allergic features and antigenic properties. Final sequence of Zika virus, with accession number (APO40588.1) was selected based on high antigenic score and non-allergenicity. Final protein sequence used various computational approaches including antigenicity testing, toxicity evaluation, allergenicity, and conservancy assessment to identify superior B-cell and T-cell epitopes. Two B-cell epitopes, five MHC-six MHC-II epitopes and I were used to construct an immunogenic multi-epitope-based vaccine by using suitable linkers. A 50S ribosomal protein was added at N terminal to improve the immunogenicity of vaccine. In molecular docking, strong interactions were presented between constructed vaccine and Toll-like receptor 9 (− 1100.6 kcal/mol), suggesting their possible relevance in the immunological response to vaccine. The molecular dynamics simulations ensure the dynamic and structural stability of constructed vaccine. The results of C-immune simulation revealed that constructed vaccine activate B and T lymphocytes which induce high level of antibodies and cytokines to combat Zika infection. The constructed vaccine is an effective biomarker with non-sensitization, nontoxicity; nonallergic, good immunogenicity, and antigenicity, however, experimental assays are required to verify the results of present study. [ABSTRACT FROM AUTHOR]

Abstract Background Numerous tools exist for biological sequence comparisons and search. One case of particular interest for immunologists is finding matches for linear peptide T cell epitopes, typically between 8 and 15 residues in length, in a large set of protein sequences. Both to find exact matches or matches that account for residue substitutions. The utility of such tools is critical in applications ranging from identifying conservation across viral epitopes, identifying putative epitope targets for allergens, and finding matches for cancer-associated neoepitopes to examine the role of tolerance in tumor recognition. Results We defined a set of benchmarks that reflect the different practical applications of short peptide sequence matching. We evaluated a suite of existing methods for speed and recall and developed a new tool, PEPMatch. The tool uses a deterministic k-mer mapping algorithm that preprocesses proteomes before searching, achieving a 50-fold increase in speed over methods such as the Basic Local Alignment Search Tool (BLAST) without compromising recall. PEPMatch’s code and benchmark datasets are publicly available. Conclusions PEPMatch offers significant speed and recall advantages for peptide sequence matching. While it is of immediate utility for immunologists, the developed benchmarking framework also provides a standard against which future tools can be evaluated for improvements. The tool is available at https://nextgen-tools.iedb.org , and the source code can be found at https://github.com/IEDB/PEPMatch .

With the development of novel vaccine strategies, T-cell epitope-based vaccines have become promising prophylactic and therapeutic tools against infectious diseases that cannot be controlled via traditional vaccines. T-cell epitope-based vaccines leverage specific immunogenic peptides to elicit protective T-cell responses against infectious pathogens. Compared to traditional vaccines, they provide superior efficacy and safety, minimizing the risk of adverse side effects. In this review, we summarized and compared the prediction and identification methods of T-cell epitopes. By integrating bioinformatic prediction and experimental validation, efficient and precise screening of T-cell epitopes can be achieved. Importantly, we delved into the development approaches to diverse T-cell epitope-based vaccines, comparing their merits and demerits, as well as discussing the prevalent challenges and perspectives in their applications. This review offers fresh perspectives for the formulation of safe and efficacious epitope-based vaccines for the devastating diseases against which no vaccines are currently available.

Citrullinated proteins and anti-citrullinated protein antibodies (ACPAs) play an important role in the pathogenesis of rheumatoid arthritis (RA). It has been suggested that during inflammation or dysbiosis, bacteria could initiate production of ACPAs. Most patients with RA are seropositive for ACPAs, but these antibodies have overlapping reactivity to different posttranslational modifications (PTMs). For initiation and development of RA, T lymphocytes and T cell epitopes are still required. In this study, we evaluated the ability of bacterial L-asparaginase to modify RA-related T cell epitopes within type II collagen (CII259-273 and CII311-325), as well as whether these modified epitopes are recognized by ACPAs from RA patients. We included 12 patients with early RA and 11 healthy subjects selected according to predefined specific criteria. LC-MS/MS analyses revealed that the bacterial L-asparaginase can modify investigated T cell epitopes. ELISA tests showed cross-reactivity of ACPA positive sera from early RA patients towards the enzymatically modified immunodominant T cell epitopes within type II collagen (CII), but not to the modified irrelevant peptides. These data suggest that the cross-reactive ACPAs recognize the “carbonyl-Gly-Pro” motif in CII. Moreover, the T cell recognition of the modified major immunodominant T cell epitope Gal264-CII259-273 was not affected. This epitope was still able to activate autoreactive T cells from early RA patients. It is likely that such modifications are the missing link between the T cell priming and the development of anti-modified protein antibodies (AMPAs). Our results provide additional information on the etiology and pathogenesis of RA.

Abstract Background An efficient and reliable data-driven method is essential to aid robust vaccine design, particularly in the case of an epidemic like Influenza A. Although various prediction tools are existing, most of them focus on the MHC-peptide binding affinity predictions. A tool which can incorporate more features other than binding affinity which characterizes the T-cell epitopes as vaccine candidates would be of much value in this scenario. The objective of this study is to develop two separate neural network models for the predictions of CTLs (cytotoxic T lymphocyte) and HTLs (helper T lymphocyte) with the manually curated datasets as a part of this study from the raw viral sequences of Influenza A. Results The epitope datasets curated from the raw sequences of the broadly protective Neuraminidase protein were utilized for building and training the models for CTLs and HTLs. Each set consisted of nearly a balanced mix of vaccine candidates and non-vaccine candidates for both CTLs and HTLs. These were fed to neural networks as they are proven to be powerful for the predictions when compared with the other machine/deep learning algorithms. A set of epitopes experimentally proved were chosen to validate the model which was also tested through mutational analysis and cross-reactivity. The prepared dataset gave some valuable insights into the epitope distribution statistics and their conservancy in various outbreaks. An idea about the most probable range of peptide-MHC binding affinities was also obtained. Both the models performed well giving high accuracies when validated. These epitopes were checked for cross-reactivity with other antigens upon which it proved to be highly conservative and ideal for vaccine formulation. Conclusions The combination of various features and the resulting model efficiencies in turn proved that the collected features are valuable in the easy identification of the vaccine candidates. This suggests that our proposed models have more potential for conserved epitope prediction compared to other existing models trained on similar data and features. The possibility of refining the model with more set threshold values based on more parameters is an added feature that makes it more user driven. Furthermore, the uniqueness of the model due to exclusive set of Neuraminidase epitopes paves a robust way for rapid vaccine design. Graphical abstract

The class I HLA genotype has been widely recognized as a factor influencing HIV disease progression in treatment‐naïve subjects. However, little is known regarding its role in HIV disease course and how it influences the size of the viral reservoir once anti‐retroviral therapy (ART) is started. Here, leveraging on cutting‐edge bioinformatic tools, we explored the relationship between HLA class I and the HIV reservoir in a cohort of 90 people living with HIV (PLWH) undergoing ART and who achieved viral suppression. Analysis of HLA allele distribution among patients with high and low HIV reservoir allowed us to document a predominant role of HLA‐B and ‐C genes in regulating the size of HIV reservoir. We then focused on the analysis of HIV antigen (Ag) repertoire, by investigating immunogenetic parameters such as the degree of homozygosity, HLA evolutionary distance and Ag load. In particular, we used two different bioinformatic algorithms, NetMHCpan and MixMHCpred, to predict HLA presentation of immunogenic HIV‐derived peptides and identified HLA‐B*57:01 and HLA‐B*58:01 among the highest ranking HLAs in terms of total load, suggesting that their previously reported protective role against HIV disease progression might be linked to a more effective viral recognition and presentation to Cytotoxic T lymphocytes (CTLs). Further, we speculated that some peptide‐HLA complexes, including those produced by the interaction between HLA‐B*27 and the HIV Gag protein, might be particularly relevant for the efficient regulation of HIV replication and containment of the HIV reservoir. Last, we provide evidence of a possible synergistic effect between the CCR5 ∆32 mutation and Ag load in controlling HIV reservoir. [ABSTRACT FROM AUTHOR]

Background: Numerous tools exist for biological sequence comparisons and search. One case of particular interest for immunologists is finding matches for linear peptide T cell epitopes, typically between 8 and 15 residues in length, in a large set of protein sequences. Both to find exact matches or matches that account for residue substitutions. The utility of such tools is critical in applications ranging from identifying conservation across viral epitopes, identifying putative epitope targets for allergens, and finding matches for cancer-associated neoepitopes to examine the role of tolerance in tumor recognition. Results: We defined a set of benchmarks that reflect the different practical applications of short peptide sequence matching. We evaluated a suite of existing methods for speed and recall and developed a new tool, PEPMatch. The tool uses a deterministic k-mer mapping algorithm that preprocesses proteomes before searching, achieving a 50-fold increase in speed over methods such as the Basic Local Alignment Search Tool (BLAST) without compromising recall. PEPMatch's code and benchmark datasets are publicly available. Conclusions: PEPMatch offers significant speed and recall advantages for peptide sequence matching. While it is of immediate utility for immunologists, the developed benchmarking framework also provides a standard against which future tools can be evaluated for improvements. The tool is available at https://nextgen-tools.iedb.org, and the source code can be found at https://github.com/IEDB/PEPMatch. [ABSTRACT FROM AUTHOR]

Cow milk (CM) allergy is the most prevalent food allergy in young children in the United States and Great Britain. Current diagnostic tests are either unreliable (IgE test and skin prick test) or resource-intensive with risks (food challenges). We sought to determine whether allergen-specific T cells in CM-allergic (CMA) patients have a distinct quality and/or quantity that could potentially be used as a diagnostic marker. Using PBMCs from 147 food-allergic pediatric subjects, we mapped T-cell responses to a set of reactive epitopes in CM that we compiled in a peptide pool. This pool induced cytokine responses in in vitro cultured cells distinguishing subjects with CMA from subjects without CMA. We further used the pool to isolate and characterize antigen-specific CD4 memory T cells using flow cytometry and single-cell RNA/TCR sequencing assays. We detected significant changes in the transcriptional program and clonality of CM antigen-specific (CM+) T cells elicited by the pool in subjects with CMA versus subjects without CMA ex vivo. CM+ T cells from subjects with CMA had increased percentages of FOXP3+ cells over FOXP3− cells. FOXP3+ cells are often equated with regulatory T cells that have suppressive activity, but CM+ FOXP3+ cells from subjects with CMA showed significant expression of interferon-responsive genes and dysregulated chemokine receptor expression compared with subjects without CMA, suggesting that these are not conventional regulatory T cells. The CM+ FOXP3+ cells were also more clonally expanded than the FOXP3− population. We were further able to use surface markers (CD25, CD127, and CCR7) in combination with our peptide pool stimulation to quantify these CM+ FOXP3+ cells by a simple flow-cytometry assay. We show increased percentages of CM+ CD127−CD25+ cells from subjects with CMA in an independent cohort, which could be used for diagnostic purposes. Looking specifically for T H 2 cells normally associated with allergic diseases, we found a small population of clonally expanded CM+ cells that were significantly increased in subjects with CMA and that had high expression of T H 2 cytokines and pathogenic T H 2/T follicular helper markers. Overall, these findings suggest that there are several differences in the phenotypes of CM+ T cells with CM allergy and that the increase in CM+ FOXP3+ cells is a potential diagnostic marker of an allergic state. Such markers have promising applications in monitoring natural disease outgrowth and/or the efficacy of immunotherapy that will need to be validated in future studies. [ABSTRACT FROM AUTHOR]

Background: An efficient and reliable data-driven method is essential to aid robust vaccine design, particularly in the case of an epidemic like Influenza A. Although various prediction tools are existing, most of them focus on the MHC-peptide binding affinity predictions. A tool which can incorporate more features other than binding affinity which characterizes the T-cell epitopes as vaccine candidates would be of much value in this scenario. The objective of this study is to develop two separate neural network models for the predictions of CTLs (cytotoxic T lymphocyte) and HTLs (helper T lymphocyte) with the manually curated datasets as a part of this study from the raw viral sequences of Influenza A. Results: The epitope datasets curated from the raw sequences of the broadly protective Neuraminidase protein were utilized for building and training the models for CTLs and HTLs. Each set consisted of nearly a balanced mix of vaccine candidates and non-vaccine candidates for both CTLs and HTLs. These were fed to neural networks as they are proven to be powerful for the predictions when compared with the other machine/deep learning algorithms. A set of epitopes experimentally proved were chosen to validate the model which was also tested through mutational analysis and cross-reactivity. The prepared dataset gave some valuable insights into the epitope distribution statistics and their conservancy in various outbreaks. An idea about the most probable range of peptide-MHC binding affinities was also obtained. Both the models performed well giving high accuracies when validated. These epitopes were checked for cross-reactivity with other antigens upon which it proved to be highly conservative and ideal for vaccine formulation. Conclusions: The combination of various features and the resulting model efficiencies in turn proved that the collected features are valuable in the easy identification of the vaccine candidates. This suggests that our proposed models have more potential for conserved epitope prediction compared to other existing models trained on similar data and features. The possibility of refining the model with more set threshold values based on more parameters is an added feature that makes it more user driven. Furthermore, the uniqueness of the model due to exclusive set of Neuraminidase epitopes paves a robust way for rapid vaccine design. Highlights: The analysis of the past viral strains of Neuraminidase, delivered an interesting list of possible epitopes for vaccine design. The class-I & class-II MHC binding reports of the test set of epitopes, strongly validate the high performance (~ or above 90%) of the ML models. The homology studies with nematode antigens suggest that our predicted epitopes are free from cross-reactivity with parasitic epitopes. The very few mutations reported for Neuraminidase (being the conserved one among the other proteins) from the mutational analysis prove that the vaccine formulations with our predicted epitopes are capable of overcoming any antigenic drifts in the future. [ABSTRACT FROM AUTHOR]

Vaccines that confer protection through induction of adaptive T-cell immunity rely on understanding T-cell epitope (TCE) evolution induced by immune escape. This is poorly understood in tuberculosis (TB), an ancient, chronic disease, where CD4 T-cell immunity is of recognized importance. We probed 905 functionally validated, curated human CD4 T cell epitopes in 79 Mycobacterium tuberculosis (Mtb) whole genomes from India. This screen resulted in identifying 64 mutated epitopes in these strains initially using a computational pipeline and subsequently verified by single nucleotide polymorphism (SNP) analysis. SNP based phylogeny revealed the 79 Mtb strains to cluster to East African Indian (EAI), Central Asian Strain (CAS), and Beijing (BEI) lineages. Eighty-nine percent of the mutated T-cell epitopes (mTCEs) identified in the 79 Mtb strains from India has not previously been reported. These mTCEs were encoded by genes with high nucleotide diversity scores including seven mTCEs encoded by six antigens in the top 10% of rapidly divergent Mtb genes encoded by these strains. Using a T cell functional assay readout, we demonstrate 62% of mTCEs tested to significantly alter CD4 T-cell IFNγ and/or IL2 secretion with associated changes in predicted HLA-DR binding affinity: the gain of function mutations displayed higher predicted HLA-DR binding affinity and conversely mutations resulting in loss of function displayed lower predicted HLA-DR binding affinity. Most mutated antigens belonged to the cell wall/cell processes, and, intermediary metabolism and respiration families though all known Mtb proteins encoded mutations. Analysis of the mTCEs in an SNP database of 5,310 global Mtb strains identified 82% mTCEs to be significantly more prevalent in Mtb strains isolated from India, including 36 mTCEs identified exclusively in strains from India. These epitopes had a significantly higher predicted binding affinity to HLA-DR alleles that were highly prevalent in India compared to HLA-DR alleles rare in India, highlighting HLA-DR maybe an important driver of these mutations. This first evidence of region-specific TCE mutations potentially employed by Mtb to escape host immunity has important implications for TB vaccine design.

Multiple vaccines were developed and administered to immunize people worldwide against SARS-CoV-2 infection. However, changes in platelet count following the course of vaccination have been reported by many studies, suggesting vaccine-induced thrombocytopenia. In this context, designing an effective targeted subunit vaccine with high specificity and efficiency for people with low platelet counts has become a challenge for researchers. Using the in silico-based approaches and methods, the present study explored the antigenic epitopes of the spike protein of SARS-CoV-2 involved in initial binding of the virus with the angiotensin converting enzyme-2 receptor (ACE-2) on the respiratory epithelial cells. The top ten major histocompatibility complex-I (MHC-I) and MHC-II restricted epitopes were found to have 95.26% and 99.99% HLA-class-I population coverage, respectively. Among the top ten promiscuous MHC-I restricted epitopes, 'FTISVTTEI' had the highest global HLA population coverage of 53.24%, with an antigenic score of 0.85 and a docking score of −162.4 Kcal/mol. The epitope 'KLNDLCFTNV' had the best antigenic score of 2.69 and an HLA population coverage of 43.4% globally. The study predicted and documented the most suitable epitopes with the widest global HLA coverage for synthesis of an efficient peptide-based vaccine against the deadly COVID-19. [ABSTRACT FROM AUTHOR]

Reports on T-cell cross-reactivity against SARS-CoV-2 epitopes in unexposed individuals have been linked with prior exposure to the human common cold coronaviruses (HCCCs). Several studies suggested that cross-reactive T-cells response to live attenuated vaccines (LAVs) such as BCG (Bacillus Calmette–Guérin), OPV (Oral Polio Vaccine), and MMR (measles, mumps, and rubella) can limit the development and severity of COVID-19. This study aims to identify potential cross-reactivity between SARS-CoV-2, HCCCs, and LAVs in the context of T-cell epitopes peptides presented by HLA (Human Leukocyte Antigen) alleles of the Indonesian population. SARS-CoV-2 derived T-cell epitopes were predicted using immunoinformatics tools and assessed for their conservancy, variability, and population coverage. Two fully conserved epitopes with 100% similarity and nine heterologous epitopes with identical T-cell receptor (TCR) contact residues were identified from the ORF1ab fragment of SARS-CoV-2 and all HCCCs. Cross-reactive epitopes from various proteins of SARS-CoV-2 and LAVs were also identified (15 epitopes from BCG, 7 epitopes from MMR, but none from OPV). A majority of the identified epitopes were observed to belong to ORF1ab, further suggesting the vital role of ORF1ab in the coronaviruses family and suggesting it as a candidate for a potential universal coronavirus vaccine that protects against severe disease by inducing cell mediated immunity. [ABSTRACT FROM AUTHOR]

Visceral leishmaniasis (VL) is a tropical disease that can be fatal if acute and untreated. Diagnosis is difficult, the treatment is toxic and prophylactic vaccines do not exist. Leishmania parasites express hundreds of proteins and several of them are relevant for the host's immune system. In this context, in the present study, 10 specific T-cell epitopes from 5 parasite proteins, which were identified by antibodies in VL patients’ sera, were selected and used to construct a gene codifying the new chimeric protein called rCHI. The rCHI vaccine was developed and thoroughly evaluated for its potential effectiveness against Leishmania infantum infection. We used monophosphoryl lipid A (MPLA) and polymeric micelles (Mic) as adjuvant and/or delivery system. The results demonstrated that both rCHI/MPLA and rCHI/Mic significantly stimulate an antileishmanial Th1-type cellular response, with higher production of IFN- γ , TNF- α , IL-12 and nitrite in vaccinated animals, and this response was sustained after challenge. In addition, these mice significantly reduced the parasitism in internal organs and increased the production of IgG2a isotype antibodies. In vivo and in vitro toxicity showed that rCHI is safe for the mammalians, and the recombinant protein also induced in vitro lymphoproliferative response and production of Th1-type cytokines by human cells, which were collected from healthy subjects and treated VL patients. These data suggest rCHI plus MPLA or micelles could be considered as a vaccine candidate against VL.

Background: Bovine leukemia virus (BLV) is an oncogenic delta-retrovirus causing bovine leucosis. Studies on BLV have shown the association with human breast cancer. However, the exact molecular mechanism is neither known nor their appropriate preventative measure to halt the disease initiation and progression. In this study, we designed a multi-epitope vaccine against BLV using a computational analyses. Methods: Following a rigorous assessment, the vaccine was constructed using the T-cell epitopes from each BLV-derived protein with suitable adjuvant and linkers. Both physicochemistry and immunogenic potency as well as the safeness of the vaccine candidate were assessed. Population coverage was done to evaluate the vaccine probable efficiency in eliciting the immune response worldwide. After homology modeling, the three-dimensional structure was refined and validated to determine the quality of the designed vaccine. The vaccine protein was then subjected to molecular docking with Toll-like receptor 3 (TLR3) to evaluate the binding efficiency followed by dynamic simulation for stable interaction. Results: Our vaccine construct has the potential immune response and good physicochemical properties. The vaccine is antigenic and immunogenic, and has no allergenic or toxic effect on the human body. This novel vaccine contains a significant interactions and binding affinity with the TLR3 receptor. Conclusions: The proposed vaccine candidate would be structurally stable and capable of generating an effective immune response to combat BLV infections. However, experimental evaluations are essential to validate the exact safety and immunogenic profiling of this vaccine. [ABSTRACT FROM AUTHOR]

Vaccination is the most effective means of protecting people from influenza virus infection. The effectiveness of existing vaccines is very limited due to antigenic drift of the influenza virus. Therefore, there is a requirement to develop a universal vaccine that provides broad and long-lasting protection against influenza. CD8+ T-cell response played a vital role in controlling influenza virus infection, reducing viral load, and less clinical syndrome. In this study, we optimized the HA sequences of human seasonal influenza viruses (H1N1, H3N2, Victoria, and Yamagata) by designing multivalent vaccine antigen sets using a mosaic vaccine design strategy and genetic algorithms, and designed an HA mosaic cocktail containing the most potential CTL epitopes of seasonal influenza viruses. We then tested the recombinant mosaic antigen, which has a significant number of potential T-cell epitopes. Results from genetic evolutionary analyses and 3D structural simulations demonstrated its potential to be an effective immunogen. In addition, we have modified an existing neutralizing antibody-based seasonal influenza virus vaccine to include a component that activates cross-protective T cells, which would provide an attractive strategy for improving human protection against seasonal influenza virus drift and mutation and provide an idea for the development of a rationally designed influenza vaccine targeting T lymphocyte immunity. [ABSTRACT FROM AUTHOR]

Background: The increase in global mortality rates from SARS-COV2 (COVID-19) infection has been alarming thereby necessitating the continual search for viable therapeutic interventions. Due to minimal microbial components, subunit (peptide-based) vaccines have demonstrated improved efficacies in stimulating immunogenic responses by host B- and T-cells. Methods: Integrative immunoinformatics algorithms were used to determine linear and discontinuous B-cell epitopes from the S-glycoprotein sequence. End-point selection of the most potential B-cell epitope was based on highly essential physicochemical attributes. NetCTL-I and NetMHC-II algorithms were used to predict probable MHC-I and II T-cell epitopes for globally frequent HLA-A∗O2:01, HLA-B∗35:01, HLA-B∗51:01 and HLA-DRB1∗15:02 molecules. Highly probable T-cell epitopes were selected based on their high propensities for C-terminal cleavage, transport protein (TAP) processing and MHC-I/II binding. Results: Preferential epitope binding sites were further identified on the HLA molecules using a blind peptide-docking method. Phylogenetic analysis revealed close relativity between SARS-CoV-2 and SARS-CoV S-protein. LALHRSYLTPGDSSSGWTAGAA242→263 was the most probable B-cell epitope with optimal physicochemical attributes. MHC-I antigenic presentation pathway was highly favourable for YLQPRTFLL269-277 (HLA-A∗02:01), LPPAYTNSF24-32 (HLA-B∗35:01) and IPTNFTISV714-721 (HLA-B∗51:01). Also, LTDEMIAQYTSALLA865-881 exhibited the highest binding affinity to HLA-DR B1∗15:01 with core interactions mediated by IAQYTSALL870-878. COVID-19 YLQPRTFLL269-277 was preferentially bound to a previously undefined site on HLA-A∗02:01 suggestive of a novel site for MHC-I-mediated T-cell stimulation. Conclusion: This study implemented combinatorial immunoinformatics methods to model B- and T-cell epitopes with high potentials to trigger immunogenic responses to the S protein of SARS-CoV-2.

COVID-19 brought scenes from sci-fi movies into real life. Infected individuals include asymptomatic cases to severe disease leading to death, suggesting the involvement of the genetic constitution of populations and pathogens contributing to differential individuals' outcomes. To investigate shared immunogenic features between SARS-CoV-2 targets and other coronaviruses, we modeled their peptides in 3D structures of HLA-A*02:01 (pMHC), comparing their molecular surfaces These structures were also compared with a panel of epitopes from unrelated viruses, looking for potential triggers conferring cross-protection in uninfected individuals. As expected, SARS-CoV 1 and 2 peptides share molecular and physicochemical features, providing an explanation for the verified experimental immunogenicity among them. Surprisingly, even discordant sequences from human coronaviruses 229E, OC43 and epitopes from unrelated viruses involved in endemic human infections exhibit similar fingerprints of immunogenicity with SARS-CoV-2 peptides. The same approach indicates a conserved CD8+ T cell recognition between Wuhan SARS-CoV-2 sequences and altered peptides from Variants of Concern. Examination of structural data over epitope sequence analysis here could explain how previous infections may produce a heterologous immunity response in a global scale against emergent diseases such as Covid-19, mitigating its full lethal potential, and paves the way for the development of wide spectrum vaccine development. [ABSTRACT FROM AUTHOR]

Computational prediction to screen potential vaccine candidates has been proven to be a reliable way to provide guarantees for vaccine discovery in infectious diseases. As an important class of organisms causing infectious diseases, pathogenic eukaryotes (such as parasitic protozoans) have evolved the ability to colonize a wide range of hosts, including humans and animals; meanwhile, protective vaccines are urgently needed. Inspired by the immunological idea that pathogen-derived epitopes are able to mediate the CD8+ T-cellrelated host adaptive immune response and with the available positive and negative CD8+ T-cell epitopes (TCEs), we proposed a novel predictor called CD8TCEI-EukPath to detect CD8+ TCEs of eukaryotic pathogens. Our method integrated multiple amino acid sequence-based hybrid features, employed a well-established feature selection technique, and eventually built an efficient machine learning classifier to differentiate CD8+ TCEs from non-CD8+ TCEs. Based on the feature selection results, 520 optimal hybrid features were used for modeling by utilizing the LightGBM algorithm. CD8TCEIEukPath achieved impressive performance, with an accuracy of 79.255% in ten-fold cross-validation and an accuracy of 78.169% in the independent test. Collectively, CD8TCEI-EukPath will contribute to rapidly screening epitope-based vaccine candidates, particularly from large peptide-coding datasets. To conduct the prediction of CD8+ TCEs conveniently, an online web server is freely accessible (http://lab.malab.cn/~hrs/CD8TCEI-EukPath/). [ABSTRACT FROM AUTHOR]

Peptides are widely used for the diagnostics, prevention, and therapy of certain human diseases. How useful can they be for the disease caused by the SARS-CoV-2 coronavirus? In this review, we discuss the possibility of using synthetic and recombinant peptides and polypeptides for prevention of COVID-19 via blocking the interaction between the virus and its main receptor ACE2, as well as components of antiviral vaccines, in particular, against new emerging virus variants. [ABSTRACT FROM AUTHOR]

Currently, there is no licensed vaccine to protect against human visceral leishmaniasis (VL), a potentially fatal disease caused by infection with Leishmania parasites. In the current study, a recombinant chimeric protein ChimT was developed based on T-cell epitopes identified from the immunogenic Leishmania amastigote proteins LiHyp1, LiHyV, LiHyC and LiHyG. ChimT was associated with the adjuvants saponin (Sap) or monophosphoryl lipid A (MPLA) and used to immunize mice, and their immunogenicity and protective efficacy were evaluated. Both ChimT/Sap and ChimT/MPLA induced the development of a specific Th1-type immune response, with significantly high levels of IFN-γ, IL-2, IL-12, TNF-α and GM-CSF cytokines produced by CD4+ and CD8+ T cell subtypes (p < 0.05), with correspondingly low production of anti-leishmanial IL-4 and IL-10 cytokines. Significantly increased (p < 0.05) levels of nitrite, a proxy for nitric oxide, and IFN-γ expression (p < 0.05) were detected in stimulated spleen cell cultures from immunized and infected mice, as was significant production of parasite-specific IgG2a isotype antibodies. Significant reductions in the parasite load in the internal organs of the immunized and infected mice (p < 0.05) were quantified with a limiting dilution technique and quantitative PCR and correlated with the immunological findings. ChimT/MPLA showed marginally superior immunogenicity than ChimT/Sap, and although this was not statistically significant (p > 0.05), ChimT/MPLA was preferred since ChimT/Sap induced transient edema in the inoculation site. ChimT also induced high IFN-γ and low IL-10 levels from human PBMCs isolated from healthy individuals and from VL-treated patients. In conclusion, the experimental T-cell multi-epitope amastigote stage Leishmania vaccine administered with adjuvants appears to be a promising vaccine candidate to protect against VL. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic emerged in 2020 and has caused an unprecedented burden to all countries in the world. SARS-CoV-2 continues to circulate and antigenically evolve, enabling multiple reinfections. To address the issue of the virus antigenic variability, T cell-based vaccines are being developed, which are directed to more conserved viral epitopes. We used live attenuated influenza vaccine (LAIV) virus vector to generate recombinant influenza viruses expressing various T-cell epitopes of SARS-CoV-2 from either neuraminidase (NA) or non-structural (NS1) genes, via the P2A self-cleavage site. Intranasal immunization of human leukocyte antigen-A*0201 (HLA-A2.1) transgenic mice with these recombinant viruses did not result in significant SARS-CoV-2-specific T-cell responses, due to the immunodominance of NP366 influenza T-cell epitope. However, side-by-side stimulation of peripheral blood mononuclear cells (PBMCs) of COVID-19 convalescents with recombinant viruses and LAIV vector demonstrated activation of memory T cells in samples stimulated with LAIV/SARS-CoV-2, but not LAIV alone. Hamsters immunized with a selected LAIV/SARS-CoV-2 prototype were protected against challenge with influenza virus and a high dose of SARS-CoV-2 of Wuhan and Delta lineages, which was confirmed by reduced weight loss, milder clinical symptoms and less pronounced histopathological signs of SARS-CoV-2 infection in the lungs, compared to LAIV- and mock-immunized animals. Overall, LAIV is a promising platform for the development of a bivalent vaccine against influenza and SARS-CoV-2. [ABSTRACT FROM AUTHOR]

Peptide immunotherapy (PIT) represents a safe and efficacious therapeutic regimen with in-consequential side-effects. The present study aims to identify T-cell epitopes of Per a 5 allergen, a delta class GST from Periplaneta americana and investigate effect of peptide treatment in murine model of cockroach allergen-mediated hyper-reactivity. The epitopes (TC-P1, TC-P2, and TC-P3) were identified as promiscuous MHC-II binders by MHC-Pred, ProPred, and IEDB analysis tool. Murine model of cockroach allergic hyper-reactivity was generated in Balb/c mice. A marked reduction in cellular infiltration in lungs (3-fold compared with Non-IT) was observed in T3-IT group as evidenced by total leucocyte count in BALF and histology. Specific IgE levels were reduced 3-fold in T2-IT and T3-IT compared with Non-IT with increase in IgG2a levels. IL-4 and IL-13 were reduced upto 2.5-fold in treatment groups compared with Non-IT group. Splenocytes revealed significant increase in levels of CD4+FoxP3+ T cells in TC-P1 and TC-P2 mice demonstrating a systemic shift towards Tregs. Peptide treatment downregulated NF-kB signalling in lung and enhanced the levels of immune-regulatory molecules α1-antitrypsin and elafin. Our results indicate that TC-P1 and TC-P3 alter Th2 cytokine milieu and antibody isotype ratio to suppress allergic inflammation. PIT modulates local and systemic mechanisms to resolve inflammation and possess potential for treatment in cockroach allergy. Per a 5-derived T-cell peptides TC-P1 and TC-P3 resolved pulmonary inflammation by expansion of T regulatory cells and downregulation of NF-kB signalling in cockroach allergy hypersensitivity murine model. [ABSTRACT FROM AUTHOR]

Tilapia tilapinevirus, known worldwide as tilapia lake virus (TiLV), is a single-stranded RNA virus that belongs to the Amnoonviridae family. The virus attacks the fish species' external and internal organs, such as the eyes, brain, and liver. Syncytial cells develop in the liver cells of infected fish, which are characterized by widespread hepatocellular necrosis and karyolytic nuclei. It is a highly infectious virus that spreads both horizontally and vertically. Despite these devastating complications, there is still no cure or vaccine for the virus. Therefore, a vaccine based on epitopes developed using immunoinformatics methods was developed against TiLV in fish. The putative polymerase basic 1 (PB1) gene was used to identify immunodominant T- and B-cell epitopes. Three probable epitopes were used to design the vaccine: CTL, HTL, and LBL. Testing of the final vaccine revealed that it was antigenic, non-allergenic, and has improved solubility. Molecular dynamics simulation revealed significant structural compactness and binding stability. Furthermore, the computer-generated immunological simulation indicated that immunization might stimulate real-life immune responses following injection. Overall, the findings of the study imply that the designed epitope vaccine might be a good option for prophylaxis for TiLV. [ABSTRACT FROM AUTHOR]

The recent success of monoclonal antibody checkpoint inhibitor therapies that enhance the ability of CD8+ T cells to detect cancer‐related antigenic peptides has refocused the need to fully understand the repertoire of peptides being presented to the immune system. Whilst the peptide ligandome presented by cell surface human leucocyte antigen class I (HLA‐I) molecules on cancer cells has been studied extensively, the ligandome of extracellular vesicles (EVs) remains poorly defined. Here, we report the HLA‐I ligandome of both the cell surface and EVs from eight breast cancer cell lines (MCF7, MDA‐MB‐231, MDA‐MB‐361, MDA‐MB‐415, MDA‐MB‐453, HCC 1806, HCC 1395, and HCC 1954), and additionally the melanoma cell line ESTDAB‐056 and the multiple myeloma line RPMI 8226. Utilizing HLA‐I immunoisolation and mass spectrometry, we detected a total of 6574 peptides from the cell surface and 2461 peptides from the EVs of the cell lines studied. Within the EV HLA‐I ligandome, we identified 150 peptides derived from tumour associated antigenic proteins, of which 19 peptides have been shown to elicit T‐cell responses in previous studies. Our data thus show the prevalence of clinically relevant tumour‐associated antigenic peptides in the HLA‐I ligandome presented on EV. [ABSTRACT FROM AUTHOR]

Dengue outbreaks are a serious public health concern that occurs on a regular basis in various locations of India. According to the Government of India's National Center for Vector-Borne Disease Control, a total of 1,23,106 dengue cases were identified in India as of October 2021. The currently available dengue vaccine was found to be ineffective against all serotypes of the virus. Dengue virus serotype 2 was reported to be the sole predominant serotype in Eastern Uttar Pradesh, India. An epitope-based peptide vaccine is believed to be safe and effective against all serotypes of the dengue virus. In this work, an epitope-based peptide vaccine based on envelope protein against the dengue virus was developed using the reverse vaccinology method. T-cell epitopes present in the envelope protein were screened using different immunoinformatic tools. Epitopes predicted by all servers were chosen and additionally picked out on the grounds of their antigenic reactivity, immunogenicity, toxicity, and allergenicity assessment. Three potent T cell epitopes as IVQPENLEY, ILIGVVITW, and DTAWDFGSL were screened, which binds with HLA-B*35:01, HLA-B*58:01, HLA-A*26:01 alleles, respectively. To build a 3D structure model of epitopes and alleles, the PepstrMod and Swiss-Model servers were used. Predicted epitopes and HLA alleles were docked using the HPEPDOCK server to confirm binding ability. These anticipated epitopes were found to cover the greatest number of populations in India and around the world. These identified epitopes have a high potential for eliciting an immune response in the development of a vaccine against the dengue virus, while further experimental validation is required for final confirmation. [ABSTRACT FROM AUTHOR]

Computational prediction to screen potential vaccine candidates has been proven to be a reliable way to provide guarantees for vaccine discovery in infectious diseases. As an important class of organisms causing infectious diseases, pathogenic eukaryotes (such as parasitic protozoans) have evolved the ability to colonize a wide range of hosts, including humans and animals; meanwhile, protective vaccines are urgently needed. Inspired by the immunological idea that pathogen-derived epitopes are able to mediate the CD8+ T-cell-related host adaptive immune response and with the available positive and negative CD8+ T-cell epitopes (TCEs), we proposed a novel predictor called CD8TCEI-EukPath to detect CD8+ TCEs of eukaryotic pathogens. Our method integrated multiple amino acid sequence-based hybrid features, employed a well-established feature selection technique, and eventually built an efficient machine learning classifier to differentiate CD8+ TCEs from non-CD8+ TCEs. Based on the feature selection results, 520 optimal hybrid features were used for modeling by utilizing the LightGBM algorithm. CD8TCEI-EukPath achieved impressive performance, with an accuracy of 79.255% in ten-fold cross-validation and an accuracy of 78.169% in the independent test. Collectively, CD8TCEI-EukPath will contribute to rapidly screening epitope-based vaccine candidates, particularly from large peptide-coding datasets. To conduct the prediction of CD8+ TCEs conveniently, an online web server is freely accessible (http://lab.malab.cn/∼hrs/CD8TCEI-EukPath/).

COVID-19 brought scenes from sci-fi movies into real life. Infected individuals include asymptomatic cases to severe disease leading to death, suggesting the involvement of the genetic constitution of populations and pathogens contributing to differential individuals’ outcomes. To investigate shared immunogenic features between SARS-CoV-2 targets and other coronaviruses, we modeled their peptides in 3D structures of HLA-A*02:01 (pMHC), comparing their molecular surfaces These structures were also compared with a panel of epitopes from unrelated viruses, looking for potential triggers conferring cross-protection in uninfected individuals. As expected, SARS-CoV 1 and 2 peptides share molecular and physicochemical features, providing an explanation for the verified experimental immunogenicity among them. Surprisingly, even discordant sequences from human coronaviruses 229E, OC43 and epitopes from unrelated viruses involved in endemic human infections exhibit similar fingerprints of immunogenicity with SARS-CoV-2 peptides. The same approach indicates a conserved CD8+ T cell recognition between Wuhan SARS-CoV-2 sequences and altered peptides from Variants of Concern. Examination of structural data over epitope sequence analysis here could explain how previous infections may produce a heterologous immunity response in a global scale against emergent diseases such as Covid-19, mitigating its full lethal potential, and paves the way for the development of wide spectrum vaccine development.

Celiac disease (CeD) is an autoimmune enteropathy induced by prolamin and glutelin proteins in wheat, barley, rye, and triticale recognized by genetically restricted major histocompatibility (MHC) receptors. Patients with CeD must avoid consuming these proteins. Regulators in Europe and the United States expect an evaluation of CeD risks from proteins in genetically modified (GM) crops or novel foods for wheat-related proteins. Our database includes evidence-based causative peptides and proteins and two amino acid sequence comparison tools for CeD risk assessment. Sequence entries are based on the review of published studies of specific gluten-reactive T cell activation or intestinal epithelial toxicity. The initial database in 2012 was updated in 2018 and 2022. The current database holds 1,041 causative peptides and 76 representative proteins. The FASTA sequence comparison of 76 representative CeD proteins provides an insurance for possible unreported epitopes. Validation was conducted using protein homologs from Pooideae and non-Pooideae monocots, dicots, and non-plant proteins. Criteria for minimum percent identity and maximum E-scores are guidelines. Exact matches to any of the 1,041 peptides suggest risks, while FASTA alignment to the 76 CeD proteins suggests possible risks. Matched proteins should be tested further by CeD-specific CD4/8+ T cell assays or in vivo challenges before their use in foods.

Identification of relevant epitopes is crucial for the development of subunit peptide vaccines inducing neutralizing and cellular immunity against SARS-CoV-2. Our aim was the characterization of epitopes in the receptor-binding domain (RBD) of SARS-CoV-2 spike (S) protein to generate a peptide vaccine. Epitope mapping using a panel of 10 amino acid overlapped 15-mer peptides covering region 401-515 from RBD did not identify linear epitopes when tested with sera from infected individuals or from RBD-immunized mice. However, immunization of mice with these 15-mer peptides identified four peptides located at region 446-480 that induced antibodies recognizing the peptides and RBD/S1 proteins. Immunization with peptide 446-480 from S protein formulated with Freund’s adjuvant or with CpG oligodeoxinucleotide/Alum induced polyepitopic antibody responses in BALB/c and C56BL/6J mice, recognizing RBD (titres of 3 × 104–3 × 105, depending on the adjuvant) and displaying neutralizing capacity (80–95% inhibition capacity; p

Background: Pulmonary tuberculosis (PTB) is still a major health problem worldwide. The espD has a potential to be a new biomarker because it is important for the espA, espC, and ESX-1 protein secretion system that are actively expressed in active multiplication of Mycobacterium tuberculosis complex. Methods: A total of 55 sputum samples and 41 culture isolates from newly diagnosed PTB patients at Dr. Soetomo Academic Hospital were collected from September 2016 to April 2019. The tested samples using polymerase chain reaction targeted 555 bp of espD gene and sequencing. Clone Manager Version 6 and NCBI BLAST were used to align the gene sequence against wild-type M. tuberculosis. The prediction of T-cell epitope in espD gene was detected by GENETYX. The three-dimensional (3D) structure of espD was modeled by SWISS-MODEL and I-TASSER and was visualized with PyMOL. Results: From 55 sputum samples, 43 (78.18%) showed positive results, and all culture isolates showed positive results. In addition, all sequenced samples showed 100% homolog with M. tuberculosis H37Rv gene without detected variant or mutation. There were four T-cell epitopes that could be obtained. The 3D model had a I-TASSER confidence score of 3.91 with estimated RMSD of approximately 14.5 Å. The structure consists of a main fold of a three-stranded antiparallel β-sheet and a long α-helix surrounded by several minor secondary structures. Conclusions: This study provides a brief information about the sequence, epitope prediction, and 3D structure of EspD protein from M. tuberculosis strains in Indonesia.

Coronavirus disease 2019 (COVID-19) is the most devastating pandemic of the century, which is still far from over. The remarkable success of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines is the working hope, but the evolving variants are the huge concern that can turn the tide. Potential immune escape mutations (PIEMs) in the past and circulating variants were not studied at large scale (all available data). Hence, the conservation of antigenic determinants (epitopes) was analyzed in all available sequences of SARS-CoV-2 according to time (months), proteins, hosts, and variants. Numerous highly conserved B- and T-cell epitopes were identified in 24 proteins of SARS-CoV-2. A decrease in the conservation of epitopes with time was observed in almost all proteins, which was more rapid in neutralizing epitopes. Delta variant still has the highest PIEM in the circulating strains, which pose threat to the effectiveness of current vaccines. The inclusion of identified, highly conserved, and important epitopes in subunit vaccines can increase vaccine effectiveness against evolving variants. Trends in the conservation of epitopes in different proteins, hosts, and variants with time may also help to inspire the counter measure against the current pandemic. [ABSTRACT FROM AUTHOR]

Since the first outbreak of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019, its high infectivity led to its prevalence around the world in an exceptionally short time. Efforts have been made to control the ongoing outbreak, and among them, vaccine developments are going on high priority. New clinical trials add to growing evidence that vaccines from many countries were highly effective at preventing SARS-CoV-2 virus infection. One of them is B cell-based vaccines, which were common during a pandemic. However, neutralizing antibody therapy becomes less effective when viruses mutate. In order to tackle the problem, we focused on T-cell immune mechanism. In this study, the mutated strains of the virus were selected globally from India (B.1.617.1 and B.1.617.2), United Kingdom (B.1.1.7), South Africa (B.1.351), and Brazil (P.1), and the overlapping peptides were collected based on mutation sites of S-protein. After that, residue scanning was used to predict the affinity between overlapping peptide and HLA-A*11:01, the most frequent human leukocyte antigen (HLA) allele among the Chinese population. Then, the binding free energy was evaluated with molecular docking to further verify the affinity changes after the mutations happen in the virus genomes. The affinity test results of three epitopes on spike protein from experimental validation were consistent with our predicted results, thereby supporting the inclusion of the epitope 374FSTFKCYGL382 in future vaccine design and providing a useful reference route to improve vaccine development. [ABSTRACT FROM AUTHOR]