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Identifying epitopes and their corresponding T-cell receptor (TCR) sequences is crucial in the face of rapidly mutating viruses. Peptide synthesis is often required to confirm the exact epitope sequences, which is time-consuming and expensive. In this study, we introduce a scalable workflow to identify the exact sequences of virus epitopes and reactive TCRs targeting the epitopes from memory T cells. Following the narrowing down of epitopes to specific regions via the tandem minigene (TMG) system, our workflow incorporates the utilization of peptide-major histocompatibility complex-displaying yeasts (pMHC-displaying yeasts) to rapidly screen immunogenic epitopes' precise sequences, obviating the necessity for the chemical synthesis of peptides. Focusing on SARS-CoV-2, we identify the precise sequences of reactive TCRs, targeting conserved epitopes across the Coronaviridae family, from the blood of COVID-19-recovered individuals over 8 months. Notably, we reveal that at least 75% (6/8) of the tested donors harbor T cells targeting a shared epitope, KTFPPTEPK, derived from the N protein. Furthermore, several identified TCRs exhibit cross-reactivity to mutant epitopes, suggesting a potential mechanism for sustained T-cell responses against emerging SARS-CoV-2 variants. A scalable workflow involving a pMHC-displaying yeast system is introduced to identify precise virus epitope sequences and corresponding T-cell receptor (TCR) sequences from memory T cells. [ABSTRACT FROM AUTHOR]

Advances in mass spectrometry accelerates the characterization of HLA ligandome, necessitating the development of efficient methods for immunopeptidomics analysis and (neo)antigen prediction. We develop ImmuneApp, an interpretable deep learning framework trained on extensive HLA ligand datasets, which improves the prediction of HLA-I epitopes, prioritizes neoepitopes, and enhances immunopeptidomics deconvolution. ImmuneApp extracts informative embeddings and identifies key residues for pHLA binding. We also present a more accurate model-based deconvolution approach and systematically analyzed 216 multi-allelic immunopeptidomics samples, identifying 835,551 ligands restricted to over 100 HLA-I alleles. Our investigation reveals the effectiveness of the composite model, denoted as ImmuneApp-MA, which integrates mono- and multi-allelic data to enhance predictive performance. Leveraging ImmuneApp-MA as a pre-trained model, we built ImmuneApp-Neo, an immunogenicity predictor that outperforms existing methods for prioritizing immunogenic neoepitope. ImmuneApp demonstrates its utility across various immunopeptidomics datasets, which will promote the discovery of novel neoantigens and the development of new immunotherapies. The identification of HLA epitopes is essential for vaccine and immunotherapy development. Here, authors develop ImmuneApp using deep learning on extensive immunopeptidomics data, advancing antigen presentation prediction, neoepitope prioritisation, and immunopeptidomics deconvolution. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic continues to cause infections and deaths, which are attributable to the SARS-CoV-2 Omicron variant of concern (VOC). Moderna's response to the declining protective efficacies of current SARS-CoV-2 vaccines against Omicron was to develop a bivalent booster vaccine based on the Spike (S) protein from the Wuhan and Omicron BA.4/BA.5 strains. This approach, while commendable, is unfeasible in light of rapidly emerging mutated viral strains. PubMed and Google Scholar were systematically reviewed for peer-reviewed papers up to January 2024. Articles included focused on specific themes such as the clinical history of recombinant protein vaccine development against different diseases, including COVID-19, the production of recombinant protein vaccines using different host expression systems, aspects to consider in recombinant protein vaccine development, and overcoming problems associated with large-scale recombinant protein vaccine production. In silico approaches to identify conserved and immunogenic epitopes could provide broad protection against SARS-CoV-2 VOCs but require validation in animal models. The recombinant protein vaccine development platform has shown a successful history in clinical development. Recombinant protein vaccines incorporating conserved epitopes may utilize a number of expression systems, such as yeast (Saccharomyces cerevisiae), baculovirus-insect cells (Sf9 cells), and Escherichia coli (E. coli). Current multi-epitope subunit vaccines against SARS-CoV-2 utilizing synthetic peptides are unfeasible for large-scale immunizations. Recombinant protein vaccines based on conserved and immunogenic proteins produced using E. coli offer high production yields, convenient purification, and cost-effective production of large-scale vaccine quantities capable of protecting against the SARS-CoV-2 D614G strain and its VOCs. [ABSTRACT FROM AUTHOR]

During pregnancy the immune system needs to maintain immune tolerance of the foetus while also responding to infection, which can cause premature activation of the inflammatory pathways leading to the onset of labour and preterm birth. The vaginal microbiome is an important modifier of preterm birth risk, with Lactobacillus dominance during pregnancy associated with term delivery while high microbial diversity is associated with an increased risk of preterm birth. Glycans on glycoproteins along the lower female reproductive tract are fundamental to microbiota-host interactions and the mediation of inflammatory responses. However, the specific glycan epitopes involved in these processes are not well understood. To address this, we conducted glycomic analyses of cervicovaginal fluid (CVF) from 36 pregnant women at high risk of preterm birth and 4 non-pregnant women. Our analysis of N- and O-glycans revealed a rich CVF glycome. While O-glycans were shown to be the main carriers of ABO blood group epitopes, the main features of N-glycans were the presence of abundant paucimannose and high mannose glycans, and a remarkable diversity of complex bi-, tri-, and tetra-antennary glycans decorated with fucose and sialic acid. We identified immuno-regulatory epitopes, such as Lewis antigens, and found that fucosylation was negatively correlated to pro-inflammatory factors, such as IL-1β, MMP-8, C3a and C5a, while glycans with only sialylated antennae were mainly positively correlated to those. Similarly, paucimannose glycans showed a positive correlation to pro-inflammatory factors. We revealed a high abundance of glycans which have previously been identified as hallmarks of cancer and viral glycosylation, such as Man8 and Man9 high mannose glycans. Although each pregnant woman had a unique glycomic profile, longitudinal studies showed that the main glycosylation features were consistent throughout pregnancy in women who delivered at term, whereas women who experienced extreme preterm birth exhibited sharp changes in the CVF glycome shortly before delivery. These findings shed light on the processes underlying the role of glycosylation in maintaining a healthy vaginal microbiome and associated host immune responses. In addition, these discoveries facilitate our understanding of the lower female reproductive tract which has broad implications for women's health. [ABSTRACT FROM AUTHOR]

Coagulation factor replacement therapy for the X-linked bleeding disorder Haemophilia, characterized by a deficiency of coagulation protein factor VIII (FVIII), is severely complicated by antibody (inhibitors) formation. The development of FVIII inhibitors drastically alters the quality of life of the patients and is associated with a tremendous increase in morbidity as well as treatment costs. The ultimate goal of inhibitor control is antibody elimination. Immune tolerance induction (ITI) is the only clinically established approach for developing antigen-specific tolerance to FVIII. This work aims to establish a novel cost-effective strategy to produce FVIII molecules in fusion with cholera toxin B (CTB) subunit at the N terminus using the Bacillus subtilis expression system for oral tolerance, as the current clinical immune tolerance protocols are expensive. Regions of B-Domain Deleted (BDD)-FVIII that have potential epitopes were identified by employing Bepipred linear epitope prediction; 2 or more epitopes in each domain were combined and cDNA encoding these regions were fused with CTB and cloned in the Bacillus subtilis expression vector pHT43 and expression analysis was carried out. The expressed CTB-fused FVIII epitope domains showed strong binding affinity towards the CTB-receptor GM1 ganglioside. To conclude, Bacillus subtilis expressing FVIII molecules might be a promising candidate for exploring for the induction of oral immune tolerance. [ABSTRACT FROM AUTHOR]

Immunoglobulin E (IgE) plays pivotal roles in allergic diseases through interaction with a high-affinity receptor (FcεRI). We established that Fab fragments of anti-IgE antibodies (HMK-12 Fab) rapidly dissociate preformed IgE-FcεRI complexes in a temperature-dependent manner and inhibit IgE-mediated anaphylactic reactions, even after allergen challenge. X-ray crystallographic studies revealed that HMK-12 Fab interacts with each of two equivalent epitopes on the Cε2 homodimer domain involved in IgE F(ab')2. Consequently, HMK-12 Fab-mediated targeting of Cε2 reduced the binding affinity of Fc domains and resulted in rapid removal of IgE from the receptor complex. This unexpected finding of allosteric inhibition of IgE-FcεRI interactions by simultaneous targeting of two epitope sites on the Cε2 homodimer domain of IgE F(ab')2 may have implications for the development of novel therapies for allergic disease. The authors show that the allosteric inhibition of the interactions between Immunoglobulin E and the high-affinity receptor FcεRI by targeting two epitope sites of IgE may have implications for the development of novel therapies for allergic diseases. [ABSTRACT FROM AUTHOR]

Porcine epidemic diarrhea virus (PEDV) is a serious disease that poses a significant threat to the pig industry. This study focused on analyzing the Spike protein of PEDV, which harbors crucial antigenic determinants, in identifying dominant epitopes. Immunoinformatics tools were used to screen for B-cell, CD4+ and CD8+ predominance epitopes. These epitopes were then connected to the N-terminal of ferritin to form a self-assembled nanoparticle vaccine. Various physical and chemical properties of the candidate vaccine were analyzed, including secondary structure prediction, tertiary structure modeling, molecular docking, immune response simulation and computer cloning. The results demonstrated that the candidate vaccine was antigenic, soluble, stable, non-allergic, and formed a stable complex with the target receptor TLR-3. Immune simulation analysis showed that the candidate vaccine effectively stimulated both cellular and humoral reactions, leading to increased related cytokines production. Furthermore, efficient and stable expression of the candidate vaccine was achieved through reverse translation in the Escherichia coli K12 expression system following codon optimization and in silico cloning. The developed nanoparticle candidate vaccine in this study holds promise as an effective PEDV vaccine candidate, offering a new approach for the research, development and improvement of vaccines targeting porcine enteric diarrhea coronavirus. [ABSTRACT FROM AUTHOR]

HIV-1 envelope glycoproteins (Envs) of most primary HIV-1 strains exist in closed conformation and infrequently sample open states, limiting access to internal epitopes. Thus, immunogen design aims to mimic the closed Env conformation as preferred target for eliciting broadly neutralizing antibodies (bnAbs). Here we identify incompletely closed Env conformations of 6 out of 13 transmitted/founder (T/F) strains that are sensitive to antibodies that recognize internal epitopes typically exposed on open Envs. A 3.6 Å cryo-electron microscopy structure of unliganded, incompletely closed T/F Envs (1059-SOSIP) reveals protomer motion that increased sampling of states with incompletely closed trimer apex. We reconstruct de novo the post-transmission evolutionary pathway of a second T/F. Evolved viruses exhibit increased Env resistance to cold, soluble CD4 and 19b, all of which correlate with closing of the adapted Env trimer. Lastly, we show that the ultra-broad N6 bnAb efficiently recognizes different Env conformations and exhibits improved antiviral breadth against VRC01-resistant Envs isolated during the first-in-humans antibody-mediated-prevention trial. HIV-1 is a formidable target for vaccine development. Here, Parthasarathy et al. show that envelope glycoproteins of some HIV-1 primary strains exhibit inherent conformational flexibility that may contribute to HIV-1 evasion from neutralizing antibodies. [ABSTRACT FROM AUTHOR]

Context: Flaviviruses cause severe encephalitic or hemorrhagic diseases in humans. Its members, Kyasanur forest disease virus (KFDV) and Alkhumra hemorrhagic fever virus (ALKV), cause hemorrhagic fever and are prevalent in India and Saudi Arabia, respectively, while the tick-borne encephalitis virus (TBEV) causes a dangerous encephalitic infection in Europe and Asia. However, little information is available about the targets of immune responses for these deadly viruses. Here, we predict potential antigenic peptide epitopes of viral envelope protein for inducing a cell-mediated and humoral immune response. Methods: Using the Immune Epitope Database and Analysis Resource (IEDB-AR), we identified 13 MHC-I and two MHC-II dominant conserved epitopes in KFDV and ALKV and six MHC-I and three MHC-II epitopes in TBEV envelope proteins. Parallelly, we also predicted B-cell linear and discontinuous envelope protein epitopes for these viruses. Interestingly, the epitopes are conserved in all three viral envelope proteins. Further, the discontinuous epitopes are structurally compared with the available DENV, ZIKV, WNV, TBEV, and LIV envelope protein antibody structures. Overall structural comparison analyses highlight (i) lateral ridge epitope in the ED-III domain of E protein, and (ii) envelope dimer epitope (EDE) could be targeted for developing potent vaccine candidates as well as therapeutic antibody production. Moreover, existing structural and biochemical functions of the same epitopes in homologous viruses are predicted to have a reduced antibody-dependent enhancement (ADE) effect on flaviviral infection. [ABSTRACT FROM AUTHOR]

The Middle East has witnessed a greater spread of infectious Dengue viruses, with serotype 2 (DENV-2) being the most prevalent form. Through this work, multi-epitope peptide vaccines against DENV-2 that target E and nonstructural (NS1) proteins were generated through an immunoinformatic approach. MHC class I and II and LBL epitopes among NS1 and envelope E proteins sequences were predicted and their antigenicity, toxicity, and allergenicity were investigated. Studies of the population coverage denoted the high prevalence of NS1 and envelope-E epitopes among different countries where DENV-2 endemic. Further, both the CTL and HTL epitopes retrieved from NS1 epitopes exhibited high conservancies' percentages with other DENV serotypes (1, 3, and 4). Three vaccine constructs were created and the expected immune responses for the constructs were estimated using C-IMMSIM and HADDOCK (against TLR 2,3,4,5, and 7). Molecular dynamics simulation for vaccine construct 2 with TLR4 denoted high binding affinity and stability of the construct with the receptor which might foretell favorable in vivo interaction and immune responses. [ABSTRACT FROM AUTHOR]

Arthropod-borne viruses represent a crucial public health threat. Current arboviral serology assays are either labor intensive or incapable of distinguishing closely related viruses, and many zoonotic arboviruses that may transition to humans lack any serologic assays. In this study, we present a programmable phage display platform, ArboScan, that evaluates antibody binding to overlapping peptides that represent the proteomes of 691 human and zoonotic arboviruses. We confirm that ArboScan provides detailed antibody binding information from animal sera, human sera, and an arthropod blood meal. ArboScan identifies distinguishing features of antibody responses based on exposure history in a Colombian cohort of Zika patients. Finally, ArboScan details epitope level information that rapidly identifies candidate epitopes with potential protective significance. ArboScan thus represents a resource for characterizing human and animal arbovirus antibody responses at cohort scale. Arboviruses are transmitted by arthropods and include a number of critical human and zoonotic pathogens. Here the authors report a phage display library, ArboScan, for evaluating antibody binding to the peptidome of 691 human and zoonotic arthropod borne viruses, and use it to profile anti-arbovirus antibodies from diverse samples. [ABSTRACT FROM AUTHOR]

Respirovirus 3 is a leading cause of severe acute respiratory infections in vulnerable human populations. Entry into host cells is facilitated by the attachment glycoprotein and the fusion glycoprotein (F). Because of its crucial role, F represents an attractive therapeutic target. Here, we identify 13 F-directed heavy-chain-only antibody fragments that neutralize recombinant respirovirus 3. High-resolution cryo-EM structures of antibody fragments bound to the prefusion conformation of F reveal three distinct, previously uncharacterized epitopes. All three antibody fragments bind quaternary epitopes on F, suggesting mechanisms for neutralization that may include stabilization of the prefusion conformation. Studies in cotton rats demonstrate the prophylactic efficacy of these antibody fragments in reducing viral load in the lungs and nasal passages. These data highlight the potential of heavy-chain-only antibody fragments as effective interventions against respirovirus 3 infection and identify neutralizing epitopes that can be targeted for therapeutic development. Respirovirus 3 is a major cause of respiratory infection. Here authors generate and explore heavy-chain antibody fragments that target the fusion protein and test these in vitro and in an animal model. [ABSTRACT FROM AUTHOR]

Reticulocyte-binding protein homologue 5 (RH5), a leading blood-stage Plasmodium falciparum malaria vaccine target, interacts with cysteine-rich protective antigen (CyRPA) and RH5-interacting protein (RIPR) to form an essential heterotrimeric "RCR-complex". We investigate whether RCR-complex vaccination can improve upon RH5 alone. Using monoclonal antibodies (mAbs) we show that parasite growth-inhibitory epitopes on each antigen are surface-exposed on the RCR-complex and that mAb pairs targeting different antigens can function additively or synergistically. However, immunisation of female rats with the RCR-complex fails to outperform RH5 alone due to immuno-dominance of RIPR coupled with inferior potency of anti-RIPR polyclonal IgG. We identify that all growth-inhibitory antibody epitopes of RIPR cluster within the C-terminal EGF-like domains and that a fusion of these domains to CyRPA, called "R78C", combined with RH5, improves the level of in vitro parasite growth inhibition compared to RH5 alone. These preclinical data justify the advancement of the RH5.1 + R78C/Matrix-M™ vaccine candidate to Phase 1 clinical trial. RH5, which is part of the trimeric RCR-complex essential for invasion, is a vaccine candidate for malaria. Here, Williams et al. show that monoclonal antibodies targeting each of the three proteins in the RCR-complex can work together to more effectively block the invasion of red blood cells by Plasmodium falciparum and design a combination vaccine candidate. [ABSTRACT FROM AUTHOR]

Aim: This study was undertaken to explicate the shared and distinctive genetic susceptibility and immune dysfunction in patients with T1D alone and T1D with CD (T1D + CD). Methods: A total of 100 T1D, 50 T1D + CD and 150 healthy controls were recruited. HLA-DRB1/DQB1 alleles were determined by PCR-sequence-specific primer method, SNP genotyping for CTLA-4 and PTPN22 was done by simple probe-based SNP-array and genotyping for INS-23 Hph1 A/T was done by RFLP. Autoantibodies and cytokine estimation was done by ELISA. Immune-regulation was analysed by flow-cytometry. Clustering of autoantigen epitopes was done by epitope cluster analytical tool. Results: Both T1D alone and T1D + CD had a shared association of DRB1*03:01, DRB1*04, DRB3*01:07/15 and DQB1*02. DRB3*01:07/15 confers the highest risk for T1D with relative risk of 11.32 (5.74–22.31). Non-HLA gene polymorphisms PTPN22 and INS could discriminate between T1D and T1D + CD. T1D + CD have significantly higher titers of autoantibodies, expression of costimulatory molecules on CD4 and CD8 cells, and cytokine IL-17A and TGF-β1 levels compared to T1D patients. Epitopes from immunodominant regions of autoantigens of T1D and CD clustered together with 40% homology. Conclusion: Same HLA genes provide susceptibility for both T1D and CD. Non-HLA genes CTLA4, PTPN22 and INS provide further susceptibility while different polymorphisms in PTPN22 and INS can discriminate between T1D and T1D + CD. Epitope homology between autoantigens of two diseases further encourages the two diseases to occur together. The T1D + CD being more common in females along with co-existence of thyroid autoimmunity, and have more immune dysregulated state than T1D alone. [ABSTRACT FROM AUTHOR]

The names Coccoloba caracasana, C. caracasana f. glabra, C. cozumelensis, C. floribunda, C. humboldtii var. longipedicellata, and Campderia mexicana are lectotypified, and seventeen specimens with mature fruits are proposed as epitypes to facilitate the recognition and delimitation of Coccoloba species distributed in Mexico and Central America. The presence of fruits in these specimens allowed us to recognize and reinstate the names Coccoloba lapathifolia, C. euvelutina, and C. matudae. [ABSTRACT FROM AUTHOR]

The development and creation of a new generation vaccines based on recombinant proteins that assemble into virus-like particles (VLPs), as well as recombinant proteins in the form of nanoparticles, are promising directions in modern biotechnology. Due to their large size (20–200 nm) and multiplicity of viral antigenic determinants on the surface, VLPs can stimulate strong humoral and cellular immune responses. The main types of VLPs, as well as the features and disadvantages of the main expression systems used for their biosynthesis, are considered in this review. The main focus was on plant expression systems that ensure the biosynthesis of a target recombinant protein from a DNA matrix integrated into the nuclear or chloroplast genomes of a plant (stable expression) or from a matrix for temporary production of the target product (transient expression). Various approaches for increasing the yield of VLP-forming recombinant proteins, including fusion with a transit peptide that directed the protein into the chloroplast, were discussed. The possibility of accumulation of recombinant proteins expressed in plants and intended for creation of VLP-vaccines in another type of nanoparticle, protein bodies, using specific signal sequences was also considered. [ABSTRACT FROM AUTHOR]

Efficiently cleaved HIV-1 Envs are the closest mimics of functional Envs as they specifically expose only bNAb (broadly neutralizing antibody) epitopes and not non-neutralizing ones, making them suitable for developing vaccine immunogens. We have previously identified several efficiently cleaved Envs from clades A, B, C and B/C. We also described that truncation of the CT (C-terminal tail) of a subset of these Envs, but not others, impairs their ectodomain conformation/antigenicity on the cell surface in a CT conserved hydrophilic domain (CHD) or Kennedy epitope (KE)-dependent manner. Here, we report that those Envs (4 − 2.J41 and JRCSF), whose native-like ectodomain conformation/antigenicity on the cell surface is disrupted upon CT truncation, but not other Envs like JRFL, whose CT truncation does not have an effect on ectodomain integrity on the cell surface, are also defective in retrograde transport from early to late endosomes. Restoration of the CHD/KE in the CT of these Envs restores wild-type levels of distribution between early and late endosomes. In the presence of retrograde transport inhibitor Retro 2, cell surface expression of 4 − 2.J41 and JRCSF Envs increases [as does in the presence of Rab7a DN and Rab7b DN (DN: dominant negative)] but particle formation decreases for 4 − 2.J41 and JRCSF Env pseudotyped viruses. Our results show for the first time a correlation between CT-dependent, CHD/KE regulated retrograde transport and cell surface expression/viral particle formation of these efficiently cleaved Envs. Based on our results we hypothesize that a subset of these efficiently cleaved Envs use a CT-dependent, CHD/KE-mediated mechanism for assembly and release from late endosomes. [ABSTRACT FROM AUTHOR]

Respiratory syncytial virus (RSV) is one of the most important pathogens causing respiratory tract infection in humans, especially in infants and the elderly. The identification and structural resolution of the potent neutralizing epitopes on RSV fusion (F) protein enable an "epitope-focused" vaccine design. However, the display of RSV F epitope II on the surface of the widely-used human hepatitis B virus core antigen (HBcAg) has failed to induce neutralizing antibody response in mice. Here, we used the hepadnavirus core protein (HcAg) from different mammalian hosts as scaffolds to construct chimeric virus-like particles (VLPs) presenting the RSV F epitope II. Mouse immunization showed that different HcAg-based chimeric VLPs elicited significantly different neutralizing antibody responses, among which the HcAg derived from roundleaf bat (RBHcAg) is the most immunogenic. Furthermore, RBHcAg was used as the scaffold platform to present multiple RSV F epitopes, and the immunogenicity was further improved in comparison to that displaying a single epitope II. The designed RBHcAg-based multiple-epitope-presenting VLP formulated with MF59-like adjuvant elicited a potent and balanced Th1/Th2 immune response, and offered substantial protection in mice against the challenge of live RSV A2 virus. The designed chimeric VLPs may serve as the potential starting point for developing epitope-focused vaccines against RSV. Our study also demonstrated that RBHcAg is an effective VLP carrier for presenting foreign epitopes, providing a promising platform for epitope-focused vaccine design. [ABSTRACT FROM AUTHOR]

Bispecific antibodies are a successful and expanding therapeutic class. Standard approaches to generate bispecifics are complicated by the need for disulfide reduction/oxidation or specialized formats. Here we present SpyMask, a modular approach to bispecifics using SpyTag/SpyCatcher spontaneous amidation. Two SpyTag-fused antigen-binding modules can be precisely conjugated onto DoubleCatcher, a tandem SpyCatcher where the second SpyCatcher is protease-activatable. We engineer a panel of structurally-distinct DoubleCatchers, from which binders project in different directions. We establish a generalized methodology for one-pot assembly and purification of bispecifics in 96-well plates. A panel of binders recognizing different HER2 epitopes were coupled to DoubleCatcher, revealing unexpected combinations with anti-proliferative or pro-proliferative activity on HER2-addicted cancer cells. Bispecific activity depended sensitively on both binder orientation and DoubleCatcher scaffold geometry. These findings support the need for straightforward assembly in different formats. SpyMask provides a scalable tool to discover synergy in bispecific activity, through modulating receptor organization and geometry. Bispecific antibody architecture is often important for function but rarely optimized. Here, authors present a modular approach to assemble bispecifics in varied formats using a SpyTag/SpyCatcher approach called SpyMask, and build anti-HER2 bispecifics whose activities depend on binder orientation and bispecific geometry. [ABSTRACT FROM AUTHOR]

As part of an ongoing taxonomic study of the genus Deyeuxia, typifications for 12 names belonging to subtribe Agrostidinae from South America are presented here. A neotype for Bromidium rigescens var. brevifolium is herein designated. Eleven names belonging to the genera Agrostis, Calamagrostis, and Deyeuxia are lectotypified. Epitypes for Calamagrostis heterophylla var. robustior and Deyeuxia velutina are designated. [ABSTRACT FROM AUTHOR]

Background: Skeeter syndrome is a severe local allergic response to mosquito bites that is accompanied by considerable inflammation and, in some cases, a systemic response like fever. People with the syndrome develop serious allergies, ranging from rashes to anaphylaxis or shock. The few available studies on mosquito venom immunotherapy have utilized whole-body preparations and small sample sizes. Still, owing to their little success, vaccination remains a promising alternative as well as a permanent solution for infections like Skeeter's. Methods: This study, therefore, illustrated the construction of an epitope-based vaccine candidate against Skeeter Syndrome using established immunoinformatic techniques. We selected three species of mosquitoes, Anopheles melas, Anopheles funestus, and Aedes aegypti, to derive salivary antigens usually found in mosquito bites. Our construct was also supplemented with bacterial epitopes known to elicit a strong TH1 response and suppress TH2 stimulation that is predicted to reduce hypersensitivity against the bites. Results: A quality factor of 98.9496, instability index of 38.55, aliphatic index of 79.42, solubility of 0.934747, and GRAVY score of -0.02 indicated the structural (tertiary and secondary) stability, thermostability, solubility, and hydrophilicity of the construct, respectively. The designed Aedes–Anopheles vaccine (AAV) candidate was predicted to be flexible and less prone to deformability with an eigenvalue of 1.5911e-9 and perfected the human immune response against Skeeter (hypersensitivity) and many mosquito-associated diseases as we noted the production of 30,000 Th1 cells per mm3 with little (insignificant production of Th2 cells. The designed vaccine also revealed stable interactions with the pattern recognition receptors of the host. The TLR2/vaccine complex interacted with a free energy of − 1069.2 kcal/mol with 26 interactions, whereas the NLRP3/vaccine complex interacted with a free energy of − 1081.2 kcal/mol with 16 molecular interactions. Conclusion: Although being a pure in-silico study, the in-depth analysis performed herein speaks volumes of the potency of the designed vaccine candidate predicting that the proposition can withstand rigorous in-vitro and in-vivo clinical trials and may proceed to become the first preventative immunotherapy against mosquito bite allergy. [ABSTRACT FROM AUTHOR]

There is still incomplete knowledge of which Mycobacterium tuberculosis (Mtb) antigens can trigger distinct T cell responses at different stages of infection. Here, a proteome-wide screen of 20,610 Mtb-derived peptides in 21 patients mid-treatment for active tuberculosis (ATB) reveals IFNγ-specific T cell responses against 137 unique epitopes. Of these, 16% are recognized by two or more participants and predominantly derived from cell wall and cell processes antigens. There is differential recognition of antigens, including TB vaccine candidate antigens, between ATB participants and interferon-gamma release assay (IGRA + /−) individuals. We developed an ATB-specific peptide pool (ATB116) consisting of epitopes exclusively recognized by ATB participants. This pool can distinguish patients with pulmonary ATB from IGRA + /− individuals from various geographical locations, with a sensitivity of over 60% and a specificity exceeding 80%. This proteome-wide screen of T cell reactivity identified infection stage-specific epitopes and antigens for potential use in diagnostics and measuring Mtb-specific immune responses. T cells play critical roles in the immune pathology of tuberculosis. Here the authors perform a proteome-wide screen of T cell antigens and reactivity to mycobacterium tuberculosis at different stages of infection. [ABSTRACT FROM AUTHOR]

The current epidemiological situation, including the existence of new SARS-CoV-2 virus with a high mutagenicity, requires fundamentally new deadlines for the development of vaccines, which may be achieved only applying modern computing technologies and simulation. Epitopes have been found in the spike protein of the SARS-CoV-2 virus using immunoinformatics methods, and their allergenicity and immunogenecity was predicted. It is shown that a vaccine against SARS-CoV-2 can be designed based on these epitopes. [ABSTRACT FROM AUTHOR]

The spatial structure of the envelope protein of African swine fever (ASF) virus is modeled; its topology relative to the cell membrane is calculated; the B- and T-cell epitopes are predicted for this protein; and their immunogenecity, allergenicity, and toxicity are estimated. The variability of protein amino acids and the conservativity of the found epitopes are studied. It is shown that a new peptide vaccine against ASF can be developed based on the found epitopes. [ABSTRACT FROM AUTHOR]

The placenta and tumors can exhibit a shared expression profile of proto-oncogenes. The basis of placenta-derived heat shock protein gp96, which induces prophylactic and therapeutic T cell responses against cancer including hepatocellular carcinoma (HCC), remains unknown. Here, we identified the associated long peptides from human placental gp96 using matrix-assisted laser desorption/ionization-time-of-flight and mass spectrometry and analyzed the achieved proteins through disease enrichment analysis. We found that placental gp96 binds to numerous peptides derived from 73 proteins that could be enriched in multiple cancer types. Epitope-harboring peptides from glypican 3 (GPC3) and paternally expressed gene 10 (PEG10) were the major antigens mediating anti-HCC T cell immunity. Molecular docking analysis showed that the GPC3- and PEG10-derived peptides, mainly obtained from the cytotrophoblast layer of the mature placenta, bind to the lumenal channel and client-bound domain of the gp96 dimer. Immunization with bone marrow-derived dendritic cells pulsed with recombinant gp96-GPC3 or recombinant gp96-PEG10 peptide complex induced specific T cell responses, and T cell transfusion led to pronounced growth inhibition of HCC tumors in nude mice. We demonstrated that the chaperone gp96 can capture antigenic peptides as an efficient approach for defining tumor rejection oncoantigens in the placenta and provide a basis for developing GPC3 and PEG10 peptide-based vaccines against HCC. This study provides insight into the underlying mechanism of the antitumor response mediated by embryonic antigens from fetal tissues, and this will incite more studies to identify potential tumor rejection antigens from placenta. [ABSTRACT FROM AUTHOR]

Small cell lung cancer (SCLC) is one of the most common cancers and it is the sixth common cause for cancer-related deaths. The high plasticity and metastasis have been a major challenge for humanity to treat the disease. Hence, a vaccine for SCLC has become an urgent need of the hour due to public health concern. Implementation of immunoinformatics technique is one of the best way to find a suitable vaccine candidate. Immunoinformatics tools can be used to overcome the limitations and difficulties of traditional vaccinological techniques. Multi-epitope cancer vaccines have become a next-generation technique in vaccinology which can be used to stimulate more potent immune response against a particular antigen by eliminating undesirable molecules. In this study, we used multiple computational and immunoinformatics approach to design a novel multi-epitope vaccine for small cell lung cancer. Nucleolar protein 4 (NOL4) is an autologous cancer-testis antigen overexpressed in SCLC cells. Seventy-five percent humoral immunity have been identified for this particular antigen. In this study, we mapped immunogenic cytotoxic T lymphocyte, helper T lymphocyte, and interferon-gamma epitopes present in NOL4 antigen and designed a multi-epitope-based vaccine using the predicted epitopes. The designed vaccine was antigenic, non-allergenic, and non-toxic with 100% applicability on human population. The chimeric vaccine construct showed stable and significant interaction with endosomal and plasmalemmal toll-like receptors in molecular docking and protein–peptide interaction analysis, thus assuring a strong potent immune response against the vaccine upon administration. Therefore, these preliminary results can be used to carry out further experimental investigations. [ABSTRACT FROM AUTHOR]

Epstein-Barr virus (EBV) is a global lymphotropic virus and has been associated with various malignancies, among which colorectal cancer (CRC) is the prevalent one causing mortality worldwide. In the recent past, numerous research efforts have been made to develop a potential vaccine against this virus; however, none is effective possibly due to their low throughput, laboriousness, and lack of sensitivity. In this study, we designed a multi-epitope subunit vaccine that targets latent membrane protein (LMP-2B) of EBV using pan-genome and reverse vaccinology approaches. Twenty-three major histocompatibility complex (MHC) epitopes (five class-I and eighteen class-II) and eight B-cell epitopes, which have been found to be antigenic, immunogenic, and non-toxic, were selected for the vaccine construction. Furthermore, 24 vaccine constructs (VCs) were designed from the predicted epitopes and out of which VC1 was selected and finalized based on its structural parameters. The functionality of VC1 was validated through molecular docking with different immune receptors (MHC class-I, MHC class-II, and TLRs). The binding affinity, molecular and immune simulation revealed that the VC1 had more stable interaction and is believed to elicit good immune responses against EBV. Highlights: Pan-genome and reverse vaccinology approaches were used to design a multi-epitope subunit vaccine against LMP-2B protein of EBV. Epitopes were selected based on the antigenic, immunogenic, and non-toxic properties. Twenty-four vaccine constructs (VCs) were designed from the predicted epitopes. Designed vaccine VC1 has shown good binding affinity and molecular and immune simulation. VC1 was validated using molecular docking with different immune receptors. [ABSTRACT FROM AUTHOR]

Context Marburg virus (MARV) is a member of the Filoviridae family and causes Marburg virus disease (MVD) among humans and primates. With fatality rates going up to 88%, there is currently no commercialized cure or vaccine to combat the infection. The National Institute of Allergy and Infectious Diseases (NIAID) classified MARV as priority pathogen A, which presages the need for a vaccine candidate which can provide stable, long-term adaptive immunity. The surface glycoprotein (GP) and fusion protein (FP) mediate the adherence, fusion, and entry of the virus into the host cell via the TIM-I receptor. Being important antigenic determinants, studies reveal that GP and FP are prone to evolutionary mutations, underscoring the requirement of a vaccine construct capable of eliciting a robust and sustained immune response. In this computational study, a reverse vaccinology approach was employed to design a combinatorial vaccine from conserved and antigenic epitopes of essential viral proteins of MARV, namely GP, VP24, VP30, VP35, and VP40 along with an endogenous protein large polymerase (L). Methods Epitopes for T-cell and B-cell were predicted using TepiTool and ElliPro, respectively. The surface-exposed TLRs like TLR2, TLR4, and TLR5 were used to screen high-binding affinity epitopes using the protein-peptide docking platform MdockPeP. The best binding epitopes were selected and assembled with linkers to design a recombinant multi-epitope vaccine construct which was then modeled in Robetta. The in silico biophysical and biochemical analyses of the recombinant vaccine were performed. The docking and MD simulation of the vaccine using WebGro and CABS-Flex against TLRs support the stable binding of vaccine candidates. A virtual immune simulation to check the immediate and long-term immunogenicity was carried out using the C-ImmSim server. Results The biochemical characteristics and docking studies with MD simulation establish the recombinant protein vaccine construct MarVax as a stable, antigenic, and potent vaccine molecule. Immune simulation studies reveal 1-year passive immunity which needs to be validated by in vivo studies. [ABSTRACT FROM AUTHOR]

Background Immunoinformatics is an emerging interdisciplinary field which integrates immunology, bioinformatics, and computational biology to study the immune system. In this study, we apply immunoinformatics approaches to explore the dengue proteome in order to design a multi-epitope vaccine construct. Methods We used existing databases and algorithms to predict potential epitopes on dengue proteins and used a bioinformatics approach to identify the most promising epitopes. We then used molecular modelling to develop a multi-epitope construct which could be used as a potential vaccine. The results of this study demonstrate that immunoinformatics is a powerful tool for exploring and designing potential vaccines for infectious diseases like dengue. Results Here, we found four CD4+ epitopes NLKYSVIVTVHTGDQ, ANPIVTDKEKPVNIE, LDPVVYDAKFEKQL, and VGAIALDFKPGTSGS that were used to design vaccine construct. The vaccine construct docked with TLR5. RMSD values suggest that docked complex of TLR5 and vaccine construct have putative stable interaction to induce immunogenic effects on host. Conclusions Furthermore, our study provides a proof of concept for the use of immunoinformatics approaches in DENV vaccine design. This vaccine can be effective in treating patients infected with DENV virus. [ABSTRACT FROM AUTHOR]

The class I proteins of the major histocompatibility complex (MHC-I) display epitopic peptides derived from endogenous proteins on the cell surface for immune surveillance. Accurate modeling of peptides bound to the human MHC, HLA, has been mired by conformational diversity of the central peptide residues, which are critical for recognition by T cell receptors. Here, analysis of X-ray crystal structures within our curated database (HLA3DB) shows that pHLA complexes encompassing multiple HLA allotypes present a discrete set of peptide backbone conformations. Leveraging these backbones, we employ a regression model trained on terms of a physically relevant energy function to develop a comparative modeling approach for nonamer pHLA structures named RepPred. Our method outperforms the top pHLA modeling approach by up to 19% in structural accuracy, and consistently predicts blind targets not included in our training set. Insights from our work may be applied towards predicting antigen immunogenicity, and receptor cross-reactivity. Structure prediction of peptide/HLA (pHLA) complexes has been mired by the inability to accurately model the middle of the peptide. Here, the authors present a curated database of pHLA structures (HLA3DB) and identify discrete peptide backbone conformations that are used for high fidelity modelling. [ABSTRACT FROM AUTHOR]

Amongst the potential contribution of protein or peptide-display systems to study epitopes with relevant immunological features, the RAD display system stands out as a highly stable scaffold protein that allows the presentation of constrained target peptides. Here, we employed the RAD display system to present peptides derived from the SARS-CoV-2 Spike (S) protein as a tool to detect specific serum antibodies and to generate polyclonal antibodies capable of inhibiting SARS-CoV-2 infectivity in vitro. 44 linear S-derived peptides were genetically fused with the RAD scaffold (RAD-SCoV-epitopes) and screened for antigenicity with sera collected from COVID-19-infected patients. In a second step, selected RAD-SCoV-epitopes were used to immunize mice and generate antibodies. Phenotypic screening showed that some of these antibodies were able to recognize replicating viral particles in VERO CCL-81 and most notably seven of the RAD-SCoV-epitopes were able to induce antibodies that inhibited viral infection. Our findings highlight the RAD display system as an useful platform for the immunological characterization of peptides and a potentially valuable strategy for the design of antigens for peptide-based vaccines, for epitope-specific antibody mapping, and for the development of antibodies for diagnostic and therapeutic purposes. [ABSTRACT FROM AUTHOR]

Antibody derivatives have sought to recapitulate the antigen binding properties of antibodies, but with improved biophysical attributes convenient for therapeutic, diagnostic and research applications. However, their success has been limited by the naturally occurring structure of the immunoglobulin dimer displaying hypervariable binding loops, which is hard to modify by traditional engineering approaches. Here, we devise geometrical principles for de novo designing single-chain immunoglobulin dimers, as a tunable two-domain architecture that optimizes biophysical properties through more favorable dimer interfaces. Guided by these principles, we computationally designed protein scaffolds that were hyperstable, structurally accurate and robust for accommodating multiple functional loops, both individually and in combination, as confirmed through biochemical assays and X-ray crystallography. We showcase the modularity of this architecture by deep-learning-based diversification, opening up the possibility for tailoring the number, positioning, and relative orientation of ligand-binding loops targeting one or two distal epitopes. Our results provide a route to custom-design robust protein scaffolds for harboring multiple functional loops. Here the authors describe principles for de novo designing single-chain immunoglobulin dimers with interfaces diverging from those seen in antibodies, showing enhanced stability and both robustness and modularity for harboring multiple functional loops. [ABSTRACT FROM AUTHOR]

Respiratory virus infections play a major role in asthma, while there is a close correlation between asthma and food allergy. We hypothesized that T cell-mediated heterologous immunity may induce asthma symptoms among sensitized individuals and used two independent in silico pipelines for the identification of cross-reactive virus- and food allergen- derived T cell epitopes, considering individual peptide sequence similarity, MHC binding affinity and immunogenicity. We assessed the proteomes of human rhinovirus (RV1b), respiratory syncytial virus (RSVA2) and influenza-strains contained in the seasonal quadrivalent influenza vaccine 2019/2020 (QIV 2019/2020), as well as SARS-CoV-2 for human HLA alleles, in addition to more than 200 most common food allergen protein sequences. All resulting allergen-derived peptide candidates were subjected to an elaborate scoring system considering multiple criteria, including clinical relevance. In both bioinformatics approaches, we found that shortlisted peptide pairs that are potentially binding to MHC class II molecules scored up to 10 × lower compared to MHC class I candidate epitopes. For MHC class I food allergen epitopes, several potentially cross-reactive peptides from shrimp, kiwi, apple, soybean and chicken were identified. The shortlisted set of peptide pairs may be implicated in heterologous immune responses and translated to peptide immunization strategies with immunomodulatory properties. [ABSTRACT FROM AUTHOR]

Linear-B cell epitopes (LBCE) play a vital role in vaccine design; thus, efficiently detecting them from protein sequences is of primary importance. These epitopes consist of amino acids arranged in continuous or discontinuous patterns. Vaccines employ attenuated viruses and purified antigens. LBCE stimulate humoral immunity in the body, where B and T cells target circulating infections. To predict LBCE, the underlying protein sequences undergo a process of feature extraction, feature selection, and classification. Various system models have been proposed for this purpose, but their classification accuracy is only moderate. In order to enhance the accuracy of LBCE classification, this paper presents a novel 2-step metaheuristic variant-feature selection method that combines a linear support vector classifier (LSVC) with a Modified Genetic Algorithm (MGA). The feature selection model employs mono-peptide, dipeptide, and tripeptide features, focusing on the most diverse ones. These selected features are fed into a machine learning (ML)-based parallel ensemble classifier. The ensemble classifier combines correctly classified instances from various classifiers, including k-Nearest Neighbor (kNN), random forest (RF), logistic regression (LR), and support vector machine (SVM). The ensemble classifier came up with an impressively high accuracy of 99.3% as a result of its work. This accuracy is superior to the most recent models that are considered to be state-of-the-art for linear B-cell classification. As a direct consequence of this, the entire system model can now be utilised effectively in real-time clinical settings. [ABSTRACT FROM AUTHOR]

Antibodies against the receptor-binding domain of the SARS-CoV-2 spike protein (RBD S-protein) contribute significantly to the humoral immune response during coronavirus infection (COVID-19) and after vaccination. The main focus of the studies of the RBD epitope composition is usually concentrated on the epitopes recognized by the virus-neutralizing antibodies. The role of antibodies that bind to RBD but do not neutralize SARS-CoV-2 remains unclear. In this study, immunochemical properties of the two mouse monoclonal antibodies (mAbs), RS17 and S11, against the RBD were examined. Both mAbs exhibited high affinity to RBD, but they did not neutralize the virus. The epitopes of these mAbs were mapped using phage display: the epitope recognized by the mAb RS17 is located at the N-terminal site of RBD (348-SVYAVNRKRIS-358); the mAb S11 epitope is inside the receptor-binding motif of RBD (452-YRLFRKSN-459). Three groups of sera were tested for presence of antibodies competing with the non-neutralizing mAbs S11 and RS17: (i) sera from the vaccinated healthy volunteers without history of COVID-19; (ii) sera from the persons who had a mild form of COVID-19; (iii) sera from the persons who had severe COVID-19. Antibodies competing with the mAb S11 were found in each group of sera with equal frequency, whereas presence of the antibodies competing with the mAb RS17 in the sera was significantly more frequent in the group of sera obtained from the patients recovered from severe COVID-19 indicating that such antibodies are associated with the severity of COVID-19. In conclusion, despite the clear significance of anti-RBD antibodies in the effective immune response against SARS-CoV-2, it is important to analyze their virus-neutralizing activity and to confirm absence of the antibody-mediated enhancement of infection by the anti-RBD antibodies. [ABSTRACT FROM AUTHOR]

Bispecific antibodies (bsAbs) are some of the most promising biotherapeutics due to the versatility provided by their structure and functional features. bsAbs simultaneously bind two antigens or two epitopes on the same antigen. Moreover, they are capable of directing immune effector cells to cancer cells and delivering various compounds (radionuclides, toxins, and immunologic agents) to the target cells, thus offering a broad spectrum of clinical applications. Current review is focused on the technologies used in bsAb engineering, current progress and prospects of these antibodies, and selection of various heterologous expression systems for bsAb production. We also discuss the platforms development of bsAbs for the therapy of solid tumors. [ABSTRACT FROM AUTHOR]

This study reviews the Ficus americana species complex, a group mostly distributed throughout South America. Following the taxonomic analysis of approximately 60 names related to the group, we specify the new Kinuppii series of 9 species, a ramiflorous group which is delimited by the presence of spurs in the branches, a unique characteristic of the new taxon of Neotropical Ficus. Ficus longifolia and F. schippii are included in the new series, but have not previously been cited as part of the F. americana species complex. Ficus clusiifolia, F. fresnoensis, F. guianensis, F. mathewsii, and F. subapiculata are treated as accepted species names and no longer considered varieties of F. americana. Completing the new series are F. albert-smithii and F. sphenophylla. Epitypes were designated for F. clusiifolia and F. longifolia and a neotype for F. herthae. In this study, F. leiophylla is considered a synonym of F. mathewsii as the leaf shape varies considerably within the taxon. Synonyms, analysis of protologues, types, descriptions, taxonomic key, examined materials, and maps complete the analysis. [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]

Prediction of conformational B-cell epitopes (CBCE) is an essential phase for vaccine design, drug invention, and accurate disease diagnosis. Many laboratorial and computational approaches have been developed to predict CBCE. However, laboratorial experiments are costly and time consuming, leading to the popularity of Machine Learning (ML)-based computational methods. Although ML methods have succeeded in many domains, achieving higher accuracy in CBCE prediction remains a challenge. To overcome this drawback and consider the limitations of ML methods, this paper proposes a novel DL-based framework for CBCE prediction, leveraging the capabilities of deep learning in the medical domain. The proposed model is named Deep Learning-based Temporal Convolutional Neural Network (DL-TCNN), which hybridizes empirical hyper-tuned 1D-CNN and TCN. TCN is an architecture that employs causal convolutions and dilations, adapting well to sequential input with extensive receptive fields. To train the proposed model, physicochemical features are firstly extracted from antigen sequences. Next, the Synthetic Minority Oversampling Technique (SMOTE) is applied to address the class imbalance problem. Finally, the proposed DL-TCNN is employed for the prediction of CBCE. The model's performance is evaluated and validated on a benchmark antigen–antibody dataset. The DL-TCNN achieves 94.44% accuracy, and 0.989 AUC score for the training dataset, 78.53% accuracy, and 0.661 AUC score for the validation dataset; and 85.10% accuracy, 0.855 AUC score for the testing dataset. The proposed model outperforms all the existing CBCE methods. [ABSTRACT FROM AUTHOR]

Background: Influenza is a highly contagious respiratory disease which poses a serious threat to public health globally, causing severe diseases in 3-5 million humans and resulting in 650,000 deaths annually. The current licensed seasonal influenza vaccines lacked cross-reactivity against novel emerging influenza strains as they conferred limited neutralising capabilities. To address the issue, we designed a multi-epitope peptide-based vaccine delivered by the self-adjuvanting PLGA nanoparticles against influenza infections. Methods: A total of six conserved peptides representing B- and T-cell epitopes of Influenza A were identified and they were formulated in either incomplete Freund's adjuvant containing CpG ODN 1826 or being encapsulated in PLGA nanoparticles for the evaluation of immunogenicity in BALB/c mice. Results: The self-adjuvanting PLGA nanoparticles encapsulating the six conserved peptides were capable of eliciting the highest levels of IgG and IFN- γ producing cells. In addition, the immunogenicity of the six peptides encapsulated in PLGA nanoparticles showed greater humoral and cellular mediated immune responses elicited by the mixture of six naked peptides formulated in incomplete Freund's adjuvant containing CpG ODN 1826 in the immunized mice. Peptide 3 from the mixture of six peptides was found to exert necrotic effect on CD3+ T-cells and this finding indicated that peptide 3 should be removed from the nanovaccine formulation. Conclusion: The study demonstrated the self-adjuvanting properties of the PLGA nanoparticles as a delivery system without the need for incorporation of toxic and costly conventional adjuvants in multi-epitope peptide-based vaccines. [ABSTRACT FROM AUTHOR]

The synthesis of a lipid conjugate of immunostimulatory oligodeoxyribonucleotide CpG-ODN (PD-CpG-DOPE) is described. Liposomes loaded with a composition of T-cell epitopes of the SARS-CoV-2 virus (7 peptides) and carrying the PD-CpG-DOPE conjugate in the membrane, including lyophilized liposomes suitable for long-term storage, were prepared. In vitro experiments on mouse peritoneal exudate cells showed a tendency to increase the immunogenicity of liposomes with peptides when the PD-CpG-DOPE conjugate was introduced into the lipid bilayer, compared with the addition of the (commercial) phosphorothioate derivative of CpG-ODN in solution. [ABSTRACT FROM AUTHOR]

No approved vaccine exists for Klebsiella pneumoniae yet. Outer membrane protein-K17 (OMPK17) is involved in K. pneumoniae pathogenesis. No information has been found about OMPK17 dominant epitopes in the literature. Therefore, this study aimed to predict both T cell and B cell epitopes of K. pneumoniae OMPK17 via immunoinformatics approaches. Both T cell (class-I and II) and B cell (linear and discontinuous) epitopes of OMPK17 were predicted. Several screening analyses were performed including clustering, immunogenicity, human similarity, toxicity, allergenicity, conservancy, docking, and structural/physicochemical suitability. The results showed that some regions of OMPK17 have more potential as epitopes. The most possible epitopes were found via several analyses including the selection of higher-scoring epitopes, the epitopes predicted with more tools, more immunogenic epitopes, the epitopes capable of producing interferon-gamma, the epitopes with more dissimilarity to human peptides, and non-toxic and non-allergenic epitopes. By comparing the best T cell and B cell epitopes, we reached a 25-mer peptide containing both T cell (class-I and class-II) and B cell (linear) epitopes and comprising appropriate physicochemical characteristics that are required for K. pneumoniae vaccine development. The in vitro/in vivo study of this peptide is recommended to clarify its actual efficiency and efficacy. [ABSTRACT FROM AUTHOR]

Tuberculosis, caused by Mycobacterium tuberculosis complex (MTBC) organisms, affects a range of humans and animals globally. Mycobacterial pathogenesis involves manipulation of the host immune system, partially through antigen presentation. Epitope sequences across the MTBC are evolutionarily hyperconserved, suggesting their recognition is advantageous for the bacterium. Mycobacterium tuberculosis var. bovis (MBO) strain Ravenel is an isolate known to provoke a robust immune response in cattle, but typically fails to produce lesions and persist. Unlike attenuated MBO BCG strains that lack the critical RD1 genomic region, Ravenel is classic-type MBO structurally, suggesting genetic variation is responsible for defective pathogenesis. This work explores variation in epitope sequences in MBO Ravenel by whole genome sequencing, and contrasts such variation against a fully virulent clinical isolate, MBO strain 10-7428. Validated MTBC epitopes (n = 4818) from the Immune Epitope Database were compared to their sequences in MBO Ravenel and MBO 10-7428. Ravenel yielded 3 modified T cell epitopes, in genes rpfB, argC, and rpoA. These modifications were predicted to have little effect on protein stability. In contrast, T cells epitopes in 10-7428 were all WT. Considering T cell epitope hyperconservation across MTBC variants, these altered MBO Ravenel epitopes support their potential contribution to overall strain attenuation. The affected genes may provide clues on basic pathogenesis, and if so, be feasible targets for reverse vaccinology. [ABSTRACT FROM AUTHOR]

Approximate 70% of cobra venom is composed of cytotoxin (CTX), which is responsible for the dermonecrotic symptoms of cobra envenomation. However, CTX is generally low in immunogenicity, and the antivenom is ineffective in attenuating its in vivo toxicity. Furthermore, little is known about its epitope properties for empirical antivenom therapy. This study aimed to determine the epitope sequences of CTX using the immunoinformatic analyses and epitope-omics profiling. A conserved CTX was used in this study to determine its T-cell and B-cell epitope sequences using immunoinformatic tools and molecular docking simulation with different Human Leukocyte Antigens (HLAs). The potential T-cell and B-cell epitopes were 'KLVPLFY,' 'CPAGKNLCY,' 'MFMVSTPTK,' and 'DVCPKNSLL.' Molecular docking simulations disclosed that the HLA-B62 supertype exhibited the greatest binding affinity towards cobra venom cytotoxin. The namely L7, G18, K19, N20, M25, K33, V43, C44, K46, N47, and S48 of CTX exhibited prominent intermolecular interactions with HLA-B62. The multi-enzymatic-limited-digestion/liquid chromatography-mass spectrometry (MELD/LC–MS) also revealed three potential epitope sequences as 'LVPLFYK,' 'MFMVS,' and 'TVPVKR'. From different epitope mapping approaches, we concluded four potential epitope sites of CTX as 'KLVPLFYK', 'AGKNL', 'MFMVSTPKVPV' and 'DVCPKNSLL'. Site-directed mutagenesis of these epitopes confirmed their locations at the functional loops of CTX. These epitope sequences are crucial to CTX's structural folding and cytotoxicity. The results concluded the epitopes that resided within the functional loops constituted potential targets to fabricate synthetic epitopes for CTX-targeted antivenom production. [ABSTRACT FROM AUTHOR]

Immunotherapeutic strategies aimed at enhancing tumor cell killing by tumor-specific T cells hold great potential for reducing tumor burden and prolonging survival of cancer patients. Although many potential tumor antigens have been described, identifying relevant targets when designing anti-cancer vaccines or targeted cell therapies remains a challenge. To identify novel, potentially immunogenic candidate tumor antigens, we performed integrated tumor transcriptomic, seromic, and proteomic analyses of high grade serous ovarian cancer (HGSC) patient tumor samples. We identified tumor neo-antigens and over-expressed antigens using whole exome and RNA sequencing and examined these in relation to patient-matched auto-antibody repertoires. Focusing on MHC class I epitopes recognized by CD8+ T cells, HLA-binding epitopes were identified or predicted from the highly expressed, mutated, or auto-antibody target antigen, or MHC-associated peptides (MAPs). Recognition of candidate antigenic peptides was assessed within the tumor-infiltrating T lymphocyte (TIL) population expanded from each patient. Known tumor-associated antigens (TAA) and cancer/testis antigens (CTA) were commonly found in the auto-antibody and MAP repertoires and CD8+ TILs recognizing epitopes from these antigens were detected, although neither expression level nor the presence of auto-antibodies correlated with TIL recognition. Auto-antibodies against tumor-mutated antigens were found in most patients, however, no TIL recognition of the highest predicted affinity neo-epitopes was detected. Using high expression level, auto-antibody recognition, and epitope prediction algorithms, we identified epitopes in 5 novel antigens (MOB1A, SOCS3, TUBB, PRKAR1A, CCDC6) recognized by HGSC patient TILs. Furthermore, selection of epitopes from the MAP repertoire identified 5 additional targets commonly recognized by multiple patient TILs. We find that the repertoire of TIL specificities includes recognition of highly expressed and immunogenic self-antigens that are processed and presented by tumors. These results indicate an ongoing autoimmune response against a range of self-antigens targeted by HGSC TILs. [ABSTRACT FROM AUTHOR]

Background: COVID-19 has proved to be a fatal disease of the year 2020, due to which thousands of people globally have lost their lives, and still, the infection cases are at a high rate. Experimental studies suggested that SARS-CoV-2 interacts with various microorganisms, and this coinfection is accountable for the augmentation of infection severity. Methods and results: In this study, we have designed a multi-pathogen vaccine by involving the immunogenic proteins from S. pneumonia, H. influenza, and M. tuberculosis, as they are dominantly associated with SARS-CoV-2. A total of 8 antigenic protein sequences were selected to predict B-cell, HTL, and CTL epitopes restricted to the most prevalent HLA alleles. The selected epitopes were antigenic, non-allergenic, and non-toxic and were linked with adjuvant and linkers to make the vaccine protein more immunogenic, stable, and flexible. The tertiary structure, Ramachandran plot, and discontinuous B-cell epitopes were predicted. Docking and MD simulation study has shown efficient binding of the chimeric vaccine with the TLR4 receptor. Conclusion: The in silico immune simulation analysis has shown a high level of cytokines and IgG after a three-dose injection. Hence, this strategy could be a better way to decrease the disease's severity and could be used as a weapon to prevent this pandemic. [ABSTRACT FROM AUTHOR]

Duck adenovirus 3 (DAdV-3), a newly emerged duck adenovirus, has resulted in significant economic losses to the duck industry across China since 2014. However, little is known about the B cell epitopes in major antigen of DAdV-3 and the serological approach for detection of DAdV-3 is not available. In this study, four monoclonal antibodies (mAbs) specific to Fiber-2 protein of DAdV-3 were first generated and designated as 2G10, 3D9, 5E6, and 6B12. Indirect immunofluorescence assay (IFA) showed that all of the mAbs reacted with the Fiber-2. Moreover, mAbs 2G10, 5E6, and 6B12 demonstrated good activity with Fiber-2 in Western blot. Notably, the Fiber-2 could be immunoprecipitated efficiently by mAb 3D9. Epitope mapping revealed that mAbs 2G10, 3D9, 5E6, and 6B12 recognized 397-429aa, 463-481aa, 67-99aa, and 1-66aa of Fiber-2, respectively. Besides, a novel sandwich ELISA for efficient detection of DAdV-3 was developed based on mAb 3D9 and horseradish peroxidase (HRP) conjugated mAb 3D9. The sandwich ELISA only reacted with DAdV-3 but not with other duck-associated viruses. The limit of detection of the ELISA was 6.25 × 103 TCID50/mL. Overall, the mAbs generated laid the foundation for elucidating the critical role of Fiber-2 in mediating infection and pathogenesis, and the sandwich ELISA approach established here provided efficient and rapid serological diagnostic tool for DAdV-3. Key points: Four mAbs against Fiber-2 of DAdV-3 were generated. Four novel B cell epitopes in Fiber-2 of DAdV-3 were identified. An efficient sandwich ELISA for detection of DAdV-3 was developed. [ABSTRACT FROM AUTHOR]

Human noroviruses (HuNoV) are the leading cause of acute gastroenteritis worldwide. The humoral immune response plays an important role in clearing HuNoV infections and elucidating the antigenic landscape of HuNoV during an infection can shed light on antibody targets to inform vaccine design. Here, we utilized Jun-Fos-assisted phage display of a HuNoV genogroup GI.1 genomic library and deep sequencing to simultaneously map the epitopes of serum antibodies of six individuals infected with GI.1 HuNoV. We found both unique and common epitopes that were widely distributed among both nonstructural proteins and the major capsid protein. Recurring epitope profiles suggest immunodominant antibody footprints among these individuals. Analysis of sera collected longitudinally from three individuals showed the presence of existing epitopes in the pre-infection sera, suggesting these individuals had prior HuNoV infections. Nevertheless, newly recognized epitopes surfaced seven days post-infection. These new epitope signals persisted by 180 days post-infection along with the pre-infection epitopes, suggesting a persistent production of antibodies recognizing epitopes from previous and new infections. Lastly, analysis of a GII.4 genotype genomic phage display library with sera of three persons infected with GII.4 virus revealed epitopes that overlapped with those identified in GI.1 affinity selections, suggesting the presence of GI.1/GII.4 cross-reactive antibodies. The results demonstrate that genomic phage display coupled with deep sequencing can characterize HuNoV antigenic landscapes from complex polyclonal human sera to reveal the timing and breadth of the human humoral immune response to infection. [ABSTRACT FROM AUTHOR]

Vaccination clearly decreases coronavirus disease 2019 (COVID-19) mortality; however, they also impose selection pressure on the virus, which promotes the evolution of immune escape variants. For example, despite the high vaccination level in especially Western countries, the Omicron variant caused millions of breakthrough infections, suggesting that the highly mutated spike protein in the Omicron variant can escape antibody immunity much more efficiently than the other variants of concern (VOCs). In this study, we investigated the resistance/susceptibility of T helper cell responses that are necessary for generating efficient long-lasting antibody immunity, in several VOCs. By predicting T helper cell epitopes on the spike protein for most common HLA-DRB1 alleles worldwide, we found that although most of high frequency HLA-DRB1 alleles have several potential T helper cell epitopes, few alleles like HLA-DRB1 13:01 and 11:01 are not predicted to have any significant T helper cell responses after vaccination. Using these predictions, a population based on realistic human leukocyte antigen-II (HLA-II) frequencies were simulated to visualize the T helper cell immunity on the population level. While a small fraction of this population had alarmingly little predicted CD4 T cell epitopes, the majority had several epitopes that should be enough to generate efficient B cell responses. Moreover, we show that VOC spike mutations hardly affect T helper epitopes and mainly occur in other residues of the spike protein. These results suggest that lack of long-lasting antibody responses is not likely due to loss of T helper cell epitopes in new VOCs. [ABSTRACT FROM AUTHOR]

Accurately detecting linear B-cell epitopes (BCEs) makes great sense in vaccine design, immunodiagnostic test, antibody production, disease prevention and treatment. Wet-lab experiments for determining linear BCEs are both expensive and laborious, which are not able to meet the recognition needs of modern massive protein sequence data. Instead, computational methods can efficiently identify linear BCEs with low cost. Although several computational methods are available, the performance is still not satisfactory. Thus, we propose a new method, LBCE-XGB, to forecast linear BCEs based on XGBoost algorithm. To represent the biological information concealed in peptide sequences, the embeddings of the residues were obtained from a pre-trained domain-specific BERT model. In addition, the other five types of attributes comprising amino acid composition, amino acid antigenicity scale were also extracted. The best feature combination was determined according to the cross-validation results. Against the models developed by other deep learning and machine learning algorithms, LBCE-XGB achieves the top performance with an AUROC of 0.845 for fivefold cross-validation. The results on the independent test set show that our model attains an AUROC of 0.838 which is substantially higher than other state-of-the-art methods. The outcomes indicate that the representations of BERT could be an effective feature in predicting linear BCEs and we believe that LBCE-XGB could be a useful medium for detecting linear B cell epitopes with high accuracy and low cost. [ABSTRACT FROM AUTHOR]