Immunogenic Epitopes Research Articles

Leptospiral Leucine-Rich Repeat Protein-Based Lateral Flow for Assessment of Canine Leptospiral Immunoglobulin G.

The recombinant, modified leucine-rich repeat protein rhKU_Sej_LRR_2271 has been suggested as a candidate for leptospiral vaccine development since it was predicted to be a transmembrane protein containing leucine-rich repeat motifs and immunogenic epitopes. The immunogenic epitopes showed binding affinities with lower IC50 values than peptides of known antigenic proteins, e.g., LipL32. Moreover, this protein was immunoreactive with hyperimmune sera against several serovars. In this study, we aimed to develop a lateral flow strip test using the rhKU_Sej_LRR_2271 protein for the detection of anti-leptospiral IgG in dogs. The lateral flow assay was performed with 184 dog plasma samples and evaluated with a culture method, 16S ribosomal RNA gene (rss) analysis real-time PCR, and LipL32 ELISA. The culture method failed to detect leptospires in the dog blood samples. Six of nine symptomatic dogs gave positive results with the real-time PCR assay. The lateral flow assay and LipL32 ELISA gave positive results with 59 and 50 dogs, respectively. The sensitivity, specificity, and accuracy of the rhKU_Sej_LRR_2271 lateral flow strip test were 70.00, 82.09, and 78.80%, respectively, when compared with LipL32 ELISA. There was a significant association between the LipL32 ELISA and the rhKU_Sej_LRR_2271 lateral flow assay. The rhKU_Sej_LRR_2271 lateral flow strip test has therefore demonstrated a good potential to detect anti-leptospiral IgG in dogs.

High-Yield Production of Chimeric Hepatitis E Virus-Like Particles Bearing the M2e Influenza Epitope and Receptor Binding Domain of SARS-CoV-2 in Plants Using Viral Vectors.

Capsid protein of Hepatitis E virus (HEV) is capable of self-assembly into virus-like particles (VLPs) when expressed in Nicotiana benthamiana plants. Such VLPs could be used as carriers of antigens for vaccine development. In this study, we obtained VLPs based on truncated coat protein of HEV bearing the M2e peptide of Influenza A virus or receptor-binding domain of SARS-CoV-2 spike glycoprotein (RBD). We optimized the immunogenic epitopes' presentation by inserting them into the protruding domain of HEV ORF2 at position Tyr485. The fusion proteins were expressed in Nicotiana benthamiana plants using self-replicating potato virus X (PVX)-based vector. The fusion protein HEV/M2, targeted to the cytosol, was expressed at the level of about 300-400 μg per gram of fresh leaf tissue and appeared to be soluble. The fusion protein was purified using metal affinity chromatography under native conditions with the final yield about 200 μg per gram of fresh leaf tissue. The fusion protein HEV/RBD, targeted to the endoplasmic reticulum, was expressed at about 80-100 μg per gram of fresh leaf tissue; the yield after purification was up to 20 μg per gram of fresh leaf tissue. The recombinant proteins HEV/M2 and HEV/RBD formed nanosized virus-like particles that could be recognized by antibodies against inserted epitopes. The ELISA assay showed that antibodies of COVID-19 patients can bind plant-produced HEV/RBD virus-like particles. This study shows that HEV capsid protein is a promising carrier for presentation of foreign antigen.

Relationship of Covid-19 Severity with SARS-CoV-2 NS8 Protein Mutations Depending on Virus Strain

In mid-2021, the Delta strain of SARS-CoV-2 caused the third wave of the COVID-19 pandemic. Huge efforts have been devoted to studying the effect of its mutations on the effectiveness of neutralizing antibodies. Much less attention was paid to the individual features of the presentation of its peptides by molecules of the major histocompatibility complex class I (MCHC-I). In this study, the correlation of the HLA-I genotype of patients under the age of 60 years with the severity of COVID-19 caused by the two most common variants of the SARS-CoV-2 Delta strain in the summer of 2021: AY.122 and B.1.617.2 was studied. Analysis of the severity of the course of COVID-19 revealed a more severe course of the disease caused by the AY.122 variant. Comparison of the mutation profile of the two most common variants of the Delta strain showed that that the G8R mutation in the NS8 protein makes the greatest contribution to the ability of MHC-I to present viral peptides. Given that the NS8 protein is able to suppress the maturation of MHC-I molecules, the appearance of a mutation in one of its immunogenic epitopes could make a significant contribution to the prevalence of the AY.122 variant in the Russian population.

Abstract B003: Cross-reacting antigens between the intestinal microbiome and tumor neoantigen are associated with immune checkpoint inhibitor response in a gastrointestinal tumor cohort

Abstract Background: Immune checkpoint inhibitor (ICI) is a revolutionary therapy that promotes the activation of effector T cells against tumors. Despite the potential for long-term benefit, a large proportion of patients does not respond to ICI therapy. One reason for this heterogenic response is due to the high variability in the intestinal microbiota among different patients. The abundance of certain bacteria has been associated with different responses and fecal meta transplant from responding donors was shown to rescue a beneficial phenotype in refractory patients. The presence of cross-reactive antigens (CRAgs) between the gut microbiome and tumor neoantigens has been proposed as a potential mechanism that could link the intestinal microbiota with ICI response. However, empirical evidence of CRAg’s role in ICI therapy is limited to a few studies. Methods: We investigated ICI response in a cohort of 22 stage IV gastrointestinal (GI) tumor patients in which whole-exome and gut metagenomic sequencing data were available. This cohort included patients with gastric cancer (n=11), esophageal carcinoma (n=6), and colon cancer (n=5). For each patient, we characterized the tumor neoantigen load based on epitopes that show high affinity and presentability in HLA molecules. Neoantigens were matched to the intestinal microbiome to identify corresponding CRAgs. CRAg quality, which ranks CRAgs according to their immunogenic potential, was defined based on matches in immunogenic protein or epitope databases. Results: We found the total number of CRAgs varied per tumor type, with a higher abundance in colon cancer (median µ=619) followed by esophageal (µ =287.5) and gastric (µ = 243). Interestingly, colon cancer patients showed a better progression-free survival (PFS) curve followed by esophageal and gastric cancer patients, respectively. We also observed that CRAg load was better associated with longer PFS (p=.03) than neoantigen load (p=0.07). Moreover, CRAg’s quality showed to be an important predictor of PFS. Patients with a high proportion of CRAgs matching at least one of the quality databases showed better PFS (p=0.02). Further, a taxa-specific analysis indicated that commensal CRAgs load was a better predictor of PFS (p<0.008) than relative abundance. Altogether, our work supports a mechanistic link between the microbiome, neoantigens, and immuno-therapy. Citation Format: Ravin Poudel, Die Dai, Fang Li, Xiaochen Yin, Yan Kou, Antonio L. C. Gomes. Cross-reacting antigens between the intestinal microbiome and tumor neoantigen are associated with immune checkpoint inhibitor response in a gastrointestinal tumor cohort [abstract]. In: Proceedings of the AACR Special Conference on Colorectal Cancer; 2022 Oct 1-4; Portland, OR. Philadelphia (PA): AACR; Cancer Res 2022;82(23 Suppl_1):Abstract nr B003.

Allergenic food protein consumption is associated with systemic IgG antibody responses in non-allergic individuals

Although food-directed immunoglobulin E (IgE) has been studied in the context of allergies, the prevalence and magnitude of IgG responses against dietary antigens are incompletely characterized in the general population. Here, we measured IgG binding against food and environmental antigens obtained from allergen databases and the immune epitope database (IEDB), represented in a phage displayed library of 58,233 peptides. By profiling blood samples of a large cohort representing the average adult Israeli population (n= 1,003), we showed that many food antigens elicited systemic IgG in up to 50% of individuals. Dietary intake of specific food protein correlated with antibody binding, suggesting that diet can shape the IgG epitope repertoire. Our work documents abundant systemic IgG responses against food antigens and provides a reference map of the exact immunogenic epitopes on a population scale, laying the foundation to unravel the role of food- and environmental antigen-directed antibody binding in disease contexts.

An Approach to Identify HLA Class II Immunogenic Epitopes in the Greek Population through Machine Learning Algorithms

Current pre-transplantation routine matching involves serum anti-HLA antibodies quantification but cannot always preclude unfavorable graft outcomes. Epitope-based matching is proposed as a more precise approach, but to date no epitope-matching algorithm provides a satisfactory predictive tool for transplantation outcomes. In this study, anti-HLA-II loci responses from 1748 patients were analyzed with unsupervised machine learning algorithms, namely principal component analysis (PCA) and antigenic distances, projected as dendrograms. PCA for anti-HLA-DR anti-bodies revealed three main clusters of responses: anti-HLA-DR51 combined with anti-HLA-DRB1*01, anti-HLA-DR52 combined with anti-HLA-DRB1*08 and anti-HLA-DR53 combined with anti-HLA-DRB1*10. The dendrogram for anti-HLA-DR confirmed the pattern and showed further bisection of each cluster. Common epitopes present exclusively in all HLA molecules of each cluster were determined following the HLA epitope registry. Thus, we propose that 19 out of 123 HLA-DR epitopes are those that mainly lead anti-HLA-DR responses in the studied population. Likewise, we identified 22 out of 83 epitopes responsible for anti-HLA-DQ and 13 out of 62 responsible for anti-HLA-DP responses. Interpretation of these results may elucidate mechanisms of interlocus cross-reactivity, providing an alternative way of estimating the significance of each epitope in a population and thus suggesting a novel strategy towards optimal donor selection.

Immune signature atlas of vaccines: learning from the good responders.

Understanding immune determinants of vaccine-mediated immunogenicity could further provide rational vaccine design. Two research groups revealed pre-existing and early innate immune signatures associated with better vaccine-mediated antibody responses.

Epitope profiling of monoclonal antibodies to the immunodominant antigen BmGPI12 of the human pathogen Babesia microti.

The significant rise in the number of tick-borne diseases represents a major threat to public health worldwide. One such emerging disease is human babesiosis, which is caused by several protozoan parasites of the Babesiagenus of which B. microti is responsible for most clinical cases reported to date. Recent studies have shown that during its intraerythrocytic life cycle, B. microti exports several antigens into the mammalian host using a novel vesicular-mediated secretion mechanism. One of these secreted proteins is the immunodominant antigen BmGPI12, which has been demonstrated to be a reliable biomarker of active B. microti infection. The major immunogenic determinants of this antigen remain unknown. Here we provide a comprehensive molecular and serological characterization of a set of eighteen monoclonal antibodies developed against BmGPI12 and a detailed profile of their binding specificity and suitability in the detection of active B. microti infection. Serological profiling and competition assays using synthetic peptides identified five unique epitopes on the surface of BmGPI12 which are recognized by a set of eight monoclonal antibodies. ELISA-based antigen detection assays identified five antibody combinations that specifically detect the secreted form of BmGPI12 in plasma samples from B. microti-infected mice and humans but not from other Babesia species or P. falciparum.

In silico and in vitro arboviral MHC class I-restricted-epitope signatures reveal immunodominance and poor overlapping patterns.

The present work sought to identify MHC-I-restricted peptide signatures for arbovirus using in silico and in vitro peptide microarray tools. First, an in-silico analysis of immunogenic epitopes restricted to four of the most prevalent human MHC class-I was performed by identification of MHC affinity score. For that, more than 10,000 peptide sequences from 5 Arbovirus and 8 different viral serotypes, namely Zika (ZIKV), Dengue (DENV serotypes 1-4), Chikungunya (CHIKV), Mayaro (MAYV) and Oropouche (OROV) viruses, in addition to YFV were analyzed. Haplotype HLA-A*02.01 was the dominant human MHC for all arboviruses. Over one thousand HLA-A2 immunogenic peptides were employed to build a comprehensive identity matrix. Intending to assess HLAA*02:01 reactivity of peptides in vitro, a peptide microarray was designed and generated using a dimeric protein containing HLA-A*02:01. The comprehensive identity matrix allowed the identification of only three overlapping peptides between two or more flavivirus sequences, suggesting poor overlapping of virus-specific immunogenic peptides amongst arborviruses. Global analysis of the fluorescence intensity for peptide-HLA-A*02:01 binding indicated a dose-dependent effect in the array. Considering all assessed arboviruses, the number of DENV-derived peptides with HLA-A*02:01 reactivity was the highest. Furthermore, a lower number of YFV-17DD overlapping peptides presented reactivity when compared to non-overlapping peptides. In addition, the assessment of HLA-A*02:01-reactive peptides across virus polyproteins highlighted non-structural proteins as "hot-spots". Data analysis supported these findings showing the presence of major hydrophobic sites in the final segment of non-structural protein 1 throughout 2a (Ns2a) and in nonstructural proteins 2b (Ns2b), 4a (Ns4a) and 4b (Ns4b). To our knowledge, these results provide the most comprehensive and detailed snapshot of the immunodominant peptide signature for arbovirus with MHC-class I restriction, which may bring insight into the design of future virus-specific vaccines to arboviruses and for vaccination protocols in highly endemic areas.

Immunogenicity of the Currently Recommended Pneumococcal Vaccination Schedule in Patients with Chronic Lymphocytic Leukaemia

Background Patients with chronic lymphocytic leukemia (CLL) are at increased risk of both invasive pneumococcal disease (IPD) and community acquired pneumonia (CAP) caused by Streptococcus pneumoniae. Therefore, international guidelines recommend pneumococcal vaccination for all CLL patients, preferably before initiation of treatment. The vaccination schedule recommended in the European Conference on Infections in Leukaemia (ECIL) 7 guideline consists of Prevnar13®, a 13-valent pneumococcal conjugated vaccine (PCV13) followed 2 months later by Pneumovax23®, a 23-valent polysaccharide vaccine (PPSV23). However, the immunogenicity of this sequential pneumococcal vaccination schedule in CLL patients is unknown. The aim of this study is to assess the immunogenicity of PCV13 followed by PPSV23 in untreated and treated CLL patients, as CLL treatment has been shown to be a major determinant of COVID-19 vaccine immunogenicity. Methods We quantified pneumococcal immunoglobulin G (IgG) concentrations to 5 pneumococcal serotypes shared across both vaccines (6B, 9V, 14, 19F, 23F) and 4 serotypes unique to PPSV23 (8, 15B, 20, 33F) before and 4-8 weeks after vaccination using a validated multiplex immunoassay, Luminex®. The primary outcome was the serologic response rate (SRR), defined as a ≥4-fold increase in ≥70% of the serotype-specific anti-pneumococcal IgGs. Secondary outcome was serologic protection, defined as an antibody concentration of ≥1.3 mcg/ml for ≥70% of all measured serotypes, in accordance with the definition by the American Academy of Allergy, Asthma & Immunology. Additional secondary outcomes were serotype-specific serologic protection and IgG level dynamics. Results We included 113 CLL patients (mean age 66 years; 39/113 female) in one academic and six teaching hospitals in the Netherlands. All completed the vaccination and measurement schedule. Median time since CLL diagnosis was 3.6 years. Of the 113 patients 33 had previously received CLL treatment, including rituximab (22 patients), cytotoxic chemotherapy (11), ibrutinib (10) and/or venetoclax (7). Seven patients received intravenous immunoglobulin prior to the vaccinations, while 6 received this during the vaccination scheme. The SRR was 11.5% (15% in untreated and 3% in treated patients) (Table 1). A statistically significant increase in all serotype-specific antibody concentrations was observed after vaccination (p <0.001) (Figure 1). The immunogenicity varied per serotype: the percentage of patients mounting a 4-fold increase was lowest for serotype 20 (16%) and highest for serotype 9V (40%). The serotype-specific anti-pneumococcal IgGs after vaccination were all significantly lower in treated than in previously untreated patients. Nevertheless, treatment status was not statistically significant associated with the SRR. Total IgG concentration prior to vaccination was the only evaluated factor associated with the SRR (OR 5.69; p = 0.008). Serologic protection increased from 1.8% before vaccination to 10.6% after both vaccinations (13.8% in untreated and 3% in treated patients). Serotype-specific protection was highest for serotype 14 and 33F (43.4% of patients obtained a concentration of ≥1.3 mcg/ml) and lowest for serotype 6B (16.8%). Conclusion The serologic response to combined PCV13 and PPSV23 vaccination is impaired in previously treated CLL patients as well as in treatment-naive patients, a contrast with COVID-19 vaccination. These findings emphasize the importance of further investigation into the pneumococcal vaccination response in CLL patients. Since patients with CLL are insufficiently protected after a single dose of PCV13, research should focus on multi-dose PCV schedules with the currently available higher valent T cell dependent conjugate vaccines. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

CTIM-30. THE PRIVATE AND RECURRING ANTIGENIC PROFILE OF HUMAN MEDULLOBLASTOMA

Abstract BACKGROUND Identifying tumor rejection antigens remains a major barrier to developing effective immunotherapeutics and their application to pediatric brain tumors. We performed a multi-faceted computer algorithm, the Open Reading Frame Antigen Network (O.R.A.N.), on medulloblastoma transcription profiles and predicted antigens across a broad array of antigen classes. METHODS Patient-specific HLA haplotypes were called via customized Optitype and Phlat algorithms. Only expressed mutations such as single nucleotide variations, small indels, gene fusions, and Tumor Associated Antigens (TAAs) were used for antigenic epitope predictions. TAAs were selected only if expressed &amp;gt; 1 transcript per million (TPM) in tumor and the standardized expression across a human tissue database. Immunogenic TAA epitopes were screened against a customized human proteomic library to guarantee that epitopes were not shared by other expressed isoforms or genes. Immune deconvolution with single cell RNASeq integration was leveraged for teasing out medulloblastoma immunologic landscape. RESULTS We hypothesized that medulloblastomas are immunologically heterogeneous and express genes with limited normal tissue expression that may serve as targets for immunotherapy. In this study, most neoantigens from medulloblastoma patients were found private suggesting a personalized neoantigen based therapy was on demand. In addition, recurring neoantigens were common in SHH but composed only a small proportion of putative antigens in WNT, Group 3 and Group 4 patients. However, recurring TAAs were found to be more commonly expressed in the latter three molecular subgroups but not in SHH. Together, combining personalized neoantigen vaccine and taking advantage of recurring TAAs approach may maximize anti medulloblastoma effect. CONCULSION Medulloblastoma is a heterogeneous disease, and the current standard of care treatments don’t take that into account. Newer, and safer, patient-specific treatment approaches are required to treat high-risk patients who are not cured by the standard therapies .Cellular immunotherapy might be key to improving survival and avoiding morbidity.

Mucosal Infection with Unmasked Candida albicans Cells Impacts Disease Progression in a Host Niche-Specific Manner.

Shielding the immunogenic cell wall epitope β(1, 3)-glucan under an outer layer of mannosylated glycoproteins is an essential virulence factor deployed by Candida albicans during systemic infection. Accordingly, mutants with increased β(1, 3)-glucan exposure (unmasking) display increased immunostimulatory capabilities in vitro and attenuated virulence during systemic infection in mice. However, little work has been done to assess the impact of increased unmasking during the two most common manifestations of candidiasis, namely, oropharyngeal candidiasis (OPC) and vulvovaginal candidiasis (VVC). We have shown previously that the expression of a single hyperactive allele of the MAP3K STE11ΔN467 induces unmasking via the Cek1 MAPK pathway, attenuates fungal burden, and prolongs survival during systemic infection in mice. Here, we expand on these findings and show that infection with an unmasked STE11ΔN467 mutant also impacts disease progression during OPC and VVC murine infection models. Male mice sublingually infected with the STE11ΔN467 mutant showed a significant reduction in tongue fungal burden at 2 days postinfection and a modest reduction at 5 days postinfection. However, we find that selection for STE11ΔN467 suppressor mutants that no longer display increased unmasking occurs within the oral cavity and is likely responsible for the restoration of fungal burden trends to wild-type levels later in the infection. In the VVC infection model, no attenuation in fungal burden was observed. However, polymorphonuclear cell recruitment and interleukin-1β (IL-1β) levels within the vaginal lumen, markers of immunopathogenesis, were increased in mice infected with unmasked STE11ΔN467 cells. Thus, our data suggest a niche-specific impact for unmasking on disease progression.

Genome-wide scan for potential CD4+ T-cell vaccine candidates in Candida auris by exploiting reverse vaccinology and evolutionary information.

Candida auris is a globally emerging fungal pathogen responsible for causing nosocomial outbreaks in healthcare associated settings. It is known to cause infection in all age groups and exhibits multi-drug resistance with high potential for horizontal transmission. Because of this reason combined with limited therapeutic choices available, C. auris infection has been acknowledged as a potential risk for causing a future pandemic, and thus seeking a promising strategy for its treatment is imperative. Here, we combined evolutionary information with reverse vaccinology approach to identify novel epitopes for vaccine design that could elicit CD4+ T-cell responses against C. auris. To this end, we extensively scanned the family of proteins encoded by C. auris genome. In addition, a pathogen may acquire substitutions in epitopes over a period of time which could cause its escape from the immune response thus rendering the vaccine ineffective. To lower this possibility in our design, we eliminated all rapidly evolving genes of C. auris with positive selection. We further employed highly conserved regions of multiple C. auris strains and identified two immunogenic and antigenic T-cell epitopes that could generate the most effective immune response against C. auris. The antigenicity scores of our predicted vaccine candidates were calculated as 0.85 and 1.88 where 0.5 is the threshold for prediction of fungal antigenic sequences. Based on our results, we conclude that our vaccine candidates have the potential to be successfully employed for the treatment of C. auris infection. However, in vivo experiments are imperative to further demonstrate the efficacy of our design.

Cancer stem cell antigen nanodisc cocktail elicits anti-tumor immune responses in melanoma.

One of the major reasons for poor cancer outcomes is the existence of cancer stem cells (CSCs). CSCs are a small subpopulation of tumor cells that can self-renew, differentiate into the majority of tumor cells, and maintain tumorigenicity. As CSCs are resistant to traditional chemotherapy and radiation, they contribute to metastasis and relapse. Thus, new approaches are needed to target and eliminate CSCs. Here, we sought to target and reduce the frequency of CSCs in melanoma by therapeutic vaccination against CSC-associated transcription factors, such as Sox2 and Nanog, and aldehyde dehydrogenase (ALDH). Toward this goal, we have identified novel immunogenic peptide epitopes derived from CSC-associated Sox2 and Nanog and synthesized synthetic high-density lipoprotein (sHDL) nanodisc vaccine formulated with Sox2, Nanog, and ALDH antigen peptides together with CpG, a Toll-like receptor 9 agonist. Vaccination with nanodiscs containing six CSC antigen peptides elicited robust T cell responses against CSC-associated antigens and promoted intratumoral infiltration of CD8+ T cells, while reducing the frequency of CSCs and CD4+ regulatory T cells within melanoma tumors. Nanodisc vaccination effectively reduced tumor growth and significantly extended animal survival without toxicity toward normal stem cells. Overall, our therapeutic strategy against CSCs represents a cost-effective, safe, and versatile approach that may be applied to melanoma and other cancer types, as well as serve as a critical component in combined therapies to target and eliminate CSCs.

The Advantage of Using Immunoinformatic Tools on Vaccine Design and Development for Coronavirus.

After the outbreak of SARS-CoV-2 by the end of 2019, the vaccine development strategies became a worldwide priority. Furthermore, the appearances of novel SARS-CoV-2 variants challenge researchers to develop new pharmacological or preventive strategies. However, vaccines still represent an efficient way to control the SARS-CoV-2 pandemic worldwide. This review describes the importance of bioinformatic and immunoinformatic tools (in silico) for guide vaccine design. In silico strategies permit the identification of epitopes (immunogenic peptides) which could be used as potential vaccines, as well as nonacarriers such as: vector viral based vaccines, RNA-based vaccines and dendrimers through immunoinformatics. Currently, nucleic acid and protein sequential as well structural analyses through bioinformatic tools allow us to get immunogenic epitopes which can induce immune response alone or in complex with nanocarriers. One of the advantages of in silico techniques is that they facilitate the identification of epitopes, while accelerating the process and helping to economize some stages of the development of safe vaccines.

Exploring YidR Gene from Klebsiella pneumoniae To Design a Multi-epitope Vaccine Using Immunoinformatics Approach

Klebsiella pneumoniae is the main leading cause of hospital-acquired infection, leading to severe infections such as pneumonia and urinary tract infection. There is an urge to develop an efficient Klebsiella vaccine, and epitope-based vaccines may offer a practical choice. Therefore, this study aims to design an epitope-based vaccine construct. YidR gene is expressed in all strains of Klebsiella with 97.6% of sequence homology, which makes it a potential vaccine candidate. In silico approach was used to make a multi-epitope vaccine construct consisting of immunogenic epitopes against the YidR gene of Klebsiella. Acquired multi-epitopes vaccine was analyzed for antigenicity, allergenicity, toxicity, and various physicochemical parameters. Molecular docking simulation was performed using TLR2 and TLR4 to asses binding affinity with the designed vaccine construct. The results showed that the predicted multi-epitope-based vaccine candidate is non-allergen, non-toxic, and has an efficient binding affinity towards TLR2 and TLR4 that could effectively induce immune responses.

Immunogenic analysis of epitope-based vaccine candidate induced by photodynamic therapy in MDA-MB-231 triple-negative breast cancer cells

BackgroundPhotodynamic therapy (PDT) is used to treat tumors through selective cytotoxic effects. PDT induces damage-associated molecular patterns (DAMPs) expression, which can cause an immunogenic death cell (IDC). In this study we identified potential immunogenic epitopes generated by PDT on triple-negative breast cancer cell line (MDA-MB-231). MethodsMDA-MB-231 cells were exposed to PDT using ALA (160 µg/mL)/630 nm at 8 J/cm2. Membrane proteins were extracted and separated by 2D PAGE. Proteins overexpressed were identified by LC-MS/MS and analyzed in silico through a peptide-HLA docking in order to identify the epitopes with more immunogenicity and antigenicity properties, as well as lower allergenicity and toxicity activity. The selected peptides were evaluated in response to macrophage activation and cytokine release by flow cytometry. ResultsDifferential proteins were overexpressed in the cells treated with PDT. A group of 16 peptides were identified from them, established in a rigorous selection by measuring antigenicity, immunogenicity, allergenicity, and toxicity in silico. The final selection was based on molecular dynamics, where 2 peptides showed the highest stability regarding to the RMSD value. These peptides were obtained from the proteins calreticulin and HSP90. The cytokine analysis evidenced macrophage activation by the releasing of TNF. ConclusionTwo peptides were identified from calreticulin and HSP90; proteins induced by PDT in MDA-MB-231 cells. Both epitopes showed immunogenic potential as a peptide-based vaccine for triple-negative breast cancer.

Genome-Based Multi-Antigenic Epitopes Vaccine Construct Designing against Staphylococcus hominis Using Reverse Vaccinology and Biophysical Approaches.

Staphylococcus hominis is a Gram-positive bacterium from the staphylococcus genus; it is also a member of coagulase-negative staphylococci because of its opportunistic nature and ability to cause life-threatening bloodstream infections in immunocompromised patients. Gram-positive and opportunistic bacteria have become a major concern for the medical community. It has also drawn the attention of scientists due to the evaluation of immune evasion tactics and the development of multidrug-resistant strains. This prompted the need to explore novel therapeutic approaches as an alternative to antibiotics. The current study aimed to develop a broad-spectrum, multi-epitope vaccine to control bacterial infections and reduce the burden on healthcare systems. A computational framework was designed to filter the immunogenic potent vaccine candidate. This framework consists of pan-genomics, subtractive proteomics, and immunoinformatics approaches to prioritize vaccine candidates. A total of 12,285 core proteins were obtained using a pan-genome analysis of all strains. The screening of the core proteins resulted in the selection of only two proteins for the next epitope prediction phase. Eleven B-cell derived T-cell epitopes were selected that met the criteria of different immunoinformatics approaches such as allergenicity, antigenicity, immunogenicity, and toxicity. A vaccine construct was formulated using EAAAK and GPGPG linkers and a cholera toxin B subunit. This formulated vaccine construct was further used for downward analysis. The vaccine was loop refined and improved for structure stability through disulfide engineering. For an efficient expression, the codons were optimized as per the usage pattern of the E coli (K12) expression system. The top three refined docked complexes of the vaccine that docked with the MHC-I, MHC-II, and TLR-4 receptors were selected, which proved the best binding potential of the vaccine with immune receptors; this was followed by molecular dynamic simulations. The results indicate the best intermolecular bonding between immune receptors and vaccine epitopes and that they are exposed to the host’s immune system. Finally, the binding energies were calculated to confirm the binding stability of the docked complexes. This work aimed to provide a manageable list of immunogenic and antigenic epitopes that could be used as potent vaccine candidates for experimental in vivo and in vitro studies.

Immunoinformatic-based design of immune-boosting multiepitope subunit vaccines against monkeypox virus and validation through molecular dynamics and immune simulation.

Monkeypox virus is the causative agent of monkeypox disease, belonging to an orthopoxvirus genus, with a disease pattern similar to that of smallpox. The number of monkeypox cases have robustly increased recently in several countries around the world, potentially causing an international threat. Therefore, serious measures are indispensable to be taken to mitigate the spread of the disease and hence, under these circumstances, vaccination is the best choice to neutralize the monkeypox virus. In the current study, we used immunoinformatic approaches to target the L1R, B5R, and A33R proteins of the monkeypox virus to screen for immunogenic cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and B-cell epitopes to construct multiepitope subunit vaccines. Various online tools predicted the best epitope from immunogenic targets (L1R, B5R, and A33R) of monkeypox virus. The predicted epitopes were joined together by different linkers and subjected to 3D structure prediction. Molecular dynamics simulation analysis confirmed the proper folding of the modeled proteins. The strong binding of the constructed vaccines with human TLR-2 was verified by the molecular docking and determination of dissociation constant values. The GC content and codon adaptation index (CAI) values confirmed the high expression of the constructed vaccines in the pET-28a (+) expression vector. The immune response simulation data delineated that the injected vaccines robustly activated the immune system, triggering the production of high titers of IgG and IgM antibodies. In conclusion, this study provided a solid base of concept to develop dynamic and effective vaccines that contain several monkeypox virus-derived highly antigenic and nonallergenic peptides to control the current pandemic of monkeypox virus.

Computational Clues of Immunogenic Hotspots in Plasmodium falciparum Erythrocytic Stage Vaccine Candidate Antigens: In Silico Approach.

Malaria is the most pernicious parasitic infection, and Plasmodium falciparum is the most virulent species with substantial morbidity and mortality worldwide. The present in silico investigation was performed to reveal the biophysical characteristics and immunogenic epitopes of the 14 blood-stage proteins of the P. falciparum using comprehensive immunoinformatics approaches. For this aim, various web servers were employed to predict subcellular localization, antigenicity, allergenicity, solubility, physicochemical properties, posttranslational modification sites (PTMs), the presence of signal peptide, and transmembrane domains. Moreover, structural analysis for secondary and 3D model predictions were performed for all and stable proteins, respectively. Finally, human helper T lymphocyte (HTL) epitopes were predicted using HLA reference set of IEDB server and screened in terms of antigenicity, allergenicity, and IFN-γ induction as well as population coverage. Also, a multiserver B-cell epitope prediction was done with subsequent screening for antigenicity, allergenicity, and solubility. Altogether, these proteins showed appropriate antigenicity, abundant PTMs, and many B-cell and HTL epitopes, which could be directed for future vaccination studies in the context of multiepitope vaccine design.