Prediction Of Antigenic Epitopes Research Articles

Phylogenetic analysis and antigenic epitope prediction for E6 and E7 of Alpha-papillomavirus 9 in Taizhou, China.

Alpha-papillomavirus 9 (α-9) is a member of the human papillomavirus (HPV) α genus, causing 75% invasive cervical cancers worldwide. The purpose of this study was to provide data for effective treatment of HPV-induced cervical lesions in Taizhou by analysing the genetic variation and antigenic epitopes of α-9 HPV E6 and E7. Cervical exfoliated cells were collected for HPV genotyping. Positive samples of the α-9 HPV single type were selected for E6 and E7 gene sequencing. The obtained nucleotide sequences were translated into amino acid sequences (protein primary structure) using MEGA X, and positive selection sites of the amino acid sequences were evaluated using PAML. The secondary and tertiary structures of the E6 and E7 proteins were predicted using PSIPred, SWISS-MODEL, and PyMol. Potential T/B-cell epitopes were predicted by Industrial Engineering Database (IEDB). From 2012 to 2023, α-9 HPV accounted for 75.0% (7815/10423) of high-risk HPV-positive samples in Taizhou, both alone and in combination with other types. Among these, single-type-positive samples of α-9 HPV were selected, and the entire E6 and E7 genes were sequenced, including 298 HPV16, 149 HPV31, 185 HPV33, 123 HPV35, 325 HPV52, and 199 HPV58 samples. Compared with reference sequences, 34, 12, 10, 2, 17, and 17 nonsynonymous nucleotide mutations were detected in HPV16, 31, 33, 35, 52, and 58, respectively. Among all nonsynonymous nucleotide mutations, 19 positive selection sites were selected, which may have evolutionary significance in rendering α-9 HPV adaptive to its environment. Immunoinformatics predicted 57 potential linear and 59 conformational B-cell epitopes, many of which are also predicted as CTL epitopes. The present study provides almost comprehensive data on the genetic variations, phylogenetics, positive selection sites, and antigenic epitopes of α-9 HPV E6 and E7 in Taizhou, China, which will be helpful for local HPV therapeutic vaccine development.

Design and development of multiepitope chimeric antigens by bioinformatic and bacterial based recombinant expression methods, with potential application for bovine tuberculosis serodiagnosis

Bovine tuberculosis (bTB), which is caused by Mycobacterium bovis, is a single health concern, which causes economic losses, is a sanitary barrier and is a zoonotic concern. The golden-pattern intradermic tests have low sensitivity of about 50%. To fix this sensitivity problem, immunoassays could be a powerful tool. However, few studies produced antigens for bTB immunoassays, which needs improvements. Aim of this study was to produce multiepitope chimeric antigens (MCA) to use for bTB diagnosis. To achieve MCA design and development, extensive bibliographic search, antigenic epitope prediction, specificity, hydrophobicity, and 3D structure modeling analyses were performed, as well as cloning, expression and purification. Seven epitopes from four different target proteins (MPB-70, MPB-83, ESAT-6 and GroEL) were combined in five chimeras containing five repetitions of each epitope to enhance antibodies affinity. 3D predicted models revealed that all chimeras have a high percentage of disorder, which could enhance antibody recognition, although taking to protein instability. Each chimera was cloned into pET28a (+) expression plasmids and expressed in six Escherichia coli expression strains. Chimeras 3, 4 and 5 could be solubilized in 8 M urea and purified by ion exchange affinity chromatography. Against bTB positive and negative sera, purified chimera 5 had the best results in indirect dot blot and ELISA, as well as in lateral flow dot blot immunoassay. In conclusion, chimera 5, an MPB-83 containing MCA, could be used for further studies, aimed to develop a serologic or rapid test for bTB diagnosis.

UspA gene-based phylogenetic analysis and antigenic epitope prediction for Escherichia coli strains of avian origin.

Pathogenic Escherichia coli (E. coli) is responsible for various local and systemic infections in animal and human populations. Conventional methods for the detection and identification of E. coli are time-consuming and less reliable for atypical strains. The uspA gene has been widely used as a target for the detection of E. coli. The present study was aimed at phylogenetic analysis of the uspA gene sequences to determine the evolutionary relationships between the strains and other members of the Enterobacteriaceae family. In addition, the unique differences in the sequences of the current study with Salmonella and Shigella species were tested using Tajima's molecular clock test. Antigenic epitope prediction was performed to locate the B-cell epitope region of the UspA protein. Two E. coli isolates of avian origin and strains from the National Center for Biotechnology Information (NCBI) database were used for prediction. The Immune Epitope Database (IEDB) server, Bepitope, ABCpred, SVMTrip, and ElliPro server were used to identify B-cell epitopes. The 3D structure was predicted using SWISS-MODEL. Phylogenetic analysis of the isolates from the current study revealed that both OM837340 and OM837341 sequences from the current study had maximum nucleotide homology (nt) of 99.87%-100% with E. coli isolates and minimum nt homology of 84.08% with Salmonella enteritidis and S. Hissar. The isolates in the current study had a homology of 98.87%, while the homology with Shigella species was 99.25%. Seven silent mutations were observed in the coding region of the UspA protein of ECO9LTBW (current study). Modeling of the UspA protein revealed a maximum homology of 67.86% with the Protein Data Bank in Europe (PDBe), also validated by the Ramachandran plot. No significant differences were found in the coding regions of uspA of Salmonella, Shigella, and E. coli with Tajima's test. For the E. coli isolates, a total of 24 linear B-cell and seven discontinuous epitopes were predicted using in-silico analysis. When the results of the predicted peptides were compared, two peptides, namely ARPYNA and YSDLYTGLIDVNLGDMQKRISEE, were found suitable candidates. In conclusion, the uspA gene appears to be conserved among E. coli isolates and can be used for molecular detection.

Sequence characteristics of Rhipicephalus microplus Enolase gene and prediction of structure and antigenic epitopes of its encoding protein

To analyze the sequence characteristics of Rhipicephalus microplus Enolase gene, and to predict the secondary and tertiary structure and antigenic epitopes of the Enolase protein. Sixty-two engorged female R. microplus were sampled from a yellow cattle breeding farm in Zhijiang County, Huaihua City, Hunan Province in June 25, 2022. Genomic DNA was isolated from R. microplus, and the Enolase gene was amplified using PCR assay, followed by cloning, sequencing and expression of the amplification product. The sequence characteristics of the Enolase gene were analyzed using the software Clustal X, and the gene sequence was translated into amino acid sequences. The secondary and tertiary structures of the Enolase protein were deduced using the software PRABI, and the physicochemical properties of the Enolase protein were analyzed using the software PRABI. In addition, the B- and T-cell epitopes of the Enolase protein were predicted using the software ABCpred Prediction, Scratch, IEDB and NetCTL. The R. microplus Enolase gene sequence was 1 323 bp in size, and the contents of A, T, G and C bases were 24.5%, 22.5%, 27.0% and 26.0%,with 47.0% of A + T content and 53.0% of G + C content. The R. microplus Enolase gene encoded 434 amino acids, and the Enolase protein had a molecular weight of 47.12 kDa. The secondary structure of the Enolase protein contained 186 α-helixes (42.86%), 32 β-turns (7.37%), 144 random coils (33.18%) and 72 extended strands (16.59%). The Enolase protein was most probably present in cytoplasm (76.7%), followed by in mitochondrion (39.1%) and nucleus (21.7%), and the Enolase protein had no signal peptide or transmembrane domain. In addition, the Enolase protein had 14 B-cell dominant epitopes and 8 T-cell dominant epitopes. The R. microplus Enolase gene sequence exhibits a GC preference, and its encoding Enolase protein is an acidic and hydrophilic protein, with α-helixes and random coils as its primary structure, and presenting B- and T-cell dominant epitopes, which is a potential target for development of vaccines against R. microplus.

A New Strategy for Mapping Epitopes of LACK and PEPCK Proteins of Leishmania amazonensis Specific for Major Histocompatibility Complex Class I.

Leishmaniasis represents a complex of diseases with a broad clinical spectrum and epidemiological diversity, considered a major public health problem. Although there is treatment, there are still no vaccines for cutaneous leishmaniasis. Because Leishmania spp. is an intracellular protozoan with several escape mechanisms, a vaccine must provoke cellular and humoral immune responses. Previously, we identified the Leishmania homolog of receptors for activated C kinase (LACK) and phosphoenolpyruvate carboxykinase (PEPCK) proteins as strong immunogens and candidates for the development of a vaccine strategy. The present work focuses on the in silico prediction and characterization of antigenic epitopes that might interact with mice or human major histocompatibility complex class I. After immunogenicity prediction on the Immune Epitope Database (IEDB) and the Database of MHC Ligands and Peptide Motifs (SYFPEITHI), 26 peptides were selected for interaction assays with infected mouse lymphocytes by flow cytometry and ELISpot. This strategy identified nine antigenic peptides (pL1-H2, pPL3-H2, pL10-HLA, pP13-H2, pP14-H2, pP15-H2, pP16-H2, pP17-H2, pP18-H2, pP26-HLA), which are strong candidates for developing a peptide vaccine against leishmaniasis.

Eukaryotic expression and antigen epitope prediction of the LRRC15 protein in excretory secretory antigens of Taenia solium cysticercus

To conduct eukaryotic expression of the leucine-rich repeat containing 15 (LRRC15), a differentially expressed protein in excretory secretory antigens of Taenia solium cysticercus, and predict its antigen epitope. The molecular weight, stability, amino acid sequence composition, isoelectric point and T lymphocyte epitope of the LRRC15 protein were predicted using the bioinformatics online softwares ExPASy-PortParam and Protean. The full-length splicing primers were designed using PCR-based accurate synthesis, and the LRRC15 gene was synthesized. The recombinant pcDNA3.4-LRRC15 plasmid was constructed and transfected into HEK293 cells to express the LRRC15 protein. In addition, the LRRC15 protein was characterized by sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) and Western blotting. The recombinant pcDNA3.4-LRRC15 plasmid was successfully constructed, which expressed the target LRRC15 protein with an approximately molecular weight of 70 kDa. Bioinformatics prediction with the ExPASy-PortParam software showed that LRRC15 was a hydrophilic protein, which was consisted of 644 amino acids and had a molecular weight of 69.89 kDa and an isoelectric point of 5.6. The molecular formula of the LRRC15 protein was C3073H4942N846O953S28 and had an instability coefficient is 50.3, indicating that LRRC15 was an instable protein. Bioinformatics prediction with the Protean software showed that the dominant T-cell antigen epitopes were located in 292 to 295, 353 to 361, 521 to 526 and 555 to 564 amino acids of the LRRC15 protein, and the T-cell antigen epitopes with a high hydrophilicity, good flexibility, high surface accessibility and high antigenicity index were found in 122 to 131, 216 to 233, 249 to 254, 333 to 343, 358 to 361, 368 to 372, 384 to 386, 407 to 412, 445 to 450, 469 to 481, 553 to 564, 588 to 594, 607 to 617 and 624 to 639 amino acids. Following transfection of the recombinant pcDNA3.4-LRRC15 plasmid into HEK293 cells, SDS-PAGE and Western blotting identified LRRC15 proteins in cell secretory culture media, cell lysis supernatants and sediments. The LRRC15-His fusion protein was purified from the cell culture medium, and SDS-PAGE identified a remarkable band at approximately 70 kDa, while Western blotting successfully recognized the band of the recombinant LRRC15 protein. The eukaryotic expression and antigen epitope prediction of the LRRC15 protein in the excretory secretory antigens of T. solium cysticercus have been successfully performed, which provides insights into further understandings of its biological functions.

Omicron variant receptor-binding domain phylogenetics and molecular dynamics

BackgroundWe investigated the evolutionary relationships, mutations, antigenic epitopes, and structural dynamics of the receptor-binding domain (RBD) of SARS-CoV-2, Omicron and other recently evolved variants. MethodsThe RBD of SARS-CoV-2 and its Omicron, Alpha, Beta, Gamma, Delta, and Mu variants were subjected to pairwise sequence matrix evaluation, antigenic epitope prediction, and phylogenetic relationship and structural dynamics analyses. ResultsThe Omicron RBD contained 13–15 amino acid mutations, of which 12 were new and three conserved with other variants. In addition, two mutations found in the Alpha, Beta, Gamma, and Mu variants were not found in the Omicron RBD. The ultrametric clustering unweighted pair group method with arithmetic mean identified Omicron as a novel monophyletic class, but the neighbor-joining method clustered Omicron with Alpha and Delta variants. In the SARS-CoV-2 RBD, five main antigenic epitopes were predicted, and these epitopes were conserved across all SARS-CoV-2 variants tested. Surprisingly, the additional mutations in the Omicron variant increased the size of the expected antigenic sites in two of these antigenic epitopes. Molecular dynamics (MD) simulations revealed higher root-mean-square deviation in the Omicron RBD, greater residue fluctuation at residues 32–42 and 140–160, and increased solvent-accessible surface area. ConclusionsThe Omicron RBD mutations indicate the variant is within a new phylogenetic class of SARS-CoV-2 and significantly impact RBD structure, conformation, and molecular dynamics. However, conserved anticipated antigenic sites may imply partial changes in receptor affinity and response to immune reactions. Omicron RBD binding with the angiotensin-converting enzyme 2 receptor was suggested to be weaker than the original SARS-CoV-2 binding in MD simulations.

Design of a Novel Multi-Epitope Vaccine Against Echinococcus granulosus in Immunoinformatics.

All the time, echinococcosis is a global zoonotic disease which seriously endangers public health all over the world. In order to speed up the development process of anti-Echinococcus granulosus vaccine, at the same time, it can also save economic cost. In this study, immunoinformatics tools and molecular docking methods were used to predict and screen the antigen epitopes of Echinococcus granulosus, to design a multi-epitope vaccine containing B- and T-cell epitopes. The multi-epitope vaccine could activate B lymphocytes to produce specific antibodies theoretically, which could protect the human body against Echinococcus granulosus infection. It also could activate T lymphocytes and clear the infected parasites in the body. In this study, four CD8+ T-cell epitopes, three CD4+ T-cell epitopes and four B-cell epitopes of Protein EgTeg were identified by immunoinformatics methods. Meanwhile, three CD8+ T-cell epitopes, two CD4+ T-cell epitopes and four B-cell epitopes of Protein EgFABP1 were identified. We constructed the multi-epitope vaccine using linker proteins. The study based on the traditional methods of antigen epitope prediction, further optimized the prediction results combined with molecular docking technology and improved the precision and accuracy of the results. Finally, in vivo and in vitro experiments had verified that the vaccine designed in this study had good antigenicity and immunogenicity.

Abstract SY22-02: Personalized cancer vaccines: Antigen selection and translation into the clinic

Abstract Personalized cancer vaccination targets specific cancer mutations of the individual patient's tumor, also referred to as neoantigens. Such “bespoke” vaccines are now being tested in multiple cancers and in combination with checkpoint inhibitors. This session will discuss our computational methods for antigenic epitope prediction, antigen selection (personalized and shared neoantigens derived from frame-shift mutations), validation in vitro and in vivo and future directions for the field. Citation Format: Nina Bhardwaj. Personalized cancer vaccines: Antigen selection and translation into the clinic [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr SY22-02.

Computational evaluation of anticipated PE_PGRS39 protein involvement in host-pathogen interplay and its integration into vaccine development.

Mycobacterium tuberculosis causes more than 1 million deaths every year, which is higher than any other bacterial pathogen. Its success depends on its interaction with the host and its ability to regulate the host’s immune system for its own survival. Mycobacterium tuberculosis H37Rv (Mtb) proteome consists of unique PE_PGRS family proteins, which present a significant role in bacterial pathogenesis over the past years. Earlier evidence suggests that some PE_PGRS proteins display fibronectin-binding activity. In this manuscript, computational characterization of the PE_PGRS39 protein has indicated something peculiar about this protein. Investigation showed that PE_PGRS39 is an extracellular protein that, instead of acting as fibronectin-binding protein, might mimic fibronectin which binds to alpha-5 beta-1 (α5β1) integrin. PE_PGRS39 protein additionally turned into proven pieces of evidence to have motifs such as DXXG and GGXGXD and PXXP that bind with guanosine triphosphate (GTP), calcium, and host Src homology 3 (SH3) domains, respectively, in conjunction with RGD-integrin binding. These interactions designate the direct role of PE_PGRS39 in bacterial pathogenesis via cell adhesion and signaling. Additionally, the analysis showed that PE_PGRS39 is an antigenic protein and epitope prediction provided functional regions of the protein that trigger a cellular immune response facilitated by T or B cells. Further, an experimental analysis could also open up new avenues for developing novel drugs by targeting signaling motifs or novel vaccines using functional epitopes that could evoke an immune response in the host.

Current and prospective computational approaches and challenges for developing COVID-19 vaccines.

SARS-CoV-2, which causes COVID-19, was first identified in humans in late 2019 and is a coronavirus which is zoonotic in origin. As it spread around the world there has been an unprecedented effort in developing effective vaccines. Computational methods can be used to speed up the long and costly process of vaccine development. Antigen selection, epitope prediction, and toxicity and allergenicity prediction are areas in which computational tools have already been applied as part of reverse vaccinology for SARS-CoV-2 vaccine development. However, there is potential for computational methods to assist further. We review approaches which have been used and highlight additional bioinformatic approaches and PK modelling as in silico methods which may be useful for SARS-CoV-2 vaccine design but remain currently unexplored. As more novel viruses with pandemic potential are expected to arise in future, these techniques are not limited to application to SARS-CoV-2 but also useful to rapidly respond to novel emerging viruses.

Whole Genome Sequence Analysis of Porcine Astroviruses Reveals Novel Genetically Diverse Strains Circulating in East African Smallholder Pig Farms.

Astroviruses (AstVs) are widely distributed and are associated with gastroenteritis in human and animals. The knowledge of the genetic diversity and epidemiology of AstVs in Africa is limited. This study aimed to characterize astroviruses in asymptomatic smallholder piglets in Kenya and Uganda. Twenty-four samples were randomly selected from a total of 446 piglets aged below 6 months that were initially collected for rotavirus study and sequenced for whole genome analysis. Thirteen (13/24) samples had contigs with high identity to genus Mamastrovirus. Analysis of seven strains with complete (or near complete) AstV genome revealed variable nucleotide and amino acid sequence identities with known porcine astrovirus (PoAstV) strains. The U083 and K321 strains had nucleotide sequence identities ranging from 66.4 to 75.4% with the known PoAstV2 strains; U460 strain had nucleotide sequence identities of 57.0 to 65.1% regarding the known PoAstV3; and K062, K366, K451, and K456 strains had nucleotide sequence identities of 63.5 to 80% with the known PoAstV4 strains. The low sequence identities (<90%) indicate that novel genotypes of PoAstVs are circulating in the study area. Recombination analysis using whole genomes revealed evidence of multiple recombination events in PoAstV4, suggesting that recombination might have contributed to the observed genetic diversity. Linear antigen epitope prediction and a comparative analysis of capsid protein of our field strains identified potential candidate epitopes that could help in the design of immuno-diagnostic tools and a subunit vaccine. These findings provide new insights into the molecular epidemiology of porcine astroviruses in East Africa.

Analyzing 16S rRNA sequences from Vietnamese pathogenic Leptospira strains and in-silico prediction of potential antigenic epitopes on LipL21, LipL32 outer membrane lipoproteins

Leptospirosis, a zoonosis caused by Leptospira, is recognized as an emergent infectious disease. In currently, the lack of adequate diagnostic tools, vaccines are an attractive intervention strategy. In this experiment, a 550 bp fragment of large ribosomal RNA gene (16S rRNA) was sequenced and constructed phylogenetic tree from a panel of six Vietnamese pathogenic strains of Leptospira spirochetes (e.g., Pomona, Canicola, Mitis, Ictero haemohagiae, Bataviae, and Grippotyphosa). The results showed a close relationship of L.Pomona_VN and L.Hardjo (bootstrap: 99%). L.Canicola_VN and L.Ictero haemohagiae_VN appeared to be weak related to the classic L.Canicola, L. Grippotyphosa, these assemblage have a bootstrap support of 62%. The other strains (L.Mitis_VN and L.Grippotyphosa_VN) were appeared monophyletic, while their sister group (L.Bataviae_VN) relationship found only weak support (bootstrap: 62%). We also selected six genes [e.g. the immunoglobulin like proteins A and B (LigA and LigB genes), outer membrane protein (OmpL1 gene), and lipopolysaccharide (LipL32, LipL41, and LipL21 genes)] and checked gene expression in these Leptospira strains by polymerase chain reaction (PCR) method. There were three genes (e.g., LipL32, LipL21, and LigA genes) expressed in all strains, OmpL1 gene occured in 4 strains (L.Bataviae_VN, L.Canicola_VN, L.Grippotyphosa_VN and L.Mitis_VN), whereas LipL41 and LigB genes did not appear in any Leptospira strains. A multi-antigenic epitope potential of two gene (Lip L21 and Lip L32) was predicted by bioinformatic tools for designing a recombinant vaccine against leptospirosis. There were 3 multi-epitope regions (1 region and 95 antigenic epitope for B and T cells of LipL21 peptide; 2 regions and 124 antigenic epitope for both B and T cells of LipL32 peptide). It should be more of the deeply molecular biology studies to confirm the level agglutinating, antigen cleavage, peptide specificity matrices as well as neutralizing antibodies in the immune responses of DNA vaccine of these genes.

Improvement in prediction of antigenic epitopes using stacked generalisation: an ensemble approach.

The major intent of peptide vaccine designs, immunodiagnosis and antibody productions is to accurately identify linear B-cell epitopes. The determination of epitopes through experimental analysis is highly expensive. Therefore, it is desirable to develop a reliable model with significant improvement in prediction models. In this study, a hybrid model has been designed by using stacked generalisation ensemble technique for prediction of linear B-cell epitopes. The goal of using stacked generalisation ensemble approach is to refine predictions of base classifiers and to get rid of the worse predictions. In this study, six machine learning models are fused to predict variable length epitopes (6-49 mers). The proposed ensemble model achieves 76.6% accuracy and average accuracy of repeated 10-fold cross-validation is 73.14%. The trained ensemble model has been tested on the benchmark dataset and compared with existing sequential B-cell epitope prediction techniques including APCpred, ABCpred, BCpred and [inline-formula removed].

EPCES and EPSVR: Prediction of B-Cell Antigenic Epitopes on Protein Surfaces with Conformational Information.

Accurate prediction of discontinuous antigenic epitopes is important for immunologic research and medical applications, but it is not an easy problem. Currently, there are only a few prediction servers available, though discontinuous epitopes constitute the majority of all B-cell antigenic epitopes. In this chapter, we describe two online servers, EPCES and EPSVR, for discontinuous epitope prediction. All methods were benchmarked by a curated independent test set, in which all antigens had no complex structures with the antibody, and their epitopes were identified by various biochemical experiments. The servers and all datasets are available at http://sysbio.unl.edu/EPCES/ and http://sysbio.unl.edu/EPSVR/ .

Prediction of antigenic epitopes for coat protein of Potato virus Y, Egypt

Isolated Potato virus Y Egypt (PVY- EG) obtained from naturally infected potato plants in El-Sharkia, Egypt, was identified by biological, molecular and serological assays. The aims of this study were to predict the antigenic determinants (epitopes) of the isolated PVY using immunoinformatics; to prepare antibodies then apply them for PVY screening in potato plants in the field, as well as comparison with antibodies against coat protein. The amino acid sequence of PVY isolate was expected by DNAStar protean system; in which four parameters for epitope prediction including antigenicity, surface probability, hydrophobicity and secondary structure were used. These models were applied to PVY as a case study to predict immunogenic peptides for antibodies production. The most hydrophilic regions of PVY-coat protein (PVY- CP) were; 36-40, 46-47, 67-74, 96-98, 130-133, 164-166 and 198-200, which showed high hydrophobicity of this protein. This indicated that this protein was one of the best candidates to be immunogenic, and capable of producing antibodies that cross react with PVY. The peptide was chemically synthesized and injected into a rabbit. Obtained antibodies were evaluated using Double antibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA), and Immune Dot-Blot assay. These antibodies positively reacted against PVY infected potato tissues.

Parechovirus A Detection by a Comprehensive Approach in a Clinical Laboratory.

Parechovirus A (Human parechovirus, HPeV) causes symptoms ranging from severe neonatal infection to mild gastrointestinal and respiratory disease. Use of molecular approaches with RT-PCR and genotyping has improved the detection rate of HPeV. Conventional methods, such as viral culture and immunofluorescence assay, together with molecular methods facilitate comprehensive viral diagnosis. To establish the HPeV immunofluorescence assay, an antibody against HPeV capsid protein VP0 was generated by using antigenic epitope prediction data. The specificity of the anti-HPeV VP0 antibody was demonstrated on immunofluorescence assay, showing that this antibody was specific for HPeV but not enteroviruses. A total of 74 HPeV isolates, 7 non–polio-enteroviruses and 12 HPeV negative cell culture supernatant were used for evaluating the efficiency of the anti-HPeV VP0 antibody. The sensitivity of HPeV detection by the anti-HPeV VP0 antibody was consistent with 5′untranslated region (UTR) RT-PCR analysis. This study established comprehensive methods for HPeV detection that include viral culture and observation of cytopathic effect, immunofluorescence assay, RT-PCR and genotyping. The methods were incorporated into our routine clinical practice for viral diagnosis. In conclusion, this study established a protocol for enterovirus and HPeV virus identification that combines conventional and molecular methods and would be beneficial for HPeV diagnosis.

Detection ofepitopes in systemic lupus erythematosus using peptide microarray.

Systemic lupus erythematosus (SLE) is a common autoimmune disease, which features the secretion of antibodies directed against autoantigens in vivo. In the present study, a peptide microarray was developed to detect the epitopes recognized by autoantibodies in patients with SLE for an effective method of diagnosis. SLE-associated epitopes in 14 autoantigens were predicted using the antigenic epitope prediction software DNA star. Peptides were synthesized based on the predicted antigenic epitopes and immobilized on a slide surface and developed into a peptide microarray. Using this peptide microarray the autoantibodies in 120 patients with SLE and 110 healthy subjects were detected. A total of 73 potential antigenic epitopes in 14 autoantigens were predicted and screened. The peptide microarray based on the 73 epitopes was used to detect the autoantibodies in patients with SLE. A total of 14 epitopes with potential diagnostic values were screened out. The sensitivity and specificity of the 14 epitopes for the diagnosis of SLE were 71.6 and 85.8%, respectively. An optimal set of epitopes for SLE diagnosis was obtained. As individual patients had a specific autoantibody spectrum it was possible to detect autoantibodies in SLE and perform the diagnosis of SLE using the peptide microarray.

Computational prediction and analysis of potential antigenic CTL epitopes in Zika virus: A first step towards vaccine development

The Zika virus disease is an Aedes mosquito-borne disease caused by the ZIKA virus. The unavailability of vaccines or proper chemotherapeutic treatment emphasizes the need for the development of preventive and therapeutic vaccines. T cell specific epitopes have been used as vaccine candidates to generate desired immune responses against a variety of viral pathogens. Herein, the immune-informatics approach was used for the screening of potential major histocompatibility complex class I restricted epitopes, which may be competent to generate a cell-mediated immune response in humans. A total of 63 epitopes were identified, which revealed a comprehensive binding affinity to the 42 different human leukocyte antigen class I supertypes: A01, A02, A08, A23, A24, A25, A26, A29, A30, A32, A66, A68, A69, A80, B07, B08, B14, B15, B27, B35, B39, B40, B42, B45, B46, B48, B51, B53, B54, B57, B58, B83, C12, C03, C04, C05, C06, C07, C08, C12, C14, and C15, and which had no homologs in humans. By combining the human leukocyte antigen binding specificity and population coverage, nine promiscuous epitopes located in Capsid 1 Protein (MVLAILAFL(P1)), Envelop Protein (RLKGVSYSL (P2) and RLITANPVI (P3)), NS2A (AILAALTPL (P4)), NS4B (LLVAHYMYL (P5) and LVAHYMYLI (P6)) and NS5 (SLINGVVRL (P7), ALNTFTNLV (P8) and YLSTQVRYL (P9)) were shortlisted. Most of these consensus epitopes revealed 100% conservancy in all Zika virus strains and were very less conserved against the human proteome. The combination of the selected epitopes accounted for an optimal coverage in the world wide population (>99%) independent of ethnicity. Structural analysis of these selected epitopes by the PatchDock web server showed their preferential mode of presentation to the T cell receptor. All these results recommended the possibility of a combined epitope vaccine strategy and can therefore be further investigated for their immunological relevance and usefulness as vaccine candidates.

Computational antigenic epitope prediction by calculating electrostatic desolvation penalties of protein surfaces.

The prediction of antigenic epitopes on the surface of proteins is of great importance for vaccine development and to specifically design recombinant antibodies. Computational methods based on the three-dimensional structure of the protein allow for the detection of noncontinuous epitopes in contrast to methods based on the primary amino-acid sequence only. A method recently developed to predict protein-protein binding sites is presented, and the application to predict putative antigenic epitopes is described in detail. The prediction approach is based on the local perturbation of the electrostatic field at the surface of a protein due to a neutral probe of low dielectric constant that represents an approaching binding partner. The calculated change in electrostatic energy corresponds to an energy penalty of desolvating a protein surface region, and antigenic epitope surface regions tend to be associated with a lower penalty compared to the average protein surface. The protocol to perform the calculations is described and illustrated on an example antigen, the outer surface protein A of Borrelia burgdorferi, a pathogenic organism causing lyme disease.