BepiPred-2.0: improving sequence-based B-cell epitope prediction using conformational epitopes

Role of pentamer complex-specific and IgG subclass 3 antibodies in HCMV hyperimmunoglobulin and standard intravenous IgG preparations

BACKGROUND

HCMV hyperimmunoglobulin-preparations (HIG) contain high concentrations of HCMV-specific IgG. The reduced maternofetal-HCMV-transmission rate of IgG may be due to HCMV-specific neutralizing antibodies against the HCMV pentameric complex (PC). In contrast to HIG, standard intravenous immunoglobulin (IVIG) may have more neutralization (NT) capacity than HIG due to higher IgG subclass 3 levels (Planitzer et al., 2011).

METHODS

We investigated the HCMV-specific NT-capacity of HIG Cytotect^®, using a recombinant pentameric complex (gHgLUL128-131A) for specific antibody-depletion. We used a modified UL130-peptide (TANQNPSPPWSKLTYSKPH) based on original-sequence of Saccoccio et al. (Vaccine 29(15):2705-2711, 2011) (SWSTLTANQNPSPPWSKLTY) as neutralization target. Both UL130-peptides and the PC were bound via sixfold HisTag and anti-HisTag mAbs to magnetic beads to deplete HCMV-specific IgGs from HIG (Cytotect^®). Modifying this depletion strategy, we analyzed the role of IgG subclass 3 in both HIG and IVIG.

RESULTS

After CMV IgG-normalization of HIG and IVIG, we found a significant trend towards a decrease (16%) of neutralization-capacity for the UL130 TAN-peptide, but not for the original UL130 SWS-peptide. However, highly significant loss of NT-capacity could be only observed by PC depletion (42%). The IgG subclass 3 depletion revealed no significant reduction of NT-capacity in both HIG and IVIG.

CONCLUSION

Via specific antibody depletion, we could demonstrate that pentameric complex-specific antibodies are present in HIG and bind to the recombinant PC resulting in a highly significant reduction of NT-capacity compared to the UL130 TAN-and SWS-peptides. We could not confirm the functional role of IgG subclass 3 neutralizing antibodies in IgG-preparations.

iBCE-EL: A New Ensemble Learning Framework for Improved Linear B-Cell Epitope Prediction

Identification of B-cell epitopes (BCEs) is a fundamental step for epitope-based vaccine development, antibody production, and disease prevention and diagnosis. Due to the avalanche of protein sequence data discovered in postgenomic age, it is essential to develop an automated computational method to enable fast and accurate identification of novel BCEs within vast number of candidate proteins and peptides. Although several computational methods have been developed, their accuracy is unreliable. Thus, developing a reliable model with significant prediction improvements is highly desirable. In this study, we first constructed a non-redundant data set of 5,550 experimentally validated BCEs and 6,893 non-BCEs from the Immune Epitope Database. We then developed a novel ensemble learning framework for improved linear BCE predictor called iBCE-EL, a fusion of two independent predictors, namely, extremely randomized tree (ERT) and gradient boosting (GB) classifiers, which, respectively, uses a combination of physicochemical properties (PCP) and amino acid composition and a combination of dipeptide and PCP as input features. Cross-validation analysis on a benchmarking data set showed that iBCE-EL performed better than individual classifiers (ERT and GB), with a Matthews correlation coefficient (MCC) of 0.454. Furthermore, we evaluated the performance of iBCE-EL on the independent data set. Results show that iBCE-EL significantly outperformed the state-of-the-art method with an MCC of 0.463. To the best of our knowledge, iBCE-EL is the first ensemble method for linear BCEs prediction. iBCE-EL was implemented in a web-based platform, which is available at http://thegleelab.org/iBCE-EL. iBCE-EL contains two prediction modes. The first one identifying peptide sequences as BCEs or non-BCEs, while later one is aimed at providing users with the option of mining potential BCEs from protein sequences.

BPSL1626: Reverse and Structural Vaccinology Reveal a Novel Candidate for Vaccine Design against Burkholderia pseudomallei

Due to significant advances in computational biology, protein prediction, together with antigen and epitope design, have rapidly moved from conventional methods, based on experimental approaches, to in silico-based bioinformatics methods. In this context, we report a reverse vaccinology study that identified a panel of 104 candidate antigens from the Gram-negative bacterial pathogen Burkholderia pseudomallei, which is responsible for the disease melioidosis. B. pseudomallei can cause fatal sepsis in endemic populations in the tropical regions of the world and treatment with antibiotics is mostly ineffective. With the aim of identifying potential vaccine candidates, we report the experimental validation of predicted antigen and type I fimbrial subunit, BPSL1626, which we show is able to recognize and bind human antibodies from the sera of Burkholderia infected patients and to stimulate T-lymphocytes in vitro. The prerequisite for a melioidosis vaccine, in fact, is that both antibody- and cell-mediated immune responses must be triggered. In order to reveal potential antigenic regions of the protein that may aid immunogen re-design, we also report the crystal structure of BPSL1626 at 1.9 Å resolution on which structure-based epitope predictions were based. Overall, our data suggest that BPSL1626 and three epitope regions here-identified can represent viable candidates as potential antigenic molecules.

Potent O-antigen-deficient (rough) mutants of Salmonella Typhimurium secreting Lawsonia intracellularis antigens enhance immunogenicity and provide single-immunization protection against proliferative enteropathy and salmonellosis in a murine model

The obligate intracellular pathogen Lawsonia intracellularis (LI), the etiological agent of proliferative enteropathy (PE), poses a substantial economic loss in the swine industry worldwide. In this study, we genetically engineered an O-antigen-deficient (rough) Salmonella strain secreting four selected immunogenic LI antigens, namely OptA, OptB, LfliC, and Lhly. The genes encoding these antigens were individually inserted in the expression vector plasmid pJHL65, and the resultant plasmids were transformed into the ∆asd ∆lon ∆cpxR ∆rfaL Salmonella Typhimurium (ST) strain JOL1800. The individual expression of the selected LI antigens in JOL1800 was validated by an immunoblotting assay. We observed significant (P < 0.05) induction of systemic IgG and mucosal IgA responses against each LI antigen or Salmonella outer membrane protein in mice immunized once orally with a mixture of four JOL1800-derived strains. Further, mRNA of IL-4 and IFN-γ were highly upregulated in splenic T cells re-stimulated in vitro with individual purified antigens. Subsequently, immunized mice showed significant protection against challenge with 10^6.9 TCID₅₀ LI or 2 × 10⁹ CFU of a virulent ST strain. At day 8 post-challenge, no mice in the immunized groups showed the presence of LI-specific genomic DNA (gDNA) in stool samples, while 50% of non-immunized mice were positive for LI-specific gDNA. Further, all the immunized mice survived the virulent ST challenge, compared to a 20% mortality rate observed in the control mice. Collectively, the constructed rough ST-based LI vaccine candidate efficiently elicited LI and ST-specific humoral and cell-mediated immunity and conferred proper dual protection against PE and salmonellosis.

Characterization of Plasmodium vivax Proteins in Plasma-Derived Exosomes From Malaria-Infected Liver-Chimeric Humanized Mice

Exosomes are extracellular vesicles of endocytic origin containing molecular signatures implying the cell of origin; thus, they offer a unique opportunity to discover biomarkers of disease. Plasmodium vivax, responsible for more than half of all malaria cases outside Africa, is a major obstacle in the goal of malaria elimination due to the presence of dormant liver stages (hypnozoites), which after the initial infection may reactivate to cause disease. Hypnozoite infection is asymptomatic and there are currently no diagnostic tools to detect their presence. The human liver-chimeric (FRG huHep) mouse is a robust P. vivax infection model for exo-erythrocytic development of liver stages, including hypnozoites. We studied the proteome of plasma-derived exosomes isolated from P. vivax infected FRG huHep mice with the objective of identifying liver-stage expressed parasite proteins indicative of infection. Proteomic analysis of these exosomes showed the presence of 290 and 234 proteins from mouse and human origin, respectively, including canonical exosomal markers. Human proteins include proteins previously detected in liver-derived exosomes, highlighting the potential of this chimeric mouse model to study plasma exosomes derived unequivocally from human hepatocytes. Noticeably, we identified 17 parasite proteins including enzymes, surface proteins, components of the endocytic pathway and translation machinery, as well as uncharacterized proteins. Western blot analysis validated the presence of human arginase-I and an uncharacterized P. vivax protein in plasma-derived exosomes. This study represents a proof-of-principle that plasma-derived exosomes from P. vivax infected FRG-huHep mice contain human hepatocyte and P. vivax proteins with the potential to unveil biological features of liver infection and identify biomarkers of hypnozoite infection.

Genotype replacement of the human parainfluenza virus type 2 in Croatia between 2011 and 2017 - the role of neutralising antibodies

Previously we reported on the HPIV2 genotype distribution in Croatia 2011-2014. Here we expand this period up to 2017 and confirm that G1a genotype has replaced G3 genotype from the period 2011-2014. Our hypothesis was that the G1a-to-G3 genotype replacement is an antibody-driven event. A cross-neutralisation with anti-HPIV2 sera specific for either G1a or G3 genotype revealed the presence of genotype-specific antigenic determinants. By the profound, in silico analyses three potential B cell epitopic regions were identified in the hemagglutinin neuraminidase (regions 314-361 and 474-490) and fusion protein (region 440-484). The region identified in the fusion protein does not show any unique site between the G1a and G3 isolates, five differentially glycosylated sites in the G1a and G3 genotype isolates were identified in epitopic regions of hemagglutinin neuraminidase. All positively selected codons were found to be located either in the region 314-316 or in the region 474-490 what indicates a strong positive selection in this region and reveals that these regions are susceptible to evolutionary pressure possibly caused by antibodies what gives a strong verification to our hypothesis that neutralising antibodies are a key determinant in the inherently complex adaptive evolution of HPIV2 in the region.

Postgenomic Approaches and Bioinformatics Tools to Advance the Development of Vaccines against Bacteria of the Burkholderia cepacia Complex

Bacteria of the Burkholderia cepacia complex (Bcc) remain an important cause of morbidity and mortality among patients suffering from cystic fibrosis. Eradication of these pathogens by antimicrobial therapy often fails, highlighting the need to develop novel strategies to eradicate infections. Vaccines are attractive since they can confer protection to particularly vulnerable patients, as is the case of cystic fibrosis patients. Several studies have identified specific virulence factors and proteins as potential subunit vaccine candidates. So far, no vaccine is available to protect from Bcc infections. In the present work, we review the most promising postgenomic approaches and selected web tools available to speed up the identification of immunogenic proteins with the potential of conferring protection against Bcc infections.

Development of a novel peptide aptamer-based immunoassay to detect Zika virus in serum and urine

Zika virus (ZIKV) has been identified as a cause of adverse outcomes of pregnancy, including microcephaly and other congenital diseases. Most people infected with ZIKV do not show any symptoms. Development of a method to discriminate dengue virus (DENV) and ZIKV infections has been challenging, and efficient assays for patient management are limited, attributable to high levels of cross-reactivity among co-circulating Flaviviruses. Thus, there is an urgent need for a specific high-throughput diagnostic assay to discriminate ZIKV infections from other Flavivirus infections. Methods: A novel epitope peptide of the ZIKV envelope protein was predicted using three immune epitope database analysis tools and then further modified. A molecular docking study was conducted using three-dimensional structures of the ZIKV envelope and peptide. Experimentally, interactions between the selected peptides and virus were assessed via a fluorescence-linked sandwich immunosorbent assay (FLISA), and performance of peptide-linked sandwich FLISA was evaluated in virus-spiked human serum and urine. Results: The Z_10.8 peptide (KRAVVSCAEA) was predicted to be a suitable detector, with a higher binding affinity than other candidates based on four criteria (binding affinity, root mean square deviation, position of amine residue of lysine at the N-terminus, and interactive site) in a docking study. Z_10.8 was significantly more efficient at detecting ZIKV than the other two peptides, as shown in the direct FLISA (P < 0.001). Further, the equilibrium dissociation constant (K_d) for the Z_10.8 peptide was 706.0 ± 177.9 (mean ± SD, nM), with specificity to discriminate ZIKV from DENV. The limit of detection for the sandwich FLISA was calculated as 1×10⁴ tissue culture infective dose (TCID)₅₀/mL. The presence of serum or urine did not interfere with the performance of the Z_10.8-linked sandwich FLISA. Conclusion: Four criteria are suggested for the development of an in silico modeled peptide aptamer; this computerized peptide aptamer discriminated ZIKV from DENV via immunoassay.

Design of peptide epitope from the neuraminidase protein of influenza A and influenza B towards short peptide vaccine development

Influenza viruses A and B are important human respiratory pathogens causing seasonal, endemic and pandemic infections in several parts of the globe with high morbidity and considerable mortality. The current inactivated and live attenuated vaccines are not effective. Therefore, it is of interest to design universal influenza virus vaccines with high efficacy. The peptide GQSVVSVKLAGNSSL of pandemic influenza, the peptide DKTSVTLAGNSSLCS of seasonal influenza and the peptide DILLKFSPTEITAPT of influenza B were identified as potential linear cell mediated epitopes. The epitopes predicted by BepiPred (B-cell epitope designer) program was subjected to docking experiment-using HexDock and CABS dock programs. The epitopes of pandemic H1N1 influenza A gave similar score of high affinity in docking. The epitope DKTSVTLAGNSSLCS of seasonal influenza A and epitope DILLKFSPTEITAPT of influenza B had high binding energy. It is further observed that the peptides GQSVVSVKLAGNSSL (pandemic influenza), DKTSVTLAGNSSLCS (seasonal influenza) DILLKFSPTEITAPT (influenza B) are found to interact with some known MHC class II alleles. These peptides have high-affinity binding with known MHC class II alleles. Thus, they have the potential to elicit cell immune response. These vaccines have to be further evaluated in animal models and human volunteers. These findings have application in the development of peptide B-cell epitope vaccines against influenza viruses.

Comparative systems analysis of the secretome of the opportunistic pathogen Aspergillus fumigatus and other Aspergillus species

Aspergillus fumigatus and multiple other Aspergillus species cause a wide range of lung infections, collectively termed aspergillosis. Aspergilli are ubiquitous in environment with healthy immune systems routinely eliminating inhaled conidia, however, Aspergilli can become an opportunistic pathogen in immune-compromised patients. The aspergillosis mortality rate and emergence of drug-resistance reveals an urgent need to identify novel targets. Secreted and cell membrane proteins play a critical role in fungal-host interactions and pathogenesis. Using a computational pipeline integrating data from high-throughput experiments and bioinformatic predictions, we have identified secreted and cell membrane proteins in ten Aspergillus species known to cause aspergillosis. Small secreted and effector-like proteins similar to agents of fungal-plant pathogenesis were also identified within each secretome. A comparison with humans revealed that at least 70% of Aspergillus secretomes have no sequence similarity with the human proteome. An analysis of antigenic qualities of Aspergillus proteins revealed that the secretome is significantly more antigenic than cell membrane proteins or the complete proteome. Finally, overlaying an expression dataset, four A. fumigatus proteins upregulated during infection and with available structures, were found to be structurally similar to known drug target proteins in other organisms, and were able to dock in silico with the respective drug.

Current progress of immunoinformatics approach harnessed for cellular- and antibody-dependent vaccine design

Immunoinformatics plays a pivotal role in vaccine design, immunodiagnostic development, and antibody production. In the past, antibody design and vaccine development depended exclusively on immunological experiments which are relatively expensive and time-consuming. However, recent advances in the field of immunological bioinformatics have provided feasible tools which can be used to lessen the time and cost required for vaccine and antibody development. This approach allows the selection of immunogenic regions from the pathogen genomes. The ideal regions could be developed as potential vaccine candidates to trigger protective immune responses in the hosts. At present, epitope-based vaccines are attractive concepts which have been successfully trailed to develop vaccines which target rapidly mutating pathogens. In this article, we provide an overview of the current progress of immunoinformatics and their applications in the vaccine design, immune system modeling and therapeutics.

Proteome-wide mapping of immune features onto Plasmodium protein three-dimensional structures

Humoral immune responses against the malaria parasite are an important component of a protective immune response. Antibodies are often directed towards conformational epitopes, and the native structure of the antigenic region is usually critical for antibody recognition. We examined the structural features of various Plasmodium antigens that may impact on epitope location, by performing a comprehensive analysis of known and modelled structures from P. falciparum. Examining the location of known polymorphisms over all available structures, we observed a strong propensity for polymorphic residues to be exposed on the surface and to occur in particular secondary structure segments such as hydrogen-bonded turns. We also utilised established prediction algorithms for B-cell epitopes and MHC class II binding peptides, examining predicted epitopes in relation to known polymorphic sites within structured regions. Finally, we used the available structures to examine polymorphic hotspots and Tajima's D values using a spatial averaging approach. We identified a region of PfAMA1 involving both domains II and III under a high degree of balancing selection relative to the rest of the protein. In summary, we developed general methods for examining how sequence-based features relate to one another in three-dimensional space and applied these methods to key P. falciparum antigens.

In Silico Tools and Databases for Designing Peptide-Based Vaccine and Drugs

The prolonged conventional approaches of drug screening and vaccine designing prerequisite patience, vigorous effort, outrageous cost as well as additional manpower. Screening and experimentally validating thousands of molecules for a specific therapeutic property never proved to be an easy task. Similarly, traditional way of vaccination includes administration of either whole or attenuated pathogen, which raises toxicity and safety issues. Emergence of sequencing and recombinant DNA technology led to the epitope-based advanced vaccination concept, i.e., small peptides (epitope) can stimulate specific immune response. Advent of bioinformatics proved to be an adjunct in vaccine and drug designing. Genomic study of pathogens aid to identify and analyze the protective epitope. A number of in silico tools have been developed to design immunotherapy as well as peptide-based drugs in the last two decades. These tools proved to be a catalyst in drug and vaccine designing. This review solicits therapeutic peptide databases as well as in silico tools developed for designing peptide-based vaccine and drugs.

Antigenic and functional profiles of a Lawsonia intracellularis protein that shows a flagellin-like trait and its immuno-stimulatory assessment

The obligate intracellular Lawsonia intracellularis (LI), the etiological agent of proliferative enteropathy (PE), is an economically important disease in the swine industry. Due to extreme difficulty of in vitro culture of the pathogen, molecular characterization of protein components of LI that are targets of the immune system, is difficult; thus, the scientific evidence to drive the development of preventive measures is lacking. In this work, we investigated the antigenic and functional characteristics of a putative flagellar-associated protein, LI0570, using in silico computational approaches for epitope prediction and an in vitro protein-based molecular assay. The amino acid sequence of LI0570 exhibited similarities to flagellar-associated proteins in four different bacterial strains. The presence of B cell linear confirmative epitopes of the protein predicted by a bioinformatics tool was validated by western blot analysis using anti-LI mouse hyperimmune serum, which implied that LI0570 induced production of antigen-specific antibodies in vivo. Further, TLR5-stimulating activity and IL-8 cytokine expression produced via downstream signaling were observed in HEK-Blue™-hTLR5 cells stimulated with LI0570. This result indicates that the LI0570 protein can trigger an innate immune response followed by a T-cell-related adaptive immune response in an infected host. Collectively, the data presented here support that the LI0570 protein which shows the antigenic potential could be a useful component of a recombinant vaccine against PE, providing progress toward an effective prevention strategy.

Exploring the potential of 3D Zernike descriptors and SVM for protein-protein interface prediction

Background

The correct determination of protein–protein interaction interfaces is important for understanding disease mechanisms and for rational drug design. To date, several computational methods for the prediction of protein interfaces have been developed, but the interface prediction problem is still not fully understood. Experimental evidence suggests that the location of binding sites is imprinted in the protein structure, but there are major differences among the interfaces of the various protein types: the characterising properties can vary a lot depending on the interaction type and function. The selection of an optimal set of features characterising the protein interface and the development of an effective method to represent and capture the complex protein recognition patterns are of paramount importance for this task.

Results

In this work we investigate the potential of a novel local surface descriptor based on 3D Zernike moments for the interface prediction task. Descriptors invariant to roto-translations are extracted from circular patches of the protein surface enriched with physico-chemical properties from the HQI8 amino acid index set, and are used as samples for a binary classification problem. Support Vector Machines are used as a classifier to distinguish interface local surface patches from non-interface ones. The proposed method was validated on 16 classes of proteins extracted from the Protein–Protein Docking Benchmark 5.0 and compared to other state-of-the-art protein interface predictors (SPPIDER, PrISE and NPS-HomPPI).

Conclusions

The 3D Zernike descriptors are able to capture the similarity among patterns of physico-chemical and biochemical properties mapped on the protein surface arising from the various spatial arrangements of the underlying residues, and their usage can be easily extended to other sets of amino acid properties. The results suggest that the choice of a proper set of features characterising the protein interface is crucial for the interface prediction task, and that optimality strongly depends on the class of proteins whose interface we want to characterise. We postulate that different protein classes should be treated separately and that it is necessary to identify an optimal set of features for each protein class.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2043-3) contains supplementary material, which is available to authorized users.

The generation of a simian adenoviral vectored HCV vaccine encoding genetically conserved gene segments to target multiple HCV genotypes

BACKGROUND

Hepatitis C virus (HCV) genomic variability is a major challenge to the generation of a prophylactic vaccine. We have previously shown that HCV specific T-cell responses induced by a potent T-cell vaccine encoding a single strain subtype-1b immunogen target epitopes dominant in natural infection. However, corresponding viral regions are highly variable at a population level, with a reduction in T-cell reactivity to these variants. We therefore designed and manufactured second generation simian adenovirus vaccines encoding genomic segments, conserved between viral genotypes and assessed these for immunogenicity.

METHODS

We developed a computer algorithm to identify HCV genomic regions that were conserved between viral subtypes. Conserved segments below a pre-defined diversity threshold spanning the entire HCV genome were combined to create novel immunogens (1000-1500 amino-acids), covering variation in HCV subtypes 1a and 1b, genotypes 1 and 3, and genotypes 1-6 inclusive. Simian adenoviral vaccine vectors (ChAdOx) encoding HCV conserved immunogens were constructed. Immunogenicity was evaluated in C57BL6 mice using panels of genotype-specific peptide pools in ex-vivo IFN-ϒ ELISpot and intracellular cytokine assays.

RESULTS

ChAdOx1 conserved segment HCV vaccines primed high-magnitude, broad, cross-reactive T-cell responses; the mean magnitude of total HCV specific T-cell responses was 1174 SFU/10⁶ splenocytes for ChAdOx1-GT1-6 in C57BL6 mice targeting multiple genomic regions, with mean responses of 935, 1474 and 1112 SFU/10⁶ against genotype 1a, 1b and 3a peptide panels, respectively. Functional assays demonstrated IFNg and TNFa production by vaccine-induced CD4 and CD8 T-cells. In silico analysis shows that conserved immunogens contain multiple epitopes, with many described in natural HCV infection, predicting immunogenicity in humans.

CONCLUSIONS

Simian adenoviral vectored vaccines encoding genetic segments that are conserved between all major HCV genotypes contain multiple T-cell epitopes and are highly immunogenic in pre-clinical models. These studies pave the way for the assessment of multi-genotypic HCV T-cell vaccines in humans.

Antigenic characterization of classical swine fever virus YC11WB isolates from wild boar

Classical swine fever (CSF), a highly contagious disease that affects domestic pigs and wild boar, has serious economic implications. The present study examined the virulence and transmission of CSF virus strain YC11WB (isolated from a wild boar in 2011) in breeding wild boar. Virulence of strain YC11WB in domestic pigs was also examined. Based on the severe clinical signs and high mortality observed among breeding wild boar, the pathogenicity of strain YC11WB resembled that of typical acute CSF. Surprisingly, in contrast to strain SW03 (isolated from breeding pigs in 2003), strain YC11WB showed both acute and strong virulence in breeding pigs. None of three specific monoclonal antibodies (7F2, 7F83, and 6F65) raised against the B/C domain of the SW03 E2 protein bound to the B/C domain of strain YC11WB due to amino acid mutations (⁷²⁰K→R and ⁷²³N→S) in the YC11WB E2 protein. Although strains YC11WB and SW03 belong to subgroup 2.1b, they had different mortality rates in breeding pigs. Thus, if breeding pigs have not developed protective immunity against CSF virus, they may be susceptible to strain YC11WB transmitted by wild boar, resulting in severe economic losses for the pig industry.

Fundamentals and Methods for T- and B-Cell Epitope Prediction

Adaptive immunity is mediated by T- and B-cells, which are immune cells capable of developing pathogen-specific memory that confers immunological protection. Memory and effector functions of B- and T-cells are predicated on the recognition through specialized receptors of specific targets (antigens) in pathogens. More specifically, B- and T-cells recognize portions within their cognate antigens known as epitopes. There is great interest in identifying epitopes in antigens for a number of practical reasons, including understanding disease etiology, immune monitoring, developing diagnosis assays, and designing epitope-based vaccines. Epitope identification is costly and time-consuming as it requires experimental screening of large arrays of potential epitope candidates. Fortunately, researchers have developed in silico prediction methods that dramatically reduce the burden associated with epitope mapping by decreasing the list of potential epitope candidates for experimental testing. Here, we analyze aspects of antigen recognition by T- and B-cells that are relevant for epitope prediction. Subsequently, we provide a systematic and inclusive review of the most relevant B- and T-cell epitope prediction methods and tools, paying particular attention to their foundations.

Identification and characterization of pro-interleukin-16 from mud crab Scylla paramamosain: The first evidence of proinflammatory cytokine in crab species

IL-16 is a pro-inflammatory cytokine originally designated as a lymphocyte chemoattractant factor. In mammal and avian, it has been characterized as an essential regulator of various cellular processes including cell recruitment and activation against pathogen invasion. So far, neither of the full-length of IL-16 homologue nor the response mechanism against pathogen was reported in crab species. In the present study, the pro-IL-16 homologue was firstly cloned and characterized from mud crab Scylla paramamosain. The full-length Sp-pro-IL-16 consisted of 4107 bp with an opening reading frame encoding 1369 amino acids. Multiple alignment analysis showed the putative amino acid sequence of Sp-pro-IL-16 had about 73.86% identity with Litopenaeus vannamei pro-IL-16. Additionally, two conserved PDZ domains and protein binding sites were found in Sp-pro-IL-16 and showed high similarities about 94.19% and 51.14% with their Litopenaeus vannamei and Mus musculus counterparts. RT-PCR analysis indicated that Sp-pro-IL-16 transcripts were constitutively expressed in all tissues examined with an extreme high level in hepatopancreas. Moreover, Sp-pro-IL-16 transcripts in hepatopancreas were significantly up-regulated 15-fold at 72 h after Vibrio alginolyticus challenge and 3.5-fold at 12 h after virus-analog Poly (I:C) challenge. The Western blot analysis revealed that Sp-pro-IL-16 can be cleaved to its bioactive form, an approximately 35 kDa mature IL-16, and the protein levels of both pro-IL-16 and mature IL-16 increased after Vibrio alginolyticus challenge. It is the first experimental identification of pro-inflammatory cytokine IL-16 in arthropods. This study could shed new light on further understanding of the response mechanism of pro-inflammatory cytokine IL-16 in Scylla paramamosain against pathogens. Meanwhile, it brought new insight into the origin and evolution of IL-16 in crab species.