Overexpression,Purification and Validation of Antigenic Salmonella enterica Serovar Typhi Proteins Identified from LC-MS/MS

In our earlier study, an immunoblot analysis using sera from febrile patients revealed that a 50-kDa band from an outer membrane protein fraction of Salmonella enterica serovar Typhi was specifically recognized only by typhoid sera and not sera from other febrile illnesses. Here, we investigated the identities of the proteins contained in the immunogenic 50-kDa band to pinpoint antigens responsible for its immunogenicity. We first used LC-MS/MS for protein identification, then used the online tool ANTIGENpro for antigenicity prediction and produced recombinant proteins of the lead antigens for validation in an enzyme-linked immunosorbent assay (ELISA). We found that proteins TolC, GlpK and SucB were specific to typhoid sera but react to antibodies differently under native and denatured conditions. This difference suggests the presence of linear and conformational epitopes on these proteins.     

In silico identification of outer membrane protein (Omp) and subunit vaccine design against pathogenic Vibrio cholerae

Virulence-related outer membrane proteins (Omps) are expressed in bacteria (Gram-negative) such as V. cholerae and are vital to bacterial invasion in to eukaryotic cell and survival within macrophages that could be best candidate for development of vaccine against V. cholerae. Applying in silico approaches, the 3-D model of the Omp was developed using Swiss model server and validated byProSA and Procheck web server. The continuous stretch of amino acid sequences 26 mer: RTRSNSGLLTWGDKQTITLEYGDPAL and 31 mer: FFAGGDNNLRGYGYKSISPQDASGALTGAKY having B-cell binding sites were selected from sequence alignment after B cell epitopes prediction by BCPred and AAP prediction modules of BCPreds. Further, the selected antigenic sequences (having B-cell epitopes) were analyzed for T-cell epitopes (MHC I and MHC II alleles binding sequence) by using ProPred 1 and ProPred respectively. The epitope (9 mer: YKSISPQDA) that binds to both the MHC classes (MHC I and MHC II) and covers maximum MHC alleles were identified. The identified epitopes can be useful in designing comprehensive peptide vaccine development against V. cholerae by inducing optimal immune response.     

Immunogenicity of Foot-and-Mouth Disease Virus Dendrimer Peptides: Need for a T-Cell Epitope and Ability to Elicit Heterotypic Responses

An approach based on a dendrimer display of B- and T-cell epitopes relevant for antibody induction has been shown to be effective as a foot-and-mouth disease (FMD) vaccine. B₂T dendrimers combining two copies of the major FMD virus (FMDV) type O B-cell epitope (capsid proteinVP1 (140–158)) covalently linked to a heterotypic T-cell epitope from non-structural protein 3A (21–35), henceforth B₂T-3A, has previously been shown to elicit high neutralizing antibody (nAb) titers and IFN-γ-producing cells in both mice and pigs. Here, we provide evidence that the B- and T-cell epitopes need to be tethered to a single molecular platform for successful T-cell help, leading to efficient nAb induction in mice. In addition, mice immunized with a non-covalent mixture of B₂T-3A dendrimers containing the B-cell epitopes of FMDV types O and C induced similarly high nAb levels against both serotypes, opening the way for a multivalent vaccine platform against a variety of serologically different FMDVs. These findings are relevant for the design of vaccine strategies based on B- and T-cell epitope combinations.     

Do Toxoplasma gondii apicoplast proteins have antigenic potential? An in silico study

Toxoplasma gondii, one of the extensively studied Apicomplexan parasites, is prevalent worldwide in animals and humans. Apart from its nuclear genome, T. gondii contains an apicoplast genome in 35 kb length which is originated from a secondary endosymbiotic event. In this study, we aimed to investigate the antigenic potential of apicoplast genome encoded proteins (n:28) of T. gondii using in silico analysis. For this purpose, proteins were primarily predicted to reveal antigenic probability and then, several bioinformatics analyses were applied for all predicted antigenic apicoplast proteins to analyze physico-chemical parameters, subcellular localization and transmembrane domain. Also, further prediction analyses including structural, B cell and MHC-I/II epitope sites as well as post-translational modifications were performed for antigenic proteins that have a signal peptide or a high antigenicity value. Of the 28 apicoplast proteins, 19 were predicted as probable antigen. Among antigenic proteins, ribosomal protein S5, L11 and S2 were predicted to have signal peptide whereas ribosomal protein L36 and S17 were predicted to have a significantly high antigenicity value (P < 0.05). In addition, ribosomal protein S5, L11, S2, L36 and S17 were predicted to have a lot of epitopes which have low IC50 and percentile rank value indicating a strong binding among epitopes and MHC-I/II alleles, and post-translational modifications such as N-linked glycosylation, acetylation and phosphorylation. To the best of authors’ knowledge this is the first study to show the antigenic potential and other properties of apicoplast-derived proteins of T. gondii.     

Designing an efficient multi-epitope peptide vaccine against Vibrio cholerae via combined immunoinformatics and protein interaction based approaches

Cholera continues to be a major global health concern. Among different Vibrio cholerae strains, only O1 and O139 cause acute diarrheal diseases that are related to epidemic and pandemic outbreaks. The currently available cholera vaccines are mainly lived and attenuated vaccines consisting of V. cholerae virulence factors such as toxin-coregulated pili (TCP), outer membrane proteins (Omps), and nontoxic cholera toxin B subunit (CTB). Nowadays, there is a great interest in designing an efficient epitope vaccine against cholera. Epitope vaccines consisting of immunodominant epitopes and adjuvant molecules enhance the possibility of inciting potent protective immunity. In this study, V. cholerae protective antigens (OmpW, OmpU, TcpA and TcpF) and the CTB, which is broadly used as an immunostimulatory adjuvant, were analyzed using different bioinformatics and immunoinformatics tools. The common regions between promiscuous epitopes, binding to various HLA-II supertype alleles, and B-cell epitopes were defined based upon the aforementioned protective antigens. The ultimately selected epitopes and CTB adjuvant were fused together using proper GPGPG linkers to enhance vaccine immunogenicity. A three-dimensional model of the thus constructed vaccine was generated using I-TASSER. The model was structurally validated using the ProSA-web error-detection software and the Ramachandran plot. The validation results indicated that the initial 3D model needed refinement. Subsequently, a high-quality model obtained after various refinement cycles was used for defining conformational B-cell epitopes. Several linear and conformational B-cell epitopes were determined within the epitope vaccine, suggesting likely antibody triggering features of our designed vaccine. Next, molecular docking was performed between the 3D vaccine model and the tertiary structure of the toll like receptor 2 (TLR2). To gain further insight into the interaction between vaccine and TLR2, molecular dynamics simulation was performed, corroborating stable vaccine-TLR2 binding. In sum, the results suggest that our designed epitope vaccine could incite robust long-term protective immunity against V. cholera.     

Two highly similar LAEDDTNAQKT and LTDKIGTEI epitopes in G glycoprotein may be useful for effective epitope based vaccine design against pathogenic Henipavirus

Nipah virus and Hendra virus, two members of the genus Henipavirus, are newly emerging zoonotic pathogens which cause acute respiratory illness and severe encephalitis in human. Lack of the effective antiviral therapy endorses the urgency for the development of vaccine against these deadly viruses. In this study, we employed various computational approaches to identify epitopes which has the potential for vaccine development. By analyzing the immune parameters of the conserved sequences of G glycoprotein using various databases and bioinformatics tools, we identified two potential epitopes which may be used as peptide vaccines. Using different B cell epitope prediction servers, four highly similar B cell epitopes were identified. Immunoinformatics analyses revealed that LAEDDTNAQKT is a highly flexible and accessible B-cell epitope to antibody. Highly similar putative CTL epitopes were analyzed for their binding with the HLA-C 12*03 molecule. Docking simulation assay revealed that LTDKIGTEI has significantly lower binding energy, which bolstered its potential as epitope-based vaccine design. Finally, cytotoxicity analysis has also justified their potential as promising epitope-based vaccine candidate. In sum, our computational analysis indicates that either LAEDDTNAQKT or LTDKIGTEI epitope holds a promise for the development of universal vaccine against all kinds of pathogenic Henipavirus. Further in vivo and in vitro studies are necessary to validate the obtained findings.     

质谱技术在免疫分子的结构研究中的应用

质谱技术用于生物大分子的研究具有直接、简单、快速、经济等优点。近十年来 ,基质辅助激光解吸质谱 (MALDI MS)和电喷雾质谱 (ESI MS)在免疫学领域的研究中作出了重要贡献。本文着重对抗原、抗体、抗原 抗体复合物、抗原决定簇等免疫分子结构的质谱研究作一评述。大体分为四方面内容 :免疫分子的分子量、翻译后修饰、异质性、构象变化的分析 ;质谱指纹图的取得和串联质谱测序 ;抗原 抗体复合物的证明 ;B 细胞表位和T 细胞表位序列的测定。这些研究结果对于理解免疫分子的免疫功能、对于疾病的早期诊断、对于发展新药和疫苗具有重要意义     

In silico analyses of heat shock protein 60 and calreticulin to designing a novel vaccine shifting immune response toward T helper 2 in atherosclerosis

Recent experiments demonstrated that atherosclerosis is a Th1 dominant autoimmune condition, whereas Th2 cells are rarely detected within the atherosclerotic lesions. Several studies have indicated that Th2 type cytokines could be effective in the reduction and stabilization of atherosclerotic plaque. Therefore, the modulation of the adaptive immune response by shifting immune responses toward Th2 cells by a novel vaccine could represent a promising approach to prevent from progression and thromboembolic events in coronary artery disease. In the present study, an in silico approach was applied to design a novel multi-epitope vaccine to elicit a desirable immune response against atherosclerosis. Six novel IL-4 inducing epitopes were selected from HSP60 and calreticulin proteins. To enhance epitope presentation, IL-4 inducing epitopes were linked together by AAY and HEYGAEALERAG linkers. In addition, helper epitopes selected from Tetanus toxin fragment C (TTFrC) were applied to induce CD4+ helper T lymphocytes (HTLs) responses. Moreover, cholera toxin B (CTB) was employed as an adjuvant. A multi-epitope construct was designed based on predicted epitopes which was 320 residues in length. Then, the physico-chemical properties, secondary and tertiary structures, stability, intrinsic protein disorder, solubility and allergenicity of this chimeric protein were analyzed using bioinformatics tools and servers. Based on bioinformatics analysis, a soluble, and non-allergic protein with 35.405 kDa molecular weight was designed. Expasy ProtParam classified this chimeric protein as a stable protein. In addition, predicted epitopes in the chimeric vaccine indicated strong potential to induce B-cell mediated immune response and shift immune responses toward protective Th2 immune response. Various in silico analyses indicate that this vaccine is a qualified candidate for improvement of atherosclerosis by inducing immune responses toward T helper 2.     

Structural functionality, catalytic mechanism modeling and molecular allergenicity of phenylcoumaran benzylic ether reductase, an olive pollen (Ole e 12) allergen

Isoflavone reductase-like proteins (IRLs) are enzymes with key roles in the metabolism of diverse flavonoids. Last identified olive pollen allergen (Ole e 12) is an IRL relevant for allergy amelioration, since it exhibits high prevalence among atopic patients. The goals of this study are the characterization of (A) the structural-functionality of Ole e 12 with a focus in its catalytic mechanism, and (B) its molecular allergenicity by extensive analysis using different molecular computer-aided approaches covering (1) physicochemical properties and functional-regulatory motifs, (2) sequence analysis, 2-D and 3D structural homology modeling comparative study and molecular docking, (3) conservational and evolutionary analysis, (4) catalytic mechanism modeling, and (5) sequence, structure-docking based B-cell epitopes prediction, while T-cell epitopes were predicted by inhibitory concentration and binding score methods. Structural-based detailed features, phylogenetic and sequences analysis have identified Ole e 12 as phenylcoumaran benzylic ether reductase. A catalytic mechanism has been proposed for Ole e 12 which display Lys133 as one of the conserved residues of the IRLs catalytic tetrad (Asn-Ser-Tyr-Lys). Structure characterization revealed a conserved protein folding among plants IRLs. However, sequence polymorphism significantly affected residues involved in the catalytic pocket structure and environment (cofactor and substrate interaction-recognition). It might also be responsible for IRLs isoforms functionality and regulation, since micro-heterogeneities affected physicochemical and posttranslational motifs. This polymorphism might have large implications for molecular differences in B- and T-cells epitopes of Ole e 12, and its identification may help designing strategies to improve the component-resolving diagnosis and immunotherapy of pollen and food allergy through development of molecular tools.     

A combination of epitope prediction and molecular docking allows for good identification of MHC class I restricted T-cell epitopes

In silico identification of T-cell epitopes is emerging as a new methodology for the study of epitope-based vaccines against viruses and cancer. In order to improve accuracy of prediction, we designed a novel approach, using epitope prediction methods in combination with molecular docking techniques, to identify MHC class I restricted T-cell epitopes. Analysis of the HIV-1 p24 protein and influenza virus matrix protein revealed that the present approach is effective, yielding prediction accuracy of over 80% with respect to experimental data. Subsequently, we applied such a method for prediction of T-cell epitopes in SARS coronavirus (SARS-CoV) S, N and M proteins. Based on available experimental data, the prediction accuracy is up to 90% for S protein. We suggest the use of epitope prediction methods in combination with 3D structural modelling of peptide-MHC-TCR complex to identify MHC class I restricted T-cell epitopes for use in epitope based vaccines like HIV and human cancers, which should provide a valuable step forward for the design of better vaccines and may provide in depth understanding about activation of T-cell epitopes by MHC binding peptides.     

T-cell epitopes of the La/SSB autoantigen: prediction based on the homology modeling of HLA-DQ2/DQ7 with the insulin-B peptide/HLA-DQ8 complex

T-cell epitopes are important components of the inappropriate response of the immune system to self-proteins in autoimmune diseases. In this study, the candidate T-cell epitopes of the La/SSB autoantigen, the main target of the autoimmune response in patients with Sjogren's Syndrome (SS), and Systemic Lupus Erythematosus (SLE) were predicted using as a template the HLA-DQ2 and DQ7 molecules, which are genetically linked to patients with SS and SLE. Modeling of DQ2 and DQ7 was based on the crystal structure of HLA-DQ8, an HLA molecule of high risk factor of type I diabetes, which is also an autoimmune disease. The quality and reliability of the modeled DQ2 and DQ7 was confirmed by the Ramachandran plot and the TINKER molecular modeling software. Common and/or similar candidate T-cell epitopes, obtained by comparing three different approaches the Taylor's sequence pattern, the TEPITOPE quantitative matrices, and the MULTIPRED artificial neural network, were subjected to homology modeling with the crystal structure of the insulin-B peptide complexed with HLA-DQ8, and the best superposed candidate epitopes were placed into the modeled HLA-DQ2 and DQ7 binding grooves to perform energy minimization calculations. Six T-cell epitopes were predicted for HLA-DQ7 and nine for HLA-DQ2 covering parts of the amino-terminal and the central regions of the La/SSB autoantigen. Residues corresponding to the P1, P4, and P9 pockets of the HLA-DQ2 and DQ7 binding grooves experience very low SASA because they are less exposed to the microenvironment of the groove. The proposed T-cell epitopes complexed with HLA-DQ2/DQ7 were further evaluated for their binding efficiency according to their potential interaction energy, binding affinity, and IC50 values. Our approach constitutes the ground work for a rapid and reliable experimentation concerning the T-cell epitope mapping of autoantigens, and could lead to the development of T-cell inhibitors as immunotherapeutics in autoimmune diseases.     

A novel in silico minigene vaccine based on CD4+ T-helper and B-cell epitopes of EG95 isolates for vaccination against cystic echinococcosis

EG95 oncospheral antigen plays a crucial role in Echinococcus granulosus pathogenicity. Considering the diversity of antigen among different EG95 isolates, it seems to be an ideal antigen for designing a universal multivalent minigene vaccine, so-called multi-epitope vaccine. This is the first in silico study to design a construct for the development of global EG95-based hydatid vaccine against E. granulosus in intermediate hosts. After antigen sequence selection, the three-dimensional structure of EG95 was modeled and multilaterally validated. The preliminary parameters for B-cell epitope prediction were implemented such as the possible transmembrane helix, signal peptide, post-translational modifications and allergenicity. The high ranked linear and conformational B-cell epitopes derived from several online web-servers (e.g., ElliPro, BepiPred v1.0, BcePred, ABCpred, SVMTrip, IEDB algorithms, SEPPA v2.0 and Discotope v2.0) were utilized for multiple sequence alignment and then for engineering the vaccine construct. T-helper based epitopes were predicted by molecular docking between the high frequent ovar class II allele (Ovar-DRB1*1202) and hexadecamer fragments of the EG95 protein. Having used the immune-informatics tools, we formulated the first EG95-based minigene vaccine based on T-helper epitope with high-binding affinity to the ovar MHC allele. This designed construct was analyzed for different physicochemical properties. It was also codon-optimized for high-level expression in Escherichia coli k12. Taken all, we propose the present in silico vaccine constructs as a promising platform for the generation of broadly protective vaccines for species and genus-specific immunization of the natural hosts of the parasite.     

Using random forest to classify T-cell epitopes based on amino acid properties and molecular features

T-lymphocyte (T-cell) is a very important component in human immune system. T-cell epitopes can be used for the accurately monitoring the immune responses which activation by major histocompatibility complex (MHC), and rationally designing vaccines. Therefore, accurate prediction of T-cell epitopes is crucial for vaccine development and clinical immunology. In current study, two types peptide features, i.e., amino acid properties and chemical molecular features were used for the T-cell epitopes peptide representation. Based on these features, random forest (RF) algorithm, a powerful machine learning algorithm, was used to classify T-cell epitopes and non-T-cell epitopes. The classification accuracy, sensitivity, specificity, Matthews correlation coefficient (MCC), and area under the curve (AUC) values for proposed method are 97.54%, 97.22%, 97.60%, 0.9193, and 0.9868, respectively. These results indicate that current method based on the combined features and RF is effective for T-cell epitopes prediction.     

A totally synthetic, self-assembling, adjuvant-free MUC1 glycopeptide vaccine for cancer therapy

In the development of vaccines for epithelial tumors, the key targets are MUC1 proteins, which have a variable number of tandem repeats (VNTR) bearing tumor-associated carbohydrate antigens (TACAs), such as Tn and STn. A major obstacle in vaccine development is the low immunogenicity of the short MUC1 peptide. To overcome this obstacle, we designed, synthesized, and evaluated several totally synthetic self-adjuvanting vaccine candidates with self-assembly domains. These vaccine candidates aggregated into fibrils and displayed multivalent B-cell epitopes under mild conditions. Glycosylation of Tn antigen on the Thr residue of PDTRP sequence in MUC1 VNTR led to effective immune response. These vaccines elicited a high level antibody response without any adjuvant and induced antibodies that recognized human breast tumor cells. These vaccines appeared to act through a T-cell independent pathway and were associated with the activation of cytotoxic T cells. These fully synthetic, molecularly defined vaccine candidates had several features that hold promise for anticancer therapy.     

Actinic Prurigo in Singaporean Chinese: A Positive Association with HLA‐DRB1*03:01

Studies have reported the association of human leukocyte antigen (HLA) genes with susceptibility to develop actinic prurigo (AP) in Caucasians, but there were no studies in Asian populations, including the Chinese. Our study was performed to determine if AP is associated with susceptibility or protective HLA alleles or haplotypes in Singaporean Chinese. All Chinese patients diagnosed with AP at National Skin Center, Singapore, from January 2002 to April 2015 were invited to participate in the study. Clinical data and phototesting results were collated, and HLA typing was performed. Among 14 patients included, 11 were male and the mean age was 49.6 (37.9–61.3) years. All patients did not have a family history of AP and none had mucosal involvement, as such these clinical features differed from Caucasian AP patients. The frequency of DRB1*03:01 in AP patients was significantly higher compared to healthy controls (43% vs 16%, P = 0.022, odds ratio (OR) 3.89). Concurrently, the frequency of HLA‐B*58:01‐DRB1*03:01 haplotype was also significantly increased (25% vs 7%, P = 0.004, OR 4.23). In conclusion, HLA‐DRB1*03:01 was associated with AP in Singaporean Chinese patients. This novel allelic association may possibly be utilized as a biological marker to aid in the diagnosis of AP in Chinese patients.     

Immuno-fluorescence based Vi capsular polysaccharide detection for specific recognition of Salmonella enterica serovar Typhi in clinical samples

Typhoid fever is a life threatening bacterial infection that remains a major global health concern. This continued high burden associated with significant morbidity and mortality rate demands specific and rapid detection technique. This work reports a new sandwich type fluorescence immunoassay format using polymyxin B, a cationic receptor molecule, as a binder agent while anti-Vi antibody served as the capturing agent for specifically detecting Salmonella enterica serovar Typhi. Anti-Vi IgG antibody raised against Vi–BSA conjugate revealed affinity of 7.779 nM⁻¹ signifying immunodominancy of O-acetyls groups in Vi polysaccharide. The detection limit of the developed assay was around 10¹ cells mL⁻¹ of Vi expressing Salmonella enterica serovar Typhi with a correlation coefficient (R²) equal to 0.97. Positive response obtained for all the tested serovar Typhi clinical isolates as well as the pathogen spiked blood samples recommended specificity and accuracy of Vi antigen as a biomarker during typhoid fever. The intra- and inter-assay precision with Vi spiked samples were satisfactory revealing coefficient of variance (CV%) with a mean of 4.05% and 5.97% respectively. This may be the novel attempt and constructive report on the fluorescence based detection of Vi antigen of serovar Typhi in the epidemic as well as pandemic outbreaks.     

Predicting class I major histocompatibility complex (MHC) binders using multivariate statistics: comparison of discriminant analysis and multiple linear regression

The accurate in silico identification of T-cell epitopes is a critical step in the development of peptide-based vaccines, reagents, and diagnostics. It has a direct impact on the success of subsequent experimental work. Epitopes arise as a consequence of complex proteolytic processing within the cell. Prior to being recognized by T cells, an epitope is presented on the cell surface as a complex with a major histocompatibility complex (MHC) protein. A prerequisite therefore for T-cell recognition is that an epitope is also a good MHC binder. Thus, T-cell epitope prediction overlaps strongly with the prediction of MHC binding. In the present study, we compare discriminant analysis and multiple linear regression as algorithmic engines for the definition of quantitative matrices for binding affinity prediction. We apply these methods to peptides which bind the well-studied human MHC allele HLA-A*0201. A matrix which results from combining results of the two methods proved powerfully predictive under cross-validation. The new matrix was also tested on an external set of 160 binders to HLA-A*0201; it was able to recognize 135 (84%) of them.     

Epitopes based drug design for dengue virus envelope protein: A computational approach

Dengue virus (DENV) has emerged as a rapidly spreading epidemic throughout the tropical and subtropical regions around the globe. No suitable drug has been designed yet to fight against DENV, therefore, the need for safe and effective antiviral drug has become imperative. The envelope protein of DENV is responsible for mediating the fusion process between viral and host membranes. This work reports an in silico approach to target B and T cell epitopes for dengue envelope protein inhibition. A conserved region “QHGTI” in B and T cell epitopes of dengue envelope glycoprotein was confirmed to be valid for targeting by visualizing its interactions with the host cell membrane TIM-1 protein which acts as a receptor for serotype 2 and 3. A reverse pharmacophore mapping approach was used to generate a seven featured pharmacophore model on the basis of predicted epitope. This pharmacophore model as a 3D query was used to virtually screen a chemical compounds dataset “Chembridge”. A total of 1010 compounds mapped on the developed pharmacophore model. These retrieved hits were subjected to filtering via Lipinski’s rule of five, as a result 442 molecules were shortlisted for further assessment using molecular docking. Finally, 14 hits of different structural properties having interactions with the active site residues of dengue envelope glycoprotein were selected as lead candidates. These structurally diverse lead candidates have strong likelihood to act as further starting structures in the development of novel and potential drugs for the treatment of dengue fever.     

Structural and immunogenicity analysis of reconstructed ancestral and consensus P48/45 for cross-species anti malaria transmission-blocking vaccine

The development of the anti-malaria vaccine holds a promising future in malaria control. One of the anti-malaria vaccine strategies known as the transmission-blocking vaccine (TBV) is to inhibit the parasite transmission between humans and mosquitoes by targeting the parasite gametocyte. Previously, we found that P48/45 included in the 6-Cysteine protein family shared by Plasmodium sp. We also detected vaccine properties possessed by all human-infecting Plasmodium and could be used as a cross-species anti-malaria vaccine. In this study, we investigated the efficacy of P48/45 through the ancestral and consensus reconstruction approach. P48/45 phylogenetic and time tree analysis was done by RAXML and BEAST2. GRASP server and Ugene software were used to reconstruct ancestral and consensus sequences, respectively. The protein structural prediction was made by using a psipred and Rosetta program. Each protein characteristic of P48/45 was analyzed by assessing hydrophobicity and Post-Translational Modification sites. Meanwhile, the Epitope sequence for B-cell, T-cell, and HLA was determined using an immunoinformatics approach. Lastly, molecular docking simulation was done to determine native binding interactions of P48/45-P230. The result showed a distinct protein characteristic of ancestral and consensus sequences. The immunogenicity analysis revealed the number of epitopes in the ancestral sequence is greater than the consensus sequence. The study also found a conserved epitope located in the binding site and consists of specific Post-Translational Modification sites. Hence, our research provides detailed insight into ancestral and consensus P48/45 efficacy for the cross-species anti-malaria vaccine.     

Same-single-cell analysis using the microfluidic biochip to reveal drug accumulation enhancement by an amphiphilic diblock copolymer drug formulation

Multidrug resistance (MDR) is one of the major obstacles in drug delivery, and it is usually responsible for unsuccessful cancer treatment. MDR may be overcome by using MDR inhibitors. Among different classes of these inhibitors that block drug efflux mediated by permeability-glycoprotein (P-gp), less toxic amphiphilic diblock copolymers composed of methoxypolyethyleneglycol-block-polycaprolactone (MePEG-b-PCL) have been studied extensively. The purpose of this work is to evaluate how these copolymer molecules can reduce the efflux, thereby enhancing the accumulation of P-gp substrates (e.g., daunorubicin or DNR) in MDR cells. Using conventional methods, it was found that the low-molecular-weight diblock copolymer, MePEG₁₇-b-PCL₅ (PCL5), enhanced drug accumulation in MDCKII-MDR1 cells, but the high-molecular-weight version, MePEG₁₁₄-b-PCL₂₀₀ (PCL200), did not. However, when PCL200 was mixed with PCL5 (and DNR) in order to encapsulate them to facilitate drug delivery, there was no drug enhancement effect attributable to PCL5, and the reason for this negative result was unclear. Since drug accumulation measured on different cell batches originated from single cells, we employed the same-single-cell analysis in the accumulation mode (SASCA-A) to find out the reason. A microfluidic biochip was used to select single MDR cells, and the accumulation of DNR was fluorescently measured in real time on these cells in the absence and presence of PCL5. The SASCA-A method allowed us to obtain drug accumulation information faster in comparison to conventional assays. The SASCA-A results, and subsequent curve-fitting analysis of the data, have confirmed that when PCL5 was encapsulated in PCL200 nanoparticles as soon as they were synthesized, the ability of PCL5 to enhance DNR accumulation was retained, thus suggesting PCL200 as a promising delivery system for encapsulating P-gp inhibitors, such as PCL5. Graphical Abstract

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