CD4+ and CD8+ T-cell multi-epitope chimeric protein associated with an MPLA adjuvant induce protective efficacy and long-term immunological memory for the immunoprophylaxis of American Tegumentary Leishmaniasis.

American Tegumentary Leishmaniasis (ATL) is a disease of high severity and incidence in Brazil, in addition to being a worldwide concern in public health. Leishmania amazonensis is one of the etiological agents of ATL, and the inefficiency of control measures, associated with the high toxicity of the treatment and the lack of effective immunoprophylactic strategies, makes the development of vaccines indispensable and imminent. In this light, the present study proposes to elaborate a chimeric protein (rChiP), based on the fusion of multiple epitopes of CD4+/CD8+ T cells, identified in the immunoproteome of the parasites L. amazonensis and L. braziliensis. The designed chimeric protein was tested in the L. amazonensis murine model of infection using the following formulations: 25 µg of the rChiP in saline (rChiP group) and 25 µg of the rChiP plus 25 µg of MPLA-PHAD® (rChiP+MPLA group). After completing immunization, CD4+ and CD8+ T cells, stimulated with SLa-Antigen or rChiP, showed an increased production of nitric oxide and intracytoplasmic pro-inflammatory cytokines, in addition to the generation of central and effector memory T cells. rChiP and rChiP+MPLA formulations were able to promote an effective protection against L. amazonensis infection determined by a reduction in the development of skin lesions and lower parasitic burden. Reduction in the development of skin lesions and lower parasitic burden in the vaccinated groups were associated with an increase of nitrite, CD4+/CD8+IFN-γ+TNF-α+ and CD4+/CD8+CD44highCD62Lhigh/low T cells, IgGTotal, IgG2a, and lower rates of IgG1 and CD4+/CD8+IL-10+. This data suggests that proposed formulations could be considered potential tools to prevent ATL.

In silico designing of multi-epitope vaccine against canine parvovirus using reverse vaccinology.

Canine parvovirus (CPV-2) is a highly contagious virus affecting dogs worldwide, posing a significant threat. The VP2 protein stands out as the predominant and highly immunogenic structural component of CPV-2. Soon after its emergence, CPV-2 was replaced by variants known as CPV-2a, 2b and 2c, marked by changes in amino acid residue 426 of VP2. Additional amino acid alterations have been identified within VP2, with certain modifications serving as signatures of emerging variants. In Brazil, CPV-2 outbreaks persist with diverse VP2 profiles. Vaccination is the main preventive measure against the virus. However, the emergence of substitutions presents challenges to conventional vaccine methods. Commercial vaccines are formulated with strains that usually do not match those currently circulating in the field. To address this, the study aimed to investigate CPV-2 variants in Brazil, predict epitopes, and design an in silico vaccine tailored to local variants employing reverse vaccinology. The methodology involved data collection, genetic sequence analysis, and amino acid comparison between field strains and vaccines, followed by the prediction of B and T cell epitope regions. The predicted epitopes were evaluated for antigenicity, allergenicity and toxicity. The final vaccine construct consisted of selected epitopes linked to an adjuvant and optimized for expression in Escherichia coli. Structural predictions confirmed the stability and antigenicity of the vaccine, while molecular docking demonstrated interaction with the canine toll-like receptor 4. Molecular dynamics simulations indicated a stable complex formation. In silico immune simulations demonstrated a progressive immune response post-vaccination, including increased antibody production and T-helper cell activity. The multi-epitope vaccine design targeted prevalent CPV-2 variants in Brazil and potentially other regions globally. However, experimental validation is essential to confirm our in silico findings.

Immunoinformatics-Based Design of Multi-epitope DNA and mRNA Vaccines Against Zika Virus.

In this study, we used an immunoinformatics approach to predict antigenic epitopes of Zika virus (ZIKV) proteins to assist in designing a vaccine antigen against ZIKV. We performed the prediction of CD8+ T-lymphocyte and antigenic B-cell epitopes of ZIKV proteins. The binding interactions of T-cell epitopes with major histocompatibility complex class I (MHC-I) proteins were assessed. We selected the antigenic, conserved, nontoxic, and immunogenic epitopes, which indicated significant interactions with the human leucocyte antigen (HLA-A and HLA-B) alleles and worldwide population coverage of 76.35%. The predicted epitopes were joined with the help of linkers and an adjuvant. The vaccine antigen was then analyzed through molecular docking with TLR3 and TLR8, and it was in silico cloned in the pVAX1 vector to be used as a DNA vaccine and designed as a mRNA vaccine.

Understanding SARS-CoV-2 spike glycoprotein clusters and their impact on immunity of the population from Rio Grande do Norte, Brazil.

SARS-CoV-2 genome underwent mutations since it started circulating within the human population. The aim of this study was to understand the fluctuation of the spike clusters concomitant to the population immunity either due to natural infection and/or vaccination in a state of Brazil that had both high rate of natural infection and vaccination coverage. A total of 1725 SARS-CoV-2 sequences from the state of Rio Grande do Norte, Brazil, were retrieved from GISAID and subjected to cluster analysis. Immunoinformatics were used to predict T- and B-cell epitopes, followed by simulation to estimate either pro- or anti-inflammatory responses and to correlate with circulating variants. From March 2020 to June 2022, the state of Rio Grande do Norte reported 579,931 COVID-19 cases with a 1.4% fatality rate across the three major waves: May-Sept 2020, Feb-Aug 2021, and Jan-Mar 2022. Cluster 0 variants (wild type strain, Zeta) were prevalent in the first wave and Delta (AY.*), which circulated in Brazil in the latter half of 2021, featuring fewer unique epitopes. Cluster 1 (Gamma (P.1 + P.1.*)) dominated the first half of 2021. Late 2021 had two new clusters, Cluster 2 (Omicron, (B.1.1.529 + BA.*)), and Cluster 3 (BA.*) with the most unique epitopes, in addition to Cluster 4 (Delta sub lineages) which emerged in the second half of 2021 with fewer unique epitopes. Cluster 1 epitopes showed a high pro-inflammatory propensity, while others exhibited a balanced cytokine induction. The clustering method effectively identified Spike groups that may contribute to immune evasion and clinical presentation, and explain in part the clinical outcome.

Integrated computational approaches assisted development of a novel multi-epitope vaccine against MDR Streptococcus pseudopneumoniae / Abordagens computacionais integradas que auxiliaram no desenvolvimento de uma nova vacina multiepítopo contra Streptococcus pseudopneumoniae multirresistente

The emergence of antibiotic resistance (AR) in bacteria is becoming an alarming health concern because it allows them to adapt themselves to changing environments. It is possible to prevent the spread of AR in many ways, such as reducing antibiotic misuse in human and veterinary medicine. Streptococcus pseudopneumoniae is one of these AR bacterial species that can cause pneumonia in humans and is responsible for high mortality and morbidity rates. It is oval shaped gram-positive bacterium that shows resistance to several antibiotics like penicillin, tetracycline, ciprofloxacin, erythromycin, and co-trimoxazale and no approved vaccine is available to overcome diseases of the pathogen. Thus, substantial efforts are necessary to select protective antigens from a whole genome of pathogens that are easily tested experimentally. The in silico designed vaccine was safe and potent in immunizing individuals against the aforementioned pathogens. Herein, we utilized a subtractive genomic approach to identify potential epitope-based vaccine candidates against S. pseudopneumoniae. In total, 50850 proteins were retrieved from the NCBI, representing the complete genome of S. pseudopneumoniae. Out of the total, CD-HIT analysis identified 1022 proteins as non-redundant and 49828 proteins as redundant and further subjected for subcellular localization in which bulk of proteins was located in the cytoplasm, with seven extracellular proteins (penicillin-binding protein, alpha-amylase, solute-binding protein, hypothetical protein, CHAP domain-containing protein, polysaccharide deacetylase family protein, hypothetical protein). Six immune cells epitopes (SNLQSENDRL, RNDSLQKQAR, NPTTTSEGF, KVKKKNNKK, AYSQGSQKEH, and SVVDQVSGDF) were predicted with the help of the IEDB server. To design a multi-epitopes vaccine these immune cell epitopes were together by GPGPG and adjuvant linker to enhance immune response efficacy. The 3D structure of the designed vaccine was modeled and conducted molecular docking and dynamic simulation studies were to check the binding efficacy with immune cells receptor and dynamic behavior of the docked complex. Finally, we concluded that the designed vaccine construct can provoke a proper and protective immune response against S. pseudopneumoniae.

O surgimento de resistência a antibióticos (AR) em bactérias tem se tornando uma preocupação sanitária alarmante, uma vez que permite que elas se adaptem a ambientes em constante alteração. É possível prevenir a disseminação da RA de várias maneiras, como reduzir o uso indevido de antibióticos na medicina humana e veterinária. O Streptococcus pseudopneumoniae é uma dessas espécies bacterianas de AR que podem causar pneumonia em humanos e são responsáveis por altas taxas de mortalidade e morbidade. É uma bactéria gram-positiva de forma oval que mostra resistência a diversos antibióticos como penicilina, tetraciclina, ciprofloxacina, eritromicina e cotrimoxazale, além disso, nenhuma vacina aprovada está disponível para superar as doenças do patógeno. Assim, esforços substanciais são necessários para selecionar antígenos protetores de todo um genoma de patógenos que são facilmente testados experimentalmente. A vacina projetada in silico foi considerada segura e potente na imunização de indivíduos contra os patógenos mencionados. Neste trabalho, utilizamos uma abordagem genômica subtrativa para identificar potenciais candidatos a vacinas baseadas em epítopos contra S. pseudopneumoniae. No total, 50.850 proteínas foram recuperadas do NCBI, representando o genoma completo de S. pseudopneumoniae. Do total, a análise de CD-HIT identificou 1.022 proteínas como não redundantes e 49.828 proteínas como redundantes e posteriormente submetidas à localização subcelular na qual a maior parte das proteínas estava localizada no citoplasma, com sete proteínas extracelulares (proteína de ligação à penicilina, alfa- amilase, proteína de ligação a soluto, proteína hipotética, proteína contendo domínio CHAP, proteína da família polissacarídeo desacetilase, proteína hipotética). Seis epítopos de células imunes (SNLQSENDRL, RNDSLQKQAR, NPTTTSEGF, KVKKKNNKK, AYSQGSQKEH e SVVDQVSGDF) foram previstos com a ajuda do servidor IEDB. Para projetar uma vacina de múltiplos epítopos, esses epítopos de células imunes foram reunidos por GPGPG e um ligante adjuvante para aumentar a eficácia da resposta imune. A estrutura 3D da vacina projetada foi modelada e conduzido estudos de docking molecular e simulação dinâmica para verificar a eficácia da ligação com o receptor de células imunes e o comportamento dinâmico do complexo docked. Finalmente, concluímos que a construção da vacina projetada pode provocar uma resposta imune adequada e protetora contra S. pseudopneumoniae.

Avanços sobre vacinas e anti-soros contra veneno de serpentes e estudo de epítopos para a família de toxinas fosfolipase A2

Animal venoms are produced by specialized glands into their predators and injected in the prey, releasing secretions rich in toxins that are harmful to health. Those venomous animals trigger countless accidents around the world. These include snakebite accidents, which have been included by the World Health Organisation (WHO) in the list of neglected tropical diseases. This public health problem is caused by snakes whose toxins include proteins such as phospholipases A2 (PLA2), enzymes that are widely present in venom and trigger various physiological effects. The treatment recommended by the Ministry of Health is the application of antiophidic serum, which is manufacture based on hyperimmunization carried out on horses capable of neutralizing the action of the venom. However, this procedure has some disadvantages that end up hampering its benefits and effectiveness for victims. Thus, new methods of producing antivenom have been developed with the aim of creating alternative therapies that can improve and minimize problems. Consequently, in silico studies of immunobiologicals are becoming an option to facilitate the development of new antivenoms. This project therefore proposes the use of computational tools to predict epitopes in snake venoms, with a focus on the PLA2 family. Extracting PLA2 protein sequences from databases such as UniProt and the Immune Epitope Database in order to make predictions and classify epitope candidates. As a result, we obtained 17 candidate positions based on in silico analyses and experimental evidence from the literature. It is expect that these approaches will support studies in this area, as they will become an useful tool for developing the next generation of antivenoms.

As peçonhas animais são produzidas por glândulas especializadas em seus predadores, as quais são injetadas nas presas, liberando secreções ricas em toxinas prejudiciais à saúde. Estes animais peçonhentos desencadeiam inúmeros acidentes no mundo todo. Dentre eles, estão os acidentes ofídicos que passaram a ser incluídos pela Organização Mundial da Saúde (OMS) na lista das doenças tropicais negligenciadas. Esse problema de saúde pública é ocasionado pelas serpentes que apresentam na composição de suas toxinas proteínas como as fosfolipases A2 (PLA2), uma das enzimas mais presentes em peçonhas, as quais desencadeiam diversos efeitos fisiológicos. O tratamento preconizado pelo Ministério da Saúde é a aplicação de soro antiofídico, o qual é fabricado a partir da hiperimunização realizada em cavalos capazes de neutralizar a ação do veneno. Entretanto, esse procedimento possui algumas desvantagens que podem diminuir seus benefícios e eficácia às vítimas. Dessa forma, novas elaborações na produção de antiveneno vêm sendo desenvolvidas com intuito de criar terapias alternativas que gerem melhorias e minimizem os problemas. Consequentemente, estudos in silico de imunobiológicos se tornam opções para facilitar o desenvolvimento de novos antivenenos. Em virtude disto, neste projeto propõe o uso de ferramentas computacionais para predição de epítopos em venenos de serpentes com foco na família PLA2. Extraindo sequências proteicas de PLA2 de bancos de dados como UniProt e Immune Epitope Database, a fim de realizar as predições e classificar os candidatos a epítopos. Como resultado obtivemos 17 posições candidatas com base nas análises in sílico e evidências experimentais da literatura. Espera-se que essa abordagem possa auxiliar estudos nessa área, uma vez que se torna uma ferramenta útil para o desenvolvimento da próxima geração de antivenenos.

Bibliometric analysis of the use of Immunoinformatics in the production of SARS-CoV-2 vaccine prototypes

The COVID-19-19 pandemic's global impact has accelerated the need for effective vaccines, challenging traditional, time-consuming, and costly vaccinology methods. Immunoinformatics emerges as a promising alternative to expedite vaccine development, thus this study aims to provide a comprehensive bibliometric analysis of its application in formulating SARS-CoV-2 vaccine prototypes. Employing VOSviewer software and data from the Web of Science database, this study conducted a bibliometric analysis. Key metrics included the global distribution of scientific publications, the most productive countries and institutions, influential authors, co-citation and co-authorship networks, and prevalent keywords in immunoinformatics research related to SARS-CoV-2 vaccines. The analysis encompassed 138 scholarly articles, with India emerging as a pivotal contributor, particularly through notable contributions from Adamas and Fakir Mohan universities. The most cited article, authored by Bhattacharya, received 226 citations, while Doytchinova was a prominent cited source, referenced in 96 of the 138 analyzed documents. The study observed substantial collaborative efforts among authors from 45 nations, with 85% of the research concentrated in just six countries. Pakistan demonstrated the highest level of international collaboration, contributing to 15/20 collaborative publications. Keywords such as 'SARS-CoV-2', 'immunoinformatics', and 'prediction' were frequently encountered across most of these documents. This bibliometric analysis elucidates the primary research trends in the field and delineates the global scope and distribution of immunoinformatics studies in the realm of SARS-CoV-2 vaccine development. These findings offer a vital overview of the current landscape, guiding future research directions and potential collaborative efforts in the pursuit of effective COVID-19 vaccines.

El impacto global de la pandemia de COVID-19 ha acelerado la necesidad de vacunas efectivas, lo que ha desafiado los métodos tradicionales de vacunología que son costosos y consumen mucho tiempo. La inmunoinformática surge como una alternativa prometedora para acelerar el desarrollo de vacunas. Este estudio tuvo como objetivo proporcionar un análisis bibliométrico exhaustivo de su aplicación en la formulación de prototipos de vacunas contra el SARS-CoV-2. Utilizando el software VOSviewer y datos de la base de datos Web of Science, se realizó un análisis bibliométrico. Las métricas clave incluyeron: la distribución global de publicaciones científicas, los países e instituciones más productivos, autores influyentes, redes de cocitación y coautoría y palabras clave prevalentes en la investigación de inmunoinformática relacionada con las vacunas contra el SARS-CoV-2. El análisis abarcó 138 artículos académicos; la India emergió como un contribuyente principal, particularmente a través de contribuciones notables de las universidades Adamas y Fakir Mohan. El artículo más citado fue el de Bhattacharya, que recibió 226 citas; mientras que Doytchinova fue una fuente citada prominente, referenciada en 96 de los 138 documentos analizados. El estudio observó esfuerzos colaborativos sustanciales entre autores de 45 naciones con el 85 % de la investigación concentrada en seis países. Pakistán demostró el nivel más alto de colaboración internacional, al contribuir con 15 de los 20 artículos colaborativos. Palabras clave como 'SARS-CoV-2', 'immunoinformatics' y 'prediction' se encontraron frecuentemente en la mayoría de estos documentos. Este análisis bibliométrico aclara las principales tendencias de investigación en el campo y delinea el alcance global y la distribución de los estudios de inmunoinformática en el ámbito del desarrollo de vacunas contra el SARS-CoV-2. Los hallazgos ofrecen una visión vital del panorama actual, guían investigaciones futuras y posibles esfuerzos colaborativos en la búsqueda de vacunas efectivas contra la COVID-19.

Surveillance of SARS-CoV-2 immunogenicity: loss of immunodominant HLA-A*02-restricted epitopes that activate CD8+ T cells.

Introduction and methods: In this present work, coronavirus subfamilies and SARS-CoV-2 Variants of Concern (VOCs) were investigated for the presence of MHC-I immunodominant viral peptides using in silico and in vitro tools. Results: In our results, HLA-A*02 haplotype showed the highest number of immunodominant epitopes but with the lowest combined prediction score. Furthermore, a decrease in combined prediction score was observed for HLA-A*02-restricted epitopes when the original strain was compared to the VOCs, indicating that the mutations on the VOCs are promoting escape from HLA-A2-mediated antigen presentation, which characterizes a immune evasion process. Additionally, epitope signature analysis revealed major immunogenic peptide loss for structural (S) and non-structural (ORF8) proteins of VOCs in comparison to the Wuhan sequence. Discussion: These results may indicate that the antiviral CD8+ T-cell responses generated by original strains could not be sufficient for clearance of variants in either newly or reinfection with SARS-CoV-2. In contrast, N epitopes remain the most conserved and reactive peptides across SARS-CoV-2 VOCs. Overall, our data could contribute to the rational design and development of new vaccinal platforms to induce a broad cellular CD8+ T cell antiviral response, aiming at controlling viral transmission of future SARS-CoV-2 variants.

The high identity of the Trypanosoma cruzi Group-I of trans-sialidases points them as promising vaccine immunogens.

Trans-sialidase (TS) superfamily of proteins comprises eight subgroups, being the proteins of Group-I (TS-GI) promising immunogens in vaccine approaches against Trypanosoma cruzi. Strikingly, TS-GI antigenic variability among parasite lineages and their influence on vaccine development has not been previously analyzed. Here, a search in GenBank detects 49 TS-GI indexed sequences, whereas the main infecting human different parasite discrete typing units (DTU) are represented. In silico comparison among these sequences indicate that they share an identity above 92%. Moreover, the antigenic regions (T-cell and B-cell epitopes) are conserved in most sequences or present amino acid substitutions that scarcely may alter the antigenicity. Additionally, since the generic term TS is usually used to refer to different immunogens of this broad family, a further in silico analysis of the TS-GI-derived fragments tested in preclinical vaccines was done to determine the coverage and identity among them, showing that overall amino acid identity of vaccine immunogens is high, but the segment coverage varies widely. Accordingly, strong H-2K, H-2I, and B-cell epitopes are dissimilarly represented among vaccine TS-derived fragments depending on the extension of the TG-GI sequence used. Moreover, bioinformatic analysis detected a set of 150 T-cell strong epitopes among the DTU-indexed sequences that strongly bind human HLA-I supertypes. In all currently reported experimental vaccines based on TS-GI fragments, mapping these 150 epitopes showed that they are moderately represented. However, despite vaccine epitopes do not present all the substitutions observed in the DTUs, these regions of the proteins are equally recognized by the same HLAs.  Interestingly, the predictions regarding global and South American population coverage estimated in these 150 epitopes are similar to the estimations in experimental vaccines when the complete sequence of TS-GI is used as an antigen. In silico prediction also shows that a number of these MHC-I restricted T-cell strong epitopes could be also cross-recognized by HLA-I supertypes and H-2Kb or H-2Kd backgrounds, indicating that these mice may be used to improve and facilitate the development of new TS-based vaccines and suggesting an immunogenic and protective potential in humans. Further molecular docking analyses were performed to strengthen these results. Taken together, different strategies that would cover more or eventually fully of these T-cell and also B-cell epitopes to reach a high level of coverage are considered.

Immunoinformatics Vaccine Design for Zika Virus.

Zika virus (ZIKV) is an emerging virus from the Flaviviridae family and Flavivirus genus that has caused important outbreaks around the world. ZIKV infection is associated with severe neuropathology in newborns and adults. Until now, there is no licensed vaccine available for ZIKV infection. Therefore, the development of a safe and effective vaccine against ZIKV is an urgent need. Recently, we designed an in silico multi-epitope vaccine for ZIKV based on immunoinformatics tools. To construct this in silico ZIKV vaccine, we used a consensus sequence generated from ZIKV sequences available in databank. Then, we selected CD4+ and CD8+ T cell epitopes from all ZIKV proteins based on the binding prediction to class II and class I human leukocyte antigen (HLA) molecules, promiscuity, and immunogenicity. ZIKV Envelope protein domain III (EDIII) was added to the construct and B cell epitopes were identified. Adjuvants were associated to increase immunogenicity. Distinct linkers were used for connecting the CD4+ and CD8+ T cell epitopes, EDIII, and adjuvants. Several analyses, such as antigenicity, population coverage, allergenicity, autoimmunity, and secondary and tertiary structures of the vaccine, were evaluated using various immunoinformatics tools and online web servers. In this chapter, we present the protocols with the rationale and detailed steps needed for this in silico multi-epitope ZIKV vaccine design.

Immunoinformatics-guided design of a multi-valent vaccine against Rotavirus and Norovirus (ChRNV22).

Rotavirus (RV) and Norovirus (NV) are the main viral etiologic agents of acute gastroenteritis (AG), a serious pediatric condition associated with significant death rates and long-term complications. Anti-RV vaccination has been proved efficient in the reduction of severe AG worldwide, however, the available vaccines are all attenuated and have suboptimal efficiencies in developing countries, where AG leads to substantial disease burden. On the other hand, no NV vaccine has been licensed so far. Therefore, we used immunoinformatics tools to develop a multi-epitope vaccine (ChRNV22) to prevent severe AG by RV and NV. Epitopes were predicted against 17 prevalent genotypes of four structural proteins (NV's VP1, RV's VP4, VP6 and VP7), and then assembled in a chimeric protein, with two small adjuvant sequences (tetanus toxin P2 epitope and a conserved sequence of RV's enterotoxin, NSP4). Simulations of the immune response and interactions with immune receptors indicated the immunogenic properties of ChRNV22, including a Th1-biased response. In silico search for putative host-homologous, allergenic and toxic regions also indicated the vaccine safety. In summary, we developed a multi-epitope vaccine against different NV and RV genotypes that seems promising for the prevention of severe AG, which will be further assessed by in vivo tests.

Diversity of HLA-A2-Restricted and Immunodominant Epitope Repertoire of Human T-Lymphotropic Virus Type 1 (HTLV-1) Tax Protein: Novel Insights among N-Terminal, Central and C-Terminal Regions.

The present study sought to search for the immunodominance related to the N-terminal, Central and C-terminal regions of HTLV-1 Tax using novel, cutting-edge peptide microarray analysis. In addition, in silico predictions were performed to verify the presence of nine amino acid peptides present along Tax restricted to the human leukocyte antigen (HLA)-A2.02*01 haplotype, as well as to verify the ability to induce pro-inflammatory and regulatory cytokines, such as IFN-γ and IL-4, respectively. Our results indicated abundant dose-dependent reactivity for HLA-A*02:01 in all regions (N-terminal, Central and C-terminal), but with specific hotspots. Furthermore, the results of fold-change over the Tax11-19 reactivity obtained at lower concentrations of HLA-A*02:01 reveal that peptides from the three regions contain sequences that react 100 times more than Tax11-19. On the other hand, Tax11-19 has similar or superior HLA-A*02:01 reactivity at higher concentrations of this haplotype. The in silico analysis showed a higher frequency of IFN-γ-inducing peptides in the N-terminal portion, while the C-terminal portion showed a higher frequency of IL-4 inducers. Taken together, these results shed light on the search for new Tax immunodominant epitopes, in addition to the canonic Tax11-19, for the rational design of immunomodulatory strategies for HTLV-1 chronic diseases.

Computational vaccinology guided design of multi-epitope subunit vaccine against a neglected arbovirus of the Americas.

Mayaro virus (MAYV) is an arbovirus found in the Americas that can cause debilitating arthritogenic disease. Although it is an emerging virus, the only current approach is vector control, as there are no approved vaccines to prevent MAYV infection nor therapeutics to treat it. In search of an effective vaccine candidate against MAYV, we used immunoinformatics and molecular modeling to attempt to identify promiscuous T-cell epitopes of the nonstructural polyproteins (nsP1, nsP2, nsP3, and nsP4) from 127 MAYV genomes sequenced in the Americas (08 Bolivia, 72 Brazil, 04 French Guiana, 05 Haiti, 20 Peru, 04 Trinidad and Tobago, and 14 Venezuela). For this purpose, consensus sequences of 360 proteins were used to identify short protein sequences that can bind to MHC I class (MHC II). Our analysis revealed 56 potential MHC-I/TCD8+ (29 MHC-II/TCD4+) epitopes, but only 6 (16) TCD8+ (TCD4+) epitopes showed high antigenicity and conservation, non-allergenicity, non-toxicity, and excellent population coverage. Finally, classical and quantum mechanical calculations (QM:MM) were used to improve the quality of the docking calculations, with the QM part of the simulations performed using the density functional theory formalism (DFT). These results provide insights for the advancement of diagnostic platforms, vaccine development, and immunotherapeutic interventions.Communicated by Ramaswamy H. Sarma.

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

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

Immunoprophylactic properties of the Corynebacterium pseudotuberculosis-derived MBP:PLD:CP40 fusion protein.

Caseous lymphadenitis (CLA) is a disease that affects small ruminants, and the best way to prevent its spread on a herd is through immunoprophylaxis. Thus, we aimed to evaluate the MBP:PLD:CP40 fusion protein as a new CLA immunogen. The fusion protein was constructed by combining Corynebacterium pseudotuberculosis PLD and CP40 proteins with maltose-binding protein (MBP) as an intrinsic adjuvant. The antigenicity, allergenic potential, prediction of B epitopes, binding to MHC receptors, and docking on the Toll-Like 2 receptor were evaluated in silico. MBP:PLD:CP40 was expressed and purified. 40 BALB/c were divided into four groups (G1 - control, G2 - Saponin, G3 - MBP:PLD:CP40, and G4 - rPLD + rCP40). Total IgG, IgG1, and IgG2a were quantified, and the expressions of cytokines after splenocyte in vitro stimulation were assessed. Mice were challenged 42 days after the first immunization. The in silico analysis showed that MBP:PLD:CP40 has immunogenic potential, does not have allergic properties, and can dock on the TRL2 receptor. MBP:PLD:CP40 stimulated the production of IgG1 antibodies in a fivefold proportion to IgG2a, and TNF and IL-17 were significantly expressed in response to the antigenic stimuli. When rPLD and rCP40 were used together for immunization, they could induce IFN-γ and IL-12, but with no detectable antibody production. The G3 and G4 groups presented a survival of 57.14% and 42.86%, respectively, while the G1 and G2 mice were all dead 15 days after the challenge. MBP:PLD:CP40 partially protected the mice against C. pseudotuberculosis infection and can be considered a potential new CLA immunogen. KEY POINTS: • The fusion protein induced more IgG1 than IgG2a antibodies; • The fusion protein also induced the expression of the TNF and IL-17 cytokines; • Mice inoculated with MBP:PLD:CP40 presented a 57.14% survival.

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

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

Immunoinformatic analysis of the whole proteome for vaccine design: An application to Clostridium perfringens.

Clostridium perfringens is a dangerous bacterium and known biological warfare weapon associated with several diseases, whose lethal toxins can produce necrosis in humans. However, there is no safe and fully effective vaccine against C. perfringens for humans yet. To address this problem, we computationally screened its whole proteome, identifying highly immunogenic proteins, domains, and epitopes. First, we identified that the proteins with the highest epitope density are Collagenase A, Exo-alpha-sialidase, alpha n-acetylglucosaminidase and hyaluronoglucosaminidase, representing potential recombinant vaccine candidates. Second, we further explored the toxins, finding that the non-toxic domain of Perfringolysin O is enriched in CTL and HTL epitopes. This domain could be used as a potential sub-unit vaccine to combat gas gangrene. And third, we designed a multi-epitope protein containing 24 HTL-epitopes and 34 CTL-epitopes from extracellular regions of transmembrane proteins. Also, we analyzed the structural properties of this novel protein using molecular dynamics. Altogether, we are presenting a thorough immunoinformatic exploration of the whole proteome of C. perfringens, as well as promising whole-protein, domain-based and multi-epitope vaccine candidates. These can be evaluated in preclinical trials to assess their immunogenicity and protection against C. perfringens infection.

In silico designing of a recombinant multi-epitope antigen for leprosy diagnosis.

BACKGROUND: Leprosy is caused by Mycobacterium leprae and Mycobacterium lepromatosis. Most of the affected population lives in low-income countries and may take up to 10 years to show any clinical signs, which is how physicians diagnose it. However, due to progressive cell damage, early diagnosis is very important. The best way to confirm leprosy is through bacilloscopic, which only confirms the diagnosis and has low accuracy or PCR, that requires specialized operators and is expensive. Since the bacteria are fastidious and do not grow in any culture media, therefore, diagnosing leprosy in the lab is still a challenge. In this concern, a recombinant multi-epitope protein can be a beneficial strategy in the management of the diagnosis, as diverse immunogenic epitopes are precisely selected to detect specific antibodies. Therefore, the purposes of the present study were to select immunogenic epitopes from different relevant proteins, with immunogenic properties, and then to construct a recombinant multi-epitope protein that accuses the presence of the antibodies in the early stages of the disease, making it more than appropriate to be applied as a diagnostic tool. RESULTS: We selected 22 common proteins from both species and, using bioinformatics tools, predicted B and T cell epitopes. After multiple filtering and analyzing, we ended up with 29 epitopes {MHC-I (total 18) and MHC-II (total 11)} from 10 proteins, which were then merged into one construct. Its secondary and tertiary structures were also predicted and refined to comprise the amino acid residues in the best conformation possible. The multi-epitope protein construct was stable, non-host homologous, non-allergic, non-toxic, and elicit humoral and cellular responses. It has conformational B cell epitopes and potential to elicit IFN-γ, IL-4, and IL-10 secretion. CONCLUSIONS: This novel recombinant multi-epitope protein constructed using the common epitopes from M. leprae and M. lepromatosis has a huge immunological potential, is stable, and can be lyophilized to be used in ELISA plates or even in biosensors, which are user-friendly diagnosis tools, facilitating translation into human sample tests.

Chikungunya Virus E2 Structural Protein B-Cell Epitopes Analysis.

The Togaviridae family comprises a large and diverse group of viruses responsible for recurrent outbreaks in humans. Within this family, the Chikungunya virus (CHIKV) is an important Alphavirus in terms of morbidity, mortality, and economic impact on humans in different regions of the world. The objective of this study was to perform an IgG epitope recognition of the CHIKV's structural proteins E2 and E3 using linear synthetic peptides recognized by serum from patients in the convalescence phase of infection. The serum samples used were collected in the state of Sergipe, Brazil in 2016. Based on the results obtained using immunoinformatic predictions, synthetic B-cell peptides corresponding to the epitopes of structural proteins E2 and E3 of the CHIKV were analyzed by the indirect peptide ELISA technique. Protein E2 was the main target of the immune response, and three conserved peptides, corresponding to peptides P3 and P4 located at Domain A and P5 at the end of Domain B, were identified. The peptides P4 and P5 were the most reactive and specific among the 11 epitopes analyzed and showed potential for use in serological diagnostic trials and development and/or improvement of the Chikungunya virus diagnosis and vaccine design.

In Silico Designed Multi-Epitope Immunogen "Tpme-VAC/LGCM-2022" May Induce Both Cellular and Humoral Immunity against Treponema pallidum Infection.

Syphilis, a sexually transmitted infection caused by the spirochete Treponema pallidum, has seen a resurgence over the past years. T. pallidum is capable of early dissemination and immune evasion, and the disease continues to be a global healthcare burden. The purpose of this study was to design a multi-epitope immunogen through an immunoinformatics-based approach. Multi-epitope immunogens constitute carefully selected epitopes belonging to conserved and essential bacterial proteins. Several physico-chemical characteristics, such as antigenicity, allergenicity, and stability, were determined. Further, molecular docking and dynamics simulations were performed, ensuring binding affinity and stability between the immunogen and TLR-2. An in silico cloning was performed using the pET-28a(+) vector and codon adaptation for E. coli. Finally, an in silico immune simulation was performed. The in silico predictions obtained in this work indicate that this construct would be capable of inducing the requisite immune response to elicit protection against T. pallidum. Through this methodology we have designed a promising potential vaccine candidate for syphilis, namely Tpme-VAC/LGCM-2022. However, it is necessary to validate these findings in in vitro and in vivo assays.