Designing an efficient multi-epitope vaccine against Campylobacter jejuni using immunoinformatics and reverse vaccinology approach

Epitope mapping targeting the K205R protein of African swine fever virus using nanobody as a novel tool

African swine fever (ASF) is a highly infectious and lethal swine disease, leading to enormous losses in the pig industry. K205R, a non-structural protein of ASF virus (ASFV), is abundantly expressed at the early stages of viral infection and induces a strong immune response. In our previous study, five strains of K205R-specific nanobodies (Nbs) were screened through phage display technology, among which Nb1, Nb14, Nb35, and Nb82 exhibited good affinity. In the present study, the above four Nbs were successfully expressed in HEK293T cells and exhibited strong reactivity. Four Nbs recognized linear B-cell epitopes of K205R in both prokaryotic and eukaryotic expression systems. Besides, four Nbs specifically reacted with the K205R protein of ASFV-infected cells. Two epitopes 1MVEPR5 and 188RTQF191 were further identified, with highly conserved in different ASFV strains, and could interact with inactivated ASFV-positive sera, indicating that the two epitopes were natural linear B-cell epitopes. Moreover, structural analysis indicated that both epitopes were exposed on the surface of the K205R molecule. Notably, the identified epitope 188RTQF191 was first reported. Overall, these findings provide valuable insights for K205R as an effective diagnostic tool and vaccine development.IMPORTANCEAfrican swine fever (ASF) is the number one killer affecting the pig industry, and there are no effective strategies for prevention. The ASFV K205R protein is prominently expressed in the early stages of viral infection, triggering a robust immune response. The full understanding of K205R protein epitopes provides a theoretical basis for the development of vaccine-candidate proteins. Nanobodies exhibit superior capability in detecting concealed epitopes of antigens compared with traditional antibodies. Here, we identify two epitopes 1MVEPR5 and 188RTQF191 based on nanobodies as a tool. Notably, the epitope188RTQF191 is being reported for the first time. These epitopes are highly conserved in different ASFV strains and represent natural linear B-cell epitopes. This study opens up nanobodies as a new tool for the identification of epitopes and also provides a direct material basis for the development of ASFV vaccines.

Designing a multi-epitope influenza vaccine: an immunoinformatics approach

Influenza continues to be one of the top public health problems since it creates annual epidemics and can start a worldwide pandemic. The virus's rapid evolution allows the virus to evade the host defense, and then seasonal vaccines need to be reformulated nearly annually. However, it takes almost half a year for the influenza vaccine to become accessible. This delay is especially concerning in the event of a pandemic breakout. By producing the vaccine through reverse vaccinology and phage display vaccines, this time can be reduced. In this study, epitopes of B lymphocytes, cytotoxic T lymphocytes, and helper T lymphocytes of HA, NA, NP, and M2 proteins from two strains of Influenza A were anticipated. We found two proper epitopes (ASFIYNGRL and LHLILWITDRLFFKC) in Influenza virus proteins for CTL and HTL cells, respectively. Optimal epitopes and linkers in silico were cloned into the N-terminal end of M13 protein III (pIII) to create a multi-epitope-pIII construct, i.e., phage display vaccine. Also, prediction of tertiary structure, molecular docking, molecular dynamics simulation, and immune simulation were performed and showed that the designed multi-epitope vaccine can bind to the receptors and stimulate the immune system response.

Exploring the nuclear proteins, viral capsid protein, and early antigen protein using immunoinformatic and molecular modeling approaches to design a vaccine candidate against Epstein Barr virus

The available Epstein Barr virus vaccine has tirelessly harnessed the gp350 glycoprotein as its target epitope, but the result has not been preventive. Right here, we designed a global multi-epitope vaccine for EBV; with special attention to making sure all strains and preventive antigens are covered. Using a robust computational vaccine design approach, our proposed vaccine is armed with 6-16 mers linear B-cell epitopes, 4-9 mer CTL epitopes, and 8-15 mer HTL epitopes which are verified to induce interleukin 4, 10 & IFN-gamma. We employed deep computational mining coupled with expert intelligence in designing the vaccine, using human Beta defensin-3-which has been reported to induce the same TLRs as EBV-as the adjuvant. The tendency of the vaccine to cause autoimmune disorder is quenched by the assurance that the construct contains no EBNA-1 homolog. The protein vaccine construct exhibited excellent physicochemical attributes such as Aliphatic index 59.55 and GRAVY - 0.710; and a ProsaWeb Z score of - 3.04. Further computational analysis revealed the vaccine docked favorably with EBV indicted TLR 1, 2, 4 & 9 with satisfactory interaction patterns. With global coverage of 85.75% and the stable molecular dynamics result obtained for the best two interactions, we are optimistic that our nontoxic, non-allergenic multi-epitope vaccine will help to ameliorate the EBV-associated diseases-which include various malignancies, tumors, and cancers-preventively.

Proteomics-based vaccine targets annotation and design of multi-epitope vaccine against antibiotic-resistant Streptococcus gallolyticus

Streptococcus gallolyticus is a non-motile, gram-positive bacterium that causes infective endocarditis. S. gallolyticus has developed resistance to existing antibiotics, and no vaccine is currently available. Therefore, it is essential to develop an effective S. gallolyticus vaccine. Core proteomics was used in this study together with subtractive proteomics and reverse vaccinology approach to find antigenic proteins that could be utilized for the design of the S. gallolyticus multi-epitope vaccine. The pipeline identified two antigenic proteins as potential vaccine targets: penicillin-binding protein and the ATP synthase subunit. T and B cell epitopes from the specific proteins were forecasted employing several immunoinformatics and bioinformatics resources. A vaccine (360 amino acids) was created using a combination of seven cytotoxic T cell lymphocyte (CTL), three helper T cell lymphocyte (HTL), and five linear B cell lymphocyte (LBL) epitopes. To increase immune responses, the vaccine was paired with a cholera enterotoxin subunit B (CTB) adjuvant. The developed vaccine was highly antigenic, non-allergenic, and stable for human use. The vaccine's binding affinity and molecular interactions with the human immunological receptor TLR4 were studied using molecular mechanics/generalized Born surface area (MMGBSA), molecular docking, and molecular dynamic (MD) simulation analyses. Escherichia coli (strain K12) plasmid vector pET-28a ( +) was used to examine the ability of the vaccine to be expressed. According to the outcomes of these computer experiments, the vaccine is quite promising in terms of developing a protective immunity against diseases. However, in vitro and animal research are required to validate our findings.

Expression, Purification, and Evaluation of Antibody Responses and Antibody-Immunogen Complex Simulation of a Designed Multi-Epitope Vaccine against SARS-COV-2

BACKGROUND

The spread of the COVID-19 disease is the result of an infection caused by the SARS-CoV2 virus. Four crucial proteins, spike (S), membrane (M), nucleocapsid (N), and envelope (E) in coronaviruses have been considered to a large extent.

OBJECTIVE

This research aimed to express the recombinant protein of a multiepitope immunogen construct and evaluate the immunogenicity of the multiepitope vaccine that was previously designed as a candidate immunogenic against SARS-Cov-2.

MATERIALS AND METHODS

Plasmid pET26b was transferred to the expression host E. coli BL21 (DE3) and the recombinant protein was expressed with IPTG induction. The recombinant protein was purified by Ni-NTA column affinity chromatography, and western blotting was used to confirm it. Finally, mice were immunized with recombinant protein in three doses. Then, the interaction of the 3D structure of the vaccine with the human neutralizing antibodies3D structures (7BWJ and 7K8N) antibody was evaluated by docking and molecular dynamics simulation.

RESULTS

The optimized gene had a codon compatibility index of 0.96. The expression of the recombinant protein of the SARS-Cov-2 vaccine in an E. coli host led to the production of the recombinant protein with a weight of about 70 kDa with a concentration of 0.7 mg/ml. Immunization of mice with recombinant protein of SARS-Cov-2 vaccine-induced IgG serum antibody response. Statistical analysis showed that the antibody titer in comparison with the control sample has a significant difference, and the antibody titer was acceptable up to 1/256000 dilution. The simulation of vaccine binding with human antibodies by molecular dynamics showed that Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), Radius of Gyration, and H-bond as well as van der Waals energies and electrostatic of Molecular mechanics Poisson- Boltzmann surface area (MM/PBSA) analysis have stable interaction.

CONCLUSION

This recombinant protein can probably be used as an immunogen candidate for the development of vaccines against SARS-CoV2 in future research.

Evaluation of Two Recombinant Protein-Based Vaccine Regimens against Campylobacter jejuni: Impact on Protection, Humoral Immune Responses and Gut Microbiota in Broilers

Campylobacter infections in humans are traced mainly to poultry products. While vaccinating poultry against Campylobacter could reduce the incidence of human infections, no vaccine is yet available on the market. In our previous study using a plasmid DNA prime/recombinant protein boost vaccine regimen, vaccine candidate YP437 induced partial protective immune responses against Campylobacter in broilers. In order to optimise vaccine efficacy, the vaccination protocol was modified using a protein prime/protein boost regimen with a different number of boosters. Broilers were given two or four intramuscular protein vaccinations (with the YP437 vaccine antigen) before an oral challenge by C. jejuni during a 42-day trial. The caecal Campylobacter load, specific systemic and mucosal antibody levels and caecal microbiota in the vaccinated groups were compared with their respective placebo groups and a challenge group (Campylobacter infection only). Specific humoral immune responses were induced, but no reduction in Campylobacter caecal load was observed in any of the groups (p > 0.05). Microbiota beta diversity analysis revealed that the bacterial composition of the groups was significantly different (p ≤ 0.001), but that vaccination did not alter the relative abundance of the main bacterial taxa residing in the caeca. The candidate vaccine was ineffective in inducing a humoral immune response and therefore did not provide protection against Campylobacter spp. infection in broilers. More studies are required to find new candidates.

A novel approach to design a multiepitope peptide as a vaccine candidate for Bordetella pertussis

Bordetella pertussis is a very contagious pathogen in humans, causing pertussis disease. Pertussis is one of the 10 leading causes of death due to infectious diseases, especially among infants and children. Antibiotic-resistant strains have recently emerged in this bacterium, and despite the high vaccination coverage, the prevalence of this disease has been increasing recently in both developed and developing countries. The objective of this study is to introduce a novel in silico vaccine candidate aimed at countering B. pertussis effectively. Differing from other comparable studies, this research employed a computational screening methodology to assess the genome of 'Bordetella pertussis 18323.' The purpose was to identify an innovative antigen for the development of a vaccine against B. pertussis. Notably, our investigation introduces an innovative antigen distinguished by its elevated immunogenicity score. Importantly, this antigen lacks toxicity and allergenicity, making it recognizable to the immune system and thus capable of inducing a robust immune response. In the subsequent phase, our antigen was utilized to identify potential epitopes conducive to the construction of a B. pertussis vaccine. These epitopes, alongside linkers, his-tag and adjuvants, were amalgamated to form the vaccine candidate. Subsequently, a comprehensive evaluation of the vaccine was conducted, encompassing various computational tests such as secondary and tertiary structure analysis, physicochemical examination, and structural analysis involving docking and molecular dynamics simulations. Importantly, our vaccine successfully passed all in silico tests.Communicated by Ramaswamy H. Sarma.

Conserved Domains in Variable Surface Lipoproteins A-G of Mycoplasma hyorhinis May Serve as Probable Multi-Epitope Candidate Vaccine: Computational Reverse Vaccinology Approach

Mycoplasma hyorhinis (M. hyorhinis) is responsible for infections in the swine population. Such infections are usually cured by using antimicrobials and lead to develop resistance. Until now, there has been no effective vaccine to eradicate the disease. This study used conserved domains found in seven members of the variable lipoprotein (VlpA-G) family in order to design a multi-epitope candidate vaccine (MEV) against M. hyorhinis. The immunoinformatics approach was followed to predict epitopes, and a vaccine construct consisting of an adjuvant, two B cell epitopes, two HTL epitopes, and one CTL epitope was designed. The suitability of the vaccine construct was identified by its non-allergen, non-toxic, and antigenic nature. A molecular dynamic simulation was executed to assess the stability of the TLR2 docked structure. An immune simulation showed a high immune response toward the antigen. The protein sequence was reverse-translated, and codons were optimized to gain a high expression level in E. coli. The proposed vaccine construct may be a candidate for a multi-epitope vaccine. Experimental validation is required in future to test the safety and efficacy of the hypothetical candidate vaccine.

Identification of a linear B-cell epitope on the African swine fever virus CD2v protein

African swine fever virus (ASFV) poses a serious threat to domestic pigs and wild boars, which is responsible for substantial production and economic losses. A dominant ASFV specific linear B cell epitope that reacted with the convalescent serum was explored and identified with the help of immune informatics techniques. It is essential in understanding the host immunity and in developing diagnostic technical guidelines and vaccine design. The confirmation of dominant epitopes with a positive serological matrix is feasible. To improve the immunogenicity of the epitope, we designed the dominant epitope of CD2v in the form of 2 branch Multiple-Antigen peptide (MAPs-2), CD2v-MAPs-2. Notably, CD2v peptide can be taken up by dendritic cells (DCs) to activate T lymphocytes and induce highly effective valence antibodies in BALB/c mice. The specific CD8+ T cell response were observed. The dominant epitope peptide identified in this study was able to effectively activate humoral and cellular immunity in mice model.

In silico prediction and expression analysis of vaccine candidate genes of Campylobacter jejuni

Campylobacter jejuni (C. jejuni) is the most common food-borne pathogen that causes human gastroenteritis in the United States. Consumption of contaminated poultry products is considered as the major source of human Campylobacter infection. An effective vaccine would be a promising alternative to antibiotic supplements to curb C. jejuni colonization in poultry gastrointestinal (GI) tract. However, the genetic diversity among the C. jejuni isolates makes vaccine production more challenging. Despite many attempts, an effective Campylobacter vaccine is not yet available. This study aimed to identify suitable candidates to develop a subunit vaccine against C. jejuni, which could reduce colonization in the GI tract of the poultry. In the current study, 4 C. jejuni strains were isolated from retail chicken meat and poultry litter samples and their genomes were sequenced utilizing next-generation sequencing technology. The genomic sequences of C. jejuni strains were screened to identify potential antigens utilizing the reverse vaccinology approach. In silico genome analysis predicted 3 conserved potential vaccine candidates (phospholipase A [PldA], TonB dependent vitamin B12 transporter [BtuB], and cytolethal distending toxin subunit B [CdtB]) suitable for the development of a vaccine. Furthermore, the expression of predicted genes during host-pathogen interaction was analyzed by an infection study using an avian macrophage-like immortalized cell line (HD11). The HD11 was infected with C. jejuni strains, and the RT-qPCR assay was performed to determine the expression of the predicted genes. The expression difference was analyzed using ΔΔCt methods. The results indicate that all 3 predicted genes, PldA, BtuB, and CdtB, were upregulated in 4 tested C. jejuni strains irrespective of their sources of isolation. In conclusion, in silico prediction and gene expression analysis during host-pathogen interactions identified 3 potential vaccine candidates for C. jejuni.

A Vaccine Construction against COVID-19-Associated Mucormycosis Contrived with Immunoinformatics-Based Scavenging of Potential Mucoralean Epitopes

Mucormycosis is a group of infections, caused by multiple fungal species, which affect many human organs and is lethal in immunocompromised patients. During the COVID-19 pandemic, the current wave of mucormycosis is a challenge to medical professionals as its effects are multiplied because of the severity of COVID-19 infection. The variant of concern, Omicron, has been linked to fatal mucormycosis infections in the US and Asia. Consequently, current postdiagnostic treatments of mucormycosis have been rendered unsatisfactory. In this hour of need, a preinfection cure is needed that may prevent lethal infections in immunocompromised individuals. This study proposes a potential vaccine construct targeting mucor and rhizopus species responsible for mucormycosis infections, providing immunoprotection to immunocompromised patients. The vaccine construct, with an antigenicity score of 0.75 covering, on average, 92-98% of the world population, was designed using an immunoinformatics approach. Molecular interactions with major histocompatibility complex-1 (MHC-I), Toll-like receptors-2 (TLR2), and glucose-regulated protein 78 (GRP78), with scores of -896.0, -948.4, and -925.0, respectively, demonstrated its potential to bind with the human immune receptors. It elicited a strong predicted innate and adaptive immune response in the form of helper T (Th) cells, cytotoxic T (TC) cells, B cells, natural killer (NK) cells, and macrophages. The vaccine cloned in the pBR322 vector showed positive amplification, further solidifying its stability and potential. The proposed construct holds a promising approach as the first step towards an antimucormycosis vaccine and may contribute to minimizing postdiagnostic burdens and failures.

Designing of a Recombinant Multi-Epitopes Based Vaccine against Enterococcus mundtii Using Bioinformatics and Immunoinformatics Approaches

Enterococcus species are an emerging group of bacterial pathogens that have a significant role in hospital-associated infections and are associated with higher mortality and morbidity rates. Among these pathogens, Enterococcus mundtii is one of the causative agents of multiple hospital associated infections. Currently, no commercially available licensed vaccine is present, and multi-drug resistant strains of the pathogen are prominent. Due to several limitations of experimental vaccinology, computational vaccine designing proved to be helpful in vaccine designing against several bacterial pathogens. Herein, we designed a multi-epitope-based vaccine against E. mundtii using in silico approaches. After an in-depth analysis of the core genome, three probable antigenic proteins (lytic polysaccharide monooxygenase, siderophore ABC transporter substrate-binding protein, and lytic polysaccharide monooxygenase) were shortlisted for epitope prediction. Among predicted epitopes, ten epitopes-GPADGRIAS, TTINHGGAQA, SERTALSVTT, GDGGNGGGEV, GIKEPDLEK, KQADDRIEA, QAIGGDTSN, EPLDEQTASR, AQWEPQSIEA, QPLKFSDFEL-were selected for multi-epitope vaccine construct designing. The screened B- and T-cell epitopes were joined with each other via specific linkers and linked to the cholera toxin B subunit as an adjuvant to enhance vaccine immune protection efficacy. The designed vaccine construct induced cellular and humoral immune responses. Blind docking with immune cell receptors, followed by molecular dynamic simulation results confirms the good binding potency and stability of the vaccine in providing protection against the pathogen.

Designing a Recombinant Vaccine against Providencia rettgeri Using Immunoinformatics Approach

Antibiotic resistance (AR) is the resistance mechanism pattern in bacteria that evolves over some time, thus protecting the bacteria against antibiotics. AR is due to bacterial evolution to make itself fit to changing environmental conditions in a quest for survival of the fittest. AR has emerged due to the misuse and overuse of antimicrobial drugs, and few antibiotics are now left to deal with these superbug infections. To combat AR, vaccination is an effective method, used either therapeutically or prophylactically. In the current study, an in silico approach was applied for the design of multi-epitope-based vaccines against Providencia rettgeri, a major cause of traveler's diarrhea. A total of six proteins: fimbrial protein, flagellar hook protein (FlgE), flagellar basal body L-ring protein (FlgH), flagellar hook-basal body complex protein (FliE), flagellar basal body P-ring formation protein (FlgA), and Gram-negative pili assembly chaperone domain proteins, were considered as vaccine targets and were utilized for B- and T-cell epitope prediction. The predicted epitopes were assessed for allergenicity, antigenicity, virulence, toxicity, and solubility. Moreover, filtered epitopes were utilized in multi-epitope vaccine construction. The predicted epitopes were joined with each other through specific GPGPG linkers and were joined with cholera toxin B subunit adjuvant via another EAAAK linker in order to enhance the efficacy of the designed vaccine. Docking studies of the designed vaccine construct were performed with MHC-I (PDB ID: 1I1Y), MHC-II (1KG0), and TLR-4 (4G8A). Findings of the docking study were validated through molecular dynamic simulations, which confirmed that the designed vaccine showed strong interactions with the immune receptors, and that the epitopes were exposed to the host immune system for proper recognition and processing. Additionally, binding free energies were estimated, which highlighted both electrostatic energy and van der Waals forces to make the complexes stable. Briefly, findings of the current study are promising and may help experimental vaccinologists to formulate a novel multi-epitope vaccine against P. rettgeri.

Chikungunya Virus Vaccine Development: Through Computational Proteome Exploration for Finding of HLA and cTAP Binding Novel Epitopes as Vaccine Candidates

Chikungunya virus is a major arbovirus of great public health concern in the whole world, but no vaccine is yet available, still advance therapeutic treatment and effective vaccines are in progress. The present multistep screening and structural binding analysis with CHIKV proteome exploration can be crucial in the development phase of CHIKV epitope based vaccine. The approach employed in two phases (i) Sequence based screening of peptides through propred and IEDB Server (ii) Structure based study through autodocking and NAMD VMD simulation analysis. Among all 29 extracted peptides, only two peptides ²LLANTTFPC¹⁰ of protein E3 and ⁹⁸VNSVAIPLL¹⁰⁶ of protein nsP3 were observed most prominent over all consider parameters such as peptide conserve nature, supertype population coverage, TAP binding, docking and simulation study. During docking interaction study, the best peptide and allele docked complexes such as ²LLANTTFPC¹⁰–B*0702 allele and ⁹⁸VNSVAIPLL¹⁰⁶–A*0301 allele exhibited best binding energy of − 3.13 kcal/mol and − 3.19 kcal/mol, respectively, with stable bonding patterns and their motion during NAMD simulation which confirm conserve peptide and allele stable interaction. The current study also exhibited the good docking interaction of both peptides ²LLANTTFPC¹⁰ and ⁹⁸VNSVAIPLL¹⁰⁶ with c TAP1 protein (1jj7 -PDB ID) cavity which confirm as a channel passageway to peptide transport through the cytoplasm to lumen of ER during antigen processing and presentation. Overall, this multistep screening and crosscheck structural binding analysis with an exploration of the complete proteome of CHIKV can be a novel step in the development of CHIKV epitope based vaccine as well as diagnostic development with aspect of time, cost and side effects.

Application of Reverse Vaccinology and Immunoinformatic Strategies for the Identification of Vaccine Candidates Against Shigella flexneri

Reverse vaccinology (RV) was first introduced by Rappuoli for the development of an effective vaccine against serogroup B Neisseria meningitidis (MenB). With the advances in next generation sequencing technologies, the amount of genomic data has risen exponentially. Since then, the RV approach has widely been used to discover potential vaccine protein targets by screening whole genome sequences of pathogens using a combination of sophisticated computational algorithms and bioinformatic tools. In contrast to conventional vaccine development strategies, RV offers a novel method to facilitate rapid vaccine design and reduces reliance on the traditional, relatively tedious, and labor-intensive approach based on Pasteur"s principles of isolating, inactivating, and injecting the causative agent of an infectious disease. Advances in biocomputational techniques have remarkably increased the significance for the rapid identification of the proteins that are secreted or expressed on the surface of pathogens. Immunogenic proteins which are able to induce the immune response in the hosts can be predicted based on the immune epitopes present within the protein sequence. To date, RV has successfully been applied to develop vaccines against a variety of infectious pathogens. In this chapter, we apply a pipeline of bioinformatic programs for identification of Shigella flexneri potential vaccine candidates as an illustration immunoinformatic tools available for RV.

A reverse vaccinology and immunoinformatics approach for designing a multiepitope vaccine against SARS-CoV-2

Since 2019, the world was involved with SARS-CoV-2 and consequently, with the announcement by the World Health Organization that COVID-19 was a pandemic, scientific were an effort to obtain the best approach to combat this global dilemma. The best way to prevent the pandemic from spreading further is to use a vaccine against COVID-19. Here, we report the design of a recombinant multi-epitope vaccine against the four proteins spike or crown (S), membrane (M), nucleocapsid (N), and envelope (E) of SARS-CoV-2 using immunoinformatics tools. We evaluated the most antigenic epitopes that bind to HLA class 1 subtypes, along with HLA class 2, as well as B cell epitopes. Beta-defensin 3 and PADRE sequence were used as adjuvants in the structure of the vaccine. KK, GPGPG, and AAY linkers were used to fuse the selected epitopes. The nucleotide sequence was cloned into pET26b(+) vector using restriction enzymes XhoI and NdeI, and HisTag sequence was considered in the C-terminal of the construct. The results showed that the proposed candidate vaccine is a 70.87 kDa protein with high antigenicity and immunogenicity as well as non-allergenic and non-toxic. A total of 95% of the selected epitopes have conservancy with similar sequences. Molecular docking showed a strong binding between the vaccine structure and tool-like receptor (TLR) 7/8. The docking, molecular dynamics, and MM/PBSA analysis showed that the vaccine established a stable interaction with both structures of TLR7 and TLR8. Simulation of immune stimulation by this vaccine showed that it evokes immune responses related to humoral and cellular immunity.

Designing multiepitope-based vaccine against Eimeria from immune mapped protein 1 (IMP-1) antigen using immunoinformatic approach

Drug resistance against coccidiosis has posed a significant threat to chicken welfare and productivity worldwide, putting daunting pressure on the poultry industry to reduce the use of chemoprophylactic drugs and live vaccines in poultry to treat intestinal diseases. Chicken coccidiosis, caused by an apicomplexan parasite of Eimeria spp., is a significant challenge worldwide. Due to the experience of economic loss in production and prevention of the disease, development of cost-effective vaccines or drugs that can stimulate defence against multiple Eimeria species is imperative to control coccidiosis. This study explored Eimeria immune mapped protein-1 (IMP-1) to develop a multiepitope-based vaccine against coccidiosis by identifying antigenic T-cell and B-cell epitope candidates through immunoinformatic techniques. This resulted in the design of 7 CD8⁺, 21 CD4⁺ T-cell epitopes and 6 B-cell epitopes, connected using AAY, GPGPG and KK linkers to form a vaccine construct. A Cholera Toxin B (CTB) adjuvant was attached to the N-terminal of the multiepitope construct to improve the immunogenicity of the vaccine. The designed vaccine was assessed for immunogenicity (8.59968), allergenicity and physiochemical parameters, which revealed the construct molecular weight of 73.25 kDa, theoretical pI of 8.23 and instability index of 33.40. Molecular docking simulation of vaccine with TLR-5 with binding affinity of - 151.893 kcal/mol revealed good structural interaction and stability of protein structure of vaccine construct. The designed vaccine predicts the induction of immunity and boosted host's immune system through production of antibodies and cytokines, vital in hindering surface entry of parasites into host. This is a very important step in vaccine development though further experimental study is still required to validate these results.

Pan-vaccinomics approach towards a universal vaccine candidate against WHO priority pathogens to address growing global antibiotic resistance

Antimicrobial resistance (AMR) in bacterial pathogens is a major global distress. Due to the slow progress of antibiotics development and the fast pace of resistance acquisition, there is an urgent need for effective vaccines against such bacterial pathogens. In-silico approaches including pan-genomics, subtractive proteomics, reverse vaccinology, immunoinformatics, molecular docking, and dynamics simulation studies were applied in the current study to identify a universal potential vaccine candidate against the 18 multi-drug resistance (MDRs) bacterial pathogenic species from a WHO priority list. Ten non-redundant, non-homologous, virulent, and antigenic vaccine candidates were filtered against all targeted species. Nine B-cell-derived T-cell antigen epitopes which show a great affinity to the dominant HLA allele (DRB1*0101) in the human population were screened from selected vaccine candidates using immunoinformatics approaches. Screened epitopes were then used to design a multi-epitope peptide vaccine construct (MEPVC) along with β-defensin adjuvant to improve the immunogenic properties of the proposed vaccine construct. Molecular docking and MD simulation were carried out to study the binding affinity and molecular interaction of MEPVC with human immune receptors (TLR2, TLR3, TLR4, and TLR6). The final MEPVC construct was reverse translated and in-silico cloned in the pET28a(+) vector to ensure its effectiveness. This in silico construct is expected to be helpful for vaccinologists to assess its immune protection effectiveness in vivo and in vitro to counter rising antibiotic resistance worldwide.

Top Down Computational Approach: A Vaccine Development Step to Find Novel Superantigenic HLA Binding Epitopes from Dengue Virus Proteome

Dengue virus (DENV) is a major mosquito vector based human pathogenic flavivirus which is causing major threat worldwide, yet the availability of therapeutic treatment and several vaccines, still called for advance treatment and vaccine development. The present top down computational approach is a vaccine development step to find novel super antigenic HLA binding epitopes from DENV proteome. The approach used sequence based screening to find complete conserve and high population coverage, common epitopes among all DENV serotype. Propred and Immune Epitope Data Base were used for sequence based screening with recommended parameters. Among top 29 identified epitopes, five structural protein epitopes viz. ³³LQGRGPLKL⁴¹, ²⁴⁹VVVLGSQEG²⁵⁷, ¹⁷²LVGIVTLYL¹⁸⁰, ¹⁴⁶MKILIGVVI¹⁵⁴, ⁷²YIIVGVEPG⁸⁰ and one nonstructural protein epitope ¹⁸LKNDIPMTG²⁶ were showed high conserve nature and high population coverage from complete DENV proteome. Further structure based study involving docking and molecular dynamic simulation to confirm stable behavior of HLA allele–peptide complex to give potent cell mediated immune response. Docking of epitope ⁷²YIIVGVEPG⁸⁰–DRB1 0401 allele and epitope ³³LQGRGPLKL⁴¹–B*5101 allele complexes showed the best binding energy of − 7.71 and − 7.20 kcal/mol, respectively and stable binding pattern over the time window during molecular dynamic simulation. This computational approach resulted novel epitopes which can be used in the design and development of short epitope based vaccines as well as diagnosis tools for dengue infection.

Cellulolytic bacterium characterization and genome functional analysis: An attempt to lay the foundation for waste management

Lignocellulosic waste has offered a cost-effective and food security-wise substrate for the generation of biofuels and value-added products. Here, whole-genome sequencing and comparative genomic analyses were performed for Serratia sp. AXJ-M. The results showed that strain AXJ-M contained a high proportion of strain-specific genes related to carbohydrate metabolism. Furthermore, the genetic basis of strain AXJ-M for efficient degradation of cellulose was identified. Cellulase activity tests revealed strong cellulose degradation ability and cellulase activities in strain AXJ-M. mRNA expression indicated that GH1, GH3 and GH8 might determine the strain's cellulose degradation ability. The SWISS-MODEL and Ramachandran Plot were used to predict and evaluate the 3D structure, respectively. High performance liquid chromatography (HPLC) and gas chromatography-mass spectrometer (GC-MS) were used to analyze the cellulose degradation products. Further research is needed to elucidate the cellulose degradation mechanism and to develop industrial applications for lignocellulosic biomass degradation and waste management.

Design of a Multi-epitope Vaccine Against Acinetobacter baumannii Using Immunoinformatics Approach

Acinetobacter baumannii is one of the most successful pathogens causing nosocomial infections and has significantly multidrug-resistant. So far, there are no certain treatments to protect against infection with A. baumannii, therefore an effective A. baumannii vaccine needed. The purpose of this study was to predict antigenic epitopes of CarO protein for designing the A. baumannii vaccine using immunoinformatics analysis. CarO protein is one of the most important factors in the resistance against the antibiotic Carbapenem. In this study, T and B-cell epitopes of CarO protein were predicted and screened based on the antigenicity, toxicity, allergenicity features. The epitopes were linked by suitable linkers. Four different adjuvants were attached to the vaccine constructs which among them, vaccine construct 3 was chosen to predict the secondary and the 3D structure of the vaccine. The refinement process was performed to improve the quality of the 3D model structure; the validation process is performed using the Ramachandran plot and ProSA z-score. The designed vaccine's binding affinity to six various HLA molecules and TLR 2 and TLR4 were evaluated by molecular docking. Finally, in silico gene cloning was performed in the pET28a (+) vector. The findings suggest that the vaccine may be a promising vaccine to prevent A. baumannii infection.

In silico analysis of epitope-based CadF vaccine design against Campylobacter jejuni

Objective

Vaccination is an important strategy for the eradication of infectious diseases. CadF protein of Campylobacter jejuni is one of the important factors in the pathogenesis of this bacterium. The purpose of this work was to perform a bioinformatics study to identify an epitope-based CadF vaccine, as a subunit vaccine. Full protein sequences of CadF were extracted from the NCBI and UniProt databases and subjected to in silico evaluations, including sequence analysis, allergenicity, antigenicity, epitope conservancy, and molecular docking assessments done by different servers.

Results

The results showed that CadF was a highly conserved protein belonging to the outer member proteins superfamily. Among the evaluated epitopes, LSDSLALRL was identified as an antigenic and non-allergenic peptide with a suitable structure for vaccine development. It was also able to stimulate both T and B cells. This 9-mer peptide was located in 136–144 segment of CadF protein and interacted with both HLA-A 0101 and HLA-DRB1 0101 alleles. Overall, the obtained theoretical results showed that CadF protein could be used for designing and evaluating a new effective vaccine against C. jejuni.