Identification Of Potential Vaccine Candidates Research Articles

Insights into structural vaccinology harnessed for universal coronavirus vaccine development.

Structural vaccinology is pivotal in expediting vaccine design through high-throughput screening of immunogenic antigens. Leveraging the structural and functional characteristics of antigens and immune cell receptors, this approach employs protein structural comparison to identify conserved patterns in key pathogenic components. Molecular modeling techniques, including homology modeling and molecular docking, analyze specific three-dimensional (3D) structures and protein interactions and offer valuable insights into the 3D interactions and binding affinity between vaccine candidates and target proteins. In this review, we delve into the utilization of various immunoinformatics and molecular modeling tools to streamline the development of broad-protective vaccines against coronavirus disease 2019 variants. Structural vaccinology significantly enhances our understanding of molecular interactions between hosts and pathogens. By accelerating the pace of developing effective and targeted vaccines, particularly against the rapidly mutating severe acute respiratory syndrome coronavirus 2 and other prevalent infectious diseases, this approach stands at the forefront of advancing immunization strategies. The combination of computational techniques and structural insights not only facilitates the identification of potential vaccine candidates but also contributes to the rational design of vaccines, fostering a more efficient and targeted approach to combatting infectious diseases.

Immunoinformatics and Reverse Vaccinology Approach for the Identification of Potential Vaccine Candidates against Vandammella animalimors.

Vandammella animalimorsus is a Gram-negative and non-motile bacterium typically transmitted to humans through direct contact with the saliva of infected animals, primarily through biting, scratches, or licks on fractured skin. The absence of a confirmed post-exposure treatment of V. animalimorsus bacterium highlights the imperative for developing an effective vaccine. We intended to determine potential vaccine candidates and paradigm a chimeric vaccine against V. animalimorsus by accessible public data analysis of the strain by utilizing reverse vaccinology. By subtractive genomics, five outer membranes were prioritized as potential vaccine candidates out of 2590 proteins. Based on the instability index and transmembrane helices, a multidrug transporter protein with locus ID A0A2A2AHJ4 was designated as a potential candidate for vaccine construct. Sixteen immunodominant epitopes were retrieved by utilizing the Immune Epitope Database. The epitope encodes the strong binding affinity, nonallergenic properties, non-toxicity, high antigenicity scores, and high solubility revealing the more appropriate vaccine construct. By utilizing appropriate linkers and adjuvants alongside a suitable adjuvant molecule, the epitopes were integrated into a chimeric vaccine to enhance immunogenicity, successfully eliciting both adaptive and innate immune responses. Moreover, the promising physicochemical features, the binding confirmation of the vaccine to the major innate immune receptor TLR-4, and molecular dynamics simulations of the designed vaccine have revealed the promising potential of the selected candidate. The integration of computational methods and omics data has demonstrated significant advantages in discovering novel vaccine targets and mitigating vaccine failure rates during clinical trials in recent years.

Modeling airway persistent infection of Moraxella catarrhalis and nontypeable Haemophilus influenzae by using human in vitro models.

Non-typeable Haemophilus influenzae (NTHi) and Moraxella catarrhalis (Mcat) are two common respiratory tract pathogens often associated with acute exacerbations in Chronic Obstructive Pulmonary Disease (COPD) as well as with otitis media (OM) in children. Although there is evidence that these pathogens can adopt persistence mechanisms such as biofilm formation, the precise means through which they contribute to disease severity and chronicity remains incompletely understood, posing challenges for their effective eradication. The identification of potential vaccine candidates frequently entails the characterization of the host-pathogen interplay in vitro even though this approach is limited by the fact that conventional models do not permit long term bacterial infections. In the present work, by using air-liquid-interface (ALI) human airway in vitro models, we aimed to recreate COPD-related persistent bacterial infections. In particular, we explored an alternative use of the ALI system consisting in the assembly of an inverted epithelium grown on the basal part of a transwell membrane with the aim to enable the functionality of natural defense mechanisms such as mucociliary clearance and cellular extrusion that are usually hampered during conventional ALI infection experiments. The inversion of the epithelium did not affect tissue differentiation and considerably delayed NTHi or Mcat infection progression, allowing one to monitor host-pathogen interactions for up to three weeks. Notably, the use of these models, coupled with confocal and transmission electron microscopy, revealed unique features associated with NTHi and Mcat infection, highlighting persistence strategies including the formation of intracellular bacterial communities (IBCs) and surface-associated biofilm-like structures. Overall, this study demonstrates the possibility to perform long term host-pathogen investigations in vitro with the aim to define persistence mechanisms adopted by respiratory pathogens and individuate potential new vaccine targets.

Generative AI and large language models: A new frontier in reverse vaccinology

Reverse vaccinology is an emerging concept in the field of vaccine development as it facilitates the identification of potential vaccine candidates. Biomedical research has been revolutionized with the recent innovations in Generative Artificial Intelligence (AI) and Large Language Models (LLMs). The intersection of these two technologies is explored in this study. In this study, the impact of Generative AI and LLMs in the field of vaccinology is explored. Through a comprehensive analysis of existing research, prospective use cases, and an experimental case study, this research highlights that LLMs and Generative AI have the potential to enhance the efficiency and accuracy of vaccine candidate identification. This work also discusses the ethical and privacy challenges, such as data consent and potential biases, raised by such applications that require careful consideration. This study paves the way for experts, researchers, and policymakers to further investigate the role and impact of Generative AI and LLM in vaccinology and medicine.

An integrated multi-pronged reverse vaccinology and biophysical approaches for identification of potential vaccine candidates against Nipah virus

Nipah virus, a paramyxovirus linked to Hendra virus that first appeared in Malaysia and is the etiological agent of viral lethal encephalitis, has emerged as a strong threat to the health community in recent decades. Viral infections are seriously affecting global health. Since there are now no efficient therapeutic options, it will take considerable effort to develop appropriate therapeutic management for the Nipah virus. The main purpose of this study was to design a messenger RNA-based multi-epitope vaccine construct against Nipah virus. This purpose was achieved through multiple immunogenic epitopes prediction using Nipah virus antigenic protein using the immune epitope database and analysis resource (IEDB) followed by the vaccine construction and processing. As in multi-epitopes vaccine construction we selected immunogenic potential fragments of viral proteins, therefore in host immune stimulation we observed proper immune responses toward a multi-epitopes vaccine. In this study, the Nipah virus V protein was used to identify immunodominant epitopes utilizing several reverse vaccinology, immunoinformatics and biophysical methods. The potential antigenic predicted epitopes were further analyzed for immunoinformatics analysis and only selected probable antigenic and non-toxic epitopes were used in designing a multi-epitope mRNA based in silico vaccine against the target pathogen. In vaccine designing a total number of 03B cell epitopes, 09 Cytotoxic T lymphocytes (CTLs) and 01 Helper T lymphocytes (HTL) were prioritized as a good vaccine candidate. In the vaccine construction phase, the selected epitopes were linked together using EAAAK, GPGPG, KK, and AAY linkers, and B-defensin (adjuvant), and MITD sequences were also added to the vaccine construct to increase the potency. After vaccine construction, the physiochemical properties of the vaccine construct were evaluated which predicted that the vaccine construct comprises 320 amino acids with 34.29 kDa (kDa) molecular weight. The instability index was 36.55 proving its stability with the aliphatic index of 82.88. Furthermore, 9.0 theoretical pI and −0.317, GRAVY (Grand Average of Hydropathy) values were predicted in physicochemical properties analysis. A solubility check was applied against the vaccine construct depicting that the vaccine construct is soluble with its calculated value of 0.6. Additionally, after prediction the 3D structure was modeled and refined for docking analysis, the refined 3D structure of the vaccine candidate was further checked for binding affinity with immune cell receptors through docking analysis, in the docking analysis we observed that the vaccine construct has a good binding affinity with immune cells receptor and can induce a proper immune response in host cells. As we predicted effective binding of the designed vaccine construct, hence it can further facilitate the development of vaccine formulation against the Nipah virus. Additionally, molecular dynamic simulation was done using the AMBER v20 package for analysis of the dynamic behaviour of the docked complexes and we observed proper binding stability of the vaccine with target receptor. In C-immune simulation, different humoral and cellular antibody titer was observed in response to the vaccine. Overall using bioinformatics, immunoinformatics, and biophysical approaches we observed that this mRNA base epitopes vaccine construct could facilitate the proof of concept for the formation of the experimental base vaccine against the Nipah virus, as the in silico predictions indicated that the vaccine is highly promising in terms of developing protective immunity. However experimental validation is required to disclose the real immune-protective efficacy of the vaccine.

Vaccine Design Against Leptospirosis Using an Immunoinformatic Approach.

Vaccination is the best way to prevent the spread of emerging or reemerging infectious disease. Current research for vaccine development is mainly focused on recombinant-, subunit-, and peptide-based vaccine. At this point, immunoinformatics has been proven as a powerful method for identification of potential vaccine candidates, by analyzing immunodominat B- and T-cell epitopes. This method can reduce the time and cost of experiment to a great extent, by reducing the number of vaccine candidates for experimental testing for their efficacy. This chapter describes the use of immunoinformatics and molecular docking methods to screen potential vaccine candidates by taking Leptospira as a model.

Genotypic and phenotypic characterization of Edwardsiella isolates from different fish species and geographical areas in Asia: Implications for vaccine development.

The genus Edwardsiella is one of the major causes of fish diseases globally. Herein, we examined 37 isolates from ten different fish species from India, South Korea and Taiwan to gain insight into their phenotypic and genotypic properties, of which 30 were characterized as E.tarda with phenotypic homology estimated at 85.71% based on API-20E biochemical tests. Genotyping using 16S rRNA put all isolates together with E.anguillarum, E.hoshinae, E.tarda, E.piscicida and E.ictaluri reference strains in a monophyletic group. In contrast, the gyrB phylogenetic tree clearly separated E.ictaluri, E.tarda and E.hoshinae reference strains from our isolates and put our isolates into two groups with group I being homologous with the E.anguillarum reference strain while group II was homologous with the E.piscicida reference strain. Hence, our findings point to E.piscicida and E.anguillarum as species infecting different fish species in Asia. Homology of the ompW protein suggested that strains with broad protective coverage could be identified as vaccine candidates. This study underscores the importance of combining genotyping with phenotyping for valid species classification. In addition, it accentuates the importance of phylogenetic comparison of bacterial antigens for identification of potential vaccine candidates.

Surface proteome mining for identification of potential vaccine candidates against Campylobacter jejuni: an in silico approach.

Campylobacter jejuni remains a major cause of human gastroenteritis with estimated annual incidence rate of 450 million infections worldwide. C. jejuni is a major burden to public health in both socioeconomically developing and industrialized nations. Virulence determinants involved in C. jejuni pathogenesis are multifactorial in nature and not yet fully understood. Despite the completion of the first C. jejuni genome project in 2000, there are currently no vaccines in the market against this pathogen. Traditional vaccinology approach is an arduous and time extensive task. Omics techniques coupled with sequencing data have engaged researcher's attention to reduce the time and resources applied in the process of vaccine development. Recently, there has been remarkable increase in development of in silico analysis tools for efficiently mining biological information obscured in the genome. In silico approaches have been crucial for combating infectious diseases by accelerating the pace of vaccine development. This study employed a range of bioinformatics approaches for proteome scale identification of peptide vaccine candidates. Whole proteome of C. jejuni was investigated for varied properties like antigenicity, allergenicity, major histocompatibility class (MHC)-peptide interaction, immune cell processivity, HLA distribution, conservancy, and population coverage. Predicted epitopes were further tested for binding in MHC groove using computational docking studies. The predicted epitopes were conserved; covered more than 80% of the world population and were presented by MHC-I supertypes. We conclude by underscoring that the epitopes predicted are believed to expedite the development of successful vaccines to control or prevent C. jejuni infections albeit the results need to be experimentally validated.

Evaluation of the Leptospira interrogans Outer Membrane Protein OmpL37 as a Vaccine Candidate

The identification of potential vaccine candidates against leptospirosis remains a challenge. However, one such candidate is OmpL37, a potentially surface-exposed antigen that has the highest elastin-binding ability described to date, suggesting that it plays an important role in host colonization. In order to evaluate OmpL37’s ability to induce a protective immune response, prime-boost, DNA and subunit vaccine strategies were tested in the hamster model of lethal leptospirosis. The humoral immune response was evaluated using an indirect ELISA test, and the cytokine profile in whole blood was determined by quantitative real-time PCR. Unlike the DNA vaccine, the administration of recombinant OmpL37 induced a strong IgG antibody response. When individually administrated, both formulations stimulated a TNF-α mediated inflammatory response. However, none of the OmpL37 formulations or vaccination strategies induced protective immunity. Further studies are required towards the identification of new vaccine targets against leptospirosis.

Novel Vaccine Candidates against Brucella melitensis Identified through Reverse Vaccinology Approach

Global health therapeutics is a rapidly emerging facet of postgenomics medicine. In this connection, Brucella melitensis is an intracellular bacterium that causes the zoonotic infectious disease, brucellosis. Presently, no licensed vaccines are available for human brucellosis. Here, we report the identification of potential vaccine candidates against B. melitensis using a reverse vaccinology approach. Based on a systematic screening of exoproteome and secretome of B. melitensis 16 M, we identified eight proteins as potential vaccine candidates, including LPS-assembly protein LptD, a polysaccharide export protein, a cell surface protein, heme transporter BhuA, flagellin FliC, 7-alpha-hydroxysteroid dehydrogenase, immunoglobulin-binding protein EIBE, and hemagglutinin. Among these, the roles of BhuA and hemagglutinin in the virulence of Brucella are essential to establish infection. Roles of other proteins in the virulence are yet to be studied. Prediction of protein-protein interactions revealed that these proteins can interact with other proteins involved in virulence, secretion system, metabolism, and transport. From these eight potential vaccine candidates, we predicted three surface exposed novel antigenic epitopes that can induce both B-cell and T-cell immune responses. These peptides can be used for the development of either exclusive peptide vaccines or multi-component vaccines against human brucellosis. Reverse vaccinology is an important strategy for discovery of novel global health therapeutics.

Identification of Potential Vaccine Candidates Against Streptococcus pneumoniae by Reverse Vaccinology Approach

In the past few decades, genome-based approaches have contributed significantly to vaccine development. Our aim was to identify the most conserved and immunogenic antigens of Streptococcus pneumoniae, which can be potential vaccine candidates in the future. BLASTn was done to identify the most conserved antigens. PSORTb 3.0.2 was run to predict the subcellular localization of the proteins. B cell epitope prediction was done for the immunogenicity testing. Finally, BLASTp was done for verifying the extent of similarity to human proteome to exclude the possibility of autoimmunity. Proteins failing to comply with the set parameters were filtered at each step. Based on the above criteria, out of the initial 22 pneumococcal proteins selected for screening, pavB and pullulanase were the most promising candidate proteins.

Identification and characterization of antigens as vaccine candidates against Klebsiella pneumoniae

Nosocomial infections, also called “hospital acquired infections,” occur worldwide and affect both developed and resource-poor countries, thus having a major impact on their health care systems. Klebsiella pneumoniae, which is an opportunistic Gram-negative pathogen, is responsible for causing pneumonia, urinary tract infections and septicemia in immune compromised hosts such as neonates. Unfortunately, there is no vaccine or mAb available for prophylactic or therapeutic use against K. pneumoniae infections. For this reason, we sought for a protein-based subunit vaccine capable of combating K. pneumoniae infections, by applying our ANTIGENome technology for the identification of potential vaccine candidates, focusing on conserved protein antigens present in strains with different serotypes. We identified numerous novel immunogenic proteins using genomic surface display libraries and human serum antibodies from donors exposed to or infected by K. pneumoniae. Vaccine candidate antigens were finally selected based on animal protection in a murine lethal-sepsis model. The protective and highly conserved antigens identified in this study are promising candidates for the development of a protein-based vaccine to prevent infection by K. pneumoniae.

The new multicomponent vaccine against meningococcal serogroup B, 4CMenB: Immunological, functional and structural characterization of the antigens

Neisseria meningitidis is a major cause of endemic cases and epidemics of meningitis and devastating septicemia. Although effective vaccines exist for several serogroups of pathogenic N. meningitidis, conventional vaccinology approaches have failed to provide a universal solution for serogroup B (MenB) which consequently remains an important burden of disease worldwide. The advent of whole-genome sequencing changed the approach to vaccine development, enabling the identification of potential vaccine candidates starting directly with the genomic information, with a process named reverse vaccinology. The application of reverse vaccinology to MenB allowed the identification of new protein antigens able to induce bactericidal antibodies. Three highly immunogenic antigens (fHbp, NadA and NHBA) were combined with outer membrane vesicles and formulated for human use in a multicomponent vaccine, named 4CMenB. This is the first MenB vaccine based on recombinant proteins able to elicit a robust bactericidal immune response in adults, adolescents and infants against a broad range of serogroup B isolates. This review describes the successful story of the development of the 4CMenB vaccine, with particular emphasis on the functional, immunological and structural characterization of the protein antigens included in the vaccine.

A Reverse Vaccinology Approach for the Identification of Potential Vaccine Candidates from Leishmania spp

Leishmaniasis is a group of diseases with a spectrum of clinical manifestations ranging from cutaneous ulcers to visceral leishmaniasis, which results from the bite of an infected sandfly to human. Attempts to develop an effective vaccine have been shown to be feasible but no vaccine is in active clinical use. This study adopts a Reverse Vaccinology approach to identify common vaccine candidates from both highly pathogenic species Leishmania major and Leishmania infantum. Total proteome of both species were compared to identify common proteins, which are further taken for sub-cellular localization and transmembrane helices prediction. Plasma membrane proteins having only one transmembrane helix were first identified and analyzed which are non-homologous in human and mouse in order to avoid molecular mimicry with other proteins. Selected proteins were analyzed for their binding efficiency to both major histocompatibility complex (MHC) class I and class II alleles. As a result, 19 potential epitopes are screened in this study using different approaches, which can be further verified through in vivo experiments in MHC compatible animal models. This study demonstrates that Reverse Vaccinology approach has potential in discovering various immunogenic antigens from in silico analysis of pathogen's genome or proteome instead of culturing the whole organism by conventional methods.

Using Sybil for interactive comparative genomics of microbes on the web

Motivation: Analysis of multiple genomes requires sophisticated tools that provide search, visualization, interactivity and data export. Comparative genomics datasets tend to be large and complex, making development of these tools difficult. In addition to scalability, comparative genomics tools must also provide user-friendly interfaces such that the research scientist can explore complex data with minimal technical expertise.Results: We describe a new version of the Sybil software package and its application to the important human pathogen Streptococcus pneumoniae. This new software provides a feature-rich set of comparative genomics tools for inspection of multiple genome structures, mining of orthologous gene families and identification of potential vaccine candidates.Availability: The S.pneumoniae resource is online at http://strepneumo-sybil.igs.umaryland.edu. The software, database and website are available for download as a portable virtual machine and from http://sourceforge.net/projects/sybil.Contact: driley@som.umaryland.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Vaccination with Brucella abortus Recombinant In Vivo-Induced Antigens Reduces Bacterial Load and Promotes Clearance in a Mouse Model for Infection

Current vaccines used for the prevention of brucellosis are ineffective in inducing protective immunity in animals that are chronically infected with Brucella abortus, such as elk. Using a gene discovery approach, in vivo-induced antigen technology (IVIAT) on B. abortus, we previously identified ten loci that encode products up-regulated during infection in elk and consequently may play a role in virulence. In our present study, five of the loci (D15, 0187, VirJ, Mdh, AfuA) were selected for further characterization and compared with three additional antigens with virulence potential (Hia, PrpA, MltA). All eight genes were PCR-amplified from B. abortus and cloned into E. coli. The recombinant products were then expressed, purified, adjuvanted, and delivered subcutaneously to BALB/c mice. After primary immunization and two boosts, mice were challenged i.p. with 5×104 CFU of B. abortus strain 19. Spleens from challenged animals were harvested and bacterial loads determined by colony count at various time points. While vaccination with four of the eight individual proteins appeared to have some effect on clearance kinetics, mice vaccinated with recombinant Mdh displayed the most significant reduction in bacterial colonization. Furthermore, mice immunized with Mdh maintained higher levels of IFN-γ in spleens compared to other treatment groups. Collectively, our in vivo data gathered from the S19 murine colonization model suggest that vaccination with at least three of the IVIAT antigens conferred an enhanced ability of the host to respond to infection, reinforcing the utility of this methodology for the identification of potential vaccine candidates against brucellosis. Mechanisms for immunity to one protein, Mdh, require further in vitro exploration and evaluation against wild-type B. abortus challenge in mice, as well as other hosts. Additional studies are being undertaken to clarify the role of Mdh and other IVI antigens in B. abortus virulence and induction of protective immunity.

Immunoproteomic analyses of outer membrane proteins ofMannheimia haemolyticaand identification of potential vaccine candidates

Immunoproteomic analyses were used to characterize the outer membrane proteome of Mannheimia haemolytica, formerly Pasteurella haemolytica, serotype 1, and determine potential vaccine candidate proteins. 2-DE of M. haemolytica outer membranes was followed by immunoblot analyses using naïve and convalescent bovine sera. Proteins were identified using MALDI-TOF and LC-MS/MS. Spectral data was used to mine M. haemolytica protein database and 132 immunoreactive proteins were identified. Bioinformatic analysis using PSORTb, SubLoc, LipoP, BOMP, MCMBB, and TMB-Hunt/BBTM to predict subcellular localization of immunoreactive proteins and beta-barrels narrowed the list down to 55 candidates. Functional characterization of 55 proteins predicted 16 (29%) are involved in cell structure, 13 (23.6%) in transport/virulence, ten (18.2%) as unknown, six (10.9%) in general metabolism, four (7.27%) in cell process, two (3.64%) in translation, and one (1.8%) each in DNA replication, regulation, transcription, and virulence. Prediction of beta-barrel formation was between 11 and 31 immunoreactive proteins depending on the bioinformatic tool employed. Some of these proteins have potentials to be developed into stand-alone vaccines or components of vaccines. Of those proteins, several have already been characterized. Finally, although characteristics of many of M. haemolytica immunoreactive proteins identified in this study were obtained from published data and predictions using bioinformatics tools, five proteins previously listed in the published M. haemolytica sequence as unidentified were found to have correlates with functional proteins in other bacterial species.

Mining the Proteome of Haemophilus ducreyi for Identification of Potential Drug Targets

Chancroid is an extremely infectious sexually transmitted disease (STD) caused by the bacterium Haemophilus ducreyi, prevalent in Africa, United States and in some parts of South Asia. Chancroid has been recognized as a cofactor for human immunodeficiency virus (HIV) transmission. So, there is a requirement to develop an efficient drug to combat chancroid, which can also diminish the HIV prevalence in those populations where chancroid is a prime source for HIV infection. The availability of the complete proteome information of H. ducreyi help enabled in silico analysis for identification of potential vaccine candidates and drug targets. Our study revealed 1226 proteins in H. ducreyi to be nonhomologous with human proteome. Screening these proteins using the Database of Essential Genes (DEG) resulted in the identification of 451 essential proteins. Analysis of the identified essential proteins, using the KEGG Automated Annotation Server (KAAS), revealed 40 proteins of H. ducreyi as potential drug targets as they are involved in pathogen specific metabolic pathways. Subcellular localization prediction of these 451 essential proteins revealed that 11 proteins lie on the outer membrane of the pathogen which could be potential vaccine candidates. Functional family prediction for the 50 putative uncharacterized essential proteins of H. ducreyi by SVM-Prot web server revealed that out of 50, 3 proteins as transmembrane proteins, which may be potential drug targets. Identification of potential inhibitors against these targets through virtual screening may consequence in detection of novel lead compounds effective against H. ducreyi to combat chancroid.

Identification of genome-derived vaccine candidates conserved between human and mouse-adapted strains of H. pylori

Computational methods accelerate vaccine development by rapid identification of potential vaccine candidates. We screened the Helicobacter pylori J99 and 26695 genomes for T-cell epitopes using the epitope mapping algorithm EpiMatrix and selected 150 sequences for experimental validation in a pre-clinical mouse model. Because strains of H. pylori that infect humans do not generally infect mice, and the sequence of the mouse-adapted “Sydney” strain (SS1) is not publicly available, we used targeted PCR to confirm that epitopes we computationally predicted from the human H. pylori isolates J99 and 26695 are conserved in SS1. Epitopes conserved in SS1 were further analyzed for binding to MHC in vitro and for antigenicity in infected mice to select candidates for an epitope-based vaccine.

In vitro feeding assays for hard ticks

Prevention of tick bites and transmission of tick-borne pathogens requires the use of molecules that target physiological processes crucial to both tick and pathogen survival. These molecules are best tested in standardized in vitro assays. Because hard ticks require several days to feed to repletion, the development of in vitro feeding assays for these species is challenging. A standard and easily automated feeding assay has been developed for the tick Ixodes ricinus that involves feeding on blood through a membrane that mimics the elasticity of skin. The system can be adapted to feed other hard tick species in vitro. This assay permits, among others, investigations on the role of tick endosymbionts on tick survival, the identification of potential vaccine candidates and drugs, and the application of genomic tools in vitro, including RNA interference experiments.