Computer aided selection of candidate vaccine antigens

Immunoinformatics is an emergent branch of informatics science that long ago pullulated from the tree of knowledge that is bioinformatics. It is a discipline which applies informatic techniques to problems of the immune system. To a great extent, immunoinformatics is typified by epitope prediction methods. It has found disappointingly limited use in the design and discovery of new vaccines, which is an area where proper computational support is generally lacking. Most extant vaccines are not based around isolated epitopes but rather correspond to chemically-treated or attenuated whole pathogens or correspond to individual proteins extract from whole pathogens or correspond to complex carbohydrate. In this chapter we attempt to review what progress there has been in an as-yet-underexplored area of immunoinformatics: the computational discovery of whole protein antigens. The effective development of antigen prediction methods would significantly reduce the laboratory resource required to identify pathogenic proteins as candidate subunit vaccines. We begin our review by placing antigen prediction firmly into context, exploring the role of reverse vaccinology in the design and discovery of vaccines. We also highlight several competing yet ultimately complementary methodological approaches: sub-cellular location prediction, identifying antigens using sequence similarity, and the use of sophisticated statistical approaches for predicting the probability of antigen characteristics. We end by exploring how a systems immunomics approach to the prediction of immunogenicity would prove helpful in the prediction of antigens.

Vaccine adjuvant systems: enhancing the efficacy of sub-unit protein antigens

Vaccination remains a key tool in the protection and eradication of diseases. However, the development of new safe and effective vaccines is not easy. Various live organism based vaccines currently licensed, exhibit high efficacy; however, this benefit is associated with risk, due to the adverse reactions found with these vaccines. Therefore, in the development of vaccines, the associated risk-benefit issues need to be addressed. Sub-unit proteins offer a much safer alternative; however, their efficacy is low. The use of adjuvanted systems have proven to enhance the immunogenicity of these sub-unit vaccines through protection (i.e. preventing degradation of the antigen in vivo) and enhanced targeting of these antigens to professional antigen-presenting cells. Understanding of the immunological implications of the related disease will enable validation for the design and development of potential adjuvant systems. Novel adjuvant research involves the combination of both pharmaceutical analysis accompanied by detailed immunological investigations, whereby, pharmaceutically designed adjuvants are driven by an increased understanding of mechanisms of adjuvant activity, largely facilitated by description of highly specific innate immune recognition of components usually associated with the presence of invading bacteria or virus. The majority of pharmaceutical based adjuvants currently being investigated are particulate based delivery systems, such as liposome formulations. As an adjuvant, liposomes have been shown to enhance immunity against the associated disease particularly when a cationic lipid is used within the formulation. In addition, the inclusion of components such as immunomodulators, further enhance immunity. Within this review, the use and application of effective adjuvants is investigated, with particular emphasis on liposomal-based systems. The mechanisms of adjuvant activity, analysis of complex immunological characteristics and formulation and delivery of these vaccines are considered.

The SEF14 fimbrial antigen of Salmonella enterica serovar Enteritidis is encoded within a pathogenicity islet

The DNA sequence of the chromosomal gene cluster encoding the SEF14 fimbriae of Salmonella enterica serovar Enteritidis was determined. Five contiguous open reading frames, sefABCDE, were identified. The sefE gene shared significant homology with araC-like positive regulators. Serovar-associated virulence plasmid (SAP) genes orf7,8,9 and pefI were identified immediately adjacent to the sef operon. The pefI gene encoded a putative regulator of the Plasmid-encoded fimbrial antigen (PEF) expression. The entire sef--pef region, flanked by two IS-like elements, was inserted adjacent to leuX that encoded a transfer RNA molecule. The organisation of this region was suggestive of a classic pathogenicity islet. Southern hybridisation confirmed two copies of the SAP derived orf7,8,9 and pefI region in S. Enteritidis, one in the chromosome and one on the SAP. Of other group D Salmonella, only S. Blegdam and S. Moscow harboured both chromosomal and plasmid copies of pefI--orf9 region although polymorphism was evident.

Induction of inflammatory cytokines and nitric oxide in J774.2 cells and murine macrophages by lipoteichoic acid and related cell wall antigens from Staphylococcus epidermidis

Staphylococcus epidermidis causes infections associated with medical devices including central venous catheters, orthopaedic prosthetic joints and artificial heart valves. This coagulase-negative Staphylococcus produces a conventional cellular lipoteichoic acid (LTA) and also releases a short-glycerophosphate-chain-length form of LTA (previously termed lipid S) into the medium during growth. The relative pro-inflammatory activities of cellular and short-chain-length exocellular LTA were investigated in comparison with peptidoglycan and wall teichoic acid from S. epidermidis and LPS from Escherichia coli O111. The ability of these components to stimulate the production of proinflammatory cytokines [interleukin (IL)-1β, IL-6 and tumour necrosis factor (TNF)-α] and nitric oxide was investigated in a murine macrophage-like cell line (J774.2), and in peritoneal and splenic macrophages. On a weight-for-weight basis the short-chain-length exocellular LTA was the most active of the S. epidermidis products, stimulating significant amounts of each of the inflammatory cytokines and nitric oxide, although it was approximately 100-fold less active than LPS from E. coli. By comparison the full-chain-length cellular LTA and peptidoglycan were less active and the wall teichoic acid had no activity. As an exocellular product potentially released from S. epidermidis biofilms, the short-chain-length exocellular LTA may act as the prime mediator of the host inflammatory response to device-related infection by this organism and act as the Gram-positive equivalent of LPS in Gram-negative sepsis. The understanding of the role of short-chain-length exocellular LTA in Gram-positive sepsis may lead to improved treatment strategies. © 2005 SGM.

AntigenDB:an immunoinformatics database of pathogen antigens

The continuing threat of infectious disease and future pandemics, coupled to the continuous increase of drug-resistant pathogens, makes the discovery of new and better vaccines imperative. For effective vaccine development, antigen discovery and validation is a prerequisite. The compilation of information concerning pathogens, virulence factors and antigenic epitopes has resulted in many useful databases. However, most such immunological databases focus almost exclusively on antigens where epitopes are known and ignore those for which epitope information was unavailable. We have compiled more than 500 antigens into the AntigenDB database, making use of the literature and other immunological resources. These antigens come from 44 important pathogenic species. In AntigenDB, a database entry contains information regarding the sequence, structure, origin, etc. of an antigen with additional information such as B and T-cell epitopes, MHC binding, function, gene-expression and post translational modifications, where available. AntigenDB also provides links to major internal and external databases. We shall update AntigenDB on a rolling basis, regularly adding antigens from other organisms and extra data analysis tools. AntigenDB is available freely at http://www.imtech.res.in/raghava/antigendb and its mirror site http://www.bic.uams.edu/raghava/antigendb.