Immunomics

Abstract: It can be argued that the arrival of the "genomics era" has significantly shifted the paradigm of vaccine and therapeutics development from microbiological to sequence-based approaches. Genome sequences provide a previously unattainable route to investigate the mechanisms that underpin pathogenesis. Genomics, transcriptomics, metabolomics, structural genomics, proteomics, and immunomics are being exploited to perfect the identification of targets, to design new vaccines and drugs, and to predict their effects in patients. Furthermore, human genomics and related studies are providing insights into aspects of host biology that are important in infectious disease. This ever-growing body of genomic data and new genome-based approaches will play a critical role in the future to enable timely development of vaccines and therapeutics to control emerging infectious diseases.

Abstract: 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.