Proteomic overlap and infectious disease

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Our work is in the area of immuno-informatics: the combination of computer science and immunology. A proteome is the entire set of proteins produced by an organism or cell. Proteomic overlap is the degree to which the proteome of one organism is duplicated in the proteome of another organism. A fundamental principle in mammalian immunity is the distinction between "self" and "non-self" proteins. The immune system must be able to recognize non-self proteins, so that it can mount a defence against a foreign pathogen, while tolerating the presence of (not reacting to) self proteins. Obviously, the level of proteomic overlap between organisms will affect the balance between self and non-self proteins (in the case of infection) and will have immunological implications. Unfortunately, we do not yet fully understand the mechanisms behind self/non-self determination, and the immunological implications of non-self proteins. We intend to contribute to resolution of some of the open problems in this area by investigating proteomic overlap. Specifically, using bioinformatics tools we aim to address such questions as: how much overlap can be expected at random between two proteomes of specific sizes? What is the biological and immunological significance of portions of the Hepatitis C virus proteome which have atypically high or low overlap with the human proteome? What proteins might account for specific kinds of drug resistance in strains of Neisseria bacteria (e.g. bacteria which cause meningitis and gonorrhea)? Some small protein fragments (peptides) are not found in the proteome of any organism, and some of these can cause enhanced immunological response when added to the proteins of a pathogen. Why? Pursuing the answers to some of these questions requires design and implementation of new bioinformatics tools. The results of our work may lead to better in treatments for disease, and in new, cheaper, and more effective vaccines.