The HPA Bioinformatics Unit at the Centre for Infections pursues research activities in the analysis, presentation, storage and dissemination of biological information in the public health arena. We are also actively engaged in the development of technologies to facilitate these functions for Public Health professionals.
A virulence factor can be loosely described as any product produced by a pathogen that either increases its capacity to cause disease or increases the severity of disease. We have several research projects aimed at predicting which genes in pathogen genomes may be responsible for virulence. Our ultimate goal is to be able to determine which organisms are likely to be more pathogenic and to rapidly detect these in patient or environmental samples.
Molecular typing represents a rapid and portable way of distinguishing strains. For some species there are already established schemes, but for many a molecular tying that matches exiting non-molecular techniques in specificity and sensitivity is still not available. We are researching ways of finding genetic loci that demonstrate suitable levels of discrimination between strains and are suitable for exploitation in molecular assays using the most applicable techniques.
One of the major applications of bioinformatics is to understand the relationship of amino acid sequence and three-dimensional structure in proteins. An examination of protein structure allows the investigation of many functional characteristics, particularly during protein-protein and protein-small molecule interactions. Specifc research avenues include selective viral attachment mechanisms and antimicrobial resistance.
More information on structural biology
Preliminary analysis of a subset of VNTR loci with high internal conservation, and hence high predicted polymorphism showed that a high proportion of them are in the coding regions of surface proteins (echoing the observation of that these regions may be selected for their hypermutability). Protein structural in silico work will be carried out to determine the effect of VNTR size polymorphism on protein structure and hence protein function. From these results, hypothesis-driven arguments can be made about the effect of these VNTR polymorphisms on surface-proteins, and hence their effects on the colonisation stage of the organisms life cycle.
One of the major challenges in tracking infectious diseases (eg: HIV, HBV, HCV, etc.) is integrating data obtained from epidemiological, serological, virological/ bacteriological, and sequence analyses with research data such as drug resistance profiles, and then deriving the valuable information from it. We are employing different database systems, programming languages and bioinformatic algorithms to effectively model and organise the diverse data in novel ways, presenting the information in a user friendly manner as online web pages consisting of tables, charts and graphs.
Examples can be found on the Microbial Identification and Typing Databases page.