Reservoirs of Antibiotic Resistance--Bioinformatics

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With the emergence of antibiotic resistance threatening our ability to treat pathogenic bacterial infection, successful control of infectious diseases must consider every potential source of resistance. The selective forces antibiotics exert act not only on the treated infection, but also on all organisms with which the drugs come into contact. Numerous mechanisms of cross-species gene transfer suggest that the frequency of resistance genes in commensal organisms may act as a marker or predictor of the emergence of resistance in pathogenic bacteria. Collection of data on resistance gene frequencies in commensal and pathogenic organisms is necessary for the analysis of the relationship between these frequencies, and the subsequent development of a tool for predicting the emergence of antibiotic resistance problems. We therefore propose a 3 step process to address the hypothesis that the frequency of antibiotic resistance genes in commensal organisms can be used to predict the subsequent emergence of antibiotic resistance in pathogenic bacterial populations 1) Implementation of a bioinformatics database to profile resistance genotypes in commensal organisms. 2) Implementation of research projects by Reservoirs of Antibiotic Resistance (ROAR) network participants to fully utilize the collected data in specifically addressing the hypothesis that the frequency of resistance genes in commensal organisms found in the environment can act as a predictor for the emergency of antibiotic resistance in pathogenic bacterial organisms; 3) Development of a mathematical model that will serve as a tool for predicting the emergence of resistance in medically important bacterial species, using analyses of the data gathered in Aim 2 to test and refine the model. These new bioinformatics tools and the research activities that they facilitate will have applications in the management of antibiotic prophylaxis and therapy in human disease, animal husbandry and horticulture and in management of genetically modified organisms. The continued growth of the ROAR network, applied to this question, will thus accelerate the pace of basic and applied research, and better inform the continuing efforts to contain antibiotic resistance.