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Developing Computational Tools to Identify Critical Control Points for Mitigating the Spread of Antibiotic Resistance in Agro-ecosystems

Pruden, Amy
Virginia Polytechnic Institute and State University
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The overall goals are to 1) develop publicly-accessible computational tools for identifying CCPs that most effectively mitigate dissemination of antibiotic resistance in agro-ecosystems and 2) engage in education and outreach efforts to advance the use of metagenomics and computational modeling to inform policy and decision-making for mitigating the spread of antibiotic resistance in agro-ecosystems.The specific objectives are to:Conduct an integrated meta-analysis of the response of the antibiotic resistome to various agricultural management practices through cross-comparison of multiple data sets;Construct computational models of the antibiotic resistome through candidate CCPs in manure-affected agro-ecosystems;Build a computational system that allows users such as veterinarians and farm managers to predict the potential for management practices to mitigate the spread of antibiotic resistance as a function of local constraints, such as soil and livestock type;Conduct a field-scale experiment to compare observed and predicted resistomes and inform model validation;Develop and implement educational and outreach activities and resources focused on mitigation of agricultural sources of antibiotic resistance for undergraduate and graduate students and disseminate to relevant stakeholders.
Funding Source
Nat'l. Inst. of Food and Agriculture
Project source
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Antimicrobial Resistance
Education and Training
Policy and Planning