Project Number: 5030-31320-004-017-R
Project Type: Reimbursable Cooperative Agreement
Start Date: Jan 1, 2016
End Date: Dec 31, 2019
The objectives of this research are: 1) to develop technology to investigate, characterize, monitor, and quantify the ecology of antibiotic-resistance genes (ARGs) in animals, soil, and water; 2) to validate the technology by modeling the fate and transport of ARG-associated genes in a laboratory soil column ecosystem; 3) to test the technology in a field study of a confined swine feeding operation and its immediate watershed; 4) to design training, education, and outreach so that the technology can be used and adapted by users in the food chain.
The approach of this research is to develop novel technology that will generate quantitative and qualitative data on antibiotic-resistance genes in environmental samples. The advantages of this approach over existing technologies are that it does not require the cultivability of environmental bacteria; hundreds of resistance genes can be detected simultaneously; hundreds of samples can be tested simultaneously; phylogenetic information can be inferred and then associated with a given resistance gene; and the potential for horizontal gene transfer can be measured. Applying this technology to environmental samples (e.g., feces, soil, water, and carcass) will determine points of maximum resistance gene diversity, thereby identifying the most efficacious mitigation points along the food chain. We propose the development of a transformative approach that we are calling DARTE (Diversity of Antibiotic Resistance genes and Transfer Elements) that uses a highly parallel sequencing technology. Approximately 300 primer pairs detecting nearly 200 resistance genes, markers of horizontal gene transfer, and housekeeping genes will be employed simultaneously to generate DNA sequence data on dozens of samples in parallel. Open-access bioinformatic pipelines will be developed to analyze the data for abundance, richness, diversity, and membership, thereby defining the structure and associated functions of the antibiotic-resistance gene community. The high-throughput nature of DARTE will allow for the simultaneous sequencing of multiple samples, enabling comparisons among environments on an unprecedented scale. DARTE will be validated on an in vitro system of soil columns to which manure, antibiotics, and antibiotic-resistant bacteria will be experimentally applied. The power of DARTE will then be tested on environmental samples from a confined swine feeding operation, the adjacent field to which the swine manure is applied biannually, and the nearby watershed to measure the diversity of resistance genes along an agricultural transect. Finally, the DARTE bioinformatics tools will be made freely available and information on DARTE will be disseminated in workshops and lectures, with the goal of reaching the maximum number of antibiotic resistance researchers and stakeholders.