Recently there has been growing local, national, and international concern about the potential impacts of antibiotic use in agriculture. In particular, a better understanding about the effects of farm practices on the spread of antibiotic resistance genes (ARG) is needed. ARG impart the ability of microbes to survive in the presence of antibiotics, and thus can diminish the effectiveness of antibiotics for treating human disease. However, our recent AES-supported research demonstrated promising results, indicating that appropriate management of animal wastes can help to reduce the spread of ARG in the environment. <P>Therefore, the main goal of this proposed research will be to take our findings a step further by determining the response of ARG to treatment in full-scale on-farm lagoons. By investigating a cross-section of animal operations as well as different lagoon management strategies, best management practices for reducing the spread of ARG will be formulated and disseminated to the farming community.<P> This research will be driven by the following three synergistic objectives: <P>Objective 1 is to monitor concentrations of tetracycline, sulfonamide, and macrolide ARG in on-farm animal waste lagoons representing a cross-section of animal operations. <P>Objective 2 is to explore the relationship of temporal ARG concentrations to lagoon operating and water quality characteristics.<P> Objective 3 is to characterize ARG signatures in lagoons to aid source-tracking of ARG in the environment.
Non-Technical Summary: Antibiotic resistance of microbes to pharmaceuticals is a growing concern to human health. The purpose of this project is to explore the potential of animal waste lagoons for reducing antibiotic resistance genes (ARG) prior to land application. <P> Approach: A cross-section of existing full-scale animal waste lagoons, including two organic dairies, two traditional dairies, two beef feedlots, one pork confined animal feeding operation (CAFO), and two poultry farms will be monitored over a two year period. Where possible, sampling will be targeted at the lagoon inlet, outlet, and the middle, including both water column samples and settled solids. This will help provide an idea of the effectiveness of treatment in each lagoon. An inflatable raft will be used to access the samples and a portable probe will be used to measure the dissolved oxygen, pH, and temperature in the field. Samples will be transported to the lab for chemical oxygen demand (COD), nitrate, ammonia, and total phosphorus measurements in order to determine the relationship between these water quality characteristics and ARG. Additionally, the metals present in the samples will be profiled using inductively coupled plasma atomic emission spectroscopy (ICP-AES) using the facilities available at the Colorado State University Soil and Water Testing Laboratory. Based on recent reports in the literature and on our recent work (Pei et al., 2007), the presence of heavy metals is a strong correlate with ARG, perhaps because the metal resistance genes are linked to the ARG. DNA will be extracted from the samples and ARG will be quantified implementing real-time quantitative polymerase chain reaction (Q-PCR) techniques developed by the PIs research group. Six ARG from three different classes will be quantified: tetracycline ARG (tetO and tetW), sulfonamide ARG (sulI and sulII), and macrolide ARG (ereA, and msrA). A Cepheid Smart Cycler and an Applied Biosystems 3100 real-time PCR cyclers are available in the PIs laboratory to facilitate high-throughput analysis of these ARG. Bacterial 16S rRNA genes will also be quantified by Q-PCR in order to provide a reference for normalizing the number of ARG quantified. In parallel work, ARG signatures will be characterized using a capillary electrophoresis single strand conformation polymorphism (CE-SSCP) procedure currently under development in the PIs lab. This will help support larger goals of identifying human versus agricultural sources of ARG in the environment. ARG concentrations with time will be analyzed with respect to lagoon operating conditions. In particular, we will examine the effect of the kind of manure and the estimated lagoon retention time. Correlation analyses will be conducted in order to determine if there is a relationship between the levels of ARG and the concentrations or characteristics of the various water quality characteristics being monitored. This will provide a means to identify: 1.) Which practices are associated with attenuating initially high levels of ARGs and 2.) Which practices are associated with maintaining low levels of ARG. Statistical analyses will be implemented as appropriate in order to make sound judgments in this regard. The final results will be synthesized into practical operating guidelines in terms of best management practices.