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Predicting Antibiotic Resistance in the Poultry Production System


<P>The major goals of this project are: 1) To quantify the ability of antibiotic and non-antibiotic factors to select for antibiotic resistance. Specifically, we will a) quantify the fitness costs of maintaining specific antibiotic resistance genes in the presence and absence of antibiotic and non-antibiotic compounds, b) examine the stability of multidrug resistance plasmids in the presence and absence of antibiotic and non-antibiotic compounds, and c) estimate the transmissibility of multidrug resistance plasmids in the presence and absence of antibiotic and non-antibiotic compounds. 2) To develop a dynamic simulation model for predicting the emergence, spread and persistence of antibiotic resistant bacteria. Specifically, we will a) build a mathematical model that simulates the poultry production system, and b) use industry data and antibiotic resistance selection estimates from Aim 1 to predict the fate of resistant bacteria within the poultry production system. </P>

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<P>NON-TECHNICAL SUMMARY: Bacterial resistance to antibiotics continues to pose a serious threat to human and animal health. Attempts to reduce the prevalence of resistance in specific bacterial populations through changes in antibiotic use patterns have had variable success, thus leading us to question whether antibiotic use is the only (or even the predominant) selection pressure maintaining antibiotic resistance. We hypothesize that both antibiotic and non-antibiotic factors contribute to the emergence, persistence and dissemination of antibiotic resistance, but that non-antibiotic factors may be more important in the long-term selection of antibiotic resistance, particularly with respect to multidrug resistant bacteria. The results of this study will provide quantified estimates of antibiotic resistance selection under a variety of conditions and will be used to populate a mathematical model that enables the prediction of antibiotic resistance emergence, spread and persistence as well as the potential efficacy of targeted interventions. </P>
<P>APPROACH: The results from each of the sub-Aims in Aim 1 will be graphed on a log2 scale to determine the relationship between plasmid characteristics and selective agent concentration. We will specifically evaluate whether there is a threshold concentration at which activity occurs, whether the relationship is linear or non-linear, and whether the plasmid characteristics are asymptotic at either the lower or higher concentrations. We will then develop probability distributions for each of the plasmid characteristics for each selective agent that reflect the nature of the selective pressure. Specifically, this distribution will reflect the probability that the agent selects for resistance over its range of concentrations. We will generate these probability distributions using the software @Risk (Palisade Corporation, Ithaca, NY), with which we have considerable experience. These probability distributions will become inputs to the models developed in Aim 2. We do not anticipate any problems with this Aim given that we have already developed the rfp approach and have experience with the assays. The results from Aim 2 are twofold. First, and perhaps most important, we will have a mathematical model with which we can use to evaluate strategies for reducing animal and human health risks associated with poultry production. Specifically, this tool will help us evaluate ways in which the poultry industry can reduce the risks associated with antibiotic resistance. Second, this Aim will help determine the relative importance of different selective pressures that are found within the poultry production system and quantify their impact on resistance emergence, persistence and spread. Given the complexity of the model we are developing, it is possible that STELLA® will not adequately handle the complexity of the system dynamics. If necessary, we will shift the model to the software Analytica, a more complex modeling platform, with which we also have experience. Analytica is not as widely available as STELLA® and is therefore not our first choice. </P>

Johnson, Timothy; Singer, Randall
University of Minnesota
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