Practical implications of erythromycin resistance gene diversity on surveillance and monitoring of resistance

Authors: CHOI, JINLYUNG - Iowa State University; RIEKE, ELIZABETH - Iowa State University; Moorman, Thomas; SOUPIR, MICHELLE - Iowa State University; Allen, Heather; SMITH, SCHUYLER - Iowa State University; HOWE, ADINA - Iowa State University

Submitted to: FEMS Microbiology Ecology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/12/2018
Publication Date: 1/15/2018
Publication URL: https://handle.nal.usda.gov/10113/6562439
Citation: Choi, J., Rieke, E.L., Moorman, T.B., Soupir, M.L., Allen, H.K., Smith, S., Howe, A. 2018. Practical implications of erythromycin resistance gene diversity on surveillance and monitoring of resistance. FEMS Microbiology Ecology. 94(4). https://doi.org/10.1093/femsec/fiy006.
DOI: https://doi.org/10.1093/femsec/fiy006

Interpretive Summary: The antibiotic resistance problem is the global dissemination of antibiotic resistance genes into human pathogens, and international efforts are focused on mitigating the antibiotic resistance problem. Central to evaluating the effectiveness of mitigation efforts is the ability to determine whether or not resistance genes of interest are present or absent after a given intervention. Researchers in this area have struggled to determine which resistance genes should be detected and what probes should be used to detect them. Here we conduct a broad analysis of one type of resistance to macrolide antibiotics (erm), comparing all known erm sequences to all known erm probes. The results showed that only 40 percent of the known probes detected the known sequences, suggesting that more probes need to be developed to fully query this resistance gene in environmental reservoirs. In addition, we specifically analyzed this type of resistance gene in manure datasets because manure is one source of resistance gene dissemination in the environment. We found that existing probes detect approximately 80 percent of this type of resistance gene in the manure samples we analyzed. The results are useful to researchers and stakeholders who seek to evaluate the efficacy of mitigation efforts because we suggest erm probes that would be most informative when investigating manure or manure-contaminated environments. Finally, our study is a model for how researchers could approach the problem in an informed way by sequencing and analyzing a few samples, then using that information to determine what probes to use on a larger scale.

Technical Abstract: Use of antibiotics in human and animal medicine has applied selective pressure for the global dissemination of antibiotic-resistant bacteria. Therefore, it is of interest to develop strategies to mitigate the continued amplification and transmission of resistance genes in environmental reservoirs such as farms, hospitals, and watersheds. However, the efficacy of mitigation strategies is difficult to evaluate because it is unclear which resistance genes are important to monitor, and which primers to use to detect those genes. Here we evaluated the diversity of one type of macrolide antibiotic resistance gene (erm) in one type of environment (manure) to determine which primers would be most informative to use in a mitigation study of that environment. We first analyzed all known erm genes and assessed the ability of previously published erm primers to detect the diversity. The results showed that all known erm resistance genes group into 66 clusters, and 25 of these clusters (40 percent) can be targeted with primers found in the literature. These primers can target 74-85 percent of the erm gene diversity in the manures analyzed. In addition, the analysis revealed an erm gene cluster that is abundant in manures but is not readily detected with known primers, suggesting that new primers need to be developed to fully detect the diversity of erm resistance genes in manure environments. We propose that although the use of metagenomics for antibiotic resistance gene analysis is cost-prohibitive, the sequence and analysis of a small number of metagenomes from an environment of interest can be useful to inform thoughtful primer selection for resistance gene detection via PCR or other probe-based technologies.