Quantification And Characterization Of Antibiotic Resistance Gene Profiles In Freshwater Sediments

Abstract

Antibiotic resistance is a growing public health problem worldwide, one that is threatening our ability to treat infections that were once easy to handle. Therefore, antibiotic resistance genes (ARGs), those genes that confer resistance to microorganisms, are receiving increased attention. While we understand how antibiotic resistant bacteria and their associated resistance genes behave in the face of antibiotics and other selective pressures at small scales, the result of these stresses in large, environmental scales, is less clear. Of particular concern are the antibiotic residues associated with municipal treated wastewater and runoff from agricultural practices, as human medicine and animal agriculture are the two biggest consumers of antibiotics, leading to large quantities of residues in these waste streams and the environments they impact. To observe more complete antibiotic resistance gene profiles, a multiplex, microfluidic qPCR method was developed which was capable of quantifying genes encoding for resistance to most major classes of antibiotics, metal resistance genes, and antibiotic resistance associated genes. This method is able to simultaneously quantify 48 genes, each of which can be quantified over 3-5 orders of magnitude with optimum PCR efficiency, while still allowing for observation of amplification and melt curves in order to check for inhibition and non-specific amplification, respectively. Once this method was successfully developed, antibiotic resistance genes conferring resistance to most major classes of antibiotics, metal resistance genes, and antibiotic resistance genes were quantified in sediment cores collected from 4 lakes in Minnesota and river surface sediments collected along the Minnesota and Mississippi Rivers to provide a detailed antibiotic resistance profile. Results of this work demonstrated that treated municipal wastewater and agricultural runoff do not significantly impact the concentration of antibiotic resistance genes present in river and lake sediments. Heavy metals were quantified in these samples as well, due to the ability of heavy metals to co-select for antibiotic resistance and maintain a reservoir of resistance, even in the absence of antibiotics. These results suggest that heavy metals in sediments play an important role in determining the concentration of antibiotic resistance genes. The results presented here can be used to better understand the behavior of antibiotic resistance genes in response to various selective pressures in the environment.