|Barrett, John - Benny|
Submitted to: American Society for Microbiology General Meeting
Publication Type: Abstract only
Publication Acceptance Date: 2/16/2014
Publication Date: 5/17/2014
Citation: Williams, L.E., Mcclelland, M., Mcarthur, A., Waglechner, N., Nizam, F., Desai, P.T., Weinstock, G., Barrett, J.B., Hiott, L.M., Jackson, C.R., Frye, J.G. 2014. Genetic variation and genomic context of antibiotic resistance genes and mobile genetic elements in Salmonella from animals and food production facilities. American Society for Microbiology General Meeting. May 17-20, 2014. Boston, Massachusetts. Interpretive Summary:
Technical Abstract: Background: From 1998-2008, Salmonella was the most common bacterial cause of foodborne disease outbreaks and antibiotic resistant Salmonella are considered a serious threat when treatment is warranted. Both agricultural and clinical uses of antibiotics contribute to the development of resistant Salmonella. We sequenced and analyzed Salmonella from animals and federally inspected slaughter facilities to investigate the development of antibiotic resistance. Materials: Salmonella isolates (n=195) were chosen from the National Antimicrobial Resistance Monitoring System (NARMS) collection based on antibiotic resistance phenotypes determined by broth micro-dilution. These isolates represent a diverse range of serovars, geographic locations and animal hosts. Draft genomes were assembled from Illumina paired-end data using Velvet and meet standards developed by the Human Microbiome Project. Results: Eighty-nine isolates (46%) are resistant to three or more antibiotics. To determine resistance genotypes, we used the Comprehensive Antibiotic Resistance Database (CARD). Preliminary analysis of a subset of the draft genomes detected multiple antibiotic resistance genes. For example, a serovar Heidelberg isolate resistant to ten antibiotics encodes multidrug efflux pumps, aminoglycoside resistance, tetracycline resistance and a beta-lactamase. Our preliminary analysis informed modifications to CARD, and we are analyzing all draft genomes with the updated database. Because antibiotic resistance genes are frequently located on mobile genetic elements, we also characterized plasmid content. Using an in silico simulation of PCR-based plasmid replicon typing, we identified genes associated with particular plasmid families in 123 isolates (63%). IncI1, IncA/C and the IncFII replicon characteristic of Salmonella virulence plasmids were the most frequently detected. We also used sequence similarity searches to expand our detection of plasmid genes. For example, we identified relaxase genes characteristic of IncX plasmids in 46 isolates. Conclusion: High-throughput genomics enabled analysis of the genetic variation and genomic context of antibiotic resistance genes in 195 Salmonella isolates. By examining plasmid genes, we can assess linkage of resistance and mobility to further clarify how antibiotic resistance is spread by plasmids.