S35 Quantitative risk analysis for resistant E. coli in surface waters caused by antibiotic use in biofuel systems
Wednesday, November 12, 2014: 10:30 AM
Union Square Ballroom, Mezzanine Level
Alya Limayem1, Elizabeth M. Martin2, Robert Donofrio3 and Chao Zhang1, (1)Department of Cell Biology, Microbiology and Molecular Biology, University of South Florida, Tampa, FL, (2)Biological and Agricultural Engineering, University of Arkansas, Fayetteville, AR, (3)Applied Research Center, NSF International, Ann Arbor, MI

Background

Recently, the FDA (2013) detected antibiotic residues in 53% of 60 samples from livestock feed products, dried distillers grains with solubles collected from biofuel distilleries in the U.S. included mainly virginiamycin (33%). Given the upsurge of the antibiotic resistant Escherichia coli bacteria originating from industrial waste and found in the surface waters, a novel statistical method namely, microbial risk assessment (MRA) was performed, to evaluate the probability of infection by resistant E. coli on human populations exposed to recreational waters in close proximity of imprudent antibiotic use in biofuel systems.

Methods

Probability of infection Model

A comparative risk analysis was performed between a typical E. coli pathway and a case scenario aggravated by antibiotic agents from industrial waste by using probability distribution functions based on available experts data related to the U.S. Great Lake E. coli level.

Best fit dose-response model adapted to E. coli contaminants:

Results

1. (a) Typical scenario: 50% to a population of 1% to be infected, (b) Worst case scenario: 50% chance of infection for 20% of the exposed populations (Fig. 1).

2. The sensitivity chart indicates that the variable concentration of E. coli in water surface contributed the most to the dose-response model with 92.1% (typical scenario) and 90.2% (the worst-case scenario) over the volume of water ingested (Fig. 2).

Conclusion

Resistant microbes in surface waters that were generated from a sublethal dose of antibiotic pollutants originating from an uncontrolled industrial waste would increase the probability of infection by 10 fold on exposed human populations.