Picture of wind turbine against blue sky

Open Access research with a real impact...

The Strathprints institutional repository is a digital archive of University of Strathclyde research outputs.

The Energy Systems Research Unit (ESRU) within Strathclyde's Department of Mechanical and Aerospace Engineering is producing Open Access research that can help society deploy and optimise renewable energy systems, such as wind turbine technology.

Explore wind turbine research in Strathprints

Explore all of Strathclyde's Open Access research content

Differential fate of erythromycin and beta-lactam resistance genes from swine lagoon waste under different aquatic conditions

Knapp, Charles W and Zhang, Wen and Sturm, Belinda SM and Graham, David W. (2010) Differential fate of erythromycin and beta-lactam resistance genes from swine lagoon waste under different aquatic conditions. Environmental Pollution, 158 (5). pp. 1506-1512. ISSN 0269-7491

Full text not available in this repository. (Request a copy from the Strathclyde author)

Abstract

The attenuation and fate of erythromycin-resistance-methylase (erm) and extendedspectrum beta-lactamse (bla) genes were quantified over time in aquatic systems by adding 20-L swine waste to 11,300-L outdoor mesocosms that simulated receiving water conditions below intensive agricultural operations. The units were prepared with two different light-exposure scenarios and included artificial substrates to assess gene movement into biofilms. Of eleven genes tested, only erm(B), erm(F), blaSHV and blaTEM were found in sufficient quantity for monitoring. The genes disappeared rapidly from the water column and first-order water-column disappearance coefficients were calculated. However, detected gene levels became elevated in the biofilms within 2 days, but then disappeared overtime. Differences were observed between sunlight and dark treatments and among individual genes, suggesting that ecological and gene-specific factors play roles in the fate of these genes after release into the environment. Ultimately, this information will aid in generating better predictive models for gene fate.