Antibiotic Resistance Gene Abundances Correlate with Metal and Geochemical Conditions in Archived Scottish Soils

• Published in: PloS one Vol. 6; no. 11; p. e27300
• Main Authors: Knapp, Charles W., McCluskey, Seánín M., Singh, Brajesh K., Campbell, Colin D., Hudson, Gordon, Graham, David W.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 09.11.2011; Public Library of Science (PLoS)
• Subjects: Agriculture; Antibiotic resistance; Antibiotics; Archives & records; Bacteria; Biology; Chromium; Chromium - analysis; Civil engineering; Copper; Copper - analysis; Correlation; Creeks & streams; Drug resistance; Drug Resistance, Microbial - genetics; Ecological risk assessment; Environmental science; Epidemiology; Genes; Geochemistry; Iron; Iron - analysis; Lead; Lead - analysis; Linear Models; Markvetenskap; Metal concentrations; Microbial drug resistance; Natural environment; Nickel; Nickel - analysis; Polymerase Chain Reaction; Salinity; Scotland; Sediments; Soil - analysis; Soil - chemistry; Soil Science; Soils; Zinc - analysis; United Kingdom > UK
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0027300

The vast majority of antibiotic resistant genes (ARG) acquired by human pathogens have originated from the natural environment. Therefore, understanding factors that influence intrinsic levels of ARG in the environment could be epidemiologically significant. The selection for metal resistance often promotes AR in exposed organisms; however, the relationship between metal levels in nature and the intrinsic presence of ARG has not been fully assessed. Here, we quantified, using qPCR, the abundance of eleven ARG and compared their levels with geochemical conditions in randomly selected soils from a Scottish archive. Many ARG positively correlated with soil copper levels, with approximately half being highly significant (p<0.05); whereas chromium, nickel, lead, and iron also significantly correlated with specific ARG. Results show that geochemical metal conditions innately influence the potential for AR in soil. We suggest soil geochemical data might be used to estimate baseline gene presence on local, regional and global scales within epidemiological risk studies related to AR transmission from the environment.