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Distribution of specific tetracycline and erythromycin resistance genes in environmental samples assessed by macroarray detection
Author(s) -
Patterson Andrea J.,
Colangeli Roberto,
Spigaglia Patrizia,
Scott Karen P.
Publication year - 2007
Publication title -
environmental microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.954
H-Index - 188
eISSN - 1462-2920
pISSN - 1462-2912
DOI - 10.1111/j.1462-2920.2006.01190.x
Subject(s) - biology , tetracycline , erythromycin , gene , distribution (mathematics) , genetics , microbiology and biotechnology , computational biology , antibiotics , mathematical analysis , mathematics
Summary A macroarray system was developed to screen environmental samples for the presence of specific tetracycline (Tc R ) and erythromycin (erm R ) resistance genes. The macroarray was loaded with polymerase chain reaction (PCR) amplicons of 23 Tc R genes and 10 erm R genes. Total bacterial genomic DNA was extracted from soil and animal faecal samples collected from different European countries. Macroarray hybridization was performed under stringent conditions and the results were analysed by fluorescence scanning. Pig herds in Norway, reared without antibiotic use, had a significantly lower incidence of antibiotic resistant bacteria than those reared in other European countries, and organic herds contained lower numbers of resistant bacteria than intensively farmed animals. The relative proportions of the different genes were constant across the different countries. Ribosome protection type Tc R genes were the most common resistance genes in animal faecal samples, with the tet (W) gene the most abundant, followed by tet (O) and tet (Q). Different resistance genes were present in soil samples, where erm (V) and erm (E) were the most prevalent followed by the efflux type Tc R genes. The macroarray proved a powerful tool to screen DNA extracted from environmental samples to identify the most abundant Tc R and erm R genes within those tested, avoiding the need for culturing and biased PCR amplification steps.