Abstract: Concentrations of the tetracycline resistance gene tet(M) per square centimeter were assessed in meat from the slaughterhouse (n = 100) and from retail (n = 100) by real-time quantitative PCR. The study revealed a substantial contamination of retail meat with the tetracycline resistance gene tet(M), with a mean of 4.34 log copies per cm2 fasces in chicken and 5.58 log copies per cm2 fasces in pork. Quantitative resistance gene analysis provides an interesting tool for risk assessment and is becoming increasingly important. For both chicken and pork, tet(M) concentrations were significantly higher in meat at retail, compared to meat at slaughter. Cultural investigations revealed substantial differences in the prevalence of listeria and enterococci, and of E. coli and coliforms, between meat at slaughter (n = 500) and at retail (n = 500). However, the differences in the prevalence of 2 investigated groups of potential tet(M)-carriers (enterococci, listeria) could not sufficiently explain the differences in tet(M) concentrations, since increasing concentrations of tet(M) were accompanied by decreasing prevalences of these potential tet(M)-carriers. The percentage of tetracycline susceptible indicator bacteria (E. faecalis, E. coli) did not differ between meat at slaughter and meat at retail. Higher concentrations of tet(M) at retail might correlate with the proliferation of other genera than enterococci and listeria, but there is also a reason to discuss whether secondary contaminants might carry tet(M) more often than the primary flora of meat.
Practical Application: We successfully applied the direct quantitative monitoring of resistance genes in meat, which generally might aid as a useful and rapid additional tool for risk assessment. We know that bacteria provide a large pool of resistance genes, which are widely shared between each other—the larger the pool is, the more genes might be exchanged. Thus, in terms of resistance gene monitoring, we should sometimes overcome the restricted view on single bacteria and look at the gene pool, instead.