Ecological dynamic between the anthropogenic disturbance and the genetic platform of class 1 integrons

CENTRÓN DANIELA; SCALZO PAULA MARINA; NARDELLI MAXIMILIANO; QUIROGA MARÍA PAULA; RAMÍREZ MARÍA SOLEDAD; CASSINI MARCELO H.

Brisbane

Congreso; The 10th International Congress of Ecology (INTECOL); 2009

The International Association for Ecology

Since their discovery during the 20th century, antibiotics have reduced the threat posed by infectious diseases. These profits are now seriously put at risk by the emergence and spread of bacteria that are resistant to these drugs. The geographic and temporal heterogeneity in the distribution of resistance, and the multiple mechanisms that affect its evolution, must be investigated with a multidisciplinary approach. Class 1 integrons are usually associated to multidrug resistance in clinical isolates. The objective of this work was to analyse the spatial relationship between the anthropogenic disturbance and integron occurrence. We sampled bacteria in 8 sites that were a gradient of anthropogenic disturbance, at Patagonia, Argentina. We found that 6 out of 99 samples harbored a complete sequence of the inti1 gene, with several mutations never reported before. In addition, we searched for 3 genetic markers, usually found in the same genetic platform of class 1 integrons: the 36,5% of the samples had the qacE/Δ1 gene, the 18,8% had the tniC gene, both with 100% identity with genes reported for clinical isolates, and the 11,5% had alleles of the sul1 gene. The different frequencies of genetic markers reveals a particular distribution for each gene, and they were not allways associated to the environmental type 1 integron integrase genes found. The alleles of sul1 were significantly related to sites with greater exposure to antropogenic disturbance, suggesting a direct selection under antibiotic contaminants from the environment. On the other hand, the finding of alleles of this gene, evidences a genomic plasticity and/or a selection pressure different for this marker at a molecular level. These results highlights the need of studying antimicrobial resistance mechanisms in combination with ecological data in order to facilitate the prediction of strategies that help to minimize the impact of spreading of multidrug resistance.