| Résumé | A customized DNA microarray was designed to detect Escherichia coli virulence genes in addition to Gram-negative genes conferring resistance to antimicrobials belonging to the aminoglycoside, β-lactam, tetracycline, sulfonamide, phenicol, and quinolone families as well as to rifampin, erythromycin, trimethoprim, olaquindox, quaternary ammonium compound resistant determinant genes, and mobile genetic elements such as class 1, 2, 3 integrons and transposon Tn21. This microarray was applied in the genotyping of two collection strains coming from colibacillosis outbreaks in rabbit and cattle facilities located in Italy and Iran, respectively. For each collection, the positive gene distribution and frequency per encoded enzyme or protein involved in antimicrobial resistance was first determined. Thereafter, strains positive for integrons were matched with the presence of transposon Tn21 (tnpM gene) in order to highlight the genetic potential of resistance (multi-resistance) transferability in the examined strains. Fourteen of 26 strains in our rabbit E. coli collection were positive for a class 1 integron, six of which were associated with the tnpM gene and multidrug resistance-related genes to the aminoglycoside, tetracycline, and sulfonamide-trimethoprim antimicrobial families, prevalently. Class 1 and/or class 2 and 3 integrons were also detected in 23 out of 51 strains in our cattle E. coli collection, 13 of which were also positive for tnpM gene. The presence of multiple drug resistance involving the aminoglycoside, tetracycline, and sulfonamide antimicrobial families are positively associated with this tnpM gene group. Moreover, strains having positive genes for integrons and transposons were also carriers, to a lesser extent, of class A and/or class C β-lactamase (11 strains) and quinolone (9 strains) resistant genes. The DNA microarray used in this chapter has proven to be a powerful tool in determining the genetic profile of antimicrobial resistance in E. coli field strains. The DNA microarray technology may be an appropriate technology for inclusion in antimicrobial resistance monitoring programs because of its adaptability to and ease of data collection for any particular monitoring program. Furthermore, this technology could be used to assess the effectiveness of antimicrobial use-reduction plans or in comparative studies between traditional and antibiotic-free animal production systems. |
|---|
