Occurrence of tet(O/M/O) Mosaic Gene in Tetracycline-Resistant Campylobacter.
Lorena HormeñoMaria Jorge CamposSantiago VadilloAlberto QuesadaPublished in: Microorganisms (2020)
Campylobacter is one of the most important microorganisms responsible for foodborne diseases in the EU. In this study, we investigated resistance to tetracycline in 139 Campylobacter jejuni and Campylobacter coli samples isolated from human clinical cases. From these, 110 were resistant to tetracycline, with MIC (minimal inhibitory concentration) varying in a range of 1 to >512 μg/mL, and 109 (78.4%) carried tet(O), a gene that confers resistance to tetracycline through the expression of a protein that confers protection to the ribosome. Amongst the tetracycline-resistant isolates, one C. jejuni (HCC30) was the only tet(O)-negative sample, presenting an MIC of 256 μg/mL. Instead, the mosaic gene tet(O/M/O) was found in HCC30 and, as far as we know, this is the first description of this chimeric gene originating from homologous recombination between tet(O) and tet(M). The previously described mosaic gene tet(O/32/O), also found in Campylobacter, presents a chimeric structure very similar to that of tet(O/M/O), affecting domains II and III of encoded proteins distantly related to the elongation factor G (EF-G). The tet(O/M/O) mosaic gene has been found in nucleotide databases in several genomes of Campylobacter isolated from different origins, indicating its frequent acquisition, even though it can be undetected through screening by PCR with specific tet(O) primers. In this work, we address the improvement of classical PCR to efficiently diagnose the most prevalent tetracycline resistance determinants in Campylobacter, including tet(O/M/O), which should be taken into account in the optimization of campylobacteriosis treatments.
Keyphrases
- biofilm formation
- antimicrobial resistance
- copy number
- genome wide
- genome wide identification
- escherichia coli
- stem cells
- poor prognosis
- cell therapy
- dna methylation
- gene expression
- machine learning
- mass spectrometry
- transcription factor
- atomic force microscopy
- long non coding rna
- mesenchymal stem cells
- candida albicans
- single molecule
- artificial intelligence