Whole genome-based characterisation of antimicrobial resistance and genetic diversity in Campylobacter jejuni and Campylobacter coli from ruminants
Campylobacter , a leading cause of gastroenteritis in humans, asymptomatically colonises the intestinal tract of a wide range of animals.Although antimicrobial treatment is restricted to severe cases, the increase of antimicrobial resistance (AMR) is a concern. Considering the significant contributi...
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Veröffentlicht in: | Scientific reports 2021-04, Vol.11 (1), p.8998-8998, Article 8998 |
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Sprache: | eng |
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Zusammenfassung: | Campylobacter
, a leading cause of gastroenteritis in humans, asymptomatically colonises the intestinal tract of a wide range of animals.Although antimicrobial treatment is restricted to severe cases, the increase of antimicrobial resistance (AMR) is a concern. Considering the significant contribution of ruminants as reservoirs of resistant
Campylobacter
, Illumina whole-genome sequencing was used to characterise the mechanisms of AMR in
Campylobacter jejuni
and
Campylobacter coli
recovered from beef cattle, dairy cattle, and sheep in northern Spain. Genome analysis showed extensive genetic diversity that clearly separated both species. Resistance genotypes were identified by screening assembled sequences with BLASTn and ABRicate, and additional sequence alignments were performed to search for frameshift mutations and gene modifications. A high correlation was observed between phenotypic resistance to a given antimicrobial and the presence of the corresponding known resistance genes. Detailed sequence analysis allowed us to detect the recently described mosaic
tet
(O/M/O) gene in one
C. coli
, describe possible new alleles of
bla
OXA-61
-like genes, and decipher the genetic context of aminoglycoside resistance genes, as well as the plasmid/chromosomal location of the different AMR genes and their implication for resistance spread. Updated resistance gene databases and detailed analysis of the matched open reading frames are needed to avoid errors when using WGS-based analysis pipelines for AMR detection in the absence of phenotypic data. |
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ISSN: | 2045-2322 2045-2322 |
DOI: | 10.1038/s41598-021-88318-0 |