Whole Genome Sequence-Based Prediction of Resistance Determinants in High-Level Multidrug-Resistant Campylobacter jejuni Isolates in Lithuania

Spread of antibiotic resistance via mobile genetic elements associates with transfer of genes providing resistance against multiple antibiotics. Use of various comparative genomics analysis techniques enables to find intrinsic and acquired genes associated with phenotypic antimicrobial resistance (A...

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Veröffentlicht in:Microorganisms (Basel) 2020-12, Vol.9 (1), p.66
Hauptverfasser: Aksomaitiene, Jurgita, Novoslavskij, Aleksandr, Kudirkiene, Egle, Gabinaitiene, Ausra, Malakauskas, Mindaugas
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Sprache:eng
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Zusammenfassung:Spread of antibiotic resistance via mobile genetic elements associates with transfer of genes providing resistance against multiple antibiotics. Use of various comparative genomics analysis techniques enables to find intrinsic and acquired genes associated with phenotypic antimicrobial resistance (AMR) in genome sequences with exceptionally high-level multidrug resistance. In this study, we used whole genome sequences of seven to identify isolate-specific genomic features associated with resistance and virulence determinants and their role in multidrug resistance (MDR). All isolates were phenotypically highly resistant to tetracycline, ciprofloxacin, and ceftriaxone (MIC range from 64 to ≥256 µg/mL). Besides, two isolates were resistant to gentamicin, and one was resistant to erythromycin. The extensive drug-resistance profiles were confirmed for the two isolates assigned to ST-4447 (CC179). The most occurring genetic antimicrobial-resistance determinants were , beta-lactamase, and multidrug efflux pumps. In this study, mobile genetic elements (MGEs) were detected in genomic islands carrying genes that confer resistance to MDR, underline their importance for disseminating antibiotic resistance in . The genomic approach showed a diverse distribution of virulence markers, including both plasmids and phage sequences that serve as horizontal gene transfer tools. The study findings describe in silico prediction of AMR and virulence genetics determinants combined with phenotypic AMR detection in multidrug-resistant isolates from Lithuania.
ISSN:2076-2607
2076-2607
DOI:10.3390/microorganisms9010066