Dataset Information

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

ABSTRACT: 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 Campylobacter jejuni genome sequences with exceptionally high-level multidrug resistance. In this study, we used whole genome sequences of seven C. jejuni 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 C. jejuni isolates were resistant to gentamicin, and one was resistant to erythromycin. The extensive drug-resistance profiles were confirmed for the two C. jejuni isolates assigned to ST-4447 (CC179). The most occurring genetic antimicrobial-resistance determinants were tetO, 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 C. jejuni. 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 C. jejuni isolates from Lithuania.

SUBMITTER: Aksomaitiene J

PROVIDER: S-EPMC7823968 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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

Aksomaitiene Jurgita J Novoslavskij Aleksandr A Kudirkiene Egle E Gabinaitiene Ausra A Malakauskas Mindaugas M

Microorganisms 20201229 1

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 Campylobacter jejuni genome sequences with exceptionally high-level multidrug resistance. In this study, we used whole genome sequences of seven C. jejuni to identify isolate-spec ...[more]

PMID: 33383765

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Project description:Defining the precise relationship between resistance mutations and quantitative phenotypic drug susceptibility testing will increase the value of whole-genome sequencing (WGS) for predicting tuberculosis drug resistance. However, a large number of WGS data sets currently lack corresponding quantitative phenotypic data-the MICs. Using MYCOTBI plates, we determined the MICs to nine antituberculosis drugs for 154 clinical multidrug-resistant tuberculosis isolates from the Shenzhen Center for Chronic Disease Control in Shenzhen, China. Comparing MICs with predicted drug-resistance profiles inferred by WGS showed that WGS could predict the levels of resistance to isoniazid, rifampicin, streptomycin, fluoroquinolones, and aminoglycosides. We also found some mutations that may not be associated with drug resistance, such as EmbB D328G, mutations in the gid gene, and C-12T in the eis promoter. However, some strains carrying the same mutations showed different levels of resistance to the corresponding drugs. The MICs of different strains with the RpsL K88R, fabG1 C-15T mutations and some with mutations in embB and rpoB, had MICs to the corresponding drugs that varied by 8-fold or more. This variation is unexplained but could be influenced by the bacterial genetic background. Additionally, we found that 32.3% of rifampicin-resistant isolates were rifabutin-susceptible, particularly those with rpoB mutations H445D, H445L, H445S, D435V, D435F, L452P, S441Q, and S441V. Studying the influence of bacterial genetic background on the MIC and the relationship between rifampicin-resistant mutations and rifabutin resistance levels should improve the ability of WGS to guide the selection of medical treatment regimens. IMPORTANCE Whole-genome sequencing (WGS) has excellent potential in drug-resistance prediction. The MICs are essential indications of adding a particular antituberculosis drug dosage or changing the entire treatment regimen. However, the relationship between many known drug-resistant mutations and MICs is unclear, especially for rarer ones. The results showed that WGS could predict resistance levels to isoniazid, rifampicin, streptomycin, fluoroquinolones, and aminoglycosides. However, some mutations may not be associated with drug resistance, and some others may confer various MICs to strains carrying them. Also, 32.3% of rifampicin (RIF)-resistant strains were classified as sensitive to rifabutin (RFB), and some mutations in the rpoB gene may be associated with this phenotype. Our data on the MIC distribution of strains with some rarer mutations add to the accumulated data on the resistance level associated with such mutations to help guide further research and draw meaningful conclusions.

Dataset Information

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

Publications

Whole Genome Sequence-Based Prediction of Resistance Determinants in High-Level Multidrug-Resistant <i>Campylobacter jejuni</i> Isolates in Lithuania.

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