Characterization of Plasmid-Mediated Quinolone Resistance Determinants in High-Level Quinolone-ResistantEnterobacteriaceaeIsolates from the Community: First Report ofqnrDGene in Algeria

Yanat, Betitera; Machuca, Jesús; Díaz-de-Alba, Paula; Mezhoud, Halima; Touati, Abdelaziz; Pascual, Álvaro; Rodríguez-Martínez, José Manuel

doi:10.1089/mdr.2016.0031

Cited by 15 publications

(6 citation statements)

References 39 publications

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“…This novel variant, aac(6’)Ib-cr , was shown to confer a median fold increase in ciprofloxacin MIC of 6.9 (range: 1-62.5x fold increase, Table 2). 52, 71–76…”

Section: Resultsmentioning

confidence: 99%

Quantifying the contribution of four resistance mechanisms to ciprofloxacin minimum inhibitory concentration inEscherichia coli: a systematic review

Remondini

Pasquini

et al. 2018

Preprint

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SynopsisIntroductionCiprofloxacin resistance in Escherichia coli is widespread and adds to the burden of E. coli infections. Reviews assessing the genetic basis of ciprofloxacin resistance have mostly been qualitative. However, to allow for the prediction of a resistance phenotype of clinical relevance based on genotypic characteristics, it is essential to quantify the contribution of prevalent genotypic determinants to resistance. We carried out a systematic review to assess the relative contribution of currently known genomic resistance determinants to the minimum inhibitory concentration (MIC) of ciprofloxacin in E. coli.MethodsPubMed and Web of Science were searched for English language studies that assessed both ciprofloxacin MIC and the presence or introduction of genetic determinants of ciprofloxacin resistance in E. coli. We included experimental and observational studies without time restrictions. Medians and ranges of MIC fold changes were calculated for each resistance determinant and for combinations of determinants.ResultsWe included 66 studies, describing 604 E. coli isolates that carried at least one genetic resistance determinant. Genes coding for targets of ciprofloxacin (gyrA and parC) are strongest contributors to ciprofloxacin resistance, with median MIC fold increases ranging from 24 (range 4-133) for single Ser83Leu (gyrA) mutants to 1533 (range 256-8533) for triple Ser83Leu, Asp87Asn/Gly (gyrA) and Ser80Ile/Arg (parC) mutants. Other resistance mechanisms, including efflux, physical blocking or enzymatic modification, conferred smaller increases in ciprofloxacin MIC (median MIC fold increases typically around 15, range 1-125). However, the (combined) presence of these other resistance mechanisms further increases resistance with median MIC fold increases of up to 4000, and even in the absence of gyrA and parC mutations up to 250.ConclusionThis report provides a comprehensive and quantitative overview of the contribution of different genomic determinants to ciprofloxacin resistance in E. coli. Additionally, the data demonstrate the complexity of resistance phenotype prediction from genomic data and could serve as a reference point for studies aiming to address ciprofloxacin resistance prediction using genomics, in E. coli.

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“…This novel variant, aac(6’)Ib-cr , was shown to confer a median fold increase in ciprofloxacin MIC of 6.9 (range: 1-62.5x fold increase, Table 2). 52, 71–76…”

Section: Resultsmentioning

confidence: 99%

Quantifying the contribution of four resistance mechanisms to ciprofloxacin minimum inhibitory concentration inEscherichia coli: a systematic review

Remondini

Pasquini

et al. 2018

Preprint

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“…Of note, QnrD gene (quinolone-resistance determinant D), a plasmid-mediated quinolone resistance typically present in Gram-negative bacteria, was also detected in HOM. This resistance gene, first reported in a human clinical isolate of Salmonella in China [47], was then detected in Proteus mirabilis and Morganella morganii in Europe, and subsequently spread in other Enterobacteriaceae [48,49]. Some differences were observed between female and male cohorts of participants (Fig.…”

Section: Resistome Analysismentioning

confidence: 86%

Defining the oral microbiome by whole-genome sequencing and resistome analysis: the complexity of the healthy picture

et al. 2020

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Background The microbiome of the oral cavity is the second-largest and diverse microbiota after the gut, harboring over 700 species of bacteria and including also fungi, viruses, and protozoa. With its diverse niches, the oral cavity is a very complex environment, where different microbes preferentially colonize different habitats. Recent data indicate that the oral microbiome has essential functions in maintaining oral and systemic health, and the emergence of 16S rRNA gene next-generation sequencing (NGS) has greatly contributed to revealing the complexity of its bacterial component. However, a detailed site-specific map of oral microorganisms (including also eukaryotes and viruses) and their relative abundance is still missing. Here, we aimed to obtain a comprehensive view of the healthy oral microbiome (HOM), including its drug-resistance features. Results The oral microbiome of twenty healthy subjects was analyzed by whole-genome sequencing (WGS) and real-time quantitative PCR microarray. Sampled oral micro-habitat included tongue dorsum, hard palate, buccal mucosa, keratinized gingiva, supragingival and subgingival plaque, and saliva with or without rinsing. Each sampled oral niche evidenced a different microbial community, including bacteria, fungi, and viruses. Alpha-diversity evidenced significant differences among the different sampled sites (p < 0.0001) but not among the enrolled subjects (p = 0.876), strengthening the notion of a recognizable HOM. Of note, oral rinse microbiome was more representative of the whole site-specific microbiomes, compared with that of saliva. Interestingly, HOM resistome included highly prevalent genes conferring resistance to macrolide, lincosamides, streptogramin, and tetracycline. Conclusions The data obtained in 20 subjects by WGS and microarray analysis provide for the first time a comprehensive view of HOM and its resistome, contributing to a deeper understanding of the composition of oral microbiome in the healthy subject, and providing an important reference for future studies, allowing to identify microbial signatures related to functional and metabolic alterations associated with diseases, potentially useful for targeted therapies and precision medicine.

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“… 5 Although the PMQR determinants lead to low-level quinolone resistance, they facilitate the chromosome-encoded quinolone resistance. 6 ESBL-producing Enterobacteriaceae has emerged as multidrug-resistant (MDR), especially resistant to trimethoprim/sulfamethoxazole, aminoglycosides, and fluoroquinolones. 7…”

Section: Introductionmentioning

confidence: 99%

The prevalence of plasmid-mediated quinolone resistance and ESBL-production in Enterobacteriaceae isolated from urinary tract infections

Azargun

Sadeghi

Barhaghi

et al. 2018

IDR

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Introductionβ-lactam and fluoroquinolone antibiotics are usually used for the treatment of urinary tract infections (UTIs). The aim of this study was to determine the prevalence of plasmid-mediated quinolone resistance (PMQR) and extended spectrum β-lactamases (ESBLs) in Enterobacteriaceae isolated from UTIs.Materials and methodsTwo hundred and nineteen samples of Enterobacteriaceae isolated from UTIs were collected in the Northwest of Iran. Antimicrobial susceptibility testing was determined by the disk diffusion method. ESBLs were detected by the double-disk test. ESBL and PMQR-encoding genes were screened using the polymerase chain reaction.ResultsThe rate of resistance to moxifloxacin, nalidixic acid, gatifloxacin, ofloxacin, ciprofloxacin, and levofloxacin in ESBL-producing isolates was 89.3%, 88%, 84%, 80%, 78.7%, and 73.3%, respectively. PMQR-producing Enterobacteriaceae isolates were identified in 67 samples (89.1%). The most prevalent PMQR genes were aac (6′)-Ib-cr 120 (68.6%) followed by oqxB 72 (41.1%), oqxA 59 (33.7%), qnrB 36 (20.6%), qnrS 33 (18.9%), qnrD 19 (10.9%), qepA 13 (7.4 %), qnrA 10 (5.7%), and qnrC 9 (5.1%). There was a strong association between PMQR genes and blaCTX-M-15 and blaTEM-116 and other ESBL genes.ConclusionHigh resistance rates were detected to quinolones among ESBL-producing isolates from UTIs. There is a high prevalence of PMQR genes in Enterobacteriaceae in Azerbaijan and Iran, and the most common PMQR is aac(6′)-Ib-cr. There is a significant association between PMQR and ESBL-producing isolates.

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Characterization of Plasmid-Mediated Quinolone Resistance Determinants in High-Level Quinolone-ResistantEnterobacteriaceaeIsolates from the Community: First Report ofqnrDGene in Algeria

Abstract: Our findings indicate that PMQR determinants are prevalent in Enterobacteriaceae isolates from the community studied. We describe the first report of the qnrD gene in Algeria.

Cited by 15 publications

References 39 publications

Quantifying the contribution of four resistance mechanisms to ciprofloxacin minimum inhibitory concentration inEscherichia coli: a systematic review

Quantifying the contribution of four resistance mechanisms to ciprofloxacin minimum inhibitory concentration inEscherichia coli: a systematic review

Defining the oral microbiome by whole-genome sequencing and resistome analysis: the complexity of the healthy picture

The prevalence of plasmid-mediated quinolone resistance and ESBL-production in <em>Enterobacteriaceae </em>isolated from urinary tract infections

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