Antimicrobial resistance and molecular epidemiology using whole-genome sequencing of Neisseria gonorrhoeae in Ireland, 2014–2016: focus on extended-spectrum cephalosporins and azithromycin

2018 ◽  
Vol 37 (9) ◽  
pp. 1661-1672 ◽  
Author(s):  
L. Ryan ◽  
D. Golparian ◽  
N. Fennelly ◽  
L. Rose ◽  
P. Walsh ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Neisseria Gonorrhoeae ◽  
Molecular Epidemiology ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome ◽  
Extended Spectrum

scholarly journals Neisseria gonorrhoeae clustering to reveal major European whole-genome-sequencing-based genogroups in association with antimicrobial resistance

2020 ◽  
Author(s):  
Miguel Pinto ◽  
Vítor Borges ◽  
Joana Isidro ◽  
João Carlos Rodrigues ◽  
Luís Vieira ◽  
...  
Keyword(s):  
Antimicrobial Resistance ◽  
Neisseria Gonorrhoeae ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Type Species ◽  
Transmitted Disease ◽  
Epidemiological Surveillance ◽  
Whole Genome ◽  
Content Type ◽  
Link Type

Neisseria gonorrhoeae , the bacterium responsible for the sexually transmitted disease gonorrhoea, has shown an extraordinary ability to develop antimicrobial resistance (AMR) to multiple classes of antimicrobials. With no available vaccine, managing N. gonorrhoeae infections demands effective preventive measures, antibiotic treatment and epidemiological surveillance. The latter two are progressively being supported by the generation of whole-genome sequencing (WGS) data on behalf of national and international surveillance programmes. In this context, this study aims to perform N. gonorrhoeae clustering into genogroups based on WGS data, for enhanced prospective laboratory surveillance. Particularly, it aims to identify the major circulating WGS-genogroups in Europe and to establish a relationship between these and AMR. Ultimately, it enriches public databases by contributing with WGS data from Portuguese isolates spanning 15 years of surveillance. A total of 3791 carefully inspected N. gonorrhoeae genomes from isolates collected across Europe were analysed using a gene-by-gene approach (i.e. using cgMLST). Analysis of cluster composition and stability allowed the classification of isolates into a two-step hierarchical genogroup level determined by two allelic distance thresholds revealing cluster stability. Genogroup clustering in general agreed with available N. gonorrhoeae typing methods [i.e. MLST (multilocus sequence typing), NG-MAST ( N. gonorrhoeae multi-antigen sequence typing) and PubMLST core-genome groups], highlighting the predominant genogroups circulating in Europe, and revealed that the vast majority of the genogroups present a dominant AMR profile. Additionally, a non-static gene-by-gene approach combined with a more discriminatory threshold for potential epidemiological linkage enabled us to match data with previous reports on outbreaks or transmission chains. In conclusion, this genogroup assignment allows a comprehensive analysis of N. gonorrhoeae genetic diversity and the identification of the WGS-based genogroups circulating in Europe, while facilitating the assessment (and continuous monitoring) of their frequency, geographical dispersion and potential association with specific AMR signatures. This strategy may benefit public-health actions through the prioritization of genogroups to be controlled, the identification of emerging resistance carriage, and the potential facilitation of data sharing and communication.

scholarly journals Antimicrobial resistance profiling and phylogenetic analysis of Neisseria gonorrhoeae clinical isolates from Kenya in a resource-limited setting

2020 ◽  
Author(s):  
Meshack O Juma ◽  
Arun Sankaradoss ◽  
Redcliff Ndombi ◽  
Patrick Mwaura ◽  
Tina Damodar ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Phylogenetic Analysis ◽  
Antimicrobial Resistance ◽  
Neisseria Gonorrhoeae ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome ◽  
Resource Limited Settings ◽  
Resource Limited ◽  
The World

Background Africa has one of the highest incidences of gonorrhoea, but not much information is available on the relatedness with strains from other geographical locations. Antimicrobial resistance (AMR) in Neisseria gonorrhoeae is a major public health threat, with the bacteria gaining resistance to most of the available antibiotics, compromising treatment across the world. Whole-genome sequencing is an efficient way of predicting AMR determinants and their spread in the human population. Previous studies on Kenyan gonococcal samples have focused on plasmid-mediated drug resistance and fluoroquinolone resistance using Illumina sequencing. Recent advances in next-generation sequencing technologies like Oxford Nanopore Technology (ONT) have helped in the generation of longer reads of DNA in a shorter duration with lower cost. However, long-reads are error-prone. The increasing accuracy of base-calling algorithms, high throughput, error-correction strategies, and ease of using the mobile sequencer in remote areas is leading to the adoption of the MinION sequencer (ONT), for routine microbial genome sequencing. Methods To investigate whether MinION-only sequencing is sufficient for diagnosis, genome sequencing and downstream analysis like inferring phylogenetic relationships and detection of AMR in resource-limited settings, we sequenced the genomes of fourteen clinical isolates suspected to be N. gonorrhoeae from Nairobi, Kenya. The isolates were tested using standard bacteriological methods for identification, interpretted using analytical profile index and antibiotic susceptibility tests had indicated ciprofloxacin and gentamycin resistance. Using whole genome sequencing, the isolates were confirmed to be cases of N. gonorrhoeae (n=12), Additionally, we identified reads from N. meningitidis (n=2) and both of N. gonorrhoeae and Moraxella osloensis (n=3) in the sample (co-infections) respectively, which have been implicated in sexually transmitted infections in the recent years. The near-complete N. gonorrhoeae genomes (n=10) were anaysed further for mutations/factors causing AMR using an in-house database of mutations curated from the literature. We attempted to understand the basis of drug resistance using homology modelling of AMR proteins, using known structures from other bacteria. Results We observe that Ciprofloxacin resistance is associated with multiple mutations in both gyrA and parC. We identified mutations conferring tetracycline (rpsJ) and Sulfonamide (folA) resistance in all the isolates and plasmids encoding beta-lactamase and tet(M) were identified in almost all of the strains. Phylogenetic analysis clustered the nine isolates into clades containing previously sequenced genomes from Kenya and countries across the world. Conclusion Here, we demonstrate the utility of mobile DNA sequencing technology supplemented with reference-based assembly in sequence typing and elucidating the basis of AMR. Bioinformatics profiling to predict AMR can be used along with routine AMR susceptibily tests in clinics. The workflow followed in the study, including AMR mutation dataset creation and the genome identification, assembly and analysis, can be used for the genome assembly and analysis of any clinical isolate. Further studies are required to determine the utility of real-time sequencing in the outbreak investigations, diagnosis and management of infections, especially in resource-limited settings.

scholarly journals Whole-Genome Sequencing-Based Antimicrobial Resistance Characterization and Phylogenomic Investigation of 19 Multidrug-Resistant and Extended-Spectrum Beta-Lactamase-Positive Escherichia coli Strains Collected From Hospital Patients in Benin in 2019

2021 ◽  
Vol 12 ◽  
Author(s):  
Carine Laurence Yehouenou ◽  
Bert Bogaerts ◽  
Sigrid C. J. De Keersmaecker ◽  
Nancy H. C. Roosens ◽  
Kathleen Marchal ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Antimicrobial Resistance ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Surgical Site Infections ◽  
Multidrug Resistant ◽  
Whole Genome ◽  
Beta Lactamase ◽  
Extended Spectrum Beta Lactamase ◽  
Extended Spectrum

The increasing worldwide prevalence of extended-spectrum beta-lactamase (ESBL) producing Escherichia coli constitutes a serious threat to global public health. Surgical site infections are associated with high morbidity and mortality rates in developing countries, fueled by the limited availability of effective antibiotics. We used whole-genome sequencing (WGS) to evaluate antimicrobial resistance and the phylogenomic relationships of 19 ESBL-positive E. coli isolates collected from surgical site infections in patients across public hospitals in Benin in 2019. Isolates were identified by MALDI-TOF mass spectrometry and phenotypically tested for susceptibility to 16 antibiotics. Core-genome multi-locus sequence typing and single-nucleotide polymorphism-based phylogenomic methods were used to investigate the relatedness between samples. The broader phylogenetic context was characterized through the inclusion of publicly available genome data. Among the 19 isolates, 13 different sequence types (STs) were observed, including ST131 (n = 2), ST38 (n = 2), ST410 (n = 2), ST405 (n = 2), ST617 (n = 2), and ST1193 (n = 2). The blaCTX-M-15 gene encoding ESBL resistance was found in 15 isolates (78.9%), as well as other genes associated with ESBL, such as blaOXA-1 (n = 14) and blaTEM-1 (n = 9). Additionally, we frequently observed genes encoding resistance against aminoglycosides [aac-(6')-Ib-cr, n = 14], quinolones (qnrS1, n = 4), tetracyclines [tet(B), n = 14], sulfonamides (sul2, n = 14), and trimethoprim (dfrA17, n = 13). Nonsynonymous chromosomal mutations in the housekeeping genes parC and gyrA associated with resistance to fluoroquinolones were also detected in multiple isolates. Although the phylogenomic investigation did not reveal evidence of hospital-acquired transmissions, we observed two very similar strains collected from patients in different hospitals. By characterizing a set of multidrug-resistant isolates collected from a largely unexplored environment, this study highlights the added value for WGS as an effective early warning system for emerging pathogens and antimicrobial resistance.

scholarly journals Expanding U.S. Laboratory Capacity for Neisseria gonorrhoeae Antimicrobial Susceptibility Testing and Whole-Genome Sequencing through the CDC's Antibiotic Resistance Laboratory Network

2020 ◽  
Vol 58 (4) ◽  
Author(s):  
Ellen N. Kersh ◽  
Cau D. Pham ◽  
John R. Papp ◽  
Robert Myers ◽  
Richard Steece ◽  
...  
Keyword(s):  
Public Health ◽  
Antibiotic Resistance ◽  
Neisseria Gonorrhoeae ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Antimicrobial Susceptibility ◽  
Susceptibility Testing ◽  
Whole Genome ◽  
Content Type ◽  
Laboratory Capacity

ABSTRACT U.S. gonorrhea rates are rising, and antibiotic-resistant Neisseria gonorrhoeae (AR-Ng) is an urgent public health threat. Since implementation of nucleic acid amplification tests for N. gonorrhoeae identification, the capacity for culturing N. gonorrhoeae in the United States has declined, along with the ability to perform culture-based antimicrobial susceptibility testing (AST). Yet AST is critical for detecting and monitoring AR-Ng. In 2016, the CDC established the Antibiotic Resistance Laboratory Network (AR Lab Network) to shore up the national capacity for detecting several resistance threats including N. gonorrhoeae. AR-Ng testing, a subactivity of the CDC’s AR Lab Network, is performed in a tiered network of approximately 35 local laboratories, four regional laboratories (state public health laboratories in Maryland, Tennessee, Texas, and Washington), and the CDC’s national reference laboratory. Local laboratories receive specimens from approximately 60 clinics associated with the Gonococcal Isolate Surveillance Project (GISP), enhanced GISP (eGISP), and the program Strengthening the U.S. Response to Resistant Gonorrhea (SURRG). They isolate and ship up to 20,000 isolates to regional laboratories for culture-based agar dilution AST with seven antibiotics and for whole-genome sequencing of up to 5,000 isolates. The CDC further examines concerning isolates and monitors genetic AR markers. During 2017 and 2018, the network tested 8,214 and 8,628 N. gonorrhoeae isolates, respectively, and the CDC received 531 and 646 concerning isolates and 605 and 3,159 sequences, respectively. In summary, the AR Lab Network supported the laboratory capacity for N. gonorrhoeae AST and associated genetic marker detection, expanding preexisting notification and analysis systems for resistance detection. Continued, robust AST and genomic capacity can help inform national public health monitoring and intervention.

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