Genomic Epidemiology and Molecular Resistance Mechanisms of Azithromycin-Resistant Neisseria gonorrhoeae in Canada from 1997 to 2014

Antimicrobial treatment and resistance in sexually transmitted bacterial infections

Sexually transmitted infections (STIs) have been part of human life since ancient times, and their symptoms affect quality of life, and sequelae are common. Socioeconomic and behavioural trends affect the prevalence of STIs, but the discovery of antimicrobials gave hope for treatment, control of the spread of infection and lower rates of sequelae. This has to some extent been achieved, but increasing antimicrobial resistance and increasing transmission in high-risk sexual networks threaten this progress. For Neisseria gonorrhoeae, the only remaining first-line treatment (with ceftriaxone) is at risk of becoming ineffective, and for Mycoplasma genitalium, for which fewer alternative antimicrobial classes are available, incurable infections have already been reported. For Chlamydia trachomatis, in vitro resistance to first-line tetracyclines and macrolides has never been confirmed despite decades of treatment of this highly prevalent STI. Similarly, Treponema pallidum, the cause of syphilis, has remained susceptible to first-line penicillin.

Genome-based epidemiology and antimicrobial resistance of Neisseria gonorrhoeae in Spain: A prospective multicentre study

BACKGROUND

Whole-genome sequencing (WGS) of Neisseria gonorrhoeae isolates combined with epidemiological and phenotypic data provides better understanding of population dynamics.

AIM

The objective of this study was to investigate the molecular epidemiology of N. gonorrhoeae isolates from three centres in Spain and determine associations of antimicrobial resistance.

METHODS

Genetic characterization was performed in 170 N. gonorrhoeae isolates. WGS was carried out with the HiSeq platform (Illumina). Genome assemblies were submitted to the PubMLST Neisseria database website to determine NG-MAST, MLST and NG-STAR. Antimicrobial resistance genes and point mutations were identified with PubMLST. Phylogenomic comparison was based on whole-genome single nucleotide polymorphism analysis.

RESULTS

Twenty-six MLST, 49 NG-MAST and 41 NG-STAR sequence types were detected, the most prevalent being MLST-ST9363 (27.1%), NG-MAST ST569 (12.4%) and NG-STAR ST193 (14.7%). Phylogenetic analysis identified 13 clusters comprising 69% of the isolates, with two of note: one involved cefixime-resistant isolates from Barcelona presenting a mosaic penA X and belonging to MLST-ST7363 and the other involved azithromycin-resistant isolates from Mallorca that possessed the C2611T mutation in the four 23S rRNA alleles belonging to MLST-ST1901.

CONCLUSION

The population of N. gonorrhoeae is quite heterogeneous in Spain. Our results agree with previous data published in Europe, albeit with some differences in distribution between regions. This study describes the circulation of two gonococcal populations with a specific resistance profile and sequence type in a specific geographic area. WGS is an effective tool for epidemiological surveillance of gonococcal infection and detection of resistance genes.

Use of genome sequencing to resolve differences in gradient diffusion and agar dilution antimicrobial susceptibility testing performance of Neisseria gonorrhoeae isolates in Alberta, Canada

Agar dilution is the gold standard method for phenotypic antimicrobial susceptibility testing (AST) for Neisseria gonorrhoeae. However, this method is laborious and requires expertise, so laboratories that perform N. gonorrhoeae AST may choose alternative methods such as disk diffusion and gradient diffusion. In this study, we retrospectively compare the performance of gradient diffusion to agar dilution for 2,394 unique N. gonorrhoeae isolates identified in Alberta from 2017 to 2020 against azithromycin, cefixime, ceftriaxone, ciprofloxacin, penicillin, and tetracycline. Genome sequencing was utilized to resolve discrepancies between AST methods, detect antimicrobial resistance markers, and identify trends between error rates and sequence types (STs) of isolates. Over 90% of N. gonorrhoeae isolates were susceptible to azithromycin, cefixime, and ceftriaxone, whereas decreased susceptibility was observed for ciprofloxacin, penicillin, and tetracycline. Categorical (CA) and essential agreement (EA) was poorest between the two methods for penicillin (CA: 86.02%; EA: 77.69%) and tetracycline (CA: 47.22%; EA: 55.96%); however, the low CA was primarily attributed to minor errors. Antimicrobial agents with errors outside of acceptable limits included azithromycin (very major error: 18.42%; major error: 7.73%) and tetracycline (very major error: 6.17%). Genome sequencing on a subset of isolates resolved 30.3% of the azithromycin major errors and confirmed the azithromycin or tetracycline very major errors. Significant associations between certain STs and error types for azithromycin and tetracycline were also identified. Overall, gradient diffusion compared well to agar dilution for cefixime, ceftriaxone, and ciprofloxacin, and genome sequencing was identified as a useful tool to arbitrate discrepant susceptibility testing results between gradient diffusion and agar dilution for N. gonorrhoeae.

Rolling the evolutionary dice: Neisseria commensals as proxies for elucidating the underpinnings of antibiotic resistance mechanisms and evolution in human pathogens

Species within the genus Neisseria are especially adept at sharing adaptive allelic variation across species' boundaries, with commensal species repeatedly transferring resistance to their pathogenic relative N. gonorrhoeae. However, resistance in commensal Neisseria is infrequently characterized at both the phenotypic and genotypic levels, limiting our ability to predict novel and potentially transferable resistance mechanisms that ultimately may become important clinically. Unique evolutionary starting places of each Neisseria species will have distinct genomic backgrounds, which may ultimately control the fate of evolving populations in response to selection, as epistatic and additive interactions may coerce lineages along divergent evolutionary trajectories. However alternatively, similar genetic content present across species due to shared ancestry may constrain the adaptive solutions that exist. Thus, identifying the paths to resistance across commensals may aid in characterizing the Neisseria resistome - or the reservoir of alleles within the genus, as well as its depth. Here, we use in vitro evolution of four commensal species to investigate the potential for and repeatability of resistance evolution to two antimicrobials, the macrolide azithromycin and the β-lactam penicillin. After 20 days of selection, commensals evolved elevated minimum inhibitory concentrations (MICs) to penicillin and azithromycin in 11/16 and 12/16 cases respectively. Almost all cases of resistance emergence converged on mutations within ribosomal components or the mtrRCDE efflux pump for azithromycin-based selection, and mtrRCDE or penA for penicillin selection; thus, supporting constrained adaptive solutions despite divergent evolutionary starting points across the genus for these particular drugs. However, continuing to explore the paths to resistance across different experimental conditions and genomic backgrounds, which could shunt evolution down alternative evolutionary trajectories, will ultimately flesh out the full Neisseria resistome.

Emergence of Azithromycin-Resistant Neisseria gonorrhoeae Isolates Belonging to the NG-MAST Genogroup 12302 in Russia

The goal of this work was to determine the factors affecting the emergence of azithromycin-resistant Neisseria gonorrhoeae isolates in Russia, where azithromycin was never recommended for the treatment of gonococcal infections. Clinical N. gonorrhoeae isolates collected in 2018-2021 (428 isolates) were analyzed. No azithromycin-resistant isolates were found in 2018-2019, but in 2020-2021, a significant increase in the ratio of azithromycin-resistant isolates was observed: 16.8% and 9.3%, respectively. A hydrogel DNA microarray was developed for the analysis of resistance determinants: mutations in the genes encoding the mtrCDE efflux system and in all four copies of the 23S rRNA gene (position 2611). A majority of the azithromycin-resistant Russian isolates belonged to the NG-MAST G12302 genogroup, and the resistance was associated with the presence of a mosaic structure of the mtrR gene promoter region with the -35 delA deletion, an Ala86Thr mutation in the mtrR gene, and a mosaic structure of the mtrD gene. A comparative phylogenetic study of modern Russian and European N. gonorrhoeae populations allowed us to conclude that the emergence of azithromycin resistance in Russia in 2020 was the result of the appearance and spread of European N. gonorrhoeae strains belonging to the G12302 genogroup due to possible cross-border transfer.

Prior Exposure to Azithromycin and Azithromycin Resistance Among Persons Diagnosed With Neisseria gonorrhoeae Infection at a Sexual Health Clinic: 2012-2019

BACKGROUND

There is conflicting evidence on whether prior azithromycin (AZM) exposure is associated with reduced susceptibility to AZM (AZMRS) among persons infected with Neisseria gonorrhoeae (NG).

METHODS

The study population included Public Health-Seattle and King County Sexual Health Clinic (SHC) patients with culture-positive NG infection at ≥1 anatomic site whose isolates were tested for AZM susceptibility in 2012-2019. We used multivariate logistic regression to examine the association of time since last AZM prescription from the SHC in ≤12 months with subsequent diagnosis with AZMRS NG (minimum inhibitory concentration [MIC], ≥2.0 µg/mL) and used linear regression to assess the association between the number of AZM prescriptions in ≤12 months and AZM MIC level, controlling for demographic, behavioral, and clinical characteristics.

RESULTS

A total of 2155 unique patients had 2828 incident NG infections, 156 (6%) of which were caused by AZMRS NG. AZMRS NG was strongly associated with receipt of AZM from the SHC in the prior 29 days (adjusted odds ratio, 6.76; 95% confidence interval [CI], 1.76 to 25.90) but not with receipt of AZM in the prior 30-365 days. Log AZM MIC level was not associated with the number of AZM prescriptions within ≤12 months (adjusted correlation, 0.0004; 95% CI, -.04 to .037) but was associated with number of prescriptions within <30 days (adjusted coefficient, 0.56; 95% CI, .13 to .98).

CONCLUSIONS

Recent individual-level AZM treatment is associated with subsequent AZMRS gonococcal infections. The long half-life and persistence of subtherapeutic levels of AZM may result in selection of resistant NG strains in persons with recent AZM use.

Machine learning models for Neisseria gonorrhoeae antimicrobial susceptibility tests

Neisseria gonorrhoeae is an urgent public health threat due to the emergence of antibiotic resistance. As most isolates in the United States are susceptible to at least one antibiotic, rapid molecular antimicrobial susceptibility tests (ASTs) would offer the opportunity to tailor antibiotic therapy, thereby expanding treatment options. With genome sequence and antibiotic resistance phenotype data for nearly 20,000 clinical N. gonorrhoeae isolates now available, there is an opportunity to use statistical methods to develop sequence-based diagnostics that predict antibiotic susceptibility from genotype. N. gonorrhoeae, therefore, provides a useful example illustrating how to apply machine learning models to aid in the design of sequence-based ASTs. We present an overview of this framework, which begins with establishing the assay technology, the performance criteria, the population in which the diagnostic will be used, and the clinical goals, and extends to the choices that must be made to arrive at a set of features with the desired properties for predicting susceptibility phenotype from genotype. While we focus on the example of N. gonorrhoeae, the framework generalizes to other organisms for which large-scale genotype and antibiotic resistance data can be combined to aid in diagnostics development.

Azithromycin Susceptibility Testing and Molecular Investigation of Neisseria gonorrhoeae Isolates Collected in Russia, 2020-2021

The aim of this work was to study the resistance to macrolides (azithromycin) in the modern Russian population of N. gonorrhoeae with the analysis of genetic resistance determinants. Azithromycin is not used to treat gonococcal infection in Russia. However, among 162 isolates collected in 2020-2021, 22 isolates (13.6%) were phenotypically resistant to azithromycin. Mutations in 23S rRNA genes were found only in two isolates; erm and mefA genes were absent. Azithromycin resistance was shown to be predominantly associated with mutations in the mtrR and mtrD genes of the MtrCDE efflux pump and their mosaic alleles which may have formed due to a horizontal transfer from N. meningitidis. A total of 30 types of mtrR alleles and 10 types of mtrD alleles were identified including mosaic variants. Matching between the mtrR and mtrD alleles was revealed to indicate the cooperative molecular evolution of these genes. A link between the mtrR and mtrD alleles and NG-MAST types was found only for NG-MAST 228 and 807, typical of N. gonorrhoeae in Russia. The high level of resistance to azithromycin in Russia may be related to the spread of multiple transferable resistance to antimicrobials regardless of their use in the treatment of gonococcal infection.

Canary in the Coal Mine: How Resistance Surveillance in Commensals Could Help Curb the Spread of AMR in Pathogenic Neisseria

Antimicrobial resistance (AMR) is widespread within Neisseria gonorrhoeae populations. Recent work has highlighted the importance of commensal Neisseria (cN) as a source of AMR for their pathogenic relatives through horizontal gene transfer (HGT) of AMR alleles, such as mosaic penicillin binding protein 2 (penA), multiple transferable efflux pump (mtr), and DNA gyrase subunit A (gyrA) which impact beta-lactam, azithromycin, and ciprofloxacin susceptibility, respectively. However, nonpathogenic commensal species are rarely characterized. Here, we propose that surveillance of the universally carried commensal Neisseria may play the role of the "canary in the coal mine," and reveal circulating known and novel antimicrobial resistance determinants transferable to pathogenic Neisseria. We summarize the current understanding of commensal Neisseria as an AMR reservoir, and call to increase research on commensal Neisseria species, through expanding established gonococcal surveillance programs to include the collection, isolation, antimicrobial resistance phenotyping, and whole-genome sequencing (WGS) of commensal isolates. This will help combat AMR in the pathogenic Neisseria by: (i) determining the contemporary AMR profile of commensal Neisseria, (ii) correlating AMR phenotypes with known and novel genetic determinants, (iii) qualifying and quantifying horizontal gene transfer (HGT) for AMR determinants, and (iv) expanding commensal Neisseria genomic databases, perhaps leading to the identification of new drug and vaccine targets. The proposed modification to established Neisseria collection protocols could transform our ability to address AMR N. gonorrhoeae, while requiring minor modifications to current surveillance practices. IMPORTANCE Contemporary increases in the prevalence of antimicrobial resistance (AMR) in Neisseria gonorrhoeae populations is a direct threat to global public health and the effective treatment of gonorrhea. Substantial effort and financial support are being spent on identifying resistance mechanisms circulating within the gonococcal population. However, these surveys often overlook a known source of resistance for gonococci-the commensal Neisseria. Commensal Neisseria and pathogenic Neisseria frequently share DNA through horizontal gene transfer, which has played a large role in rendering antibiotic therapies ineffective in pathogenic Neisseria populations. Here, we propose the expansion of established gonococcal surveillance programs to integrate a collection, AMR profiling, and genomic sequencing pipeline for commensal species. This proposed expansion will enhance the field's ability to identify resistance in and from nonpathogenic reservoirs and anticipate AMR trends in pathogenic Neisseria.

Transcriptional regulation of the mtrCDE efflux pump operon: importance for Neisseria gonorrhoeae antimicrobial resistance

This review focuses on the mechanisms of transcriptional control of an important multidrug efflux pump system (MtrCDE) possessed by Neisseria gonorrhoeae, the aetiological agent of the sexually transmitted infection termed gonorrhoea. The mtrCDE operon that encodes this tripartite protein efflux pump is subject to both cis- and trans-acting transcriptional factors that negatively or positively influence expression. Critically, levels of MtrCDE can influence levels of gonococcal susceptibility to classical antibiotics, host-derived antimicrobials and various biocides. The regulatory systems that control mtrCDE can have profound influences on the capacity of gonococci to resist current and past antibiotic therapy regimens as well as virulence. The emergence, mechanisms of action and clinical significance of the transcriptional regulatory systems that impact mtrCDE expression in gonococci are reviewed here with the aim of linking bacterial antimicrobial resistance with multidrug efflux capability.

Genetic characteristics of azithromycin-resistant Neisseria gonorrhoeae collected in Hyogo, Japan during 2015-2019

Introduction. Azithromycin (AZM) is a therapeutic drug for sexually transmitted infections and is used for Neisseria gonorrhoeae when first- and second-line drugs are not available. Recently, the susceptibility of N. gonorrhoeae against AZM has been decreasing worldwide.Hypothesis/Gap Statement. Azithromycin-resistance (AZM-R) rates among N. gonorrhoeae in Japan are increasing, and the gene mutations and epidemiological characteristics of AZM-R in N. gonorrhoeae have not been fully investigated.Aim. We determined the susceptibility to AZM and its correlation with genetic characteristics of N. gonorrhoeae.Methodology. We investigated the susceptibility to AZM and genetic characteristics of N. gonorrhoeae. Mutations in domain V of the 23S rRNA gene and mtrR were examined in 93 isolates, including 13 AZM-R isolates. Spread and clonality were examined using sequence types (STs) of multi-antigen sequence typing for N. gonorrhoeae (NG-MAST), and whole genome analysis (WGA) to identify single nucleotide polymorphisms.Results. The number of AZM-R isolates increased gradually from 2015 to 2019 in Hyogo (P=0.008). C2599T mutations in 23S rRNA significantly increased in AZM-R isolates (P<0.001). NG-MAST ST4207 and ST6762 were frequently detected in AZM-R isolates, and they had higher MICs to AZM from 6 to 24 µg/ml. The phylogenic tree-based WGA showed that all isolates with ST4207 were contained in the same clade, and isolates with ST6762 were divided into two clades, AZM-S isolates and AZM-R isolates, which were different from the cluster containing ST1407.Conclusion. Our study showed yearly increases in AZM-R rates in N. gonorrhoeae. NG-MAST ST4207 and ST6762 were not detected in our previous study in 2015 and were frequently identified in isolates with higher MICs to AZM. WGA confirmed that isolates with these STs are closely related to each other. Continued surveillance is needed to detect the emergence and confirm the spread of NG-MAST ST4207 and ST6762.

Prediction of Antimicrobial Minimal Inhibitory Concentrations for Neisseria gonorrhoeae using Machine Learning Models

The lowest concentration of an antimicrobial agent that can inhibit the visible growth of a microorganism after overnight incubation is called as minimum inhibitory concentration (MIC) and the drug prescriptions are made on the basis of MIC data to ensure successful treatment outcomes. Therefore, reliable antimicrobial susceptibility data is crucial, and it will help clinicians about which drug to prescribe. Although few prediction studies based on strategies have been conducted, however, no single machine learning (ML) modelling has been carried out to predict MICs in N. gonorrhoeae. In this study, we propose a ML based approach that can predict MICs of a specific antibiotic using unitigs sequences data. We retrieved N. gonorrhoeae genomes from European Nucleotide Archive and NCBI and analysed them combined with their respective MIC data for cefixime, ciprofloxacin, and azithromycin and then we constructed unitigs by using de Brujin graphs. We built and compared 35 different ML regression models to predict MICs. Our results demonstrate that RandomForest and CATBoost models showed best performance in predicting MICs of the three antibiotics. The coefficient of determination, R², (a statistical measure of how well the regression predictions approximate the real data points) for cefixime, ciprofloxacin, and azithromycin was 0.75787, 0.77241, and 0.79009 respectively using RandomForest. For CATBoost model, the R² value was 0.74570, 0.77393, and 0.79317 for cefixime, ciprofloxacin, and azithromycin respectively. Lastly, using feature importance, we explore the important genomic regions identified by the models for predicting MICs. The major mutations which are responsible for resistance against these three antibiotics were chosen by ML models as a top feature in case of each antibiotics. CATBoost, DecisionTree, GradientBoosting, and RandomForest regression models chose the same unitigs which are responsible for resistance. This unitigs-based strategy for developing models for MIC prediction, clinical diagnostics, and surveillance can be applicable for other critical bacterial pathogens.

Evolutionary paths to macrolide resistance in a Neisseria commensal converge on ribosomal genes through short sequence duplications

Neisseria commensals are an indisputable source of resistance for their pathogenic relatives. However, the evolutionary paths commensal species take to reduced susceptibility in this genus have been relatively underexplored. Here, we leverage in vitro selection as a powerful screen to identify the genetic adaptations that produce azithromycin resistance (≥ 2 μg/mL) in the Neisseria commensal, N. elongata. Across multiple lineages (n = 7/16), we find mutations that reduce susceptibility to azithromycin converge on the locus encoding the 50S ribosomal L34 protein (rpmH) and the intergenic region proximal to the 30S ribosomal S3 protein (rpsC) through short tandem duplication events. Interestingly, one of the laboratory evolved mutations in rpmH is identical (7LKRTYQ12), and two nearly identical, to those recently reported to contribute to high-level azithromycin resistance in N. gonorrhoeae. Transformations into the ancestral N. elongata lineage confirmed the causality of both rpmH and rpsC mutations. Though most lineages inheriting duplications suffered in vitro fitness costs, one variant showed no growth defect, suggesting the possibility that it may be sustained in natural populations. Ultimately, studies like this will be critical for predicting commensal alleles that could rapidly disseminate into pathogen populations via allelic exchange across recombinogenic microbial genera.

Increasing azithromycin resistance in Neisseria gonorrhoeae due to NG-MAST 12302 clonal spread in Canada, 2015-2018

Objectives: Azithromycin resistant (AZIR) gonorrhea has been steadily increasing in Canada over the past decade which is cause for alarm as azithromycin (AZI) has been part of the combination therapy recommended by the Canadian Guidelines on Sexually Transmitted Infections (CGSTI) since 2012.

Method: Neisseria gonorrhoeae (NG) with AZI MICs ≥ 1 mg/L collected between 2015 and 2018 as part of the Gonococcal Antimicrobial Surveillance Program-Canada underwent antimicrobial susceptibility testing, molecular typing and whole genome sequencing. Regional, demographic and clinical isolation site comparisons were made to aid in our understanding of AZI susceptibility trending.

Results: 3,447 NG with AZI MICs ≥ 1 mg/L were identified in Canada, increasing from 6.3% in 2015 to 26.5% of isolates in 2018. Central Canada had the highest proportion rising from 9.2% in 2015 to 31.2% in 2018. 273 different NG-MAST sequence types were identified among these isolates with ST-12302 the most prevalent (50.9%). Whole genome sequencing identified the Neisseria lactamica -like mosaic mtr locus as the mechanism of AZIR in isolates of ST-12302 and isolates genetically similar (differ by ≤ 5 base pairs) designated as the ST-12302 genogroup, accounting for 65.2% of study isolateswhich were originally identified in central Canada but spread to other regions by 2018.

Conclusion: Genomic analysis indicated that AZIR in Canadian NG expanded rapidly due to clonal spread of the ST-12302 genogroup. The rapid expansion of this AZIR clonal group in all regions of Canada is of concern. CGSTI are currently under review to address the increase in AZIR in Canada.

Global emergence and dissemination of Neisseria gonorrhoeae ST-9363 isolates with reduced susceptibility to azithromycin

Neisseria gonorrhoeae multi-locus sequence type (ST) 9363 core-genogroup isolates have been associated with reduced azithromycin susceptibility (AZMrs) and show evidence of clonal expansion in the U.S. Here we analyze a global collection of ST-9363 core-genogroup genomes to shed light on the emergence and dissemination of this strain. The global population structure of ST-9363 core-genogroup falls into three lineages: Basal, European, and North American; with 32 clades within all lineages. Although, ST-9363 core-genogroup is inferred to have originated from Asia in the mid-19th century; we estimate the three modern lineages emerged from Europe in the late 1970s to early 1980s. The European lineage appears to have emerged and expanded from around 1986 to 1998, spreading into North America and Oceania in the mid-2000s with multiple introductions, along with multiple secondary reintroductions into Europe. Our results suggest two separate acquisition events of mosaic mtrR and mtrR promoter alleles: first during 2009-2011 and again during the 2012-2013 time, facilitating the clonal expansion of this core-genogroup with AZMrs in the U.S. By tracking phylodynamic evolutionary trajectories of clades that share distinct demography as well as population-based genomic statistics, we demonstrate how recombination and selective pressures in the mtrCDE efflux operon granted a fitness advantage to establish ST-9363 as a successful gonococcal lineage in the U.S. and elsewhere. Although it is difficult to pinpoint the exact timing and emergence of this young core-genogroup, it remains critically important to continue monitoring it, as it could acquire additional resistance markers.

Antimicrobial resistance prediction in Neisseria gonorrhoeae: Current status and future prospects

INTRODUCTION

Several nucleic acid amplification tests (NAATs), mostly real-time PCRs, to detect antimicrobial resistance (AMR) determinants and predict AMR in Neisseria gonorrhoeae are promising, and some may be ready to apply at the point-of-care (POC), but important limitations remain with most NAATs. Next-generation sequencing (NGS) can overcome many of these limitations.Areas covered: Recent advances, with main focus on publications since 2017, in the development and use of NAATs and NGS to predict gonococcal AMR for surveillance and clinical use, and pros and cons of these tests as well as future perspectives for appropriate use of molecular AMR prediction for N. gonorrhoeae.Expert Commentary: NAATs and/or NGS for AMR prediction should supplement culture-based AMR surveillance, which will remain because it detects also AMR due to unknown AMR determinants, and translation into POC tests is imperative for the end-goal of individualized treatment, sparing ceftriaxone±azithromycin. Several challenges for direct testing of clinical, especially pharyngeal, specimens and for accurate prediction of cephalosporins and azithromycin resistance, especially using NAATs, remain. The choice of AMR prediction assay needs to carefully consider the intended use of the assay; limitations intrinsic to the AMR prediction technology, algorithms and specific to chosen methodology; specimen types analyzed; and cost-effectiveness.

WHO global antimicrobial resistance surveillance for Neisseria gonorrhoeae 2017-18: a retrospective observational study

BACKGROUND

Gonorrhoea and antimicrobial resistance (AMR) in Neisseria gonorrhoeae are major health concerns globally. Increased global surveillance of gonococcal AMR is essential. We aimed to describe the 2017-18 data from WHO's global gonococcal AMR surveillance, and to discuss priorities essential for the effective management and control of gonorrhoea.

METHODS

We did a retrospective observational study of the AMR data of gonococcal isolates reported to WHO by 73 countries in 2017-18. WHO recommends that each country collects at least 100 gonococcal isolates per year, and that quantitative methods to determine the minimum inhibitory concentration of antimicrobials, interpreted by internationally standardised resistance breakpoints, are used.

FINDINGS

In 2017-18, 73 countries provided AMR data for one or more drug. Decreased susceptibility or resistance to ceftriaxone was reported by 21 (31%) of 68 reporting countries and to cefixime by 24 (47%) of 51 reporting countries. Resistance to azithromycin was reported by 51 (84%) of 61 reporting countries and to ciprofloxacin by all 70 (100%) reporting countries. The annual proportion of decreased susceptibility or resistance across countries was 0-21% to ceftriaxone and 0-22% to cefixime, and that of resistance was 0-60% to azithromycin and 0-100% to ciprofloxacin. The number of countries reporting gonococcal AMR and resistant isolates, and the number of examined isolates, have increased since 2015-16. Surveillance remains scarce in central America and the Caribbean and eastern Europe, and in the WHO African, Eastern Mediterranean, and South-East Asian regions.

INTERPRETATION

In many countries, ciprofloxacin resistance was exceedingly high, azithromycin resistance was increasing, and decreased susceptibility or resistance to ceftriaxone and cefixime continued to emerge. WHO's global surveillance of gonococcal AMR needs to expand internationally to provide imperative data for national and international management guidelines and public health policies. Improved prevention, early diagnosis, treatment of index patients and partners, enhanced surveillance (eg, infection, AMR, treatment failures, and antimicrobial use or misuse), and increased knowledge on antimicrobial selection, stewardship, and pharmacokinetics or pharmacodynamics are essential. The development of rapid, accurate, and affordable point-of-care gonococcal diagnostic tests, new antimicrobials, and gonococcal vaccines is imperative.

FUNDING

None.

Linear regression equations to predict β-lactam, macrolide, lincosamide and fluoroquinolone minimum inhibitory concentrations from molecular antimicrobial resistance determinants in Streptococcus pneumoniae

Antimicrobial resistance in Streptococcus pneumoniae represents a threat to public health and monitoring the dissemination of resistant strains is essential to guiding health policy. Multiple-variable linear regression modeling was used to determine the contributions of molecular antimicrobial resistance determinants to antimicrobial minimum inhibitory concentration (MIC) for penicillin, ceftriaxone, erythromycin, clarithromycin, clindamycin, levofloxacin, and trimethoprim/sulfamethoxazole. Training data sets consisting of Canadian S. pneumoniae isolated from 1995 to 2019 were used to generate multiple-variable linear regression equations for each antimicrobial. The regression equations were then applied to validation data sets of Canadian (n=439) and USA (n=607 and n=747) isolates. The MIC for β-lactam antimicrobials were fully explained by amino acid substitutions in motif regions of the penicillin binding proteins PBP1a, PPB2b, and PBP2x. Accuracy of predicted MICs within one doubling dilution to phenotypically determined MICs for penicillin was 97.4%, ceftriaxone 98.2%; erythromycin 94.8%; clarithromycin 96.6%; clindamycin 98.2%; levofloxacin 100%; and trimethoprim/sulfamethoxazole 98.8%; with an overall sensitivity of 95.8% and specificity of 98.0%. Accuracy of predicted MICs to the phenotypically determined MICs was similar to phenotype-only MIC comparison studies. The ability to acquire detailed antimicrobial resistance information directly from molecular determinants will facilitate the transition from routine phenotypic testing to whole genome sequencing analysis and can fill the surveillance gap in an era of increased reliance on nucleic acid assay diagnostics to better monitor the dynamics of S. pneumoniae.

Prediction of ceftriaxone MIC in Neisseria gonorrhoeae using DNA microarray technology and regression analysis

BACKGROUND

Decreased susceptibility of Neisseria gonorrhoeae to extended-spectrum cephalosporins is a major concern. Elucidation of the phenotypic and genetic characteristics of such isolates is a priority task.

METHODS

We developed a method for predicting the N. gonorrhoeae ceftriaxone susceptibility level (MICcro) by identifying genetic determinants of resistance using low-density hydrogel microarrays and a regression equation. A training dataset, containing 5631 isolates from the Pathogenwatch database and 181 isolates obtained in the Russian Federation during 2018-19, was used to build a regression model. The regression equation was tested on 14 WHO reference strains. Ceftriaxone resistance determinants for the 448 evaluated clinical isolates collected in Russia were identified using microarray analysis, and MICcro values were calculated using the regression equation and compared with those measured by the serial dilution method.

RESULTS

The regression equation for calculating MICcro values included 20 chromosomal resistance determinants. The greatest contributions to the increase in MICcro were shown to be PBP2: Ala-501→Pro, Ala-311→Val, Gly-545→Ser substitutions, Asp(345-346) insertion; and PorB: Gly-120→Arg substitution. The substitutions PBP2: Ala-501→Thr/Val, PorB: Gly-120→Asn/Asp/Lys and PBP1: Leu-421→Pro had weaker effects. For 94.4% of the isolates in the evaluation set, the predicted MICcro was within one doubling dilution of the experimentally determined MICcro. No ceftriaxone-resistant isolates were identified in the analysed samples from Russia, and no interpretative errors were detected in the MICcro calculations.

CONCLUSIONS

The developed strategy for predicting ceftriaxone MIC can be used for the continuous surveillance of known and emerging resistant N. gonorrhoeae isolates.

Recent advances in understanding and combatting Neisseria gonorrhoeae: a genomic perspective

The sexually transmitted infection (STI) gonorrhoea remains a major global public health concern. The World Health Organization (WHO) estimates that 87 million new cases in individuals who were 15 to 49 years of age occurred in 2016. The growing number of gonorrhoea cases is concerning given the rise in gonococci developing antimicrobial resistance (AMR). Therefore, a global action plan is needed to facilitate surveillance. Indeed, the WHO has made surveillance leading to the elimination of STIs (including gonorrhoea) a global health priority. The availability of whole genome sequence data offers new opportunities to combat gonorrhoea. This can be through (i) enhanced surveillance of the global prevalence of AMR, (ii) improved understanding of the population biology of the gonococcus, and (iii) opportunities to mine sequence data in the search for vaccine candidates. Here, we review the current status in Neisseria gonorrhoeae genomics. In particular, we explore how genomics continues to advance our understanding of this complex pathogen.

Genomic Epidemiology of Azithromycin-Nonsusceptible Neisseria gonorrhoeae, Argentina, 2005-2019

Azithromycin-nonsusceptible Neisseria gonorrhoeae strains are an emerging global public health threat. During 2015–2018, the prevalence of azithromycin-nonsusceptible gonococcal infection increased significantly in Argentina. To investigate the genomic epidemiology and resistance mechanisms of these strains, we sequenced 96 nonsusceptible isolates collected in Argentina during 2005–2019. Phylogenomic analysis revealed 2 main clades, which were characterized by a limited geographic distribution, circulating during January 2015–November 2019. These clades included the internationally spreading multilocus sequence types (STs) 1580 and 9363. The ST1580 isolates, which had MICs of 2–4 μg/mL, had mutations in the 23S rRNA. The ST9363 isolates, which had MICs of 2–4 or >256 μg/mL, had mutations in the 23S rRNA, a mosaic mtr locus, or both. Identifying the geographic dissemination and characteristics of these predominant clones will guide public health policies to control the spread of azithromycin-nonsusceptible N. gonorrhoeae in Argentina.

The Accuracy of Molecular Detection Targeting the Mutation C2611T for Detecting Moderate-Level Azithromycin Resistance in Neisseria gonorrhoeae: A Systematic Review and Meta-Analysis

BACKGROUND

Neisseria gonorrhoeae (N. gonorrhoeae) is now recognized as a commonly reported sexually transmitted pathogen, and the increasing drug resistance of N. gonorrhoeae has become a serious public health problem. The accuracy of molecular detection for detecting moderate-level azithromycin resistance is not well-established. We summarized the data from studies of the N. gonorrhoeae 23S rRNA mutation at position 2611 with azithromycin resistance to determine the relationship between the mutation and resistance.

METHODS AND FINDINGS

In this systematic review and meta-analysis, two researchers independently searched six databases for studies with data for the azithromycin minimum inhibitory concentrations (MICs) and the 23S rRNA mutation C2611T of each N. gonorrhoeae isolate. Since the breakpoint of moderate-level resistance to azithromycin (ML-AzmR) was not determined, we divided the moderate level into two groups according to the range of MICs (moderate resistance limited to 2-128 mg/L or 4-128 mg/L) for data extraction. A random-effects model was used to calculate the pooled sensitivity rate, the specificity rate, the pooled positive likelihood ratio (PLR), the negative likelihood ratio (NLR), and the diagnostic odds ratio (DOR). Meta-regression analyses by detection method, isolates sampling (a random sample or not), location, and sample size were performed to explore the possible causes of heterogeneity. The potential publication bias of the included studies was conducted by the Deeks' test. We included 20 studies in our study: 20 studies have data of N. gonorrhoeae with MICs between 2 and 128 mg/L with mutation or without mutation at position 2611(4759 samples), and 14 studies have data of N. gonorrhoeae with MICs between 4 and 128 mg/L (3367 samples). In the group with the moderate level of 2-128 mg/L, the pooled sensitivity rate of the molecular assays was determined to be 71.9% (95% CI, 67.6-74%), the pooled specificity rate was 98.7% (95% CI, 98.2-99.0%), and the DOR ranged from 55.0 to 351.3 (mean, 139.1). In the 4-128 mg/L group, the pooled sensitivity rate was 91.9% (95% CI, 88.9-94.2%), the pooled specificity rate was 95.9% (95% CI, 95.1-96.6%), and the DOR ranged from 41.9 to 364.1 (mean, 123.6).

CONCLUSION

Through this meta-analysis, we found that the C2611T mutation of 23S rRNA is valuable for the molecular diagnostic of moderate-level azithromycin resistance (ML-AzmR) in N. gonorrhoeae, especially when the moderate level is set at 4-128 mg/L. This rapid molecular detection method can be used for the rapid identification of ML-AzmR isolates in the clinic.

Emergence and dissemination of three mild outbreaks of Neisseria gonorrhoeae with high-level resistance to azithromycin in Barcelona, 2016-18

BACKGROUND

Neisseria gonorrhoeae (NG) isolates with high-level azithromycin resistance (HL-AziR) have emerged worldwide in recent decades, threatening the sustainability of current dual-antimicrobial therapy.

OBJECTIVES

This study aimed to characterize the first 16 NG isolates with HL-AziR in Barcelona between 2016 and 2018.

METHODS

WGS was used to identify the mechanisms of antimicrobial resistance, to establish the MLST ST, NG multiantigen sequence typing (NG-MAST) ST and NG sequence typing for antimicrobial resistance (NG-STAR) ST and to identify the clonal relatedness of the isolates with other closely related NG previously described in other countries based on a whole-genome SNP analysis approach. The sociodemographic characteristics of the patients included in the study were collected by comprehensive review of their medical records.

RESULTS

Twelve out of 16 HL-AziR isolates belonged to the MLST ST7823/NG-MAST ST5309 genotype and 4 to MLST ST9363/NG-MAST ST3935. All presented the A2059G mutation in all four alleles of the 23S rRNA gene. MLST ST7823/NG-MAST ST5309 isolates were only identified in men who have sex with women and MLST ST9363/NG-MAST ST3935 were found in MSM. Phylogenomic analysis revealed the presence of three transmission clusters of three different NG strains independently associated with sexual behaviour.

CONCLUSIONS

Our findings support the first appearance of three mild outbreaks of NG with HL-AziR in Spain. These results highlight the continuous capacity of NG to develop antimicrobial resistance and spread among sexual networks. The enhanced resolution of WGS provides valuable information for outbreak investigation, complementing the implementation of public health measures focused on the prevention and dissemination of MDR NG.

Bioinformatics tools used for whole-genome sequencing analysis of Neisseria gonorrhoeae: a literature review

Whole-genome sequencing (WGS) data are well established for the investigation of gonococcal transmission, antimicrobial resistance prediction, population structure determination and population dynamics. A variety of bioinformatics tools, repositories, services and platforms have been applied to manage and analyze Neisseria gonorrhoeae WGS datasets. This review provides an overview of the various bioinformatics approaches and resources used in 105 published studies (as of 30 April 2021). The challenges in the analysis of N. gonorrhoeae WGS datasets, as well as future bioinformatics requirements, are also discussed.

Genomic analysis and antimicrobial resistance of Neisseria gonorrhoeae isolates from Vietnam in 2011 and 2015-16

OBJECTIVES

Antimicrobial resistance (AMR) in Neisseria gonorrhoeae, compromising gonorrhoea treatment, is a threat to reproductive health globally. South-East and East Asia have been major sources of emergence and subsequent international spread of AMR gonococcal strains during recent decades. We investigated gonococcal isolates from 2011 and 2015-16 in Vietnam using AMR testing, WGS and detection of AMR determinants.

METHODS

Two hundred and twenty-nine gonococcal isolates cultured in 2015-16 (n = 121) and 2011 (n = 108) in Vietnam were examined. AMR testing was performed using Etest and WGS with Illumina MiSeq.

RESULTS

Resistance among the 2015-16 isolates was as follows: ciprofloxacin, 100%; tetracycline, 79%; benzylpenicillin, 50%; cefixime, 15%; ceftriaxone, 1%; spectinomycin, 0%; and 5% were non-WT to azithromycin. Eighteen (15%) isolates were MDR. The MIC range for gentamicin was 2-8 mg/L. Among the 2015-16 isolates, 27% (n = 33) contained a mosaic penA allele, while no isolates had a mosaic penA allele in 2011. Phylogenomic analysis revealed introduction after 2011 of two mosaic penA-containing clones (penA-10.001 and penA-34.001), which were related to cefixime-resistant strains spreading in Japan and Europe, and a minor clade (eight isolates) relatively similar to the XDR strain WHO Q.

CONCLUSIONS

From 2011 to 2015-16, resistance in gonococci from Vietnam increased to all currently and previously used antimicrobials except ceftriaxone, spectinomycin and tetracycline. Two mosaic penA-containing clones were introduced after 2011, explaining the increased cefixime resistance. Significantly increased AMR surveillance, antimicrobial stewardship and use of WGS for molecular epidemiology and AMR prediction for gonococcal isolates in Vietnam and other Asian countries are crucial.

Antimicrobial resistance and molecular epidemiological typing of Neisseria gonorrhoeae isolates from Kyrgyzstan in Central Asia, 2012 and 2017

Background

Gonorrhoea and antimicrobial resistance (AMR) in Neisseria gonorrhoeae are significant public health concerns globally. Nearly no gonococcal AMR data are available from Central Asia, and no data from Kyrgyzstan has been published. We examined, for the first time, AMR and molecular epidemiology of N. gonorrhoeae isolates cultured in Kyrgyzstan in 2012 and 2017, in order to inform refinements of the Kyrgyz national gonorrhoea management guidelines.

Methods

N. gonorrhoeae isolates cultured in 2012 (n = 84) and 2017 (n = 72) in Kyrgyzstan were examined. MICs of nine antimicrobials were determined using Etest and, where available, clinical breakpoints from the EUCAST were applied. N. gonorrhoeae multiantigen sequence typing (NG-MAST) was also performed.

Results

The overall resistance levels were high to ciprofloxacin (88.5%), tetracycline (56.9%), benzylpenicillin (39.1%), and kanamycin (4.7%). Resistance to cefixime (0.6%, n = 1 isolate), azithromycin (0.6%, n = 1), and gentamicin (0.6%, n = 1) was rare. No resistance to ceftriaxone or spectinomycin was found. However, the proportion of isolates with decreased susceptibility (MIC = 0.125 mg/L) to ceftriaxone and cefixime was 12.8 and 11.5%, respectively. Gonococcal isolates were assigned 69 sequence types, of which 52 (75.4%) were new.

Conclusions

The gonococcal population in Kyrgyzstan in 2012 and 2017 showed a high genetic diversity. Ceftriaxone, 500–1000 mg, in combination with azithromycin 2 g or doxycycline, particularly when chlamydial infection has not been excluded, should be recommended as empiric first-line treatment. Spectinomycin 2 g could be an alternative treatment, and given with azithromycin 2 g if pharyngeal gonorrhoea has not been excluded. Fluoroquinolones, aminoglycosides, benzylpenicillin, or tetracyclines should not be used for empiric treatment of gonorrhoea in Kyrgyzstan. Timely updating and high compliance to national gonorrhoea treatment guidelines based on quality-assured AMR data is imperative. Expanded and improved gonococcal AMR surveillance in Kyrgyzstan is crucial.

Evidence of Horizontal Gene Transfer of 50S Ribosomal Genes rplB, rplD, and rplY in Neisseria gonorrhoeae

Horizontal gene transfer (HGT) in the penA and multidrug efflux pump genes has been shown to play a key role in the genesis of antimicrobial resistance in Neisseria gonorrhoeae. In this study, we evaluated if there was evidence of HGT in the genes coding for the ribosomal proteins in the Neisseria genus. We did this in a collection of 11,659 isolates of Neisseria, including N. gonorrhoeae and commensal Neisseria species (N. cinerea, N. elongata, N. flavescens, N. mucosa, N. polysaccharea, and N. subflava). Comparative genomic analyses identified HGT events in three genes: rplB, rplD, and rplY coding for ribosomal proteins L2, L4 and L25, respectively. Recombination events were predicted in N. gonorrhoeae and N. cinerea, N. subflava, and N. lactamica were identified as likely progenitors. In total, 2,337, 2,355, and 1,127 isolates possessed L2, L4, and L25 HGT events. Strong associations were found between HGT in L2/L4 and the C2597T 23S rRNA mutation that confers reduced susceptibility to macrolides. Whilst previous studies have found evidence of HGT of entire genes coding for ribosomal proteins in other bacterial species, this is the first study to find evidence of HGT-mediated chimerization of ribosomal proteins.

Antimicrobial resistance in Neisseria gonorrhoeae isolates and gonorrhoea treatment in the Republic of Belarus, Eastern Europe, 2009-2019

Background

Limited antimicrobial resistance (AMR) data for Neisseria gonorrhoeae are available in Eastern Europe. We investigated AMR in N. gonorrhoeae isolates in the Republic of Belarus from 2009 to 2019, antimicrobial treatment recommended nationally, and treatment given to patients with gonorrhoea.

Methods

N. gonorrhoeae isolates (n = 522) cultured in three regions of Belarus in 2009–2019 were examined. Determination of minimum inhibitory concentrations (MICs) of eight antimicrobials was performed using Etest. Resistance breakpoints from the European Committee on Antimicrobial Susceptibility Testing were applied where available. A Nitrocefin test identified β-lactamase production. Gonorrhoea treatment for 1652 patients was also analysed. Statistical significance was determined by the Z-test, Fisher’s exact test, or Mann-Whitney U test with p-values of < 0.05 indicating significance.

Results

In total, 27.8% of the N. gonorrhoeae isolates were resistant to tetracycline, 24.7% to ciprofloxacin, 7.0% to benzylpenicillin, 2.7% to cefixime, and 0.8% to azithromycin. No isolates were resistant to ceftriaxone, spectinomycin, or gentamicin. However, 14 (2.7%) isolates had a ceftriaxone MIC of 0.125 mg/L, exactly at the resistance breakpoint (MIC > 0.125 mg/L). Only one (0.2%) isolate, from 2013, produced β-lactamase. From 2009 to 2019, the levels of resistance to ciprofloxacin and tetracycline were relatively high and stable. Resistance to cefixime was not identified before 2013 but peaked at 22.2% in 2017. Only sporadic isolates with resistance to azithromycin were found in 2009 (n = 1), 2012 (n = 1), and 2018–2019 (n = 2). Overall, 862 (52.2%) patients received first-line treatment according to national guidelines (ceftriaxone 1 g). However, 154 (9.3%) patients received a nationally recommended alternative treatment (cefixime 400 mg or ofloxacin 400 mg), and 636 (38.5%) were given non-recommended treatment.

Conclusions

The gonococcal resistance to ciprofloxacin and tetracycline was high, however, the resistance to azithromycin was low and no resistance to ceftriaxone was identified. Ceftriaxone 1 g can continuously be recommended as empiric first-line gonorrhoea therapy in Belarus. Fluoroquinolones should not be prescribed for treatment if susceptibility has not been confirmed by testing. Timely updating and high compliance with national evidence-based gonorrhoea treatment guidelines based on quality-assured AMR data are imperative. The need for continued, improved and enhanced surveillance of gonococcal AMR in Belarus is evident.

First Case of High-Level Azithromycin-Resistant Neisseria gonorrhoeae in North Carolina

We report on the first high-level azithromycin-resistant Neisseria gonorrhoeae isolate (minimum inhibitory concentration, ≥256 μg/mL) in North Carolina isolated from a pharyngeal swab of a 33-year-old HIV-negative man who has sex with men. In addition, the isolate was found to be susceptible to cefixime, ceftriaxone, and penicillin and resistant to tetracycline. By whole-genome sequencing, the strain was assigned as MLST ST9363, NG-MAST ST5035, and a novel NG-STAR sequence type, ST1993.

A community-driven resource for genomic epidemiology and antimicrobial resistance prediction of Neisseria gonorrhoeae at Pathogenwatch

BACKGROUND

Antimicrobial-resistant (AMR) Neisseria gonorrhoeae is an urgent threat to public health, as strains resistant to at least one of the two last-line antibiotics used in empiric therapy of gonorrhoea, ceftriaxone and azithromycin, have spread internationally. Whole genome sequencing (WGS) data can be used to identify new AMR clones and transmission networks and inform the development of point-of-care tests for antimicrobial susceptibility, novel antimicrobials and vaccines. Community-driven tools that provide an easy access to and analysis of genomic and epidemiological data is the way forward for public health surveillance.

METHODS

Here we present a public health-focussed scheme for genomic epidemiology of N. gonorrhoeae at Pathogenwatch ( https://pathogen.watch/ngonorrhoeae ). An international advisory group of experts in epidemiology, public health, genetics and genomics of N. gonorrhoeae was convened to inform on the utility of current and future analytics in the platform. We implement backwards compatibility with MLST, NG-MAST and NG-STAR typing schemes as well as an exhaustive library of genetic AMR determinants linked to a genotypic prediction of resistance to eight antibiotics. A collection of over 12,000 N. gonorrhoeae genome sequences from public archives has been quality-checked, assembled and made public together with available metadata for contextualization.

RESULTS

AMR prediction from genome data revealed specificity values over 99% for azithromycin, ciprofloxacin and ceftriaxone and sensitivity values around 99% for benzylpenicillin and tetracycline. A case study using the Pathogenwatch collection of N. gonorrhoeae public genomes showed the global expansion of an azithromycin-resistant lineage carrying a mosaic mtr over at least the last 10 years, emphasising the power of Pathogenwatch to explore and evaluate genomic epidemiology questions of public health concern.

CONCLUSIONS

The N. gonorrhoeae scheme in Pathogenwatch provides customised bioinformatic pipelines guided by expert opinion that can be adapted to public health agencies and departments with little expertise in bioinformatics and lower-resourced settings with internet connection but limited computational infrastructure. The advisory group will assess and identify ongoing public health needs in the field of gonorrhoea, particularly regarding gonococcal AMR, in order to further enhance utility with modified or new analytic methods.

Emergence and evolution of antimicrobial resistance genes and mutations in Neisseria gonorrhoeae

BACKGROUND

Antimicrobial resistance in Neisseria gonorrhoeae is a global health concern. Strains from two internationally circulating sequence types, ST-7363 and ST-1901, have acquired resistance to third-generation cephalosporins, mainly due to mosaic penA alleles. These two STs were first detected in Japan; however, the timeline, mechanism, and process of emergence and spread of these mosaic penA alleles to other countries remain unknown.

METHODS

We studied the evolution of penA alleles by obtaining the complete genomes from three Japanese ST-1901 clinical isolates harboring mosaic penA allele 34 (penA-34) dating from 2005 and generating a phylogenetic representation of 1075 strains sampled from 35 countries. We also sequenced the genomes of 103 Japanese ST-7363 N. gonorrhoeae isolates from 1996 to 2005 and reconstructed a phylogeny including 88 previously sequenced genomes.

RESULTS

Based on an estimate of the time-of-emergence of ST-1901 (harboring mosaic penA-34) and ST-7363 (harboring mosaic penA-10), and > 300 additional genome sequences of Japanese strains representing multiple STs isolated in 1996-2015, we suggest that penA-34 in ST-1901 was generated from penA-10 via recombination with another Neisseria species, followed by recombination with a gonococcal strain harboring wildtype penA-1. Following the acquisition of penA-10 in ST-7363, a dominant sub-lineage rapidly acquired fluoroquinolone resistance mutations at GyrA 95 and ParC 87-88, by independent mutations rather than horizontal gene transfer. Data in the literature suggest that the emergence of these resistance determinants may reflect selection from the standard treatment regimens in Japan at that time.

CONCLUSIONS

Our findings highlight how antibiotic use and recombination across and within Neisseria species intersect in driving the emergence and spread of drug-resistant gonorrhea.

The mosaic mtr locus as major genetic determinant of azithromycin resistance of Neisseria gonorrhoeae, Germany, 2018

Within the German Gonococcal Resistance Network (GORENET) Neisseria gonorrhoeae (NG) sample collection, azithromycin-resistant NG isolates increased from 4.3% in 2016 to 9.2% in 2018. We aim to understand this observed increase using whole genome sequencing of NG isolates combined with epidemiological and clinical data. Reduced susceptibility to azithromycin in 2018 was predominately clonal (NG-MAST G12302) and could mainly be accounted to the recently described mosaic-like mtr locus. Our data suggest that, together with horizontal gene transfer of resistance determinants and well-established point mutations, international spread of resistant lineages plays a major role regarding azithromycin resistance in Germany.

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

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.

Molecular Typing of Neisseria gonorrhoeae Clinical Isolates in Russia, 2018-2019: A Link Between penA Alleles and NG-MAST Types

This work aimed to study penA gene polymorphisms in clinical isolates of Neisseria gonorrhoeae collected in Russia in 2018-2019 and the contribution of the penA allele type to susceptibility to β-lactam antibiotics. A total of 182 isolates were analyzed. penA allele types were determined by sequencing, and the minimum inhibitory concentrations (MICs) of benzylpenicillin and ceftriaxone were measured. The influence of genetic factors on MICs was evaluated by regression analysis. All isolates were susceptible to ceftriaxone, and 40.1% of isolates were susceptible to penicillin. Eleven penA allele types were identified. The mosaic type XXXIV penA allele and the Gly120Lys substitution in PorB made the greatest contributions to increasing the ceftriaxone MIC; the presence of the bla_TEM plasmid, Gly120Asp, Ala121Gly/Asn substitutions in PorB, and the adenine deletion in the promoter region of the mtrR gene caused an increase in the penicillin MIC. Among 61 NG-MAST types identified, the most frequent were types 228, 807, 9486, 1993, and 6226. A link between penA alleles and Neisseria gonorrhoeae multi-antigen sequence typing (NG-MAST) types was established. Resistance to two groups of β-lactam antibiotics was associated with non-identical changes in penA alleles. To prevent the emergence of ceftriaxone resistance in Russia, NG-MAST genotyping must be supplemented with penA allele analysis.

Increased power from conditional bacterial genome-wide association identifies macrolide resistance mutations in Neisseria gonorrhoeae

The emergence of resistance to azithromycin complicates treatment of Neisseria gonorrhoeae, the etiologic agent of gonorrhea. Substantial azithromycin resistance remains unexplained after accounting for known resistance mutations. Bacterial genome-wide association studies (GWAS) can identify novel resistance genes but must control for genetic confounders while maintaining power. Here, we show that compared to single-locus GWAS, conducting GWAS conditioned on known resistance mutations reduces the number of false positives and identifies a G70D mutation in the RplD 50S ribosomal protein L4 as significantly associated with increased azithromycin resistance (p-value = 1.08 × 10-11). We experimentally confirm our GWAS results and demonstrate that RplD G70D and other macrolide binding site mutations are prevalent (present in 5.42% of 4850 isolates) and widespread (identified in 21/65 countries across two decades). Overall, our findings demonstrate the utility of conditional associations for improving the performance of microbial GWAS and advance our understanding of the genetic basis of macrolide resistance.

Exploration of the Neisseria Resistome Reveals Resistance Mechanisms in Commensals That May Be Acquired by N. gonorrhoeae through Horizontal Gene Transfer

Nonpathogenic Neisseria transfer mutations encoding antibiotic resistance to their pathogenic relative Neisseria gonorrhoeae. However, the resistance genotypes and subsequent phenotypes of nonpathogens within the genus have been described infrequently. Here, we characterize the minimum inhibitory concentrations (MICs) of a panel of Neisseria (n = 26)—including several commensal species—to a suite of diverse antibiotics. We furthermore use whole genome sequencing and the Comprehensive Antibiotic Resistance Database Resistance Gene Identifier (RGI) platform to predict putative resistance-encoding mutations. Resistant isolates to all tested antimicrobials including penicillin (n = 5/26), ceftriaxone (n = 2/26), cefixime (n = 3/26), tetracycline (n = 10/26), azithromycin (n = 11/26), and ciprofloxacin (n = 4/26) were found. In total, 63 distinct mutations were predicted by RGI to be involved in resistance. The presence of several mutations had clear associations with increased MIC such as DNA gyrase subunit A (gyrA) (S91F) and ciprofloxacin, tetracycline resistance protein (tetM) and 30S ribosomal protein S10 (rpsJ) (V57M) and tetracycline, and TEM-type β-lactamases and penicillin. However, mutations with strong associations to macrolide and cephalosporin resistance were not conclusive. This work serves as an initial exploration into the resistance-encoding mutations harbored by nonpathogenic Neisseria, which will ultimately aid in prospective surveillance for novel resistance mechanisms that may be rapidly acquired by N. gonorrhoeae.

Whole-genome sequencing as an improved means of investigating Neisseria gonorrhoeae treatment failures

Background Although rare, Neisseria gonorrhoeae treatment failures associated with ceftriaxone have been reported. The World Health Organization (WHO) recommends standardised protocols to verify these cases. Two cases from Australia were previously investigated using N. gonorrhoeae multiantigen sequence typing (NG-MAST), which has been used extensively to assess treatment failures. Case 1 pharyngeal isolates were indistinguishable, whereas Case 2 pharyngeal isolates were distinguished based on an 18-bp deletion in the major outer membrane porin encoded by the porB gene, questioning the reliability of NG-MAST results. Here we used whole-genome sequencing (WGS) to reinvestigate Cases 1 and 2, with a view to examining WGS to assess treatment failures.

METHODS

Pre- and post-treatment isolates for each case underwent Illumina sequencing, and the two post-treatment isolates underwent additional long-read sequencing using Pacific Biosciences. Sequence data were interrogated to identify differences at single nucleotide resolution.

RESULTS

WGS identified variation in the pilin subunit encoded by the pilE locus for both cases and the specific 18-bp porB deletion in Case 2 was confirmed, but otherwise the isolates in each case were indistinguishable.

CONCLUSIONS

The WHO recommends standardised protocols for verifying N. gonorrhoeae treatment failures. Case 2 highlights the enhanced resolution of WGS over NG-MAST and emphasises the immediate effect that WGS can have in a direct clinical application for N. gonorrhoeae. Assessing the whole genome compared with two highly variable regions also provides a more confident predictor for determining treatment failure. Furthermore, WGS facilitates rapid comparisons of these cases in the future.

Adaptation to the cervical environment is associated with increased antibiotic susceptibility in Neisseria gonorrhoeae

Neisseria gonorrhoeae is an urgent public health threat due to rapidly increasing incidence and antibiotic resistance. In contrast with the trend of increasing resistance, clinical isolates that have reverted to susceptibility regularly appear, prompting questions about which pressures compete with antibiotics to shape gonococcal evolution. Here, we used genome-wide association to identify loss-of-function (LOF) mutations in the efflux pump mtrCDE operon as a mechanism of increased antibiotic susceptibility and demonstrate that these mutations are overrepresented in cervical relative to urethral isolates. This enrichment holds true for LOF mutations in another efflux pump, farAB, and in urogenitally-adapted versus typical N. meningitidis, providing evidence for a model in which expression of these pumps in the female urogenital tract incurs a fitness cost for pathogenic Neisseria. Overall, our findings highlight the impact of integrating microbial population genomics with host metadata and demonstrate how host environmental pressures can lead to increased antibiotic susceptibility.

Azithromycin susceptibility of Neisseria gonorrhoeae in the USA in 2017: a genomic analysis of surveillance data

Background

The number of cases of gonorrhoea in the USA and worldwide caused by Neisseria gonorrhoeae is increasing (555 608 reported US cases in 2017, and 87 million cases worldwide in 2016). Many countries report declining in vitro susceptibility of azithromycin, which is a concern because azithromycin and ceftriaxone are the recommended dual treatment in many countries. We aimed to identify strain types associated with decreased susceptibility to azithromycin.

Methods

We did a genomic analysis of N gonorrhoeae isolates obtained by the US Gonococcal Isolate Surveillance Project. Isolates were whole-genome sequenced based on decreased susceptibility to azithromycin (minimal inhibitory concentration [MIC] ≥2 μg/mL, using agar dilution antibiotic susceptibility testing) and geographical representation. Bioinformatic analyses established genomic diversity, strain population dynamics, and antimicrobial resistance profiles.

Findings

410 isolates were sorted into more than 20 unique phylogenetic clades. One predominant persistent clade (consisting of 97 isolates) included the most isolates with azithromycin MICs of 2 μg/mL or higher (61 of 97 [63%] vs 59 of 311 [19%]; p<0·0001) and carried a mosaic mtr (multiple transferable resistance) locus (68 of 97 [70%] vs two of 313 [1%]; p<0·0001). Of the remaining 313 isolates, 57 (18%) had decreased susceptibility to azithromycin (MIC ≥4 μg/mL), which was attributed to 23S rRNA variants (56 of 57 [98%]) and formed phylogenetically diverse clades, showing various levels of clonal expansion.

Interpretation

Reduced azithromycin susceptibility was associated with expanding and persistent clades harbouring two well described resistance mechanisms, mosaic mtr locus and 23S rRNA variants. Understanding the role of recombination, particularly within the mtr locus, on the fitness and expansion of strains with decreased susceptibility has important implications for the public health response to minimise gonorrhoea transmission.

Funding

US Centers for Disease Control and Prevention (CDC), CDC Combating Antibiotic Resistant Bacteria initiative, Oak Ridge Institute for Science Education, US Department of Energy/CDC/Emory University, National Institutes of Health, and Biomedical Laboratory Research and Development Service of the US Department of Veterans Affairs.

Investigation of Macrolide Resistance Genotypes in Mycoplasma bovis Isolates from Canadian Feedlot Cattle

Mycoplasma bovis is associated with bovine respiratory disease (BRD) and chronic pneumonia and polyarthritis syndrome (CPPS) in feedlot cattle. No efficacious vaccines for M. bovis exist; hence, macrolides are commonly used to control mycoplasmosis. Whole genome sequences of 126 M. bovis isolates, derived from 96 feedlot cattle over 12 production years, were determined. Antimicrobial susceptibility testing (AST) of five macrolides (gamithromycin, tildipirosin, tilmicosin, tulathromycin, tylosin) was conducted using a microbroth dilution method. The AST phenotypes were compared to the genotypes generated for 23S rRNA and the L4 and L22 ribosomal proteins. Mutations in domains II (nucleotide 748; E. coli numbering) and V (nucleotide 2059 and 2060) of the 23S rRNA (rrl) gene alleles were associated with resistance. All isolates with a single mutation at Δ748 were susceptible to tulathromycin, but resistant to tilmicosin and tildipirosin. Isolates with mutations in both domain II and V (Δ748Δ2059 or Δ748Δ2060) were resistant to all five macrolides. However, >99% of isolates were resistant to tildipirosin and tilmicosin, regardless of the number and positions of the mutations. Isolates with a Δ748 mutation in the 23S rRNA gene and mutations in L4 and L22 were resistant to all macrolides except for tulathromycin.

Genome-based epidemiology and antimicrobial resistance determinants of Neisseria gonorrhoeae isolates with decreased susceptibility and resistance to extended-spectrum cephalosporins in Argentina in 2011-16

OBJECTIVES

Our aim was to describe the molecular epidemiology and antimicrobial resistance determinants of isolates of Neisseria gonorrhoeae with decreased susceptibility and resistance to extended-spectrum cephalosporins (ESCs) in Argentina in 2011-16.

METHODS

Gonococcal isolates (n=158) with decreased susceptibility and resistance to ESCs collected in 2011-16 across Argentina were subjected to WGS and antimicrobial susceptibility testing for six antimicrobials.

RESULTS

In total, 50% of the isolates were resistant to cefixime, 1.9% were resistant to ceftriaxone, 37.3% were resistant to azithromycin and 63.9% of the isolates showed an MDR phenotype. Resistance and decreased susceptibility to ESCs was mainly associated with isolates possessing the mosaic penA-34.001, in combination with an mtrR promoter A deletion, and PorB1b amino acid substitutions G120K/A121N. Phylogenetic analysis revealed two main clades of circulating strains, which were associated with the N. gonorrhoeae multiantigen sequence typing (NG-MAST) ST1407 and closely related STs, and characterized by a high prevalence rate, wide geographical distribution and temporal persistence.

CONCLUSIONS

N. gonorrhoeae isolates with decreased susceptibility and resistance to ESCs in Argentina have emerged and rapidly spread mainly due to two clonal expansions after importation of one or two strains, which are associated with the international MDR NG-MAST ST1407 clone. The identification of the geographical dissemination and characteristics of these predominant clones may help to focus action plans and public health policies to control the spread of ESC resistance in Argentina. Dual antimicrobial therapy (ceftriaxone plus azithromycin) for gonorrhoea needs to be considered in Argentina.

Evidence of Recent Genomic Evolution in Gonococcal Strains With Decreased Susceptibility to Cephalosporins or Azithromycin in the United States, 2014-2016

BACKGROUND

Given the lack of new antimicrobials or a vaccine, understanding the evolutionary dynamics of Neisseria gonorrhoeae is a significant public and global health priority. We investigated the emergence and spread of gonococcal strains with decreased susceptibility to cephalosporins and azithromycin using detailed genomic analyses of gonococcal isolates collected in the United States, 2014-2016.

METHODS

We sequenced genomes of 649 isolates collected through the Gonococcal Isolate Surveillance Project. We examined the genetic relatedness of isolates and assessed associations between clades and various genotypic and phenotypic combinations.

RESULTS

We identified a large and clonal lineage of strains (MLST ST9363) associated with elevated azithromycin minimum inhibitory concentration (AZIem), characterized by a mosaic mtr locus (C substitution in the mtrR promoter, mosaic mtrR and mtrD). Mutations in 23S rRNA were sporadically distributed among AZIem strains. Another clonal group (MLST ST1901) possessed 7 unique PBP2 patterns, and it shared common mutations in other genes associated with cephalosporin resistance.

CONCLUSIONS

Whole-genome sequencing methods can enhance monitoring of antimicrobial resistant gonococcal strains by identifying gonococcal populations containing mutations of concern. These methods could inform the development of point-of-care diagnostic tests designed to determine the specific antibiotic susceptibility profile of a gonococcal infection in a patient.

Equations To Predict Antimicrobial MICs in Neisseria gonorrhoeae Using Molecular Antimicrobial Resistance Determinants

The emergence of Neisseria gonorrhoeae strains that are resistant to azithromycin and extended-spectrum cephalosporins represents a public health threat, that of untreatable gonorrhea infections. Multivariate regression modeling was used to determine the contributions of molecular antimicrobial resistance determinants to the overall antimicrobial MICs for ceftriaxone, cefixime, azithromycin, tetracycline, ciprofloxacin, and penicillin. A training data set consisting of 1,280 N. gonorrhoeae strains was used to generate regression equations which were then applied to validation data sets of Canadian (n = 1,095) and international (n = 431) strains. The predicted MICs for extended-spectrum cephalosporins (ceftriaxone and cefixime) were fully explained by 5 amino acid substitutions in PenA, A311V, A501P/T/V, N513Y, A517G, and G543S; the presence of a disrupted mtrR promoter; and the PorB G120 and PonA L421P mutations. The correlation of predicted MICs within one doubling dilution to phenotypically determined MICs of the Canadian validation data set was 95.0% for ceftriaxone, 95.6% for cefixime, 91.4% for azithromycin, 98.2% for tetracycline, 90.4% for ciprofloxacin, and 92.3% for penicillin, with an overall sensitivity of 99.9% and specificity of 97.1%. The correlations of predicted MIC values to the phenotypically determined MICs were similar to those from phenotype MIC-only comparison studies. The ability to acquire detailed antimicrobial resistance information directly from molecular data will facilitate the transition to whole-genome sequencing analysis from phenotypic testing and can fill the surveillance gap in an era of increased reliance on nucleic acid assay testing (NAAT) diagnostics to better monitor the dynamics of N. gonorrhoeae.

Characterization of antimicrobial resistance genes from Neisseria gonorrhoeae positive remnant Aptima urine specimens

Aim: To ascertain the antimicrobial resistance and strain types (STs) of Neisseria gonorrhoeae from 50 remnant Aptima urine specimens using molecular methods. Methods: Mutations predictive of resistance to six antibiotics were identified in eight genes. STs were determined using NG-MAST and NG-STAR. Results: All eight antimicrobial resistance genes could be characterized in 36 specimens. A total of 17 specimens were predicted to be susceptible to all antibiotics, including ceftriaxone. Decreased susceptibility to cefixime and ciprofloxacin resistance was predicted in 11 specimens (PBP2 type 34.001). Overall, 38/50 specimens were predicted to be ciprofloxacin susceptible; three were azithromycin resistant. Nineteen NG-MAST and 21 NG-STAR STs were noted. Conclusion: Molecular analysis of remnant Aptima specimens enabled the prediction of emerging gonococcal cefixime and azithromycin resistance which would otherwise have been undetected.

Antimicrobial resistance genetic factor identification from whole-genome sequence data using deep feature selection

BACKGROUND

Antimicrobial resistance (AMR) is a major threat to global public health because it makes standard treatments ineffective and contributes to the spread of infections. It is important to understand AMR's biological mechanisms for the development of new drugs and more rapid and accurate clinical diagnostics. The increasing availability of whole-genome SNP (single nucleotide polymorphism) information, obtained from whole-genome sequence data, along with AMR profiles provides an opportunity to use feature selection in machine learning to find AMR-associated mutations. This work describes the use of a supervised feature selection approach using deep neural networks to detect AMR-associated genetic factors from whole-genome SNP data.

RESULTS

The proposed method, DNP-AAP (deep neural pursuit - average activation potential), was tested on a Neisseria gonorrhoeae dataset with paired whole-genome sequence data and resistance profiles to five commonly used antibiotics including penicillin, tetracycline, azithromycin, ciprofloxacin, and cefixime. The results show that DNP-AAP can effectively identify known AMR-associated genes in N. gonorrhoeae, and also provide a list of candidate genomic features (SNPs) that might lead to the discovery of novel AMR determinants. Logistic regression classifiers were built with the identified SNPs and the prediction AUCs (area under the curve) for penicillin, tetracycline, azithromycin, ciprofloxacin, and cefixime were 0.974, 0.969, 0.949, 0.994, and 0.976, respectively.

CONCLUSIONS

DNP-AAP can effectively identify known AMR-associated genes in N. gonorrhoeae. It also provides a list of candidate genes and intergenic regions that might lead to novel AMR factor discovery. More generally, DNP-AAP can be applied to AMR analysis of any bacterial species with genomic variants and phenotype data. It can serve as a useful screening tool for microbiologists to generate genetic candidates for further lab experiments.