The distribution and spread of susceptible and resistant Neisseria gonorrhoeae across demographic groups in a major metropolitan center

The scope of the antimicrobial resistance challenge

Each year, an estimated 7·7 million deaths are attributed to bacterial infections, of which 4.95 million are associated with drug-resistant pathogens, and 1·27 million are caused by bacterial pathogens resistant to the antibiotics available. Access to effective antibiotics when indicated prolongs life, reduces disability, reduces health-care expenses, and enables access to other life-saving medical innovations. Antimicrobial resistance undoes these benefits and is a major barrier to attainment of the Sustainable Development Goals, including targets for newborn survival, progress on healthy ageing, and alleviation of poverty. Adverse consequences from antimicrobial resistance are seen across the human life course in both health-care-associated and community-associated infections, as well as in animals and the food chain. The small set of effective antibiotics has narrowed, especially in resource-poor settings, and people who are very young, very old, and severely ill are particularly susceptible to resistant infections. This paper, the first in a Series on the challenge of antimicrobial resistance, considers the global scope of the problem and how it should be measured. Robust and actionable data are needed to drive changes and inform effective interventions to contain resistance. Surveillance must cover all geographical regions, minimise biases towards hospital-derived data, and include non-human niches.

Navigating the network: a narrative overview of AMR surveillance and data flow in the United States

The antimicrobial resistance (AMR) surveillance landscape in the United States consists of a data flow that starts in the clinical setting and is maintained by a network of national and state public health laboratories. These organizations are well established, with robust methodologies to test and confirm antimicrobial susceptibility. Still, the bridge that guides the flow of data is often one directional and caught in a constant state of rush hour that can only be refined with improvements to infrastructure and automation in the data flow. Moreover, there is an absence of information in the literature explaining the processes clinical laboratories use to coalesce and share susceptibility test data for AMR surveillance, further complicated by variability in testing procedures. This knowledge gap limits our understanding of what is needed to improve and streamline data sharing from clinical to public health laboratories. Successful models of AMR surveillance display attributes like 2-way communication between clinical and public health laboratories, centralized databases, standardized data, and the use of electronic health records or data systems, highlighting areas of opportunity and improvement. This article explores the roles and processes of the organizations involved in AMR surveillance in the United States and identifies current knowledge gaps and opportunities to improve communication between them through standardization, communication, and modernization of data flow.

Gonorrhoea on the rise in Denmark since 2022: distinct clones drive increase in heterosexual individuals

A surge in gonorrhoea in Denmark has occurred since 2022, a 46% increase from 2021. National surveillance, leveraging mandatory reporting and epidemiological data, highlights three distinct clades linked to heterosexual transmission. Despite the rise, these exhibit high susceptibility, contrasting MSM-associated strains. Geographical hotspots and age-specific patterns further illuminate transmission dynamics. The combination of genomic and epidemiological data provides novel insights into the evolving landscape of gonorrhoea, indicating potential shifts in infection dynamics and transmissibility.

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.

CanB is a metabolic mediator of antibiotic resistance in Neisseria gonorrhoeae

The evolution of the obligate human pathogen Neisseria gonorrhoeae has been shaped by selective pressures from diverse host niche environments and antibiotics. The varying prevalence of antibiotic resistance across N. gonorrhoeae lineages suggests that underlying metabolic differences may influence the likelihood of acquisition of specific resistance mutations. We hypothesized that the requirement for supplemental CO₂, present in approximately half of isolates, reflects one such example of metabolic variation. Here, using a genome-wide association study and experimental investigations, we show that CO₂ dependence is attributable to a single substitution in a β-carbonic anhydrase, CanB. CanB^19E is necessary and sufficient for growth in the absence of CO₂, and the hypomorphic CanB^19G variant confers CO₂ dependence. Furthermore, ciprofloxacin resistance is correlated with CanB^19G in clinical isolates, and the presence of CanB^19G increases the likelihood of acquisition of ciprofloxacin resistance. Together, our results suggest that metabolic variation has affected the acquisition of fluoroquinolone resistance.

Decreased thermal niche breadth as a trade-off of antibiotic resistance

Evolutionary theory predicts that adaptations, including antibiotic resistance, should come with associated fitness costs; yet, many resistance mutations seemingly contradict this prediction by inducing no growth rate deficit. However, most growth assays comparing sensitive and resistant strains have been performed under a narrow range of environmental conditions, which do not reflect the variety of contexts that a pathogenic bacterium might encounter when causing infection. We hypothesized that reduced niche breadth, defined as diminished growth across a diversity of environments, can be a cost of antibiotic resistance. Specifically, we test whether chloramphenicol-resistant Escherichia coli incur disproportionate growth deficits in novel thermal conditions. Here we show that chloramphenicol-resistant bacteria have greater fitness costs at novel temperatures than their antibiotic-sensitive ancestors. In several cases, we observed no resistance cost in growth rate at the historic temperature but saw diminished growth at warmer and colder temperatures. These results were consistent across various genetic mechanisms of resistance. Thus, we propose that decreased thermal niche breadth is an under-documented fitness cost of antibiotic resistance. Furthermore, these results demonstrate that the cost of antibiotic resistance shifts rapidly as the environment changes; these context-dependent resistance costs should select for the rapid gain and loss of resistance as an evolutionary strategy.

The antimicrobial resistance landscape of Neisseria gonorrhoeae in New Zealand from November 2018 to March 2019 and the role of sexual orientation in transmission

The increasing use of culture independent diagnostic testing for the diagnosis of Neisseria gonorrhoeae infection has led to gaps in surveillance of antimicrobial resistance (AMR) rates due to limited availability of cultures. Our study reports the findings of a second national survey of N. gonorrhoeae in New Zealand, utilizing whole-genome sequencing (WGS) to study the population structure, prevalence of AMR, epidemiology and transmission of gonorrhoea isolates. We analysed 314 isolates and found a strong correlation between carriage of acquired resistance genes or chromosomal point mutations and phenotypic susceptibility testing results. Overall, the New Zealand rates of azithromycin resistance and decreased susceptibility to ceftriaxone remain lower than in most countries, which are part of the World Health Organization (WHO) Global Gonococcal Antimicrobial Surveillance Programme (GASP). The phylogeny provides evidence of a diverse population significantly associated with sexual behaviour groups. Transmission clustering with a ten single nucleotide polymorphism (SNP) cut-off identified 49 clusters, of which ten were solely associated with men who have sex with men (MSM), whereas remaining clusters included heterosexual patients, as well as MSM, suggesting that bridging of sexual networks is occurring. Utilizing pairwise SNP differences between isolates of the same sequence types we determined genetic variation for the three typing schemes used in this study [Multi locus sequence typing (MLST), multi-antigen sequence typing (NG-MAST), and sequence typing for antimicrobial resistance (NG-STAR)]. A median of 0.0 to 52.5 pairwise SNP differences within a single NG-STAR sequence type underlines previous findings of the superiority of the NG-STAR typing scheme in terms of genomic inherency. With our analysis incorporating epidemiological and genomic data, we were able to show a comprehensive overview of the N. gonorrhoeae population circulating in New Zealand, focussing on AMR and transmission within sexual networks. Regular surveillance studies to understand the origin, evolution and spread of AMR for gonorrhoea remain necessary to make informed decisions about public health guidelines, as the internationally rising rates of ceftriaxone and azithromycin resistance have already led to adaptation of current treatment guidelines in the UK and the USA, highlighting the importance of regular surveillance in individual countries.

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.

Identification of bile acid and fatty acid species as candidate rapidly bactericidal agents for topical treatment of gonorrhoea

BACKGROUND

Novel therapeutic strategies are urgently needed for Neisseria gonorrhoeae, given its increasing antimicrobial resistance. Treatment of oropharyngeal N. gonorrhoeae infections has proven particularly challenging, with most reported treatment failures of the first-line drug ceftriaxone occurring at this site and lower cure rates in recent trials of new antibiotics reported for oropharyngeal infections compared with other sites of infection. However, the accessibility of the oropharynx to topical therapeutics provides an opportunity for intervention. Local delivery of a therapeutic at a high concentration would enable the use of non-traditional antimicrobial candidates, including biological molecules that exploit underlying chemical sensitivities of N. gonorrhoeae but lack the potency or pharmacokinetic profiles required for effective systemic administration.

METHODS

Two classes of molecules that are thought to limit gonococcal viability in vivo, bile acids and short- and medium-chain fatty acids, were examined for rapid bactericidal activity.

RESULTS

The bile acids deoxycholic acid (DCA) and chenodeoxycholic acid (CDCA), but not other bile acid species, exerted extremely rapid bactericidal properties against N. gonorrhoeae, reducing viability more than 100 000-fold after 1 min. The short-chain fatty acids formic acid and hexanoic acid shared this rapid bactericidal activity. All four molecules are effective against a phylogenetically diverse panel of N. gonorrhoeae strains, including clinical isolates with upregulated efflux pumps and resistance alleles to the most widely used classes of existing antimicrobials. DCA and CDCA are both approved therapeutics for non-infectious indications and are well-tolerated by cultured epithelial cells.

CONCLUSIONS

DCA and CDCA are attractive candidates for further development as anti-gonococcal agents.

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.

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.

Draft Genome Sequences of Three Penicillin-Resistant Neisseria gonorrhoeae Strains Isolated in Cincinnati, Ohio, in 1994

Here, we report the draft genome sequences of three penicillin-resistant Neisseria gonorrhoeae isolates. We include associated data on MICs and genetic relationships to other N. gonorrhoeae strains collected from across the United States. Resistance mutations known to contribute to reduced penicillin susceptibility are annotated in each genome.

Here, we report the draft genome sequences of three penicillin-resistant Neisseria gonorrhoeae isolates. We include associated data on MICs and genetic relationships to other N. gonorrhoeae strains collected from across the United States. Resistance mutations known to contribute to reduced penicillin susceptibility are annotated in each genome.

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.