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

penA profile of Neisseria gonorrhoeae in Guangdong, China: Novel penA alleles are related to decreased susceptibility to ceftriaxone or cefixime

BACKGROUND

Resistance to extended-spectrum cephalosporins (ESCs) has become a public health concern with the spread of Neisseria gonorrhoeae and increasing antimicrobial resistance. Mutation of penA, encoding penicillin-binding protein 2, represents a mechanism of ESC resistance. This study sought to assess penA alleles and mutations associated with decreased susceptibility (DS) to ESCs in N. gonorrhoeae.

MATERIALS AND METHODS

In 2021, 347 gonococci were collected in Guangdong, China. Minimum inhibitory concentations (MICs) of ceftriaxone and cefixime were determined, and whole-genome sequencing and phylogenetic analysis were performed. Multi-locus sequence typing (MLST) and conventional resistance determinants such as penA, mtrR, PonA and PorB were analysed. penA was genotyped and sequence-aligned using PubMLST.

RESULTS

Genome-wide phylogenetic analysis revealed that the prevalence of DS to ESCs was highest in Clade 11.1 (100.0%), Clade 2 (66.7%) and Clade 0 (55.7%), and the leading cause was strains with penA-60.001 or new penA alleles in clades. The penA phylogenetic tree is divided into two branches: non-mosaic penA and mosaic penA. The latter contained penA-60.001, penA-10 and penA-34. penA profile analysis indicated that A311V and T483S are closely related to DS to ESCs in mosaic penA. The new alleles NEIS1753_2840 and NEIS1753_2837 are closely related to penA-60.001, with DS to ceftriaxone and cefixime of 100%. NEIS1753_2660, a derivative of penA-10 (A486V), has increased DS to ceftriaxone. NEIS1753_2846, a derivative of penA-34.007 (G546S), has increased DS to cefixime.

CONCLUSION

This study identified critical penA alleles related to elevated MICs, and trends of gonococcus-evolved mutated penA associated with DS to ESCs in Guangdong.

Classification of Neisseria meningitidis genomes with a bag-of-words approach and machine learning

Whole genome sequencing of bacteria is important to enable strain classification. Using entire genomes as an input to machine learning (ML) models would allow rapid classification of strains while using information from multiple genetic elements. We developed a "bag-of-words" approach to encode, using SentencePiece or k-mer tokenization, entire bacterial genomes and analyze these with ML. Initial model selection identified SentencePiece with 8,000 and 32,000 words as the best approach for genome tokenization. We then classified in Neisseria meningitidis genomes the capsule B group genotype with 99.6% accuracy and the multifactor invasive phenotype with 90.2% accuracy, in an independent test set. Subsequently, in silico knockouts of 2,808 genes confirmed that the ML model predictions aligned with our current understanding of the underlying biology. To our knowledge, this is the first ML method using entire bacterial genomes to classify strains and identify genes considered relevant by the classifier.

The oropharynx of men using HIV pre-exposure prophylaxis is enriched with antibiotic resistance genes: A cross-sectional observational metagenomic study

BACKGROUND

Phenotypic studies have found high levels of antimicrobial resistance to cephalosporins, macrolides and fluoroquinolones in commensal Neisseria species in the oropharynx of men who have sex with men (MSM) using HIV pre-exposure prophylaxis (PrEP). These species include Neisseria subflava and Neisseria mucosa. This may represent a risk to pathogens like Neisseria gonorrhoeae which tend to take up antibiotic resistance genes (ARGs) from other bacteria. We aimed to explore to what extent the oropharyngeal resistome of MSM using PrEP differed from the general population.

METHODS

We collected oropharyngeal swabs from 32 individuals of the general population and from 64 MSM using PrEP. Thirty-two MSM had consumed antibiotics in the previous six months, whereas none of the other participants had. Samples underwent shotgun metagenomic sequencing. Sequencing reads were mapped against MEGARes 2.0 to estimate ARG abundance. ARG abundance was compared between groups by zero-inflated negative binomial regression.

FINDINGS

ARG abundance was significantly lower in the general population than in MSM (ratio 0.41, 95% CI 0.26-0.65). More specifically, this was the case for fluoroquinolones (0.33, 95% CI 0.15-0.69), macrolides (0.37, 95% CI 0.25-0.56), tetracyclines (0.41, 95% CI 0.25-0.69), and multidrug efflux pumps (0.11, 95% CI 0.03-0.33), but not for beta-lactams (1.38, 95% CI 0.73-2.61). There were no significant differences in ARG abundance between MSM who had used antibiotics and those that had not.

INTERPRETATION

The resistome of MSM using PrEP is enriched with ARGs, independent of recent antibiotic use. Stewardship campaigns should aim to reduce antibiotic consumption in populations at high risk for STIs.