Genomic trends and emerging antimicrobial resistance in <i>Neisseria gonorrhoeae</i> over two decades in Kenya
Bibliographic record
Abstract
ABSTRACT We investigated the trends and antimicrobial resistance (AMR) of Neisseria gonorrhoeae (NG) in Kenya with whole-genome sequencing (WGS) of isolates collected in 2002–2009 ( n = 108) and 2020–2022 ( n = 110). Phenotypic AMR was confirmed by agar dilution. Predicted minimum inhibitory concentrations (MICs), multi-locus sequence typing (MLST), multi-antigen ST (NG-MAST), NG-STAR, and AMR genetic determinants were determined using WGS and detection of molecular markers. The WGS cgMLST typing used LIN codes. Resistance to penicillin, ciprofloxacin, and tetracycline was common throughout. In 2020–2022, azithromycin resistance ( n = 2) and cephalosporin alert values ( n = 5) were observed. Phylogenetic clusters were congruent with the LIN code lineage, though other typing schemes (MLST, NG-STAR, and NG-MAST) were not as consistent. There were major shifts over time in the lineages and genetic determinants. Circumcision and HIV status were associated with several AMR, housekeeping, metabolism, and iron acquisition genetic determinants. These findings highlight dynamic NG genomic trends, emerging macrolide resistance, and the value of WGS for surveillance. Behavioral and biological factors may contribute to AMR emergence and warrant further investigation. IMPORTANCE This work highlights the significant value of using whole-genome sequencing to track the evolution and epidemiology of gonorrhea over 20 years: (i) we documented the emergence of azithromycin resistance and cephalosporin reduced susceptibility and relationship to genetics of gonorrhea; (ii) by combining epidemiological and genetic data, we found that circumcision and HIV status were linked to specific genetic features of gonorrhea, including those tied to antibiotic resistance; and (iii) we used novel and traditional genetic typing methods to expand and refine the understanding of lineage shifts and genetic determinants, enhancing surveillance and intervention efforts. Some isolates had potential decreasing susceptibility for cephalosporins, highlighting the critical importance of ongoing surveillance and the opportunity for novel resistance gene identification. Studying how gonorrhea strains relate to a person’s immune system, other bacteria (microbiome), and sexual networks could help us understand how certain strains spread and what the potential factors amplifying antimicrobial resistance are.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".