<i>Neisseria gonorrhoeae</i> antimicrobial susceptibility testing: application of traditional agar dilution to a high-throughput 96-well microtiter assay
Bibliographic record
Abstract
ABSTRACT The global rise in Neisseria gonorrhoeae infections and increasing antimicrobial resistance underscores the urgent need for accessible and efficient antimicrobial susceptibility testing methods. While accurate, the gold standard agar dilution method is labor-intensive and resource-demanding, limiting its practicality for research. To address this, we developed and validated a high-throughput 96-well microtiter assay as a viable alternative for measuring minimum inhibitory concentrations (MIC). In addition, we assessed the use of the simple-defined Kellogg’s supplement compared to the CLSI-recommended complex-defined growth supplement. Using 17 standard laboratory strains with different resistance profiles, we evaluated the assay against azithromycin, ceftriaxone, ciprofloxacin, and gentamicin. Both 96-well microtiter assays demonstrated no major errors for any antimicrobial, with some minor errors with azithromycin and consistent minor errors with gentamicin. Essential agreement (EA) and categorical agreement (CA) ranged from 33% to 100%, with gentamicin contributing the most variability across methods. This study establishes the 96-well microtiter assay with Kellogg’s supplement as a reliable and scalable tool for N. gonorrhoeae antimicrobial susceptibility testing, reducing the time and resources required for resistance profiling. IMPORTANCE The rapid emergence of antimicrobial resistance in Neisseria gonorrhoeae presents a critical challenge for global public health. Accurate and accessible methods for assessing antimicrobial susceptibility are essential for monitoring resistance trends and guiding effective treatment strategies. However, traditional methods, such as agar dilution, are labor-intensive and resource-intensive, limiting their widespread application in research. Our study introduces a 96-well microtiter assay that simplifies and scales up susceptibility testing while maintaining the accuracy of the gold standard. By validating the use of the simpler alternative, Kellogg’s supplement, we further lower the barriers to adoption in research settings. This innovation supports timely and efficient antimicrobial resistance surveillance and enhances the capacity for high-throughput testing of novel therapeutic compounds. By increasing the feasibility of susceptibility testing, this method can potentially improve response strategies against drug-resistant gonorrhea and other fastidious pathogens.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".