Fast and Accurate Prediction of Antibiotic Susceptibility in Clinical Methicillin-Resistant <i>S. aureus</i> Isolates Using ATR-FTIR Spectroscopy: A Model Validation Study
Bibliographic record
Abstract
Diagnosing antimicrobial resistance (AMR) remains critical for improving patient survival rates and treatment outcomes. Current antibiotic susceptibility tests (AST) suffer prolonged turnaround times, necessitating a minimum of 24 h for results. Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy emerges as a promising phenotypic testing method in bacteriology due to its rapid chemical characterization capability. Here, we present an innovative approach utilizing ATR-FTIR spectroscopy for rapid AMR assessment, distinguishing between methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-susceptible S. aureus (MSSA). Our approach focuses on detecting early markers of effective antibiotic action and using these to predict resistance profiles. To identify the earliest time for detection, five MSSA and five MRSA strains were subjected to oxacillin exposure for up to 2 h. We observed discernible molecular changes arising in MSSA as early as 1 h after exposure to oxacillin, which were absent in MRSA strains. Bands at 1624 and 1515 cm –1 were identified as markers of positive drug response in MSSA using principal component analysis (PCA) and were associated with peptidoglycan precursor accumulation upon transpeptidation inhibition. To develop predictive models for determining resistance profiles, we implemented ML-based modeling of the spectral data, reflective of the oxacillin-induced chemical composition changes in MSSA and MRSA. Partial least squares discriminant analysis (PLS-DA) and support vector machines classification (SVM-C) algorithms produced the best results, achieving 100% consistency with minimum inhibitory concentration (MIC) classification. Our models were independently validated by blind testing with 35 clinical strains and demonstrated 100% agreement with resistance profiling determined by MIC. Our study underscores the potential of ATR-FTIR spectroscopy for rapid and accurate AMR assessment, with the capacity to revolutionize diagnostics in combating antibiotic resistance.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".