Fast and Accurate
Prediction of Antibiotic Susceptibility
in Clinical Methicillin-Resistant S. aureus Isolates Using ATR-FTIR Spectroscopy: A Model Validation Study
posted on 2025-03-10, 18:34authored byKamila Kochan, Jhih-Hang Jiang, Xenia Kostoulias, Elizabeth Lai, Zack Richardson, Savithri Pebotuwa, Philip Heraud, Bayden R. Wood, Anton Y. Peleg
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.