Surface-Enhanced Raman Spectroscopy and Multivariate Analysis for Elucidating Mechanisms of Action in Antibacterial Agents

Abstract

Antibiotic and antibacterial-resistant bacteria continue to pose a global-health threat. Understanding the mechanism of action (MoA) of antibacterial agents is crucial for developing precise and novel treatment methods. Traditionally, the MoA of a novel treatment is studied with genome sequencing and mass spectrometry, which are both labor-intensive and costly. In contrast, surface-enhanced Raman spectroscopy (SERS) provides a rapid, sensitive, and noninvasive alternative for analyzing bacterial molecular responses to antibacterial agents. In this study, we employed SERS to analyze the effects of various antibacterial agents on Escherichia coli. We treated E. coli cultures with agents that have different known MoAs, including oxidative stress, metabolic disruption, and membrane lysis. Through partial least-squares (PLS) analysis, we correlated changes in the SERS spectra with bacterial viability, achieving high predictive accuracy (R² > 0.98). From the PLS models, we were able to extract variable importance projection scores, which were used to identify the MoA in subsets of the data. Our results revealed distinct spectral signatures associated with each MoA, demonstrating the potential of SERS to differentiate between different antibacterial treatments. This study highlights the feasibility of using SERS combined with multivariate analysis to rapidly characterize the molecular effects of antibacterial agents even with smaller data sets. By providing a real-time method for monitoring bacterial responses, this SERS approach could accelerate the discovery of novel antibacterial therapies while reducing dependency on more time-consuming and expensive analytical techniques.