Monitoring the Mode of Action of Antibiotics Using Raman Spectroscopy:  Investigating Subinhibitory Effects of Amikacin on Pseudomonas aeruginosa

Abstract

During the last 20 years the rate at which new antimicrobial agents are produced has decreased dramatically, with concomitant increase in the number of pathogens that are becoming multidrug resistant. Together these have created a patient healthcare risk and this is of great concern. A crucial aspect for the discovery of new antibiotics is the development of new techniques that allow rapid and accurate characterization of the mode of action of the pharmacophore. In this work UV resonance Raman (UVRR) spectroscopy has been developed to monitor the concentration effect of antibiotics on bacterial cells. UVRR was conducted at 244 nm and spectra were collected in typically 60 s. Supervised multivariate analysis and 2D correlation spectroscopy were used to evaluate whether the UVRR spectra contained valuable information that could be used to study the mode of action of antibiotics. The clustering pattern in the discriminant factors space correlated directly to the concentration of amikacin, and partial least squares (PLS) regression analysis of the UVRR spectra was able to predict the concentration of amikacin to which bacterial cells had been exposed. 2D correlation spectroscopy contour maps indicated that spectral changes due to the presence of amikacin in the growth media occur according to the known mode of action of the studied antibiotic. Therefore, we conclude that UVRR spectroscopy, when coupled with chemometrics and 2D correlation spectroscopy, constitutes a powerful approach for the development and screening of new antibiotics.

Phenotypic Profiling of Antibiotic Response Signatures in Escherichia coli Using Raman Spectroscopy

“…Raman spectroscopy has been used with a similar excitation wavelength to study the effects of the protein synthesis inhibitor amikacin on Pseudomonas aeruginosa. As the concentration of amikacin was increased, the intensity of protein-related Raman peaks decreased, whereas the intensity of nucleic acid bands increased, consistent with the mechanism of action of amikacin (29). Similar results were reported, as Raman spectroscopy was used to monitor the relative protein and DNA content of individual E. coli cells treated with cefazolin (18).…”

“…The authors found the resulting Raman spectra contained spectral features suggesting higher lipid and RNA content and lower cytochrome content in E. coli harboring the plasmid. In addition, Raman spectroscopy has been used to monitor the metabolic state under antibiotic stress (18,(27)(28)(29). For example, Neugebauer et al (28) used Raman spectroscopy with a 244-nm excitation wavelength to track the ratio of protein to nucleic acids during the growth of Bacillus pumilus treated with ciprofloxacin.…”

“…This technique is often referred to as "laser tweezers" Raman spectroscopy (30). Finally, it has been suggested that Raman spectroscopy could provide critical insight into the mechanisms of action of different antibiotics (27,29,30). For example, Moritz et al (30) used laser tweezers Raman spectroscopy to study the response of E. coli to penicillin G-streptomycin and cefazolin.…”

Investigating Antibacterial Effects of Garlic (Allium sativum) Concentrate and Garlic-Derived Organosulfur Compounds on Campylobacter jejuni by Using Fourier Transform Infrared Spectroscopy, Raman Spectroscopy, and Electron Microscopy

“…Bacteria can be identified within 6 h by Raman spectroscopy and 8 h by infrared spectroscopy (9,22,29). Recently, these spectroscopic methods have been intensively applied to study bacterial injury and inactivation by various treatments, such as bacteriocin (8), antibiotics (28,33,40), heat (3,4), and sonication (27). Infrared spectroscopy is useful for bulk bacterial detection (the detection limit is ϳ10 4 to 10 5 CFU/ml) (12), while Raman spectroscopy can potentially detect single bacterial cells (46), especially when a nanosubstrate is employed to signal enhancement, a technique called surface-enhanced Raman spectroscopy (SERS) (13).…”

“…The selected unrelated principal components (PCs) are plotted and visualized in cluster forms (18). DFA can construct branched dendrogram structures using prior knowledge of the composition of a biological sample (28). SIMCA is a supervised classification method.…”