Antimicrobial Resistance Studies Using Raman Spectroscopy on Clinically Relevant Bacterial Strains

环丙沙星 抗生素 化学 庆大霉素 抗生素耐药性 抗菌剂 微生物学 拉曼光谱 美罗培南 鲍曼不动杆菌 细菌 生物 铜绿假单胞菌 遗传学 光学 物理
作者
Saumya Singh,Taru Verma,Balaram Khamari,Eswarappa Pradeep Bulagonda,Dipankar Nandi,Siva Umapathy
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:95 (30): 11342-11351 被引量:26
标识
DOI:10.1021/acs.analchem.3c01453
摘要

There has been a steep rise in the emergence of antibiotic-resistant bacteria in the past few years. A timely diagnosis can help in initiating appropriate antibiotic therapy. However, conventional techniques for diagnosing antibiotic resistance are time-consuming and labor-intensive. Therefore, we investigated the potential of Raman spectroscopy as a rapid surveillance technology for tracking the emergence of antibiotic resistance. In this study, we used Raman spectroscopy to differentiate clinical isolates of antibiotic-resistant and -sensitive bacteria of Escherichia coli, Acinetobacter baumannii, and Enterobacter species. The spectra were collected with or without exposure to various antibiotics (ciprofloxacin, gentamicin, meropenem, and nitrofurantoin), each having a distinct mechanism of action. Ciprofloxacin- and meropenem-treated sensitive strains showed a decrease in the intensity of Raman bands associated with DNA (667, 724, 785, 1378, 1480, and 1575 cm-1) and proteins (640 and 1662 cm-1), coupled with an increase in the intensity of lipid bands (891, 960, and 1445 cm-1). Gentamicin- and nitrofurantoin-treated sensitive strains showed an increase in the intensity of nucleic acid bands (668, 724, 780, 810, 1378, 1480, and 1575 cm-1) while a decrease in the intensity of protein bands (640, 1003, 1606, and 1662 cm-1) and the lipid band (1445 cm-1). The Raman spectral changes observed in the antibiotic-resistant strains were opposite to that of antibiotic-sensitive strains. The Raman spectral data correlated well with the antimicrobial susceptibility test results. The Raman spectral dataset was used for partial least-squares (PLS) analysis to validate the biomarkers obtained from the univariate analysis. Overall, this study showcases the potential of Raman spectroscopy for detecting antibiotic-resistant and -sensitive bacteria.
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