New frontiers against antibiotic resistance: A Raman-based approach for rapid detection of bacterial susceptibility and biocide-induced antibiotic cross-tolerance

被引:19
作者
Barzan, Giulia [1 ,2 ]
Sacco, Alessio [1 ,2 ]
Mandrile, Luisa [1 ]
Giovannozzi, Andrea M. [1 ]
Brown, James [3 ]
Portesi, Chiara [1 ]
Alexander, Morgan R. [4 ]
Williams, Paul [3 ]
Hardie, Kim R. [3 ]
Rossi, Andrea M. [1 ]
机构
[1] Ist Nazl Ric Metrol INRiM, Quantum Metrol & Nano Technol Div, Str Cacce 91, I-10135 Turin, Italy
[2] Politecn Torino, Dept Elect & Telecommun, Corso Duca Abruzzi 24, I-10129 Turin, Italy
[3] Univ Nottingham, Sch Life Sci, Ctr Biomol Sci, Nottingham NG7 2RD, England
[4] Univ Nottingham, Sch Pharm, Nottingham NG7 2RD, England
基金
欧盟地平线“2020”;
关键词
Raman spectroscopy; Dielectrophoresis; E; coli; Antibiotic resistance; Ciprofloxacin; Antibiotic susceptibility test; CIPROFLOXACIN;
D O I
10.1016/j.snb.2020.127774
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
To overcome the widespread misuse of antibiotics and reduce the growing problem of multidrug resistance, rapid, sensitive and specific novel methods to determine bacterial antibiotic susceptibility are needed. This study presents a combined dielectrophoresis (DEP) - Raman Spectroscopy (RS) method to obtain direct, real-time measurements of the susceptibility of a suspension of planktonic bacteria without labelling or other time-consuming and intrusive sample preparation processes. Using an in-house constructed DEP-Raman device, we demonstrated the susceptibility of Escherichia coli MG1655 towards the second-generation fluoroquinolone antibiotic ciprofloxacin (CP) after only 1 h of treatment, by monitoring spectral changes in the chemical fingerprint of bacteria related to the mode of action of the drug. Spectral variance was modelled by multivariate techniques and a classification model was calculated to determine bacterial viability in the exponential growth phase at the minimum bactericidal concentration (MBC) over a 3 h time span. Further tests at a sub-minimum inhibitory concentration (MIC) and with a CP-resistant E. coli were carried out to validate the model. The method was then successfully applied for class prediction in a biocide cross-induced tolerance assay that involved pre-treating E. coli with triclosan (TCS), an antimicrobial used in many consumer products. High specificity and adequate sensitivity of the proposed method was thereby demonstrated. Simultaneously, standard microbiological assays based on cell viability, turbidity and fluorescence microscopy, were carried out as reference methods to confirm the observed Raman response.
引用
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页数:8
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