Urinary tract infection (UTI) multi-bacteria multi-antibiotic testing using surface enhanced Raman spectroscopy (SERS)

2013 ◽  
Author(s):  
Katerina Hadjigeorgiou ◽  
Evdokia Kastanos ◽  
Costas Pitris
Keyword(s):  
Raman Spectroscopy ◽  
Urinary Tract Infection ◽  
Urinary Tract ◽  
Tract Infection ◽  
Surface Enhanced Raman Spectroscopy ◽  
Surface Enhanced ◽  
Surface Enhanced Raman

scholarly journals Diagnosis of Bacterial Pathogens in the Urine of Urinary-Tract-Infection Patients Using Surface-Enhanced Raman Spectroscopy

Molecules ◽  
2018 ◽  
Vol 23 (12) ◽  
pp. 3374 ◽  
Author(s):  
Ni Tien ◽  
Tzu-Hsien Lin ◽  
Zen-Chao Hung ◽  
Hsiu-Shen Lin ◽  
I-Kuan Wang ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Urinary Tract Infection ◽  
Raman Spectrum ◽  
Urinary Tract ◽  
Tract Infection ◽  
Surface Enhanced Raman Spectroscopy ◽  
Bacteria Identification ◽  
Surface Enhanced ◽  
Surface Enhanced Raman ◽  
Recognition Software

(1) Background: surface-enhanced Raman spectroscopy (SERS) is a novel method for bacteria identification. However, reported applications of SERS in clinical diagnosis are limited. In this study, we used cylindrical SERS chips to detect urine pathogens in urinary tract infection (UTI) patients. (2) Methods: Urine samples were retrieved from 108 UTI patients. A 10 mL urine sample was sent to conventional bacterial culture as a reference. Another 10 mL urine sample was loaded on a SERS chip for bacteria identification and antibiotic susceptibility. We concentrated the urine specimen if the intensity of the Raman spectrum required enhancement. The resulting Raman spectrum was analyzed by a recognition software to compare with spectrum-form reference bacteria and was further confirmed by principal component analysis (PCA). (3) Results: There were 97 samples with single bacteria species identified by conventional urine culture and, among them, 93 can be successfully identified by using SERS without sample concentration. There were four samples that needed concentration for bacteria identification. Antibiotic susceptibility can also be found by SERS. There were seven mixed flora infections found by conventional culture, which can only be identified by the PCA method. (4) Conclusions: SERS can be used in the diagnosis of urinary tract infection with the aid of the recognition software and PCA.

Bacterial detection and differentiation via direct volatile organic compound sensing with surface enhanced Raman spectroscopy

2017 ◽  
Author(s):  
Caitlin S. DeJong ◽  
David I. Wang ◽  
Aleksandr Polyakov ◽  
Anita Rogacs ◽  
Steven J. Simske ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Bacterial Infections ◽  
Direct Detection ◽  
Point Of Care ◽  
Surface Enhanced Raman Spectroscopy ◽  
E Coli ◽  
Recent Emergence ◽  
Surface Enhanced ◽  
Volatile Organic ◽  
Surface Enhanced Raman

Through the direct detection of bacterial volatile organic compounds (VOCs), via surface enhanced Raman spectroscopy (SERS), we report here a reconfigurable assay for the identification and monitoring of bacteria. We demonstrate differentiation between highly clinically relevant organisms: <i>Escherichia coli</i>, <i>Enterobacter cloacae</i>, and <i>Serratia marcescens</i>. This is the first differentiation of bacteria via SERS of bacterial VOC signatures. The assay also detected as few as 10 CFU/ml of <i>E. coli</i> in under 12 hrs, and detected <i>E. coli</i> from whole human blood and human urine in 16 hrs at clinically relevant concentrations of 10<sup>3</sup> CFU/ml and 10<sup>4</sup> CFU/ml, respectively. In addition, the recent emergence of portable Raman spectrometers uniquely allows SERS to bring VOC detection to point-of-care settings for diagnosing bacterial infections.

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