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Open AccessArticle

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

1
Department of Laboratory Medicine, China Medical University Hospital, No. 2 Yu-Der Rd, North district, Taichung 40447, Taiwan
2
Department of Medical Laboratory Science and Biotechnology, China Medical University, No. 49, Hsueh-Shih Rd, North District, Taichung 40402, Taiwan
3
College of Medicine, China Medical University, Taiwan, No. 49, Hsueh-Shih Rd, North District, Taichung 40402, Taiwan
4
Division of Nephrology, China Medical University Hospital, No. 2 Yu-Der Rd, North district, Taichung 40447, Taiwan
5
Division of Nephrology, Asia University Hospital, No. 222, Fuxin Road, Wufeng District, Taichung 41354, Taiwan
*
Author to whom correspondence should be addressed.
Molecules 2018, 23(12), 3374; https://doi.org/10.3390/molecules23123374
Received: 15 November 2018 / Revised: 13 December 2018 / Accepted: 18 December 2018 / Published: 19 December 2018
(This article belongs to the Special Issue Raman Spectroscopy: A Spectroscopic 'Swiss-Army Knife')
(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. View Full-Text
Keywords: urinary tract infection; Raman spectroscopy; SERS urinary tract infection; Raman spectroscopy; SERS
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MDPI and ACS Style

Tien, N.; Lin, T.-H.; Hung, Z.-C.; Lin, H.-S.; Wang, I.-K.; Chen, H.-C.; Chang, C.-T. Diagnosis of Bacterial Pathogens in the Urine of Urinary-Tract-Infection Patients Using Surface-Enhanced Raman Spectroscopy. Molecules 2018, 23, 3374.

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