Literature DB >> 27485760

Diagnosis of bacterial pathogens in the dialysate of peritoneal dialysis patients with peritonitis using surface-enhanced Raman spectroscopy.

Ni Tien1, Hung-Chih Chen2, Shiow-Lan Gau3, Tzu-Hsien Lin4, Hsiu-Shen Lin1, Bang-Jau You5, Po-Chuan Tsai4, I-Ru Chen2, Ming-Fan Tsai6, I-Kuan Wang2, Chao-Jung Chen7, Chiz-Tzung Chang8.   

Abstract

BACKGROUND: Bacterial peritonitis is the most common cause of peritoneal dialysis (PD) therapy drop-out. A quick and accurate diagnosis of the bacterial pathogen can reduce the PD drop-out rate. Surface-enhanced Raman spectroscopy (SERS) can rapidly identify bacteria using chips coated with nano-sized metal particles.
METHODS: Known bacteria were loaded in the SERS-chips and illuminated with laser light to establish a reference Raman spectra library. Dialysate from PD peritonitis patients was concentrated by centrifuge and examined with the same SERS, and the resulting Raman spectra were compared with library spectra for bacteria identification. Principal component analysis was used for further confirmation. The same batches of dialysate were sent to routine culture as a reference bacteria identification method. The results of the 2 identification methods were compared.
RESULTS: A total of 43 paired-samples were sent for study. There were 37 samples with bacteria identified but 6 were culture-negative by the reference method. 31 bacteria were identified in paired-samples by SERS, among which, 29 bacteria were exactly the same as those identified by the reference method. Bacteria not included in the reference library spectra cannot be identified.
CONCLUSIONS: SERS techniques can rapidly identify bacterial pathogens in the dialysate of PD peritonitis patients.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Dialysate; Peritoneal dialysis; Peritonitis; Principal component analysis; Raman spectroscopy; Surface-enhanced Raman spectroscopy

Mesh:

Year:  2016        PMID: 27485760     DOI: 10.1016/j.cca.2016.07.026

Source DB:  PubMed          Journal:  Clin Chim Acta        ISSN: 0009-8981            Impact factor:   3.786


  4 in total

1.  Rapid identification of staphylococci by Raman spectroscopy.

Authors:  Katarína Rebrošová; Martin Šiler; Ota Samek; Filip Růžička; Silvie Bernatová; Veronika Holá; Jan Ježek; Pavel Zemánek; Jana Sokolová; Petr Petráš
Journal:  Sci Rep       Date:  2017-11-01       Impact factor: 4.379

Review 2.  Detection and Characterization of Antibiotic-Resistant Bacteria Using Surface-Enhanced Raman Spectroscopy.

Authors:  Kaidi Wang; Shenmiao Li; Marlen Petersen; Shuo Wang; Xiaonan Lu
Journal:  Nanomaterials (Basel)       Date:  2018-09-26       Impact factor: 5.076

Review 3.  Raman Spectroscopy-A Novel Method for Identification and Characterization of Microbes on a Single-Cell Level in Clinical Settings.

Authors:  Katarina Rebrosova; Ota Samek; Martin Kizovsky; Silvie Bernatova; Veronika Hola; Filip Ruzicka
Journal:  Front Cell Infect Microbiol       Date:  2022-04-22       Impact factor: 6.073

4.  Repeated centrifuging and washing concentrates bacterial samples in peritoneal dialysis for optimal culture: an original article.

Authors:  Ni Tien; Bang-Jau You; Hsuan-Jen Lin; Chieh-Ying Chang; Che-Yi Chou; Hsiu-Shen Lin; Chiz-Tzung Chang; Charles C N Wang; Hung-Chih Chen
Journal:  BMC Microbiol       Date:  2020-11-27       Impact factor: 3.605

  4 in total

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