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Proceedings Paper

Rapid detection of Pseudomonas aeruginosa biomarkers in biological fluids using surface-enhanced Raman scattering
Author(s): Xiaomeng Wu; Jing Chen; Yiping Zhao; Susu M. Zughaier
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Paper Abstract

Pseudomonas aeruginosa (PA) is an opportunistic pathogen that causes major infection not only in Cystic Fibrosis patients but also in chronic obstructive pulmonary disease and in critically ill patients in intensive care units. Successful antibiotic treatment of the infection relies on accurate and rapid identification of the infectious agents. Conventional microbiological detection methods usually take more than 3 days to obtain accurate results. We have developed a rapid diagnostic technique based on surface-enhanced Raman scattering to directly identify PA from biological fluids. P. aeruginosa strains, PAO1 and PA14, are cultured in lysogeny broth, and the SERS spectra of the broth show the signature Raman peaks from pyocyanin and pyoverdine, two major biomarkers that P. aeruginosa secretes during its growth, as well as lipopolysaccharides. This provides the evidence that the presence of these biomarkers can be used to indicate P. aeruginosa infection. A total of 22 clinical exhaled breath condensates (EBC) samples were obtained from subjects with CF disease and from non-CF healthy donors. SERS spectra of these EBC samples were obtained and further analyzed by both principle component analysis and partial least square-discriminant analysis (PLS-DA). PLS-DA can discriminate the samples with P. aeruginosa infection and the ones without P. aeruginosa infection at 99.3% sensitivity and 99.6% specificity. In addition, this technique can also discriminate samples from subject with CF disease and healthy donor with 97.5% sensitivity and 100% specificity. These results demonstrate the potential of using SERS of EBC samples as a rapid diagnostic tool to detect PA infection.

Paper Details

Date Published: 22 May 2014
PDF: 10 pages
Proc. SPIE 9107, Smart Biomedical and Physiological Sensor Technology XI, 91070A (22 May 2014); doi: 10.1117/12.2053156
Show Author Affiliations
Xiaomeng Wu, The Univ. of Georgia (United States)
Jing Chen, The Univ. of Georgia (United States)
Yiping Zhao, The Univ. of Georgia (United States)
Susu M. Zughaier, Emory Univ. School of Medicine (United States)

Published in SPIE Proceedings Vol. 9107:
Smart Biomedical and Physiological Sensor Technology XI
Brian M. Cullum; Eric S. McLamore, Editor(s)

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