Rapid identification of Candida albicans based on Raman spectral biosensing technology

Yong Li Pan, Tzyy Schiuan Yang, Tsung Chain Chang, Hsien-Chang Chang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Traditional identification methods of pathogenic Candida albicans are time-consuming due to the long-term incubation. The purpose of this study is to develop a noninvasive biomolecular sensing technology for rapid identification of Candida albicans. Surface enhanced Raman scattering (SERS) based on colloidal sliver was used to rapidly detect specific molecules on the surface of cells cultured on SDA plate. A homemade fluidic chamber was fabricated to enlarge the random sampling area, increase the path length and avoid sampling error caused by disturbance or evaporation. SERS signal was detected by a 514 nm laser with a 10x objective lens. The exposure time of CCD was 10 s. Normalization, second derivative, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were also integrated for discrimination of Candida albicans by spectral patterns precisely. The results show that SERS can be used to detect high-concentration suspended cells of Candida albicans. Candida albicans can be discriminated to genus and species level by principal component analysis and hierarchical cluster analysis of high frequency features of SERS spectral patterns.

Original languageEnglish
Title of host publication2009 IEEE 3rd International Conference on Nano/Molecular Medicine and Engineering, NANOMED 2009
Pages120-124
Number of pages5
DOIs
Publication statusPublished - 2009 Dec 1
Event2009 IEEE 3rd International Conference on Nano/Molecular Medicine and Engineering, NANOMED 2009 - Tainan, Taiwan
Duration: 2009 Oct 182009 Oct 21

Publication series

Name2009 IEEE 3rd International Conference on Nano/Molecular Medicine and Engineering, NANOMED 2009

Other

Other2009 IEEE 3rd International Conference on Nano/Molecular Medicine and Engineering, NANOMED 2009
CountryTaiwan
CityTainan
Period09-10-1809-10-21

Fingerprint

Candida albicans
Raman Spectrum Analysis
Technology
Principal Component Analysis
Cluster Analysis
Selection Bias
Lenses
Cultured Cells
Lasers

All Science Journal Classification (ASJC) codes

  • Molecular Medicine
  • Pharmacology

Cite this

Pan, Y. L., Yang, T. S., Chang, T. C., & Chang, H-C. (2009). Rapid identification of Candida albicans based on Raman spectral biosensing technology. In 2009 IEEE 3rd International Conference on Nano/Molecular Medicine and Engineering, NANOMED 2009 (pp. 120-124). [5559104] (2009 IEEE 3rd International Conference on Nano/Molecular Medicine and Engineering, NANOMED 2009). https://doi.org/10.1109/NANOMED.2009.5559104
Pan, Yong Li ; Yang, Tzyy Schiuan ; Chang, Tsung Chain ; Chang, Hsien-Chang. / Rapid identification of Candida albicans based on Raman spectral biosensing technology. 2009 IEEE 3rd International Conference on Nano/Molecular Medicine and Engineering, NANOMED 2009. 2009. pp. 120-124 (2009 IEEE 3rd International Conference on Nano/Molecular Medicine and Engineering, NANOMED 2009).
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title = "Rapid identification of Candida albicans based on Raman spectral biosensing technology",
abstract = "Traditional identification methods of pathogenic Candida albicans are time-consuming due to the long-term incubation. The purpose of this study is to develop a noninvasive biomolecular sensing technology for rapid identification of Candida albicans. Surface enhanced Raman scattering (SERS) based on colloidal sliver was used to rapidly detect specific molecules on the surface of cells cultured on SDA plate. A homemade fluidic chamber was fabricated to enlarge the random sampling area, increase the path length and avoid sampling error caused by disturbance or evaporation. SERS signal was detected by a 514 nm laser with a 10x objective lens. The exposure time of CCD was 10 s. Normalization, second derivative, principal component analysis (PCA) and hierarchical cluster analysis (HCA) were also integrated for discrimination of Candida albicans by spectral patterns precisely. The results show that SERS can be used to detect high-concentration suspended cells of Candida albicans. Candida albicans can be discriminated to genus and species level by principal component analysis and hierarchical cluster analysis of high frequency features of SERS spectral patterns.",
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Pan, YL, Yang, TS, Chang, TC & Chang, H-C 2009, Rapid identification of Candida albicans based on Raman spectral biosensing technology. in 2009 IEEE 3rd International Conference on Nano/Molecular Medicine and Engineering, NANOMED 2009., 5559104, 2009 IEEE 3rd International Conference on Nano/Molecular Medicine and Engineering, NANOMED 2009, pp. 120-124, 2009 IEEE 3rd International Conference on Nano/Molecular Medicine and Engineering, NANOMED 2009, Tainan, Taiwan, 09-10-18. https://doi.org/10.1109/NANOMED.2009.5559104

Rapid identification of Candida albicans based on Raman spectral biosensing technology. / Pan, Yong Li; Yang, Tzyy Schiuan; Chang, Tsung Chain; Chang, Hsien-Chang.

2009 IEEE 3rd International Conference on Nano/Molecular Medicine and Engineering, NANOMED 2009. 2009. p. 120-124 5559104 (2009 IEEE 3rd International Conference on Nano/Molecular Medicine and Engineering, NANOMED 2009).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Pan YL, Yang TS, Chang TC, Chang H-C. Rapid identification of Candida albicans based on Raman spectral biosensing technology. In 2009 IEEE 3rd International Conference on Nano/Molecular Medicine and Engineering, NANOMED 2009. 2009. p. 120-124. 5559104. (2009 IEEE 3rd International Conference on Nano/Molecular Medicine and Engineering, NANOMED 2009). https://doi.org/10.1109/NANOMED.2009.5559104