Document Detail

Detecting food- and waterborne viruses by surface-enhanced Raman spectroscopy.
MedLine Citation:
PMID:  20629888     Owner:  NLM     Status:  MEDLINE    
Food- and waterborne viruses pose serious health risks to humans and were associated with many outbreaks worldwide. Rapid, accurate, and nondestructive methods for detection of viruses are of great importance to protect public health. In this study, surface-enhanced Raman spectroscopy (SERS) coupled with gold SERS-active substrates was used to detect and discriminate 7 food- and waterborne viruses, including norovirus, adenovirus, parvovirus, rotavirus, coronavirus, paramyxovirus, and herpersvirus. Virus samples were purified and dialyzed in phosphate buffered saline (8 to 9 log PFU/mL) and then further diluted in deionized water for SERS measurement. After capturing the characteristic SERS spectral patterns, multivariate statistical analyses, including soft independent modeling of class analogy (SIMCA) and principal component analysis (PCA), were employed to analyze SERS spectral data for characterization and identification of viruses. The results show that SIMCA was able to differentiate viruses with and without envelope with >95% of classification accuracy, while PCA presented clear spectral data segregations between different virus strains. The virus detection limit by SERS using gold substrates reached a titer of 10(2).
Cui Fan; Zhiqiang Hu; Lela K Riley; Gregory A Purdy; Azlin Mustapha; Mengshi Lin
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Publication Detail:
Type:  Evaluation Studies; Journal Article; Research Support, U.S. Gov't, Non-P.H.S.    
Journal Detail:
Title:  Journal of food science     Volume:  75     ISSN:  1750-3841     ISO Abbreviation:  J. Food Sci.     Publication Date:  2010 Jun 
Date Detail:
Created Date:  2010-07-15     Completed Date:  2010-10-20     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0014052     Medline TA:  J Food Sci     Country:  United States    
Other Details:
Languages:  eng     Pagination:  M302-7     Citation Subset:  IM    
Food Science Program, Div. of Food Systems & Bioengineering, Univ. of Missouri, Columbia, MO 65211, USA.
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MeSH Terms
Feasibility Studies
Food Microbiology*
Principal Component Analysis
Sendai virus
Spectrum Analysis, Raman / methods*
Surface Properties
Viruses / isolation & purification*
Water Microbiology*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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