Document Detail


Label-free detection of multiple bacterial pathogens using light-scattering sensor.
MedLine Citation:
PMID:  18945607     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Technologies for rapid detection and classification of bacterial pathogens are crucial for securing the food supply. This report describes a light-scattering sensor capable of real-time detection and identification of colonies of multiple pathogens without the need for a labeling reagent or biochemical processing. Bacterial colonies consisting of the progeny of a single parent cell scatter light at 635 nm to produce unique forward-scatter signatures. Zernike moment invariants and Haralick descriptors aid in feature extraction and construction of the scatter-signature image library. The method is able to distinguish bacterial cultures at the genus and species level for Listeria, Staphylococcus, Salmonella, Vibrio, and Escherichia with an accuracy of 90-99% for samples derived from food or experimentally infected animal. Varied amounts of exopolysaccharide produced by the bacteria causes changes in phase modulation distributions, resulting in strikingly different scatter signatures. With the aid of a robust database the method can potentially detect and identify any bacteria colony essentially instantaneously. Unlike other methods, it does not destroy the sample, but leaves it intact for other confirmatory testing, if needed, for forensic or outbreak investigations.
Authors:
Padmapriya P Banada; Karleigh Huff; Euiwon Bae; Bartek Rajwa; Amornrat Aroonnual; Bulent Bayraktar; Abrar Adil; J Paul Robinson; E Daniel Hirleman; Arun K Bhunia
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2008-09-11
Journal Detail:
Title:  Biosensors & bioelectronics     Volume:  24     ISSN:  1873-4235     ISO Abbreviation:  Biosens Bioelectron     Publication Date:  2009 Feb 
Date Detail:
Created Date:  2009-02-02     Completed Date:  2009-05-26     Revised Date:  2009-07-14    
Medline Journal Info:
Nlm Unique ID:  9001289     Medline TA:  Biosens Bioelectron     Country:  England    
Other Details:
Languages:  eng     Pagination:  1685-92     Citation Subset:  IM    
Affiliation:
Department of Food Science, Molecular Food Microbiology Laboratory, Purdue University, IN 47907, USA.
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MeSH Terms
Descriptor/Qualifier:
Biosensing Techniques / instrumentation*
Colony Count, Microbial / instrumentation*
Equipment Design
Equipment Failure Analysis
Light
Refractometry / instrumentation*
Reproducibility of Results
Scattering, Radiation
Sensitivity and Specificity
Staining and Labeling

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


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