z-logo
open-access-imgOpen Access
Hyperspectral microscope imaging methods for multiplex detection of Campylobacter
Author(s) -
Bosoon Park,
Matthew Eady,
Brian B. Oakley,
Seung-Chul Yoon,
Kurt C. Lawrence,
Gary R. Gamble
Publication year - 2019
Publication title -
journal of spectral imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.256
H-Index - 6
ISSN - 2040-4565
DOI - 10.1255/jsi.2019.a6
Subject(s) - campylobacter , campylobacter jejuni , microbiology and biotechnology , biology , multiplex , clostridium perfringens , hyperspectral imaging , bacteria , artificial intelligence , bioinformatics , genetics , computer science
Campylobacter is an emerging zoonotic bacterial threat in the poultry industry. The current methods for the isolation and detection of Campylobacter are culture-based techniques with several selective agars designed to isolateCampylobacter colonies, which is time-consuming, labour intensive and has low sensitivity. Several immunological andmolecular techniques such as enzyme-linked immunosorbent assay (ELISA) and Latex agglutination are commerciallyavailable for the detection and identification of Campylobacter. However, these methods demand more advancedinstruments as well as specially trained experts. A hyperspectral microscope imaging (HMI) technique with thefluorescence in situ hybridisation (FISH) technique has the potential for multiplex foodborne pathogen detection. UsingAlexa488 and Cy3 fluorophores, the HMI (450–800 nm) technique was able to identify Campylobacter jejuni stains withhigh sensitivity and specificity. In addition, HMI was able to classify six bacteria using scattering intensity from theirspectra without a FISH fluorophore. Overall classification accuracy of quadratic discriminant analysis (QDA) method forsix bacteria including Bifidobacter longum, Campylobacter jejuni, Clostridium perfringens, Enterobacter cloacae,Lactobacillus salivarius and Shigella flexneri using the HMI technique without fluorescent markers was approximately 88.6% with pixel-wise classification.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom