B. Park, M. Eady, B. Oakley, S. Yoon, K. Lawrence, G. Gamble
{"title":"Hyperspectral microscope imaging methods for multiplex detection of Campylobacter","authors":"B. Park, M. Eady, B. Oakley, S. Yoon, K. Lawrence, G. Gamble","doi":"10.1255/JSI.2019.A6","DOIUrl":null,"url":null,"abstract":"Campylobacter is an emerging zoonotic bacterial threat in the poultry industry. The current methods for the isolation\n and detection of Campylobacter are culture-based techniques with several selective agars designed to isolate\nCampylobacter colonies, which is time-consuming, labour intensive and has low sensitivity. Several immunological and\nmolecular techniques such as enzyme-linked immunosorbent assay (ELISA) and Latex agglutination are commercially\navailable for the detection and identification of Campylobacter. However, these methods demand more advanced\ninstruments as well as specially trained experts. A hyperspectral microscope imaging (HMI) technique with the\nfluorescence in situ hybridisation (FISH) technique has the potential for multiplex foodborne pathogen detection. Using\nAlexa488 and Cy3 fluorophores, the HMI (450–800 nm) technique was able to identify Campylobacter jejuni stains with\nhigh sensitivity and specificity. In addition, HMI was able to classify six bacteria using scattering intensity from their\nspectra without a FISH fluorophore. Overall classification accuracy of quadratic discriminant analysis (QDA) method for\nsix bacteria including Bifidobacter longum, Campylobacter jejuni, Clostridium perfringens, Enterobacter cloacae,\nLactobacillus salivarius and Shigella flexneri using the HMI technique without fluorescent markers was approximately 88.6\n% with pixel-wise classification.","PeriodicalId":37385,"journal":{"name":"Journal of Spectral Imaging","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Spectral Imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1255/JSI.2019.A6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Chemistry","Score":null,"Total":0}
引用次数: 4
Abstract
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 isolate
Campylobacter colonies, which is time-consuming, labour intensive and has low sensitivity. Several immunological and
molecular techniques such as enzyme-linked immunosorbent assay (ELISA) and Latex agglutination are commercially
available for the detection and identification of Campylobacter. However, these methods demand more advanced
instruments as well as specially trained experts. A hyperspectral microscope imaging (HMI) technique with the
fluorescence in situ hybridisation (FISH) technique has the potential for multiplex foodborne pathogen detection. Using
Alexa488 and Cy3 fluorophores, the HMI (450–800 nm) technique was able to identify Campylobacter jejuni stains with
high sensitivity and specificity. In addition, HMI was able to classify six bacteria using scattering intensity from their
spectra without a FISH fluorophore. Overall classification accuracy of quadratic discriminant analysis (QDA) method for
six 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.
期刊介绍:
JSI—Journal of Spectral Imaging is the first journal to bring together current research from the diverse research areas of spectral, hyperspectral and chemical imaging as well as related areas such as remote sensing, chemometrics, data mining and data handling for spectral image data. We believe all those working in Spectral Imaging can benefit from the knowledge of others even in widely different fields. We welcome original research papers, letters, review articles, tutorial papers, short communications and technical notes.