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United States Department of Agriculture

Agricultural Research Service

Research Project: Molecular Biology of Human Pathogens Associated with Food

Location: Produce Safety and Microbiology Research

Title: Comprehensive detection and discrimination of campylobacter species using confocal micro-raman spectroscopy and multilocus sequence typing

item Lu, Xiaonan
item Huang, Qian
item Miller, William - Bill
item Aston, De
item Xu, Jie
item Xue, Feng
item Zhang, Hongwei
item Rasco, Barbara
item Wang, Shuo
item Konkel, Michael

Submitted to: Journal of Clinical Microbiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/20/2012
Publication Date: 6/27/2012
Citation: Lu, X., Huang, Q., Miller, W.G., Aston, D., Xu, J., Xue, F., Zhang, H., Rasco, B., Wang, S., Konkel, M.E. 2012. Comprehensive detection and discrimination of campylobacter species using confocal micro-raman spectroscopy and multilocus sequence typing. Journal of Clinical Microbiology. doi:10.1128/JCM.01144-12.

Interpretive Summary: Campylobacter have been isolated from a wide variety of environments, warm-blooded animals (birds, mammals. Campylobacters cause disease in both livestock and humans; human disease is primarily gastroenteritis, however other clinical outcomes, such as septicemia, can occur. Several Campylobacter species predominantly C. jejuni, have been isolated from food, milk and water; thus, several campylobacters are considered food-borne pathogens. Although the primary pathogen within Campylobacter is C. jejuni, other Campylobacter species have been associated with clinical human disease. Accurate and rapid typing methods do not exist for many of these newly-identified, emerging Campylobacter pathogens. This study uses Raman spectroscopy to type and speciate eleven different Campylobacter species, associated with human and/or animal illness. This new method was able to unequivocally identify all 11 species. Furthermore, this method was able to distinguish different strain types within each species. The Raman spectroscopy method can perform Campylobacter typing within a very short(~30 min) time frame, compared to the 1-2 day typing period for current methods, making it a potential alternative to existing typing methods for the emerging campylobacters.

Technical Abstract: A novel strategy for rapid identification and speciation of traditional and emerging Campylobacter strains based upon Raman spectroscopy (532 nm) is presented here. A total of 200 reference strains and clinical isolates of 11 different Campylobacter species recovered from infected animals and humans from China and North America was used to establish a global Raman spectroscopy-based dendrogram model for Campylobacter speciation and cross-validated for its feasibility to predict Campylobacter-associated foodborne outbreaks. Bayesian probability coupled with Monte-Carlo estimation was employed to validate the established Raman classification model on the basis of the selected principal components, mainly protein secondary structures on Campylobacter cell membrane. This Raman spectroscopy-based typing technique correlates well with multilocus sequence typing (MLST) and has an average recognition rate of 97.21%. Discriminatory power for the Raman classification model had a Simpson's index of diversity of 0.968. Intra- and inter-laboratory reproducibility using different instrumentation yielded Dy1y2 values of 4.79-6.03 for wavenumbers between 1800-650 cm-1 and demonstrated the feasibility of performing this method at different laboratories. Raman spectroscopy-based partial least squares regression (PLSR) model could precisely discriminate and quantify the actual concentration of a specific Campylobacter strain in a bacterial mixture [regression coefficient (R) > 0.98 and residual prediction deviation (RPD) > 7.88]. A standard protocol for sample preparation, spectral collection, model validation and data analyses was established for the Raman spectroscopic technique. Raman spectroscopy may have advantages compared to traditional genotyping methods for bacterial epidemiology, such as detection speed and speciation accuracy.

Last Modified: 10/18/2017
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