Page Banner

United States Department of Agriculture

Agricultural Research Service


Location: Molecular Characterization of Foodborne Pathogens

Title: Light scattering sensor for direct identification of colonies of Escherichia coli serogroups O26, O45, O103, O111, O121, O145 and O157

item Tang, Yanjie -
item Kim, Huisung -
item Singh, Atul -
item Aroonnal, Amornrat -
item Rajwa, Bartek -
item Bae, Euiwon -
item Bhunia, Arun -

Submitted to: PLoS One
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: July 21, 2014
Publication Date: N/A

Interpretive Summary: A group of bacteria known as Shiga-toxin producing Escherichia coli (STEC) have emerged as important food-borne pathogens, among which seven of these bacteria referred to as serogroups O26, O45, O103, O111, O121, O145, O157 are most frequently implicated in human infection. It is critical to be able to rapidly and accurately detect and identify these pathogens to prevent contaminated food from reaching the consumer. However, these bacteria lack unique features that allow them to be easily detected and identified on commonly used solid growth medium plates. To overcome this problem, a system known as the BARDOT was developed to rapidly identify and differentiate the different STEC serogroups on various solid growth media. The system generates a scatter pattern of the bacterial colony (a cluster of bacteria growing on a solid growth medium) growing on the different media so that they can be identified based on the image of the colony that is generated. The BARDOT was able to accurately identify the bacterial colonies on different solid media, as well as on plates that also contained a variety of other bacteria that are found in food such as lettuce and ground beef. These results demonstrate that the BARDOT system could potentially be used as a rapid screening tool to identify the most important STEC bacteria in food samples in less than 24 h, and thus it enhances the ability to prevent the sale of contaminated retail food.

Technical Abstract: Background: Shiga-toxin producing Escherichia coli (STEC) have emerged as important foodborne pathogens, among which seven serogroups (O26, O45, O103, O111, O121, O145, O157) are most frequently implicated in human infection. The aim of this study was to determine if a light scattering sensor can be used to rapidly differentiate the colonies of O157 STEC and six non-O157 STEC serovars on different selective agar plates. Methodology/Principal Findings: Initially, a total of 37 STEC strains representing seven serovars were grown on four different selective agar media, including sorbitol MacConkey (SMAC), Rainbow® Agar O157, BBLTM CHROMagar O157, and R&F® E. coli O157:H7, as well as nonselective Brain Heart Infusion (BHI) agar. The colonies were scanned by an automated light scattering sensor, known as BARDOT (BActerial Rapid Detection using Optical scattering Technology) to acquire scatter patterns of O157 and non-O157 STEC serogroups, and the scatter patterns were analyzed using an image classifier. Among all of the selective media tested, both SMAC and Rainbow provided the best differentiation results allowing multi-class classification of all serovars with an average accuracy of more than 90% after 10 to11 h of growth, even though the colony appearance was indistinguishable at that early stage of growth. SMAC was chosen for exhaustive scatter image library development, and 36 additional strains of O157:H7 and 10 non-O157 strains were examined, with each serogroup producing unique differential scatter patterns. Scatter images were also tested with samples derived from pure and mixed cultures, as well as experimentally inoculated food samples. BARDOT accurately detected O157 and O26 serovars from a mixed culture and also from inoculated lettuce and ground beef samples in the presence of natural background microbiota in less than 24 h. Conclusions/Significance: These data demonstrate that BARDOT could potentially be used as a screening tool during isolation of the most important STEC serovars on selective agar plates from food samples in less than 24 h.

Last Modified: 9/10/2014
Footer Content Back to Top of Page