Laser Optical Sensor, a Label-Free On-Plate Salmonella enterica Colony Detection Tool

Author:

Singh Atul K.1,Bettasso Amanda M.1,Bae Euiwon2,Rajwa Bartek3,Dundar Murat M.4,Forster Mark D.5,Liu Lixia5,Barrett Brent5,Lovchik Judith5,Robinson J. Paul36,Hirleman E. Daniel2,Bhunia Arun K.17

Affiliation:

1. Department of Food Science, Molecular Food Microbiology Laboratory, Purdue University, West Lafayette, Indiana, USA

2. School of Mechanical Engineering, Purdue University, West Lafayette, Indiana, USA

3. Bindley Bioscience Center, Purdue University, West Lafayette, Indiana, USA

4. Computer & Information Science Department, Indiana University, Purdue University at Indianapolis, Indianapolis, Indiana, USA

5. Indiana State Department of Health, Indianapolis, Indiana, USA

6. Department of Basic Medical Sciences, Purdue University, West Lafayette, Indiana, USA

7. Department of Comparative Pathobiology, Purdue University, West Lafayette, Indiana, USA

Abstract

ABSTRACT We investigated the application capabilities of a laser optical sensor, BARDOT ( b a cterial r apid d etection using o ptical scatter t echnology) to generate differentiating scatter patterns for the 20 most frequently reported serovars of Salmonella enterica . Initially, the study tested the classification ability of BARDOT by using six Salmonella serovars grown on brain heart infusion, brilliant green, xylose lysine deoxycholate, and xylose lysine tergitol 4 (XLT4) agar plates. Highly accurate discrimination (95.9%) was obtained by using scatter signatures collected from colonies grown on XLT4. Further verification used a total of 36 serovars (the top 20 plus 16) comprising 123 strains with classification precision levels of 88 to 100%. The similarities between the optical phenotypes of strains analyzed by BARDOT were in general agreement with the genotypes analyzed by pulsed-field gel electrophoresis (PFGE). BARDOT was evaluated for the real-time detection and identification of Salmonella colonies grown from inoculated (1.2 × 10 2  CFU/30 g) peanut butter, chicken breast, and spinach or from naturally contaminated meat. After a sequential enrichment in buffered peptone water and modified Rappaport Vassiliadis broth for 4 h each, followed by growth on XLT4 (~16 h), BARDOT detected S . Typhimurium with 84% accuracy in 24 h, returning results comparable to those of the USDA Food Safety and Inspection Service method, which requires ~72 h. BARDOT also detected Salmonella (90 to 100% accuracy) in the presence of background microbiota from naturally contaminated meat, verified by 16S rRNA sequencing and PFGE. Prolonged residence (28 days) of Salmonella in peanut butter did not affect the bacterial ability to form colonies with consistent optical phenotypes. This study shows BARDOT’s potential for nondestructive and high-throughput detection of Salmonella in food samples. IMPORTANCE High-throughput screening of food products for pathogens would have a significant impact on the reduction of food-borne hazards. A laser optical sensor was developed to screen pathogen colonies on an agar plate instantly without damaging the colonies; this method aids in early pathogen detection by the classical microbiological culture-based method. Here we demonstrate that this sensor was able to detect the 36 Salmonella serovars tested, including the top 20 serovars, and to identify isolates of the top 8 Salmonella serovars. Furthermore, it can detect Salmonella in food samples in the presence of background microbiota in 24 h, whereas the standard USDA Food Safety and Inspection Service method requires about 72 h.

Publisher

American Society for Microbiology

Subject

Virology,Microbiology

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