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

  • Yanjie Tang
  • , Huisung Kim
  • , Atul K. Singh
  • , Amornrat Aroonnual
  • , Euiwon Bae
  • , Bartek Rajwa
  • , Pina M. Fratamico
  • , Arun K. Bhunia
  • Purdue University
  • Nestec Ltd.
  • School of Mechanical Engineering, Purdue University
  • USDA ARS Eastern Regional Research Center
  • Purdue University College of Veterinary Medicine

Research output: Contribution to journalArticlepeer-review

60 Citations (Scopus)

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 was to determine if a light scattering sensor can be used to rapidly identify the colonies of STEC serogroups on 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, BBL CHROMagarO157, and R&F E. coli O157:H7, as well as nonselective Brain Heart Infusion 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 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 10-12 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 11 non-O157 serovars were examined, with each serogroup producing unique differential scatter patterns. Colony 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 (10-h broth enrichment +12-h on-plate incubation) in the presence of natural background microbiota in less than 24 h. Conclusions: 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.

Original languageEnglish
Article numbere105272
JournalPLoS ONE
Volume9
Issue number8
DOIs
Publication statusPublished - 19 Aug 2014

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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