ArticlePloS one2014
Light scattering sensor for direct identification of colonies of Escherichia coli serogroups O26, O45, O103, O111, O121, O145 and O157.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Determination of the Infection Dynamics ofFoods (Basel, Switzerland) · 2025Article
- Identifying antibiotic-resistant strains via cell sorting and elastic-light-scatter phenotyping.Applied microbiology and biotechnology · 2024Article
- Synthetic phage-based approach for sensitive and specific detection of Escherichia coli O157.Communications biology · 2024Article
- Machine learning identification of Pseudomonas aeruginosa strains from colony image data.PLoS computational biology · 2023Article
- Surface Environment and Energy Density Effects on the Detection and Disinfection of Microorganisms Using a Portable Instrument.Sensors (Basel, Switzerland) · 2023Article
- Spatio-temporal based deep learning for rapid detection and identification of bacterial colonies through lens-free microscopy time-lapses.PLOS digital health · 2022Article
- Petri-plate, bacteria, and laser optical scattering sensor.Frontiers in cellular and infection microbiology · 2022Review
- Identification of colonies of cultured shellfish-associatedCurrent research in microbial sciences · 2021Article
- Elastic Light Scatter Pattern Analysis for the Expedited Detection ofFrontiers in microbiology · 2021Article
- Development of the Correction Algorithm to Limit the Deformation of Bacterial Colonies Diffraction Patterns Caused by Misalignment and Its Impact on the Bacteria Identification in the Proposed Optical Biosensor.Sensors (Basel, Switzerland) · 2020Article
- Captive Green Iguana Carries DiarrheagenicFrontiers in veterinary science · 2020Article
- Integrated multi-channel optical system for bacteria characterization and its potential use for monitoring of environmental bacteria.Biomedical optics express · 2019Article
- Three Dimensional Vero Cell-Platform for Rapid and Sensitive Screening of Shiga-Toxin ProducingFrontiers in microbiology · 2019Article
- Colony Fingerprint-Based Discrimination ofSensors (Basel, Switzerland) · 2018Article
- Angular photodiode array-based device to detect bacterial pathogens in a wound model.IEEE sensors journal · 2017Article
- Mie scatter spectra-based device for instant, contact-free, and specific diagnosis of bacterial skin infection.Scientific reports · 2017Article
- Secretome analysis of diarrhea-inducing strains of Escherichia coli.Proteomics · 2017Article
- Colony fingerprint for discrimination of microbial species based on lensless imaging of microcolonies.PloS one · 2017Article
- Virulence Gene-Associated Mutant Bacterial Colonies Generate Differentiating Two-Dimensional Laser Scatter Fingerprints.Applied and environmental microbiology · 2016Article
- Optical scatter patterns facilitate rapid differentiation of Enterobacteriaceae on CHROMagar™ Orientation medium.Microbial biotechnology · 2016Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundShiga-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
findingsInitially, 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.
conclusionsBARDOT 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.
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