Detection of microorganisms in food samples and food processing facilities
Inventors
AMINI, Sasan • Khaksar, Ramin • Taylor, Michael • Shokralla, Shadi • Namazi, Hossein • Tran, David
Assignees
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Publication Number
US-10246704-B1
Publication Date
2019-04-02
Expiration Date
Abstract
Provided herein are methods and apparatus for the identification of pathogenic and non-pathogenic microorganisms in food and environmental samples. The disclosure solves existing challenges encountered in identifying food borne pathogens, including pathogens of the Salmonella, Campylobacter, Listeria, and Escherichia genera in a timely and efficient manner. The disclosure also provides methods for differentiating a transient versus a resident pathogen, correlating presence of non-pathogenic with pathogenic microorganisms, distinguishing live versus dead microorganisms by sequencing.
Core Innovation
The invention provides a method and system for identifying and differentiating pathogenic and non-pathogenic microorganisms in food and environmental samples. The workflow uses sequencing and molecular indexes (barcodes) to support microbial identification, including distinguishing transient and resident contamination. The approach correlates indicator and non-pathogenic taxa with pathogenic risk to support pathogen prediction.
The invention includes metagenomic scanning of polymorphic genomic regions to achieve high sensitivity and specificity for pathogen identification. The sequencing readout is used to distinguish live from dead microorganisms using epigenetic patterns, including methylation, and/or viability dyes such as PMAxx and propidium monoazide derivatives. A targeted gene scanning component can be used with server-based data transmission.
The system includes server or cloud data transmission, machine learning analysis, and workflow and system features to support automated operation. The disclosure includes risk and shelf-life prediction using machine learning, including classification models and visualization such as heat maps and PCA. Workflow features include reusing flow cells with distinct indexes, reducing barcode crosstalk, and automation that minimizes human touchpoints after enrichment.
Claims Coverage
Not explicitly described in patent.
Not explicitly described in patent.
Stated Advantages
High sensitivity and specificity for pathogen prediction.
High precision and accuracy for pathogen prediction.
Reduced barcode crosstalk using barcode/index design.
Support for distinguishing live versus dead microorganisms using sequencing readouts (epigenetic patterns such as methylation and/or viability dyes).
Ability to differentiate transient versus resident contamination.
Support for risk prediction and shelf-life or expiration prediction using machine learning.
Early detection within reported timeframes on ONT and MiSeq.
Documented Applications
Food and environmental microbiology workflow for identifying pathogens and non-pathogens, including in food processing facilities.
Monitoring and analyzing contamination dynamics by differentiating transient versus resident contamination in food and environmental contexts.
Using indicator and non-pathogenic taxa to correlate with pathogenic risk for pathogen prediction.
Live/dead discrimination of microorganisms in food and environmental samples for improved pathogen detection interpretation.
Risk and shelf-life or expiration prediction based on sequencing and machine-learning analysis for food-related use cases.
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