Detection of microorganisms in food samples and food processing facilities
Inventors
AMINI, Sasan • Khaksar, Ramin • Taylor, Michael • Namazi, Hossein • Tran, David • Haney, Christopher • Vaidyanathan, Pavan • Mortazavi, Sima • Allred, Adam
Assignees
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Publication Number
US-10676794-B2
Publication Date
2020-06-09
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 relates to systems and methods for sequencing-based detection of pathogenic and non-pathogenic microorganisms in food and environmental samples from a food processing facility. A method obtains first and second pluralities of nucleic acid sequences from first and second samples from the food processing facility, where the target nucleic acid comprises a periodic or a non-periodic barcode, and creates a data file in a computer that associates one or more nucleic acid sequences with the food processing facility.
The method scans a plurality of sequences from the second plurality of nucleic acid sequences to identify one or more sequences associated with the food processing facility in the data file association. The approach includes polymorphic genetic regions, optional highly targeted scanning, and distinguishing live versus dead microorganisms using sequencing read epigenetic patterns, for example methylation, and/or photoreactive dye treatment, and distinguishing transient versus resident pathogens.
The invention further provides classification and correlation functions for differentiating and relating indicator and non-pathogenic microorganisms with pathogen presence, including using machine learning, and enables predictive risk assessment and shelf-life or expiration prediction. The disclosed framework also includes automated sequencing apparatus with sample library preparation compartments and robotic transfer, and barcode/indexing strategies with mutually exclusive indexes and flow-cell reuse with distinct indexes, to support scanning and monitoring across samples and facilities.
Claims Coverage
The partial set includes one independent claim. Across its dependent claims, the coverage includes barcode-linked association to a specific food processing facility and scanning for sequences associated with that facility, with refinements for sample types, target differentiation, sequencing modality, and epigenetic pattern detection.
Facility-associated barcode creation and association
obtaining a first plurality of nucleic acid sequences from a first sample of a food processing facility, wherein said sample comprises a periodic or a non-periodic barcode, and creating a data file in a computer that associates one or more of said first plurality of nucleic acid sequences with said food processing facility
Barcode-linked scanning for facility-associated sequences
obtaining a second plurality of nucleic acid sequences from a second sample of said food processing facility, wherein said sample comprises a periodic or a non-periodic barcode, and scanning a plurality of sequences from said second plurality of nucleic acid sequences for one or more sequences associated with said food processing facility
Overall, the claim coverage centers on generating a facility-associated reference via barcoded nucleic acid sequences stored in a computer data file and then scanning new sequencing reads for sequences associated with that same food processing facility, with dependent refinements directed to sampling context, pathogen state, sequencing modality, and epigenetic pattern detection.
Stated Advantages
Not explicitly described in patent.
Documented Applications
Not explicitly described in patent.
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