WEBINAR SERIESDevelopment of a universal detection methodology for foodborne microbial pathogens

Welcome to Episode 7 in the CosmosID Microbiome Webinar Series where we’ll be exploring foodborne microbial pathogens.

For this webinar, Dr. Dele Ogunremi will be talking about his collaborative work with others on how genomics and bioinformatics have been applied leading to develop a universal detection methodology for microbial organisms in food.

The majority of pathogens contaminating food and capable of causing harm in humans are either not routinely tested for or sometimes escape detection, mitigating against a rational control strategy aimed at keeping the consumer safe.  Given the diversity of the various microbial hazards, the development of a universal detection methodology is predictably faced with a plethora of challenges.  Yet, a reliable universal protocol will overcome endless number of technical challenges that span different scientific fields including microscopy, virology, bacteriology, parasitology, molecular biology and statistics. Often enough, analyses of food samples result in lack of detection of the contaminating pathogen or inaccurate, suspicious and ambiguous outcomes and unactionable inferences.  The application of genomics and bioinformatics layered on a foundational and sound understanding of the biology of the various microbial pathogens has led to the development of a unified protocol consisting of distinct steps that include: (a) global amplification of the DNA of the metagenome derived from a food sample, (b) nanopore sequencing of amplified DNA, and (c) optimized bioinformatics detection of targets using the CosmosID proprietary technology.  Our protocol  has led to the sensitive and accurate detection and identification to the species level of microbial contamination of lettuce (25 g) following spiking with bacteria, viruses and/or parasites at levels that include low pathogen load, namely: 1 colony forming unit of Salmonella, 5 oocysts of Cryptosporidium parvum  and 500 plaque forming units of Hepatitis A virus.  We have confirmed the approach using (1) spiked food samples blindly submitted to the testing laboratory and (2) naturally contaminated food samples that were the subjects of regulatory food recall.  Although potentially disruptive, a reliable universal detection method will simplify and democratize hazard identification with the promise of application in both a controlled laboratory environment and on the field.