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ACCORDING TO THE U.S. CENTERS FOR DISEASE CONTROL AND PREVENTION, FOODBORNE ILLNESSES AFFECT AN ESTIMATED 1 IN 6 AMERICANS EVERY YEAR, CAUSING 128,000 HOSPITALIZATIONS AND 3,000 DEATHS. FOOD SAFETY RISK ASSESSMENT, THE EVALUATION OF ADVERSE HEALTH EFFECTS RESULTING FROM HUMAN EXPOSURE TO FOODBORNE HAZARDS, HAS GAINED MOMENTUM IN RECENT DECADES. RISK ASSESSMENT CAN PROVIDE SCIENTIFICALLY SOUND BASES FOR INFORMED MANAGEMENT AND POLICY DECISIONS. THE QUANTITATIVE MICROBIAL RISK ASSESSMENT (QMRA) APPROACH HAS GREAT SIGNIFICANCE TO FOOD SAFETY, AND CAN BE USED TO SYSTEMATICALLY ORGANIZE RELEVANT FOOD SAFETY INFORMATION. ADVANCES IN FOOD SAFETY RISK ASSESSMENT ARE CRITICAL TO UNDERSTAND AND CONTROL THE RISK OF FOODBORNE DISEASES. RECENTLY, WHOLE GENOME SEQUENCING (WGS) OF FOODBORNE PATHOGENS HAS GAINED POPULARITY IN FOOD SAFETY, AND IS BEING INCREASINGLY INCORPORATED AS A REGULAR COMPONENT OF EPIDEMIOLOGICAL AND MOLECULAR STUDIES. THIS PROVIDES US WITH AN UNPRECEDENTED OPPORTUNITY TO IMPROVE CURRENT RISK MODELS BY DEVELOPING NOVEL APPROACHES TO INTEGRATE WGS AND QMRA. IN ORDER TO ACHIEVE THIS, THERE IS AN URGENT, UNMET NEED FOR BIOINFORMATICS PIPELINES OR TOOLS TO RAPIDLY PROCESS WGS DATA. IN THIS STUDY, THE PERSISTENT PATHOGEN-FOOD PAIR OF SALMONELLA IN CHICKEN WILL BE USED AS AN EXAMPLE TO DEMONSTRATE THE USE OF ADVANCED BIOINFORMATICS AND COMPUTATIONAL METHODS IN TRANSLATING GENOMIC DATA INTO A QMRA FRAMEWORK. SALMONELLA IS A MAJOR FOODBORNE PATHOGEN RESPONSIBLE FOR AN ESTIMATED 1.2 MILLION CASES OF FOODBORNE ILLNESSES PER YEAR. THIS BACTERIAL SPECIES COMPRISES THOUSANDS OF SUB-SPECIES AND SEROVARS WITH HIGHLY VARIABLE PATHOGENICITY, IN TERMS OF DISEASE SEVERITY, VIRULENCE, ANTIBIOTIC RESISTANCE, AND PREVALENCE, DUE TO MINUTE CHANGES IN ITS GENETIC MAKE-UP. CURRENT RISK ESTIMATES FOR SALMONELLA IN CHICKEN DO NOT TAKE INTO ACCOUNT THIS VARIABILITY ARISING FROM VARIATIONS IN ITS GENETIC PROFILE. THE OBJECTIVES OF OUR PROJECT ARE TO DEVELOP ADVANCED COMPUTATIONAL PIPELINES AND TOOLS TO ANALYZE WGS DATASETS IN ORDER TO OBTAIN INFORMATION THAT CAN BE APPLIED IN A QMRA, VERIFY THE OBTAINED COMPUTATIONAL MODELS USING EXPERIMENTAL STUDIES, AND DEVELOP A NOVEL WGS-BASED QMRA USING THE GENERATED INFORMATION. WE WILL EMPLOY ADVANCED MACHINE LEARNING, COMPUTATIONAL METHODS, AND EXPERIMENTAL TECHNIQUES TO ACHIEVE OUR OBJECTIVES. OUR MODELS AND RESULTS WOULD HELP IDENTIFY SOURCES OF HETEROGENEITY AMONG VARIOUS TYPES OF SALMONELLA THAT COULD BE LINKED TO INCREASED RISK OF DISEASE. THIS STUDY WILL HELP IN IMPROVING CURRENT RISK ESTIMATES, WHICH IN TURN WILL ASSIST IN IMPROVED RISK MANAGEMENT DECISIONS TO IMPROVE FOOD SAFETY AND PROTECT PUBLIC HEALTH.

$499,989FY2020National Institute of Food and AgricultureUSDA

University Of Maryland, College Park, College Park MD

Investigators

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ACCORDING TO THE U.S. CENTERS FOR DISEASE CONTROL AND PREVENTION, FOODBORNE ILLNESSES AFFECT AN ESTIMATED 1 IN 6 AMERICANS EVERY YEAR, CAUSING 128,000 HOSPITALIZATIONS AND 3,000 DEATHS. FOOD SAFETY RISK ASSESSMENT, THE EVALUATION OF ADVERSE HEALTH EFFECTS RESULTING FROM HUMAN EXPOSURE TO FOODBORNE HAZARDS, HAS GAINED MOMENTUM IN RECENT DECADES. RISK ASSESSMENT CAN PROVIDE SCIENTIFICALLY SOUND BASES FOR INFORMED MANAGEMENT AND POLICY DECISIONS. THE QUANTITATIVE MICROBIAL RISK ASSESSMENT (QMRA) APPROACH HAS GREAT SIGNIFICANCE TO FOOD SAFETY, AND CAN BE USED TO SYSTEMATICALLY ORGANIZE RELEVANT FOOD SAFETY INFORMATION. ADVANCES IN FOOD SAFETY RISK ASSESSMENT ARE CRITICAL TO UNDERSTAND AND CONTROL THE RISK OF FOODBORNE DISEASES. RECENTLY, WHOLE GENOME SEQUENCING (WGS) OF FOODBORNE PATHOGENS HAS GAINED POPULARITY IN FOOD SAFETY, AND IS BEING INCREASINGLY INCORPORATED AS A REGULAR COMPONENT OF EPIDEMIOLOGICAL AND MOLECULAR STUDIES. THIS PROVIDES US WITH AN UNPRECEDENTED OPPORTUNITY TO IMPROVE CURRENT RISK MODELS BY DEVELOPING NOVEL APPROACHES TO INTEGRATE WGS AND QMRA. IN ORDER TO ACHIEVE THIS, THERE IS AN URGENT, UNMET NEED FOR BIOINFORMATICS PIPELINES OR TOOLS TO RAPIDLY PROCESS WGS DATA. IN THIS STUDY, THE PERSISTENT PATHOGEN-FOOD PAIR OF SALMONELLA IN CHICKEN WILL BE USED AS AN EXAMPLE TO DEMONSTRATE THE USE OF ADVANCED BIOINFORMATICS AND COMPUTATIONAL METHODS IN TRANSLATING GENOMIC DATA INTO A QMRA FRAMEWORK. SALMONELLA IS A MAJOR FOODBORNE PATHOGEN RESPONSIBLE FOR AN ESTIMATED 1.2 MILLION CASES OF FOODBORNE ILLNESSES PER YEAR. THIS BACTERIAL SPECIES COMPRISES THOUSANDS OF SUB-SPECIES AND SEROVARS WITH HIGHLY VARIABLE PATHOGENICITY, IN TERMS OF DISEASE SEVERITY, VIRULENCE, ANTIBIOTIC RESISTANCE, AND PREVALENCE, DUE TO MINUTE CHANGES IN ITS GENETIC MAKE-UP. CURRENT RISK ESTIMATES FOR SALMONELLA IN CHICKEN DO NOT TAKE INTO ACCOUNT THIS VARIABILITY ARISING FROM VARIATIONS IN ITS GENETIC PROFILE. THE OBJECTIVES OF OUR PROJECT ARE TO DEVELOP ADVANCED COMPUTATIONAL PIPELINES AND TOOLS TO ANALYZE WGS DATASETS IN ORDER TO OBTAIN INFORMATION THAT CAN BE APPLIED IN A QMRA, VERIFY THE OBTAINED COMPUTATIONAL MODELS USING EXPERIMENTAL STUDIES, AND DEVELOP A NOVEL WGS-BASED QMRA USING THE GENERATED INFORMATION. WE WILL EMPLOY ADVANCED MACHINE LEARNING, COMPUTATIONAL METHODS, AND EXPERIMENTAL TECHNIQUES TO ACHIEVE OUR OBJECTIVES. OUR MODELS AND RESULTS WOULD HELP IDENTIFY SOURCES OF HETEROGENEITY AMONG VARIOUS TYPES OF SALMONELLA THAT COULD BE LINKED TO INCREASED RISK OF DISEASE. THIS STUDY WILL HELP IN IMPROVING CURRENT RISK ESTIMATES, WHICH IN TURN WILL ASSIST IN IMPROVED RISK MANAGEMENT DECISIONS TO IMPROVE FOOD SAFETY AND PROTECT PUBLIC HEALTH. · GrantIndex