Predictive microbiology targets poultry pathogens.

Predictive microbiology, which involves the use of modeling software to forecast the behavior of foodborne pathogens in response to environmental conditions encountered in food production and processing operations, continues to grow in interest. Models predict how long it takes for pathogens to grow under certain conditions, and how fast they grow once they start.

An estimated 1.4 million cases of salmonellosis food poisoning occur annually in the United States, according to the Centers for Disease Control and Prevention, and about 10% of those cases are from poultry. One way to better assess food safety is to develop pathogen models that take into account real-life competition from other microbes present in food.

Previously models were often developed based on the growth of microbes in broth with no other microbes present. Researchers thought this would allow them to accurately predict pathogen behavior in food. But recent findings indicate that this is not always the case. USDA-ARS researchers will develop more realistic models by using the "acceptable prediction zone method," a system they developed that establishes criteria for verifying and validating models as having acceptable or unacceptable predictive records; classifies them to show which are best; and then pinpoints any changes that are needed.

Models are evaluated under specific conditions to determine which ones meet established standards and demonstrate a level of performance that could be used with confidence in the food industry to predict food safety. The researchers are working on two promising techniques to improve the models. One is to introduce a jellyfish gene into Salmonella to make the bacteria fluoresce, or glow, so they'll be easier to detect among other microorganisms on raw poultry.

The researchers have had more immediate success with the second approach. They found that a strain of antibiotic-resistant Salmonella can be a valuable tool for modeling pathogen growth. Salmonella typhimurium DT104 is known to be resistant to five different antibiotics. The researchers put four of those five antibiotics in an agar medium to determine the amount of Salmonella in a food sample. The antibiotics killed competing microorganisms on the agar plates and left just the Salmonella.

The scientists were able to follow the surviving Salmonella and model its growth on raw poultry meat, showing how it behaves in a real food environment. The DT104 strain helped confirm their theory that models developed in the absence of microbial competition do not accurately predict pathogen behavior in foods that contain other spoilage organisms. The models and methods have been published in the scientific literature and are ready for commercial use.

Further information. Thomas Oscar, USDA-ARS Poultry Food Safety Research Laboratory, Room 2111, Center for Food Science and Technology, University of Maryland Eastern Shore, Princess Anne, MD 21853; phone: [phone]; fax: [phone]; email: [e-mail].