A COMPUTER model of the battles between bacterial colonies could lead to salamis that are safer to eat and have longer shelf lives. The model could also help food scientists devise new ways to tackle the growth of dangerous bacteria in food.
The bacterium Listeria monocytogenes is a leading source of food-borne disease in meats and other products. To understand how it grows in food, scientists often turn to computer models which describe how bacteria reproduce given a source of food and variables such as temperature, pH and humidity.
Unfortunately, these models ignore the competition that L. monocytogenes faces from other bacterial species, says food safety specialist Alessandro Giuffrida at the University of Messina in Italy. He and colleagues have now developed a new model for bacterial growth that includes both competition and environmental influences.
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The Italian team has focused on the way bacteria grows in traditional Sicilian salami during the fermentation stage of its preparation 鈥� a period of curing in which L. monocytogenes, if present, competes with a population of harmless lactic acid bacteria.
The new model simulates this competition for resources as well as the effects of fluctuations in environmental factors such as temperature and accurately reproduces experimental data on the growth of L. monocytogenes.
The model could be useful for devising ways to control the bacterial growth during the fermentation process. The model suggests that fluctuations of temperature, pH or humidity can be used to limit bacterial growth. In the fermentation stage, greater fluctuations in these conditions led to slower growth of L. monocytogenes although the researchers have yet to work out why. So controlling these bacterial battles could produce food with a longer shelf life. The work will be published in the journal European Food Research and Technology.
鈥淐ontrolling bacterial battles could give food a longer shelf life鈥�
Software is on the market for predicting the shelf life of various foods based on the growth rates of single species of bacteria, but the ability to model two species is a step towards better prediction. 鈥淭his is the first detailed look at the interplay of environmental noise and interactions between bacterial species,鈥� says Fabio Marchesoni at the University of Camerino. 鈥淚t鈥檚 an important advance in predictive microbiology.鈥�
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