Determination of the microbial content in foods is important, not only for safe consumption, but also for food quality, value, and yield. A variety of molecular techniques are currently available for both identification and quantification of microbial content within samples; however, their success is often contingent upon proper sample preparation when the subject of investigation is a complex mixture of components such as foods. Because of the importance of sample preparation, the present study employs a systematic approach to compare the effects of four different separation techniques (glass wool, 50 μm polypropylene filters, graphite felt, and continuous flow centrifugation (CFC)) on sample preparation. To define the physical effects associated with the use of these separation methods, a multifactorial analysis was performed where particle size and composition, both pre- and post- processing, were analyzed for four different food matrices including lean ground beef, ground pork, ground turkey and spinach. Retention of three important foodborne bacterial pathogens (Escherichia coli
O157:H7, Salmonella enterica
, and Listeria monocytogenes
) was also examined to evaluate the feasibility of the aforementioned methods to be utilized within the context of foodborne pathogen detection. Data from the multifactorial analysis not only delineated the particle size ranges but also defined the unique compositional profiles and quantified the bacterial retention. The three filtration membranes allowed for the passage of bacteria with minimal loss while CFC concentrated the inoculated bacteria. In addition, the deposition and therefore concentration of food matrix observed with CFC was considerably higher for meat samples relative to spinach. However, filtration with glass wool prior to CFC helped clarify meat samples, which led to considerably lower amounts of solids in the CFC vessel post processing and an increase in the recovery of the bacteria. Overall, by laying a framework for the deductive selection of sample preparation techniques, the results of the study can be applied to a range of applications where it would be beneficial to scientifically guide the pairing of the criteria associated with a downstream detection method with the most advantageous sample preparation techniques for complex matrices such as foods.
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