Identifying optimal methods of recovering bacteria from food processing plants for downstream microbiome analyses (POC)

Microbiome studies have provided important insights into how microorganisms impact human and public health. While a large number of them identify microbial communities in the gastrointestinal tract of humans and animals, there is increasing interest in understanding diversity in the built environment such as food processing facilities. An accurate map of a building’s microbiome requires the use of robust methods capable of recovering a representative collection of all microorganisms found on food-contact and noncontact surfaces. The current approach starts by swabbing surfaces with a pre-wetted swab or sponge, followed by DNA extraction. Given the importance of this step, it is surprising that potential sources of sampling bias are not rigorously tested in most microbiome surveys of food processing plants. In this proof-of-principle study, we will test four sampling-related assumptions made in many microbiome studies, with the longer-term goal of optimizing these methods before using them as part of a study currently funded by the FDA to study Listeria monocytogenes
contamination in apple-packing houses. These assumptions include 1) That microbial communities are similar at proximal sites; 2) That recovery of microbial communities do not differ significantly using sampling devices made with different materials such as polyurethane, polypropylene, and cellulose; 3) That similar communities are recoverable from porous vs. non-porous surfaces; 4) That the amount of time spent swabbing a surface plays little role in the microbial communities recovered.