Defining Niche-Specific Microbial Community Dynamics To Inform Targeted Sanitation And Hygienic Design

Thelong-term goalof this proposal is to reduce environmental cross-contamination during food manufacturing. A barrier to achieving this goal is thatcurrent environmental sanitation strategies often neglect niche-specific differences in microbial load and community composition. We propose leveraging a combination of metagenomic, machine learning, and Multiphysics modeling tools to define the attributes of niches which drive microbial selection and mediate the physical aspects of sanitation. Our findings will guide the development of targeted principles in sanitation and hygienic design that will reduce the incidence of pathogen cross-contamination that leads to outbreaks and recalls.We aim to define the specific microbial communities within different environmental niches to better understand the reservoirs of environmental pathogens likeL. monocytogenes. We will collect 1,200 environmental samples from three large dairy plants and use targeted metagenomics to define the microbiome of different niches. We will then apply machine learning algorithms to identify the features most predictive of specific microbial taxa, verifying these associations using laboratory studies. Finally, we will explore how complex features of the niche impact environmental sanitation by restricting fluid flow, quantifying wall shear stress and using sanitation challenge studies to determine how sanitation impacts diverse microbial communities.Overall goals:Identifying the locations in food plants that harbor particular bacterial and fungal populations will improve our ability to assess risk and more efficiently track and eliminate contaminants. The findings from this work will enable plant staff to more rapidlyidentify the most effective interventions, rather than having to try a range of potential interventions in the hopes of addressing the root cause. Targeted interventions will in turn save the plant money. Our work can also enable more precise assessments ofL. monocytogenescross-protection within biofilms so that plants can more strategically apply enhanced sanitation. Overall, we aim to reduce the incidence of cross-contamination, decrease the likelihood and duration of outbreaks, reduce food waste, limit the application of excessive and wasteful sanitizer, and increase customer satisfaction.Structural design is strongly predictive of pathogen harborage. However, capital investments are expensive, and it is difficult to ensure that niches will be eliminated. Additionally, preventative maintenance, such as the regular replacement of wearable goods, has been shown to improve control over environmental biota. Yet, with limited direct evidence, maintenance staff are often left to self-determine the frequency and nature of these activities. In the long term, our work can help plants identify problematic niches by their attributes and implement strategic capital improvements in hygienic design and preventative maintenance.