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Biology subjects

Snyder, A. B.

Publications and source records attributed to Snyder, A. B..

2 recordsLinked to original sources

Reduction of Listeria on stainless steel surfaces is impacted by sanitizer application method

Pathogen cross-contamination during food production is controlled through sanitation. However, sanitizer efficacy is often studied in bench-scale experiments (e.g., submerged coupons in static or stirred sanitizer) which poorly approximate fluid dynamics. This limits our understanding of how effective sanitization is in commercial application. This study paired computational fluid dynamic (CFD) estimates of shear stress during spray application of sanitizer with measurements of Listeria innocua reduction on stainless steel by 100 ppm hypochlorite sanitizer under various application methods. Static submersion of inoculated coupons for 3 s resulted in a log reduction of 2.3 {+/-} 0.1 log CFU. Bench-scale spray application for 3 s had the largest microbial reduction at the point of sanitizer spray impingement (7.5 {+/-} 0.5 log CFU) and directly adjacent to the impingement point (6.4 {+/-} 0.7 log CFU) where shear stress was the highest. Surface locations below the impingement point that only received fluid film sanitizer run-off had a significantly lower microbial reduction of 0.4 {+/-} 0.1 log CFU (p < 0.05). At the pilot scale, sanitizer spray manually applied by operators achieved a 2.5 {+/-} 0.4 log CFU reduction, which was significantly lower than what was achieved during bench-scale spray application (p < 0.05). Microbial reduction from manual operation of spray equipment was also significantly different among operators (p < 0.05). Discrepancies between bench-scale spraying, pilot-scale spraying, and submerged coupons underscores the need for sanitizer validation under realistic conditions to better understand the risk reduction achieved through sanitation programs during food processing.

microbiology↗

A schema for digitized surface swab site metadata in open-source DNA sequence databases

Large, open-source DNA sequence databases have been generated, in part, through the collection of microbial pathogens from swabbing surfaces in built environments. Analyzing these data in aggregate through public health surveillance requires digitization of the complex, domain-specific metadata associated with swab site locations. However, the swab site location information is currently collected in a single, free-text "isolation source" field promoting generation of poorly detailed descriptions with varying word order, granularity, and linguistic errors, making automation difficult and reducing machine-actionability. We assessed 1,498 free-text swab site descriptions generated during routine foodborne pathogen surveillance. The lexicon of free-text metadata was evaluated to determine the informational facets and quantity of unique terms used by data collectors. Open Biological Ontologies (OBO) foundry libraries were used to develop hierarchical vocabularies connected with logical relationships to describe swab site locations. Five informational facets described by 338 unique terms were identified via content analysis. Term hierarchy facets were developed as were statements (called axioms) about how entities within these five domains were related. The schema developed through this study has been integrated into a publicly available pathogen metadata standard, facilitating ongoing surveillance and investigations. The One Health Enteric Package is available at NCBI BioSample beginning in 2022. Collective use of metadata standards increases the interoperability of DNA sequence databases, enabling large-scale approaches to data sharing, artificial intelligence, and big-data solutions to food safety. IMPORTANCERegular analysis of whole genome sequence data in collections such as NCBIs Pathogen Detection Database is used by many public health organizations to detect outbreaks of infectious disease. However, isolate metadata in these databases are often incomplete and poor quality. These complex raw metadata must often be re-organized and manually formatted for use in aggregate analysis. These processes are inefficient and time-consuming, increasing the interpretative labor needed by public health groups to extract actionable information. Future use of open genomic epidemiology networks will be supported through the development of an internationally applicable vocabulary system to describe swab site locations.

genomics↗