Expanding the Use of Farmer-Run Biphasic Vibrio Test Kits to Monitor Seafood Safety in Oysters

Abstract

Vibrio vulnificus (Vv) and V. parahaemolyticus (Vp) are naturally occurring estuarine bacteria that are of concern due to their potential to cause illness in humans upon the consumption of raw shellfish. However, testing capabilities for these bacteria are limited and expensive, and do not allow for testing at the farm-level where management practices substantially influence Vibrio abundances. In this study, novel biphasic assays for Vv and Vp were evaluated for accuracy and on-farm use to empower farmers to gain insights into their own sites’ dynamics. The objectives for chapter 1 were to 1) evaluate the ruggedness of the biphasic assays to reagent variation, 1) determine if the biphasic assays produced comparable results to that of an FDA-approved method, and 3) evaluate the specificity of the assays to their target Vibrio species. Vv assays were comparable to real-time PCR results, robust to reagent variation, and highly specific. In contrast, Vp assays had the tendency to underestimate Vp abundance, produced significantly different results between reagent lots, and generated numerous false positives when pure Vibrio isolates were tested, indicating further optimization is required to improve reliability and consistency across reagent lots and environmental conditions. The objective of chapter 2 was to implement and assess the feasibility of using Vibrio biphasic assays to monitor Vv and Vp at two U.S. Gulf Coast oyster farms. Following 2-5 training sessions, growers were able to independently perform the assays. Farmers were able to generate seasonal data that was consistent with the literature. This study demonstrated that these assays can be readily incorporated on oyster farms, providing growers with the ability to evaluate Vibrio risk. More broadly, the implementation of decentralized testing has the potential to improve industry awareness, enhance management strategies and inform regulatory discussions by incorporating site-specific data in risk assessment frameworks.