Optimizing methods for the detection and quantification of infectious human norovirus from fresh berries using human intestinal enteroids

Foodborne viruses, such as human norovirus (HuNoV) and hepatitis A virus (HAV), are responsible for the majority of foodborne outbreaks associated with berries. Identification of these outbreaks relies on epidemiological investigations; however, these viruses are often not isolated from implicated berries. The current FDA standard method for HuNoV and HAV detection in berries relies on detection of small pieces of viral RNA by molecular assays (realtime RT-qPCR). Historically, HuNoV lacked a permissive cell line to estimate its infectivity; in contrast HAV can be adapted to replicate in cell culture such as the FRhK-4 cells (rhesus monkey kidney epithelial cells). A recent breakthrough in HuNoV cell culture allowed the detection of infectious norovirus. This cell culture system is derived from human stem cells that are grown as 3D human intestinal enteroids (HIE), forming mini-guts with similar morphology and functions to the human gut. Therefore, in this project, we propose to optimize the various steps of the FDA standard method for recovery of infectious HuNoV and HAV from berries using HIE and FRhK-4 cells, respectively. The optimized method’s detection limit, recovery efficiency, as well as the relationship between viral RNA or Ct values and infectivity, will be determined for both viruses using various berries (blueberry, blackberry, raspberry and strawberry). The optimized method will be used to investigate the persistence of infectious HuNoV and HAV on various berries under postharvest conditions. Using the novel cell culture system for HuNoV, this project is uniquely designed to optimize the FDA standard method for detection of infectious HuNoV and HAV from various berries and to generate the necessary log-reduction data for future QMRA studies.