Pioneering use of human intestinal enteroids to prevent foodborne transmission of human norovirus

Human norovirus (HuNoV) is a leading cause of foodborne viral gastroenteritis and a significant public health concern. Its high transmission rates and ability to persist in diverse environments contribute to substantial morbidity and economic burden. Traditional cell culture methodologies have proven inadequate for HuNoV research due to the inability of the virus to replicate in conventional cell lines. However, the recent development of human intestinal enteroid (HIE) cell cultures, which support HuNoV replication, has advanced our understanding of this challenging virus. This review provides an updated analysis of research on the applications of the HIE model to control HuNoV across various food systems. It examines the challenges associated with HuNoV replication, and explores the potential of HIE models to help mitigate foodborne transmission of HuNoV. Finally, the review discusses the limitations of current HIE methodologies and outlines promising avenues of future research to improve preventive and control strategies, ultimately reducing the risk of HuNoV exposure for consumers. The HIE system offers a physiologically relevant model for studying HuNoV infectivity, survival, and inactivation, aiding the development of effective strategies to prevent and control foodborne transmission. While limited for routine detection, integrating HIE studies with RNA detection, surrogate research, data modeling, and risk assessment is recommended to comprehensively evaluate and enhance the reliability of strategies for real-world food safety applications. • Foodborne HuNoV outbreaks significantly threaten global public health. • HuNoV research has been hindered by the lack of effective cell culture models • Human intestinal enteroids enhance understanding and control of HuNoV infections • HIE aids in assessing HuNoV persistence and control in food systems • Optimizing HIE will enable the study of HuNoV infectivity in complex food matrices