Real-time PCR-based quantification of Shigella sonnei in beef and a modified Gompertz equation-based predictive modeling of its growth

Abstract

Shigella sonnei shares many physiological aspects with Escherichia coli; thus, so far no culture-based method has been developed to detect and quantify S. sonnei separately from E. coli. Therefore, little information is available for the growth characteristics of S. sonnei in food. This study aimed to address a systematic scheme to quantify S. sonnei in beef separately from E. coli using quantitative real-time polymerase chain reaction (qRT-PCR) and subsequently predict its growth characteristics. The use of S. sonnei-specific primers in qRT-PCR allowed to obtain growth curves of S. sonnei in beef at different temperatures, and the fitting of curves into a modified Gompertz model let us analyze the growth characteristics such as the lag time, maximum growth rate, and maximum quantity of S. sonnei in beef at different temperatures. A systematic scheme for RT-PCR-based quantification and a predictive modeling described in this study may be a useful means to analyze S. sonnei growth in food.