Institute of Environmental Science and Research, Christchurch Science Centre, P.O. Box 29-181, Ilam, Christchurch, New Zealand.
Appl Environ Microbiol. 2011 Apr;77(7):2458-70. doi: 10.1128/AEM.02322-10. Epub 2011 Feb 4.
Shiga toxin-producing Escherichia coli (STEC) is a zoonotic pathogen that causes diarrheal disease in humans and is of public health concern because of its ability to cause outbreaks and severe disease such as hemorrhagic colitis or hemolytic-uremic syndrome. More than 400 serotypes of STEC have been implicated in outbreaks and sporadic human disease. The aim of this study was to develop a PCR binary typing (P-BIT) system that could be used to aid in risk assessment and epidemiological studies of STEC by using gene targets that would represent a broad range of STEC virulence genes. We investigated the distribution of 41 gene targets in 75 O157 and non-O157 STEC isolates and found that P-BIT provided 100% typeability for isolates, gave a diversity index of 97.33% (compared with 99.28% for XbaI pulsed-field gel electrophoresis [PFGE] typing), and produced 100% discrimination for non-O157 STEC isolates. We identified 24 gene targets that conferred the same level of discrimination and produced the same cluster dendrogram as the 41 gene targets initially examined. P-BIT clustering identified O157 from non-O157 isolates and identified seropathotypes associated with outbreaks and severe disease. Numerical analysis of the P-BIT data identified several genes associated with human or nonhuman sources as well as high-risk seropathotypes. We conclude that P-BIT is a useful approach for subtyping, offering the advantage of speed, low cost, and potential for strain risk assessment that can be used in tandem with current molecular typing schema for STEC.
产志贺毒素大肠杆菌(STEC)是一种人畜共患病病原体,可引起人类腹泻病,因其引发暴发和严重疾病(如出血性结肠炎或溶血尿毒综合征)的能力而引起公共卫生关注。超过 400 种 STEC 血清型与暴发和散发性人类疾病有关。本研究旨在开发一种 PCR 二元分型(P-BIT)系统,该系统可用于通过使用代表广泛 STEC 毒力基因的基因靶标来辅助 STEC 的风险评估和流行病学研究。我们调查了 75 株 O157 和非 O157 STEC 分离株中 41 个基因靶标的分布情况,发现 P-BIT 对分离株的分型率为 100%,多样性指数为 97.33%(与 XbaI 脉冲场凝胶电泳[PFGE]分型的 99.28%相比),而非 O157 STEC 分离株的分辨率为 100%。我们确定了 24 个基因靶标,它们提供了与最初检查的 41 个基因靶标相同的分辨率,并产生了相同的聚类树状图。P-BIT 聚类可将 O157 与非 O157 分离株区分开来,并确定与暴发和严重疾病相关的血清型。对 P-BIT 数据的数值分析确定了与人类或非人类来源以及高风险血清型相关的几个基因。我们得出结论,P-BIT 是一种有用的亚型分析方法,具有速度快、成本低和对 STEC 菌株风险评估的潜力等优点,可与当前的分子分型方案结合使用。