Cookson Adrian L, Marshall Jonathan C, Biggs Patrick J, Rogers Lynn E, Collis Rose M, Devane Megan, Stott Rebecca, Brightwell Gale
Food System Integrity, AgResearch Limited, Hopkirk Research Institute, Massey University, Cnr University Avenue and Library Road, Private Bag 11008, Palmerston North, 4442, New Zealand.
mEpiLab, School of Veterinary Science, Massey University, Palmerston North, New Zealand.
Sci Rep. 2024 Dec 30;14(1):32099. doi: 10.1038/s41598-024-83594-y.
Understanding the composition of complex Escherichia coli populations from the environment is necessary for identifying strategies to reduce the impacts of fecal contamination and protect public health. Metabarcoding targeting the hypervariable gene gnd was used to reveal the complex population diversity of E. coli and phenotypically indistinct Escherichia species in water, soil, sediment, aquatic biofilm, and fecal samples from native forest and pastoral sites. The resulting amplicons were cross-referenced against a database containing over 700 different partial gnd sequences from E. coli/non-E. coli Escherichia species. Alpha and beta measures of diversity of Escherichia populations were lowest in feces, soil and sediment compared to water and aquatic biofilm samples. Escherichia populations recovered from extensive freshwater catchments dominated by sheep, beef and dairy farming were extremely diverse but well-separated from a wetland dairy site. In contrast, Escherichia populations from the low-impact native forest site with fewer fecal sources were less diverse. Metabarcoding distinguished E. coli populations important to fecal contamination monitoring from non-E. coli Escherichia environmental populations. These data represent in-depth analysis and geographic stability of Escherichia populations from environmental samples with extensive heterogeneity, and reveal links with diverse fecal sources, land-use and the overall burden of fecal contamination at sample sites.
了解环境中复杂的大肠杆菌种群组成对于确定减少粪便污染影响和保护公众健康的策略至关重要。针对高变基因gnd的宏条形码技术被用于揭示水、土壤、沉积物、水生生物膜以及来自原生森林和牧场的粪便样本中大肠杆菌和表型难以区分的埃希氏菌属物种的复杂种群多样性。将所得扩增子与一个数据库进行交叉比对，该数据库包含来自大肠杆菌/非大肠杆菌埃希氏菌属物种的700多个不同的部分gnd序列。与水和水生生物膜样本相比，粪便、土壤和沉积物中埃希氏菌种群的α和β多样性指标最低。从以绵羊、牛肉和奶牛养殖为主的广阔淡水集水区中回收的埃希氏菌种群极为多样，但与一个湿地奶牛场的种群有明显区分。相比之下，来自粪便来源较少的低影响原生森林地点的埃希氏菌种群多样性较低。宏条形码技术区分了对粪便污染监测重要的大肠杆菌种群和非大肠杆菌埃希氏菌环境种群。这些数据代表了对具有广泛异质性的环境样本中埃希氏菌种群的深入分析和地理稳定性，并揭示了与不同粪便来源、土地利用以及样本地点粪便污染总体负担的联系。
