UCD School of Biomolecular and Biomedical Science, UCD Earth Institute, UCD Conway Institute, University College Dublin, Dublin, Ireland.
Computational Genomics Laboratory, Department of Genetics, Microbiology and Statistics, University of Barcelona, Barcelona, Catalonia, Spain.
Sci Total Environ. 2020 Sep 20;736:139573. doi: 10.1016/j.scitotenv.2020.139573. Epub 2020 May 21.
Fecal pollution of water bodies poses a serious threat for public health and ecosystems. Microbial source tracking (MST) is used to track the source of this pollution facilitating better management of pollution at the source. In this study we tested 12 MST markers to track human, ruminant, sheep, horse, pig and gull pollution to assess their usefulness as an effective management tool of water quality. First, the potential of the selected markers to track the source was evaluated using fresh fecal samples. Subsequently, we evaluated their performance in a catchment with different impacts, considering land use and environmental conditions. All MST markers showed high sensitivity and specificity, although none achieved 100% for both. Although some of the MST markers were detected in hosts other than the intended ones, their abundance in the target group was always several orders of magnitude higher than in the non-target hosts, demonstrating their suitability to distinguish between sources of pollution. The MST analysis matched the land use in the watershed allowing an accurate assessment of the main sources of pollution, in this case mainly human and ruminant pollution. Correlating environmental parameters including temperature and rainfall with MST markers provided insight into the dynamics of the pollution in the catchment. The levels of the human marker showed a significant negative correlation with rainfall in human polluted areas suggesting a dilution of the pollution, whereas at agricultural areas the ruminant marker increased with rainfall. There were no seasonal differences in the levels of human marker, indicating human pollution as a constant pressure throughout the year, whereas the levels of the ruminant marker was influenced by the seasons, being more abundant in summer and autumn. MST analysis integrated with land use and environmental data can improve the management of fecal polluted areas and set up best practice.
水体粪便污染对公共卫生和生态系统构成严重威胁。微生物源追踪 (MST) 用于追踪污染来源，从而更好地进行源头污染管理。在本研究中，我们测试了 12 种 MST 标记物，以追踪人类、反刍动物、绵羊、马、猪和海鸥的污染情况，评估它们作为水质有效管理工具的有用性。首先，使用新鲜粪便样本评估所选标记物追踪来源的潜力。随后，我们在具有不同影响的集水区中评估了它们的性能，考虑了土地利用和环境条件。所有 MST 标记物均表现出高灵敏度和特异性，尽管没有一种标记物在两者上均达到 100%。尽管一些 MST 标记物在预期宿主之外的宿主中被检测到，但它们在目标群体中的丰度始终比非目标宿主高几个数量级，证明它们适合区分污染来源。MST 分析与流域中的土地利用相匹配，能够准确评估主要污染源，在这种情况下，主要是人类和反刍动物污染。将环境参数（包括温度和降雨量）与 MST 标记物相关联，提供了对集水区污染动态的深入了解。人类标记物的水平与人类污染区域的降雨量呈显著负相关，表明污染被稀释，而在农业区域，反刍动物标记物随降雨量增加。人类标记物的水平没有季节性差异，表明人类污染是全年持续存在的压力，而反刍动物标记物的水平受季节影响，夏季和秋季更为丰富。与土地利用和环境数据相结合的 MST 分析可以改善粪便污染区域的管理，并制定最佳实践。
