Department of Water Resources and Environment, Sun Yat-sen University, Guangzhou, 510275, PR China.
The Key Laboratory of Water and Air Pollution Control of Guangdong Province, South China Institute of Environmental Sciences, Ministry of Ecology and Environment of the People's Republic of China, Guangzhou, 510000, PR China; State Environmental Protection Key Laboratory of Water Environmental Simulation and Pollution Control, South China Institute of Environmental Sciences, Ministry of Ecology and Environment of the People's Republic of China, Guangzhou, 510530, PR China.
Water Res. 2020 May 15;175:115670. doi: 10.1016/j.watres.2020.115670. Epub 2020 Mar 2.
Numerous genetic markers have been developed to establish microbial source tracking (MST) assays in the last decade. However, the selection of suitable markers is challenging due to a lack of understanding of fundamental factors such as sensitivity, specificity, and concentration in target/nontarget hosts, especially in East Asia. In this study, a total of 506 faecal samples comprised of human and 12 nonhuman hosts were collected from 28 cities across China and tested for marker performance characteristics. We firstly tested 40 host-associated markers based on a binary (presence/absence) criterion. Here, 15 markers (7 human-associated, 4 pig-associated, 3 ruminant-associated, and 1 poultry-associated) showed potential applicability in our study area. The selected 15 markers were then tested using qualitative and quantitative methods to characterise their performance. Overall, Bacteroidales markers presented higher sensitivity and concentrations in target samples compared to other bacterial or viral markers, but their specificity was low. Among nontarget samples, pets accounted for 43.7% and 35.7% of cross-reactivity with human-associated and poultry-associated markers, respectively. Noncommon animals, including horse and donkey, contributed 61.3% of cross-reactivity with ruminant-associated markers. When considering the quantitative distribution of markers, their concentration in nontarget samples were 1-3 orders of magnitude lower than in target samples. Moreover, a novel classification method was proposed to classify the nontarget hosts into four groups spanning "no cross-reactivity", "weak cross-reactivity", "moderate cross-reactivity", and "strong cross-reactivity" animal hosts. There were 77.9% nontarget samples identified as no cross-reactivity and weak cross-reactivity hosts, suggesting that these nontarget hosts produce little interference for corresponding markers. Our findings elucidate the performance of host-associated markers around China in a qualitative and quantitative manner, and reveal the interference degree of cross-reactivity from nontarget animals to genetic markers, which will facilitate tracking of multiple faecal pollution sources and planning timely remedial strategies in China.
在过去十年中，已经开发出许多遗传标记来建立微生物源追踪 (MST) 测定。然而，由于缺乏对基本因素（如敏感性、特异性和目标/非目标宿主中的浓度）的理解，选择合适的标记仍然具有挑战性，尤其是在东亚。在本研究中，共收集了来自中国 28 个城市的 506 个人和 12 种非人类宿主的粪便样本，并对标记性能特征进行了测试。我们首先基于二元（存在/不存在）标准测试了 40 个宿主相关标记。其中，15 个标记（7 个人类相关、4 个猪相关、3 个反刍动物相关和 1 个家禽相关）在我们的研究区域具有潜在适用性。然后使用定性和定量方法测试了选定的 15 个标记，以表征其性能。总体而言，与其他细菌或病毒标记相比，Bacteroidales 标记在目标样本中表现出更高的敏感性和浓度，但特异性较低。在非目标样本中，宠物分别占人类相关和家禽相关标记交叉反应的 43.7%和 35.7%。非常见动物，包括马和驴，与反刍动物相关标记的交叉反应率为 61.3%。考虑到标记的定量分布，它们在非目标样本中的浓度比目标样本低 1-3 个数量级。此外，提出了一种新的分类方法，将非目标宿主分为四个组，涵盖“无交叉反应”、“弱交叉反应”、“中等交叉反应”和“强交叉反应”动物宿主。有 77.9%的非目标样本被确定为无交叉反应和弱交叉反应宿主，这表明这些非目标宿主对相应标记产生的干扰很小。我们的研究结果以定性和定量的方式阐明了中国周边地区宿主相关标记的性能，并揭示了非目标动物对遗传标记的交叉反应干扰程度，这将有助于跟踪多种粪便污染源并在中国制定及时的补救策略。
