16S rRNA-based assays for quantitative detection of universal, human-, cow-, and dog-specific fecal Bacteroidales:: A Bayesian approach
16S rRNA-based assays for quantitative detection of universal, human-, cow-, and dog-specific fecal Bacteroidales:: A Bayesian approach
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DOI：
10.1016/j.watres.2007.06.037
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发表时间：
2007-08-01
期刊：
影响因子：
12.8
通讯作者：
Wuertz, Stefan
中科院分区：
文献类型：
--
作者：
Kildare, Beverly J.;Leutenegger, Christian M.;Wuertz, Stefan
我们报道了基于从拟杆菌目未培养细胞中扩增粪便16S rRNA标记序列而设计和验证的用于微生物来源追踪的新的TaqMan((R))检测方法。建立了排泄物污染对流域非点源输入的检测和计数方法。Bac Uni-UCD定量检测来自人类志愿者(18个样本中的18个)、猫(7个样本中的7个)、狗(8个样本中的8个)、海鸥(10个样本)、牛(8个样本)、马(8个样本)和废水样本(14个样本)的所有被测粪便样本。人的BacHum-UCD试验完全区分了人和牛的粪便样本，但没有检测到来自人类志愿者的所有粪便样本(12/18)。此外，狗粪便的检出率为12.5%(1/8)，但与猫、马或海鸥的粪便样本无交叉反应。相比之下，所有废水样本的BacHum-UCD标记均为阳性，支持将其指定为100%灵敏的混合人类来源鉴定。牛的特异性检测BacCow-UCD完全区分了牛和人的粪便样本。马粪的检出率为38%(3/8)，但与所检测的任何其他动物粪便样本均无交叉特异性。犬粪检出阳性率为62.5%(5/8)，对犬、牛粪便和海鸥粪标本有较好的鉴别能力。与人粪便22.2%(4/18)、猫粪14.3%(117)、废水28.6%(4/14)有一定的交叉反应。在使用粪便样本进行验证后，使用单盲测试进一步证明了所开发的标记物的有效性；在对水样本中存在的混合粪便来源进行定量方面，所有的分析方法都是灵敏、可重复性和准确的。最后，将新的检测方法与以前发表的序列进行了比较，结果表明新的方法更加特异和灵敏。使用贝叶斯定理，我们计算了四种检测方法正确识别加利福尼亚州一个特定分水岭的一般和宿主特定排泄物污染的条件概率，该分水岭已经分析了73个水样。这种方法允许直接比较不同的MST方法的效果，包括那些基于依赖图书馆的方法的方法。对于通用标记BacUni-UCD，检测到该标记时存在粪便污染的概率为1.00；对于人检测HF160F、奶牛检测BacCow-UCD和狗检测Baccan-UCD，存在宿主特定污染的概率分别为0.98、0.84和0.89。这些标记的应用将为帮助识别和控制受损流域的粪便污染源提供有意义的信息。(C)2007年由爱思唯尔有限公司出版。
We report the design and validation of new TaqMan((R)) assays for microbial source tracking based on the amplification of fecal 16S rRNA marker sequences from uncultured cells of the order Bacteroidales. The assays were developed for the detection and enumeration of non-point source input of fecal pollution to watersheds. The quantitative "universal" Bacteriodales assay BacUni-UCD detected all tested stool samples from human volunteers (18 out of 18), cat (7 out of 7), dog (8 out of 8), seagull (10/10), cow (8/8), horse (8/8), and wastewater effluent (14/14). The human assay BacHum-UCD discriminated fully between human and cow stool samples but did not detect all stool samples from human volunteers (12/18). In addition, there was 12.5% detection of dog stool (1/8), but no cross-reactivity with cat, horse, or seagull fecal samples. In contrast, all wastewater samples were positive for the BacHum-UCD marker, supporting its designation as 100% sensitive for mixed-human source identification. The cow-specific assay BacCow-UCD fully discriminated between cow and human stool samples. There was 38% detection of horse stool (3/8), but no cross-specificity with any of the other animal stool samples tested. The dog assay BacCan-UCD discriminated fully between dog and cow stool or seagull guano samples and detected 62.5% stool samples from dogs (5/8). There was some cross-reactivity with 22.2% detection of human stool (4/18), 14.3% detection of cat stool (117), and 28.6% detection of wastewater samples (4/14). After validation using stool samples, single-blind tests were used to further demonstrate the efficacy of the developed markers; all assays were sensitive, reproducible, and accurate in the quantification of mixed fecal sources present in aqueous samples. Finally, the new assays were compared with previously published sequences, which showed the new methodologies to be more specific and sensitive. Using Bayes' Theorem, we calculated the conditional probability that the four assays would correctly identify general and host-specific fecal pollution in a specific watershed in California for which 73 water samples had been analyzed. Such an approach allows for a direct comparison of the efficacy of different MST methods, including those based on library-dependent methodologies. For the universal marker BacUni-UCD, the probability that fecal pollution is present when the marker is detected was 1.00; the probability that host-specific pollution is present was 0.98, 0.84, and 0.89 for the human assay HF160F, the cow assay BacCow-UCD, and the dog assay BacCan-UCD, respectively The application of these markers should provide meaningful information to assist with efforts to identify and control sources of fecal pollution to impaired watersheds. (c) 2007 Published by Elsevier Ltd.