BioTechnology Institute , University of Minnesota , St. Paul , Minnesota 55108 , United States.
Department of Microbiology & Immunology , University of Minnesota , Minneapolis , Minnesota 55455 , United States.
Environ Sci Technol. 2019 Jan 2;53(1):60-68. doi: 10.1021/acs.est.8b04707. Epub 2018 Dec 6.
Community-based microbial source tracking (MST) utilizes high-throughput DNA sequencing to profile and compare the microbial communities in different fecal sources and environmental samples. SourceTracker, a program that compares a library of OTUs from fecal sources (i.e., sources) to those in environmental samples (i.e., sinks) in order to determine sources of fecal contamination, is an emerging tool for community-based MST studies. In this study, we investigated the ability of SourceTracker to determine sources of known fecal contamination in spiked, in situ mesocosms containing different source contributors. We also evaluated how SourceTracker results were impacted by accounting for autochthonous taxa present in the sink environment. While SourceTracker was able to predict most sources present in the in situ mesocosms, fecal source library composition substantially influenced the program's ability to predict source contributions. Moreover, prediction results were most reliable when the library contained only known sources, autochthonous taxa were accounted for and when source profiles had low intragroup variability. Although SourceTracker struggled to differentiate between sources with similar bacterial community structures, it was able to consistently identify abundant and expected sources, suggesting that the SourceTracker program can be a useful tool for community-based MST studies.
基于社区的微生物源追踪（MST）利用高通量 DNA 测序来分析和比较不同粪便来源和环境样本中的微生物群落。SourceTracker 是一种新兴的基于社区的 MST 研究工具，它将粪便来源（即来源）的 OTU 文库与环境样本（即汇）中的 OTU 文库进行比较，以确定粪便污染的来源。在这项研究中，我们调查了 SourceTracker 确定含有不同来源贡献者的现场中值体中已知粪便污染来源的能力。我们还评估了源追踪器的结果如何受到汇环境中存在的自生分类群的影响。虽然 SourceTracker 能够预测现场中值体中存在的大多数来源，但粪便源文库组成极大地影响了该程序预测源贡献的能力。此外，当文库仅包含已知来源、考虑自生分类群以及源谱内组内变异性较低时，预测结果最可靠。尽管 SourceTracker 难以区分具有相似细菌群落结构的来源，但它能够始终如一地识别丰富且预期的来源，这表明 SourceTracker 程序可以成为基于社区的 MST 研究的有用工具。
