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Blautia and Prevotella sequences distinguish human and animal fecal pollution in Brazil surface waters.布劳特氏菌属和普雷沃氏菌属序列可区分巴西地表水的人和动物粪便污染。
Environ Microbiol Rep. 2014 Dec;6(6):696-704. doi: 10.1111/1758-2229.12189. Epub 2014 Jul 9.
2
A single genus in the gut microbiome reflects host preference and specificity.肠道微生物群中的一个单一属反映了宿主偏好和特异性。
ISME J. 2015 Jan;9(1):90-100. doi: 10.1038/ismej.2014.97. Epub 2014 Jun 17.
3
Improved HF183 quantitative real-time PCR assay for characterization of human fecal pollution in ambient surface water samples.用于表征环境地表水样品中人类粪便污染的改进型HF183定量实时PCR检测法。
Appl Environ Microbiol. 2014 May;80(10):3086-94. doi: 10.1128/AEM.04137-13. Epub 2014 Mar 7.
4
A comprehensive evaluation of multicategory classification methods for microbiomic data.宏基因组数据多分类方法的综合评价。
Microbiome. 2013 Apr 5;1(1):11. doi: 10.1186/2049-2618-1-11.
5
Ecological succession and stochastic variation in the assembly of Arabidopsis thaliana phyllosphere communities.拟南芥叶际群落组装中的生态演替与随机变化。
mBio. 2014 Jan 21;5(1):e00682-13. doi: 10.1128/mBio.00682-13.
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Host-specificity among abundant and rare taxa in the sponge microbiome.海绵共生微生物组中丰度高和丰度低的分类群之间的宿主特异性。
ISME J. 2014 Jun;8(6):1198-209. doi: 10.1038/ismej.2013.227. Epub 2014 Jan 9.
7
Oligotyping: Differentiating between closely related microbial taxa using 16S rRNA gene data.寡核苷酸分型:利用16S rRNA基因数据区分密切相关的微生物分类群。
Methods Ecol Evol. 2013 Dec 1;4(12):1111-9. doi: 10.1111/2041-210X.12114.
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Diet rapidly and reproducibly alters the human gut microbiome.饮食可快速且可重复地改变人类肠道微生物组。
Nature. 2014 Jan 23;505(7484):559-63. doi: 10.1038/nature12820. Epub 2013 Dec 11.
9
Analysis of the gull fecal microbial community reveals the dominance of Catellicoccus marimammalium in relation to culturable Enterococci.对海鸥粪便微生物群落的分析表明,相对于可培养的肠球菌,海生哺乳动物卡特球菌占主导地位。
Appl Environ Microbiol. 2014 Jan;80(2):757-65. doi: 10.1128/AEM.02414-13. Epub 2013 Nov 15.
10
Assessment of a new Bacteroidales marker targeting North American beaver (Castor canadensis) fecal pollution by real-time PCR.应用实时 PCR 评估一种针对北美的海狸(Castor canadensis)粪便污染的新型拟杆菌目标记物。
J Microbiol Methods. 2013 Nov;95(2):201-6. doi: 10.1016/j.mimet.2013.08.016. Epub 2013 Aug 31.

发现粪便污染的新指标。

Discovering new indicators of fecal pollution.

作者信息

McLellan Sandra L, Eren A Murat

机构信息

School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, WI, USA.

Josephine Bay Paul Center, Marine Biological Laboratory, Woods Hole, MA, USA.

出版信息

Trends Microbiol. 2014 Dec;22(12):697-706. doi: 10.1016/j.tim.2014.08.002. Epub 2014 Sep 5.

DOI:10.1016/j.tim.2014.08.002
PMID:25199597
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4256112/
Abstract

Fecal pollution indicators are essential to identify and remediate contamination sources and protect public health. Historically, easily cultured facultative anaerobes such as fecal coliforms, Escherichia coli, or enterococci have been used but these indicators generally provide no information as to their source. More recently, molecular methods have targeted fecal anaerobes, which are much more abundant in humans and other mammals, and some strains appear to be associated with particular host sources. Next-generation sequencing and microbiome studies have created an unprecedented inventory of microbial communities associated with fecal sources, allowing reexamination of which taxonomic groups are best suited as informative indicators. The use of new computational methods, such as oligotyping coupled with well-established machine learning approaches, is providing new insights into patterns of host association. In this review we examine the basis for host-specificity and the rationale for using 16S rRNA gene targets for alternative indicators and highlight two taxonomic groups, Bacteroidales and Lachnospiraceae, which are rich in host-specific bacterial organisms. Finally, we discuss considerations for using alternative indicators for water quality assessments with a particular focus on detecting human sewage sources of contamination.

摘要

粪便污染指标对于识别和整治污染源以及保护公众健康至关重要。历史上,一直使用易于培养的兼性厌氧菌,如粪大肠菌群、大肠杆菌或肠球菌,但这些指标通常无法提供关于其来源的信息。最近,分子方法针对的是粪便厌氧菌,它们在人类和其他哺乳动物中更为丰富,并且一些菌株似乎与特定宿主来源相关。新一代测序和微生物组研究已经创建了与粪便来源相关的微生物群落的前所未有的清单,从而能够重新审视哪些分类群最适合作为信息性指标。使用新的计算方法,如寡核苷酸分型与成熟的机器学习方法相结合,正在为宿主关联模式提供新的见解。在本综述中,我们研究了宿主特异性的基础以及使用16S rRNA基因靶点作为替代指标的基本原理,并强调了两个分类群,拟杆菌目和毛螺菌科,它们富含宿主特异性细菌生物体。最后,我们讨论了使用替代指标进行水质评估的注意事项,特别关注检测人类污水污染源。