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Phylogenetic beta diversity metrics, trait evolution and inferring the functional beta diversity of communities.系统发育β多样性测度、性状进化及推断群落的功能β多样性。
PLoS One. 2011;6(6):e21264. doi: 10.1371/journal.pone.0021264. Epub 2011 Jun 24.
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Moving pictures of the human microbiome.人体微生物组的动态图像。
Genome Biol. 2011;12(5):R50. doi: 10.1186/gb-2011-12-5-r50.
3
Vancomycin-resistant Enterococcus domination of intestinal microbiota is enabled by antibiotic treatment in mice and precedes bloodstream invasion in humans.万古霉素耐药肠球菌在肠道微生物群中的主导地位是由小鼠的抗生素治疗所促成的,并且先于人类的血流感染。
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Evidence for bacteriophage activity causing community and performance changes in a phosphorus-removal activated sludge.噬菌体活动导致除磷活性污泥中群落和性能变化的证据。
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5
Microbial community resemblance methods differ in their ability to detect biologically relevant patterns.微生物群落相似性方法在检测具有生物学意义的模式方面的能力存在差异。
Nat Methods. 2010 Oct;7(10):813-9. doi: 10.1038/nmeth.1499. Epub 2010 Sep 5.
6
Monitoring associations between clade-level variation, overall community structure and ecosystem function in enhanced biological phosphorus removal (EBPR) systems using terminal-restriction fragment length polymorphism (T-RFLP).利用末端限制性片段长度多态性(T-RFLP)监测增强生物除磷(EBPR)系统中进化枝水平变异、整体群落结构和生态系统功能之间的关联。
Water Res. 2010 Sep;44(17):4908-23. doi: 10.1016/j.watres.2010.07.028. Epub 2010 Jul 16.
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Soil bacterial and fungal communities across a pH gradient in an arable soil.耕地土壤 pH 梯度上的土壤细菌和真菌群落。
ISME J. 2010 Oct;4(10):1340-51. doi: 10.1038/ismej.2010.58. Epub 2010 May 6.
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Forensic identification using skin bacterial communities.利用皮肤细菌群落进行法医鉴定。
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Bacterial community variation in human body habitats across space and time.人体不同空间和时间栖息地的细菌群落变化。
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10
Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities.介绍 mothur:开源、独立于平台、社区支持的软件,用于描述和比较微生物群落。
Appl Environ Microbiol. 2009 Dec;75(23):7537-41. doi: 10.1128/AEM.01541-09. Epub 2009 Oct 2.

系统发育分化的度量为微生物群落提供了强有力且互补的见解。

Measures of phylogenetic differentiation provide robust and complementary insights into microbial communities.

机构信息

Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada.

出版信息

ISME J. 2013 Jan;7(1):173-83. doi: 10.1038/ismej.2012.88. Epub 2012 Aug 2.

DOI:10.1038/ismej.2012.88
PMID:22855211
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3526167/
Abstract

High-throughput sequencing techniques have made large-scale spatial and temporal surveys of microbial communities routine. Gaining insight into microbial diversity requires methods for effectively analyzing and visualizing these extensive data sets. Phylogenetic β-diversity measures address this challenge by allowing the relationship between large numbers of environmental samples to be explored using standard multivariate analysis techniques. Despite the success and widespread use of phylogenetic β-diversity measures, an extensive comparative analysis of these measures has not been performed. Here, we compare 39 measures of phylogenetic β diversity in order to establish the relative similarity of these measures along with key properties and performance characteristics. While many measures are highly correlated, those commonly used within microbial ecology were found to be distinct from those popular within classical ecology, and from the recently recommended Gower and Canberra measures. Many of the measures are surprisingly robust to different rootings of the gene tree, the choice of similarity threshold used to define operational taxonomic units, and the presence of outlying basal lineages. Measures differ considerably in their sensitivity to rare organisms, and the effectiveness of measures can vary substantially under alternative models of differentiation. Consequently, the depth of sequencing required to reveal underlying patterns of relationships between environmental samples depends on the selected measure. Our results demonstrate that using complementary measures of phylogenetic β diversity can further our understanding of how communities are phylogenetically differentiated. Open-source software implementing the phylogenetic β-diversity measures evaluated in this manuscript is available at http://kiwi.cs.dal.ca/Software/ExpressBetaDiversity.

摘要

高通量测序技术使大规模的微生物群落时空调查成为常规。深入了解微生物多样性需要有效的方法来分析和可视化这些广泛的数据。系统发育β多样性度量方法通过允许使用标准多元分析技术来探索大量环境样本之间的关系来解决这一挑战。尽管系统发育β多样性度量方法取得了成功并得到了广泛应用,但尚未对这些方法进行广泛的比较分析。在这里,我们比较了 39 种系统发育β多样性度量方法,以确定这些度量方法之间的相对相似性以及关键特性和性能特征。虽然许多度量方法高度相关,但在微生物生态学中常用的度量方法与在经典生态学中流行的度量方法以及最近推荐的 Gower 和 Canberra 度量方法不同。许多度量方法对基因树的不同根、用于定义操作分类单位的相似性阈值的选择以及偏离的基础谱系非常稳健。这些度量方法在对稀有生物的敏感性和在替代分化模型下的有效性方面有很大差异。因此,揭示环境样本之间关系的潜在模式所需的测序深度取决于所选的度量方法。我们的结果表明,使用系统发育β多样性的补充度量方法可以进一步了解群落如何在系统发育上有所区别。本文评估的系统发育β多样性度量方法的开源软件可在 http://kiwi.cs.dal.ca/Software/ExpressBetaDiversity 上获得。