Cytometric fingerprinting for analyzing microbial intracommunity structure variation and identifying subcommunity function
Cytometric fingerprinting for analyzing microbial intracommunity structure variation and identifying subcommunity function
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DOI：
10.1038/nprot.2012.149
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发表时间：
2013-01-01
期刊：
影响因子：
14.8
通讯作者：
Mueller, Susann
中科院分区：
文献类型：
--
作者：
Koch, Christin;Guenther, Susanne;Mueller, Susann
复杂的天然微生物群落的功能是由单个细胞实现的，这些细胞对群落的整体性能有不同的贡献。通常，分子技术和最近的深度测序技术用于对微生物群落进行详细但耗费资源的系统发育或功能分析。在这里，我们提出了一种分析动态群落结构的方法，该方法通过监测细胞特异性和非生物微环境参数的变化来快速检测功能（而不是系统发育）相干的亚群落。该协议涉及使用流式细胞术来分析弹性光散射和荧光细胞标记，随后确定细胞门丰度，最后创建细胞计数社区指纹。非生物参数分析数据与动态细胞指纹图谱相关，以获得有时限的功能热图。该图谱有助于识别群落中的活动热点，这可以通过随后对关键亚群落进行细胞分选和并发系统发育分析（末端限制性片段长度多态性，tRFLP）来进一步解决。细胞计数指纹信息基于门模板设置，并且使用 R 脚本创建功能热图。细胞计数指纹识别和评估可以在 1 天内完成，并且可以在另外的 6 天内获得额外的亚群组成信息。
Functions of complex natural microbial communities are realized by single cells that contribute differently to the overall performance of a community. Usually, molecular and, more recently, deep-sequencing techniques are used for detailed but resource-consuming phylogenetic or functional analyses of microbial communities. Here we present a method for analyzing dynamic community structures that rapidly detects functional (rather than phylogenetic) coherent subcommunities by monitoring changes in cell-specific and abiotic microenvironmental parameters. The protocol involves the use of flow cytometry to analyze elastic light scattering and fluorescent cell labeling, with subsequent determination of cell gate abundance and finally the creation of a cytometric community fingerprint. Abiotic parameter analysis data are correlated with the dynamic cytometric fingerprint to obtain a time-bound functional heat map. The map facilitates the identification of activity hot spots in communities, which can be further resolved by subsequent cell sorting of key subcommunities and concurrent phylogenetic analysis (terminal restriction fragment length polymorphism, tRFLP). The cytometric fingerprint information is based on gate template settings and the functional heat maps are created using an R script. Cytometric fingerprinting and evaluation can be accomplished in 1 d, and additional subcommunity composition information can be obtained in a further 6 d.