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首页> 外文期刊>Proceedings of the National Academy of Sciences of the United States of America >Systems-level analysis of microbial community organization through combinatorial labeling and spectral imaging
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Systems-level analysis of microbial community organization through combinatorial labeling and spectral imaging

机译：通过组合标记和光谱成像对微生物群落组织进行系统级分析

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摘要

Microbes in nature frequently function as members of complex multitaxon communities, but the structural organization of these communities at the micrometer level is poorly understood because of limitations in labeling and imaging technology. We report here a combinatorial labeling strategy coupled with spectral image acquisition and analysis that greatly expands the number of fluorescent signatures distinguishable in a single image. As an imaging proof of principle, we first demonstrated visualization of Escheri-chia coli labeled by fluorescence in situ hybridization (FISH) with 28 different binary combinations of eight f luorophores. As a biological proof of principle, we then applied this Combinatorial Labeling and Spectral Imaging FISH (CLASI-FISH) strategy using genus- and family-specific probes to visualize simultaneously and differentiate 15 different phylotypes in an artificial mixture of laboratory-grown microbes. We then illustrated the utility of our method for the structural analysis of a natural microbial community, namely, human dental plaque, a microbial biofilm. We demonstrate that 15 taxa in the plaque community can be imaged simultaneously and analyzed and that this community was dominated by early colonizers, including species of Streptococcus, Prevotella, Actinomyces, and Veillonella. Proximity analysis was used to determine the frequency of inter- and intrataxon cell-to-cell associations which revealed statistically significant intertaxon pairings. Cells of the genera Prevotella and Actinomyces showed the most interspecies associations, suggesting a central role for these genera in establishing and maintaining biofilm complexity. The results provide an initial systems-level structural analysis of biofilm organization.
机译：自然界中的微生物经常充当复杂的多分类群社区的成员，但是由于标记和成像技术的局限性，人们对这些社区在微米级别的结构组织了解甚少。我们在这里报告了结合光谱图像采集和分析的组合标记策略，该方法极大地扩展了单个图像中可区分的荧光标记的数量。作为原理的成像证明，我们首先展示了通过荧光原位杂交（FISH）和8种荧光团的28种不同二元组合标记的大肠杆菌的可视化效果。作为原理的生物学证明，我们然后使用属和家族特异性探针应用了这种组合标记和光谱成像FISH（CLASI-FISH）策略，以同时可视化并区分实验室培养的微生物人工混合物中的15种不同系统型。然后，我们说明了我们的方法对天然微生物群落（即人的牙菌斑，微生物生物膜）进行结构分析的实用性。我们证明，斑块群落中的15个分类单元可以同时成像和分析，并且该群落被早期定居者所主导，包括链球菌，普雷沃氏菌，放线菌和韦永氏菌。邻近分析用于确定细胞间和细胞内的细胞间关联的频率，这揭示了统计学上显着的细胞间配对。 Prevotella和放线菌属的细胞显示出最多的种间关联，表明这些属在建立和维持生物膜复杂性中起着核心作用。结果提供了生物膜组织的初步系统级结构分析。

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