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Linking Raman-Based Phenotypic Profiling and Phylogenetic Diversity to Reveal EBPR Physiological Characteristics

机译:链接基于拉曼的表型分析和系统发育多样性,揭示EBPR生理特征

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Linking Raman-based phenotypic profiling and 16S-rRNA gene-based phylogenetic analysis could provide insights into SRT-dependent variations in EBPR ecology, physiology and P removal performance. This study demonstrated that multivariate analysis (e.g. HCA) of single-cell Raman spectral fingerprints can be a powerful tool for phenotypic characterization and classification of microbial ecosystems such as EBPR. Combined and simultaneous phylogenetic and phenotypic evaluation of EBPR ecosystems revealed that EBPR performance stability could be more associated with PAO phylogenetic and phenotypic diversity, than with the total PAO population abundance. The phenotypic diversity and plasticity of PAO populations, which otherwise could not be obtained with phylogenetic analysis alone, showed complex but potentially crucial association with EBPR process stability. The combination of phenotypic and phylogenetic characterization of microbial community therefore provides more insight into the potential association between EBPR phylogeny, physiological features, and EBPR performance and stability, and sheds light on the links between microbial ecology and ecosystem function/performance prediction.
机译:将基于拉曼的表型分析和基于16S-rRNA基因的系统发育分析联系起来,可以提供有关SPR依赖的EBPR生态学,生理学和除磷性能的变化的见解。这项研究表明,单细胞拉曼光谱指纹图谱的多变量分析(例如HCA)可能是微生物生态系统(如EBPR)的表型表征和分类的强大工具。 EBPR生态系统的组合,同时的系统发育和表型评估表明,EBPR性能的稳定性可能与PAO系统发生和表型多样性的关系更大,而不是与整个PAO种群的丰度相关。 PAO种群的表型多样性和可塑性,否则只能通过系统发育分析无法获得,显示出与EBPR过程稳定性的复杂但潜在的关键关联。因此,微生物群落的表型和系统发育特征的结合提供了对EBPR系统发育,生理特征以及EBPR性能和稳定性之间潜在联系的更多见解,并阐明了微生物生态学与生态系统功能/性能预测之间的联系。

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