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剥离流式细胞术:我们需要多少个探测器来进行细菌鉴定?

Stripping flow cytometry: How many detectors do we need for bacterial identification?

机构信息

KERMIT, Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Ghent, Belgium.

Center for Microbial Technology and Ecology (CMET), Ghent University, Ghent, Belgium.

出版信息

Cytometry A. 2017 Dec;91(12):1184-1191. doi: 10.1002/cyto.a.23284. Epub 2017 Nov 22.

Abstract

Multicolor approaches are challenging for microbial flow cytometry; as flow cytometers are mainly developed for biomedical applications, modern instruments contain more detectors than needed. Some of these additional fluorescence detectors measure biological information due to spectral overlap, yet the extent to which this information is relevant for the identification of bacterial populations is ambiguous. In this paper we characterize the usefulness of these additional detectors. We propose a data-driven detector selection method to select the smallest subset of detectors that will optimally discriminate between bacterial populations. Using a detector elimination strategy, we show that one or more detectors can be removed without loss of resolving power. A number of additional detectors are included in the final subset, which help to improve the identification of bacterial populations. Experimental data were retrieved from two types of modern cytometers with different configurations. The method reveals a clear ordering of detector importances, which depends on the instrument from which the data were retrieved. In addition, we were able to pinpoint unexpected behavior of SYBR Green I in the red spectrum. As the field of microbial flow cytometry is maturing, these results motivate the construction of a different kind of cytometric instruments for microbiologists, for which the number of detectors is reduced, but tailored toward the characteristics of microbial experiments. © 2017 International Society for Advancement of Cytometry.

摘要

多色方法对微生物流动细胞术具有挑战性;由于流动细胞仪主要用于生物医学应用,因此现代仪器包含的检测器比所需的检测器多。这些额外的荧光检测器中的一些由于光谱重叠而测量生物信息,但这些信息对于细菌群体的鉴定有多大的相关性尚不清楚。在本文中,我们描述了这些额外检测器的有用性。我们提出了一种数据驱动的检测器选择方法,以选择最佳区分细菌群体的最小检测器子集。使用检测器消除策略,我们表明可以在不损失分辨率的情况下去除一个或多个检测器。最终子集中包含了许多其他的检测器,这有助于提高细菌群体的识别能力。实验数据从两种具有不同配置的现代细胞仪中检索得到。该方法揭示了检测器重要性的清晰排序,这取决于从哪个仪器中检索数据。此外,我们还能够发现红色光谱中 SYBR Green I 的意外行为。随着微生物流动细胞术领域的成熟,这些结果促使为微生物学家构建一种不同类型的细胞仪,该细胞仪减少了检测器的数量,但针对微生物实验的特点进行了定制。 © 2017 国际细胞分析学会。

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