Department of Bioenergy, UFZ, Helmholtz Centre for Environmental Research, Leipzig, Germany.
Cytometry A. 2013 Jun;83(6):561-7. doi: 10.1002/cyto.a.22286. Epub 2013 Apr 8.
Altering environmental conditions change structures of microbial communities. These effects have an impact on the single-cell level and can be sensitively detected using community flow cytometry. However, although highly accurate, microbial monitoring campaigns are still rarely performed applying this technique. One reason is the limited access to pattern analysis approaches for the evaluation of microbial cytometric data. In this article, a new analyzing tool, Cytometric Histogram Image Comparison (CHIC), is presented, which realizes trend interpretation of variations in microbial community structures (i) without any previous definition of gates, by working (ii) person independent, and (iii) with low computational demand. Various factors influencing a sensitive determination of changes in community structures were tested. The sensitivity of this technique was found to discriminate down to 0.5% internal variation. The final protocol was exemplarily applied to a complex microbial community dataset, and correlations to experimental variation were successfully shown.
改变环境条件会改变微生物群落的结构。这些影响在单细胞水平上有体现，可以使用群落流式细胞术灵敏地检测到。然而，尽管该技术非常精确，但是微生物监测活动仍然很少采用这种技术。原因之一是评估微生物细胞计数据的模式分析方法有限。本文提出了一种新的分析工具，即细胞计量直方图图像比较（CHIC），它可以实现（i）无需事先定义门，（ii）独立于个体，（iii）计算需求低的微生物群落结构变化的趋势解释。测试了影响群落结构灵敏测定的各种因素。该技术的灵敏度被发现可以区分低至 0.5%的内部变化。最终方案被示例应用于复杂的微生物群落数据集，并成功显示了与实验变异的相关性。
