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一种基于荧光显微镜和图像处理技术的新型检测方法,用于确定杆状细菌的表型分布。

A novel assay based on fluorescence microscopy and image processing for determining phenotypic distributions of rod-shaped bacteria.

作者信息

Spetsieris Konstantinos, Zygourakis Kyriacos, Mantzaris Nikos V

机构信息

Department of Chemical and Biomolecular Engineering, MS-362, Rice University, 6100 Main Street, Houston, Texas 77005, USA.

出版信息

Biotechnol Bioeng. 2009 Feb 1;102(2):598-615. doi: 10.1002/bit.22063.

Abstract

Cell population balance (CPB) models can account for the phenotypic heterogeneity that characterizes isogenic cell populations. To utilize the predictive power of these models, however, we must determine the single-cell reaction and division rates as well as the partition probability density function of the cell population. These functions can be obtained through the Collins-Richmond inverse CPB modeling methodology, if we know the phenotypic distributions of (a) the overall cell population, (b) the dividing cell subpopulation, and (c) the newborn cell subpopulation. This study presents the development of a novel assay that combines fluorescence microscopy and image processing to determine these distributions. The method is generally applicable to rod-shaped cells dividing through the formation of a characteristic constriction. Morphological criteria were developed for the automatic identification of dividing cells and validated through direct comparison with manually obtained measurements. The newborn cell subpopulation was obtained from the corresponding dividing cell subpopulation by collecting information from the two compartments separated by the constriction. The method was applied to E. coli cells carrying the genetic toggle network with a green fluorescent marker. Our measurements for the overall cell population were in excellent agreement with the distributions obtained via flow cytometry. The new assay constitutes a powerful tool that can be used in conjunction with inverse CPB modeling to rigorously quantify single-cell behavior from data collected from highly heterogeneous cell populations.

摘要

细胞群体平衡(CPB)模型能够解释同基因细胞群体所具有的表型异质性。然而,为了利用这些模型的预测能力,我们必须确定单细胞反应和分裂速率以及细胞群体的分配概率密度函数。如果我们知道(a)整个细胞群体、(b)正在分裂的细胞亚群和(c)新生细胞亚群的表型分布,那么这些函数可以通过柯林斯 - 里士满逆CPB建模方法获得。本研究介绍了一种结合荧光显微镜和图像处理来确定这些分布的新型检测方法的开发。该方法通常适用于通过形成特征性缢缩进行分裂的杆状细胞。制定了形态学标准用于自动识别正在分裂的细胞,并通过与手动测量结果直接比较进行了验证。通过收集由缢缩分隔的两个区室的信息,从相应的正在分裂的细胞亚群中获得新生细胞亚群。该方法应用于携带绿色荧光标记的遗传toggle网络的大肠杆菌细胞。我们对整个细胞群体的测量结果与通过流式细胞术获得的分布非常吻合。这种新的检测方法构成了一种强大的工具,可与逆CPB建模结合使用,以根据从高度异质细胞群体收集的数据严格量化单细胞行为。

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