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CMEIAS JFrad:一种用于区分景观建筑分形几何和微生物生物膜中单个细胞空间模式的数字计算工具。

CMEIAS JFrad: a digital computing tool to discriminate the fractal geometry of landscape architectures and spatial patterns of individual cells in microbial biofilms.

作者信息

Ji Zhou, Card Kyle J, Dazzo Frank B

机构信息

Department of Systems Biology, Columbia University, New York, NY, 10032, USA.

出版信息

Microb Ecol. 2015 Apr;69(3):710-20. doi: 10.1007/s00248-014-0495-1. Epub 2014 Sep 26.

Abstract

Image analysis of fractal geometry can be used to gain deeper insights into complex ecophysiological patterns and processes occurring within natural microbial biofilm landscapes, including the scale-dependent heterogeneities of their spatial architecture, biomass, and cell-cell interactions, all driven by the colonization behavior of optimal spatial positioning of organisms to maximize their efficiency in utilization of allocated nutrient resources. Here, we introduce CMEIAS JFrad, a new computing technology that analyzes the fractal geometry of complex biofilm architectures in digital landscape images. The software uniquely features a data-mining opportunity based on a comprehensive collection of 11 different mathematical methods to compute fractal dimension that are implemented into a wizard design to maximize ease-of-use for semi-automatic analysis of single images or fully automatic analysis of multiple images in a batch process. As examples of application, quantitative analyses of fractal dimension were used to optimize the important variable settings of brightness threshold and minimum object size in order to discriminate the complex architecture of freshwater microbial biofilms at multiple spatial scales, and also to differentiate the spatial patterns of individual bacterial cells that influence their cooperative interactions, resource use, and apportionment in situ. Version 1.0 of JFrad is implemented into a software package containing the program files, user manual, and tutorial images that will be freely available at http://cme.msu.edu/cmeias/. This improvement in computational image informatics will strengthen microscopy-based approaches to analyze the dynamic landscape ecology of microbial biofilm populations and communities in situ at spatial resolutions that range from single cells to microcolonies.

摘要

分形几何的图像分析可用于更深入地了解自然微生物生物膜景观中发生的复杂生态生理模式和过程,包括其空间结构、生物量和细胞间相互作用的尺度依赖性异质性,所有这些均由生物体的最佳空间定位定殖行为驱动,以最大限度地提高其分配养分资源的利用效率。在此,我们介绍CMEIAS JFrad,一种分析数字景观图像中复杂生物膜结构分形几何的新计算技术。该软件具有独特的数据挖掘机会,基于11种不同数学方法的全面集合来计算分形维数,这些方法被集成到一个向导设计中,以最大限度地方便半自动分析单张图像或批量全自动分析多张图像。作为应用示例,分形维数的定量分析用于优化亮度阈值和最小对象大小等重要变量设置,以便在多个空间尺度上区分淡水微生物生物膜的复杂结构,还用于区分影响其原位合作相互作用、资源利用和分配的单个细菌细胞的空间模式。JFrad 1.0版本被集成到一个软件包中,该软件包包含程序文件、用户手册和教程图像,可在http://cme.msu.edu/cmeias/上免费获取。这种计算图像信息学的改进将加强基于显微镜的方法,以在从单细胞到微菌落的空间分辨率下原位分析微生物生物膜种群和群落的动态景观生态学。

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