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基于 CMEIAS 的微生物相互作用的空间生态学显微镜观察,涉及生物膜内细胞间通讯。

CMEIAS-aided microscopy of the spatial ecology of individual bacterial interactions involving cell-to-cell communication within biofilms.

机构信息

Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI 48824, USA.

出版信息

Sensors (Basel). 2012;12(6):7047-62. doi: 10.3390/s120607047. Epub 2012 May 29.

Abstract

This paper describes how the quantitative analytical tools of CMEIAS image analysis software can be used to investigate in situ microbial interactions involving cell-to-cell communication within biofilms. Various spatial pattern analyses applied to the data extracted from the 2-dimensional coordinate positioning of individual bacterial cells at single-cell resolution indicate that microbial colonization within natural biofilms is not a spatially random process, but rather involves strong positive interactions between communicating cells that influence their neighbors' aggregated colonization behavior. Geostatistical analysis of the data provide statistically defendable estimates of the micrometer scale and interpolation maps of the spatial heterogeneity and local intensity at which these microbial interactions autocorrelate with their spatial patterns of distribution. Including in situ image analysis in cell communication studies fills an important gap in understanding the spatially dependent microbial ecophysiology that governs the intensity of biofilm colonization and its unique architecture.

摘要

本文描述了 CMEIAS 图像分析软件的定量分析工具如何用于研究涉及生物膜内细胞间通讯的原位微生物相互作用。应用于从单个细菌细胞的二维坐标定位提取的数据的各种空间模式分析表明,天然生物膜内的微生物定植不是一个空间随机过程,而是涉及到相互交流的细胞之间的强烈正相互作用,从而影响它们邻居的聚集定植行为。对数据的地质统计学分析提供了统计上可辩护的估计值,表明这些微生物相互作用及其分布的空间模式在微米尺度上的空间异质性和局部强度上具有自相关性。将原位图像分析纳入细胞通讯研究中,填补了理解控制生物膜定植强度及其独特结构的空间相关微生物生理的重要空白。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de47/3435965/4e743ac3958e/sensors-12-07047f1.jpg

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