An Approach to Quantify Endomembrane Dynamics in Pollen Utilizing Bioactive Chemicals  

作　　者：Nolan Ung Michelle Q. Brown Glenn R. Hicks Natasha V. Raikhel 

机构地区：[1]Center for Plant Cell Biology and Department of Botany and Plant Sciences, University of California, Riverside, Riverside, CA 92521, USA

出　　处：《Molecular Plant》2013年第4期1202-1213,共12页分子植物（英文版）

基　　金：the National Science Foundation's Integrative Graduate Education and Research Traineeship (DGE0903667) to N.U，(DGE-0504249) to M.Q.B，the National Science Foundation Grant (MCB-0817916)to N.V.R.and G.R.H

摘　　要：Tip growth of pollen tubes and root hairs occurs via rapid polar growth. These rapidly elongating cells require tip-focused endomembrane trafficking for the deposition and recycling of proteins, membranes, and cell wall materials. Most of the image-based data published to date are subjective and non-quantified. Quantitative and com- parative descriptors of these highly dynamic processes have been a major challenge, but are highly desirable for genetic and chemical genomics approaches to dissect this biological network. To address this problem, we screened for small molecules that perturbed the localization of a marker for the Golgi Ras-like monomeric G-protein RAB2：GFP expressed in transgenic tobacco pollen. Semi-automated high-throughput imaging and image analysis resulted in the identifica- tion of novel compounds that altered pollen tube development and endomembrane trafficking. Six compounds that caused mislocalization and varying degrees of altered movement of RAB2：GFP-labeled endomembrane bodies were used to generate a training set of image data from which to quantify vesicle dynamics. The area, velocity, straightness, and intensity of each body were quantified using semi-automated image analysis tools revealing quantitative differences in the phenotype caused by each compound. A score was then given to each compound enabling quantitative comparisons between compounds. Our results demonstrate that image analysis can be used to quantitatively evaluate dynamic sub- cellular endomembrane phenotypes induced by bioactive chemicals, mutations, or other perturbing agents as part of a strategy to quantitatively dissect the endomembrane network.Tip growth of pollen tubes and root hairs occurs via rapid polar growth. These rapidly elongating cells require tip-focused endomembrane trafficking for the deposition and recycling of proteins, membranes, and cell wall materials. Most of the image-based data published to date are subjective and non-quantified. Quantitative and com- parative descriptors of these highly dynamic processes have been a major challenge, but are highly desirable for genetic and chemical genomics approaches to dissect this biological network. To address this problem, we screened for small molecules that perturbed the localization of a marker for the Golgi Ras-like monomeric G-protein RAB2：GFP expressed in transgenic tobacco pollen. Semi-automated high-throughput imaging and image analysis resulted in the identifica- tion of novel compounds that altered pollen tube development and endomembrane trafficking. Six compounds that caused mislocalization and varying degrees of altered movement of RAB2：GFP-labeled endomembrane bodies were used to generate a training set of image data from which to quantify vesicle dynamics. The area, velocity, straightness, and intensity of each body were quantified using semi-automated image analysis tools revealing quantitative differences in the phenotype caused by each compound. A score was then given to each compound enabling quantitative comparisons between compounds. Our results demonstrate that image analysis can be used to quantitatively evaluate dynamic sub- cellular endomembrane phenotypes induced by bioactive chemicals, mutations, or other perturbing agents as part of a strategy to quantitatively dissect the endomembrane network.

关 键 词：ENDOMEMBRANES vesicle trafficking quantification POLLEN chemical biology. 

分 类 号：TP311.131[自动化与计算机技术—计算机软件与理论] S482.39[自动化与计算机技术—计算机科学与技术]