Automatic extraction of actin networks in plants.
Automatic extraction of actin networks in plants.
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DOI：
10.1371/journal.pcbi.1011407
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发表时间：
2023-08
影响因子：
4.3
通讯作者：
中科院分区：
文献类型：
--
作者：
肌动蛋白细胞骨架在真核生物中是必不可少的，尤其是在植物界，它在细胞扩张、细胞分裂、环境反应和病原体防御中发挥着关键作用。然而，植物肌动蛋白网络特性的精确结构-功能关系仍有待解开，包括网络结构如何依赖于细胞类型、组织类型和发育阶段的细节。部分问题在于从显微镜数据中提取肌动蛋白网络特征的高质量、定量测量的难度。为了解决这个问题，我们开发了Dragon，这是一种新型的图像分析算法，可以自动提取一系列细胞类型的肌动蛋白网络，提供17种不同的定量指标来描述局部水平的网络。然后利用这个算法，我们研究了拟南芥中的一些案例，包括几个不同的组织，各种受肌动蛋白影响的突变体，以及对白粉病有反应的细胞。在许多情况下，我们发现肌动蛋白网络属性在统计学上有显着差异。除了这些结果，我们的算法被设计成可以很容易地适应其他组织、突变体和植物，因此将是全球重要作物中肌动蛋白细胞骨架的研究和未来生物工程的宝贵财富。大多数生物细胞包含一个由蛋白质细丝组成的内部网络，称为细胞骨架。这有助于为电池提供形状和结构，并用于在电池内运输货物。一个例子是肌动蛋白，它是细胞骨架中最薄的部分，既以单独的细丝形式存在，也以较厚的束状存在。肌动蛋白形成复杂的分支网络，根据需要不断变化。研究肌动蛋白网络是困难的，因为它很难准确地找到网络的形状，并跟踪它是如何随着时间的推移而变化的。在这里，通过关注植物，我们开发了一种名为Dragon的新型计算算法，它可以自动提取肌动蛋白网络的形状，给出17个描述该网络的精确数字测量结果。然后，我们使用我们的算法来检测模式植物拟南芥中的肌动蛋白，发现在组织类型、关键肌动蛋白突变体和细胞受到白粉病攻击时肌动蛋白网络存在显著差异。这项工作对全球粮食安全具有重要的潜在应用，很可能很容易适应植物以外的生物。
The actin cytoskeleton is essential in eukaryotes, not least in the plant kingdom where it plays key roles in cell expansion, cell division, environmental responses and pathogen defence. Yet, the precise structure-function relationships of properties of the actin network in plants are still to be unravelled, including details of how the network configuration depends upon cell type, tissue type and developmental stage. Part of the problem lies in the difficulty of extracting high-quality, quantitative measures of actin network features from microscopy data. To address this problem, we have developed DRAGoN, a novel image analysis algorithm that can automatically extract the actin network across a range of cell types, providing seventeen different quantitative measures that describe the network at a local level. Using this algorithm, we then studied a number of cases in Arabidopsis thaliana, including several different tissues, a variety of actin-affected mutants, and cells responding to powdery mildew. In many cases we found statistically-significant differences in actin network properties. In addition to these results, our algorithm is designed to be easily adaptable to other tissues, mutants and plants, and so will be a valuable asset for the study and future biological engineering of the actin cytoskeleton in globally-important crops. Most biological cells contain an internal network of protein filaments called the cytoskeleton. This helps provide shape and structure to the cell, and is used for transporting cargo within the cell. One example is actin, the thinnest part of the cytoskeleton, which is present as both individual filaments and thicker bundles. Actin forms complex branched networks that continually change as required. Studying the actin network is difficult since it has hard to accurately find the shape of the network and follow how this changes over time. Here, by focusing on plants, we develop a novel computational algorithm called DRAGoN that can automatically extract the shape of the actin network, giving seventeen precise numerical measurements that describe the network. We then use our algorithm to examine actin in the model plant Arabidopsis thaliana, finding significant differences in the actin network between tissue types, key actin mutants and when the cells are attacked by powdery mildew. This work has important potential applications to global food security and is likely to be easily adaptable to organisms other than plants.
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影响因子：
5.6
作者：
Narita, Akihiro;Mueller, Jan;Urban, Edit;Vinzenz, Marlene;Small, J. Victor;Maeda, Yuichiro
通讯作者：
Maeda, Yuichiro
影响因子：
6.7
作者：
Kang Y;Jelenska J;Cecchini NM;Li Y;Lee MW;Kovar DR;Greenberg JT
通讯作者：
Greenberg JT
影响因子：
64.8
作者：
通讯作者：
--
影响因子：
2
作者：
Geitmann, A;Emons, AMC
通讯作者：
Emons, AMC
影响因子：
10.9
作者：
Hadjidemetriou, Stathis;Toomre, Derek;Duncan, James
通讯作者：
Duncan, James