Iterative subtraction facilitates automated, quantitative analysis of multiple pollen tube growth features
Iterative subtraction facilitates automated, quantitative analysis of multiple pollen tube growth features
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DOI：
10.1007/s00497-018-00351-8
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发表时间：
2018-12
影响因子：
3.4
通讯作者：
Nathaniel Ponvert;Jacob Goldberg;Alexander R Leydon;Mark Johnson
中科院分区：
文献类型：
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作者：
Nathaniel Ponvert;Jacob Goldberg;Alexander R Leydon;Mark Johnson
在开花植物中，成功的繁殖和种子的产生取决于通过花粉管将不动的精子输送到雌性配子中。由于开花植物的繁殖是我们农业产业的基石，因此有必要揭示影响花粉管生长动力学的基因，小分子和环境条件。然而，测量花粉管表型的方法是劳动密集型的，并且在工作量和分辨率之间存在权衡。为了解决这些问题，我们使用了一种称为自动堆栈迭代减法（ASIST）的图像分析技术。我们的工具将生长的花粉管尖端转化为封闭的颗粒，通过现有的颗粒识别技术，可以从数百个单个细胞中自动同时提取多种花粉管表型。在这里，我们使用我们的工具来分析花粉管在离体和半体内的生长动力学。我们表明，ASIST为细胞群体中花粉管生长行为的稳健、高通量分析提供了一个框架，从而促进了花粉管表型组学。
In flowering plants, successful reproduction and generation of seed depends on the delivery of immotile sperm to female gametes via the pollen tube. As reproduction in flowering plants is the cornerstone of our agricultural industry, there is a need to uncover the genes, small molecules, and environmental conditions that affect pollen tube growth dynamics. However, methods for measuring pollen tube phenotypes are labor intensive, and suffer from a tradeoff between workload and resolution. To approach these problems, we use an image analysis technique called Automated Stack Iterative Subtraction (ASIST). Our tool converts growing pollen tube tips into closed particles, making the automated simultaneous extraction of multiple pollen tube phenotypes from hundreds of individual cells tractable via existing particle identification technology. Here we use our tool to analyze growth dynamics of pollen tubes in vitro, and semi in vivo. We show that ASIST provides a framework for robust, high throughput analysis of pollen tube growth behaviors in populations of cells, thus facilitating pollen tube phenomics.