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首页> 外文期刊>British Poultry Science >Oscillatory signatures underlie growth regimes in Arabidopsis pollen tubes: computational methods to estimate tip location, periodicity, and synchronization in growing cells
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Oscillatory signatures underlie growth regimes in Arabidopsis pollen tubes: computational methods to estimate tip location, periodicity, and synchronization in growing cells

机译：拟南芥花粉管中的振荡签名是增长制度：估计尖端位置，周期性和在生长细胞中的同步的计算方法

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摘要

Oscillations in pollen tubes have been reported for many cellular processes, including growth, extracellular ion fluxes, and cytosolic ion concentrations. However, there is a shortage of quantitative methods to measure and characterize the different dynamic regimes observed. Herein, a suite of open-source computational methods and original algorithms were integrated into an automated analysis pipeline that we employed to characterize specific oscillatory signatures in pollen tubes of Arabidopsis thaliana (Col-0). Importantly, it enabled us to detect and quantify a Ca2+ spiking behaviour upon growth arrest and synchronized oscillations involving growth, extracellular H+ fluxes, and cytosolic Ca2+, providing the basis for novel hypotheses. Our computational approach includes a new tip detection method with subpixel resolution using linear regression, showing improved ability to detect oscillations when compared to currently available methods. We named this data analysis pipeline 'Computational Heuristics for Understanding Kymographs and aNalysis of Oscillations Relying on Regression and Improved Statistics', or CHUKNORRIS. It can integrate diverse data types (imaging, electrophysiology), extract quantitative and time-explicit estimates of oscillatory characteristics from isolated time series (period and amplitude) or pairs (phase relationships and delays), and evaluate their synchronization state. Here, its performance is tested with ratiometric and single channel kymographs, ion flux data, and growth rate analysis.
机译：已经报道了花粉管中的振动，包括许多细胞方法，包括生长，细胞外离子丝量和细胞溶质离子浓度。然而，有缺乏定量方法来测量和表征观察到的不同动态制度。这里，一套开源计算方法和原始算法被整合到一种自动分析管道中，我们用于在拟南芥（COL-0）的花粉管中表征特定振荡签名。重要的是，它使我们能够在生长停滞和同步振荡时检测和量化涉及生长，细胞外H +助熔剂和细胞溶质CA2 +的CA2 +尖峰行为，为新颖假设提供基础。我们的计算方法包括使用线性回归的具有子像素分辨率的新尖端检测方法，显示与当前可用方法相比时检测振荡的能力。我们将此数据分析的数据分析依托回归和改进统计数据的宣传和分析依赖于回归和改进统计数据的计算启发式。它可以集成各种数据类型（成像，电生理学），从隔离时间序列（周期和幅度）或对（相位关系和延迟）的振荡特性的分量和时间显式估计，并评估其同步状态。在此，其性能具有比率和单通道脑脑管镜，离子通量数据和生长速率分析。

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