2017
DOI: 10.1093/jxb/erx032
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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

Abstract: A data analysis pipeline that integrates diverse data sources, detects tip growth in kymographs, and analyses oscillations and synchronization reveales oscillatory signatures underlying distinct growth regimes in Arabidopsis pollen tubes.

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Cited by 54 publications
(48 citation statements)
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“…Nonetheless, the idea of criticality that occurs in a growing plant cell appears to be in line with the detailed explanations that can be found in the literature, which combine growth rate oscillations with synchronised ion fluxes (see Fig. 2D in Damineli et al 2017), where the extracellular H + flux and growth rate curve almost overlap. Summarising, self-organised criticality is a mechanism through which open systems achieve a self-organised statistically stationary state in which they undergo a non-equilibrium phase transition.…”
Section: Introductionsupporting
confidence: 83%
“…Nonetheless, the idea of criticality that occurs in a growing plant cell appears to be in line with the detailed explanations that can be found in the literature, which combine growth rate oscillations with synchronised ion fluxes (see Fig. 2D in Damineli et al 2017), where the extracellular H + flux and growth rate curve almost overlap. Summarising, self-organised criticality is a mechanism through which open systems achieve a self-organised statistically stationary state in which they undergo a non-equilibrium phase transition.…”
Section: Introductionsupporting
confidence: 83%
“…However, the convolution of acidic pH growth and temperature growth is less shifted away from zero (lag) and is even more pronounced; see also recent outcomes in Pietruszka and Haduch-Sendecka (2016) as well as Olszewska et al (2017Olszewska et al ( , 2018 for cell wall pH (proton efflux rate) and growth rate, which are directly co-regulated in growing shoot tissue, thus strongly supporting the empirical foundations of EWS. Even more supportive for the EWS-model is the result obtained by Damineli et al (2017), where the extracellular H + flux and growth rate curves practically overlap (see Fig. 2d therein); the periods (47.7 ± 3.2 s and 48.7 ± 4.3 s, respectively) for both processes are almost identical within experimental error.…”
Section: Sensing Structural Transitionssupporting
confidence: 66%
“…structurally and temporally organised apical growth, especially since H + usually oscillates with the period similar to growth rate-see Fig. 2d in Damineli et al (2017).…”
Section: Pollen Tube Growth and Oscillationsmentioning
confidence: 97%
“…Controlled activation of MS channels from inside a plant cell might be possible through the application of focused ultrasound, as was recently demonstrated for animal TPKs expressed in oocytes [54]. Integration of localized extracellular ion flux measurements with genetically encoded ion or voltage biosensors may allow the study of MS channel function in some cellular contexts, such as pollen tubes [55]. To date, the genetically encoded sensors for transmembrane voltage used extensively in animal systems to monitor ion channel activity in vivo [56] do not yet function well in plants [57].…”
Section: Beyond the Horizon: Innovations In Ms Channel Studiesmentioning
confidence: 99%