Unverified paper record
Distinct localization patterns of actin microfilaments during early cell plate formation in plants through deep learning-based image restoration
bioRxiv · 30 Jan 2025 · 10.1101/2025.01.28.635247
Abstract
Phragmoplasts are plant-specific intracellular structures composed of microtubules, actin microfilaments (AFs), membranes, and associated proteins. Importantly, they are involved in the formation and expansion of cell plates that partition daughter cells during cell division. While previous studies have revealed the important role of cytoskeletal dynamics in the proper functioning of the phragmoplast, the localization and role of AFs in the initial phase of cell plate formation remain controversial. Here, we used deep learning-based image restoration to achieve high-resolution 4D imaging with minimal laser-induced damage, enabling us to investigate the dynamics of AFs during the initial phase of cell plate formation in transgenic tobacco BY-2 cells labeled with Lifeact-RFP or RFP-ABD2 (actin binding domain 2). This computational approach overcame the limitation of conventional imaging, namely laser-induced photobleaching and phototoxicity. The restored images indicated that RFP-ABD2 labeled AFs were predominantly localized near the daughter nucleus, whereas Lifeact-RFP labeled AFs were found not only near the daughter nucleus but also around the initial cell plate. These findings, validated by imaging with a long exposure time, highlight distinct localization patterns between the two AF probes and suggest that Lifeact-RFP labeled AFs play a role in initiating cell plate formation.
Plant phenotyping relevance
深層学習による画像復元を開発・検証し、植物細胞内のアクチン局在と動態を高解像度4D画像から取得しているため、植物表現型取得法が中心である。
abstractwe used deep learning-based image restoration to achieve high-resolution 4D imaging with minimal laser-induced damage
abstractThis computational approach overcame the limitation of conventional imaging, namely laser-induced photobleaching and phototoxicity.
abstractThese findings, validated by imaging with a long exposure time
Code and data availability
The paper's phenotyping image data and trained image-restoration models are not publicly deposited; the Data Availability Statement states all relevant data are available only from the authors on request. No public repository, code URL, or model checkpoint is provided.
No evidence-backed public reproduction asset is currently recorded.
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