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Cell Type Specific Responses of the Endoplasmic Reticulum Dynamics to Environmental Stress

bioRxiv · 27 Jan 2024 · 10.1101/2024.01.23.576814

Abstract

To overcome the challenge of balancing imaging speecd and resolution, which currently limits the accurate identification of structural and dynamic changes in the study of endoplasmic reticulum (ER) in plant cells. This research employs structured illumination microscopy techniques to achieve super-resolution real-time imaging of the ER in live Arabidopsis materials. Additionally, a self-supervised denoising framework (Blind2Unblind) was optimized to further enhance the signal-to-noise ratio of rapid microscopic imaging. Based on the images with high quality, a method for quantitative analysis of ER structures using time-lapse images is developed. Moreover, detections of changes in ER structures under environmental stress are conducted to verify the effectiveness of the method. Moreover, correlation analyses of various parameters indicate a significant positive correlation between the area and length of tubular ER with the number of growth tips and tricellular junctions, while the area of ER cisternae and bulk flow exhibits a significant negative correlation with the area and length of tubules. The super-resolution imaging and dynamic analysis method developed in this study will provide new technical approaches for further elucidating the function and regulatory mechanisms of the plant ER.

Plant phenotyping relevance

植物ERの超解像ライブイメージング、自己教師ありノイズ除去、時系列画像からの構造定量法を開発しており、環境ストレスで有効性も検証しているため、植物表現型取得・解析手法が中心である。

abstractThis research employs structured illumination microscopy techniques to achieve super-resolution real-time imaging of the ER in live Arabidopsis materials.
abstracta method for quantitative analysis of ER structures using time-lapse images is developed.
abstractThe super-resolution imaging and dynamic analysis method developed in this study will provide new technical approaches for further elucidating the function and regulatory mechanisms of the plant ER.

Code and data availability

The supplied blocks describe SIM imaging of Arabidopsis ER, a Blind2Unblind denoising framework, and a Swint-ResU-Net segmentation model, but contain no public dataset, image, code, or model deposit with an authors' URL or availability statement. No qualifying paper-specific public asset is present.

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