生物技术通报2024，Vol.40Issue(4)：67-76,10.DOI:10.13560/j.cnki.biotech.bull.1985.2023-1152
基于超分辨成像增强对拟南芥内质网动态变化的研究
Dynamic Changes of Arabidopsis Endoplasmic Reticulum Based on Enhanced Super-resolution Images
摘要
Abstract
[Objective]This work is to solve the bottleneck of accurately identifying fine structures,and dynamic changes cannot be concurrently met by imaging speed and imaging resolution in the study of plant cell endoplasmic reticulum.[Method]This study employed 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.[Result]Based on the images with high quality,a method for quantitative analysis of ER structures using time-lapse images was established.Moreover,detections of changes in ER structures under environmental stress were conducted to verify the effectiveness of the method.Moreover,correlation analyses of various parameters indicated a significantly positive correlation between the area,length of tubular ER and the number of growth tips and three-way junctions,while the area of ER cisternae and bulk flow had a significantly negative correlation with the area and length of tubules.[Conclusion]The optimized self-supervised denoising framework in this study improves the signal-to-noise ratio of images with structure illumination microscopy in living plant cells,enabling the quantification of complex structures and dynamics,such as tubular ER,cisternae in ER,bulk flow,growth tips,and nodes,with complex correlations among the structures.关键词
拟南芥/内质网/动态/超分辨率成像/成像增强/量化分析Key words
Arabidopsis thaliana/endoplasmic reticulum/dynamics/super-resolution imaging/image enhancement/quantitative analysis引用本文复制引用
张以恒,刘家正,王雪晨,孙政哲,薛雅郡,汪沛,韩华,郑宏伟,李晓娟..基于超分辨成像增强对拟南芥内质网动态变化的研究[J].生物技术通报,2024,40(4):67-76,10.基金项目
国家自然科学基金项目(91954202,31871349,32171461),第三次新疆综合科考(2022xikk1200),SunTrust Banks 2030-大型项目(2021ZD0204500,2021ZD0204503),北京林业大学科技创新计划项目(2019J003003) （91954202,31871349,32171461）
