Microstructure investigation of plant architecture with X-ray microscopy

Ke Chen, Wenting Zhang, Ting La, Philipp Alexander Bastians, Tao Guo, Chunjie Cao

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

In recent years, the plant morphology has been well studied by multiple approaches at cellular and subcellular levels. Two-dimensional (2D) microscopy techniques offer imaging of plant structures on a wide range of magnifications for researchers. However, subcellular imaging is still challenging in plant tissues like roots and seeds. Here we use a three-dimensional (3D) imaging technology based on the X-ray microscope (XRM) and analyze several plant tissues from different plant species. The XRM provides new insights into plant structures using non-destructive imaging at high-resolution and high contrast. We also utilized a workflow aiming to acquire accurate and high-quality images in the context of the whole specimen. Multiple plant samples including rice, tobacco, Arabidopsis and maize were used to display the differences of phenotypes. Our work indicates that the XRM is a powerful tool to investigate plant microstructure in high-resolution scale. Our work also provides evidence that evaluate and quantify tissue specific differences for a range of plant species. We also characterize novel plant tissue phenotypes by the XRM, such as seeds in Arabidopsis, and utilize them for novel observation measurement. Our work represents an evaluated spatial and temporal resolution solution on seed observation and screening.
Original languageEnglish (US)
Pages (from-to)110986
JournalPlant Science
Volume311
DOIs
StatePublished - Jul 1 2021

Bibliographical note

KAUST Repository Item: Exported on 2021-08-06
Acknowledgements: We thank Professor Hong-Xuan Lin (Shanghai Institute of Plant Physiology & Ecology) for sample supports. We thank Professor Xiaoshu Gao (Shanghai Ninth People's Hospital) and Zhenhuan Xue (Carl Zeiss) on expertise and advice. We thank Andrzej Lyskowski, PhD, for data analysis support. This work was supported by the China Postdoctoral Science Foundation (grant 2020T130673). This manuscript has been released as a pre-print at bioRxiv [49].

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