Large-volume fully automated cell reconstruction generates a cell atlas of plant tissues

The geometric shape and arrangement of individual cells play a role in shaping organ functions. However, analyzing multicellular features and exploring their connectomes in centimeter-scale plant organs remain challenging. Here, we established a set of frameworks named Large-Volume Fully Automated Cell Reconstruction (LVACR), enabling the exploration of three-dimensional (3D) cytological features and cellular connectivity in plant tissues. Through benchmark testing, our framework demonstrated superior efficiency in cell segmentation and aggregation, successfully addressing the inherent challenges posed by light sheet fluorescence microscopy (LSFM) imaging. Using LVACR, we successfully established a cell atlas of different plant tissues. Cellular morphology analysis revealed differences of cell clusters and shapes in between different poplar (P. simonii Carr. and P. canadensis Moench.) seeds, whereas topological analysis revealed that they maintained conserved cellular connectivity. Furthermore, LVACR spatiotemporally demonstrated an initial burst of cell proliferation, accompanied by morphological transformations at an early stage in developing the shoot apical meristem. During subsequent development, cell differentiation produced anisotropic features, thereby resulting in various cell shapes. Overall, our findings provided valuable insights into the precise spatial arrangement and cellular behavior of multicellular organisms, thus enhancing our understanding of the complex processes underlying plant growth and differentiation.

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Institutions

Publication Details

Journal
The Plant Cell
Published
2024-09-16
DOI
https://doi.org/10.1093/plcell/koae250
Citations
8
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
5.30

Funders

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article

Large-volume fully automated cell reconstruction generates a cell atlas of plant tissues

Linlin Li, Jinxing Lin, Jiahui Bian, Zhouxin Li et al.
8 citations
The Plant Cell
Cell Image Analysis Techniques
5.30
article

Large-volume fully automated cell reconstruction generates a cell atlas of plant tissues

Linlin Li, Jinxing Lin, Jiahui Bian, Zhouxin Li, Lingyu Ma, Yaning Cui, Weiwei Shen, Shiya Shen, Shunyao Yang, Xi Zhang, Hua Han, Zijian Hu, Guangchao Wang, Jiazheng Liu, Weiqian Wu, Jiale Yuan, Lijun Shen, Xiuping Xu
article en
8 citations

Abstract

The geometric shape and arrangement of individual cells play a role in shaping organ functions. However, analyzing multicellular features and exploring their connectomes in centimeter-scale plant organs remain challenging. Here, we established a set of frameworks named Large-Volume Fully Automated Cell Reconstruction (LVACR), enabling the exploration of three-dimensional (3D) cytological features and cellular connectivity in plant tissues. Through benchmark testing, our framework demonstrated superior efficiency in cell segmentation and aggregation, successfully addressing the inherent challenges posed by light sheet fluorescence microscopy (LSFM) imaging. Using LVACR, we successfully established a cell atlas of different plant tissues. Cellular morphology analysis revealed differences of cell clusters and shapes in between different poplar (P. simonii Carr. and P. canadensis Moench.) seeds, whereas topological analysis revealed that they maintained conserved cellular connectivity. Furthermore, LVACR spatiotemporally demonstrated an initial burst of cell proliferation, accompanied by morphological transformations at an early stage in developing the shoot apical meristem. During subsequent development, cell differentiation produced anisotropic features, thereby resulting in various cell shapes. Overall, our findings provided valuable insights into the precise spatial arrangement and cellular behavior of multicellular organisms, thus enhancing our understanding of the complex processes underlying plant growth and differentiation.

The Plant CellVol. 36(12)
Chinese Academy of Sciences (CN), Beijing Forestry University (CN), Shandong Institute of Automation (CN), Chinese Academy of Forestry (CN), Research Institute of Wood Industry (CN), University of Chinese Academy of Sciences (CN), State Key Laboratory of Tree Genetics and Breeding
National Natural Science Foundation of China, Chinese Academy of Sciences, Beijing Forestry University, Beijing Municipal Natural Science Foundation, Beijing Nova Program, Project 211
Life in Land
Openalex Percentile: Top 5%
Cell Image Analysis Techniques
5.30
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