A Microimage-Processing-Based Technique for Detecting Qualitative and Quantitative Characteristics of Plant Cells
Jun Feng,
Zhenting Li,
Shizhen Zhang,
Chun Bao,
Jingxian Fang,
Yun Yin,
Bolei Chen,
Lei Pan,
Bing Wang,
Yu Zheng
Affiliations
Jun Feng
State Key Laboratory of Precision Blasting, Jianghan University, Wuhan 430056, China
Zhenting Li
Hubei Province Research Center of Legume Plants, School of Life Science, Institute for Interdisciplinary Research, Jianghan University, Wuhan 430056, China
Shizhen Zhang
State Key Laboratory of Precision Blasting, Jianghan University, Wuhan 430056, China
Chun Bao
State Key Laboratory of Precision Blasting, Jianghan University, Wuhan 430056, China
Jingxian Fang
Hubei Province Research Center of Legume Plants, School of Life Science, Institute for Interdisciplinary Research, Jianghan University, Wuhan 430056, China
Yun Yin
Hubei Province Research Center of Legume Plants, School of Life Science, Institute for Interdisciplinary Research, Jianghan University, Wuhan 430056, China
Bolei Chen
State Key Laboratory of Precision Blasting, Jianghan University, Wuhan 430056, China
Lei Pan
Hubei Province Research Center of Legume Plants, School of Life Science, Institute for Interdisciplinary Research, Jianghan University, Wuhan 430056, China
Bing Wang
State Key Laboratory of Precision Blasting, Jianghan University, Wuhan 430056, China
Yu Zheng
State Key Laboratory of Precision Blasting, Jianghan University, Wuhan 430056, China
When plants encounter external environmental stimuli, they can adapt to environmental changes through a complex network of metabolism–gene expression–metabolism within the plant cell. In this process, changes in the characteristics of plant cells are a phenotype that is responsive and directly linked to this network. Accurate identification of large numbers of plant cells and quantitative analysis of their cellular characteristics is a much-needed experiment for in-depth analysis of plant metabolism and gene expression. This study aimed to develop an automated, accurate, high-throughput quantitative analysis method, ACFVA, for single-plant-cell identification. ACFVA can quantitatively address a variety of biological questions for a large number of plant cells automatically, including standard assays (for example, cell localization, count, and size) and complex morphological assays (for example, different fluorescence in cells). Using ACFVA, phenomics studies can be carried out at the plant cellular level and then combined with ever-changing sequencing technologies to address plant molecular biology and synthetic biology from another direction.
