Characterizing Cellular Physiological States with Three-Dimensional Shape Descriptors for Cell Membranes

Author:

Guan Guoye1,Chen Yixuan2ORCID,Wang Hongli12,Ouyang Qi123,Tang Chao124ORCID

Affiliation:

1. Center for Quantitative Biology, Peking University, Beijing 100871, China

2. School of Physics, Peking University, Beijing 100871, China

3. School of Physics, Zhejiang University, Hangzhou 310027, China

4. Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China

Abstract

The shape of a cell as defined by its membrane can be closely associated with its physiological state. For example, the irregular shapes of cancerous cells and elongated shapes of neuron cells often reflect specific functions, such as cell motility and cell communication. However, it remains unclear whether and which cell shape descriptors can characterize different cellular physiological states. In this study, 12 geometric shape descriptors for a three-dimensional (3D) object were collected from the previous literature and tested with a public dataset of ~400,000 independent 3D cell regions segmented based on fluorescent labeling of the cell membranes in Caenorhabditis elegans embryos. It is revealed that those shape descriptors can faithfully characterize cellular physiological states, including (1) cell division (cytokinesis), along with an abrupt increase in the elongation ratio; (2) a negative correlation of cell migration speed with cell sphericity; (3) cell lineage specification with symmetrically patterned cell shape changes; and (4) cell fate specification with differential gene expression and differential cell shapes. The descriptors established may be used to identify and predict the diverse physiological states in numerous cells, which could be used for not only studying developmental morphogenesis but also diagnosing human disease (e.g., the rapid detection of abnormal cells).

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Starry Night Science Fund of the Zhejiang University Shanghai Institute for Advanced Study

Publisher

MDPI AG

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