DeepD&Cchl: an AI tool for automated 3D single-cell chloroplast detection, counting, and cell type clustering

DeepD&Cchl: an AI tool for automated 3D single-cell chloroplast detection, counting, and cell type clustering

Chloroplast density in cells varies among different types of cells and plants. In current single-cell spatiotemporal analysis, the automatic detection and quantification of chloroplasts at the single-cell level is crucial. We developed DeepD&Cchl (Deep-learning-based Detecting-and-Counting-c...

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Bibliographic Details
Main Authors: Qun Su, Le Liu, Zhengsheng Hu, Tao Wang, Huaying Wang, Qiuqi Guo, Xinyi Liao, Yan Sha, Feng Li, Zhao Dong, Shaokai Yang, Ningjing Liu, Qiong Zhao
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-05-01
Series:Frontiers in Plant Science
Subjects:
chloroplasts
DeepD&Cchl
deep learning
automatic detection and counting
single cell
cell type clustering
Online Access:https://www.frontiersin.org/articles/10.3389/fpls.2025.1513953/full
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Summary:Chloroplast density in cells varies among different types of cells and plants. In current single-cell spatiotemporal analysis, the automatic detection and quantification of chloroplasts at the single-cell level is crucial. We developed DeepD&Cchl (Deep-learning-based Detecting-and-Counting-chloroplasts), an AI tool for single-cell chloroplast detection and cell-type clustering. It utilizes You-Only-Look-Once (YOLO), a real-time detection algorithm, for accurate and efficient performance. DeepD&Cchl has been proved to identify chloroplasts in plant cells across various imaging types, including light microscopy, electron microscopy, and fluorescence microscopy. Integrated with an Intersection Over Union (IOU) module, DeepD&Cchl precisely counts chloroplasts in single- or multi-layered images, while eliminating double-counting errors. Furthermore, when combined with Cellpose, a single-cell segmentation tool, DeepD&Cchl enhances its effectiveness at the single-cell level. By counting chloroplasts within individual cells, it supports cell-type-specific clustering based on chloroplast number versus cell size, offering valuable morphological insights for single-cell studies. In summary, DeepD&Cchl is a significant advancement in plant cell analysis. It offers accuracy and efficiency in chloroplast identification, counting and cell-type classification, providing a useful tool for plant research.
ISSN:1664-462X

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