論文 - 詳細
| RRC ID | 86254 |
|---|---|
| 著者 | Ichita M, Yamamichi H, Higaki T. |
| タイトル | Virtual staining from bright-field microscopy for label-free quantitative analysis of plant cell structures. |
| ジャーナル | Plant Mol Biol |
| Abstract |
The applicability of a deep learning model for the virtual staining of plant cell structures using bright-field microscopy was investigated. The training dataset consisted of microscopy images of tobacco BY-2 cells with the plasma membrane stained with the fluorescent dye PlasMem Bright Green and the cell nucleus labeled with Histone-red fluorescent protein. The trained models successfully detected the expansion of cell nuclei upon aphidicolin treatment and a decrease in the cell aspect ratio upon propyzamide treatment, demonstrating its utility in cell morphometry. The model also accurately documented the shape of Arabidopsis pavement cells in both wild type and the bpp125 triple mutant, which has an altered pavement cell phenotype. Metrics such as cell area, circularity, and solidity obtained from virtual staining analyses were highly correlated with those obtained by manual measurements of cell features from microscopy images. Furthermore, the versatility of virtual staining was highlighted by its application to track chloroplast movement in Egeria densa. The method was also effective for classifying live and dead BY-2 cells using texture-based machine learning, suggesting that virtual staining can be applied beyond typical segmentation tasks. Although this method still has some limitations, its non-invasive nature and efficiency make it highly suitable for label-free, dynamic, and high-throughput analyses in quantitative plant cell biology. |
| 巻・号 | 115(1) |
| ページ | 29 |
| 公開日 | 2025-1-31 |
| DOI | 10.1007/s11103-025-01558-w |
| PII | 10.1007/s11103-025-01558-w |
| PMID | 39885095 |
| PMC | PMC11782351 |
| MeSH | Arabidopsis / cytology Cell Nucleus / metabolism Chloroplasts / metabolism Deep Learning Microscopy* / methods Nicotiana / cytology Plant Cells* / metabolism Staining and Labeling* / methods |
| IF | 3.302 |
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オルトメトリクス指標項目
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| 最多言及媒体 | News |
| 各媒体での言及数の合計 | 3 |
| 過去6か月間でのオルトメトリクス指標の変動値 | 0.0 |
| リソース情報 | |
| シロイヌナズナ / 植物培養細胞・遺伝子 | rpc00001 |