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.
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Claims 8
Claim · model-written summary
Virtual staining detected nucleus expansion after aphidicolin treatment in tobacco BY-2 cells.
- Taxon
- tobacco
Nicotiana tabacume1 - Material
- BY-2e1
- Treatment
- aphidicolin treatmente0
- Outcome
- expansion of cell nucleie0
- Direction
- expansione0
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“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.”
e1“microscopy images of tobacco BY-2 cells”
Claim · model-written summary
Virtual staining detected a decrease in tobacco BY-2 cell aspect ratio after propyzamide treatment.
- Taxon
- tobaccoNicotiana tabacume1
- Material
- BY-2e1
- Treatment
- propyzamide treatmente0
- Outcome
- cell aspect ratioe0
- Direction
- decreasee0
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“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.”
e1“microscopy images of tobacco BY-2 cells”
Claim · model-written summary
The model accurately documented wild-type Arabidopsis pavement cell shape.
- Taxon
- Arabidopsis
Arabidopsise0 - Material
- wild typee0
- Organ / stage
- pavement cellse0
- Outcome
- shapee0
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“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.”
Claim · model-written summary
The model accurately documented pavement cell shape in the Arabidopsis bpp125 triple mutant with an altered phenotype.
- Taxon
- ArabidopsisArabidopsise0
- Material
- bpp125 triple mutante0
- Organ / stage
- pavement cellse0
- Outcome
- shapee0
- Qualifier
- altered pavement cell phenotypee0
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“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.”
Claim · model-written summary
Virtual-staining cell area, circularity and solidity were highly correlated with manual measurements.
Not reportedTaxonDirection
Verbatim
e0“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.”
Claim · model-written summary
Virtual staining tracked chloroplast movement in Egeria densa.
- Taxon
- Egeria densa
Egeria densae0 - Outcome
- chloroplast movemente0
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Furthermore, the versatility of virtual staining was highlighted by its application to track chloroplast movement in Egeria densa.”
Claim · model-written summary
Virtual staining effectively classified live and dead BY-2 cells with texture-based machine learning.
- Taxon
- tobaccoNicotiana tabacume1
- Material
- BY-2e0
- Outcome
- classifying live and dead BY-2 cellse0
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“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.”
e1“microscopy images of tobacco BY-2 cells”
Claim · model-written summary
The authors consider virtual staining highly suitable for label-free, dynamic and high-throughput quantitative plant cell analysis despite limitations.
- Outcome
- label-free, dynamic, and high-throughput analyses in quantitative plant cell biologye0
- Qualifier
- some limitationse0
Not reportedTaxon
Verbatim
e0“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.”