Label-free prediction of cell painting from brightfield images.
Springer Science and Business Media LLC
MetadataShow full item record
Cross-Zamirski, J., Mouchet, E., Williams, G., Schönlieb, C., Turkki, R., & Wang, Y. (2022). Label-free prediction of cell painting from brightfield images.. Sci Rep, 12 (1) https://doi.org/10.1038/s41598-022-12914-x
Funder: BBSRC DTP
Funder: AstraZeneca; doi: http://dx.doi.org/10.13039/100004325
Funder: AstraZeneca, Sweden
Cell Painting is a high-content image-based assay applied in drug discovery to predict bioactivity, assess toxicity and understand mechanisms of action of chemical and genetic perturbations. We investigate label-free Cell Painting by predicting the five fluorescent Cell Painting channels from brightfield input. We train and validate two deep learning models with a dataset representing 17 batches, and we evaluate on batches treated with compounds from a phenotypic set. The mean Pearson correlation coefficient of the predicted images across all channels is 0.84. Without incorporating features into the model training, we achieved a mean correlation of 0.45 with ground truth features extracted using a segmentation-based feature extraction pipeline. Additionally, we identified 30 features which correlated greater than 0.8 to the ground truth. Toxicity analysis on the label-free Cell Painting resulted a sensitivity of 62.5% and specificity of 99.3% on images from unseen batches. We provide a breakdown of the feature profiles by channel and feature type to understand the potential and limitations of label-free morphological profiling. We demonstrate that label-free Cell Painting has the potential to be used for downstream analyses and could allow for repurposing imaging channels for other non-generic fluorescent stains of more targeted biological interest.
Article, /631/114, /631/114/2397, /631/114/1564, /631/114/1305, /631/154, /631/154/53, /631/154/555, article
Engineering and Physical Sciences Research Council (EP/N014588/1)
European Commission Horizon 2020 (H2020) Marie Sk?odowska-Curie actions (777826)
External DOI: https://doi.org/10.1038/s41598-022-12914-x
This record's URL: https://www.repository.cam.ac.uk/handle/1810/338124