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PIFiA: self-supervised approach for protein functional annotation from single-cell imaging data
- Source :
- Molecular Systems Biology, Vol 20, Iss 5, Pp 521-548 (2024)
- Publication Year :
- 2024
- Publisher :
- Springer Nature, 2024.
-
Abstract
- Abstract Fluorescence microscopy data describe protein localization patterns at single-cell resolution and have the potential to reveal whole-proteome functional information with remarkable precision. Yet, extracting biologically meaningful representations from cell micrographs remains a major challenge. Existing approaches often fail to learn robust and noise-invariant features or rely on supervised labels for accurate annotations. We developed PIFiA (Protein Image-based Functional Annotation), a self-supervised approach for protein functional annotation from single-cell imaging data. We imaged the global yeast ORF-GFP collection and applied PIFiA to generate protein feature profiles from single-cell images of fluorescently tagged proteins. We show that PIFiA outperforms existing approaches for molecular representation learning and describe a range of downstream analysis tasks to explore the information content of the feature profiles. Specifically, we cluster extracted features into a hierarchy of functional organization, study cell population heterogeneity, and develop techniques to distinguish multi-localizing proteins and identify functional modules. Finally, we confirm new PIFiA predictions using a colocalization assay, suggesting previously unappreciated biological roles for several proteins. Paired with a fully interactive website ( https://thecellvision.org/pifia/ ), PIFiA is a resource for the quantitative analysis of protein organization within the cell.
Details
- Language :
- English
- ISSN :
- 17444292
- Volume :
- 20
- Issue :
- 5
- Database :
- Directory of Open Access Journals
- Journal :
- Molecular Systems Biology
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.10a4b38bbb1c488aaaefcdc1f2306ba0
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s44320-024-00029-6