Deep learning approach for quantification of organelles and misfolded polypeptide delivery within degradative compartments
- PMID: 32401604
- PMCID: PMC7359569
- DOI: 10.1091/mbc.E20-04-0269
Deep learning approach for quantification of organelles and misfolded polypeptide delivery within degradative compartments
Abstract
Endolysosomal compartments maintain cellular fitness by clearing dysfunctional organelles and proteins from cells. Modulation of their activity offers therapeutic opportunities. Quantification of cargo delivery to and/or accumulation within endolysosomes is instrumental for characterizing lysosome-driven pathways at the molecular level and monitoring consequences of genetic or environmental modifications. Here we introduce LysoQuant, a deep learning approach for segmentation and classification of fluorescence images capturing cargo delivery within endolysosomes for clearance. LysoQuant is trained for unbiased and rapid recognition with human-level accuracy, and the pipeline informs on a series of quantitative parameters such as endolysosome number, size, shape, position within cells, and occupancy, which report on activity of lysosome-driven pathways. In our selected examples, LysoQuant successfully determines the magnitude of mechanistically distinct catabolic pathways that ensure lysosomal clearance of a model organelle, the endoplasmic reticulum, and of a model protein, polymerogenic ATZ. It does so with accuracy and velocity compatible with those of high-throughput analyses.
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References
-
- Arganda-Carreras I, Kaynig V, Rueden C, Eliceiri KW, Schindelin J, Cardona A, Sebastian Seung H. (2017). Trainable Weka segmentation: a machine learning tool for microscopy pixel classification. Bioinformatics , 2424–2426. - PubMed
-
- Atherton TJ, Kerbyson DJ. (1999). Size invariant circle detection. Image Vision Comput , 795–803.
-
- Ballabio A, Bonifacino JS. (2019). Lysosomes as dynamic regulators of cell and organismal homeostasis. Nat Rev Mol Cell Biol. - PubMed
-
- Berg S, Kutra D, Kroeger T, Straehle CN, Kausler BX, Haubold C, Schiegg M, Ales J, Beier T, Rudy M, et al. (2019). iLastik: interactive machine learning for (bio)image analysis. Nat Methods , 1226–1232. - PubMed
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