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Noise Genetics: Inferring Protein Function by Correlating Phenotype with Protein Levels and Localization in Individual Human Cells


Inferring the function of proteins and the role they play in cellular processes is essential for our understanding of cell biology, genetics and biology in general. Standard genetic approaches use large perturbations to cells such as gene knockout, knockdown or over expression of genes. Such methods are powerful, but have the drawback of taking the cell far from its normal working point. Here, we provide a new and much milder approach, which uses the natural cell-cell variation in protein level and expression pattern as a source of mild perturbation. We monitor individual live cancer cells under the microscope and correlate their protein levels and localization with phenotype in the same cells. We use the motility of human cancer cells as a model system that is highly important for understanding metastasis in cancer. We find that our approach uncovers most of the known motility proteins, as well as new ones which we validate using knockdown experiments. Our novel approach is widely applicable to any phenotype that can be visualized in individual cells, and for any organism for which one can measure proteins in individual cells.


Vyšlo v časopise: Noise Genetics: Inferring Protein Function by Correlating Phenotype with Protein Levels and Localization in Individual Human Cells. PLoS Genet 10(3): e32767. doi:10.1371/journal.pgen.1004176
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1004176

Souhrn

Inferring the function of proteins and the role they play in cellular processes is essential for our understanding of cell biology, genetics and biology in general. Standard genetic approaches use large perturbations to cells such as gene knockout, knockdown or over expression of genes. Such methods are powerful, but have the drawback of taking the cell far from its normal working point. Here, we provide a new and much milder approach, which uses the natural cell-cell variation in protein level and expression pattern as a source of mild perturbation. We monitor individual live cancer cells under the microscope and correlate their protein levels and localization with phenotype in the same cells. We use the motility of human cancer cells as a model system that is highly important for understanding metastasis in cancer. We find that our approach uncovers most of the known motility proteins, as well as new ones which we validate using knockdown experiments. Our novel approach is widely applicable to any phenotype that can be visualized in individual cells, and for any organism for which one can measure proteins in individual cells.


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Genetika Reprodukčná medicína

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PLOS Genetics


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