Yeast Proteome Dynamics from Single Cell Imaging and Automated Analysis
Open accessAbstract
Proteomics has proved invaluable in generating large-scale quantitative data; however, the development of systems approaches for examining the proteome in vivo has lagged behind. To evaluate protein abundance and localization on a proteome scale, we exploited the yeast GFP-fusion collection in a pipeline combining automated genetics, high-throughput microscopy, and computational feature analysis. We developed an ensemble of binary classifiers to generate localization data from single-cell measurements and constructed maps of ∼3,000 proteins connected to 16 localization classes. To survey proteome dynamics in response to different chemical and genetic stimuli, we measure proteome-wide abundance and localization and identified changes over time. We analyzed >20 million cells to identify dynamic proteins that redistribute among multiple localizations in hydroxyurea, rapamycin, and in an rpd3Δ background. Because our localization and abundance data are quantitative, they provide the opportunity for many types of comparative studies, single cell analyses, modeling, and prediction. VIDEO ABSTRACT.
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- Authors
- Chong, Y. T., Koh, J. L. Y., Friesen, H., Kaluarachchi Duffy, S., Cox, M. J., Moses, A., Moffat, J., Boone, C., & Andrews, B. J.
- Affiliations
- University of Toronto (CA)
- Corresponding author
- Andrews, Brenda J.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2015-06
- Volume
- 161
- Issue
- 6
- Pages
- 1413-1424
- ISSN
- 0092-8674 (ISSN-L)
- OpenAlex
- W2132744522
- Cited by
- 274
- References
- 8
- Citations by year
- 2026: 4 · 2025: 17 · 2024: 19 · 2023: 16 · 2022: 22 · 2021: 24 · 2020: 30 · 2019: 29 · 2018: 28 · 2017: 34 · 2016: 38 · 2015: 13
- FWCI
- 22.88
- Type
- journal article
- Language
- en
- Update notices
- erratum (2015-07-02)
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Canadian Institutes of Health Research (MOP97939)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Advanced Fluorescence Microscopy Techniques
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
- Keywords
- protein localization, protein abundance, GFP fusion protein, single-cell imaging, automated image analysis, binary classifier ensembles, hydroxyurea, rapamycin, Saccharomyces cerevisiae
- MeSH terms
- Saccharomyces cerevisiae, Proteome, Saccharomyces cerevisiae Proteins, Single-Cell Analysis, Support Vector Machine
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