title: Yeast Proteome Dynamics from Single Cell Imaging and Automated Analysis.
abstract: 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.
authors.affiliation: The Donnelly Centre, University of Toronto, Toronto, ON M5S3E1, Canada.
authors.forename: Yolanda T
authors.initials: YT
authors.lastname: Chong
authors.affiliation: The Donnelly Centre, University of Toronto, Toronto, ON M5S3E1, Canada.
authors.forename: Judice L Y
authors.initials: JL
authors.lastname: Koh
authors.affiliation: The Donnelly Centre, University of Toronto, Toronto, ON M5S3E1, Canada.
authors.forename: Helena
authors.initials: H
authors.lastname: Friesen
authors.forename: Supipi Kaluarachchi
authors.initials: SK
authors.lastname: Duffy
authors.affiliation: The Donnelly Centre, University of Toronto, Toronto, ON M5S3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S3E1, Canada.
authors.forename: Kaluarachchi
authors.initials: K
authors.lastname: Duffy
authors.affiliation: The Donnelly Centre, University of Toronto, Toronto, ON M5S3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S3E1, Canada.
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Cox
authors.affiliation: Department of Cell and Systems Biology, University of Toronto, Toronto, ON M5S3E1, Canada.
authors.forename: Alan
authors.initials: A
authors.lastname: Moses
authors.affiliation: The Donnelly Centre, University of Toronto, Toronto, ON M5S3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S3E1, Canada.
authors.forename: Jason
authors.initials: J
authors.lastname: Moffat
authors.affiliation: The Donnelly Centre, University of Toronto, Toronto, ON M5S3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S3E1, Canada.
authors.forename: Charles
authors.initials: C
authors.lastname: Boone
authors.affiliation: The Donnelly Centre, University of Toronto, Toronto, ON M5S3E1, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S3E1, Canada. Electronic address: brenda.andrews@utoronto.ca.
authors.forename: Brenda J
authors.initials: BJ
authors.lastname: Andrews
mesh_terms: D020543:Proteome / Q000032:analysis*; D012441:Saccharomyces cerevisiae / Q000737:chemistry* / Q000166:cytology* / Q000378:metabolism; D029701:Saccharomyces cerevisiae Proteins / Q000032:analysis* / Q000378:metabolism; D059010:Single-Cell Analysis; D060388:Support Vector Machine
chemical_list: D020543:Proteome; D029701:Saccharomyces cerevisiae Proteins