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2.
Mol Cell Proteomics ; 13(11): 2812-23, 2014 Nov.
Article in English | MEDLINE | ID: mdl-25139910

ABSTRACT

The use of in vivo Förster resonance energy transfer (FRET) data to determine the molecular architecture of a protein complex in living cells is challenging due to data sparseness, sample heterogeneity, signal contributions from multiple donors and acceptors, unequal fluorophore brightness, photobleaching, flexibility of the linker connecting the fluorophore to the tagged protein, and spectral cross-talk. We addressed these challenges by using a Bayesian approach that produces the posterior probability of a model, given the input data. The posterior probability is defined as a function of the dependence of our FRET metric FRETR on a structure (forward model), a model of noise in the data, as well as prior information about the structure, relative populations of distinct states in the sample, forward model parameters, and data noise. The forward model was validated against kinetic Monte Carlo simulations and in vivo experimental data collected on nine systems of known structure. In addition, our Bayesian approach was validated by a benchmark of 16 protein complexes of known structure. Given the structures of each subunit of the complexes, models were computed from synthetic FRETR data with a distance root-mean-squared deviation error of 14 to 17 Å. The approach is implemented in the open-source Integrative Modeling Platform, allowing us to determine macromolecular structures through a combination of in vivo FRETR data and data from other sources, such as electron microscopy and chemical cross-linking.


Subject(s)
Bacterial Proteins/metabolism , Fluorescence Resonance Energy Transfer , Luminescent Proteins/metabolism , Saccharomyces cerevisiae Proteins/analysis , Saccharomyces cerevisiae Proteins/metabolism , Algorithms , Bayes Theorem , Computer Simulation , Molecular Structure , Monte Carlo Method , Protein Interaction Mapping , Protein Structure, Quaternary , Saccharomyces cerevisiae
3.
Mol Biol Cell ; 16(7): 3341-52, 2005 Jul.
Article in English | MEDLINE | ID: mdl-15872084

ABSTRACT

The spindle pole body (SPB) is the microtubule organizing center of Saccharomyces cerevisiae. Its core includes the proteins Spc42, Spc110 (kendrin/pericentrin ortholog), calmodulin (Cmd1), Spc29, and Cnm67. Each was tagged with CFP and YFP and their proximity to each other was determined by fluorescence resonance energy transfer (FRET). FRET was measured by a new metric that accurately reflected the relative extent of energy transfer. The FRET values established the topology of the core proteins within the architecture of SPB. The N-termini of Spc42 and Spc29, and the C-termini of all the core proteins face the gap between the IL2 layer and the central plaque. Spc110 traverses the central plaque and Cnm67 spans the IL2 layer. Spc42 is a central component of the central plaque where its N-terminus is closely associated with the C-termini of Spc29, Cmd1, and Spc110. When the donor-acceptor pairs were ordered into five broad categories of increasing FRET, the ranking of the pairs specified a unique geometry for the positions of the core proteins, as shown by a mathematical proof. The geometry was integrated with prior cryoelectron tomography to create a model of the interwoven network of proteins within the central plaque. One prediction of the model, the dimerization of the calmodulin-binding domains of Spc110, was confirmed by in vitro analysis.


Subject(s)
Saccharomyces cerevisiae/metabolism , Spindle Apparatus , Calmodulin/chemistry , Calmodulin-Binding Proteins , Centrioles/ultrastructure , Cryoelectron Microscopy , Cytoskeletal Proteins , Dimerization , Fluorescence Resonance Energy Transfer , Fungal Proteins , Green Fluorescent Proteins/metabolism , In Vitro Techniques , Microscopy, Electron , Microscopy, Fluorescence , Microtubule-Associated Proteins/chemistry , Models, Biological , Models, Molecular , Models, Theoretical , Nuclear Proteins/chemistry , Protein Structure, Tertiary , Saccharomyces cerevisiae Proteins/chemistry , Saccharomyces cerevisiae Proteins/metabolism
4.
Yeast ; 21(9): 793-800, 2004 Jul 15.
Article in English | MEDLINE | ID: mdl-15282802

ABSTRACT

The localization of proteins can give important clues about their function and help sort data from large-scale proteomic screens. Forty-five proteins were tagged with the GFP variant YFP. These proteins were chosen because they are encoded by genes that display strong cell cycle-dependent expression that peaks in G(1). Most of these proteins localize to either the nucleus or to sites of cell growth. We are able to assign new cellular component GO terms to ASF2, TOS4, RTT109, YBR070C, YKR090W, YOL007C, YOL019W and YPR174C. We also have localization data for 21 other proteins. Noteworthy localizations were found for Rfa1p, a member of the DNA replication A complex, and Pri2p and Pol12p, subunits of the alpha-DNA polymerase : primase complex. In addition to its nuclear localization, Rfa1p assembled into cytoplasmic foci adjacent to the nucleus in cells during the G(1)-S phase transition of the cell cycle. Pri2 and Pol12 took on a beaded appearance at the G(1)-S transition and later in the cell cycle were enriched in the nuclear envelope. A new spindle pole body/nuclear envelope component encoded by YPR174 was identified. The cell cycle-dependent abundance of Tos4p mirrored Yox1p and these two proteins were the only proteins that were found exclusively at the G(1)-S phase of the cell cycle. A complete list of localizations, along with images, can be found at our website (http://www.yeastrc.org/cln2/).


Subject(s)
Cell Cycle , Cyclins/metabolism , Saccharomyces cerevisiae Proteins/metabolism , Saccharomyces cerevisiae/cytology , Saccharomyces cerevisiae/metabolism , Cyclins/genetics , Genes, Fungal , Green Fluorescent Proteins , Luminescent Proteins/genetics , Luminescent Proteins/metabolism , Proteome/genetics , Proteome/metabolism , Recombinant Fusion Proteins/genetics , Recombinant Fusion Proteins/metabolism , Saccharomyces cerevisiae/genetics , Saccharomyces cerevisiae Proteins/genetics , Subcellular Fractions
5.
Mol Cell ; 12(6): 1353-65, 2003 Dec.
Article in English | MEDLINE | ID: mdl-14690591

ABSTRACT

Interpreting genome sequences requires the functional analysis of thousands of predicted proteins, many of which are uncharacterized and without obvious homologs. To assess whether the roles of large sets of uncharacterized genes can be assigned by targeted application of a suite of technologies, we used four complementary protein-based methods to analyze a set of 100 uncharacterized but essential open reading frames (ORFs) of the yeast Saccharomyces cerevisiae. These proteins were subjected to affinity purification and mass spectrometry analysis to identify copurifying proteins, two-hybrid analysis to identify interacting proteins, fluorescence microscopy to localize the proteins, and structure prediction methodology to predict structural domains or identify remote homologies. Integration of the data assigned function to 48 ORFs using at least two of the Gene Ontology (GO) categories of biological process, molecular function, and cellular component; 77 ORFs were annotated by at least one method. This combination of technologies, coupled with annotation using GO, is a powerful approach to classifying genes.


Subject(s)
Computational Biology , Saccharomyces cerevisiae Proteins/genetics , Saccharomyces cerevisiae Proteins/metabolism , Genome, Fungal , Oligonucleotide Array Sequence Analysis , Open Reading Frames , Proteome/analysis , Two-Hybrid System Techniques
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