Yolanda T. Chong

Cellular Pathways Regulating Responses to Compatible and Self-Incompatible Pollen in Brassica and Arabidopsis Stigmas Intersect at Exo70A1, a Putative Component of the Exocyst Complex

In the Brassicaceae, compatible pollen–pistil interactions result in pollen adhesion to the stigma, while pollen grains from unrelated plant species are largely ignored. There can also be an additional layer of recognition to prevent self-fertilization, the self-incompatibility response, whereby self pollen grains are distinguished from nonself pollen grains and rejected. This pathway is activated in the stigma and involves the ARM repeat–containing 1 (ARC1) protein, an E3 ubiquitin ligase. In a screen for ARC1-interacting proteins, we have identified Brassica napus Exo70A1, a putative component of the exocyst complex that is known to regulate polarized secretion. We show through transgenic studies that loss of Exo70A1 in Brassica and Arabidopsis thaliana stigmas leads to the rejection of compatible pollen at the same stage as the self-incompatibility response. A red fluorescent protein:Exo70A1 fusion rescues this stigmatic defect in Arabidopsis and is found to be mobilized to the plasma membrane concomitant with flowers opening. By contrast, increased expression of Exo70A1 in self-incompatible Brassica partially overcomes the self pollen rejection response. Thus, our data show that the Exo70A1 protein functions at the intersection of two cellular pathways, where it is required in the stigma for the acceptance of compatible pollen in both Brassica and Arabidopsis and is negatively regulated by Brassica self-incompatibility.

Yeast Proteome Dynamics from Single Cell Imaging and Automated Analysis

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.

Characterization of the Arabidopsis thaliana exocyst complex gene families by phylogenetic, expression profiling, and subcellular localization studies

*The exocyst is a complex of eight proteins (Sec3p, Sec5p, Sec6p, Sec8p, Sec10p, Sec15p, Exo70p and Exo84p) involved in tethering vesicles to the plasma membrane during regulated or polarized secretion. Here, the plant exocyst complex was explored in phylogenetic, expression, and subcellular localization studies. *Evolutionary relationships of predicted exocyst subunits were examined in the complete genomes of Arabidopsis thaliana, Oryza sativa, Populus trichocarpa and Physcomitrella patens. Furthermore, detailed expression profiling of the A. thaliana microarray databases was performed and subcellular localization patterns were studied. *Several plant exocyst subunit genes appear to have undergone gene expansion in a common ancestor and subsequent duplication events in independent plant lineages. Expression profiling revealed that the A. thaliana Exo70 gene family exhibits dynamic expression patterns, while the remaining exocyst subunit genes displayed more static profiles. Subcellular localization patterns for A. thaliana exocyst subunits ranged from cytosolic to endosomal compartments (with enrichment in the early endosomes and the trans-Golgi network). Interestingly, two endosomal-localized AtExo70 proteins also recruited other exocyst subunits to these compartments. *Overall subcellular localization patterns were observed that were also found in yeast and animal cells, and this, coupled with the evolutionary relationships, suggests that the exocyst may perform similar conserved functions in plants.

Exploring the Yeast Acetylome Using Functional Genomics

Lysine acetylation is a dynamic posttranslational modification with a well-defined role in regulating histones. The impact of acetylation on other cellular functions remains relatively uncharacterized. We explored the budding yeast acetylome with a functional genomics approach, assessing the effects of gene overexpression in the absence of lysine deacetylases (KDACs). We generated a network of 463 synthetic dosage lethal (SDL) interactions involving class I and II KDACs, revealing many cellular pathways regulated by different KDACs. A biochemical survey of genes interacting with the KDAC RPD3 identified 72 proteins acetylated in vivo. In-depth analysis of one of these proteins, Swi4, revealed a role for acetylation in G1-specific gene expression. Acetylation of Swi4 regulates interaction with its partner Swi6, both components of the SBF transcription factor. This study expands our view of the yeast acetylome, demonstrates the utility of functional genomic screens for exploring enzymatic pathways, and provides functional information that can be mined for future studies.

The Budding Yeast Nuclear Envelope Adjacent to the Nucleolus Serves as a Membrane Sink during Mitotic Delay

The mechanisms that dictate nuclear shape are largely unknown. Here we screened the budding yeast deletion collection for mutants with abnormal nuclear shape. A common phenotype was the appearance of a nuclear extension, particularly in mutants in DNA repair and chromosome segregation genes. Our data suggest that these mutations led to the abnormal nuclear morphology indirectly, by causing a checkpoint-induced cell-cycle delay. Indeed, delaying cells in mitosis by other means also led to the appearance of nuclear extensions, whereas inactivating the DNA damage checkpoint pathway in a DNA repair mutant reduced the fraction of cells with nuclear extensions. Formation of a nuclear extension was specific to a mitotic delay, because cells arrested in S or G2 had round nuclei. Moreover, the nuclear extension always coincided with the nucleolus, while the morphology of the DNA mass remained largely unchanged. Finally, we found that phospholipid synthesis continued unperturbed when cells delayed in mitosis, and inhibiting phospholipid synthesis abolished the formation of nuclear extensions. Our data suggest a mechanism that promotes nuclear envelope expansion during mitosis. When mitotic progression is delayed, cells sequester the added membrane to the nuclear envelope associated with the nucleolus, possibly to avoid disruption of intranuclear organization.

A quantitative literature-curated gold standard for kinase-substrate pairs

We describe the Yeast Kinase Interaction Database (KID, http://www.moseslab.csb.utoronto.ca/KID/ ), which contains high- and low-throughput data relevant to phosphorylation events. KID includes 6,225 low-throughput and 21,990 high-throughput interactions, from greater than 35,000 experiments. By quantitatively integrating these data, we identified 517 high-confidence kinase-substrate pairs that we consider a gold standard. We show that this gold standard can be used to assess published high-throughput datasets, suggesting that it will enable similar rigorous assessments in the future.We describe the Yeast Kinase Interaction Database (KID, http://www.moseslab.csb.utoronto.ca/KID/), which contains high- and low-throughput data relevant to phosphorylation events. KID includes 6,225 low-throughput and 21,990 high-throughput interactions, from greater than 35,000 experiments. By quantitatively integrating these data, we identified 517 high-confidence kinase-substrate pairs that we consider a gold standard. We show that this gold standard can be used to assess published high-throughput datasets, suggesting that it will enable similar rigorous assessments in the future.

CYCLoPs: A Comprehensive Database Constructed from Automated Analysis of Protein Abundance and Subcellular Localization Patterns in Saccharomyces cerevisiae

Changes in protein subcellular localization and abundance are central to biological regulation in eukaryotic cells. Quantitative measures of protein dynamics in vivo are therefore highly useful for elucidating specific regulatory pathways. Using a combinatorial approach of yeast synthetic genetic array technology, high-content screening, and machine learning classifiers, we developed an automated platform to characterize protein localization and abundance patterns from images of log phase cells from the open-reading frame−green fluorescent protein collection in the budding yeast, Saccharomyces cerevisiae. For each protein, we produced quantitative profiles of localization scores for 16 subcellular compartments at single-cell resolution to trace proteome-wide relocalization in conditions over time. We generated a collection of ∼300,000 micrographs, comprising more than 20 million cells and ∼9 billion quantitative measurements. The images depict the localization and abundance dynamics of more than 4000 proteins under two chemical treatments and in a selected mutant background. Here, we describe CYCLoPs (Collection of Yeast Cells Localization Patterns), a web database resource that provides a central platform for housing and analyzing our yeast proteome dynamics datasets at the single cell level. CYCLoPs version 1.0 is available at http://cyclops.ccbr.utoronto.ca. CYCLoPs will provide a valuable resource for the yeast and eukaryotic cell biology communities and will be updated as new experiments become available.

A Novel Mechanism for SUMO System Control: Regulated Ulp1 Nucleolar Sequestration

ABSTRACT The small ubiquitin-related modifiers (SUMOs) are evolutionarily conserved polypeptides that are covalently conjugated to protein targets to modulate their subcellular localization, half-life, or activity. Steady-state SUMO conjugation levels increase in response to many different types of environmental stresses, but how the SUMO system is regulated in response to these insults is not well understood. Here, we characterize a novel mode of SUMO system control: in response to elevated alcohol levels, the Saccharomyces cerevisiae SUMO protease Ulp1 is disengaged from its usual location at the nuclear pore complex (NPC) and sequestered in the nucleolus. We further show that the Ulp1 region previously demonstrated to interact with the karyopherins Kap95 and Kap60 (amino acids 150 to 340) is necessary and sufficient for nucleolar targeting and that enforced sequestration of Ulp1 in the nucleolus significantly increases steady-state SUMO conjugate levels, even in the absence of alcohol. We have thus characterized a novel mechanism of SUMO system control in which the balance between SUMO-conjugating and -deconjugating activities at the NPC is altered in response to stress via relocalization of a SUMO-deconjugating enzyme.

A picture is worth a thousand words: genomics to phenomics in the yeast Saccharomyces cerevisiae.

Large scale cell biological experiments are beginning to be applied as a systems‐level approach to decipher mechanisms that govern cellular function in health and disease. The use of automated microscopes combined with digital imaging, machine learning and other analytical tools has enabled high‐content screening (HCS) in a variety of experimental systems. Successful HCS screens demand careful attention to assay development, data acquisition methods and available genomic tools. In this minireview, we highlight developments in this field pertaining to yeast cell biology and discuss how we have combined HCS with methods for automated yeast genetics (synthetic genetic array (SGA) analysis) to enable systematic analysis of cell biological phenotypes in a variety of genetic backgrounds.

Capturing tumor complexity in vitro: Comparative analysis of 2D and 3D tumor models for drug discovery.

Two-dimensional (2D) cell cultures growing on plastic do not recapitulate the three dimensional (3D) architecture and complexity of human tumors. More representative models are required for drug discovery and validation. Here, 2D culture and 3D mono- and stromal co-culture models of increasing complexity have been established and cross-comparisons made using three standard cell carcinoma lines: MCF7, LNCaP, NCI-H1437. Fluorescence-based growth curves, 3D image analysis, immunohistochemistry and treatment responses showed that end points differed according to cell type, stromal co-culture and culture format. The adaptable methodologies described here should guide the choice of appropriate simple and complex in vitro models.