PhenoM: a database of morphological phenotypes caused by mutation of essential genes in Saccharomyces cerevisiae

About one-fifth of the genes in the budding yeast are essential for haploid viability and cannot be functionally assessed using standard genetic approaches such as gene deletion. To facilitate genetic analysis of essential genes, we and others have assembled collections of yeast strains expressing temperature-sensitive (ts) alleles of essential genes. To explore the phenotypes caused by essential gene mutation we used a panel of genetically engineered fluorescent markers to explore the morphology of cells in the ts strain collection using high-throughput microscopy. Here, we describe the design and implementation of an online database, PhenoM (Phenomics of yeast Mutants), for storing, retrieving, visualizing and data mining the quantitative single-cell measurements extracted from micrographs of the ts mutant cells. PhenoM allows users to rapidly search and retrieve raw images and their quantified morphological data for genes of interest. The database also provides several data-mining tools, including a PhenoBlast module for phenotypic comparison between mutant strains and a Gene Ontology module for functional enrichment analysis of gene sets showing similar morphological alterations. The current PhenoM version 1.0 contains 78 194 morphological images and 1 909 914 cells covering six subcellular compartments or structures for 775 ts alleles spanning 491 essential genes. PhenoM is freely available at http://phenom.ccbr.utoronto.ca/

Transcriptome profiling to identify genes involved in peroxisome assembly and function

Yeast cells were induced to proliferate peroxisomes, and microarray transcriptional profiling was used to identify PEX genes encoding peroxins involved in peroxisome assembly and genes involved in peroxisome function. Clustering algorithms identified 224 genes with expression profiles similar to those of genes encoding peroxisomal proteins and genes involved in peroxisome biogenesis. Several previously uncharacterized genes were identified, two of which, YPL112c and YOR084w, encode proteins of the peroxisomal membrane and matrix, respectively. Ypl112p, renamed Pex25p, is a novel peroxin required for the regulation of peroxisome size and maintenance. These studies demonstrate the utility of comparative gene profiling as an alternative to functional assays to identify genes with roles in peroxisome biogenesis

Expression of the Salmonella Spp. Virulence Factor SifA in Yeast Alters Rho1 Activity on Peroxisomes

SifA is a virulence protein required for assembly and tubulation of a modified phagosome that promotes Salmonella replication. We show that SifA expressed in yeast induces membrane invagination during peroxisome proliferation and requires functional Rho1p. This is consistent with SifA ability to interact with RhoA and the fact that it is a GEF structural homologue

A Systems Biology Approach Reveals the Role of a Novel Methyltransferase in Response to Chemical Stress and Lipid Homeostasis

Using small molecule probes to understand gene function is an attractive approach that allows functional characterization of genes that are dispensable in standard laboratory conditions and provides insight into the mode of action of these compounds. Using chemogenomic assays we previously identified yeast Crg1, an uncharacterized SAM-dependent methyltransferase, as a novel interactor of the protein phosphatase inhibitor cantharidin. In this study we used a combinatorial approach that exploits contemporary high-throughput techniques available in Saccharomyces cerevisiae combined with rigorous biological follow-up to characterize the interaction of Crg1 with cantharidin. Biochemical analysis of this enzyme followed by a systematic analysis of the interactome and lipidome of CRG1 mutants revealed that Crg1, a stress-responsive SAM-dependent methyltransferase, methylates cantharidin in vitro. Chemogenomic assays uncovered that lipid-related processes are essential for cantharidin resistance in cells sensitized by deletion of the CRG1 gene. Lipidome-wide analysis of mutants further showed that cantharidin induces alterations in glycerophospholipid and sphingolipid abundance in a Crg1-dependent manner. We propose that Crg1 is a small molecule methyltransferase important for maintaining lipid homeostasis in response to drug perturbation. This approach demonstrates the value of combining chemical genomics with other systems-based methods for characterizing proteins and elucidating previously unknown mechanisms of action of small molecule inhibitors

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Activation of the Anaphase Promoting Complex Reverses Multiple Drug Resistant Cancer in a Canine Model of Multiple Drug Resistant Lymphoma

Like humans, canine lymphomas are treated by chemotherapy cocktails and frequently develop multiple drug resistance (MDR). Their shortened clinical timelines and tumor accessibility make canines excellent models to study MDR mechanisms. Insulin-sensitizers have been shown to reduce the incidence of cancer in humans prescribed them, and we previously demonstrated that they also reverse and delay MDR development in vitro. Here, we treated canines with MDR lymphoma with metformin to assess clinical and tumoral responses, including changes in MDR biomarkers, and used mRNA microarrays to determine differential gene expression. Metformin reduced MDR protein markers in all canines in the study. Microarrays performed on mRNAs gathered through longitudinal tumor sampling identified a 290 gene set that was enriched in Anaphase Promoting Complex (APC) substrates and additional mRNAs associated with slowed mitotic progression in MDR samples compared to skin controls. mRNAs from a canine that went into remission showed that APC substrate mRNAs were decreased, indicating that the APC was activated during remission. In vitro validation using canine lymphoma cells selected for resistance to chemotherapeutic drugs confirmed that APC activation restored MDR chemosensitivity, and that APC activity was reduced in MDR cells. This supports the idea that rapidly pushing MDR cells that harbor high loads of chromosome instability through mitosis, by activating the APC, contributes to improved survival and disease-free duration

A negative genetic interaction map in isogenic cancer cell lines reveals cancer cell vulnerabilities

Improved efforts are necessary to define the functional product of cancer mutations currently being revealed through large-scale sequencing efforts. Using genome-scale pooled shRNA screening technology, we mapped negative genetic interactions across a set of isogenic cancer cell lines and confirmed hundreds of these interactions in orthogonal co-culture competition assays to generate a high-confidence genetic interaction network of differentially essential or differential essentiality (DiE) genes. The network uncovered examples of conserved genetic interactions, densely connected functional modules derived from comparative genomics with model systems data, functions for uncharacterized genes in the human genome and targetable vulnerabilities. Finally, we demonstrate a general applicability of DiE gene signatures in determining genetic dependencies of other non-isogenic cancer cell lines. For example, the PTEN(-/-) DiE genes reveal a signature that can preferentially classify PTEN-dependent genotypes across a series of non-isogenic cell lines derived from the breast, pancreas and ovarian cancers. Our reference network suggests that many cancer vulnerabilities remain to be discovered through systematic derivation of a network of differentially essential genes in an isogenic cancer cell model

A negative genetic interaction map in isogenic cancer cell lines reveals cancer cell vulnerabilities

Improved efforts are necessary to define the functional product of cancer mutations currently being revealed through large-scale sequencing efforts. Using genome-scale pooled shRNA screening technology, we mapped negative genetic interactions across a set of isogenic cancer cell lines and confirmed hundreds of these interactions in orthogonal co-culture competition assays to generate a high-confidence genetic interaction network of differentially essential or differential essentiality (DiE) genes. The network uncovered examples of conserved genetic interactions, densely connected functional modules derived from comparative genomics with model systems data, functions for uncharacterized genes in the human genome and targetable vulnerabilities. Finally, we demonstrate a general applicability of DiE gene signatures in determining genetic dependencies of other non-isogenic cancer cell lines. For example, the PTEN(−/−) DiE genes reveal a signature that can preferentially classify PTEN-dependent genotypes across a series of non-isogenic cell lines derived from the breast, pancreas and ovarian cancers. Our reference network suggests that many cancer vulnerabilities remain to be discovered through systematic derivation of a network of differentially essential genes in an isogenic cancer cell model

Seipin and the membrane-shaping protein Pex30 cooperate in organelle budding from the endoplasmic reticulum

Lipid droplets (LDs) and peroxisomes are ubiquitous organelles with central roles in eukaryotic cells. Although the mechanisms involved in biogenesis of these organelles remain elusive, both seem to require the endoplasmic reticulum (ER). Here we show that in yeast the ER budding of these structurally unrelated organelles has remarkably similar requirements and involves cooperation between Pex30 and the seipin complex. In the absence of these components, budding of both LDs and peroxisomes is inhibited, leading to the ER accumulation of their respective constituent molecules, such as triacylglycerols and peroxisomal membrane proteins, whereas COPII vesicle formation remains unaffected. This phenotype can be reversed by remodeling ER phospholipid composition highlighting a key function of these lipids in organelle biogenesis. We propose that seipin and Pex30 act in concert to organize membrane domains permissive for organelle budding, and that may have a lipid composition distinct from the bulk ER