Overexpression of branched-chain amino acid aminotransferases rescues the growth defects of cells lacking the Barth syndrome-related gene TAZ1.

The yeast protein Taz1 is the orthologue of human Tafazzin, a phospholipid acyltransferase involved in cardiolipin (CL) remodeling via a monolyso CL (MLCL) intermediate. Mutations in Tafazzin lead to Barth syndrome (BTHS), a metabolic and neuromuscular disorder that primarily affects the heart, muscles, and immune system. Similar to observations in fibroblasts and platelets from patients with BTHS or from animal models, abolishing yeast Taz1 results in decreased total CL amounts, increased levels of MLCL, and mitochondrial dysfunction. However, the biochemical mechanisms underlying the mitochondrial dysfunction in BTHS remain unclear. To better understand the pathomechanism of BTHS, we searched for multi-copy suppressors of the taz1Δ growth defect in yeast cells. We identified the branched-chain amino acid transaminases (BCATs) Bat1 and Bat2 as such suppressors. Similarly, overexpression of the mitochondrial isoform BCAT2 in mammalian cells lacking TAZ improves their growth. Elevated levels of Bat1 or Bat2 did not restore the reduced membrane potential, altered stability of respiratory complexes, or the defective accumulation of MLCL species in yeast taz1Δ cells. Importantly, supplying yeast or mammalian cells lacking TAZ1 with certain amino acids restored their growth behavior. Hence, our findings suggest that the metabolism of amino acids has an important and disease-relevant role in cells lacking Taz1 function. KEY MESSAGES: Bat1 and Bat2 are multi-copy suppressors of retarded growth of taz1Δ yeast cells. Overexpression of Bat1/2 in taz1Δ cells does not rescue known mitochondrial defects. Supplementation of amino acids enhances growth of cells lacking Taz1 or Tafazzin. Altered metabolism of amino acids might be involved in the pathomechanism of BTSH

Unbiased yeast screens identify cellular pathways affected in Niemann-Pick disease type C

Niemann–Pick disease type C (NPC) is a rare lysosomal storage disease caused by mutations in either the NPC1 or NPC2 genes. Mutations in the NPC1 gene lead to the majority of clinical cases (95%); however, the function of NPC1 remains unknown. To gain further insights into the biology of NPC1, we took advantage of the homology between the human NPC1 protein and its yeast orthologue, Niemann–Pick C–related protein 1 (Ncr1). We recreated the NCR1 mutant in yeast and performed screens to identify compensatory or redundant pathways that may be involved in NPC pathology, as well as proteins that were mislocalized in NCR1-deficient yeast. We also identified binding partners of the yeast Ncr1 orthologue. These screens identified several processes and pathways that may contribute to NPC pathogenesis. These included alterations in mitochondrial function, cytoskeleton organization, metal ion homeostasis, lipid trafficking, calcium signalling, and nutrient sensing. The mitochondrial and cytoskeletal abnormalities were validated in patient cells carrying mutations in NPC1, confirming their dysfunction in NPC disease

The yeast P5 type ATPase, Spf1, regulates manganese transport into the endoplasmic reticulum

The endoplasmic reticulum (ER) is a large, multifunctional and essential organelle. Despite intense research, the function of more than a third of ER proteins remains unknown even in the well-studied model organism Saccharomyces cerevisiae. One such protein is Spf1, which is a highly conserved, ER localized, putative P-type ATPase. Deletion of SPF1 causes a wide variety of phenotypes including severe ER stress suggesting that this protein is essential for the normal function of the ER. The closest homologue of Spf1 is the vacuolar P-type ATPase Ypk9 that influences Mn2+ homeostasis. However in vitro reconstitution assays with Spf1 have not yielded insight into its transport specificity. Here we took an in vivo approach to detect the direct and indirect effects of deleting SPF1. We found a specific reduction in the luminal concentration of Mn2+ in ∆spf1 cells and an increase following it’s overexpression. In agreement with the observed loss of luminal Mn2+ we could observe concurrent reduction in many Mn2+-related process in the ER lumen. Conversely, cytosolic Mn2+-dependent processes were increased. Together, these data support a role for Spf1p in Mn2+ transport in the cell. We also demonstrate that the human sequence homologue, ATP13A1, is a functionally conserved orthologue. Since ATP13A1 is highly expressed in developing neuronal tissues and in the brain, this should help in the study of Mn2+-dependent neurological disorders

High-throughput, quantitative analyses of genetic interactions in E. coli.

Large-scale genetic interaction studies provide the basis for defining gene function and pathway architecture. Recent advances in the ability to generate double mutants en masse in Saccharomyces cerevisiae have dramatically accelerated the acquisition of genetic interaction information and the biological inferences that follow. Here we describe a method based on F factor-driven conjugation, which allows for high-throughput generation of double mutants in Escherichia coli. This method, termed genetic interaction analysis technology for E. coli (GIANT-coli), permits us to systematically generate and array double-mutant cells on solid media in high-density arrays. We show that colony size provides a robust and quantitative output of cellular fitness and that GIANT-coli can recapitulate known synthetic interactions and identify previously unidentified negative (synthetic sickness or lethality) and positive (suppressive or epistatic) relationships. Finally, we describe a complementary strategy for genome-wide suppressor-mutant identification. Together, these methods permit rapid, large-scale genetic interaction studies in E. coli

Compartmentalized Synthesis of Triacylglycerol at the Inner Nuclear Membrane Regulates Nuclear Organization.

Cells dynamically adjust organelle organization in response to growth and environmental cues. This requires regulation of synthesis of phospholipids, the building blocks of organelle membranes, or remodeling of their fatty-acyl (FA) composition. FAs are also the main components of triacyglycerols (TGs), which enable energy storage in lipid droplets. How cells coordinate FA metabolism with organelle biogenesis during cell growth remains unclear. Here, we show that Lro1, an acyltransferase that generates TGs from phospholipid-derived FAs in yeast, relocates from the endoplasmic reticulum to a subdomain of the inner nuclear membrane. Lro1 nuclear targeting is regulated by cell cycle and nutrient starvation signals and is inhibited when the nucleus expands. Lro1 is active at this nuclear subdomain, and its compartmentalization is critical for nuclear integrity. These data suggest that Lro1 nuclear targeting provides a site of TG synthesis, which is coupled with nuclear membrane remodeling

Compartmentalized Synthesis of Triacylglycerol at the Inner Nuclear Membrane Regulates Nuclear Organization

Cells dynamically adjust organelle organization in response to growth and environmental cues. This requires regulation of synthesis of phospholipids, the building blocks of organelle membranes, or remodeling of their fatty-acyl (FA) composition. FAs are also the main components of triacyglycerols (TGs), which enable energy storage in lipid droplets. How cells coordinate FA metabolism with organelle biogenesis during cell growth remains unclear. Here, we show that Lro1, an acyltransferase that generates TGs from phospholipid-derived FAs in yeast, relocates from the endoplasmic reticulum to a subdomain of the inner nuclear membrane. Lro1 nuclear targeting is regulated by cell cycle and nutrient starvation signals and is inhibited when the nucleus expands. Lro1 is active at this nuclear subdomain, and its compartmentalization is critical for nuclear integrity. These data suggest that Lro1 nuclear targeting provides a site of TG synthesis, which is coupled with nuclear membrane remodeling

Functional Maps of Protein Complexes from Quantitative Genetic Interaction Data

Recently, a number of advanced screening technologies have allowed for the comprehensive quantification of aggravating and alleviating genetic interactions among gene pairs. In parallel, TAP-MS studies (tandem affinity purification followed by mass spectroscopy) have been successful at identifying physical protein interactions that can indicate proteins participating in the same molecular complex. Here, we propose a method for the joint learning of protein complexes and their functional relationships by integration of quantitative genetic interactions and TAP-MS data. Using 3 independent benchmark datasets, we demonstrate that this method is >50% more accurate at identifying functionally related protein pairs than previous approaches. Application to genes involved in yeast chromosome organization identifies a functional map of 91 multimeric complexes, a number of which are novel or have been substantially expanded by addition of new subunits. Interestingly, we find that complexes that are enriched for aggravating genetic interactions (i.e., synthetic lethality) are more likely to contain essential genes, linking each of these interactions to an underlying mechanism. These results demonstrate the importance of both large-scale genetic and physical interaction data in mapping pathway architecture and function

Genome-Wide Association Data Reveal a Global Map of Genetic Interactions among Protein Complexes

This work demonstrates how gene association studies can be analyzed to map a global landscape of genetic interactions among protein complexes and pathways. Despite the immense potential of gene association studies, they have been challenging to analyze because most traits are complex, involving the combined effect of mutations at many different genes. Due to lack of statistical power, only the strongest single markers are typically identified. Here, we present an integrative approach that greatly increases power through marker clustering and projection of marker interactions within and across protein complexes. Applied to a recent gene association study in yeast, this approach identifies 2,023 genetic interactions which map to 208 functional interactions among protein complexes. We show that such interactions are analogous to interactions derived through reverse genetic screens and that they provide coverage in areas not yet tested by reverse genetic analysis. This work has the potential to transform gene association studies, by elevating the analysis from the level of individual markers to global maps of genetic interactions. As proof of principle, we use synthetic genetic screens to confirm numerous novel genetic interactions for the INO80 chromatin remodeling complex

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/

Podbat: A Novel Genomic Tool Reveals Swr1-Independent H2A.Z Incorporation at Gene Coding Sequences through Epigenetic Meta-Analysis

Epigenetic regulation consists of a multitude of different modifications that determine active and inactive states of chromatin. Conditions such as cell differentiation or exposure to environmental stress require concerted changes in gene expression. To interpret epigenomics data, a spectrum of different interconnected datasets is needed, ranging from the genome sequence and positions of histones, together with their modifications and variants, to the transcriptional output of genomic regions. Here we present a tool, Podbat (Positioning database and analysis tool), that incorporates data from various sources and allows detailed dissection of the entire range of chromatin modifications simultaneously. Podbat can be used to analyze, visualize, store and share epigenomics data. Among other functions, Podbat allows data-driven determination of genome regions of differential protein occupancy or RNA expression using Hidden Markov Models. Comparisons between datasets are facilitated to enable the study of the comprehensive chromatin modification system simultaneously, irrespective of data-generating technique. Any organism with a sequenced genome can be accommodated. We exemplify the power of Podbat by reanalyzing all to-date published genome-wide data for the histone variant H2A.Z in fission yeast together with other histone marks and also phenotypic response data from several sources. This meta-analysis led to the unexpected finding of H2A.Z incorporation in the coding regions of genes encoding proteins involved in the regulation of meiosis and genotoxic stress responses. This incorporation was partly independent of the H2A.Z-incorporating remodeller Swr1. We verified an Swr1-independent role for H2A.Z following genotoxic stress in vivo. Podbat is open source software freely downloadable from www.podbat.org, distributed under the GNU LGPL license. User manuals, test data and instructions are available at the website, as well as a repository for third party–developed plug-in modules. Podbat requires Java version 1.6 or higher