YPL.db2: the Yeast Protein Localization database, version 2.0

Application of Machine Learning in Spatial Proteomics

Spatial proteomics is an interdisciplinary field that investigates the localization and dynamics of proteins, and it has gained extensive attention in recent years, especially the subcellular proteomics. Numerous evidence indicate that the subcellular localization of proteins is associated with various cellular processes and disease progression. Mass spectrometry (MS)-based and imaging-based experimental approaches have been developed to acquire large-scale spatial proteomic data. To allow the reliable analysis of increasingly complex spatial proteomics data, machine learning (ML) methods have been widely used in both MS-based and imaging-based spatial proteomic data analysis pipelines. Here, we comprehensively survey the applications of ML in spatial proteomics from following aspects: (1) data resources for spatial proteome are comprehensively introduced; (2) the roles of different ML algorithms in data analysis pipelines are elaborated; (3) successful applications of spatial proteomics and several analytical tools integrating ML methods are presented; (4) challenges existing in modern ML-based spatial proteomics studies are discussed. This review provides guidelines for researchers seeking to apply ML methods to analyze spatial proteomic data and can facilitate insightful understanding of cell biology as well as the future research in medical and drug discovery communities.

Determining the interaction status and evolutionary fate of duplicated homomeric proteins

Oligomeric proteins are central to life. Duplication and divergence of their genes is a key evolutionary driver, also because duplications can yield very different outcomes. Given a homomeric ancestor, duplication can yield two paralogs that form two distinct homomeric complexes, or a heteromeric complex comprising both paralogs. Alternatively, one paralog remains a homomer while the other acquires a new partner. However, so far, conflicting trends have been noted with respect to which fate dominates, primarily because different methods and criteria are being used to assign the interaction status of paralogs. Here, we systematically analyzed all Saccharomyces cerevisiae and Escherichia coli oligomeric complexes that include paralogous proteins. We found that the proportions of homo-hetero duplication fates strongly depend on a variety of factors, yet that nonetheless, rigorous filtering gives a consistent picture. In E. coli about 50%, of the paralogous pairs appear to have retained the ancestral homomeric interaction, whereas in S. cerevisiae only ~10% retained a homomeric state. This difference was also observed when unique complexes were counted instead of paralogous gene pairs. We further show that this difference is accounted for by multiple cases of heteromeric yeast complexes that share common ancestry with homomeric bacterial complexes. Our analysis settles contradicting trends and conflicting previous analyses, and provides a systematic and rigorous pipeline for delineating the fate of duplicated oligomers in any organism for which protein-protein interaction data are available.

About half of all proteins assemble as oligomers, either by self-interaction (homomers) or via interaction with another protein (heteromers). The latter can be unrelated, yet, quite commonly, the interacting proteins are paralogs, namely two genes that arose by gene duplication. Indeed, while a homomer is encoded by a single gene, heteromers demand two genes as a minimum. Duplication can therefore yield two discrete homomeric complexes or a single heteromer. Do paralogs tend to retain the ancestral homomeric interaction, or do they mostly diverge into heteromeric complexes? Despite several studies addressing this question, to date, we lack a systematic, rigorous approach for delineating the oligomeric fates of paralogs on an organism scale. To this end, we developed a new pipeline for analysis of molecular interaction databases that includes various filtering steps and unambiguous definitions of all possible oligomeric fates. Applying this method to Escherichia coli and Saccharomyces cerevisiae we noted that paralogous pairs tend to remain homomeric in the former while in the latter heteromeric complexes dominate. We consequently note a systematic trend of homomeric bacterial proteins diverging into heteromeric complexes in eukaryotes.

Harnessing sub-organelle metabolism for biosynthesis of isoprenoids in yeast

Current yeast metabolic engineering in isoprenoids production mainly focuses on rewiring of cytosolic metabolic pathway. However, the precursors, cofactors and the enzymes are distributed in various sub-cellular compartments, which may hamper isoprenoid biosynthesis. On the other side, pathway compartmentalization provides several advantages for improving metabolic flux toward target products. We here summarize the recent advances on harnessing sub-organelle for isoprenoids biosynthesis in yeast, and analyze the knowledge about the localization of enzymes, cofactors and metabolites for guiding the rewiring of the sub-organelle metabolism. This review may provide some insights for constructing efficient yeast cell factories for production of isoprenoids and even other natural products.

Protein acetylation in metabolism - metabolites and cofactors

Reversible acetylation was initially described as an epigenetic mechanism regulating DNA accessibility. Since then, this process has emerged as a controller of histone and nonhistone acetylation that integrates key physiological processes such as metabolism, circadian rhythm and cell cycle, along with gene regulation in various organisms. The widespread and reversible nature of acetylation also revitalized interest in the mechanisms that regulate lysine acetyltransferases (KATs) and deacetylases (KDACs) in health and disease. Changes in protein or histone acetylation are especially relevant for many common diseases including obesity, diabetes mellitus, neurodegenerative diseases and cancer, as well as for some rare diseases such as mitochondrial diseases and lipodystrophies. In this Review, we examine the role of reversible acetylation in metabolic control and how changes in levels of metabolites or cofactors, including nicotinamide adenine dinucleotide, nicotinamide, coenzyme A, acetyl coenzyme A, zinc and butyrate and/or β-hydroxybutyrate, directly alter KAT or KDAC activity to link energy status to adaptive cellular and organismal homeostasis.

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.

Protein acetylation and acetyl coenzyme a metabolism in budding yeast

Cells sense and appropriately respond to the physical conditions and availability of nutrients in their environment. This sensing of the environment and consequent cellular responses are orchestrated by a multitude of signaling pathways and typically involve changes in transcription and metabolism. Recent discoveries suggest that the signaling and transcription machineries are regulated by signals which are derived from metabolism and reflect the metabolic state of the cell. Acetyl coenzyme A (CoA) is a key metabolite that links metabolism with signaling, chromatin structure, and transcription. Acetyl-CoA is produced by glycolysis as well as other catabolic pathways and used as a substrate for the citric acid cycle and as a precursor in synthesis of fatty acids and steroids and in other anabolic pathways. This central position in metabolism endows acetyl-CoA with an important regulatory role. Acetyl-CoA serves as a substrate for lysine acetyltransferases (KATs), which catalyze the transfer of acetyl groups to the epsilon-amino groups of lysines in histones and many other proteins. Fluctuations in the concentration of acetyl-CoA, reflecting the metabolic state of the cell, are translated into dynamic protein acetylations that regulate a variety of cell functions, including transcription, replication, DNA repair, cell cycle progression, and aging. This review highlights the synthesis and homeostasis of acetyl-CoA and the regulation of transcriptional and signaling machineries in yeast by acetylation.

Loss of Ypk1, the yeast homolog to the human serum- and glucocorticoid-induced protein kinase, accelerates phospholipase B1-mediated phosphatidylcholine deacylation

Ypk1, the yeast homolog of the human serum- and glucocorticoid-induced kinase (Sgk1), affects diverse cellular activities, including sphingolipid homeostasis. We now report that Ypk1 also impacts the turnover of the major phospholipid, phosphatidylcholine (PC). Pulse-chase radiolabeling reveals that a ypk1Δ mutant exhibits increased PC deacylation and glycerophosphocholine production compared with wild type yeast. Deletion of PLB1, a gene encoding a B-type phospholipase that hydrolyzes PC, in a ypk1Δ mutant curtails the increased PC deacylation. In contrast to previous data, we find that Plb1 resides in the ER and in the medium. Consistent with a link between Ypk1 and Plb1, the levels of both Plb1 protein and PLB1 message are elevated in a ypk1Δ strain compared with wild type yeast. Furthermore, deletion of PLB1 in a ypk1Δ mutant exacerbates phenotypes associated with loss of YPK1, including slowed growth and sensitivity to cell wall perturbation, suggesting that increased Plb1 activity buffers against the loss of Ypk1. Because Plb1 lacks a consensus phosphorylation site for Ypk1, we probed other processes under the control of Ypk1 that might be linked to PC turnover. Inhibition of sphingolipid biosynthesis by the drug myriocin or through utilization of a lcb1-100 mutant results in increased PLB1 expression. Furthermore, we discovered that the increase in PLB1 expression observed upon inhibition of sphingolipid synthesis or loss of Ypk1 is under the control of the Crz1 transcription factor. Taken together, these results suggest a functional interaction between Ypk1 and Plb1 in which altered sphingolipid metabolism up-regulates PLB1 expression via Crz1.

Genetic variation in DNA repair pathways and risk of non-Hodgkin's lymphoma

Molecular and genetic evidence suggests that DNA repair pathways may contribute to lymphoma susceptibility. Several studies have examined the association of DNA repair genes with lymphoma risk, but the findings from these reports have been inconsistent. Here we provide the results of a focused analysis of genetic variation in DNA repair genes and their association with the risk of non-Hodgkin's lymphoma (NHL). With a population of 1,297 NHL cases and 1,946 controls, we have performed a two-stage case/control association analysis of 446 single nucleotide polymorphisms (SNPs) tagging the genetic variation in 81 DNA repair genes. We found the most significant association with NHL risk in the ATM locus for rs227060 (OR = 1.27, 95% CI: 1.13-1.43, p = 6.77×10(-5)), which remained significant after adjustment for multiple testing. In a subtype-specific analysis, associations were also observed for the ATM locus among both diffuse large B-cell lymphomas (DLBCL) and small lymphocytic lymphomas (SLL), however there was no association observed among follicular lymphomas (FL). In addition, our study provides suggestive evidence of an interaction between SNPs in MRE11A and NBS1 associated with NHL risk (OR = 0.51, 95% CI: 0.34-0.77, p = 0.0002). Finally, an imputation analysis using the 1,000 Genomes Project data combined with a functional prediction analysis revealed the presence of biologically relevant variants that correlate with the observed association signals. While the findings generated here warrant independent validation, the results of our large study suggest that ATM may be a novel locus associated with the risk of multiple subtypes of NHL.

LoQAtE--Localization and Quantitation ATlas of the yeast proteomE. A new tool for multiparametric dissection of single-protein behavior in response to biological perturbations in yeast

Living organisms change their proteome dramatically to sustain a stable internal milieu in fluctuating environments. To study the dynamics of proteins during stress, we measured the localization and abundance of the Saccharomyces cerevisiae proteome under various growth conditions and genetic backgrounds using the GFP collection. We created a database (DB) called ‘LoQAtE’ (Localizaiton and Quantitation Atlas of the yeast proteomE), available online at http://www.weizmann.ac.il/molgen/loqate/, to provide easy access to these data. Using LoQAtE DB, users can get a profile of changes for proteins of interest as well as querying advanced intersections by either abundance changes, primary localization or localization shifts over the tested conditions. Currently, the DB hosts information on 5330 yeast proteins under three external perturbations (DTT, H₂O₂ and nitrogen starvation) and two genetic mutations [in the chaperonin containing TCP1 (CCT) complex and in the proteasome]. Additional conditions will be uploaded regularly. The data demonstrate hundreds of localization and abundance changes, many of which were not detected at the level of mRNA. LoQAtE is designed to allow easy navigation for non-experts in high-content microscopy and data are available for download. These data should open up new perspectives on the significant role of proteins while combating external and internal fluctuations.

Lipid droplets and peroxisomes: key players in cellular lipid homeostasis or a matter of fat--store 'em up or burn 'em down

Lipid droplets (LDs) and peroxisomes are central players in cellular lipid homeostasis: some of their main functions are to control the metabolic flux and availability of fatty acids (LDs and peroxisomes) as well as of sterols (LDs). Both fatty acids and sterols serve multiple functions in the cell—as membrane stabilizers affecting membrane fluidity, as crucial structural elements of membrane-forming phospholipids and sphingolipids, as protein modifiers and signaling molecules, and last but not least, as a rich carbon and energy source. In addition, peroxisomes harbor enzymes of the malic acid shunt, which is indispensable to regenerate oxaloacetate for gluconeogenesis, thus allowing yeast cells to generate sugars from fatty acids or nonfermentable carbon sources. Therefore, failure of LD and peroxisome biogenesis and function are likely to lead to deregulated lipid fluxes and disrupted energy homeostasis with detrimental consequences for the cell. These pathological consequences of LD and peroxisome failure have indeed sparked great biomedical interest in understanding the biogenesis of these organelles, their functional roles in lipid homeostasis, interaction with cellular metabolism and other organelles, as well as their regulation, turnover, and inheritance. These questions are particularly burning in view of the pandemic development of lipid-associated disorders worldwide.

Comparison of parameter-adapted segmentation methods for fluorescence micrographs

Interpreting images from fluorescence microscopy is often a time-consuming task with poor reproducibility. Various image processing routines that can help investigators evaluate the images are therefore useful. The critical aspect for a reliable automatic image analysis system is a robust segmentation algorithm that can perform accurate segmentation for different cell types. In this study, several image segmentation methods were therefore compared and evaluated in order to identify the most appropriate segmentation schemes that are usable with little new parameterization and robustly with different types of fluorescence-stained cells for various biological and biomedical tasks. The study investigated, compared, and enhanced four different methods for segmentation of cultured epithelial cells. The maximum-intensity linking (MIL) method, an improved MIL, a watershed method, and an improved watershed method based on morphological reconstruction were used. Three manually annotated datasets consisting of 261, 817, and 1,333 HeLa or L929 cells were used to compare the different algorithms. The comparisons and evaluations showed that the segmentation performance of methods based on the watershed transform was significantly superior to the performance of the MIL method. The results also indicate that using morphological opening by reconstruction can improve the segmentation of cells stained with a marker that exhibits the dotted surface of cells.

Fifteen years of large scale metabolic modeling of yeast: developments and impacts

Since the first large-scale reconstruction of the Saccharomyces cerevisiae metabolic network 15 years ago the development of yeast metabolic models has progressed rapidly, resulting in no less than nine different yeast genome-scale metabolic models. Here we review the historical development of large-scale mathematical modeling of yeast metabolism and the growing scope and impact of applications of these models in four different areas: as guide for metabolic engineering and strain improvement, as a tool for biological interpretation and discovery, applications of novel computational framework and for evolutionary studies.

Identification of Yju3p as functional orthologue of mammalian monoglyceride lipase in the yeast Saccharomycescerevisiae

Monoacylglycerols (MAGs) are short-lived intermediates of glycerolipid metabolism. Specific molecular species, such as 2-arachidonoylglycerol, which is a potent activator of cannabinoid receptors, may also function as lipid signaling molecules. In mammals, enzymes hydrolyzing MAG to glycerol and fatty acids, resembling the final step in lipolysis, or esterifying MAG to diacylglycerol, are well known; however, despite the high level of conservation of lipolysis, the corresponding activities in yeast have not been characterized yet. Here we provide evidence that the protein Yju3p functions as a potent MAG hydrolase in yeast. Cellular MAG hydrolase activity was decreased by more than 90% in extracts of Yju3p-deficient cells, indicating that Yju3p accounts for the vast majority of this activity in yeast. Loss of this activity was restored by heterologous expression of murine monoglyceride lipase (MGL). Since yju3Δ mutants accumulated MAG in vivo only at very low concentrations, we considered the possibility that MAGs are re-esterified into DAG by acyltransferases. Indeed, cellular MAG levels were further increased in mutant cells lacking Yju3p and Dga1p or Lro1p acyltransferase activities. In conclusion, our studies suggest that catabolic and anabolic reactions affect cellular MAG levels. Yju3p is the functional orthologue of mammalian MGL and is required for efficient degradation of MAG in yeast.

Reversible acetylation of PGC-1: connecting energy sensors and effectors to guarantee metabolic flexibility

Organisms adapt their metabolism to meet ever changing environmental conditions. This metabolic adaptation involves at a cellular level the fine tuning of mitochondrial function, which is mainly under the control of the transcriptional co-activator proliferator-activated receptor gamma co-activator (PGC)-1alpha. Changes in PGC-1alpha activity coordinate a transcriptional response, which boosts mitochondrial activity in times of energy needs and attenuates it when energy demands are low. Reversible acetylation has emerged as a key way to alter PGC-1alpha activity. Although it is well established that PGC-1alpha is deacetylated and activated by Sirt1 and acetylated and inhibited by GCN5, less is known regarding how these enzymes themselves are regulated. Recently, it became clear that the energy sensor, AMP-activated kinase (AMPK) translates the effects of energy stress into altered Sirt1 activity by regulating the intracellular level of its co-substrate nicotinamide adenine dinucleotide (NAD)(+). Conversely, the enzyme ATP citrate lyase (ACL), relates energy balance to GCN5, through the control of the nuclear production of acetyl-CoA, the substrate for GCN5's acetyltransferase activity. We review here how these metabolic signaling pathways, affecting GCN5 and Sirt1 activity, allow the reversible acetylation-deacetylation of PGC-1alpha and the adaptation of mitochondrial energy homeostasis to energy levels.

The Yeast Resource Center Public Image Repository: A large database of fluorescence microscopy images

Background

There is increasing interest in the development of computational methods to analyze fluorescent microscopy images and enable automated large-scale analysis of the subcellular localization of proteins. Determining the subcellular localization is an integral part of identifying a protein's function, and the application of bioinformatics to this problem provides a valuable tool for the annotation of proteomes. Training and validating algorithms used in image analysis research typically rely on large sets of image data, and would benefit from a large, well-annotated and highly-available database of images and associated metadata.

Description

The Yeast Resource Center Public Image Repository (YRC PIR) is a large database of images depicting the subcellular localization and colocalization of proteins. Designed especially for computational biologists who need large numbers of images, the YRC PIR contains 532,182 TIFF images from nearly 85,000 separate experiments and their associated experimental data. All images and associated data are searchable, and the results browsable, through an intuitive web interface. Search results, experiments, individual images or the entire dataset may be downloaded as standards-compliant OME-TIFF data.

Conclusions

The YRC PIR is a powerful resource for researchers to find, view, and download many images and associated metadata depicting the subcellular localization and colocalization of proteins, or classes of proteins, in a standards-compliant format. The YRC PIR is freely available at http://images.yeastrc.org/.

Farnesylation of pex19p is required for its structural integrity and function in peroxisome biogenesis

The conserved CaaX box peroxin Pex19p is known to be modified by farnesylation. The possible involvement of this lipid modification in peroxisome biogenesis, the degree to which Pex19p is farnesylated, and its molecular function are unknown or controversial. We resolve these issues by first showing that the complete pool of Pex19p is processed by farnesyltransferase in vivo and that this modification is independent of peroxisome induction or the Pex19p membrane anchor Pex3p. Furthermore, genomic mutations of PEX19 prove that farnesylation is essential for proper matrix protein import into peroxisomes, which is supposed to be caused indirectly by a defect in peroxisomal membrane protein (PMP) targeting or stability. This assumption is corroborated by the observation that mutants defective in Pex19p farnesylation are characterized by a significantly reduced steady-state concentration of prominent PMPs (Pex11p, Ant1p) but also of essential components of the peroxisomal import machinery, especially the RING peroxins, which were almost depleted from the importomer. In vivo and in vitro, PMP recognition is only efficient when Pex19p is farnesylated with affinities differing by a factor of 10 between the non-modified and wild-type forms of Pex19p. Farnesylation is likely to induce a conformational change in Pex19p. Thus, isoprenylation of Pex19p contributes to substrate membrane protein recognition for the topogenesis of PMPs, and our results highlight the importance of lipid modifications in protein-protein interactions.

Imaging-based live cell yeast screen identifies novel factors involved in peroxisome assembly

We describe an imaging-based method in intact cells to systematically screen yeast mutant libraries for abnormal morphology and distribution of fluorescently labeled subcellular structures. In this study, chromosomally expressed green fluorescent protein (GFP) fused to the peroxisomal targeting sequence 1, consisting of serine-lysine-leucine, was introduced into 4740 viable yeast deletion mutants using a modified synthetic genetic array (SGA) technology. A benchtop robot was used to create ordered high-density arrays of GFP-expressing yeast mutants on solid media plates. Immobilized live yeast colonies were subjected to high-resolution, multidimensional confocal imaging. A software tool was designed for automated processing and quantitative analysis of acquired multichannel three-dimensional image data. The study resulted in the identification of two novel proteins, as well as of all previously known proteins required for import of proteins bearing peroxisomal targeting signal PTS1, into yeast peroxisomes. The modular method enables reliable microscopic analysis of live yeast mutant libraries in a universally applicable format on standard microscope slides, and provides a step toward fully automated high-resolution imaging of intact yeast cells.

The WASP homologue Las17 activates the novel actin-regulatory activity of Ysc84 to promote endocytosis in yeast

Actin plays an essential role in many eukaryotic cellular processes, including motility, generation of polarity, and membrane trafficking. Actin function in these roles is regulated by association with proteins that affect its polymerization state, dynamics, and organization. Numerous proteins have been shown to localize with cortical patches of yeast actin during endocytosis, but the role of many of these proteins remains poorly understood. Here, we reveal that the yeast protein Ysc84 represents a new class of actin-binding proteins, conserved from yeast to humans. It contains a novel N-terminal actin-binding domain termed Ysc84 actin binding (YAB), which can bind and bundle actin filaments. Intriguingly, full-length Ysc84 alone does not bind to actin, but binding can be activated by a specific motif within the polyproline region of the yeast WASP homologue Las17. We also identify a new monomeric actin-binding site on Las17. Together, the polyproline region of Las17 and Ysc84 can promote actin polymerization. Using live cell imaging, kinetics of assembly and disassembly of proteins at the endocytic site were analyzed and reveal that loss of Ysc84 and its homologue Lsb3 decrease inward movement of vesicles consistent with a role in actin polymerization during endocytosis.

The fidgety yeast: focus on high-resolution live yeast cell microscopy

Despite its small size of 5-8 mum - only one order of magnitude above the wavelength of visible light - yeast has developed into an attractive system for light microscopic analysis. First, the ease of genetic manipulation and integrative transformation have opened numerous experimental strategies for genome-wide tagging approaches, e.g., with fluorescent proteins (as discussed in several chapters of this issue). Second, the large number of cells that can be simultaneously visualized provides an excellent basis for statistical image analysis, resulting in reliable morphological or localization information. Third, the flexibility of yeast cultivation in terms of biochemical manipulation, rapid cellular growth, mutant isolation or drug susceptibility offers an unprecedented spectrum of possibilities for in vivo functional studies, and analysis of cellular dynamics and organelle inheritance. Although yeast in itself is an interesting cellular system, its "prototype character" in understanding cellular metabolism, physiology, and signaling in eukaryotes accounts for its popular use in technology development and biomedical research.Here we discuss experimental strategies for live yeast cell imaging, geared towards imaging-based large-scale screens. Major emphasis is on the methods for immobilizing cells under "physiological" conditions, with minimum impact on yeast. We also point out potential pitfalls resulting from live cell imaging that once again stresses the necessity for extremely careful experimental design and interpretation of data resulting from imaging experiments. It goes without saying that these problems are not restricted to yeast and are also highly relevant to "large" cells. If an image tells more than a thousand (perhaps misleading?) words, the ease of obtaining "images" thus rather suggests analyzing many thousands of images, to come up with one relevant and biologically significant conclusion.

The unfolded protein response transducer Ire1p contains a nuclear localization sequence recognized by multiple beta importins

The Ire1p transmembrane receptor kinase/endonuclease transduces the unfolded protein response (UPR) from the endoplasmic reticulum (ER) to the nucleus in Saccharomyces cerevisiae. In this study, we analyzed the capacity of a highly basic sequence in the linker region of Ire1p to function as a nuclear localization sequence (NLS) both in vivo and in vitro. This 18-residue sequence is capable of targeting green fluorescent protein to the nucleus of yeast cells in a process requiring proteins involved in the Ran GTPase cycle that facilitates nuclear import. Mutagenic analysis and importin binding studies demonstrate that the Ire1p linker region contains overlapping potential NLSs: at least one classical NLS (within sequences 642KKKRKR647 and/or 653KKGR656) that is recognized by yeast importin alpha (Kap60p) and a novel betaNLS (646KRGSRGGKKGRK657) that is recognized by several yeast importin beta homologues. Kinetic binding data suggest that binding to importin beta proteins would predominate in vivo. The UPR, and in particular ER stress-induced HAC1 mRNA splicing, is inhibited by point mutations in the Ire1p NLS that inhibit nuclear localization and also requires functional RanGAP and Ran GEF proteins. The NLS-dependent nuclear localization of Ire1p would thus seem to be central to its role in UPR signaling.

Nucleocytosolic acetyl-coenzyme a synthetase is required for histone acetylation and global transcription

Metabolic enzymes rarely regulate informational processes like gene expression. Yeast acetyl-CoA synthetases (Acs1p and 2p) are exceptional, as they are important not only for carbon metabolism but also are shown here to supply the acetyl-CoA for histone acetylation by histone acetyltransferases (HATs). acs2-Ts mutants exhibit global histone deacetylation, transcriptional defects, and synthetic growth defects with HAT mutants at high temperatures. In glycerol with ethanol, Acs1p is an alternate acetyl-CoA source for HATs. Rapid deacetylation after Acs2p inactivation suggests nuclear acetyl-CoA synthesis is rate limiting for histone acetylation. Different histone lysines exhibit distinct deacetylation rates, with N-terminal tail lysines deacetylated rapidly and H3 lysine 56 slowly. Yeast mitochondrial and nucleocytosolic acetyl-CoA pools are biochemically isolated. Thus, acetyl-CoA metabolism is directly linked to chromatin regulation and may affect diverse cellular processes in which acetylation and metabolism intersect, such as disease states and aging.

Yeast acyl-CoA synthetases at the crossroads of fatty acid metabolism and regulation

Acyl-CoA synthetases (ACSs) are a family of enzymes that catalyze the thioesterification of fatty acids with coenzymeA to form activated intermediates, which play a fundamental role in lipid metabolism and homeostasis of lipid-related processes. The products of the ACS enzyme reaction, acyl-CoAs, are required for complex lipid synthesis, energy production via beta-oxidation, protein acylation and fatty-acid dependent transcriptional regulation. ACS enzymes are also necessary for fatty acid import into cells by the process of vectorial acylation. The yeast Saccharomyces cerevisiae has four long chain ACS enzymes designated Faa1p through Faa4p, one very long chain ACS named Fat1p and one ACS, Fat2p, for which substrate specificity has not been defined. Pivotal roles have been defined for Faa1p and Faa4p in fatty acid import, beta-oxidation and transcriptional control mediated by the transcription factors Oaf1p/Pip2p and Mga2p/Spt23p. Fat1p is a bifunctional protein required for fatty acid transport of long chain fatty acids, as well as activation of very long chain fatty acids. This review focuses on the various roles yeast ACS enzymes play in cellular metabolism targeting especially the functions of specific isoforms in fatty acid transport, metabolism and energy production. We will also present evidence from directed experimentation, as well as information obtained by mining the molecular biological databases suggesting the long chain ACS enzymes are required in protein acylation, vesicular trafficking, signal transduction pathways and cell wall synthesis.

Obese Yeast: Triglyceride Lipolysis Is Functionally Conserved from Mammals to Yeast

Storage and degradation of triglycerides are essential processes to ensure energy homeostasis and availability of precursors for membrane lipid synthesis. Recent evidence suggests that an emerging class of enzymes containing a conserved patatin domain are centrally important players in lipid degradation. Here we describe the identification and characterization of a major triglyceride lipase of the adipose triglyceride lipase/Brummer family, Tgl4, in the yeast Saccharomyces cerevisiae. Elimination of Tgl4 in a tgl3 background led to fat yeast, rendering growing cells unable to degrade triglycerides. Tgl4 and Tgl3 lipases localized to lipid droplets, independent of each other. Serine 315 in the GXSXG lipase active site consensus sequence of the patatin domain of Tgl4 is essential for catalytic activity. Mouse adipose triglyceride lipase (which also contains a patatin domain but is otherwise highly divergent in primary structure from any yeast protein) localized to lipid droplets when expressed in yeast, and significantly restored triglyceride breakdown in tgl4 mutants in vivo. Our data identify yeast Tgl4 as a functional ortholog of mammalian adipose triglyceride lipase.

The spatial organization of lipid synthesis in the yeast Saccharomyces cerevisiae derived from large scale green fluorescent protein tagging and high resolution microscopy

The localization pattern of proteins involved in lipid metabolism in the yeast Saccharomyces cerevisiae was determined using C-terminal green fluorescent protein tagging and high resolution confocal laser scanning microscopy. A list of 493 candidate proteins ( approximately 9% of the yeast proteome) was assembled based on proteins of known function in lipid metabolism, their interacting proteins, proteins defined by genetic interactions, and regulatory factors acting on selected genes or proteins. Overall 400 (81%) transformants yielded a positive green fluorescent protein signal, and of these, 248 (62% of the 400) displayed a localization pattern that was not cytosolic. Observations for many proteins with known localization patterns were consistent with published data derived from cell fractionation or large scale localization approaches. However, in many cases, high resolution microscopy provided additional information that indicated that proteins distributed to multiple subcellular locations. The majority of tagged enzymes localized to the endoplasmic reticulum (91), but others localized to mitochondria (27), peroxisomes (17), lipid droplets (23), and vesicles (53). We assembled enzyme localization patterns for phospholipid, sterol, and sphingolipid biosynthetic pathways and propose a model, based on enzyme localization, for concerted regulation of sterol and sphingolipid metabolism that involves shuttling of key enzymes between endoplasmic reticulum, lipid droplets, vesicles, and Golgi.