Systematic screens for human disease genes, from yeast to human and back

The expression system influences stability, maturation efficiency, and oligomeric properties of the potassium-chloride co-transporter KCC2

The neuron-specific K+/Cl- co-transporter 2, KCC2, which is critical for brain development, regulates γ-aminobutyric acid-dependent inhibitory neurotransmission. Consistent with its function, mutations in KCC2 are linked to neurodevelopmental disorders, including epilepsy, schizophrenia, and autism. KCC2 possesses 12 transmembrane spans and forms an intertwined dimer. Based on its complex architecture and function, reduced cell surface expression and/or activity have been reported when select disease-associated mutations are present in the gene encoding the protein, SLC12A5. These data suggest that KCC2 might be inherently unstable, as seen for other complex polytopic ion channels, thus making it susceptible to cellular quality control pathways that degrade misfolded proteins. To test these hypotheses, we examined KCC2 stability and/or maturation in five model systems: yeast, HEK293 cells, primary rat neurons, and rat and human brain synaptosomes. Although studies in yeast revealed that KCC2 is selected for endoplasmic reticulum-associated degradation (ERAD), experiments in HEK293 cells supported a more subtle role for ERAD in maintaining steady-state levels of KCC2. Nevertheless, this system allowed for an analysis of KCC2 glycosylation in the ER and Golgi, which serves as a read-out for transport through the secretory pathway. In turn, KCC2 was remarkably stable in primary rat neurons, suggesting that KCC2 folds efficiently in more native systems. Consistent with these data, the mature glycosylated form of KCC2 was abundant in primary rat neurons as well as in rat and human brain. Together, this work details the first insights into the influence that the cellular and membrane environments have on several fundamental KCC2 properties, acknowledges the advantages and disadvantages of each system, and helps set the stage for future experiments to assess KCC2 in a normal or disease setting.

The power of weak, transient interactions across biology: A paradigm of emergent behavior

A growing list of diverse biological systems and their equally diverse functionalities provides realizations of a paradigm of emergent behavior. In each of these biological systems, pervasive ensembles of weak, short-lived, spatially local interactions act autonomously to convey functionalities at larger spatial and temporal scales. In this article, a range of diverse systems and functionalities are presented in a cursory manner with literature citations for further details. Then two systems and their properties are discussed in more detail: yeast chromosome biology and human respiratory mucus.

Cytotoxicity of Extracts from Petiveria alliacea Leaves on Yeast

Petiveria alliacea L. is a plant used in traditional medicine harboring pharmacological properties with anti-inflammatory, antinociceptive, hypoglycemiant and anesthetic activities. This study assessed the potential cytotoxic, genotoxic and mutagenic effects of ethanolic extract of P. alliacea on Saccharomyces cerevisiae strains. S. cerevisiae FF18733 (wild type) and CD138 (ogg1) strains were exposed to fractioned ethanolic extracts of P. alliacea in different concentrations. Three experimental assays were performed: cellular inactivation, mutagenesis (canavanine resistance system) and loss of mitochondrial function (petites colonies). The chemical analyses revealed a rich extract with phenolic compounds such as protocatechuic acid, cinnamic and catechin epicatechin. A decreased cell viability in wild-type and ogg1 strains was demonstrated. All fractions of the extract exerted a mutagenic effect on the ogg1 strain. Only ethyl acetate and n-butanol fractions increased the rate of petites colonies in the ogg1 strain, but not in the wild-type strain. The results indicate that fractions of mid-polarity of the ethanolic extract, at the studied concentrations, can induce mutagenicity mediated by oxidative lesions in the mitochondrial and genomic genomes of the ogg1-deficient S. cerevisiae strain. These findings indicate that the lesions caused by the fractions of P. alliacea ethanolic extract can be mediated by reactive oxygen species and can reach multiple molecular targets to exert their toxicity.

Benzylic Dehydroxylation of Echinocandin Antifungal Drugs Restores Efficacy against Resistance Conferred by Mutated Glucan Synthase

Each year, infections caused by fungal pathogens claim the lives of about 1.6 million people and affect the health of over a billion people worldwide. Among the most recently developed antifungal drugs are the echinocandins, which noncompetitively inhibit β-glucan synthase, a membrane-bound protein complex that catalyzes the formation of the main polysaccharide component of the fungal cell wall. Resistance to echinocandins is conferred by mutations in FKS genes, which encode the catalytic subunit of the β-glucan synthase complex. Here, we report that selective removal of the benzylic alcohol of the nonproteinogenic amino acid 3S,4S-dihydroxy-l-homotyrosine of the echinocandins anidulafungin and rezafungin, restored their efficacy against a large panel of echinocandin-resistant Candida strains. The dehydroxylated compounds did not significantly affect the viability of human-derived cell culture lines. An analysis of the efficacy of the dehydroxylated echinocandins against resistant Candida strains, which contain mutations in the FKS1 and/or FKS2 genes of the parental strains, identified amino acids of the Fks proteins that are likely to reside in proximity to the l-homotyrosine residue of the bound drug. This study describes the first example of a chemical modification strategy to restore the efficacy of echinocandin drugs, which have a critical place in the arsenal of antifungal drugs, against resistant fungal pathogens.

Fluconazole-COX Inhibitor Hybrids: A Dual-Acting Class of Antifungal Azoles

When used in combination with azole antifungal drugs, cyclooxygenase (COX) inhibitors such as ibuprofen improve antifungal efficacy. We report the conjugation of a chiral antifungal azole pharmacophore to COX inhibitors and the evaluation of activity of 24 hybrids. Hybrids derived from ibuprofen and flurbiprofen were considerably more potent than fluconazole and comparable to voriconazole against a panel of Candida species. The potencies of hybrids composed of an S-configured azole pharmacophore were higher than those with an R-configured pharmacophore. Tolerance, defined as the ability of a subpopulation of cells to grow in the presence of the drug, to the hybrids was lower than to fluconazole and voriconazole. The hybrids were active against a mutant lacking CYP51, the target of azole drugs, indicating that these agents act via a dual mode of action. This study established that azole-COX inhibitor hybrids are a novel class of potent antifungals with clinical potential.

Towards a systems-level understanding of mitochondrial biology

Human mitochondria are complex and highly dynamic biological systems, comprised of over a thousand parts and evolved to fully integrate into the specialized intracellular signaling networks and metabolic requirements of each cell and organ. Over the last two decades, several complementary, top-down computational and experimental approaches have been developed to identify, characterize and modulate the human mitochondrial system, demonstrating the power of integrating classical reductionist and discovery-driven analyses in order to de-orphanize hitherto unknown molecular components of mitochondrial machineries and pathways. To this goal, systematic, multiomics-based surveys of proteome composition, protein networks, and phenotype-to-pathway associations at the tissue, cell and organellar level have been largely exploited to predict the full complement of mitochondrial proteins and their functional interactions, therefore catalyzing data-driven hypotheses. Collectively, these multidisciplinary and integrative research approaches hold the potential to propel our understanding of mitochondrial biology and provide a systems-level framework to unraveling mitochondria-mediated and disease-spanning pathomechanisms.

Overexpression of the peroxin Pex34p suppresses impaired acetate utilization in yeast lacking the mitochondrial aspartate/glutamate carrier Agc1p

PEX34, encoding a peroxisomal protein implicated in regulating peroxisome numbers, was identified as a high copy suppressor, capable of bypassing impaired acetate utilization of agc1∆ yeast. However, improved growth of agc1∆ yeast on acetate is not mediated through peroxisome proliferation. Instead, stress to the endoplasmic reticulum and mitochondria from PEX34 overexpression appears to contribute to enhanced acetate utilization of agc1∆ yeast. The citrate/2-oxoglutarate carrier Yhm2p is required for PEX34 stimulated growth of agc1∆ yeast on acetate medium, suggesting that the suppressor effect is mediated through increased activity of a redox shuttle involving mitochondrial citrate export. Metabolomic analysis also revealed redirection of acetyl-coenzyme A (CoA) from synthetic reactions for amino acids in PEX34 overexpressing yeast. We propose a model in which increased formation of products from the glyoxylate shunt, together with enhanced utilization of acetyl-CoA, promotes the activity of an alternative mitochondrial redox shuttle, partially substituting for loss of yeast AGC1.

Yeast as a Tool for Deeper Understanding of Human Manganese-Related Diseases

The biological importance of manganese lies in its function as a key cofactor for numerous metalloenzymes and as non-enzymatic antioxidant. Due to these two essential roles, it appears evident that disturbed manganese homeostasis may trigger the development of pathologies in humans. In this context, yeast has been extensively used over the last decades to gain insight into how cells regulate intra-organellar manganese concentrations and how human pathologies may be related to disturbed cellular manganese homeostasis. This review first summarizes how manganese homeostasis is controlled in yeast cells and how this knowledge can be extrapolated to human cells. Several manganese-related pathologies whose molecular mechanisms have been studied in yeast are then presented in the light of the function of this cation as a non-enzymatic antioxidant or as a key cofactor of metalloenzymes. In this line, we first describe the Transmembrane protein 165-Congenital Disorder of Glycosylation (TMEM165-CDG) and Friedreich ataxia pathologies. Then, due to the established connection between manganese cations and neurodegeneration, the Kufor–Rakeb syndrome and prion-related diseases are finally presented.

Next-Generation Genome-Scale Models Incorporating Multilevel 'Omics Data: From Yeast to Human

Genome-scale modelling in eukaryotes has been pioneered by the yeast Saccharomyces cerevisiae. Early metabolic networks have been reconstructed based on genome sequence and information accumulated in the literature on biochemical reactions. Protein-protein interaction networks have been constructed based on experimental observations such as yeast-2-hybrid method. Gene regulatory networks were based on a variety of data types, including information on TF-promoter binding and gene coexpression. The aforementioned networks have been improved gradually, and methods for their integration were developed. Incorporation of omics data including genomics, metabolomics, transcriptomics, fluxome, and phosphoproteome led to next-generation genome-scale models. The methods tested on yeast have later been implemented in human, further, cellular components found to be important in yeast physiology under (ab)normal conditions, and (dis)regulation mechanisms in yeast shed light to the healthy and disease states in human. This chapter provides a historical perspective on next-generation genome-scale models incorporating multilevel 'omics data, from yeast to human.

Identification of putative non-host essential genes and novel drug targets against Acinetobacter baumannii by in silico comparative genome analysis

Acinetobacter baumannii, the gram-negative bacteria emerged as an extremely critical pathogen causing nosocomial and different kinds of infections. A. baumannii exhibit resistivity towards various classes of antibiotics that shows that there is a dire need to search more drug targets by exploiting the full genome of the bacteria. In doing so, a strategy is made with the combination of computational biology, pathogen informatics and cheminformatics. Comparative genomics analysis, modeling and docking studies have been performed for the prediction of non-host essential genes and novel drug candidates against A. baumannii. Among 37 unique and 82 common metabolic pathways, 92 genes were predicted as non-host genes. Similarly, using homology search between A. baumannii genome and essential genes of different bacteria, 293 genes were predicted as essential genes of A. baumannii. Among these predicted non-host and essential genes, 86 genes were predicted as non-host essential genes which could serve as potential novel drug and vaccine targets. Additional drug-target like physicochemical properties were estimated such as the molecular weight, subcellular localization and druggability potential. On the structural part, the crystal structures of all the non-host essential genes of A. baumannii were found except the three genes. Out of these three, a homology model of Undecaprenyl-diphosphatase was built using a PDB template by MODELLER [version 9.18]. The quality of the model was assessed by the ProSA and RAMPAGE. The built model was subjected as a receptor for the molecular docking with Adenosine diphosphate (ADP) as a ligand. The molecular docking was performed by AutoDock4 and the best conformation with lowest binding energy (-4.39 kcal/mol) was obtained. The LigPlot was used to identify the close interactions between the ligand the receptor's residues. This study will further aid for the selection of putative inhibitors against a novel drug target identified against A. baumannii and hence could lead to the better therapeutics.

Coupling of Human Rhodopsin to a Yeast Signaling Pathway Enables Characterization of Mutations Associated with Retinal Disease

G protein-coupled receptors (GPCRs) are crucial sensors of extracellular signals in eukaryotes, with multiple GPCR mutations linked to human diseases. With the growing number of sequenced human genomes, determining the pathogenicity of a mutation is challenging, but can be aided by a direct measurement of GPCR-mediated signaling. This is particularly difficult for the visual pigment rhodopsin-a GPCR activated by light-for which hundreds of mutations have been linked to inherited degenerative retinal diseases such as retinitis pigmentosa. In this study, we successfully engineered, for the first time, activation by human rhodopsin of the yeast mating pathway, resulting in signaling via a fluorescent reporter. We combine this novel assay for rhodopsin light-dependent activation with studies of subcellular localization, and the upregulation of the unfolded protein response in response to misfolded rhodopsin protein. We use these assays to characterize a panel of rhodopsin mutations with known molecular phenotypes, finding that rhodopsin maintains a similar molecular phenotype in yeast, with some interesting differences. Furthermore, we compare our assays in yeast with clinical phenotypes from patients with novel disease-linked mutations. We demonstrate that our engineered yeast strain can be useful in rhodopsin mutant classification, and in helping to determine the molecular mechanisms underlying their pathogenicity. This approach may also be applied to better understand the clinical relevance of other human GPCR mutations, furthering the use of yeast as a tool for investigating molecular mechanisms relevant to human disease.

Mitochondrial Genome Variation Affects Multiple Respiration and Nonrespiration Phenotypes in Saccharomyces cerevisiae

Mitochondrial genome variation and its effects on phenotypes have been widely analyzed in higher eukaryotes but less so in the model eukaryote Saccharomyces cerevisiae Here, we describe mitochondrial genome variation in 96 diverse S. cerevisiae strains and assess associations between mitochondrial genotype and phenotypes as well as nuclear-mitochondrial epistasis. We associate sensitivity to the ATP synthase inhibitor oligomycin with SNPs in the mitochondrially encoded ATP6 gene. We describe the use of iso-nuclear F1 pairs, the mitochondrial genome equivalent of reciprocal hemizygosity analysis, to identify and analyze mitochondrial genotype-dependent phenotypes. Using iso-nuclear F1 pairs, we analyze the oligomycin phenotype-ATP6 association and find extensive nuclear-mitochondrial epistasis. Similarly, in iso-nuclear F1 pairs, we identify many additional mitochondrial genotype-dependent respiration phenotypes, for which there was no association in the 96 strains, and again find extensive nuclear-mitochondrial epistasis that likely contributes to the lack of association in the 96 strains. Finally, in iso-nuclear F1 pairs, we identify novel mitochondrial genotype-dependent nonrespiration phenotypes: resistance to cycloheximide, ketoconazole, and copper. We discuss potential mechanisms and the implications of mitochondrial genotype and of nuclear-mitochondrial epistasis effects on respiratory and nonrespiratory quantitative traits.

Yeast-Based Screen to Identify Natural Compounds with a Potential Therapeutic Effect in Hailey-Hailey Disease

The term orthodisease defines human disorders in which the pathogenic gene has orthologs in model organism genomes. Yeasts have been instrumental for gaining insights into the molecular basis of many human disorders, particularly those resulting from impaired cellular metabolism. We and others have used yeasts as a model system to study the molecular basis of Hailey-Hailey disease (HHD), a human blistering skin disorder caused by haploinsufficiency of the gene ATP2C1 the orthologous of the yeast gene PMR1. We observed that K. lactis cells defective for PMR1 gene share several biological similarities with HHD derived keratinocytes. Based on the conservation of ATP2C1/PMR1 function from yeast to human, here we used a yeast-based assay to screen for molecules able to influence the pleiotropy associated with PMR1 deletion. We identified six compounds, Kaempferol, Indirubin, Lappaconite, Cyclocytidine, Azomycin and Nalidixic Acid that induced different major shape phenotypes in K. lactis. These include mitochondrial and the cell-wall morphology-related phenotypes. Interestingly, a secondary assay in mammalian cells confirmed activity for Kaempferol. Indeed, this compound was also active on human keratinocytes depleted of ATP2C1 function by siRNA-treatment used as an in-vitro model of HHD. We found that Kaempferol was a potent NRF2 regulator, strongly inducing its expression and its downstream target NQO1. In addition, Kaempferol could decrease oxidative stress of ATP2C1 defective keratinocytes, characterized by reduced NRF2-expression. Our results indicated that the activation of these pathways might provide protection to the HHD-skin cells. As oxidative stress plays pivotal roles in promoting the skin lesions of Hailey-Hailey, the NRF2 pathway could be a viable therapeutic target for HHD.

Bifurcations and limit cycles in cytosolic yeast calcium

Calcium homeostasis is a fundamental cellular process in yeast. The regulation of the cytosolic calcium concentration is required for volume preservation and to regulate many vital calcium dependent processes such as mating and response to stress. The homeostatic mechanism is often studied by applying calcium pulses: sharply changing the calcium concentration in the yeast environment and observing the cellular response. To address these experimental investigations, several mathematical models have been proposed to describe this response. In this article we demonstrate that a previously studied model for this response predicts the presence of limit point instabilities and limit cycles in the dynamics of the calcium homeostasis system. We discuss the ways in which such dynamic characteristics can be observed with luminometric techniques. We contrast these predictions with experimentally observed responses and find that the experiments reveal a number of features that are consistent with modeling predictions. In particular, we find that equilibrium cytosolic concentrations have a sharp change in behavior as pulse size changes in the micromolar range. We show that such change is consistent with the presence of limit point instabilities. Additionally, we find that the response of synchronized yeast cells to millimolar range pulses is non-monotonic in its late stages. This response has characteristics similar to those associated with limit cycles.

Scope and limitations of yeast as a model organism for studying human tissue-specific pathways

Background

Budding yeast, S. cerevisiae, has been used extensively as a model organism for studying cellular processes in evolutionarily distant species, including humans. However, different human tissues, while inheriting a similar genetic code, exhibit distinct anatomical and physiological properties. Specific biochemical processes and associated biomolecules that differentiate various tissues are not completely understood, neither is the extent to which a unicellular organism, such as yeast, can be used to model these processes within each tissue.

Results

We present a novel framework to systematically quantify the suitability of yeast as a model organism for different human tissues. To this end, we develop a computational method for dissecting the global human interactome into tissue-specific cellular networks. By individually aligning these networks with the yeast interactome, we simultaneously partition the functional space of human genes, and their corresponding pathways, based on their conservation both across species and among different tissues. Finally, we couple our framework with a novel statistical model to assess the conservation of tissue-specific pathways and infer the overall similarity of each tissue with yeast. We further study each of these subspaces in detail, and shed light on their unique biological roles in the human tissues.

Conclusions

Our framework provides a novel tool that can be used to assess the suitability of the yeast model for studying tissue-specific physiology and pathophysiology in humans. Many complex disorders are driven by a coupling of housekeeping (universally expressed in all tissues) and tissue-selective (expressed only in specific tissues) dysregulated pathways. While tissue-selective genes are significantly associated with the onset and development of a number of tissue-specific pathologies, we show that the human-specific subset has even higher association. Consequently, they provide excellent candidates as drug targets for therapeutic interventions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0253-0) contains supplementary material, which is available to authorized users.

Influence of Ogg1 repair on the genetic stability of ccc2 mutant of Saccharomyces cerevisiae chemically challenged with 4-nitroquinoline-1-oxide (4-NQO)

In Saccharomyces cerevisiae, disruption of genes by deletion allowed elucidation of the molecular mechanisms of a series of human diseases, such as in Wilson disease (WD). WD is a disorder of copper metabolism, due to inherited mutations in human copper-transporting ATPase (ATP7B). An orthologous gene is present in S. cerevisiae, CCC2 gene. Copper is required as a cofactor for a number of enzymes. In excess, however, it is toxic, potentially carcinogenic, leading to many pathological conditions via oxidatively generated DNA damage. Deficiency in ATP7B (human) or Ccc2 (yeast) causes accumulation of intracellular copper, favouring the generation of reactive oxygen species. Thus, it becomes important to study the relative importance of proteins involved in the repair of these lesions, such as Ogg1. Herein, we addressed the influence Ogg1 repair in a ccc2 deficient strain of S. cerevisiae. We constructed ccc2-disrupted strains from S. cerevisiae (ogg1ccc2 and ccc2), which were analysed in terms of viability and spontaneous mutator phenotype. We also investigated the impact of 4-nitroquinoline-1-oxide (4-NQO) on nuclear DNA damage and on the stability of mitochondrial DNA. The results indicated a synergistic effect on spontaneous mutagenesis upon OGG1 and CCC2 double inactivation, placing 8-oxoguanine as a strong lesion-candidate at the origin of spontaneous mutations. The ccc2 mutant was more sensitive to cell killing and to mutagenesis upon 4-NQO challenge than the other studied strains. However, Ogg1 repair of exogenous-induced DNA damage revealed to be toxic and mutagenic to ccc2 deficient cells, which can be due to a detrimental action of Ogg1 on DNA lesions induced in ccc2 cells. Altogether, our results point to a critical and ambivalent role of BER mediated by Ogg1 in the maintenance of genomic stability in eukaryotes deficient in CCC2 gene.

Prediction of mitochondrial protein function by comparative physiology and phylogenetic profiling

According to the endosymbiotic theory, mitochondria originate from a free-living alpha-proteobacteria that established an intracellular symbiosis with the ancestor of present-day eukaryotic cells. During the bacterium-to-organelle transformation, the proto-mitochondrial proteome has undergone a massive turnover, whereby less than 20 % of modern mitochondrial proteomes can be traced back to the bacterial ancestor. Moreover, mitochondrial proteomes from several eukaryotic organisms, for example, yeast and human, show a rather modest overlap, reflecting differences in mitochondrial physiology. Those differences may result from the combination of differential gain and loss of genes and retargeting processes among lineages. Therefore, an evolutionary signature, also called "phylogenetic profile", could be generated for every mitochondrial protein. Here, we present two evolutionary biology approaches to study mitochondrial physiology: the first strategy, which we refer to as "comparative physiology," allows the de novo identification of mitochondrial proteins involved in a physiological function; the second, known as "phylogenetic profiling," allows to predict protein functions and functional interactions by comparing phylogenetic profiles of uncharacterized and known components.

[Chemobiology at happy hour: yeast as a model for pharmacological screening]

Since its discovery and description by Louis Pasteur, the budding yeast Saccharomyces cerevisiae, which was used for thousands of years for alcoholic fermentation and as a leavening agent, has become a popular model system in biology. One of the reasons for this popularity is the strong conservation from yeast to human of most of the pathways controlling cell growth and fate. In addition, at least 30 % of human genes involved in diseases have a functional homolog in yeast. Hence, yeast is now widely used for modelling and deciphering physiopathological mechanisms as well as for developing pharmacological approaches like phenotype-based drug screening. Three examples of such yeast-based chemobiological studies are presented.

Using yeast to model calcium-related diseases: example of the Hailey-Hailey disease

Cross-complementation studies offer the possibility to overcome limitations imposed by the inherent complexity of multicellular organisms in the study of human diseases, by taking advantage of simpler model organisms like the budding yeast Saccharomyces cerevisiae. This review deals with, (1) the use of S. cerevisiae as a model organism to study human diseases, (2) yeast-based screening systems for the detection of disease modifiers, (3) Hailey-Hailey as an example of a calcium-related disease, and (4) the presentation of a yeast-based model to search for chemical modifiers of Hailey-Hailey disease. The preliminary experimental data presented and discussed here show that it is possible to use yeast as a model system for Hailey-Hailey disease and suggest that in all likelihood, yeast has the potential to reveal candidate drugs for the treatment of this disorder. This article is part of a Special Issue entitled: Calcium signaling in health and disease. Guest Editors: Geert Bultynck, Jacques Haiech, Claus W. Heizmann, Joachim Krebs, and Marc Moreau.

A yeast-based assay identifies drugs that interfere with immune evasion of the Epstein-Barr virus

Epstein-Barr virus (EBV) is tightly associated with certain human cancers, but there is as yet no specific treatment against EBV-related diseases. The EBV-encoded EBNA1 protein is essential to maintain viral episomes and for viral persistence. As such, EBNA1 is expressed in all EBV-infected cells, and is highly antigenic. All infected individuals, including individuals with cancer, have CD8(+) T cells directed towards EBNA1 epitopes, yet the immune system fails to detect and destroy cells harboring the virus. EBV immune evasion depends on the capacity of the Gly-Ala repeat (GAr) domain of EBNA1 to inhibit the translation of its own mRNA in cis, thereby limiting the production of EBNA1-derived antigenic peptides presented by the major histocompatibility complex (MHC) class I pathway. Here we establish a yeast-based assay for monitoring GAr-dependent inhibition of translation. Using this assay we identify doxorubicin (DXR) as a compound that specifically interferes with the GAr effect on translation in yeast. DXR targets the topoisomerase-II-DNA complexes and thereby causes genomic damage. We show, however, that the genotoxic effect of DXR and various analogs thereof is uncoupled from the effect on GAr-mediated translation control. This is further supported by the observation that etoposide and teniposide, representing another class of topoisomerase-II-DNA targeting drugs, have no effect on GAr-mediated translation control. DXR and active analogs stimulate, in a GAr-dependent manner, EBNA1 expression in mammalian cells and overcome GAr-dependent restriction of MHC class I antigen presentation. These results validate our approach as an effective high-throughput screening assay to identify drugs that interfere with EBV immune evasion and, thus, constitute candidates for treating EBV-related diseases, in particular EBV-associated cancers.

Contemporary, yeast-based approaches to understanding human genetic variation

Determining how genetic variation contributes to human health and disease is a critical challenge. As one of the most genetically tractable model organisms, yeast has played a central role in meeting this challenge. The advent of new technologies, including high-throughput DNA sequencing and synthesis, proteomics, and computational methods, has vastly increased the power of yeast-based approaches to determine the consequences of human genetic variation. Recent successes include systematic exploration of the effects of gene dosage, large-scale analysis of the effect of coding variation on gene function, and the use of humanized yeast to model disease. By virtue of its manipulability, small genome size, and genetic tractability, yeast is poised to help us understand human genetic variation.

Prediction of the functional effect of novel SLC25A13 variants using a S. cerevisiae model of AGC2 deficiency

AGC2, a member of the mitochondrial carrier protein family, is as an aspartate-glutamate carrier and is important for urea synthesis and the maintenance of the malate-aspartate shuttle. Mutations in SLC25A13, the gene encoding AGC2, result in two age dependent disorders: neonatal intrahepatic cholestasis caused by citrin deficiency (NICCD) and type II citrullinemia (CTLN2). The clinical features of CTLN2 are very similar to those of other urea cycle disorders making a clear diagnosis difficult. Analysis of the SLC25A13 gene sequence can provide a definitive diagnosis, however the predictive value of DNA sequencing requires that the disease association of variants be characterized. We utilized the yeast Saccharomyces cerevisiae lacking AGC1 as a model system to study the effect on the function of AGC2 variants and confirmed that this system is capable of distinguishing between AGC2 variants with normal (p.Pro632Leu) or impaired function (p.Gly437Glu, p.Gly531Asp, p.Thr546Met, p.Leu598Arg and p.Glu601Lys). Three novel AGC2 genetic variants, p.Met1? (c.2T>C), p.Pro502Leu (c.1505C>T), and p.Arg605Gln (c.1814G>A) were investigated and our analysis revealed that p.Pro502Leu and p.Arg605Gln substitutions in the AGC2 protein were without effect and these variants were fully functional. The p.Met1? mutant is capable of expressing a truncated p.Met1_Phe34del AGC2 variant, however this protein is not functional due to disruptions in a calcium binding EF hand as well as incorrect intracellular localization. Our study demonstrates that the characterization of AGC2 expressed in yeast cells is a powerful technique to investigate AGC2 variants, and this analysis should aid in establishing the disease association of novel variants.

Decoupling epigenetic and genetic effects through systematic analysis of gene position

Classic "position-effect" experiments repositioned genes near telomeres to demonstrate that the epigenetic landscape can dramatically alter gene expression. Here, we show that systematic gene knockout collections provide an exceptional resource for interrogating position effects, not only near telomeres but at every genetic locus. Because a single reporter gene replaces each deleted gene, interrogating this reporter provides a sensitive probe into different chromatin environments while controlling for genetic context. Using this approach, we find that, whereas systematic replacement of yeast genes with the kanMX marker does not perturb the chromatin landscape, chromatin differences associated with gene position account for 35% of kanMX activity. We observe distinct chromatin influences, including a Set2/Rpd3-mediated antagonistic interaction between histone H3 lysine 36 trimethylation and the Rap1 transcriptional activation site in kanMX. This interaction explains why some yeast genes have been resistant to deletion and allows successful generation of these deletion strains through the use of a modified transformation procedure. These findings demonstrate that chromatin regulation is not governed by a uniform "histone code" but by specific interactions between chromatin and genetic factors.

Untangling the Roles of Anti-Apoptosis in Regulating Programmed Cell Death using Humanized Yeast Cells

Genetically programmed cell death (PCD) mechanisms, including apoptosis, are important for the survival of metazoans since it allows, among things, the removal of damaged cells that interfere with normal function. Cell death due to PCD is observed in normal processes such as aging and in a number of pathophysiologies including hypoxia (common causes of heart attacks and strokes) and subsequent tissue reperfusion. Conversely, the loss of normal apoptotic responses is associated with the development of tumors. So far, limited success in preventing unwanted PCD has been reported with current therapeutic approaches despite the fact that inhibitors of key apoptotic inducers such as caspases have been developed. Alternative approaches have focused on mimicking anti-apoptotic processes observed in cells displaying increased resistance to apoptotic stimuli. Hormesis and pre-conditioning are commonly observed cellular strategies where sub-lethal levels of pro-apoptotic stimuli lead to increased resistance to higher or lethal levels of stress. Increased expression of anti-apoptotic sequences is a common mechanism mediating these protective effects. The relevance of the latter observation is exemplified by the observation that transgenic mice overexpressing anti-apoptotic genes show significant reductions in tissue damage following ischemia. Thus strategies aimed at increasing the levels of anti-apoptotic proteins, using gene therapy or cell penetrating recombinant proteins are being evaluated as novel therapeutics to decrease cell death following acute periods of cell death inducing stress. In spite of its functional and therapeutic importance, more is known regarding the processes involved in apoptosis than anti-apoptosis. The genetically tractable yeast Saccharomyces cerevisiae has emerged as an exceptional model to study multiple aspects of PCD including the mitochondrial mediated apoptosis observed in metazoans. To increase our knowledge of the process of anti-apoptosis, we screened a human heart cDNA expression library in yeast cells undergoing PCD due to the conditional expression of a mammalian pro-apoptotic Bax cDNA. Analysis of the multiple Bax suppressors identified revealed several previously known as well as a large number of clones representing potential novel anti-apoptotic sequences. The focus of this review is to report on recent achievements in the use of humanized yeast in genetic screens to identify novel stress-induced PCD suppressors, supporting the use of yeast as a unicellular model organism to elucidate anti-apoptotic and cell survival mechanisms.

Bacteria, yeast, worms, and flies: exploiting simple model organisms to investigate human mitochondrial diseases

The extensive conservation of mitochondrial structure, composition, and function across evolution offers a unique opportunity to expand our understanding of human mitochondrial biology and disease. By investigating the biology of much simpler model organisms, it is often possible to answer questions that are unreachable at the clinical level. Here, we review the relative utility of four different model organisms, namely the bacterium Escherichia coli, the yeast Saccharomyces cerevisiae, the nematode Caenorhabditis elegans, and the fruit fly Drosophila melanogaster, in studying the role of mitochondrial proteins relevant to human disease. E. coli are single cell, prokaryotic bacteria that have proven to be a useful model system in which to investigate mitochondrial respiratory chain protein structure and function. S. cerevisiae is a single-celled eukaryote that can grow equally well by mitochondrial-dependent respiration or by ethanol fermentation, a property that has proven to be a veritable boon for investigating mitochondrial functionality. C. elegans is a multicellular, microscopic worm that is organized into five major tissues and has proven to be a robust model animal for in vitro and in vivo studies of primary respiratory chain dysfunction and its potential therapies in humans. Studied for over a century, D. melanogaster is a classic metazoan model system offering an abundance of genetic tools and reagents that facilitates investigations of mitochondrial biology using both forward and reverse genetics. The respective strengths and limitations of each species relative to mitochondrial studies are explored. In addition, an overview is provided of major discoveries made in mitochondrial biology in each of these four model systems.

Genome-scale metabolic models of Saccharomyces cerevisiae

Systematic analysis of Saccharomyces cerevisiae metabolic functions and pathways has been the subject of extensive studies and established in many aspects. With the reconstruction of the yeast genome-scale metabolic (GSM) network and in silico simulation of the GSM model, the nature of the underlying cellular processes can be tested and validated with the increasing metabolic knowledge. GSM models are also being exploited in fundamental research studies and industrial applications. In this chapter, the principle concepts for construction, simulation and validation of GSM models, progressive applications of the yeast GSM models, and future perspectives are described. This will support and encourage researchers who are interested in systemic analysis of yeast metabolism and systems biology.

Mitochondrial involvement in cell death of non-mammalian eukaryotes

Although mitochondria are essential organelles for long-term survival of eukaryotic cells, recent discoveries in biochemistry and genetics have advanced our understanding of the requirements for mitochondria in cell death. Much of what we understand about cell death is based on the identification of conserved cell death genes in Drosophila melanogaster and Caenorhabditis elegans. However, the role of mitochondria in cell death in these models has been much less clear. Considering the active role that mitochondria play in apoptosis in mammalian cells, the mitochondrial contribution to cell death in non-mammalian systems has been an area of active investigation. In this article, we review the current research on this topic in three non-mammalian models, C. elegans, Drosophila, and Saccharomyces cerevisiae. In addition, we discuss how non-mammalian models have provided important insight into the mechanisms of human disease as they relate to the mitochondrial pathway of cell death. The unique perspective derived from each of these model systems provides a more complete understanding of mitochondria in programmed cell death. This article is part of a Special Issue entitled Mitochondria: the deadly organelle.

Quantitative proteomics by metabolic labeling of model organisms

In the biological sciences, model organisms have been used for many decades and have enabled the gathering of a large proportion of our present day knowledge of basic biological processes and their derailments in disease. Although in many of these studies using model organisms, the focus has primarily been on genetics and genomics approaches, it is important that methods become available to extend this to the relevant protein level. Mass spectrometry-based proteomics is increasingly becoming the standard to comprehensively analyze proteomes. An important transition has been made recently by moving from charting static proteomes to monitoring their dynamics by simultaneously quantifying multiple proteins obtained from differently treated samples. Especially the labeling with stable isotopes has proved an effective means to accurately determine differential expression levels of proteins. Among these, metabolic incorporation of stable isotopes in vivo in whole organisms is one of the favored strategies. In this perspective, we will focus on methodologies to stable isotope label a variety of model organisms in vivo, ranging from relatively simple organisms such as bacteria and yeast to Caenorhabditis elegans, Drosophila, and Arabidopsis up to mammals such as rats and mice. We also summarize how this has opened up ways to investigate biological processes at the protein level in health and disease, revealing conservation and variation across the evolutionary tree of life.

Correlation between TCA cycle flux and glucose uptake rate during respiro-fermentative growth of Saccharomyces cerevisiae

Glucose repression of the tricarboxylic acid (TCA) cycle in Saccharomyces cerevisiae was investigated under different environmental conditions using (13)C-tracer experiments. Real-time quantification of the volatile metabolites ethanol and CO(2) allowed accurate carbon balancing. In all experiments with the wild-type, a strong correlation between the rates of growth and glucose uptake was observed, indicating a constant yield of biomass. In contrast, glycerol and acetate production rates were less dependent on the rate of glucose uptake, but were affected by environmental conditions. The glycerol production rate was highest during growth in high-osmolarity medium (2.9 mmol g(-1) h(-1)), while the highest acetate production rate of 2.1 mmol g(-1) h(-1) was observed in alkaline medium of pH 6.9. Under standard growth conditions (25 g glucose l(-1) , pH 5.0, 30 degrees C) S. cerevisiae had low fluxes through the pentose phosphate pathway and the TCA cycle. A significant increase in TCA cycle activity from 0.03 mmol g(-1) h(-1) to about 1.7 mmol g(-1) h(-1) was observed when S. cerevisiae grew more slowly as a result of environmental perturbations, including unfavourable pH values and sodium chloride stress. Compared to experiments with high glucose uptake rates, the ratio of CO(2) to ethanol increased more than 50 %, indicating an increase in flux through the TCA cycle. Although glycolysis and the ethanol production pathway still exhibited the highest fluxes, the net flux through the TCA cycle increased significantly with decreasing glucose uptake rates. Results from experiments with single gene deletion mutants partially impaired in glucose repression (hxk2, grr1) indicated that the rate of glucose uptake correlates with this increase in TCA cycle flux. These findings are discussed in the context of regulation of glucose repression.

Evidence that msh1p plays multiple roles in mitochondrial base excision repair

Mitochondrial DNA is thought to be especially prone to oxidative damage by reactive oxygen species generated through electron transport during cellular respiration. This damage is mitigated primarily by the base excision repair (BER) pathway, one of the few DNA repair pathways with confirmed activity on mitochondrial DNA. Through genetic epistasis analysis of the yeast Saccharomyces cerevisiae, we examined the genetic interaction between each of the BER proteins previously shown to localize to the mitochondria. In addition, we describe a series of genetic interactions between BER components and the MutS homolog MSH1, a respiration-essential gene. We show that, in addition to their variable effects on mitochondrial function, mutant msh1 alleles conferring partial function interact genetically at different points in mitochondrial BER. In addition to this separation of function, we also found that the role of Msh1p in BER is unlikely to be involved in the avoidance of large-scale deletions and rearrangements.

Computationally driven, quantitative experiments discover genes required for mitochondrial biogenesis

Mitochondria are central to many cellular processes including respiration, ion homeostasis, and apoptosis. Using computational predictions combined with traditional quantitative experiments, we have identified 100 proteins whose deficiency alters mitochondrial biogenesis and inheritance in Saccharomyces cerevisiae. In addition, we used computational predictions to perform targeted double-mutant analysis detecting another nine genes with synthetic defects in mitochondrial biogenesis. This represents an increase of about 25% over previously known participants. Nearly half of these newly characterized proteins are conserved in mammals, including several orthologs known to be involved in human disease. Mutations in many of these genes demonstrate statistically significant mitochondrial transmission phenotypes more subtle than could be detected by traditional genetic screens or high-throughput techniques, and 47 have not been previously localized to mitochondria. We further characterized a subset of these genes using growth profiling and dual immunofluorescence, which identified genes specifically required for aerobic respiration and an uncharacterized cytoplasmic protein required for normal mitochondrial motility. Our results demonstrate that by leveraging computational analysis to direct quantitative experimental assays, we have characterized mutants with subtle mitochondrial defects whose phenotypes were undetected by high-throughput methods.

Mitochondria are the proverbial powerhouses of the cell, running the fundamental biochemical processes that produce energy from nutrients using oxygen. These processes are conserved in all eukaryotes, from humans to model organisms such as baker's yeast. In humans, mitochondrial dysfunction plays a role in a variety of diseases, including diabetes, neuromuscular disorders, and aging. In order to better understand fundamental mitochondrial biology, we studied genes involved in mitochondrial biogenesis in the yeast S. cerevisiae, discovering over 100 proteins with novel roles in this process. These experiments assigned function to 5% of the genes whose function was not known. In order to achieve this rapid rate of discovery, we developed a system incorporating highly quantitative experimental assays and an integrated, iterative process of computational protein function prediction. Beginning from relatively little prior knowledge, we found that computational predictions achieved about 60% accuracy and rapidly guided our laboratory work towards hundreds of promising candidate genes. Thus, in addition to providing a more thorough understanding of mitochondrial biology, this study establishes a framework for successfully integrating computation and experimentation to drive biological discovery. A companion manuscript, published in PLoS Computational Biology (doi:10.1371/journal.pcbi.1000322), discusses observations and conclusions important for the computational community.

Directing experimental biology: a case study in mitochondrial biogenesis

Computational approaches have promised to organize collections of functional genomics data into testable predictions of gene and protein involvement in biological processes and pathways. However, few such predictions have been experimentally validated on a large scale, leaving many bioinformatic methods unproven and underutilized in the biology community. Further, it remains unclear what biological concerns should be taken into account when using computational methods to drive real-world experimental efforts. To investigate these concerns and to establish the utility of computational predictions of gene function, we experimentally tested hundreds of predictions generated from an ensemble of three complementary methods for the process of mitochondrial organization and biogenesis in Saccharomyces cerevisiae. The biological data with respect to the mitochondria are presented in a companion manuscript published in PLoS Genetics (doi:10.1371/journal.pgen.1000407). Here we analyze and explore the results of this study that are broadly applicable for computationalists applying gene function prediction techniques, including a new experimental comparison with 48 genes representing the genomic background. Our study leads to several conclusions that are important to consider when driving laboratory investigations using computational prediction approaches. While most genes in yeast are already known to participate in at least one biological process, we confirm that genes with known functions can still be strong candidates for annotation of additional gene functions. We find that different analysis techniques and different underlying data can both greatly affect the types of functional predictions produced by computational methods. This diversity allows an ensemble of techniques to substantially broaden the biological scope and breadth of predictions. We also find that performing prediction and validation steps iteratively allows us to more completely characterize a biological area of interest. While this study focused on a specific functional area in yeast, many of these observations may be useful in the contexts of other processes and organisms.

Genome sequencing has provided us with “parts lists” of genes for many organisms, but many of the biological roles these genes are still unknown. While a great deal of functional genomic data exists, providing information about these genes and their roles, the rate at which these data are leveraged into concrete biological knowledge lags far behind the rate of data generation. Many computational approaches have been developed to generate accurate predictions of gene functions, with the goal of bridging this divide. However, as no large-scale experimental efforts have been based on such approaches, their validity and utility remains unproven. We have performed a study that experimentally evaluates predictions from a combination of three computational function prediction approaches, focusing on mitochondrion-related processes in brewer's yeast as a model system. By using computational predictions to guide our laboratory investigation, we have greatly accelerated the rate at which proteins can be assigned to biological processes. Further, our results demonstrate that in order to achieve the best results, it is important for computational biologists to consider both the underlying data and the algorithmic foundations of the methods used to predict function. Lastly, we demonstrate that iterating through phases of prediction and validation has quickly and extensively expanded our knowledge of mitochondrial biology.

Identification of candidate disease genes by integrating Gene Ontologies and protein-interaction networks: case study of primary immunodeficiencies

Disease gene identification is still a challenge despite modern high-throughput methods. Many diseases are very rare or lethal and thus cannot be investigated with traditional methods. Several in silico methods have been developed but they have some limitations. We introduce a new method that combines information about protein-interaction network properties and Gene Ontology terms. Genes with high-calculated network scores and statistically significant gene ontology terms based on known diseases are prioritized as candidate genes. The method was applied to identify novel primary immunodeficiency-related genes, 26 of which were found. The investigation uses the protein-interaction network for all essential immunome human genes available in the Immunome Knowledge Base and an analysis of their enriched gene ontology annotations. The identified disease gene candidates are mainly involved in cellular signaling including receptors, protein kinases and adaptor and binding proteins as well as enzymes. The method can be generalized for any disease group with sufficient information.

Identification of mitochondrial disease genes through integrative analysis of multiple datasets

Determining the genetic factors in a disease is crucial to elucidating its molecular basis. This task is challenging due to a lack of information on gene function. The integration of large-scale functional genomics data has proven to be an effective strategy to prioritize candidate disease genes. Mitochondrial disorders are a prevalent and heterogeneous class of diseases that are particularly amenable to this approach. Here we explain the application of integrative approaches to the identification of mitochondrial disease genes. We first examine various datasets that can be used to evaluate the involvement of each gene in mitochondrial function. The data integration methodology is then described, accompanied by examples of common implementations. Finally, we discuss how gene networks are constructed using integrative techniques and applied to candidate gene prioritization. Relevant public data resources are indicated. This report highlights the success and potential of data integration as well as its applicability to the search for mitochondrial disease genes.