Buffering of deoxyribonucleotide pool homeostasis by threonine metabolism

Genetic interaction between F-box motif encoding YDR131C and retrograde signaling-related RTG1 regulates the stress response and apoptosis in Saccharomyces cerevisiae

The retrograde signaling pathway is well conserved from yeast to humans, which regulates cell adaptation during stress conditions and prevents cell death. One of its components, RTG1 encoded Rtg1p in association with Rtg3p communicates between mitochondria, nucleus, and peroxisome during stress for adaptation, by regulation of transcription. The F-box motif protein encoded by YDR131C  constitutes a part of SCF ^Ydr131c -E3 ligase complex, with unknown function; however, it is known that retrograde signaling is modulated by the E3 ligase complex. This study reports epistasis interaction between YDR131C and RTG1, which regulates cell growth, response to genotoxic stress, decreased apoptosis, resistance to petite mutation, and cell wall integrity. The cells of ydr131cΔrtg1Δ genetic background exhibits growth rate improvement however, sensitivity to hydroxyurea, itraconazole antifungal agent and synthetic indoloquinazoline-based alkaloid (8-fluorotryptanthrin, RK64), which disrupts the cell wall integrity in Saccharomyces cerevisiae. The epistatic interaction between YDR131C and RTG1 indicates a link between protein degradation and retrograde signaling pathways.

High-resolution yeast quiescence profiling in human-like media reveals complex influences of auxotrophy and nutrient availability

Yeast cells survive in stationary phase culture by entering quiescence, which is measured by colony-forming capacity upon nutrient re-exposure. Yeast chronological lifespan (CLS) studies, employing the comprehensive collection of gene knockout strains, have correlated weakly between independent laboratories, which is hypothesized to reflect differential interaction between the deleted genes, auxotrophy, media composition, and other assay conditions influencing quiescence. This hypothesis was investigated by high-throughput quiescence profiling of the parental prototrophic strain, from which the gene deletion strain libraries were constructed, and all possible auxotrophic allele combinations in that background. Defined media resembling human cell culture media promoted long-term quiescence and was used to assess effects of glucose, ammonium sulfate, auxotrophic nutrient availability, target of rapamycin signaling, and replication stress. Frequent, high-replicate measurements of colony-forming capacity from cultures aged past 60 days provided profiles of quiescence phenomena such as gasping and hormesis. Media acidification was assayed in parallel to assess correlation. Influences of leucine, methionine, glucose, and ammonium sulfate metabolism were clarified, and a role for lysine metabolism newly characterized, while histidine and uracil perturbations had less impact. Interactions occurred between glucose, ammonium sulfate, auxotrophy, auxotrophic nutrient limitation, aeration, TOR signaling, and/or replication stress. Weak correlation existed between media acidification and maintenance of quiescence. In summary, experimental factors, uncontrolled across previous genome-wide yeast CLS studies, influence quiescence and interact extensively, revealing quiescence as a complex metabolic and developmental process that should be studied in a prototrophic context, omitting ammonium sulfate from defined media, and employing highly replicable protocols.

Mechanistic insights on the mode of action of an antiproliferative thiosemicarbazone-nickel complex revealed by an integrated chemogenomic profiling study

Thiosemicarbazones (TSC) and their metal complexes display diverse biological activities and are active against multiple pathological conditions ranging from microbial infections to abnormal cell proliferation. Ribonucleotide reductase (RNR) is considered one of the main targets of TSCs, yet, the existence of additional targets, differently responsible for the multifaceted activities of TSCs and their metal complexes has been proposed. To set the basis for a more comprehensive delineation of their mode of action, we chemogenomically profiled the cellular effects of bis(citronellalthiosemicarbazonato)nickel(II) [Ni(S-tcitr)₂] using the unicellular eukaryote Saccharomyces cerevisiae as a model organism. Two complementary genomic phenotyping screens led to the identification of 269 sensitive and 56 tolerant deletion mutant strains and of 14 genes that when overexpressed make yeast cells resistant to an otherwise lethal concentration of Ni(S-tcitr)₂. Chromatin remodeling, cytoskeleton organization, mitochondrial function and iron metabolism were identified as lead cellular processes responsible for Ni(S-tcitr)₂ toxicity. The latter process, and particularly glutaredoxin-mediated iron loading of RNR, was found to be affected by Ni(S-tcitr)₂. Given the multiple pathways regulated by glutaredoxins, targeting of these proteins by Ni(S-tcitr)₂ can negatively affect various core cellular processes that may critically contribute to Ni(S-tcitr)₂ cytotoxicity.

A yeast phenomic model for the influence of Warburg metabolism on genetic buffering of doxorubicin

BACKGROUND

The influence of the Warburg phenomenon on chemotherapy response is unknown. Saccharomyces cerevisiae mimics the Warburg effect, repressing respiration in the presence of adequate glucose. Yeast phenomic experiments were conducted to assess potential influences of Warburg metabolism on gene-drug interaction underlying the cellular response to doxorubicin. Homologous genes from yeast phenomic and cancer pharmacogenomics data were analyzed to infer evolutionary conservation of gene-drug interaction and predict therapeutic relevance.

METHODS

Cell proliferation phenotypes (CPPs) of the yeast gene knockout/knockdown library were measured by quantitative high-throughput cell array phenotyping (Q-HTCP), treating with escalating doxorubicin concentrations under conditions of respiratory or glycolytic metabolism. Doxorubicin-gene interaction was quantified by departure of CPPs observed for the doxorubicin-treated mutant strain from that expected based on an interaction model. Recursive expectation-maximization clustering (REMc) and Gene Ontology (GO)-based analyses of interactions identified functional biological modules that differentially buffer or promote doxorubicin cytotoxicity with respect to Warburg metabolism. Yeast phenomic and cancer pharmacogenomics data were integrated to predict differential gene expression causally influencing doxorubicin anti-tumor efficacy.

RESULTS

Yeast compromised for genes functioning in chromatin organization, and several other cellular processes are more resistant to doxorubicin under glycolytic conditions. Thus, the Warburg transition appears to alleviate requirements for cellular functions that buffer doxorubicin cytotoxicity in a respiratory context. We analyzed human homologs of yeast genes exhibiting gene-doxorubicin interaction in cancer pharmacogenomics data to predict causality for differential gene expression associated with doxorubicin cytotoxicity in cancer cells. This analysis suggested conserved cellular responses to doxorubicin due to influences of homologous recombination, sphingolipid homeostasis, telomere tethering at nuclear periphery, actin cortical patch localization, and other gene functions.

CONCLUSIONS

Warburg status alters the genetic network required for yeast to buffer doxorubicin toxicity. Integration of yeast phenomic and cancer pharmacogenomics data suggests evolutionary conservation of gene-drug interaction networks and provides a new experimental approach to model their influence on chemotherapy response. Thus, yeast phenomic models could aid the development of precision oncology algorithms to predict efficacious cytotoxic drugs for cancer, based on genetic and metabolic profiles of individual tumors.

A Humanized Yeast Phenomic Model of Deoxycytidine Kinase to Predict Genetic Buffering of Nucleoside Analog Cytotoxicity

Knowledge about synthetic lethality can be applied to enhance the efficacy of anticancer therapies in individual patients harboring genetic alterations in their cancer that specifically render it vulnerable. We investigated the potential for high-resolution phenomic analysis in yeast to predict such genetic vulnerabilities by systematic, comprehensive, and quantitative assessment of drug–gene interaction for gemcitabine and cytarabine, substrates of deoxycytidine kinase that have similar molecular structures yet distinct antitumor efficacy. Human deoxycytidine kinase (dCK) was conditionally expressed in the Saccharomyces cerevisiae genomic library of knockout and knockdown (YKO/KD) strains, to globally and quantitatively characterize differential drug–gene interaction for gemcitabine and cytarabine. Pathway enrichment analysis revealed that autophagy, histone modification, chromatin remodeling, and apoptosis-related processes influence gemcitabine specifically, while drug–gene interaction specific to cytarabine was less enriched in gene ontology. Processes having influence over both drugs were DNA repair and integrity checkpoints and vesicle transport and fusion. Non-gene ontology (GO)-enriched genes were also informative. Yeast phenomic and cancer cell line pharmacogenomics data were integrated to identify yeast–human homologs with correlated differential gene expression and drug efficacy, thus providing a unique resource to predict whether differential gene expression observed in cancer genetic profiles are causal in tumor-specific responses to cytotoxic agents.

Emerging Role of Precision Medicine in Cardiovascular Disease

Precision medicine is an integrative approach to cardiovascular disease prevention and treatment that considers an individual's genetics, lifestyle, and exposures as determinants of their cardiovascular health and disease phenotypes. This focus overcomes the limitations of reductionism in medicine, which presumes that all patients with the same signs of disease share a common pathophenotype and, therefore, should be treated similarly. Precision medicine incorporates standard clinical and health record data with advanced panomics (ie, transcriptomics, epigenomics, proteomics, metabolomics, and microbiomics) for deep phenotyping. These phenotypic data can then be analyzed within the framework of molecular interaction (interactome) networks to uncover previously unrecognized disease phenotypes and relationships between diseases, and to select pharmacotherapeutics or identify potential protein-drug or drug-drug interactions. In this review, we discuss the current spectrum of cardiovascular health and disease, population averages and the response of extreme phenotypes to interventions, and population-based versus high-risk treatment strategies as a pretext to understanding a precision medicine approach to cardiovascular disease prevention and therapeutic interventions. We also consider the search for resilience and Mendelian disease genes and argue against the theory of a single causal gene/gene product as a mediator of the cardiovascular disease phenotype, as well as an Erlichian magic bullet to solve cardiovascular disease. Finally, we detail the importance of deep phenotyping and interactome networks and the use of this information for rational polypharmacy. These topics highlight the urgent need for precise phenotyping to advance precision medicine as a strategy to improve cardiovascular health and prevent disease.

Role of Mitochondrial Retrograde Pathway in Regulating Ethanol-Inducible Filamentous Growth in Yeast

In yeast, ethanol is produced as a by-product of fermentation through glycolysis. Ethanol also stimulates a developmental foraging response called filamentous growth and is thought to act as a quorum-sensing molecule. Ethanol-inducible filamentous growth was examined in a small collection of wine/European strains, which validated ethanol as an inducer of filamentous growth. Wine strains also showed variability in their filamentation responses, which illustrates the striking phenotypic differences that can occur among individuals. Ethanol-inducible filamentous growth in Σ1278b strains was independent of several of the major filamentation regulatory pathways [including fMAPK, RAS-cAMP, Snf1, Rpd3(L), and Rim101] but required the mitochondrial retrograde (RTG) pathway, an inter-organellar signaling pathway that controls the nuclear response to defects in mitochondrial function. The RTG pathway regulated ethanol-dependent filamentous growth by maintaining flux through the TCA cycle. The ethanol-dependent invasive growth response required the polarisome and transcriptional induction of the cell adhesion molecule Flo11p. Our results validate established stimuli that trigger filamentous growth and show how stimuli can trigger highly specific responses among individuals. Our results also connect an inter-organellar pathway to a quorum sensing response in fungi.

Gene-nutrient interaction markedly influences yeast chronological lifespan

PURPOSE

Research into the genetic mechanisms of aging has expanded rapidly over the past two decades. This has in part been the result of the use of model organisms (particularly yeast, worms and flies) and high-throughput technologies, combined with a growing interest in aging research. Despite this progress, widespread consensus regarding the pathways that are fundamental to the modulation of cellular aging and lifespan for all organisms has been limited due to discrepancies between different studies. We have compared results from published genome-wide, chronological lifespan (CLS) screens of individual gene deletion strains in Saccharomyces cerevisiae in order to identify gene deletion strains with consistent influences on longevity as possible indicators of fundamental aging processes from this single-celled, eukaryotic model organism.

METHODS

Three previous reports have described genetic modifiers of chronological aging in the budding yeast (S. cerevisiae) using the yeast gene deletion strain collection. We performed a comparison among the data sets using correlation and decile distribution analysis to describe concordance between screens and identify strains that consistently increased or decreased CLS. We used gene enrichment analysis in an effort to understand the biology underlying genes identified in multiple studies. We attempted to replicate the different experimental conditions employed by the screens to identify potential sources of variability in CLS worth further investigating.

RESULTS

Among 3209 strains present in all three screens, nine deletions strains were in common in the longest-lived decile (2.80%) and thirteen were in common in the shortest-lived decile (4.05%) of all three screens. Similarly, pairwise overlap between screens was low. When the same comparison was extended to three deciles to include more mutants studied in common between the three screens, enrichment of cellular processes based on gene ontology analysis in the long-lived strains remained very limited. To test the hypothesis that different parental strain auxotrophic requirements or media formulations employed by the respective genome-wide screens might contribute to the lack of concordance, different CLS assay conditions were assessed in combination with strains having different ploidy and auxotrophic requirements (all relevant to differences in the way the three genome-wide CLS screens were performed). This limited but systematic analysis of CLS with respect to auxotrophy, ploidy, and media revealed several instances of gene-nutrient interaction.

CONCLUSIONS

There is surprisingly little overlap between the results of three independently performed genome-wide screens of CLS in S. cerevisiae. However, differences in strain genetic background (ploidy and specific auxotrophic requirements) were present, as well as different media and experimental conditions (e.g., aeration and pooled vs. individual culturing), which, along with stochastic effects such as genetic drift or selection of secondary mutations that suppress the loss of function from gene deletion, could in theory account for some of the lack of consensus between results. Considering the lack of overlap in CLS phenotypes among the set of genes reported by all three screens, and the results of a CLS experiment that systematically tested (incorporating extensive controls) for interactions between variables existing between the screens, we propose that discrepancies can be reconciled through deeper understanding of the influence of cell intrinsic factors such as auxotrophic requirements ploidy status, extrinsic factors such as media composition and aeration, as well as interactions that may occur between them, for example as a result of different pooling vs. individually aging cultures. Such factors may have a more significant impact on CLS outcomes than previously realized. Future studies that systematically account for these contextual factors, and can thus clarify the interactions between genetic and nutrient factors that alter CLS phenotypes, should aid more complete understanding of the underlying biology so that genetic principles of CLS in yeast can be extrapolated to differential cellular aging observed in animal models.

Mitochondrial retrograde signaling inhibits the survival during prolong S/G2 arrest in Saccharomyces cerevisiae

Cell senescence is dependent on the arrest in cell cycle. Here we studied the role of mitochondrial retrograde response signaling in yeast cell survival under a prolonged arrest. We have found that, unlike G1, long-term arrest in mitosis or S phase results in a loss of colony-forming abilities. Consistent with previous observations, loss of mitochondrial DNA significantly increased the survival of arrested cells. We found that this was because the loss increases the duration of G1 phase. Unexpectedly, retrograde signaling, which is typically triggered by a variety of mitochondrial dysfunctions, was found to be a negative regulator of the survival after the release from S-phase arrest induced by the telomere replication defect. Deletion of retrograde response genes decreased the arrest-induced death in such cells, whereas deletion of negative regulator of retrograde signaling MKS1 had the opposite effect. We provide evidence that these effects are due to alleviation of the strength of the S-phase arrest.

Aspartate facilitates mitochondrial function, growth arrest and survival during doxorubicin exposure

Genomic screens of doxorubicin toxicity in S. cerevisiae have identified numerous mutants in amino acid and carbon metabolism which express increased doxorubicin sensitivity. This work examines the effect of amino acid metabolism on doxorubicin toxicity. S. cerevisiae were treated with doxorubicin in combination with a variety of amino acid supplements. Strains of S. cerevisiae with mutations in pathways utilizing aspartate and other metabolites were examined for sensitivity to doxorubicin. S. cerevisiae cultures exposed to doxorubicin in minimal media showed significantly more toxicity than cultures exposed in rich media. Supplementing minimal media with aspartate, glutamate or alanine reduced doxorubicin toxicity. Cell cycle response was assessed by examining the budding pattern of treated cells. Cultures exposed to doxorubicin in minimal media arrested growth with no apparent cell cycle progression. Aspartate supplementation allowed cultures exposed to doxorubicin in minimal media to arrest after one division with a budding pattern and survival comparable to cultures exposed in rich media. Aspartate provides less protection from doxorubicin in cells mutant in either mitochondrial citrate synthase (CIT1) or NADH oxidase (NDI1), suggesting aspartate reduces doxorubicin toxicity by facilitating mitochondrial function. These data suggest glycolysis becomes less active and mitochondrial respiration more active following doxorubicin exposure.

Analysis of 589,306 genomes identifies individuals resilient to severe Mendelian childhood diseases

Genetic studies of human disease have traditionally focused on the detection of disease-causing mutations in afflicted individuals. Here we describe a complementary approach that seeks to identify healthy individuals resilient to highly penetrant forms of genetic childhood disorders. A comprehensive screen of 874 genes in 589,306 genomes led to the identification of 13 adults harboring mutations for 8 severe Mendelian conditions, with no reported clinical manifestation of the indicated disease. Our findings demonstrate the promise of broadening genetic studies to systematically search for well individuals who are buffering the effects of rare, highly penetrant, deleterious mutations. They also indicate that incomplete penetrance for Mendelian diseases is likely more common than previously believed. The identification of resilient individuals may provide a first step toward uncovering protective genetic variants that could help elucidate the mechanisms of Mendelian diseases and new therapeutic strategies.

A metabolomics-based strategy for identification of gene targets for phenotype improvement and its application to 1-butanol tolerance in Saccharomyces cerevisiae

BACKGROUND

Traditional approaches to phenotype improvement include rational selection of genes for modification, and probability-driven processes such as laboratory evolution or random mutagenesis. A promising middle-ground approach is semi-rational engineering, where genetic modification targets are inferred from system-wide comparison of strains. Here, we have applied a metabolomics-based, semi-rational strategy of phenotype improvement to 1-butanol tolerance in Saccharomyces cerevisiae.

RESULTS

Nineteen yeast single-deletion mutant strains with varying growth rates under 1-butanol stress were subjected to non-targeted metabolome analysis by GC/MS, and a regression model was constructed using metabolite peak intensities as predictors and stress growth rates as the response. From this model, metabolites positively and negatively correlated with growth rate were identified including threonine and citric acid. Based on the assumption that these metabolites were linked to 1-butanol tolerance, new deletion strains accumulating higher threonine or lower citric acid were selected and subjected to tolerance measurement and metabolome analysis. The new strains exhibiting the predicted changes in metabolite levels also displayed significantly higher growth rate under stress over the control strain, thus validating the link between these metabolites and 1-butanol tolerance.

CONCLUSIONS

A strategy for semi-rational phenotype improvement using metabolomics was proposed and applied to the 1-butanol tolerance of S. cerevisiae. Metabolites correlated with growth rate under 1-butanol stress were identified, and new mutant strains showing higher growth rate under stress could be selected based on these metabolites. The results demonstrate the potential of metabolomics in semi-rational strain engineering.

Mitochondria to nucleus signaling and the role of ceramide in its integration into the suite of cell quality control processes during aging

Mitochondria to nucleus signaling has been the most extensively studied mode of inter-organelle communication. The first signaling pathway in this category of information transfer to be discovered was the retrograde response, with its own set of signal transduction proteins. The finding that this pathway compensates for mitochondrial dysfunction to extend the replicative lifespan of yeast cells has generated additional impetus for its study. This research has demonstrated crosstalk between the retrograde response and the target of rapamycin (TOR), small GTPase RAS, and high-osmolarity glycerol (HOG) pathways in yeast, all of which are key players in replicative lifespan. More recently, the retrograde response has been implicated in the diauxic shift and survival in stationary phase, extending its operation to the yeast chronological lifespan as well. In this capacity, the retrograde response may cooperate with other, related mitochondria to nucleus signaling pathways. Counterparts of the retrograde response are found in the roundworm, the fruit fly, the mouse, and even in human cells in tissue culture. The exciting realization that the retrograde response is embedded in the network of cellular quality control processes has emerged over the past few years. Most strikingly, it is closely integrated with autophagy and the selective brand of this quality control process, mitophagy. This coordination depends on TOR, and it engages ceramide/sphingolipid signaling. The yeast LAG1 ceramide synthase gene was the first longevity gene cloned as such, and its orthologs hyl-1 and hyl-2 determine worm lifespan. Thus, the involvement of ceramide signaling in quality control gives these findings cellular context. The retrograde response and ceramide are essential components of a lifespan maintenance process that likely evolved as a cytoprotective mechanism to defend the organism from diverse stressors.

Genetic instability in budding and fission yeast-sources and mechanisms

Cells are constantly confronted with endogenous and exogenous factors that affect their genomes. Eons of evolution have allowed the cellular mechanisms responsible for preserving the genome to adjust for achieving contradictory objectives: to maintain the genome unchanged and to acquire mutations that allow adaptation to environmental changes. One evolutionary mechanism that has been refined for survival is genetic variation. In this review, we describe the mechanisms responsible for two biological processes: genome maintenance and mutation tolerance involved in generations of genetic variations in mitotic cells of both Saccharomyces cerevisiae and Schizosaccharomyces pombe. These processes encompass mechanisms that ensure the fidelity of replication, DNA lesion sensing and DNA damage response pathways, as well as mechanisms that ensure precision in chromosome segregation during cell division. We discuss various factors that may influence genome stability, such as cellular ploidy, the phase of the cell cycle, transcriptional activity of a particular region of DNA, the proficiency of DNA quality control systems, the metabolic stage of the cell and its respiratory potential, and finally potential exposure to endogenous or environmental stress.

The stability of budding and fission yeast genomes is influenced by two contradictory factors: (1) the need to be fully functional, which is ensured through the replication fidelity pathways of nuclear and mitochondrial genomes through sensing and repairing DNA damage, through precise chromosome segregation during cell division; and (2) the need to acquire changes for adaptation to environmental challenges.

Phenomic assessment of genetic buffering by kinetic analysis of cell arrays

Quantitative high-throughput cell array phenotyping (Q-HTCP) is applied to the genomic collection of yeast gene deletion mutants for systematic, comprehensive assessment of the contribution of genes and gene combinations to any phenotype of interest (phenomic analysis). Interacting gene networks influence every phenotype. Genetic buffering refers to how gene interaction networks stabilize or destabilize a phenotype. Like genomics, phenomics varies in its resolution with there being a trade-off allocating a greater number of measurements per sample to enhance quantification of the phenotype vs. increasing the number of different samples by obtaining fewer measurements per sample. The Q-HTCP protocol we describe assesses 50,000-70,000 cultures per experiment by obtaining kinetic growth curves from time series imaging of agar cell arrays. This approach was developed for the yeast gene deletion strains, but it could be applied as well to other microbial mutant arrays grown on solid agar media. The methods we describe are for creation and maintenance of frozen stocks, liquid source array preparation, agar destination plate printing, image scanning, image analysis, curve fitting, and evaluation of gene interaction.

Yeast Phenomics: An Experimental Approach for Modeling Gene Interaction Networks that Buffer Disease

The genome project increased appreciation of genetic complexity underlying disease phenotypes: many genes contribute each phenotype and each gene contributes multiple phenotypes. The aspiration of predicting common disease in individuals has evolved from seeking primary loci to marginal risk assignments based on many genes. Genetic interaction, defined as contributions to a phenotype that are dependent upon particular digenic allele combinations, could improve prediction of phenotype from complex genotype, but it is difficult to study in human populations. High throughput, systematic analysis of S. cerevisiae gene knockouts or knockdowns in the context of disease-relevant phenotypic perturbations provides a tractable experimental approach to derive gene interaction networks, in order to deduce by cross-species gene homology how phenotype is buffered against disease-risk genotypes. Yeast gene interaction network analysis to date has revealed biology more complex than previously imagined. This has motivated the development of more powerful yeast cell array phenotyping methods to globally model the role of gene interaction networks in modulating phenotypes (which we call yeast phenomic analysis). The article illustrates yeast phenomic technology, which is applied here to quantify gene X media interaction at higher resolution and supports use of a human-like media for future applications of yeast phenomics for modeling human disease.

Extension of Saccharomyces paradoxus chronological lifespan by retrotransposons in certain media conditions is associated with changes in reactive oxygen species

Retrotransposons are mobile DNA elements present throughout eukaryotic genomes that can cause mutations and genome rearrangements when they replicate through reverse transcription. Increased expression and/or mobility of retrotransposons has been correlated with aging in yeast, Caenorhabditis elegans, Drosophila melanogaster, and mammals. The many copies of retrotransposons in humans and various model organisms complicate further pursuit of this relationship. The Saccharomyces cerevisiae Ty1 retrotransposon was introduced into a strain of S. paradoxus that completely lacks retrotransposons to compare chronological lifespans (CLSs) of yeast strains with zero, low, or high Ty1 copy number. Yeast chronological lifespan reflects the progressive loss of cell viability in a nondividing state. Chronological lifespans for the strains were not different in rich medium, but were extended in high Ty1 copy-number strains in synthetic medium and in rich medium containing a low dose of hydroxyurea (HU), an agent that depletes deoxynucleoside triphosphates. Lifespan extension was not strongly correlated with Ty1 mobility or mutation rates for a representative gene. Buffering deoxynucleoside triphosphate levels with threonine supplementation did not substantially affect this lifespan extension, and no substantial differences in cell cycle arrest in the nondividing cells were observed. Lifespan extension was correlated with reduced reactive oxygen species during early stationary phase in high Ty1 copy strains, and antioxidant treatment allowed the zero Ty1 copy strain to live as long as high Ty1 copy-number strains in rich medium with hydroxyurea. This exceptional yeast system has identified an unexpected longevity-promoting role for retrotransposons that may yield novel insights into mechanisms regulating lifespan.

Threonine metabolism and embryonic stem cell self-renewal

PURPOSE OF REVIEW

Embryonic stem cells (ESCs) undergo unlimited self-renewal while maintaining a pluripotency, which is defined as the ability to develop into cells of all three embryonic germ layers. ESC self-renewal is characterized by special proliferative and epigenetic properties and a unique metabolic profile. One of the key features of this specialized nutritional metabolism is a stringent requirement for the amino acid threonine. Until recently, little was known about amino acid metabolism in stem cells beyond their general role in protein synthesis. Recent findings demonstrating a central role for threonine metabolism in multiple aspects of stem cell biology will be presented in this review.

RECENT FINDINGS

Amino acid catabolism supplies essential building blocks for biosynthetic pathways and for chemical modification of chromatin. In a series of recent studies employing combinative approaches of metabolomics, nutrition and genetics, the amino acid threonine was identified as an essential nutrient for mouse ESC (mESC). An unexpected finding from these studies was that in addition to its well known importance as protein precursor, threonine dehydrogenase-mediated threonine catabolism provides essential metabolic building blocks for use in multiple biosynthetic pathways and epigenetic modifications required for self-renewal and maintenance of pluripotency.

SUMMARY

Recent studies on threonine catabolism in mESCs suggest that amino acids can play both powerful biosynthetic and signaling roles in stem cells. These results described in mESCs should stimulate a new research area on the effect of amino acid metabolism in stem cell self-renewal and differentiation.

DNA replication stress-induced loss of reproductive capacity in S. cerevisiae and its inhibition by caloric restriction

In many organisms, attenuation of growth signaling by caloric restriction or mutational inactivation of growth signaling pathways extends lifespan and protects against cancer and other age-related diseases. The focus of many efforts to understand these effects has been on the induction of oxidative stress defenses that inhibit cellular senescence and cell death. Here we show that in the model organism S. cerevisiae, growth signaling induces entry of cells in stationary phase into S phase in parallel with loss of reproductive capacity, which is enhanced by elevated concentrations of glucose. Overexpression of RNR1 encoding a ribonucleotide reductase subunit required for the synthesis of deoxynucleotide triphosphates and DNA replication suppresses the accelerated loss of reproductive capacity of cells cultured in high glucose. The reduced reproductive capacity of these cells is also suppressed by excess threonine, which buffers dNTP pools when ribonucleotide reductase activity is limiting. Caloric restriction or inactivation of the AKT homolog Sch9p inhibits senescence and death in stationary phase cells caused by the DNA replication inhibitor hydroxyurea or by inactivation of the DNA replication and repair proteins Sgs1p or Rad27p. Inhibition of DNA replication stress represents a novel mechanism by which caloric restriction promotes longevity in S. cerevisiae. A similar mechanism may promote longevity and inhibit cancer and other age-related diseases in humans.

Mitochondrial signaling in Saccharomyces cerevisiae pseudohyphae formation induced by butanol

Yeasts growing limited for nitrogen source or treated with fusel alcohols form elongated cells--pseudohyphae. Absence of mitochondrial DNA or anaerobic conditions inhibits this process, but the precise role of mitochondria is not clear. We found that a significant percentage of pseudohyphal cells contained mitochondria with different levels of membrane potential within one cell. An uncoupler carbonyl cyanide p-(trifluoromethoxy) phenylhydrazone (FCCP), but not the ATP-synthase inhibitor oligomycin D, prevented pseudohyphal growth. Interestingly, repression of the MIH1 gene encoding phosphatase activator of the G2/M transition partially restores the ability of yeast to form pseudohyphal cells in the presence of FCCP or in the absence of mitochondrial DNA. At the same time, retrograde signaling (the one triggered by dysfunctional mitochondria) appeared to be a positive regulator of butanol-induced pseudohyphae formation: the deletion of any of the retrograde signaling genes (RTG1, RTG2, or RTG3) partially suppressed pseudohyphal growth. Together, our data suggest that two subpopulations of mitochondria are required for filamentous growth: one with high and another with low transmembrane potential. These mitochondria-activated signaling pathways appear to converge at Mih1p level.

A yeast phenomic model for the gene interaction network modulating CFTR-ΔF508 protein biogenesis

Background

The overall influence of gene interaction in human disease is unknown. In cystic fibrosis (CF) a single allele of the cystic fibrosis transmembrane conductance regulator (CFTR-ΔF508) accounts for most of the disease. In cell models, CFTR-ΔF508 exhibits defective protein biogenesis and degradation rather than proper trafficking to the plasma membrane where CFTR normally functions. Numerous genes function in the biogenesis of CFTR and influence the fate of CFTR-ΔF508. However it is not known whether genetic variation in such genes contributes to disease severity in patients. Nor is there an easy way to study how numerous gene interactions involving CFTR-ΔF would manifest phenotypically.

Methods

To gain insight into the function and evolutionary conservation of a gene interaction network that regulates biogenesis of a misfolded ABC transporter, we employed yeast genetics to develop a 'phenomic' model, in which the CFTR-ΔF508-equivalent residue of a yeast homolog is mutated (Yor1-ΔF670), and where the genome is scanned quantitatively for interaction. We first confirmed that Yor1-ΔF undergoes protein misfolding and has reduced half-life, analogous to CFTR-ΔF. Gene interaction was then assessed quantitatively by growth curves for approximately 5,000 double mutants, based on alteration in the dose response to growth inhibition by oligomycin, a toxin extruded from the cell at the plasma membrane by Yor1.

Results

From a comparative genomic perspective, yeast gene interactions influencing Yor1-ΔF biogenesis were representative of human homologs previously found to modulate processing of CFTR-ΔF in mammalian cells. Additional evolutionarily conserved pathways were implicated by the study, and a ΔF-specific pro-biogenesis function of the recently discovered ER membrane complex (EMC) was evident from the yeast screen. This novel function was validated biochemically by siRNA of an EMC ortholog in a human cell line expressing CFTR-ΔF508. The precision and accuracy of quantitative high throughput cell array phenotyping (Q-HTCP), which captures tens of thousands of growth curves simultaneously, provided powerful resolution to measure gene interaction on a phenomic scale, based on discrete cell proliferation parameters.

Conclusion

We propose phenomic analysis of Yor1-ΔF as a model for investigating gene interaction networks that can modulate cystic fibrosis disease severity. Although the clinical relevance of the Yor1-ΔF gene interaction network for cystic fibrosis remains to be defined, the model appears to be informative with respect to human cell models of CFTR-ΔF. Moreover, the general strategy of yeast phenomics can be employed in a systematic manner to model gene interaction for other diseases relating to pathologies that result from protein misfolding or potentially any disease involving evolutionarily conserved genetic pathways.

Microbial metabolic engineering for L-threonine production

L-threonine, one of the three major amino acids produced throughout the world, has a wide application in industry, as an additive or as a precursor for the biosynthesis of other chemicals. It is predominantly produced through microbial fermentation the efficiency of which largely depends on the quality of strains. Metabolic engineering based on a cogent understanding of the metabolic pathways of L-threonine biosynthesis and regulation provides an effective alternative to the traditional breeding for strain development. Continuing efforts have been made in revealing the mechanisms and regulation of L-threonine producing strains, as well as in metabolic engineering of suitable organisms whereby genetically-defined, industrially competitive L-threonine producing strains have been successfully constructed. This review focuses on the global metabolic and regulatory networks responsible for L-threonine biosynthesis, the molecular mechanisms of regulation, and the strategies employed in strain engineering.

DNA damage and DNA replication stress in yeast models of aging

DNA damage DNA damage is an important factor in aging in all eukaryotes. Although connections between DNA damage DNA damage and aging have been extensively investigated in complex organisms, only a relatively few studies have investigated DNA damage DNA damage as an aging factor in the model organism S. cerevisiae. Several of these studies point to DNA replication stress DNA replication stress as a cause of age-dependent DNA damage DNA damage in the replicative model of aging, which measures how many times budding yeast cells divide before they senesce and die. Even fewer studies have investigated how DNA damage DNA damage contributes to aging in the chronological aging chronological aging model, which measures how long cells in stationary phase cultures retain reproductive capacity. DNA replication stress DNA replication stress also has been implicated as a factor in chronological aging chronological aging . Since cells in stationary phase are generally considered to be "post-mitotic" and to reside in a quiescent G0/G1 state, the notion that defects in DNA replication might contribute to chronological aging chronological aging appears to be somewhat paradoxical. However, the results of recent studies suggest that a significant fraction of cells in stationary phase cultures are not quiescent, especially in experiments that employ defined medium, which is frequently employed to assess chronological lifespan. Most cells that fail to achieve quiescence remain in a viable, but non-dividing state until they eventually die, similar to the senescent state in mammalian cells. In this chapter we discuss the role of DNA damage DNA damage and DNA replication stress DNA replication stress in both replicative and chronological aging chronological aging in S. cerevisiae. We also discuss the relevance of these findings to the emerging view that DNA damage DNA damage and DNA replication stress DNA replication stress are important components of the senescent state that occurs at early stages of cancer.

Recursive expectation-maximization clustering: a method for identifying buffering mechanisms composed of phenomic modules

Interactions between genetic and/or environmental factors are ubiquitous, affecting the phenotypes of organisms in complex ways. Knowledge about such interactions is becoming rate-limiting for our understanding of human disease and other biological phenomena. Phenomics refers to the integrative analysis of how all genes contribute to phenotype variation, entailing genome and organism level information. A systems biology view of gene interactions is critical for phenomics. Unfortunately the problem is intractable in humans; however, it can be addressed in simpler genetic model systems. Our research group has focused on the concept of genetic buffering of phenotypic variation, in studies employing the single-cell eukaryotic organism, S. cerevisiae. We have developed a methodology, quantitative high throughput cellular phenotyping (Q-HTCP), for high-resolution measurements of gene-gene and gene-environment interactions on a genome-wide scale. Q-HTCP is being applied to the complete set of S. cerevisiae gene deletion strains, a unique resource for systematically mapping gene interactions. Genetic buffering is the idea that comprehensive and quantitative knowledge about how genes interact with respect to phenotypes will lead to an appreciation of how genes and pathways are functionally connected at a systems level to maintain homeostasis. However, extracting biologically useful information from Q-HTCP data is challenging, due to the multidimensional and nonlinear nature of gene interactions, together with a relative lack of prior biological information. Here we describe a new approach for mining quantitative genetic interaction data called recursive expectation-maximization clustering (REMc). We developed REMc to help discover phenomic modules, defined as sets of genes with similar patterns of interaction across a series of genetic or environmental perturbations. Such modules are reflective of buffering mechanisms, i.e., genes that play a related role in the maintenance of physiological homeostasis. To develop the method, 297 gene deletion strains were selected based on gene-drug interactions with hydroxyurea, an inhibitor of ribonucleotide reductase enzyme activity, which is critical for DNA synthesis. To partition the gene functions, these 297 deletion strains were challenged with growth inhibitory drugs known to target different genes and cellular pathways. Q-HTCP-derived growth curves were used to quantify all gene interactions, and the data were used to test the performance of REMc. Fundamental advantages of REMc include objective assessment of total number of clusters and assignment to each cluster a log-likelihood value, which can be considered an indicator of statistical quality of clusters. To assess the biological quality of clusters, we developed a method called gene ontology information divergence z-score (GOid_z). GOid_z summarizes total enrichment of GO attributes within individual clusters. Using these and other criteria, we compared the performance of REMc to hierarchical and K-means clustering. The main conclusion is that REMc provides distinct efficiencies for mining Q-HTCP data. It facilitates identification of phenomic modules, which contribute to buffering mechanisms that underlie cellular homeostasis and the regulation of phenotypic expression.

Phenotypic consequences of purine nucleotide imbalance in Saccharomyces cerevisiae

Coordinating homeostasis of multiple metabolites is a major task for living organisms, and complex interconversion pathways contribute to achieving the proper balance of metabolites. AMP deaminase (AMPD) is such an interconversion enzyme that allows IMP synthesis from AMP. In this article, we show that, under specific conditions, lack of AMPD activity impairs growth. Under these conditions, we found that the intracellular guanylic nucleotide pool was severely affected. In vivo studies of two AMPD homologs, Yjl070p and Ybr284p, indicate that these proteins have no detectable AMP, adenosine, or adenine deaminase activity; we show that overexpression of YJL070c instead mimics a loss of AMPD function. Expression of the yeast transcriptome was monitored in a AMPD-deficient mutant in a strain overexpressing YJL070c and in cells treated with the immunosuppressive drug mycophenolic acid, three conditions that lead to severe depletion of the guanylic nucleotide pool. These three conditions resulted in the up- or downregulation of multiple transcripts, 244 of which are common to at least two conditions and 71 to all three conditions. These transcriptome results, combined with specific mutant analysis, point to threonine metabolism as exquisitely sensitive to the purine nucleotide balance.

Dependence of mouse embryonic stem cells on threonine catabolism

Measurements of the abundance of common metabolites in cultured embryonic stem (ES) cells revealed an unusual state with respect to one-carbon metabolism. These findings led to the discovery of copious expression of the gene encoding threonine dehydrogenase (TDH) in ES cells. TDH-mediated catabolism of threonine takes place in mitochondria to generate glycine and acetyl-coenzyme A (CoA), with glycine facilitating one-carbon metabolism via the glycine cleavage system and acetyl-CoA feeding the tricarboxylic acid cycle. Culture media individually deprived of each of the 20 amino acids were applied to ES cells, leading to the discovery that ES cells are critically dependent on one amino acid--threonine. These observations show that ES cells exist in a high-flux backbone metabolic state comparable to that of rapidly growing bacterial cells.

Connecting extracellular metabolomic measurements to intracellular flux states in yeast

Background

Metabolomics has emerged as a powerful tool in the quantitative identification of physiological and disease-induced biological states. Extracellular metabolome or metabolic profiling data, in particular, can provide an insightful view of intracellular physiological states in a noninvasive manner.

Results

We used an updated genome-scale metabolic network model of Saccharomyces cerevisiae, iMM904, to investigate how changes in the extracellular metabolome can be used to study systemic changes in intracellular metabolic states. The iMM904 metabolic network was reconstructed based on an existing genome-scale network, iND750, and includes 904 genes and 1,412 reactions. The network model was first validated by comparing 2,888 in silico single-gene deletion strain growth phenotype predictions to published experimental data. Extracellular metabolome data measured in response to environmental and genetic perturbations of ammonium assimilation pathways was then integrated with the iMM904 network in the form of relative overflow secretion constraints and a flux sampling approach was used to characterize candidate flux distributions allowed by these constraints. Predicted intracellular flux changes were consistent with published measurements on intracellular metabolite levels and fluxes. Patterns of predicted intracellular flux changes could also be used to correctly identify the regions of the metabolic network that were perturbed.

Conclusion

Our results indicate that integrating quantitative extracellular metabolomic profiles in a constraint-based framework enables inferring changes in intracellular metabolic flux states. Similar methods could potentially be applied towards analyzing biofluid metabolome variations related to human physiological and disease states.

Buffering by gene duplicates: an analysis of molecular correlates and evolutionary conservation

Background

One mechanism to account for robustness against gene knockouts or knockdowns is through buffering by gene duplicates, but the extent and general correlates of this process in organisms is still a matter of debate. To reveal general trends of this process, we provide a comprehensive comparison of gene essentiality, duplication and buffering by duplicates across seven bacteria (Mycoplasma genitalium, Bacillus subtilis, Helicobacter pylori, Haemophilus influenzae, Mycobacterium tuberculosis, Pseudomonas aeruginosa, Escherichia coli), and four eukaryotes (Saccharomyces cerevisiae (yeast), Caenorhabditis elegans (worm), Drosophila melanogaster (fly), Mus musculus (mouse)).

Results

In nine of the eleven organisms, duplicates significantly increase chances of survival upon gene deletion (P-value ≤ 0.05), but only by up to 13%. Given that duplicates make up to 80% of eukaryotic genomes, the small contribution is surprising and points to dominant roles of other buffering processes, such as alternative metabolic pathways. The buffering capacity of duplicates appears to be independent of the degree of gene essentiality and tends to be higher for genes with high expression levels. For example, buffering capacity increases to 23% amongst highly expressed genes in E. coli. Sequence similarity and the number of duplicates per gene are weak predictors of the duplicate's buffering capacity. In a case study we show that buffering gene duplicates in yeast and worm are somewhat more similar in their functions than non-buffering duplicates and have increased transcriptional and translational activity.

Conclusion

In sum, the extent of gene essentiality and buffering by duplicates is not conserved across organisms and does not correlate with the organisms' apparent complexity. This heterogeneity goes beyond what would be expected from differences in experimental approaches alone. Buffering by duplicates contributes to robustness in several organisms, but to a small extent – and the relatively large amount of buffering by duplicates observed in yeast and worm may be largely specific to these organisms. Thus, the only common factor of buffering by duplicates between different organisms may be the by-product of duplicate retention due to demands of high dosage.

Stringent mating-type-regulated auxotrophy increases the accuracy of systematic genetic interaction screens with Saccharomyces cerevisiae mutant arrays

A genomic collection of haploid Saccharomyces cerevisiae deletion strains provides a unique resource for systematic analysis of gene interactions. Double-mutant haploid strains can be constructed by the synthetic genetic array (SGA) method, wherein a query mutation is introduced by mating to mutant arrays, selection of diploid double mutants, induction of meiosis, and selection of recombinant haploid double-mutant progeny. The mechanism of haploid selection is mating-type-regulated auxotrophy (MRA), by which prototrophy is restricted to a particular haploid genotype generated only as a result of meiosis. MRA escape leads to false-negative genetic interaction results because postmeiotic haploids that are supposed to be under negative selection instead proliferate and mate, forming diploids that are heterozygous at interacting loci, masking phenotypes that would be observed in a pure haploid double-mutant culture. This work identified factors that reduce MRA escape, including insertion of terminator and repressor sequences upstream of the MRA cassette, deletion of silent mating-type loci, and utilization of alpha-type instead of a-type MRA. Modifications engineered to reduce haploid MRA escape reduced false negative results in SGA-type analysis, resulting in >95% sensitivity for detecting gene-gene interactions.

A genetic screen for increased loss of heterozygosity in Saccharomyces cerevisiae

Loss of heterozygosity (LOH) can be a driving force in the evolution of mitotic/somatic diploid cells, and cellular changes that increase the rate of LOH have been proposed to facilitate this process. In the yeast Saccharomyces cerevisiae, spontaneous LOH occurs by a number of mechanisms including chromosome loss and reciprocal and nonreciprocal recombination. We performed a screen in diploid yeast to identify mutants with increased rates of LOH using the collection of homozygous deletion alleles of nonessential genes. Increased LOH was quantified at three loci (MET15, SAM2, and MAT) on three different chromosomes, and the LOH events were analyzed as to whether they were reciprocal or nonreciprocal in nature. Nonreciprocal LOH was further characterized as chromosome loss or truncation, a local mutational event (gene conversion or point mutation), or break-induced replication (BIR). The 61 mutants identified could be divided into several groups, including ones that had locus-specific effects. Mutations in genes involved in DNA replication and chromatin assembly led to LOH predominantly via reciprocal recombination. In contrast, nonreciprocal LOH events with increased chromosome loss largely resulted from mutations in genes implicated in kinetochore function, sister chromatid cohesion, or relatively late steps of DNA recombination. Mutants of genes normally involved in early steps of DNA damage repair and signaling produced nonreciprocal LOH without an increased proportion of chromosome loss. Altogether, this study defines a genetic landscape for the basis of increased LOH and the processes by which it occurs.