The chemical genomic portrait of yeast: uncovering a phenotype for all genes

Maintenance and expression of the S. cerevisiae mitochondrial genome--from genetics to evolution and systems biology

As a legacy of their endosymbiotic eubacterial origin, mitochondria possess a residual genome, encoding only a few proteins and dependent on a variety of factors encoded by the nuclear genome for its maintenance and expression. As a facultative anaerobe with well understood genetics and molecular biology, Saccharomyces cerevisiae is the model system of choice for studying nucleo-mitochondrial genetic interactions. Maintenance of the mitochondrial genome is controlled by a set of nuclear-coded factors forming intricately interconnected circuits responsible for replication, recombination, repair and transmission to buds. Expression of the yeast mitochondrial genome is regulated mostly at the post-transcriptional level, and involves many general and gene-specific factors regulating splicing, RNA processing and stability and translation. A very interesting aspect of the yeast mitochondrial system is the relationship between genome maintenance and gene expression. Deletions of genes involved in many different aspects of mitochondrial gene expression, notably translation, result in an irreversible loss of functional mtDNA. The mitochondrial genetic system viewed from the systems biology perspective is therefore very fragile and lacks robustness compared to the remaining systems of the cell. This lack of robustness could be a legacy of the reductive evolution of the mitochondrial genome, but explanations involving selective advantages of increased evolvability have also been postulated.

Roles for sphingolipids in Saccharomyces cerevisiae

Studies using Saccharomyces cerevisiae, the common baker's or brewer's yeast, have progressed over the past twenty years from knowing which sphingolipids are present in cells and a basic outline of how they are made to a complete or nearly complete directory of the genes that catalyze their anabolism and catabolism. In addition, cellular processes that depend upon sphingolipids have been identified including protein trafficking/exocytosis, endocytosis and actin cytoskeleton dynamics, membrane microdomains, calcium signaling, regulation of transcription and translation, cell cycle control, stress resistance, nutrient uptake and aging. These will be summarized here along with new data not previously reviewed. Advances in our knowledge of sphingolipids and their roles in yeast are impressive but molecular mechanisms remain elusive and are a primary challenge for further progress in understanding the specific functions of sphingolipids.

High-confidence mapping of chemical compounds and protein complexes reveals novel aspects of chemical stress response in yeast

Chemical genetics in yeast has shown great potential for clarifying the pharmacology of various drugs. Investigating these results from a systems perspective has uncovered many facets of natural chemical tolerance, but many cellular interactions of chemicals still remain poorly understood. To uncover previously overlooked players in resistance to chemical stress we integrated several independent chemical genetics datasets with protein-protein interactions and a comprehensive collection of yeast protein complexes. As a consequence we were able to identify the potential targets and mode of action of certain poorly understood compounds. However, most complexes recovered in our analysis appear to perform indirect roles in countering deleterious effects of chemicals by constituting an underlying intricate buffering system that has been so far under-appreciated. This buffering role appears to be largely contributed to by complexes pertaining to chromatin and vesicular dynamics. The former set of complexes seems to act by setting up or maintaining gene expression states necessary to protect the cell against chemical effects. Among the latter complexes we found an important role for specific vesicle tethering complexes in tolerating particular sets of compounds, indicating that different chemicals might be routed via different points in the intracellular trafficking system. We also suggest a general operational similarity between these complexes and molecular capacitors (e.g. the chaperone Hsp90). Both have a key role in increasing the system's robustness, although at different levels, through buffering stress and mutation, respectively. It is therefore conceivable that some of these complexes identified here might have roles in molding the evolution of chemical resistance and response.

Involvement of vacuolar sequestration and active transport in tolerance of Saccharomyces cerevisiae to hop iso-alpha-acids

The hop plant, Humulus lupulus L., has an exceptionally high content of secondary metabolites, the hop alpha-acids, which possess a range of beneficial properties, including antiseptic action. Studies performed on the mode of action of hop iso-alpha-acids have hitherto been restricted to lactic acid bacteria. The present study investigated molecular mechanisms of hop iso-alpha-acid resistance in the model eukaryote Saccharomyces cerevisiae. Growth inhibition occurred at concentrations of hop iso-alpha-acids that were an order of magnitude higher than those found with hop-tolerant prokaryotes. Chemostat-based transcriptome analysis and phenotype screening of the S. cerevisiae haploid gene deletion collection were used as complementary methods to screen for genes involved in hop iso-alpha-acid detoxification and tolerance. This screening and further analysis of deletion mutants confirmed that yeast tolerance to hop iso-alpha-acids involves three major processes, active proton pumping into the vacuole by the vacuolar-type ATPase to enable vacuolar sequestration of iso-alpha-acids and alteration of cell wall structure and, to a lesser extent, active export of iso-alpha-acids across the plasma membrane. Furthermore, iso-alpha-acids were shown to affect cellular metal homeostasis by acting as strong zinc and iron chelators.

Plant chemical genetics

The success of the genomics revolution to construct a genetic architecture of a variety of model organisms has placed functional biologists under pressure to show what each individual gene does in vivo. Traditionally, this task has fallen on geneticists who systematically perturb gene function and study the consequences. With the advent of large, easily accessible, small-molecule libraries and new methods of chemical synthesis, biologists now have new ways to probe gene function. Often called chemical genetics, this approach involves the screening of compounds that perturb a process of interest. In this scenario, each perturbing chemical is analogous to a specific mutation. Here, we summarize, with specific examples, how chemical genetics is being used in combination with traditional genetics to address problems in plant biology. Because chemical genetics is rooted in genetic analysis, we focus on how chemicals used in combination with genetics can be very powerful in dissecting a process of interest.

Genetics of taste and smell: poisons and pleasures

Eating is dangerous. While food contains nutrients and calories that animals need to produce heat and energy, it may also contain harmful parasites, bacteria, or chemicals. To guide food selection, the senses of taste and smell have evolved to alert us to the bitter taste of poisons and the sour taste and off-putting smell of spoiled foods. These sensory systems help people and animals to eat defensively, and they provide the brake that helps them avoid ingesting foods that are harmful. But choices about which foods to eat are motivated by more than avoiding the bad; they are also motivated by seeking the good, such as fat and sugar. However, just as not everyone is equally capable of sensing toxins in food, not everyone is equally enthusiastic about consuming high-fat, high-sugar foods. Genetic studies in humans and experimental animals strongly suggest that the liking of sugar and fat is influenced by genotype; likewise, the abilities to detect bitterness and the malodors of rotting food are highly variable among individuals. Understanding the exact genes and genetic differences that affect food intake may provide important clues in obesity treatment by allowing caregivers to tailor dietary recommendations to the chemosensory landscape of each person.

Genomic analysis of severe hypersensitivity to hygromycin B reveals linkage to vacuolar defects and new vacuolar gene functions in Saccharomyces cerevisiae

The vacuole of Saccharomyces cerevisiae has been a seminal model for studies of lysosomal trafficking, biogenesis, and function. Several yeast mutants defective in such vacuolar events have been unable to grow at low levels of hygromycin B, an aminoglycoside antibiotic. We hypothesized that such severe hypersensitivity to hygromycin B (hhy) is linked to vacuolar defects and performed a genomic screen for the phenotype using a haploid deletion strain library of non-essential genes. Fourteen HHY genes were initially identified and were subjected to bioinformatics analyses. The uncovered hhy mutants were experimentally characterized with respect to vesicular trafficking, vacuole morphology, and growth under various stress and drug conditions. The combination of bioinformatics analyses and phenotypic characterizations implicate defects in vesicular trafficking, vacuole fusion/fission, or vacuole function in all hhy mutants. The collection was enriched for sensitivity to monensin, indicative of vacuolar trafficking defects. Additionally, all hhy mutants showed severe sensitivities to rapamycin and caffeine, suggestive of TOR kinase pathway defects. Our experimental results also establish a new role in vacuolar and vesicular functions for two genes: PAF1, encoding a RNAP II-associated protein required for expression of cell cycle-regulated genes, and TPD3, encoding the regulatory subunit of protein phosphatase 2A. Thus, our results support linkage between severe hypersensitivity to hygromycin B and vacuolar defects.

A phenotypic profile of the Candida albicans regulatory network

Candida albicans is a normal resident of the gastrointestinal tract and also the most prevalent fungal pathogen of humans. It last shared a common ancestor with the model yeast Saccharomyces cerevisiae over 300 million years ago. We describe a collection of 143 genetically matched strains of C. albicans, each of which has been deleted for a specific transcriptional regulator. This collection represents a large fraction of the non-essential transcription circuitry. A phenotypic profile for each mutant was developed using a screen of 55 growth conditions. The results identify the biological roles of many individual transcriptional regulators; for many, this work represents the first description of their functions. For example, a quarter of the strains showed altered colony formation, a phenotype reflecting transitions among yeast, pseudohyphal, and hyphal cell forms. These transitions, which have been closely linked to pathogenesis, have been extensively studied, yet our work nearly doubles the number of transcriptional regulators known to influence them. As a second example, nearly a quarter of the knockout strains affected sensitivity to commonly used antifungal drugs; although a few transcriptional regulators have previously been implicated in susceptibility to these drugs, our work indicates many additional mechanisms of sensitivity and resistance. Finally, our results inform how transcriptional networks evolve. Comparison with the existing S. cerevisiae data (supplemented by additional S. cerevisiae experiments reported here) allows the first systematic analysis of phenotypic conservation by orthologous transcriptional regulators over a large evolutionary distance. We find that, despite the many specific wiring changes documented between these species, the general phenotypes of orthologous transcriptional regulator knockouts are largely conserved. These observations support the idea that many wiring changes affect the detailed architecture of the circuit, but not its overall output.

A key goal in the understanding of the biology of an organism is the description of the regulatory networks that control the expression of its genes. Changes in gene expression result in new cellular phenotypes that can be acted upon by evolutionary forces to influence the configuration of these networks. We have developed a phenotypic description of the transcriptional regulatory networks of the major fungal pathogen of humans, Candida albicans, by individually deleting genes that encode transcriptional regulators and observing the resulting phenotypes in a variety of environmental conditions. This approach provides insight into the biological roles of many previously uncharacterized regulators, and allows us to assign groups of regulators to specific biological roles, many of which are relevant to pathogenesis. For example, we identified groups of regulators that influenced sensitivity to antifungal drugs, the ability to acquire iron (a challenge for organisms in a human host), and the ability to form complex multi-cellular colonies. Our results also allow us to analyze how the phenotypes associated with transcriptional regulators change as organisms diverge. A comparison of C. albicans data with that from the well-characterized yeast S. cerevisiae revealed strong phenotypic conservation between related transcriptional regulators, despite the more than 300 million years which separate the species.

Uncovering genetic regulatory network divergence between duplicate genes using yeast eQTL landscape

Genetical genomics, a novel approach combining microarray technology and quantitative genetic analysis, aims to identify the expression quantitative trait loci (eQTLs), which may regulate the genome-wide expression pattern. In this article, we have studied yeast genomic eQTL data to investigate how the genetic eQTL regulation of ancestral gene has diverged since gene duplication. Our findings are as follows: (i) Duplicate genes have higher heritability for gene expression than single-copy genes, but little difference in their epistasis and directional effect. (ii) The divergence of trans-acting eQTLs between duplicate pairs increases with the evolutionary time since gene duplication. (iii) Trans-acting eQTL divergence can explain about 21% of the variation in expression divergence between duplicate pairs with K(S)<2.0, which increases to 27% when the transcription factor (TF)-target interaction divergence is combined. Moreover, under the partial correlation analysis, trans-acting eQTL divergence seems make a bigger contribution to expression divergence than does TF divergence. (iv) Trans-acting eQTL divergence between duplicate pairs is correlated with gene ontology categories "Biological processes" and "Cellular components," but not with "Molecular functions," and is related to fitness defect under treatment conditions, but not with fitness under normal condition. We conclude that eQTL analysis provides a novel approach to explore the effect of gene duplications on the genetic regulatory network.

Chemogenomic profiling predicts antifungal synergies

Chemotherapies, HIV infections, and treatments to block organ transplant rejection are creating a population of immunocompromised individuals at serious risk of systemic fungal infections. Since single-agent therapies are susceptible to failure due to either inherent or acquired resistance, alternative therapeutic approaches such as multi-agent therapies are needed. We have developed a bioinformatics-driven approach that efficiently predicts compound synergy for such combinatorial therapies. The approach uses chemogenomic profiles in order to identify compound profiles that have a statistically significant degree of similarity to a fluconazole profile. The compounds identified were then experimentally verified to be synergistic with fluconazole and with each other, in both Saccharomyces cerevisiae and the fungal pathogen Candida albicans. Our method is therefore capable of accurately predicting compound synergy to aid the development of combinatorial antifungal therapies.

Quantitative cell array screening to identify regulators of gene expression

In the last decade or so, advances in genome-scale technologies have allowed systematic and detailed analysis of gene function. The experimental accessibility of budding yeast makes it a test-bed for technology development and application of new functional genomic tools and resources that pave the way for comparable efforts in higher eukaryotes. In this article, we review advances in reporter screening technology to discover trans-acting regulators of promoters (or cis-elements) of interest in the context of a novel functional genomics approach called Reporter Synthetic Genetic Array (R-SGA) analysis. We anticipate that this methodology will enable researchers to collect quantitative data on hundreds of gene expression pathways in an effort to better understand transcriptional regulatory networks.

Evolving gene expression: from G to E to GxE

Analyses of gene expression data sets for multiple individuals and species promise to shed light on the mode of evolution of gene expression. However, complementary complexities challenge this goal. Characterization of the genetic variation underlying gene expression can easily be compromised by lack of environmental control. Conversely, the breadth of conclusions from studies of environmental effects has been limited by the use of single strains. Controlled studies have hinted at extensive genexenvironment interaction. Thus, both genetics and environment are key components in models of the evolution of gene expression. We review the literature on the evolution of gene expression in terms of genetics (G), environmental response (E) and GxE interactions to make this conceptual point.

Chromatin regulation and gene centrality are essential for controlling fitness pleiotropy in yeast

Background

There are a wide range of phenotypes that are due to loss-of-function or null mutations. Previously, the functions of gene products that distinguish essential from nonessential genes were characterized. However, the functions of products of non-essential genes that contribute to fitness remain minimally understood.

Principal Findings

Using data from Saccharomyces cerevisiae, we investigated several gene characteristics, which we are able to measure, that are significantly associated with a gene's fitness pleiotropy. Fitness pleiotropy is a measurement of the gene's importance to fitness. These characteristics include: 1) whether the gene's product functions in chromatin regulation, 2) whether the regulation of the gene is influenced by chromatin state, measured by chromatin regulation effect (CRE), 3) whether the gene's product functions as a transcription factor (TF) and the number of genes a TF regulates, 4) whether the gene contains TATA-box, and 5) whether the gene's product is central in a protein interaction network. Partial correlation analysis was used to study how these characteristics interact to influence fitness pleiotropy. We show that all five characteristics that were measured are statistically significantly associated with fitness pleiotropy. However, fitness pleiotropy is not associated with the presence of TATA-box when CRE is controlled. In particular, two characteristics: 1) whether the regulation of a gene is more likely to be influenced by chromatin state, and 2) whether the gene product is central in a protein interaction network measured by the number of protein interactions were found to play the most important roles affecting a gene's fitness pleiotropy.

Conclusions

These findings highlight the significance of both epigenetic gene regulation and protein interaction networks in influencing the fitness pleiotropy.

Haploid genetic screens in human cells identify host factors used by pathogens

Loss-of-function genetic screens in model organisms have elucidated numerous biological processes, but the diploid genome of mammalian cells has precluded large-scale gene disruption. We used insertional mutagenesis to develop a screening method to generate null alleles in a human cell line haploid for all chromosomes except chromosome 8. Using this approach, we identified host factors essential for infection with influenza and genes encoding important elements of the biosynthetic pathway of diphthamide, which are required for the cytotoxic effects of diphtheria toxin and exotoxin A. We also identified genes needed for the action of cytolethal distending toxin, including a cell-surface protein that interacts with the toxin. This approach has both conceptual and practical parallels with genetic approaches in haploid yeast.

Identifying and quantifying orphan protein sequences in fungi

For large regions of many proteins, and even entire proteins, no homology to known domains or proteins can be detected. These sequences are often referred to as orphans. Surprisingly, it has been reported that the large number of orphans is sustained in spite of a rapid increase of available genomic sequences. However, it is believed that de novo creation of coding sequences is rare in comparison to mechanisms such as domain shuffling and gene duplication; hence, most sequences should have homologs in other genomes. To investigate this, the sequences of 19 complete fungi genomes were compared. By using the phylogenetic relationship between these genomes, we could identify potentially de novo created orphans in Saccharomyces cerevisiae. We found that only a small fraction, <2%, of the S. cerevisiae proteome is orphan, which confirms that de novo creation of coding sequences is indeed rare. Furthermore, we found it necessary to compare the most closely related species to distinguish between de novo created sequences and rapidly evolving sequences where homologs are present but cannot be detected. Next, the orphan proteins (OPs) and orphan domains (ODs) were characterized. First, it was observed that both OPs and ODs are short. In addition, at least some of the OPs have been shown to be functional in experimental assays, showing that they are not pseudogenes. Furthermore, in contrast to what has been reported before and what is seen for older orphans, S. cerevisiae specific ODs and proteins are not more disordered than other proteins. This might indicate that many of the older, and earlier classified, orphans indeed are fast-evolving sequences. Finally, >90% of the detected ODs are located at the protein termini, which suggests that these orphans could have been created by mutations that have affected the start or stop codons.

CYSTM, a novel cysteine-rich transmembrane module with a role in stress tolerance across eukaryotes

Using sensitive sequence profile analysis, we identify a hitherto uncharacterized cysteine-rich, transmembrane (TM) module, CYSTM, found in a wide range of tail-anchored membrane proteins across eukaryotes. This superfamily includes Schizosaccharomyces Uvi15, Arabidopsis PCC1, Digtaria CDT1 and Saccharomyces proteins YDL012C and YDR210W, which have all been implicated in resistance/response to stress or pathogens. Based on the pattern of conserved cysteines and data from different chemical genetics studies, we suggest that CYSTM proteins might have critical role in responding to deleterious compounds at the plasma membrane via chelation or redox-based mechanisms. Thus, CYSTM proteins are likely to be part of a novel cellular protective mechanism that is widely active in eukaryotes, including humans.

Contact:aravind@ncbi.nih.gov

Supplementary Information:Supplementary data are available at Bioinformatics online.

A yeast killer toxin screen provides insights into a/b toxin entry, trafficking, and killing mechanisms

Like Ricin, Shiga, and Cholera toxins, yeast K28 is an A/B toxin that depends on endocytosis and retrograde trafficking for toxicity. Knowledge of the specific proteins, lipids, and mechanisms required for trafficking and killing by these toxins remains incomplete. Since K28 is a model for clinically relevant toxins, we screened over 5000 yeast mutants, identifying 365 that affect K28 sensitivity. Hypersensitive mutants revealed cytoprotective pathways, including stress-activated signaling and protein degradation. Resistant mutants clustered to endocytic, lipid organization, and cell wall biogenesis pathways. Furthermore, GPI anchors and transcriptional regulation are important for K28-cell binding. Strikingly, the AP2 complex, which in metazoans links endocytic cargo to the clathrin coat, but had no assigned function in yeast, was critical for K28 toxicity. Yeast AP2 localizes to endocytic sites and has a cargo-specific function in K28 uptake. This comprehensive genetic analysis identified conserved processes important for A/B toxin trafficking and killing.

A combined-cross analysis reveals genes with drug-specific and background-dependent effects on drug sensitivity in Saccharomyces cerevisiae

Effective pharmacological therapy is often inhibited by variable drug responses and adverse drug reactions. Dissecting the molecular basis of different drug responses is difficult due to complex interactions involving multiple genes, pathways, and cellular processes. We previously found a single nucleotide polymorphism within cystathionine beta-synthase (CYS4) that causes multi-drug sensitivity in a vineyard strain of Saccharomyces cerevisiae. However, not all variation was accounted for by CYS4. To identify additional genes influencing drug sensitivity, we used CYS4 as a covariate and conducted both single- and combined-cross linkage mapping. After eliminating numerous false-positive associations, we identified 16 drug-sensitivity loci, only 3 of which had been previously identified. Of 4 drug-sensitivity loci selected for validation, 2 showed replicated associations in independent crosses, and two quantitative trait genes within these regions, AQY1 and MKT1, were found to have drug-specific and background-dependent effects. Our results suggest that drug response may often depend on interactions between genes with multi-drug and drug-specific effects.

Harnessing gene expression to identify the genetic basis of drug resistance

The advent of cost-effective genotyping and sequencing methods have recently made it possible to ask questions that address the genetic basis of phenotypic diversity and how natural variants interact with the environment. We developed Camelot (CAusal Modelling with Expression Linkage for cOmplex Traits), a statistical method that integrates genotype, gene expression and phenotype data to automatically build models that both predict complex quantitative phenotypes and identify genes that actively influence these traits. Camelot integrates genotype and gene expression data, both generated under a reference condition, to predict the response to entirely different conditions. We systematically applied our algorithm to data generated from a collection of yeast segregants, using genotype and gene expression data generated under drug-free conditions to predict the response to 94 drugs and experimentally confirmed 14 novel gene-drug interactions. Our approach is robust, applicable to other phenotypes and species, and has potential for applications in personalized medicine, for example, in predicting how an individual will respond to a previously unseen drug.

Nutritional systems biology: definitions and approaches

Nutrigenetics and nutrigenomics are nascent areas that are evolving quickly and riding on the wave of "personalized medicine" that is providing opportunities in the discovery and development of nutraceutical compounds. The human genome sequence and sequences of model organisms provide the equivalent of comprehensive blueprints and parts lists that describe dynamic networks and the bases for understanding their responses to external and internal perturbations. Unfolding the interrelationships among genes, gene products, and dietary habits is fundamental for identifying individuals who will benefit most from, or be placed at risk by, intervention strategies. More accurate assessment of the inputs to human health and the consequences of those inputs measured as accurate transcriptomic, proteomic, and metabolomic analyses would bring personalized health/diet to practice far faster than would waiting for a predictive knowledge of genetic variation. It is widely recognized that systems and network biology has the potential to increase our understanding of how nutrition influences metabolic pathways and homeostasis, how this regulation is disturbed in a diet-related disease, and to what extent individual genotypes contribute to such diseases.

Target profiling of small molecules by chemical proteomics

The medical and pharmaceutical communities are facing a dire need for new druggable targets, while, paradoxically, the targets of some drugs that are in clinical use or development remain elusive. Many compounds have been found to be more promiscuous than originally anticipated, which can potentially lead to side effects, but which may also open up additional medical uses. As we move toward systems biology and personalized medicine, comprehensively determining small molecule-target interaction profiles and mapping these on signaling and metabolic pathways will become increasingly necessary. Chemical proteomics is a powerful mass spectrometry-based affinity chromatography approach for identifying proteome-wide small molecule-protein interactions. Here we will provide a critical overview of the basic concepts and recent advances in chemical proteomics and review recent applications, with a particular emphasis on kinase inhibitors and natural products.

Explorations in topology-delving underneath the surface of genetic interaction maps

High throughput assays, as well as advances in computational approaches, have recently allowed the acquisition of vast amounts of genetic interaction (GI) data in several organisms. Since GIs are a functional measure that reports on the effect of a mutation in one gene on the phenotype of a mutation in another, they can serve as a powerful tool to study both the function of individual genes and the wiring of biological networks. Therefore, these data hold much promise for advancing our understanding of cellular systems. In this review we focus on the methodologies currently available for using and interpreting large datasets of GIs for functional gene groups (GI maps), and elaborate on the challenges ahead. In addition, we discuss potential applications for the study of evolution and disease mechanisms, and highlight the need for comprehensive integrative analysis to extract the wealth of information found in these maps.

Identifying druggable disease-modifying gene products

Many disease genes encode proteins that are difficult to target directly using small molecule drugs. Improvements in libraries based on synthetic compounds, natural products, and other types of molecules may ultimately allow some challenging proteins to be successfully targeted; however, these developments alone are unlikely to be sufficient. A complementary strategy exploits the functional interconnectivity of intracellular networks to find druggable targets lying upstream, downstream, or in parallel to a disease-causing gene, where modulation can influence the disease process indirectly. These targets can be selected using prior knowledge of disease-associated pathways or identified using phenotypic chemical and genetic screens in model organisms and cells. These approaches should facilitate the identification of effective drug targets for many genetic disorders.

Systems-level approaches for identifying and analyzing genetic interaction networks in Escherichia coli and extensions to other prokaryotes

Molecular interactions define the functional organization of the cell. Epistatic (genetic, or gene-gene) interactions, one of the most informative and commonly encountered forms of functional relationships, are increasingly being used to map process architecture in model eukaryotic organisms. In particular, 'systems-level' screens in yeast and worm aimed at elucidating genetic interaction networks have led to the generation of models describing the global modular organization of gene products and protein complexes within a cell. However, comparable data for prokaryotic organisms have not been available. Given its ease of growth and genetic manipulation, the Gram-negative bacterium Escherichia coli appears to be an ideal model system for performing comprehensive genome-scale examinations of genetic redundancy in bacteria. In this review, we highlight emerging experimental and computational techniques that have been developed recently to examine functional relationships and redundancy in E. coli at a systems-level, and their potential application to prokaryotes in general. Additionally, we have scanned PubMed abstracts and full-text published articles to manually curate a list of approximately 200 previously reported synthetic sick or lethal genetic interactions in E. coli derived from small-scale experimental studies.

Significant bias against the ACA triplet in the tmRNA sequence of Escherichia coli K-12

The toxin MazF in Escherichia coli cleaves single-stranded RNAs specifically at ACA sequences. MazF overexpression virtually eliminates all cellular mRNAs to completely block protein synthesis. However, protein synthesis can continue on an mRNA that is devoid of ACA triplets. The finding that ribosomal RNAs remain intact in the face of complete translation arrest suggested a purpose for such preservation. We therefore examined the sequences of all transcribed RNAs to determine if there was any statistically significant bias against ACA. While ACA motifs are absent from tmRNA, 4.5S RNA, and seven of the eight 5S rRNAs, statistical analysis revealed that only for tmRNA was the absence nonrandom. The introduction of single-strand ACAs makes tmRNA highly susceptible to MazF cleavage. Furthermore, analysis of tmRNA sequences from 442 bacteria showed that the discrimination against ACA in tmRNAs was seen mostly in enterobacteria. We propose that the unusual bias against ACA in tmRNA may have coevolved with the acquisition of MazF.

Genome-wide identification of Saccharomyces cerevisiae genes required for maximal tolerance to ethanol

The understanding of the molecular basis of yeast resistance to ethanol may guide the design of rational strategies to increase process performance in industrial alcoholic fermentations. In this study, the yeast disruptome was screened for mutants with differential susceptibility to stress induced by high ethanol concentrations in minimal growth medium. Over 250 determinants of resistance to ethanol were identified. The most significant gene ontology terms enriched in this data set are those associated with intracellular organization, biogenesis, and transport, in particular, regarding the vacuole, the peroxisome, the endosome, and the cytoskeleton, and those associated with the transcriptional machinery. Clustering the proteins encoded by the identified determinants of ethanol resistance by their known physical and genetic interactions highlighted the importance of the vacuolar protein sorting machinery, the vacuolar H(+)-ATPase complex, and the peroxisome protein import machinery. Evidence showing that vacuolar acidification and increased resistance to the cell wall lytic enzyme beta-glucanase occur in response to ethanol-induced stress was obtained. Based on the genome-wide results, the particular role of the FPS1 gene, encoding a plasma membrane aquaglyceroporin which mediates controlled glycerol efflux, in ethanol stress resistance was further investigated. FPS1 expression contributes to decreased [(3)H]ethanol accumulation in yeast cells, suggesting that Fps1p may also play a role in maintaining the intracellular ethanol level during active fermentation. The increased expression of FPS1 confirmed the important role of this gene in alcoholic fermentation, leading to increased final ethanol concentration under conditions that lead to high ethanol production.

Biological and chemical approaches to diseases of proteostasis deficiency

Many diseases appear to be caused by the misregulation of protein maintenance. Such diseases of protein homeostasis, or "proteostasis," include loss-of-function diseases (cystic fibrosis) and gain-of-toxic-function diseases (Alzheimer's, Parkinson's, and Huntington's disease). Proteostasis is maintained by the proteostasis network, which comprises pathways that control protein synthesis, folding, trafficking, aggregation, disaggregation, and degradation. The decreased ability of the proteostasis network to cope with inherited misfolding-prone proteins, aging, and/or metabolic/environmental stress appears to trigger or exacerbate proteostasis diseases. Herein, we review recent evidence supporting the principle that proteostasis is influenced both by an adjustable proteostasis network capacity and protein folding energetics, which together determine the balance between folding efficiency, misfolding, protein degradation, and aggregation. We review how small molecules can enhance proteostasis by binding to and stabilizing specific proteins (pharmacologic chaperones) or by increasing the proteostasis network capacity (proteostasis regulators). We propose that such therapeutic strategies, including combination therapies, represent a new approach for treating a range of diverse human maladies.

Quantitative phenotyping via deep barcode sequencing

Next-generation DNA sequencing technologies have revolutionized diverse genomics applications, including de novo genome sequencing, SNP detection, chromatin immunoprecipitation, and transcriptome analysis. Here we apply deep sequencing to genome-scale fitness profiling to evaluate yeast strain collections in parallel. This method, Barcode analysis by Sequencing, or "Bar-seq," outperforms the current benchmark barcode microarray assay in terms of both dynamic range and throughput. When applied to a complex chemogenomic assay, Bar-seq quantitatively identifies drug targets, with performance superior to the benchmark microarray assay. We also show that Bar-seq is well-suited for a multiplex format. We completely re-sequenced and re-annotated the yeast deletion collection using deep sequencing, found that approximately 20% of the barcodes and common priming sequences varied from expectation, and used this revised list of barcode sequences to improve data quality. Together, this new assay and analysis routine provide a deep-sequencing-based toolkit for identifying gene-environment interactions on a genome-wide scale.

Exploiting gene deletion fitness effects in yeast to understand the modular architecture of protein complexes under different growth conditions

Background

Understanding how individual genes contribute towards the fitness of an organism is a fundamental problem in biology. Although recent genome-wide screens have generated abundant data on quantitative fitness for single gene knockouts, very few studies have systematically integrated other types of biological information to understand how and why deletion of specific genes give rise to a particular fitness effect. In this study, we combine quantitative fitness data for single gene knock-outs in yeast with large-scale interaction discovery experiments to understand the effect of gene deletion on the modular architecture of protein complexes, under different growth conditions.

Results

Our analysis reveals that genes in complexes show more severe fitness effects upon deletion than other genes but, in contrast to what has been observed in binary protein-protein interaction networks, we find that this is not related to the number of complexes in which they are present. We also find that, in general, the core and attachment components of protein complexes are equally important for the complex machinery to function. However, when quantifying the importance of core and attachments in single complex variations, or isoforms, we observe that this global trend originates from either the core or the attachment components being more important for strain fitness, both being equally important or both being dispensable. Finally, our study reveals that different isoforms of a complex can exhibit distinct fitness patterns across growth conditions.

Conclusion

This study presents a powerful approach to unveil the molecular basis for various complex phenotypic profiles observed in gene deletion experiments. It also highlights some interesting cases of potential functional compensation between protein paralogues and suggests a new piece to fit into the histone-code puzzle.

Genetic and epigenetic heterogeneity in cancer: a genome-centric perspective

Genetic and epigenetic heterogeneity (the main form of non-genetic heterogeneity) are key elements in cancer progression and drug resistance, as they provide needed population diversity, complexity, and robustness. Despite drastically increased evidence of multiple levels of heterogeneity in cancer, the general approach has been to eliminate the "noise" of heterogeneity to establish genetic and epigenetic patterns. In particular, the appreciation of new types of epigenetic regulation like non-coding RNA, have led to the hope of solving the mystery of cancer that the current genetic theories seem to be unable to achieve. In this mini-review, we have briefly analyzed a number of mis-conceptions regarding cancer heterogeneity, followed by the re-evaluation of cancer heterogeneity within a framework of the genome-centric concept of evolution. The analysis of the relationship between gene, epigenetic and genome level heterogeneity, and the challenges of measuring heterogeneity among multiple levels have been discussed. Further, we propose that measuring genome level heterogeneity represents an effective strategy in the study of cancer and other types of complex diseases, as emphasis on the pattern of system evolution rather than specific pathways provides a global and synthetic approach. Compared to the degree of heterogeneity, individual molecular pathways will have limited predictability during stochastic cancer evolution where genome dynamics (reflected by karyotypic heterogeneity) will dominate.

Identification of deleterious mutations within three human genomes

Each human carries a large number of deleterious mutations. Together, these mutations make a significant contribution to human disease. Identification of deleterious mutations within individual genome sequences could substantially impact an individual's health through personalized prevention and treatment of disease. Yet, distinguishing deleterious mutations from the massive number of nonfunctional variants that occur within a single genome is a considerable challenge. Using a comparative genomics data set of 32 vertebrate species we show that a likelihood ratio test (LRT) can accurately identify a subset of deleterious mutations that disrupt highly conserved amino acids within protein-coding sequences, which are likely to be unconditionally deleterious. The LRT is also able to identify known human disease alleles and performs as well as two commonly used heuristic methods, SIFT and PolyPhen. Application of the LRT to three human genomes reveals 796-837 deleterious mutations per individual, approximately 40% of which are estimated to be at <5% allele frequency. However, the overlap between predictions made by the LRT, SIFT, and PolyPhen, is low; 76% of predictions are unique to one of the three methods, and only 5% of predictions are shared across all three methods. Our results indicate that only a small subset of deleterious mutations can be reliably identified, but that this subset provides the raw material for personalized medicine.

Alternative splicing of PTC7 in Saccharomyces cerevisiae determines protein localization

It is well established that higher eukaryotes use alternative splicing to increase proteome complexity. In contrast, Saccharomyces cerevisiae, a single-cell eukaryote, conducts predominantly regulated splicing through retention of nonfunctional introns. In this article we describe our discovery of a functional intron in the PTC7 (YHR076W) gene that can be alternatively spliced to create two mRNAs that code for distinct proteins. These two proteins localize to different cellular compartments and have distinct cellular roles. The protein translated from the spliced mRNA localizes to the mitochondria and its expression is carbon-source dependent. In comparison, the protein translated from the unspliced mRNA contains a transmembrane domain, localizes to the nuclear envelope, and mediates the toxic effects of Latrunculin A exposure. In conclusion, we identified a definitive example of functional alternative splicing in S. cerevisiae that confers a measurable fitness benefit.

Biofilm matrix regulation by Candida albicans Zap1

A biofilm is a surface-associated population of microorganisms embedded in a matrix of extracellular polymeric substances. Biofilms are a major natural growth form of microorganisms and the cause of pervasive device-associated infection. This report focuses on the biofilm matrix of Candida albicans, the major fungal pathogen of humans. We report here that the C. albicans zinc-response transcription factor Zap1 is a negative regulator of a major matrix component, soluble beta-1,3 glucan, in both in vitro and in vivo biofilm models. To understand the mechanistic relationship between Zap1 and matrix, we identified Zap1 target genes through expression profiling and full genome chromatin immunoprecipitation. On the basis of these results, we designed additional experiments showing that two glucoamylases, Gca1 and Gca2, have positive roles in matrix production and may function through hydrolysis of insoluble beta-1,3 glucan chains. We also show that a group of alcohol dehydrogenases Adh5, Csh1, and Ifd6 have roles in matrix production: Adh5 acts positively, and Csh1 and Ifd6, negatively. We propose that these alcohol dehydrogenases generate quorum-sensing aryl and acyl alcohols that in turn govern multiple events in biofilm maturation. Our findings define a novel regulatory circuit and its mechanism of control of a process central to infection.

Cordycepin interferes with 3' end formation in yeast independently of its potential to terminate RNA chain elongation

Cordycepin (3' deoxyadenosine) is a biologically active compound that, when incorporated during RNA synthesis in vitro, provokes chain termination due to the absence of a 3' hydroxyl moiety. We were interested in the effects mediated by this drug in vivo and analyzed its impact on RNA metabolism of yeast. Our results support the view that cordycepin-triphosphate (CoTP) is the toxic component that is limiting cell growth through inhibition of RNA synthesis. Unexpectedly, cordycepin treatment modulated 3' end heterogeneity of ACT1 and ASC1 mRNAs and rapidly induced extended transcripts derived from CYH2 and NEL025c loci. Moreover, cordycepin ameliorated the growth defects of poly(A) polymerase mutants and the pap1-1 mutation neutralized the effects of the drug on gene expression. Our observations are consistent with an epistatic relationship between poly(A) polymerase function and cordycepin action and suggest that a major mode of cordycepin activity reduces 3' end formation efficiency independently of its potential to terminate RNA chain elongation. Finally, chemical-genetic profiling revealed genome-wide pathways linked to cordycepin activity and identified novel genes involved in poly(A) homeostasis.

Abundant indispensable redundancies in cellular metabolic networks

Cellular life is a highly redundant complex system; yet, the evolutionary maintenance of the redundancy remains unexplained. Using a systems biology approach, we infer that 37-47% of metabolic reactions in Escherichia coli and yeast can be individually removed without blocking the production of any biomass component under any nutritional condition. However, the majority of these redundant reactions are preserved because they have differential maximal efficiencies at different conditions or their loss causes an immediate fitness reduction that can only be regained via mutation, drift, and selection in evolution. The remaining redundancies are attributable to pleiotropic effects or recent horizontal gene transfers. We find that E. coli and yeast exhibit opposite relationships between the functional importance and redundancy level of a reaction, which is inconsistent with the conjecture that redundancies are preserved as an adaptation to back up important parts in the system. Interestingly, the opposite relationships can both be recapitulated by a simple model in which the natural environments of the organisms change frequently. Thus, adaptive backup is neither necessary nor sufficient to explain the high redundancy of cellular metabolic networks. Taken together, our results strongly suggest that redundant reactions are not kept as backups and that the genetic robustness of metabolic networks is an evolutionary by-product.

A systematic survey identifies prions and illuminates sequence features of prionogenic proteins

Prions are proteins that convert between structurally and functionally distinct states, one or more of which is transmissible. In yeast, this ability allows them to act as non-Mendelian elements of phenotypic inheritance. To further our understanding of prion biology, we conducted a bioinformatic proteome-wide survey for prionogenic proteins in S. cerevisiae, followed by experimental investigations of 100 prion candidates. We found an unexpected amino acid bias in aggregation-prone candidates and discovered that 19 of these could also form prions. At least one of these prion proteins, Mot3, produces a bona fide prion in its natural context that increases population-level phenotypic heterogeneity. The self-perpetuating states of these proteins present a vast source of heritable phenotypic variation that increases the adaptability of yeast populations to diverse environments.

Low frequency of mutations with strongly deleterious but nonlethal fitness effects

Most experimentally detectable effects of mutations in cellular organisms are either lethal or mildly deleterious. A possible explanation for the paucity of strongly detrimental but nonlethal mutations is that the processes constituting cellular metabolism are either essential or largely redundant. Alternatively, the partition between lethal and inconspicuous mutations exists within important biological processes. To test this, we measured maximum growth rates of yeast strains each carrying the deletion of a single gene in one of 38 protein complexes. We also used relevant data from previous high-throughput phenotypic studies of the yeast gene-deletion collection. The complexes typified well-defined sets of genes engaged in a common process. Within virtually all essential complexes there were two clear modes of phenotypic effects, that is the cessation of growth or slowdown of growth by a few percent. This uniformity is striking given that complexes differ extensively in function, size, and proportion of essential proteins. The pattern of bimodality is observed both under optimal and suboptimal environmental conditions. The generic paucity of strong effects and abundance of small ones relates to the feasibility of analyses of quantitative traits and epidemiological surveys, irrespective of the particular element of metabolism under study.

Vaccinating with the genome: a Sisyphean task?

Human trials of subunit vaccines against the asexual blood stage of malaria are yielding disappointing results, supporting the premise that a single recombinant protein will not be particularly efficacious and that additional proteins must be added. The genome sequence of Plasmodium falciparum offers a large number of additional candidates, but which should be chosen? Various criteria have been suggested to rank the additional candidates, but in the absence of even a partially effective asexual-stage vaccine, the criteria remain unvalidated. These issues are discussed here, together with some suggestions as to how the development of an asexual-stage vaccine could be progressed.

A molecular barcoded yeast ORF library enables mode-of-action analysis of bioactive compounds

We present a yeast chemical-genomics approach designed to identify genes that when mutated confer drug resistance, thereby providing insight about the modes of action of compounds. We developed a molecular barcoded yeast open reading frame (MoBY-ORF) library in which each gene, controlled by its native promoter and terminator, is cloned into a centromere-based vector along with two unique oligonucleotide barcodes. The MoBY-ORF resource has numerous genetic and chemical-genetic applications, but here we focus on cloning wild-type versions of mutant drug-resistance genes using a complementation strategy and on simultaneously assaying the fitness of all transformants with barcode microarrays. The complementation cloning was validated by mutation detection using whole-genome yeast tiling microarrays, which identified unique polymorphisms associated with a drug-resistant mutant. We used the MoBY-ORF library to identify the genetic basis of several drug-resistant mutants and in this analysis discovered a new class of sterol-binding compounds.

Precise gene-dose alleles for chemical genetics

Modulating gene dose is an effective way to alter protein levels and modify phenotypes to understand gene function. In addition, combining gene-dose alleles with chemical perturbation can provide insight into drug-gene interactions. Here, we present a strategy that combines diverse loss-of-function alleles to systematically modulate gene dose in Saccharomyces cerevisiae. The generated gene dosage allele set expands the genetic toolkit for uncovering novel phenotypes.

Reconstructing the ubiquitin network: cross-talk with other systems and identification of novel functions

A computational model of the yeast Ubiquitin system highlights interesting biological features including functional interactions between components and interplay with other regulatory mechanisms.

Background

The ubiquitin system (Ub-system) can be defined as the ensemble of components including Ub/ubiquitin-like proteins, their conjugation and deconjugation apparatus, binding partners and the proteasomal system. While several studies have concentrated on structure-function relationships and evolution of individual components of the Ub-system, a study of the system as a whole is largely lacking.

Results

Using numerous genome-scale datasets, we assemble for the first time a comprehensive reconstruction of the budding yeast Ub-system, revealing static and dynamic properties. We devised two novel representations, the rank plot to understand the functional diversification of different components and the clique-specific point-wise mutual-information network to identify significant interactions in the Ub-system.

Conclusions

Using these representations, evidence is provided for the functional diversification of components such as SUMO-dependent Ub-ligases. We also identify novel components of SCF (Skp1-cullin-F-box)-dependent complexes, receptors in the ERAD (endoplasmic reticulum associated degradation) system and a key role for Sus1 in coordinating multiple Ub-related processes in chromatin dynamics. We present evidence for a major impact of the Ub-system on large parts of the proteome via its interaction with the transcription regulatory network. Furthermore, the dynamics of the Ub-network suggests that Ub and SUMO modifications might function cooperatively with transcription control in regulating cell-cycle-stage-specific complexes and in reinforcing periodicities in gene expression. Combined with evolutionary information, the structure of this network helps in understanding the lineage-specific expansion of SCF complexes with a potential role in pathogen response and the origin of the ERAD and ESCRT systems.

Genetic basis of arsenite and cadmium tolerance in Saccharomyces cerevisiae

Background

Arsenic and cadmium are widely distributed in nature and pose serious threats to the environment and human health. Exposure to these nonessential toxic metals may result in a variety of human diseases including cancer. However, arsenic and cadmium toxicity targets and the cellular systems contributing to tolerance acquisition are not fully known.

Results

To gain insight into metal action and cellular tolerance mechanisms, we carried out genome-wide screening of the Saccharomyces cerevisiae haploid and homozygous diploid deletion mutant collections and scored for reduced growth in the presence of arsenite or cadmium. Processes found to be required for tolerance to both metals included sulphur and glutathione biosynthesis, environmental sensing, mRNA synthesis and transcription, and vacuolar/endosomal transport and sorting. We also identified metal-specific defence processes. Arsenite-specific defence functions were related to cell cycle regulation, lipid and fatty acid metabolism, mitochondrial biogenesis, and the cytoskeleton whereas cadmium-specific defence functions were mainly related to sugar/carbohydrate metabolism, and metal-ion homeostasis and transport. Molecular evidence indicated that the cytoskeleton is targeted by arsenite and that phosphorylation of the Snf1p kinase is required for cadmium tolerance.

Conclusion

This study has pin-pointed core functions that protect cells from arsenite and cadmium toxicity. It also emphasizes the existence of both common and specific defence systems. Since many of the yeast genes that confer tolerance to these agents have homologues in humans, similar biological processes may act in yeast and humans to prevent metal toxicity and carcinogenesis.