Interactions In Yeast Research Articles

Quantitative maps of genetic interactions in yeast - Comparative evaluation and integrative analysis

BackgroundHigh-throughput genetic screening approaches have enabled systematic means to study how interactions among gene mutations contribute to quantitative fitness phenotypes, with the aim of providing insights into the functional wiring diagrams of genetic interaction networks on a global scale. However, it is poorly known how well these quantitative interaction measurements agree across the screening approaches, which hinders their integrated use toward improving the coverage and quality of the genetic interaction maps in yeast and other organisms.ResultsUsing large-scale data matrices from epistatic miniarray profiling (E-MAP), genetic interaction mapping (GIM), and synthetic genetic array (SGA) approaches, we carried out here a systematic comparative evaluation among these quantitative maps of genetic interactions in yeast. The relatively low association between the original interaction measurements or their customized scores could be improved using a matrix-based modelling framework, which enables the use of single- and double-mutant fitness estimates and measurements, respectively, when scoring genetic interactions. Toward an integrative analysis, we show how the detections from the different screening approaches can be combined to suggest novel positive and negative interactions which are complementary to those obtained using any single screening approach alone. The matrix approximation procedure has been made available to support the design and analysis of the future screening studies.ConclusionsWe have shown here that even if the correlation between the currently available quantitative genetic interaction maps in yeast is relatively low, their comparability can be improved by means of our computational matrix approximation procedure, which will enable integrative analysis and detection of a wider spectrum of genetic interactions using data from the complementary screening approaches.

Cross‐species discovery of syncretic drug combinations that potentiate the antifungal fluconazole

Resistance to widely used fungistatic drugs, particularly to the ergosterol biosynthesis inhibitor fluconazole, threatens millions of immunocompromised patients susceptible to invasive fungal infections. The dense network structure of synthetic lethal genetic interactions in yeast suggests that combinatorial network inhibition may afford increased drug efficacy and specificity. We carried out systematic screens with a bioactive library enriched for off-patent drugs to identify compounds that potentiate fluconazole action in pathogenic Candida and Cryptococcus strains and the model yeast Saccharomyces. Many compounds exhibited species- or genus-specific synergism, and often improved fluconazole from fungistatic to fungicidal activity. Mode of action studies revealed two classes of synergistic compound, which either perturbed membrane permeability or inhibited sphingolipid biosynthesis. Synergistic drug interactions were rationalized by global genetic interaction networks and, notably, higher order drug combinations further potentiated the activity of fluconazole. Synergistic combinations were active against fluconazole-resistant clinical isolates and an in vivo model of Cryptococcus infection. The systematic repurposing of approved drugs against a spectrum of pathogens thus identifies network vulnerabilities that may be exploited to increase the activity and repertoire of antifungal agents.

Enrichment and aggregation of topological motifs are independent organizational principles of integrated interaction networks

Topological network motifs represent functional relationships within and between regulatory and protein-protein interaction networks. Enriched motifs often aggregate into self-contained units forming functional modules. Theoretical models for network evolution by duplication-divergence mechanisms and for network topology by hierarchical scale-free networks have suggested a one-to-one relation between network motif enrichment and aggregation, but this relation has never been tested quantitatively in real biological interaction networks. Here we introduce a novel method for assessing the statistical significance of network motif aggregation and for identifying clusters of overlapping network motifs. Using an integrated network of transcriptional, posttranslational and protein-protein interactions in yeast we show that network motif aggregation reflects a local modularity property which is independent of network motif enrichment. In particular our method identified novel functional network themes for a set of motifs which are not enriched yet aggregate significantly and challenges the conventional view that network motif enrichment is the most basic organizational principle of complex networks.

The synthetic genetic interaction network reveals small molecules that target specific pathways in Sacchromyces cerevisiae

High-throughput elucidation of synthetic genetic interactions (SGIs) has contributed to a systems-level understanding of genetic robustness and fault-tolerance encoded in the genome. Pathway targets of various compounds have been predicted by comparing chemical-genetic synthetic interactions to a network of SGIs. We demonstrate that the SGI network can also be used in a powerful reverse pathway-to-drug approach for identifying compounds that target specific pathways of interest. Using the SGI network, the method identifies an indicator gene that may serve as a good candidate for screening a library of compounds. The indicator gene is selected so that compounds found to produce sensitivity in mutants deleted for the indicator gene are likely to abrogate the target pathway. We tested the utility of the SGI network for pathway-to-drug discovery using the DNA damage checkpoint as the target pathway. An analysis of the compendium of synthetic lethal interactions in yeast showed that superoxide dismutase 1 (SOD1) has significant SGI connectivity with a large subset of DNA damage checkpoint and repair (DDCR) genes in Saccharomyces cerevisiae, and minimal SGIs with non-DDCR genes. We screened a sod1Δ strain against three National Cancer Institute (NCI) compound libraries using a soft agar high-throughput halo assay. Fifteen compounds out of ∼3100 screened showed selective toxicity toward sod1Δ relative to the isogenic wild type (wt) strain. One of these, 1A08, caused a transient increase in growth in the presence of sublethal doses of DNA damaging agents, suggesting that 1A08 inhibits DDCR signaling in yeast. Genome-wide screening of 1A08 against the library of viable homozygous deletion mutants further supported DDCR as the relevant targeted pathway of 1A08. When assayed in human HCT-116 colorectal cancer cells, 1A08 caused DNA-damage resistant DNA synthesis and blocked the DNA-damage checkpoint selectively in S-phase.

Genetic Architecture of Growth Traits Revealed by Global Epistatic Interactions

Epistasis has long been recognized as fundamentally important in understanding the structure, function, and evolutionary dynamics of biological systems. Yet, little is known about how it is distributed underlying specific traits. Based on a global map of epistatic interactions in baker's yeast, Saccharomyces cerevisiae, we show that epistasis is prevalent (∼13% increase from random expectation) and displays modular architecture among genes that underlie the same growth traits. More interestingly, our results indicate that hub genes responsible for the same growth traits tend to link epistatically with each other more frequently than random expectation. Our results provide a genome-wide perspective on the genetic architecture of growth traits in a eukaryotic organism.

First Report of Bacterium and Yeasts Associated with Pineapple Fruit Collapse in Espírito Santo State, Brazil.

In rainy and warm periods of the year, after a dry, hot season (December/March), commercially grown pineapple (Ananas comosus var. comosus) in Espírito Santo State, Brazil has been affected by fruit collapse disease with significant commercial losses (15 to 20%) each year. Symptoms include intense flesh fermentation, spontaneous exudation of liquid and froth, and ripe inner fruit tissue deterioration on plants and postharvest. Isolation of microorganisms of diseased fruits on nutrient agar, potato dextrose agar, and yeast extract peptone dextrose media consistently resulted in the recovery of a bacterium and three different yeasts. Koch's postulates were fulfilled by syringe inoculation of different concentrations of each microorganism (2.0 × 105 to 2.0 × 109 CFU/ml) singly and the organisms in combinations (only bacterium, only the yeasts, one yeast and the bacterium, two yeasts and the bacterium, and three yeasts and the bacterium) into disinfected (0.5% NaOCl) postharvest ripe pineapple fruits (cv. Pérola). Inoculated fruits were kept at 40°C for 5 days. Six fruits were used for each treatment and the experiment was repeated three times. Characteristic symptoms only occurred when all three yeasts and the bacterium were inoculated in combination at all inoculum concentrations. Each microorganism alone could not produce symptoms. Control fruits, inoculated with sterile water, did not develop disease symptoms. Cultures of each isolate were obtained and identified by morphological, physiological, biochemical, and genetic analyses. Molecular characterization by ribosomal sequence analyses of bacterium (16S rDNA) and yeasts (D1/D2 region of 26S rDNA) used universal PCR primers for bacteria (F968 and R1401) and yeast NL1 (5' GCA TAT CAA TAA GCG GAG GAA AAG 3') and NL4 (5' GGT CCG TGT TTC AAG ACG G 3'). Sequences were compared with those in GenBank. On the basis of the results, the bacterium was identified as a Klebsiella sp. and the yeasts as a Candida sp., Saccharomyces sp., and a Kloeckera sp. The bacterium was negative for protease, cellulase, and pectinase activity in the qualitative tests. We concluded that the combination of a Klebsiella sp. with the three yeasts, Candida sp., Saccharomyces sp., and Kloeckera sp., was responsible for the symptoms of pineapple fruit collapse. Symptoms of pineapple fruit collapse are similar to yeasty fermentation reported previously (2,3). These reports did not consider the interaction of yeast and bacteria. No relationship between the pineapple cultivars and the pathogens from specific field sites was found. Disease outbreaks seem related to naturally occurring fruit translucency, a physiological disturbance correlated with calcium, potassium, and nitrogen balance (1,3), which increases fruit cell-wall hydrolases and membrane permeability. This condition releases nutrients from the fruit and favors microbial growth. To our knowledge, this is the first report of a combination of bacterium and yeasts associated with collapse disease of pineapple in Brazil. Information on the pathogens responsible for collapse disease epidemics in Espírito Santo fields will be useful in breeding and disease control strategies.

Quantitative analysis of fitness and genetic interactions in yeast on a genome scale.

Global quantitative analysis of genetic interactions is a powerful approach for deciphering the roles of genes and mapping functional relationships among pathways. Using colony size as a proxy for fitness, we developed a method for measuring fitness-based genetic interactions from high-density arrays of yeast double mutants generated by synthetic genetic array (SGA) analysis. We identified several experimental sources of systematic variation and developed normalization strategies to obtain accurate single- and double-mutant fitness measurements, which rival the accuracy of other high-resolution studies. We applied the SGA score to examine the relationship between physical and genetic interaction networks, and we found that positive genetic interactions connect across functionally distinct protein complexes revealing a network of genetic suppression among loss-of-function alleles.

ConsensusPathDB: toward a more complete picture of cell biology

ConsensusPathDB is a meta-database that integrates different types of functional interactions from heterogeneous interaction data resources. Physical protein interactions, metabolic and signaling reactions and gene regulatory interactions are integrated in a seamless functional association network that simultaneously describes multiple functional aspects of genes, proteins, complexes, metabolites, etc. With 155 432 human, 194 480 yeast and 13 648 mouse complex functional interactions (originating from 18 databases on human and eight databases on yeast and mouse interactions each), ConsensusPathDB currently constitutes the most comprehensive publicly available interaction repository for these species. The Web interface at http://cpdb.molgen.mpg.de offers different ways of utilizing these integrated interaction data, in particular with tools for visualization, analysis and interpretation of high-throughput expression data in the light of functional interactions and biological pathways.

Full Repression of RNA Polymerase III Transcription Requires Interaction between Two Domains of Its Negative Regulator Maf1

Maf1, first identified in yeast Saccharomyces cerevisiae, is a general negative regulator of RNA polymerase III (Pol III). Transcription regulation by Maf1 is important under stress conditions and during the switch between fermentation and respiration. Maf1 is composed of two domains conserved during evolution. We report here that these two domains of human Maf1 are resistant to mild proteolysis and interact together as shown by pull-down and size-exclusion chromatography and that the comparable domains of yeast Maf1 interact in a two-hybrid assay. Additionally, in yeast, a mutation in the N-terminal domain is compensated by mutations in the C-terminal domain. Integrity of both domains and their direct interaction are necessary for Maf1 dephosphorylation and subsequent inhibition of Pol III transcription on a nonfermentable carbon source. These data relate Pol III transcription inhibition to Maf1 structural changes.

Towards monitoring real-time cellular response using an integrated microfluidics-matrix assisted laser desorption ionisation/nanoelectrospray ionisation-ion mobility-mass spectrometry platform.

The combination of microfluidic cell trapping devices with ion mobility-mass spectrometry offers the potential for elucidating in real time the dynamic responses of small populations of cells to paracrine signals, changes in metabolite levels and delivery of drugs and toxins. Preliminary experiments examining peptides in methanol and recording the interactions of yeast and Jurkat cells with their superfusate have identified instrumental set-up and control parameters and online desalting procedures. Numerous initial experiments demonstrate and validate this new instrumental platform. Future outlooks and potential applications are addressed, specifically how this instrumentation may be used for fully automated systems biology studies of the significantly interdependent, dynamic internal workings of cellular metabolic and signalling pathways.

Non-Saccharomyces Yeasts in Controlled Mixed Culture Fermentation in Winemaking: the Role of Metabolic Interactions

One of the most important technological advances in winemaking is the control of alcoholic fermentation through the inoculation of the grape juice with selected cultures of Saccharomyces cerevisiae . In the last decade several studies revaluated the involvement of non- Saccharomyces yeasts during alcoholic fermentation and their role in the metabolic impact and aroma complexity of the final product. Indeed, non- Saccharomyces yeasts may produce high amounts of different metabolites and enzymes able to release aroma compounds from precursors present in grape must (Fernandez et al., 2000). Thus, non- Saccharomyces yeasts may influence the perceivable characteristics of the final product (Romano et al., 2003). In view of the fact that natural fermentations remain uncontrolled processes, several studies have evaluated the possibility of using controlled multistarter cultures to increase the quality of wines. The use of non- Saccharomyces wine yeasts, together with Saccharomyces strains as part of multistarter fermentations, has been proposed as a tool to take advantages of natural fermentation and maintain the control of the fermentative process (Ciani et al., 2006, [Anfang et al., 2009] and [Ciani et al., 2010]). We evaluated the oenological aptitude of non- Saccharomyces wine yeasts belonging to nine different genera. Selected non- Saccharomyces strains with a commercial S. cerevisiae strain were used to set up mixed must microfermentations estimating biomass and fermentation evolution as well as analytical profile of wines. Results of screening allowed to select some non- Saccharomyces yeasts with suitable oenological properties. The comparison between mixed and pure fermentations showed variations in the analytical profiles. The presence and permanence of non- Saccharomyces yeasts during must mixed fermentations positively influence the final product. In particular, yeast interactions frequently allowed the reduction of some negative compounds produced by non- Saccharomyces yeasts such as acetic acid, and the enhancement of favourable aroma compounds (2-phenylethanol, phenylethyl acetate, isoamyl acetate). This work is financed by Consorzio Tuscania, Firenze.

Extensive In Vivo Metabolite-Protein Interactions Revealed by Large-Scale Systematic Analyses

Natural small compounds comprise most cellular molecules and bind proteins as substrates, products, cofactors, and ligands. However, a large-scale investigation of invivo protein-small metabolite interactions has not been performed. We developed a mass spectrometry assay for the large-scale identification of invivo protein-hydrophobic small metabolite interactions in yeast and analyzed compounds that bind ergosterol biosynthetic proteins and protein kinases. Many of these proteins bind small metabolites; a few interactions were previously known, but the vast majority are new. Importantly, many key regulatory proteins such as protein kinases bind metabolites. Ergosterol was found to bind many proteins and may function as a general regulator. It is required for the activity of Ypk1, a mammalian AKT/SGK kinase homolog. Our study defines potential key regulatory steps in lipid biosynthetic pathways and suggests that small metabolites may play a more general role as regulators of protein activity and function than previously appreciated.

The importance and ecology of yeasts in soil

This review focuses on literature pertaining to the interactions of soil yeasts with biotic and abiotic factors in their environment. Soil yeasts not only affect microbial and plant growth, but may also play a role in soil aggregate formation and maintenance of soil structure. Serving as a nutrient source for bacterial, faunal and protistan predators, soil yeasts contribute to essential ecological processes such as the mineralization of organic material and dissipation of carbon and energy through the soil ecosystem. Some soil yeasts may also play a role in both the nitrogen and sulphur cycles and have the ability to solubilize insoluble phosphates making it more readily available for plants. Recently, the potential of soil yeasts as plant growth promoters and soil conditioners has been studied with the goal of using them in the field of sustainable agriculture.

ProHits: integrated software for mass spectrometry–based interaction proteomics

ProHits: integrated software for mass spectrometry–based interaction proteomics

Collybistin and gephyrin are novel components of the eukaryotic translation initiation factor 3 complex

BackgroundCollybistin (CB), a neuron-specific guanine nucleotide exchange factor, has been implicated in targeting gephyrin-GABAA receptors clusters to inhibitory postsynaptic sites. However, little is known about additional CB partners and functions.FindingsHere, we identified the p40 subunit of the eukaryotic translation initiation factor 3 (eIF3H) as a novel binding partner of CB, documenting the interaction in yeast, non-neuronal cell lines, and the brain. In addition, we demonstrated that gephyrin also interacts with eIF3H in non-neuronal cells and forms a complex with eIF3 in the brain.ConclusionsTogether, our results suggest, for the first time, that CB and gephyrin associate with the translation initiation machinery, and lend further support to the previous evidence that gephyrin may act as a regulator of synaptic protein synthesis.

An Integrative Multi-Network and Multi-Classifier Approach to Predict Genetic Interactions

Genetic interactions occur when a combination of mutations results in a surprising phenotype. These interactions capture functional redundancy, and thus are important for predicting function, dissecting protein complexes into functional pathways, and exploring the mechanistic underpinnings of common human diseases. Synthetic sickness and lethality are the most studied types of genetic interactions in yeast. However, even in yeast, only a small proportion of gene pairs have been tested for genetic interactions due to the large number of possible combinations of gene pairs. To expand the set of known synthetic lethal (SL) interactions, we have devised an integrative, multi-network approach for predicting these interactions that significantly improves upon the existing approaches. First, we defined a large number of features for characterizing the relationships between pairs of genes from various data sources. In particular, these features are independent of the known SL interactions, in contrast to some previous approaches. Using these features, we developed a non-parametric multi-classifier system for predicting SL interactions that enabled the simultaneous use of multiple classification procedures. Several comprehensive experiments demonstrated that the SL-independent features in conjunction with the advanced classification scheme led to an improved performance when compared to the current state of the art method. Using this approach, we derived the first yeast transcription factor genetic interaction network, part of which was well supported by literature. We also used this approach to predict SL interactions between all non-essential gene pairs in yeast (http://sage.fhcrc.org/downloads/downloads/predicted_yeast_genetic_interactions.zip). This integrative approach is expected to be more effective and robust in uncovering new genetic interactions from the tens of millions of unknown gene pairs in yeast and from the hundreds of millions of gene pairs in higher organisms like mouse and human, in which very few genetic interactions have been identified to date.

Combined zebrafish-yeast chemical-genetic screens reveal gene–copper-nutrition interactions that modulate melanocyte pigmentation

Hypopigmentation is a feature of copper deficiency in humans, as caused by mutation of the copper (Cu(2+)) transporter ATP7A in Menkes disease, or an inability to absorb copper after gastric surgery. However, many causes of copper deficiency are unknown, and genetic polymorphisms might underlie sensitivity to suboptimal environmental copper conditions. Here, we combined phenotypic screens in zebrafish for compounds that affect copper metabolism with yeast chemical-genetic profiles to identify pathways that are sensitive to copper depletion. Yeast chemical-genetic interactions revealed that defects in intracellular trafficking pathways cause sensitivity to low-copper conditions; partial knockdown of the analogous Ap3s1 and Ap1s1 trafficking components in zebrafish sensitized developing melanocytes to hypopigmentation in low-copper environmental conditions. Because trafficking pathways are essential for copper loading into cuproproteins, our results suggest that hypomorphic alleles of trafficking components might underlie sensitivity to reduced-copper nutrient conditions. In addition, we used zebrafish-yeast screening to identify a novel target pathway in copper metabolism for the small-molecule MEK kinase inhibitor U0126. The zebrafish-yeast screening method combines the power of zebrafish as a disease model with facile genome-scale identification of chemical-genetic interactions in yeast to enable the discovery and dissection of complex multigenic interactions in disease-gene networks.

Functional analysis of the structural domain of ARF proteins in rice (Oryza sativa L.)

Auxin response factors (ARFs) are key regulators of plant growth and development. Through interaction with auxin/indole acetic acid (Aux/IAA) proteins, they influence the expression of auxin response genes. An ARF gene family has been predicted in rice, but the functions of the individual structural domains of the OsARFs remain obscure. Bioinformatics was used to analyse the position of the DNA-binding domain (DBD), middle region (MR), and C-terminal dimerization domain (CTD) of OsARFs, and experimentally confirmed the presence of a classical monopartite nuclear localization signal (NLS) in the DBD. The DBD was shown to contribute to nuclear localization of OsARF proteins in addition to its known DNA-binding function. Interactions between 14 integrated OsARFs and 15 OsIAA proteins were tested using yeast two-hybrid assays. It was found that eight OsARF activators interacted with the 15 OsIAA proteins, while six OsARF repressors did not. The interactions between the MR+CTD or CTD of 10 OsARFs and 15 OsIAA proteins were also tested and the results were consistent with those of each intact OsARF, although some slight differences in interaction intensity were observed by α-galactosidase quantitative assays. The truncated CTD of OsARF11 did not interact with any OsIAA, implying that the CTD is required for ARF–IAA dimerization, and that the MR influences the interaction intensity in yeast. A subset of the interactions in yeast were also observed in tobacco plants using firefly luciferase complementation imaging assays, indicating that these interactions are specific in plants, and might have a special role in the auxin signalling response. This study provides new insight into the structure of OsARF proteins and ARF–Aux/IAA interactions.

Paracoccidioides brasiliensis enolase is a surface protein that binds plasminogen and mediates interaction of yeast forms with host cells.

Paracoccidioidomycosis (PCM), caused by the dimorphic fungus Paracoccidioides brasiliensis, is a disseminated, systemic disorder that involves the lungs and other organs. The ability of the pathogen to interact with host components, including extracellular matrix (ECM) proteins, is essential to further colonization, invasion, and growth. Previously, enolase (EC 4.2.1.11) was characterized as a fibronectin binding protein in P. brasiliensis. Interaction of surface-bound enolase with plasminogen has been incriminated in tissue invasion for pathogenesis in several pathogens. In this paper, enolase was expressed in Escherichia coli as a recombinant glutathione S-transferase (GST) fusion protein (recombinant P. brasiliensis enolase [rPbEno]). The P. brasiliensis native enolase (PbEno) was detected at the fungus surface and cytoplasm by immunofluorescence with an anti-rPbEno antibody. Immobilized purified rPbEno bound plasminogen in a specific, concentration-dependent fashion. Both native enolase and rPbEno activated conversion of plasminogen to plasmin through tissue plasminogen activator. The association between PbEno and plasminogen was lysine dependent. In competition experiments, purified rPbEno, in its soluble form, inhibited plasminogen binding to fixed P. brasiliensis, suggesting that this interaction required surface-localized PbEno. Plasminogen-coated P. brasiliensis yeast cells were capable of degrading purified fibronectin, providing in vitro evidence for the generation of active plasmin on the fungus surface. Exposure of epithelial cells and phagocytes to enolase was associated with an increased expression of surface sites of adhesion. In fact, the association of P. brasiliensis with epithelial cells and phagocytes was increased in the presence of rPbEno. The expression of PbEno was upregulated in yeast cells derived from mouse-infected tissues. These data indicate that surface-associated PbEno may contribute to the pathogenesis of P. brasiliensis.

Protein–Protein Interactions Between σ 70 Region 4 of RNA Polymerase and Escherichia coli SoxS, a Transcription Activator That Functions by the Prerecruitment Mechanism: Evidence for “Off-DNA” and “On-DNA” Interactions

According to the prerecruitment hypothesis, Escherichia coli SoxS activates the transcription of the genes of the SoxRS regulon by forming binary complexes with RNA polymerase (RNAP) that scan the chromosome for class I and class II SoxS-dependent promoters. We showed previously that the α subunit's C-terminal domain plays a role in activating both classes of promoter by making protein–protein contacts with SoxS; some of these contacts are made in solution in the absence of promoter DNA, a critical prediction of the prerecruitment hypothesis. Here, we identified seven single-alanine substitutions of the region 4 of σ 70 (σ 70 R4) of RNAP that reduce SoxS activation of class II promoters. With genetic epistasis tests between these σ 70 R4 mutants and positive control mutants of SoxS, we identified 10 pairs of amino acids that interact with each other in E. coli. Using the yeast two-hybrid system and affinity immobilization assays, we showed that SoxS and σ 70 R4 can interact in solution (i.e., “off-DNA”). The interaction requires amino acids of the class I/II (but not the class II) positive control surface of SoxS, and five amino acids of σ 70 R4 that reduce activation in E. coli also reduce the SoxS–σ 70 R4 interaction in yeast. One of the epistatic interactions that occur in E. coli also occurs in the yeast two-hybrid system (i.e., off-DNA). Importantly, we infer that the five epistatic interactions occurring in E. coli that require an amino acid of the class II surface occur “on-DNA” at class II promoters. Finding that SoxS contacts σ 70 R4 both off-DNA and on-DNA is consistent with the prerecruitment hypothesis. Moreover, SoxS is now the first example of an E. coli transcriptional activator that uses a single positive control surface to make specific protein–protein contacts with two different subunits of RNAP.