Yeast Deletion Strains Research Articles

Adaptation to sorbic acid in low sugar promotes resistance of yeast to the preservative

The weak acid sorbic acid is a common preservative used in soft drink beverages to control microbial spoilage. Consumers and industry are increasingly transitioning to low-sugar food formulations, but potential impacts of reduced sugar on sorbic acid efficacy are barely characterised. In this study, we report enhanced sorbic acid resistance of yeast in low-glucose conditions. We had anticipated that low glucose would induce respiratory metabolism, which was shown previously to be targeted by sorbic acid. However, a shift from respiratory to fermentative metabolism upon sorbic acid exposure of Saccharomyces cerevisiae was correlated with relative resistance to sorbic acid in low glucose. Fermentation-negative yeast species did not show the low-glucose resistance phenotype. Phenotypes observed for certain yeast deletion strains suggested roles for glucose signalling and repression pathways in the sorbic acid resistance at low glucose. This low-glucose induced sorbic acid resistance was reversed by supplementing yeast cultures with succinic acid, a metabolic intermediate of respiratory metabolism (and a food-safe additive) that promoted respiration. The results indicate that metabolic adaptation of yeast can promote sorbic acid resistance at low glucose, a consideration for the preservation of foodstuffs as both food producers and consumers move towards a reduced sugar landscape.

Proteome-wide abundance profiling of yeast deletion strains for GET pathway members using sample multiplexing.

The GET pathway is associated with post-translational delivery of tail-anchored (TA) proteins to the endoplasmic reticulum (ER) in yeast, as well as other eukaryotes. Moreover, dysfunction of the GET pathway has been associated with various pathological conditions (i.e., neurodegenerative disorders, cardiovascular ailments, and protein misfolding diseases). In this study, we used yeast deletion strains of Get complex members (specifically, Get1, Get2, Get3, Get4, and Get5) coupled with sample multiplexing-based quantitative mass spectrometry to profile protein abundance on a proteome-wide scale across the five individual deletion strains. Our dataset consists of over 4500 proteins, which corresponds to >75% of the yeast proteome. The data reveal several dozen proteins that are differentially abundant in one or more deletion strains, some of which are membrane-associated, yet the abundance of many TA proteins remained unchanged. This study provides valuable insights into the roles of these Get genes, and the potential for alternative pathways which help maintain cellular function despite the disruption of the GET pathway.

Systematic Analysis of Assembly Intermediates in Yeast to Decipher the Mitoribosome Assembly Pathway.

Studies of yeast mitoribosome assembly have been historically hampered by the difficulty of generating mitoribosome protein-coding gene deletion strains with a stable mitochondrial genome. The identification of mitochondrial DNA-stabilizing approaches allows for the generation of a complete set of yeast deletion strains covering all mitoribosome proteins and known assembly factors. These strains can be used to analyze the integrity and assembly state of mitoribosomes by determining the sedimentation profile of these structures by sucrose gradient centrifugation of mitochondrial extracts, coupled to mass spectrometry analysis of mitoribosome composition. Subsequent hierarchical cluster analysis of mitoribosome subassemblies accumulated in mutant strains reveals details regarding the order of protein association during the mitoribosome biogenetic process. These strains also allow the expression of truncated protein variants to probe the role of mitochondrion-specific protein extensions, the relevance of protein cofactors, or the importance of RNA-protein interactions in functional sites of the mitoribosome. In this chapter, we will detail the methodology involved in these studies.

Investigation the global effect of rare earth gadolinium on the budding Saccharomyces cerevisiae by genome-scale screening.

The rare earth gadolinium (Gd) is widely used in industry and medicine, which has been treated as an emerging pollutant in environment. The increasing pollution of Gd has potential hazards to living organisms. Thus it is essential to investigate the toxicity and action mechanism of Gd in biological system. In this study, the global effect and activation mechanism of Gd on yeast were investigated by genome-scale screening. Our results show that 45 gene deletion strains are sensitive to Gd and 10 gene deletion strains are Gd resistant from the diploid gene deletion strain library of Saccharomyces cerevisiae. The result of localization analysis shows that most of these genes are involved in cell metabolism, cell cycle, transcription, translation, protein synthesis, protein folding, and cell transport. The result of functional analysis shows that four genes (CNB1, CRZ1, VCX1, and GDT1) are involved in the calcium signaling pathway, and four genes (PHO84, PHO86, PHO2, and PHO4) are involved in phosphorus metabolism. For Gd3+ has the similar ion radius with Ca2+ and easily binds to the phosphate radical, it affects Ca2+ signaling pathway and phosphorus metabolism. The genes ARF1, ARL1, ARL3, SYS1, COG5, COG6, YPT6, VPS9, SSO2, MRL1, AKL1, and TRS85 participate in vesicle transport and protein sorting. Thus, Gd accumulation affects the function of proteins related to vesicle transport, which may result in the failure of Gd transport out of cells. In addition, the intracellular Gd content in the 45 sensitive deletion strains is higher than that in the wild type yeast under Gd stress. It suggests that the sensitivity of yeast deletion strains is related to the excessive intracellular Gd accumulation.

A simplified and easy-to-use HIP HOP assay provides insights into chalcone antifungal mechanisms of action.

Elucidating the mechanism of action of an antifungal or cytotoxic compound is a time-consuming process. Yeast chemogenomic profiling provides a compelling solution to the problem but is experimentally complex. Here, we demonstrate the use of a highly simplified yeast chemical genetic assay comprising just 89 yeast deletion strains, each diagnostic for a specific mechanism of action. We use the assay to investigate the mechanism of action of two antifungal chalcone compounds, trans-chalcone and 4'-hydroxychalcone, and narrow down the mechanism to transcriptional stress. Crucially, the assay eliminates mechanisms of action such as topoisomerase I inhibition and membrane disruption that have been suggested for related chalcone compounds. We propose this simplified assay as a useful tool to rapidly identify common off-target mechanisms.

Profiling Yeast Deletion Strains Using Sample Multiplexing and Network-Based Analyses.

The yeast, Saccharomyces cerevisiae, is a widely used model system for investigating conserved biological functions and pathways. Advancements in sample multiplexing have facilitated the study of the yeast proteome, yet many yeast proteins remain uncharacterized or only partially characterized. Yeast deletion strain collections are powerful resources for yeast proteome studies, uncovering the effects of gene function, genetic interactions, and cellular stresses. As complex biological systems cannot be understood by simply analyzing the individual components, a systems approach is often required in which a protein is represented as a component of large, interacting networks. Here, we evaluate the current state of yeast proteome analysis using isobaric tag-based sample multiplexing (TMTpro16) to profile the proteomes of 75 yeast deletion strains for which we measured the abundance of nearly 5000 proteins. Using statistical approaches, we highlighted covariance and regulation subnetworks and the enrichment of gene ontology classifications for covarying and coregulated proteins. This dataset presents a resource that is amenable to further data mining to study individual deletion strains, pathways, proteins, and/or interactions thereof while serving as a template for future network-based investigations using yeast deletion strain collections.

TORC1 Signaling Controls the Stability and Function of α-Arrestins Aly1 and Aly2.

Nutrient supply dictates cell signaling changes, which in turn regulate membrane protein trafficking. To better exploit nutrients, cells relocalize membrane transporters via selective protein trafficking. Key in this reshuffling are the α-arrestins, selective protein trafficking adaptors conserved from yeast to man. α-Arrestins bind membrane proteins, controlling the ubiquitination and endocytosis of many transporters. To prevent the spurious removal of membrane proteins, α-arrestin-mediated endocytosis is kept in check through phospho-inhibition. This phospho-regulation is complex, with up to 87 phospho-sites on a single α-arrestin and many kinases/phosphatases targeting α-arrestins. To better define the signaling pathways controlling paralogous α-arrestins, Aly1 and Aly2, we screened the kinase and phosphatase deletion (KinDel) library, which is an array of all non-essential kinase and phosphatase yeast deletion strains, for modifiers of Aly-mediated phenotypes. We identified many Aly regulators, but focused our studies on the TORC1 kinase, a master regulator of nutrient signaling across eukaryotes. We found that TORC1 and its signaling effectors, the Sit4 protein phosphatase and Npr1 kinase, regulate the phosphorylation and stability of Alys. When Sit4 is lost, Alys are hyperphosphorylated and destabilized in an Npr1-dependent manner. These findings add new dimensions to our understanding of TORC1 regulation of α-arrestins and have important ramifications for cellular metabolism.

Coordinated glucose-induced Ca2+ and pH responses in yeast Saccharomyces cerevisiae

Ca2+ and pH homeostasis are closely intertwined and this interrelationship is crucial in the cells' ability to adapt to varying environmental conditions. To further understand this Ca2+-pH link, cytosolic Ca2+ was monitored using the aequorin-based bioluminescent assay in parallel with fluorescence reporter-based assays to monitor plasma membrane potentials and intracellular (cytosolic and vacuolar) pH in yeast Saccharomyces cerevisiae. At external pH 5, starved yeast cells displayed depolarized membrane potentials and responded to glucose re-addition with small Ca2+ transients accompanied by cytosolic alkalinization and profound vacuolar acidification. In contrast, starved cells at external pH 7 were hyperpolarized and glucose re-addition induced large Ca2+ transients and vacuolar alkalinization. In external Ca2+-free medium, glucose-induced pH responses were not affected but Ca2+ transients were abolished, indicating that the intracellular [Ca2+] increase was not prerequisite for activation of the two primary proton pumps, being Pma1 at the plasma membrane and the vacuolar and Golgi localized V-ATPases. A reduction in Pma1 expression resulted in membrane depolarization and reduced Ca2+ transients, indicating that the membrane hyperpolarization generated by Pma1 activation governed the Ca2+ influx that is associated with glucose-induced Ca2+ transients. Loss of V-ATPase activity through concanamycin A inhibition did not alter glucose-induced cytosolic pH responses but affected vacuolar pH changes and Ca2+ transients, indicating that the V-ATPase established vacuolar proton gradient is substantial for organelle H+/Ca2+ exchange. Finally, a systematic analysis of yeast deletion strains allowed us to reveal an essential role for both the vacuolar H+/Ca2+ exchanger Vcx1 and the Golgi exchanger Gdt1 in the dissipation of intracellular Ca2+.

A genome-wide portrait of pervasive drug contaminants

Using a validated yeast chemogenomic platform, we characterized the genome-wide effects of several pharmaceutical contaminants, including three N-nitrosamines (NDMA, NDEA and NMBA), two related compounds (DMF and 4NQO) and several of their metabolites. A collection of 4800 non-essential homozygous diploid yeast deletion strains were screened in parallel and the strain abundance was quantified by barcode sequencing. These data were used to rank deletion strains representing genes required for resistance to the compounds to delineate affected cellular pathways and to visualize the global cellular effects of these toxins in an easy-to-use searchable database. Our analysis of the N-nitrosamine screens uncovered genes (via their corresponding homozygous deletion mutants) involved in several evolutionarily conserved pathways, including: arginine biosynthesis, mitochondrial genome integrity, vacuolar protein sorting and DNA damage repair. To investigate why NDMA, NDEA and DMF caused fitness defects in strains lacking genes of the arginine pathway, we tested several N-nitrosamine metabolites (methylamine, ethylamine and formamide), and found they also affected arginine pathway mutants. Notably, each of these metabolites has the potential to produce ammonium ions during their biotransformation. We directly tested the role of ammonium ions in N-nitrosamine toxicity by treatment with ammonium sulfate and we found that ammonium sulfate also caused a growth defect in arginine pathway deletion strains. Formaldehyde, a metabolite produced from NDMA, methylamine and formamide, and which is known to cross-link free amines, perturbed deletion strains involved in chromatin remodeling and DNA repair pathways. Finally, co-administration of N-nitrosamines with ascorbic or ferulic acid did not relieve N-nitrosamine toxicity. In conclusion, we used parallel deletion mutant analysis to characterize the genes and pathways affected by exposure to N-nitrosamines and related compounds, and provide the data in an accessible, queryable database.

An Optimized Competitive-Aging Method Reveals Gene-Drug Interactions Underlying the Chronological Lifespan of Saccharomyces cerevisiae.

The chronological lifespan of budding yeast is a model of aging and age-related diseases. This paradigm has recently allowed genome-wide screening of genetic factors underlying post-mitotic viability in a simple unicellular system, which underscores its potential to provide a comprehensive view of the aging process. However, results from different large-scale studies show little overlap and typically lack quantitative resolution to derive interactions among different aging factors. We previously introduced a sensitive, parallelizable approach to measure the chronological-lifespan effects of gene deletions based on the competitive aging of fluorescence-labeled strains. Here, we present a thorough description of the method, including an improved multiple-regression model to estimate the association between death rates and fluorescent signals, which accounts for possible differences in growth rate and experimental batch effects. We illustrate the experimental procedure—from data acquisition to calculation of relative survivorship—for ten deletion strains with known lifespan phenotypes, which is achieved with high technical replicability. We apply our method to screen for gene-drug interactions in an array of yeast deletion strains, which reveals a functional link between protein glycosylation and lifespan extension by metformin. Competitive-aging screening coupled to multiple-regression modeling provides a powerful, straight-forward way to identify aging factors in yeast and their interactions with pharmacological interventions.

Investigation of Proteomic and Phosphoproteomic Responses to Signaling Network Perturbations Reveals Functional Pathway Organizations in Yeast

SUMMARYGovernance of protein phosphorylation by kinases and phosphatases constitutes an essential regulatory network in eukaryotic cells. Network dysregulation leads to severe consequences and is often a key factor in disease pathogenesis. Previous studies revealed multiple roles for protein phosphorylation and pathway structures in cellular functions from different perspectives. We seek to understand the roles of kinases and phosphatases from a protein homeostasis point of view. Using a streamlined tandem mass tag (SL-TMT) strategy, we systematically measure proteomic and phosphoproteomic responses to perturbations of phosphorylation signaling networks in yeast deletion strains. Our results emphasize the requirement for protein normalization for more complete interpretation of phosphorylation data. Functional relationships between kinases and phosphatases were characterized at both proteome and phosphoproteome levels in three ways: (1) Gene Ontology enrichment analysis, (2) Δgene-Δgene correlation networks, and (3) molecule covariance networks. This resource illuminates kinase and phosphatase functions and pathway organizations.

Quantitative Yeast Genetic Interaction Profiling of Bacterial Effector Proteins Uncovers a Role for the Human Retromer in Salmonella Infection.

Intracellular bacterial pathogens secrete a repertoire of effector proteins into host cells that are required to hijack cellular pathways and cause disease. Despite decades of research, the molecular functions of most bacterial effectors remain unclear. To address this gap, we generated quantitative genetic interaction profiles between 36 validated and putative effectors from three evolutionarily divergent human bacterial pathogens and 4,190 yeast deletion strains. Correlating effector-generated profiles with those of yeast mutants, we recapitulated known biology for several effectors with remarkable specificity and predicted previously unknown functions for others. Biochemical and functional validation in human cells revealed a role for an uncharacterized component of the Salmonella SPI-2 translocon, SseC, in regulating maintenance of the Salmonella vacuole through interactions with components of the host retromer complex. These results exhibit the power of genetic interaction profiling to discover and dissect complex biology at the host-pathogen interface.

Discovery of a Novel Dibromoquinoline Compound Exhibiting Potent Antifungal and Antivirulence Activity That Targets Metal Ion Homeostasis

Globally, invasive fungal infections pose a significant challenge to modern human medicine due to the limited number of antifungal drugs and the rise in resistance to current antifungal agents. A vast majority of invasive fungal infections are caused by species of Candida, Cryptococcus, and Aspergillus. Novel antifungal molecules consisting of unexploited chemical scaffolds with a unique mechanism are a pressing need. The present study identifies a dibromoquinoline compound (4b) with broad-spectrum antifungal activity that inhibits the growth of pertinent species of Candida (chiefly C. albicans), Cryptococcus, and Aspergillus at a concentration of as low as 0.5 μg/mL. Furthermore, 4b, at a subinhibitory concentration, interfered with the expression of two key virulence factors (hyphae and biofilm formation) involved in C. albicans pathogenesis. Three yeast deletion strains ( cox17Δ, ssa1Δ, and aft2Δ) related to metal ion homeostasis were found to be highly sensitive to 4b in growth assays, indicating that the compound exerts its antifungal effect through a unique, previously unexploited mechanism. Supplementing the media with either copper or iron ions reversed the strain sensitivity to 4b, further corroborating that the compound targets metal ion homeostasis. 4b's potent antifungal activity was validated in vivo, as the compound enhanced the survival of Caenorhabditis elegans infected with fluconazole-resistant C. albicans. The present study indicates that 4b warrants further investigation as a novel antifungal agent.

A Chemogenomic Screening Platform Used to Identify Chemotypes Perturbing HSP90 Pathways

Compounds that modulate the heat shock protein (HSP) network have potential in a broad range of research applications and diseases. A yeast-based liquid culture assay that measured time-dependent turbidity enabled the high-throughput screening of different Saccharomyces cerevisae strains to identify HSP modulators with unique molecular mechanisms. A focused set of four strains, with differing sensitivities to Hsp90 inhibitors, was used to screen a compound library of 3680 compounds. Computed turbidity curve functions were used to classify strain responses and sensitivity to chemical effects across the compound library. Filtering based on single-strain selectivity identified nine compounds as potential heat shock modulators, including the known Hsp90 inhibitor macbecin. Haploid yeast deletion strains (360), mined from previous Hsp90 inhibitor yeast screens and heat shock protein interaction data, were screened for differential sensitivities to known N-terminal ATP site-directed Hsp90 inhibitors to reveal functional distinctions. Strains demonstrating differential sensitivity (13) to Hsp90 inhibitors were used to prioritize primary screen hit compounds, with NSC145366 emerging as the lead hit. Our follow-up biochemical and functional studies show that NSC145366 directly interacts and inhibits the C-terminus of Hsp90, validating the platform as a powerful approach for early-stage identification of bioactive modulators of heat shock–dependent pathways.

High-Throughput Screening to Identify Regulators of Meiosis-Specific Gene Expression in Saccharomyces cerevisiae.

Meiosis and gamete formation are processes that are essential for sexual reproduction in all eukaryotic organisms. Multiple intracellular and extracellular signals feed into pathways that converge on transcription factors that induce the expression of meiosis-specific genes. Once triggered the meiosis-specific gene expression program proceeds in a cascade that drives progress through the events of meiosis and gamete formation. Meiosis-specific gene expression is tightly controlled by a balance of positive and negative regulatory factors that respond to a plethora of signaling pathways. The budding yeast Saccharomyces cerevisiae has proven to be an outstanding model for the dissection of gametogenesis owing to the sophisticated genetic manipulations that can be performed with the cells. It is possible to use a variety selection and screening methods to identify genes and their functions. High-throughput screening technology has been developed to allow an array of all viable yeast gene deletion mutants to be screened for phenotypes and for regulators of gene expression. This chapter describes a protocol that has been used to screen a library of homozygous diploid yeast deletion strains to identify regulators of the meiosis-specific IME1 gene.

Profiling DNA damage-induced phosphorylation in budding yeast reveals diverse signaling networks

The DNA damage response (DDR) is regulated by a protein kinase signaling cascade that orchestrates DNA repair and other processes. Identifying the substrate effectors of these kinases is critical for understanding the underlying physiology and mechanism of the response. We have used quantitative mass spectrometry to profile DDR-dependent phosphorylation in budding yeast and genetically explored the dependency of these phosphorylation events on the DDR kinases MEC1, RAD53, CHK1, and DUN1. Based on these screens, a database containing many novel DDR-regulated phosphorylation events has been established. Phosphorylation of many of these proteins has been validated by quantitative peptide phospho-immunoprecipitation and examined for functional relevance to the DDR through large-scale analysis of sensitivity to DNA damage in yeast deletion strains. We reveal a link between DDR signaling and the metabolic pathways of inositol phosphate and phosphatidyl inositol synthesis, which are required for resistance to DNA damage. We also uncover links between the DDR and TOR signaling as well as translation regulation. Taken together, these data shed new light on the organization of DDR signaling in budding yeast.

Lichen-forming fungus Caloplaca flavoruscens inhibits transcription factors and chromatin remodeling system in fungi.

Lichen-forming fungi and extracts derived from them have been used as alternative medicine sources for millennia and recently there has been a renewed interest in their known bioactive properties for anticancer agents, cosmetics and antibiotics. Although lichen-forming fungus-derived compounds are biologically and commercially valuable, few studies have been performed to determine their modes of action. This study used chemical-genetic and chemogenomic high-throughput analyses to gain insight into the modes of action of Caloplaca flavoruscens extracts. High-throughput screening of 575 lichen extracts was performed and 39 extracts were identified which inhibited yeast growth. A C. flavoruscens extract was selected as a promising antifungal and was subjected to genome-wide haploinsufficiency profiling and homozygous profiling assays. These screens revealed that yeast deletion strains lacking Rsc8, Pro1 and Toa2 were sensitive to three concentrations (IC25.5, IC25 and IC50, respectively) of C. flavoruscens extract. Gene-enrichment analysis of the data showed that C. flavoruscens extracts appear to perturb transcription and chromatin remodeling.

Varying Assay of Proteins Vital to Regulation of the Epithelial Sodium Channel (ENaC)

The epithelial sodium channel (ENaC) is a transmembrane heterotrimeric protein complex that transports sodium into epithelial cells. This channel plays a crucial role in sodium regulation, which is important for proper blood pressure and fluid balance. Located in the distal portion of nephrons within the kidney, the channel selectively regulates the reabsorption of sodium. Genetic mutations in ENaC have shown to cause disease states of hypertension in Liddle's syndrome and hypotension in pseudohypoaldosteronism type 1. Prior studies have focused on regulation of ENaC via protein‐protein interactions, such as an ubiquitin‐protein ligase Nedd4‐2, a ubiquitin transferase domain HECT, and serine/threonine‐protein kinases Sgk1, much is still unknown about ENaC. Our studies include expression of ENaC in yeast deletion strains to identify proteins necessary for ENaC function. A serial dilution pronging assay was performed for each separate deletion yeast strain. Results showed that although no tested strains had direct effect on ENaC functionality, the coated vesicle protein COPII, a Rubb1p (NEDD8) activator protein, and a p24 protein component involved in vesicle quality control all had negative effects on cell growth with and without salt present when particular ENaC subunits (β/γ) or all ENaC subunits (α/β/γ) were present. Further analysis of genes encoding proteins associated with ENaC will provide more insight into ENaC and its role in sodium homeostasis.

Prediction of Synergism from Chemical-Genetic Interactions by Machine Learning

The structure of genetic interaction networks predicts that, analogous to synthetic lethal interactions between non-essential genes, combinations of compounds with latent activities may exhibit potent synergism. To test this hypothesis, we generated a chemical-genetic matrix of 195 diverse yeast deletion strains treated with 4,915 compounds. This approach uncovered 1,221 genotype-specific inhibitors, which we termed cryptagens. Synergism between 8,128 structurally disparate cryptagen pairs was assessed experimentally and used to benchmark predictive algorithms. A model based on the chemical-genetic matrix and the genetic interaction network failed to accurately predict synergism. However, a combined random forest and Naive Bayesian learner that associated chemical structural features with genotype-specific growth inhibition had strong predictive power. This approach identified previously unknown compound combinations that exhibited species-selective toxicity toward human fungal pathogens. This work demonstrates that machine learning methods trained on unbiased chemical-genetic interaction data may be widely applicable for the discovery of synergistic combinations in different species.

Integrating transcriptional and protein interaction networks to prioritize condition-specific master regulators.

BackgroundGenome-wide libraries of yeast deletion strains have been used to screen for genes that drive phenotypes such as stress response. A surprising observation emerging from these studies is that the genes with the largest changes in mRNA expression during a state transition are not those that drive that transition. Here, we show that integrating gene expression data with context-independent protein interaction networks can help prioritize master regulators that drive biological phenotypes.ResultsGenes essential for survival had previously been shown to exhibit high centrality in protein interaction networks. However, the set of genes that drive growth in any specific condition is highly context-dependent. We inferred regulatory networks from gene expression data and transcription factor binding motifs in Saccharomyces cerevisiae, and found that high-degree nodes in regulatory networks are enriched for transcription factors that drive the corresponding phenotypes. We then found that using a metric combining protein interaction and transcriptional networks improved the enrichment for drivers in many of the contexts we examined. We applied this principle to a dataset of gene expression in normal human fibroblasts expressing a panel of viral oncogenes. We integrated regulatory interactions inferred from this data with a database of yeast two-hybrid protein interactions and ranked 571 human transcription factors by their combined network score. The ranked list was significantly enriched in known cancer genes that could not be found by standard differential expression or enrichment analyses.ConclusionsThere has been increasing recognition that network-based approaches can provide insight into critical cellular elements that help define phenotypic state. Our analysis suggests that no one network, based on a single data type, captures the full spectrum of interactions. Greater insight can instead be gained by exploring multiple independent networks and by choosing an appropriate metric on each network. Moreover we can improve our ability to rank phenotypic drivers by combining the information from individual networks. We propose that such integrative network analysis could be used to combine clinical gene expression data with interaction databases to prioritize patient- and disease-specific therapeutic targets.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-015-0228-1) contains supplementary material, which is available to authorized users.