A functional screen for copper homeostasis genes identifies a pharmacologically tractable cellular system
© Schlecht et al.; licensee BioMed Central Ltd. 2014
Received: 31 May 2013
Accepted: 10 March 2014
Published: 5 April 2014
Copper is essential for the survival of aerobic organisms. If copper is not properly regulated in the body however, it can be extremely cytotoxic and genetic mutations that compromise copper homeostasis result in severe clinical phenotypes. Understanding how cells maintain optimal copper levels is therefore highly relevant to human health.
We found that addition of copper (Cu) to culture medium leads to increased respiratory growth of yeast, a phenotype which we then systematically and quantitatively measured in 5050 homozygous diploid deletion strains. Cu’s positive effect on respiratory growth was quantitatively reduced in deletion strains representing 73 different genes, the function of which identify increased iron uptake as a cause of the increase in growth rate. Conversely, these effects were enhanced in strains representing 93 genes. Many of these strains exhibited respiratory defects that were specifically rescued by supplementing the growth medium with Cu. Among the genes identified are known and direct regulators of copper homeostasis, genes required to maintain low vacuolar pH, and genes where evidence supporting a functional link with Cu has been heretofore lacking. Roughly half of the genes are conserved in man, and several of these are associated with Mendelian disorders, including the Cu-imbalance syndromes Menkes and Wilson’s disease. We additionally demonstrate that pharmacological agents, including the approved drug disulfiram, can rescue Cu-deficiencies of both environmental and genetic origin.
A functional screen in yeast has expanded the list of genes required for Cu-dependent fitness, revealing a complex cellular system with implications for human health. Respiratory fitness defects arising from perturbations in this system can be corrected with pharmacological agents that increase intracellular copper concentrations.
KeywordsCopper Iron Yeast Functional Genomics Disulfiram Elesclomol Menkes Wilson’s Vacuole
Copper is an essential element for most living organisms. Its incorporation into specific enzymes is required for catalysis of several vital, and highly conserved cellular processes . For example, copper binding to specific sites in cytochrome c oxidase (i.e. complex IV of the electron transport chain) is required for complex assembly and stability, electron transfer activity, and ultimately respiratory metabolism . Copper metallation also has important roles in responding to oxidative stress, by activating superoxide dismutase (SOD1) [3, 4], and in regulating iron import by activating ferroxidases, which oxidize substrates for iron transporters [5–7].
The unique redox chemistry of copper ions, which allows it to exist in an oxidized (Cu2+) or reduced (Cu1+) state, is key to its catalytic properties but also contributes to its production of reactive oxygen species (ROS). To keep this deleterious capacity in check, the cell has evolved mechanisms to maintain tight regulatory control of copper storage and transport . Metallochaperones protect the cell from copper toxicity by binding to free copper and facilitating its transport to, and incorporation into, important target proteins . The yeast cytosolic chaperone Atx1 for example, delivers copper to the Ccc2 ATPase, which transports copper into the Golgi where it activates the Fet3 ferrooxidase, ultimately leading to iron uptake.
The importance of maintaining proper copper homeostasis is underscored by several rare, yet severe, genetic diseases. Wilson’s disease is an autosomal recessive disorder resulting from mutations in the copper transporter ATP7B, the human ortholog of yeast CCC2. Patients express a variety of neurological, psychiatric, and hepatic problems arising from abnormal copper accumulation, primarily in the brain and liver . Mutations in the related gene ATP7A cause the X-linked recessive disorder Menkes disease . Notably, the clinical symptoms of this disease arise from copper deficiency, and include neurological defects (mental retardation, seizures), growth retardation, hypothermia and “kinky” or “steely” hair . Mitochondrial complex IV disorders, including Leigh syndrome, have also been linked to genes with important roles in copper metabolism, including SCO1, SCO2, and SURF-1 [12–19]. Abnormal copper concentrations have also been observed in Alzheimer’s and Huntington’s disease [20–22], and copper has been shown to promote aggregation of the α-synuclein protein, a hallmark of Parkinson’s disease .
Yeast has been an exceptionally useful model organism for deciphering the cellular mechanisms regulating copper homeostasis [24, 25], and indeed yeast orthologs exist for most of the disease genes described above. Here, we leverage the dependency between respiratory growth rate and copper availability to conduct a systematic screen for genes associated with copper homeostasis. This screen identified genes with known roles in copper regulation, and those with no previously identified functional association with copper. Consistent with the vacuole being a cellular store for copper, many of the genes identified are required for vacuole acidification, and we go on to show that copper is in fact limiting under conditions of vacuole stress. Several genes were also orthologs of human disease genes that have not been previously linked to copper imbalance. Finally, we demonstrate that the approved drug disulfiram (DSF), and the experimental drug elesclomol (ES), can rescue respiratory growth defects arising from copper deficiency.
Results and discussion
Respiratory fitness and copper
Though yeast preferentially ferment glucose for energy, they are able to switch to oxidative phosphorylation in the absence of a fermentable carbon source [26, 27]. This attribute, in addition to its simple growth requirements, makes yeast a powerful model system for identifying chemical probes targeting energy metabolism . To identify chemical compounds that ‘boost’ respiratory growth, and potentially serve as leads for human mitochondrial diseases, we conducted a phenotypic screen of ~3000 natural product derivatives (TimTec) for compounds that accelerated growth of respiring yeast (grown in Yeast Extract, Peptone, Ethanol, Glycerol medium; YPEG), but not fermenting yeast (grown in Yeast Extract, Peptone, Dextrose medium; YPD). This screen identified a series of structurally related compounds with the desired effect, but we determined that this effect was attributed to the CuCl2 salt with which each compound was supplied (Additional file 1: Figure S1A and S1B).
We also tested the effect of copper depletion on respiratory growth, by culturing yeast in increasing concentrations (1 – 1000 μM) of the copper chelator, bathocuproine disulphonic acid (BCS). A significant dose-dependent reduction in growth was observed at BCS concentrations as low as 1 μM, and growth was strongly inhibited at BCS concentrations higher than 100 μM (Figure 1A and C). This inhibitory effect, however, was attenuated by addition of CuSO4 to the growth medium (Figure 1A). For example, the addition of 500 μM CuSO4 completely suppressed the inhibitory effects of BCS. Similar experiments using YPD media showed that addition of BCS does not alter fermentative growth (Figure 1C). Collectively, these results demonstrate a critical dependency between respiratory growth and copper ion concentrations in the growth medium.
A screen for copper homeostasis genes
To better understand the underlying cellular mechanisms controlling copper-dependent respiratory growth, we used the yeast homozygous gene deletion collection, in which individual diploid strains have both copies of a non-essential gene deleted. This collection has been a valuable resource for genome-scale analysis of conditions affecting growth [29–31]. Each strain contains unique 20-bp “barcode” sequences flanked by common priming sites, allowing the relative abundance of individual strains to be quantitatively monitored within a pool of competitively-grown strains [32, 33]. Previous work has used this resource to identify genes that protect fermenting yeast from toxic concentrations of copper . To identify genes that are important for Cu-dependent respiratory growth, we measured the fitness of 5050 homozygous deletion strains (Additional file 2: Table S1) in parallel in rich media (i.e. Yeast Extract, Peptone) using dextrose, ethanol, glycerol, or lactate as a carbon source, in the presence or absence of 500 μM CuSO4 (a concentration that increases respiratory growth rate of the parental strain). Each condition was tested in triplicate. CEL files are available via the NCBI's Gene Expression Omnibus  under accession number GSE47175. Though it was not a goal of this study, examination of this dataset reveals genes that are specifically required for metabolizing different non-fermentable carbon sources. For example, the fsh1Δ/fsh1Δ deletion strain showed an ethanol-specific growth defect (Additional file 1: Figure S2). This suggests a role for FSH1, a putative serine hydrolase that has sequence-similarity to the human candidate tumor suppressor OVCA2 [36, 37], in ethanol metabolism.
Importantly, these experiments identified a group of 313 respiratory-deficient strains (see Methods and Additional file 2: Table S1) that grew in YPD but were undetectable following competitive growth in media using non-fermentable carbon sources. As expected, the majority (259; ~83%) of these strains were previously identified in a screen for mutants with impaired mitochondrial respiration . Genes deleted in these strains were also enriched for the biological processes mitochondrion organization (p-value: 1.44e-99) and cellular respiration (p-value: 2.03e-22). We reasoned that the inability of these strains to compete with respiratory-proficient strains in our competitive assay may preclude accurate measurement of their response to Cu. Therefore, to better assay these strains, we assembled a smaller pool consisting only of these 313 strains, plus an additional 18 strains of interest (see Material and Methods), and interrogated this pool in YPE, in the presence or absence of 500 μM CuSO4.
We applied hierarchical clustering to the Cu-induced fitness changes observed in each of the four carbon sources for these 184 strains (Figure 2B). An examination of the clusters across the experiment axis showed that all replicate experiments correlated as nearest neighbors, confirming that the genome-wide data were highly reproducible. Samples grown in YPD clustered separately from the non-fermentable (YPE, YPG, and YPL) carbon-sources and in YPD, the fitness of most of these strains was not greatly affected by the addition of CuSO4. This is consistent with copper affecting respiratory, but not fermentative growth at the concentration tested. While the results were generally consistent between the non-fermentable carbon sources, carbon source-specific effects were apparent as well. Most notably, growth in lactate identified many more strains exhibiting an increased Cu boost than did growth in ethanol or glycerol. This difference may be attributed to the higher respiratory fitness of many strains in YPL (due to the lower pH of this media; discussed further below) which facilitates their detection in our competitive assay. While this explanation attributes carbon-source specific results to technical limitations of the competitive growth assay (i.e. slow growing strains dropping out of the pool in YPE and YPG, but not YPL), it is also possible that mechanistic differences in the catabolism of ethanol, glycerol, and lactate result in discrete genetic dependencies for the copper response. Further experimentation will be needed to determine whether such cases do indeed exist.
To search for functional enrichment among the genes that were deleted in the 105 and 79 strains identified above, we used the Biological Networks Gene Ontology plugin (BiNGO) for Cytoscape (see Methods). The two gene lists contained 11 and 6 ‘dubious’ open-reading frames, respectively, that partially overlapped with a verified gene. In several instances these strains confirmed the results for verified genes (such as the dubious ORFs YDR203W and YDR455C which overlap with RAV2 and NHX1, respectively). One gene, ADA2, was represented twice in the deletion pool and both strains were identified in our screen. For our Gene Ontology (GO) analysis we used the non-redundant set of genes. The 73 genes that were required for Cu-dependent growth (i.e. whose deletion diminished the Cu-dependent growth boost), were significantly enriched for several GO categories, including 2-oxoglutarate metabolic process, and iron ion homeostasis (Additional file 1: Figure S6 and Additional file 2: Table S2). Among the genes belonging to the latter term is FET3, which encodes the high-affinity iron uptake protein that links iron and copper homeostasis . The dependence of copper’s effects on Fet3 was verified in isogenic cultures, and in fact, the fet3Δ/fet3Δ strain exhibited reduced (not enhanced) growth in 500 μM CuSO4 (Additional file 1: Figure S7A). Copper-limiting conditions are known to result in cellular iron deficiency [24, 40], and we found that addition of high concentrations of FeSO4 was itself sufficient to enhance respiratory growth of yeast (Additional file 1: Figure S7B). Therefore, to further explore the role of iron, we repeated the experiment described in Figure 1A in the presence of excess FeSO4. Addition of 1 mM FeSO4 was found to confer resistance to low concentrations (≤10 μM) of BCS, and to effectively mask the growth advantages imparted by CuSO4 under these conditions (Additional file 1: Figure S7C). Collectively, these data suggest that increased iron uptake contributes to the respiratory growth increase arising from copper supplementation.
In contrast, the 93 genes in the enhanced growth group were significantly enriched for the GO processes Golgi to vacuole transport and vacuolar acidification (Figure 2C, Additional file 1: Figure S6 and Additional file 2: Table S3). Among this list of 93 genes are three genes that are directly linked to copper transport in yeast (CTR1, ATX1 and CCC2) and in higher eukaryotes (hCTR1/2, Atox1 and Atp7A/B). Deletion of these genes was previously shown to result in growth defects on low copper media . The cytosolic copper metallochaperone Atx1 transports Cu ions from the high-affinity copper transporter Ctr1 in the plasma membrane to Ccc2 on post-Golgi vesicles to eventually target it to Fet3 on the cell surface [6, 7, 41, 42]. Our screen also identified GEF1, a chloride channel involved in cation homeostasis. The Gef1 protein co-localizes with Ccc2 at late- and post-Golgi vesicles and is required for loading Cu ions onto Fet3 . For other genes identified by our screen, evidence supporting a functional role in cellular copper homeostasis is either limited or lacking entirely. These include YPL109C, which encodes a protein of unknown function that was detected in highly purified mitochondria [44, 45]. Figure 2D shows quantile-normalized fluorescence values for several of the deletion strains specifically discussed herein. The complete results for all strains identified in our screen are shown in Additional file 1: Figure S3 and S4. Collectively, these data will be a rich source of information for future characterization of genes involved in copper homeostasis.
Previous work in yeast has demonstrated that mitochondria maintain a non-proteinaceous copper pool that exceeds CcO-associated copper concentrations . It is thought that this pool may serve as a source of copper ions for chaperones that mediate metallation of CcO, which occurs at two CcO subunits encoded by the mitochondrial genome, Cox1 and Cox2 . The metallochaperone Cox17 transfers copper to two mitochondrial inner membrane proteins Cox11 and Sco1 , which then mediate metallation of Cox1 and Cox2, respectively . It is notable that our genomic screen did not identify the cox17, cox11, or sco1 deletion strains as being rescued by copper. These results are consistent with previous analysis of sco1 null strains , and of cox17 null strains, whose respiratory growth defect was rescued by copper, but only at concentrations much higher than those used in the present study .
Vacuole acidity and copper homeostasis
The yeast vacuole, generally regarded as the functional equivalent of the mammalian lysosome, is an acidic organelle with a variety of important functions including: protein degradation, ion and small-molecule storage, and pH homeostasis [50, 51]. Consistent with previous work demonstrating an important role for the vacuole in storage and mobilization of Cu ions [1, 52–54], several genes that maintain vacuolar pH, when deleted, were found to produce respiratory growth defects that were rescued by copper. These included numerous subunits of the vacuolar H+−ATPase (such as VMA1, VMA2, VMA3, VMA4, VMA6, VMA7, VMA11, VMA13, VMA16, and STV1) and 2 subunits of the RAVE complex (RAV1 and RAV2) which promotes assembly of the V-ATPase holoenzyme. Mobilization of vacuolar copper is thought to involve the Ctr2 protein, a copper transporter that localizes to the vacuolar membranes of budding yeast [52, 53], fission yeast , and mammalian cells . Though a ctr2Δ mutant was not included in our deletion collection and thus not identified in our screen, we did identify the CTR2-regulating transcription factors AFT1 and MAC1.
Human disease genes
Human disease genes putatively associated with copper imbalance
Golgi apparatus, Plasma membrane
Cu ion transport across membranes
Menkes disease (copper deficiency)
Golgi apparatus, Mitochondria
Wilson disease (copper overload)
Mitochondrial inter-membrane space
Energy and nucleotide metabolism
Immunodeficiency, sensorineural deafness
Energy metabolism, respiratory chain complex
Encephalopathy, growth retardation, vision loss
Endomembrane, plasma membrane
Vacuolar proton-translocating ATPase
Renal tubular acidosis, sensorineural deafness
Fatty acid biosynthesis
Encephalopathy, growth retardation, myopathy
Endosome membrane, lysosomal membrane
Chloride channels and ion transporter
Renal tubular disease, kidney stones
Osteosclerosis, multiple fractures, vision loss
Protein transport, membrane fusion
Arthrogryposis, renal dysfunction, cholestasis
pH regulation, ion transport
Mental retardation, seizures, ataxia
AP-1 adaptor complex, protein transport, vesicular trafficking
Mental retardation, cerebral calcifications
Spastic paraplegia, mental retardation
Protein transport, metal ion binding, membrane trafficking
Mental retardation, obesity, retinopathy
Cerebral malformation, mental retardation
Oligomeric Golgi complex, vesicular transport
Vitamin K deficiency, intracranial bleedings
AP-3 adaptor complex, protein transport
Platelet defect, albinism, immunodeficiency
Cholesterol biosynthesis, sterol metabolism
Mental retardation, congenital malformation
Skeletal dysplasia, leukocyte disorder
Pharmacological rescue of copper deficiencies
Pharmacological modulation of Cu homeostasis is an attractive therapeutic strategy for a variety of clinical applications. Copper chelating agents are currently the standard treatment to ameliorate copper overloading of affected tissues in Wilson’s disease , whereas early treatment of Menkes disease with copper has shown some promise in newborns having mutations that do not completely abrogate ATP7A . Recent work in model systems has also demonstrated that host cell copper metabolism influences RNA virus replication , and leveraging copper’s cytotoxic properties is also being explored for cancer therapy, and may be effective in targeted killing of tumor cells [67–72].
We next assessed the ability of DSF and ES to rescue the effects of genetically-induced copper deprivation. Our genomic screen identified the ctr1Δ/ctr1Δ strain, which lacks the primary copper transporter in yeast , as being most aided by supplemental copper among the >5000 strains tested (Figure 2D and Additional file 2: Table S1). We found that DSF rescued the severe respiratory defect of this strain in a dose-dependent manner, with the strongest effect observed at 0.468 μM DSF (Figure 4C). ES rescued growth of the ctr1Δ/ctr1Δ strain as well, and did so over a much broader concentration range, and at sub-nanomolar concentrations (Figure 4D). Comparable to the effects of Cu, both drugs also increased respiratory growth of the parental BY4743 strain (Additional file 1: Figure S8) suggesting that either drug could be used to correct a range of Cu-deficiencies. It is noteworthy that while DSF inhibited growth at higher concentrations, ES-induced growth inhibition was dependent on supplementing the media with Cu (Additional file 1: Figure S8), an observation that is consistent with previous findings . When tested against several strains listed in Table 1, most strains were rescued by both ES and DSF, but interestingly, neither drug rescued the respiratory growth defects of the gef1Δ/gef1Δ or ccc2Δ/ccc2Δ strains (Additional file 1: Figure S9), which lack genes specifically required for loading Cu into Fet3. These data suggest that, unlike CuSO4 added to the growth media, DSF- and ES-delivered copper require Gef1- and Ccc2-dependent Cu loading into Fet3 to confer enhanced growth.
ES is a promising anti-cancer agent that induces oxidative stress in a copper-dependent manner [67, 72]. DSF has been used for the treatment of alcoholism for decades  and confers therapeutic value by inhibiting aldehyde dehydrogenase (ALDH), which decreases the alcohol tolerance in patients . DSF has also been shown to perturb vacuolar pH in yeast, and inhibit V-ATPase activity in cell-free assays . Though our results clearly identify copper homeostasis as a rate-limiting effect of these drugs on respiratory growth, further experiments will be required to determine their precise mechanism-of-action. Nevertheless, our data highlight the ability of copper ionophores to potently and precisely tune cellular fitness under copper-limiting conditions. Leveraging the pharmacological tractability of copper homeostasis, though confronted with inherent cytoxicity obstacles, may warrant exploration as a therapeutic strategy for copper- or iron-deficiency in man.
A systematic screen of the yeast deletion collection was conducted to identify genes that have a role in Cu-dependent respiratory fitness. The screen revealed a complex cellular system involving many genes that were not previously associated with copper homeostasis. The results are consistent with copper limitation producing a secondary iron deficiency that negatively impacts respiratory growth, and with the vacuole playing a vital role in regulating intracellular copper levels. Roughly half of the genes identified in our screen are conserved in man, and many of these are associated with Mendelian diseases, underscoring the potential translation of our findings to human health. Pharmacological agents that increase intracellular copper concentrations can be effective in compensating for perturbations in copper homeostasis.
Copper (II) sulfate, tetraethylthiuram disulfide (disulfiram), and bathocuproine disulfonic acid disodium salt (BCS) were purchased from Sigma-Aldrich. Elesclomol was purchased from Selleckchem and bafilomycin A1 was purchased from Enzo Life Sciences. Copper (II) sulfate was dissolved in water and stored at room temperature. BCS, elesclomol, bafilomycin A1, and disulfiram were dissolved in DMSO, aliquoted, and stored at −20°C until use. We used a HP D300 Liquid Dispenser (Tecan) for all experiments involving DMSO-dissolved compounds.
Media and growth rate analysis
All media was prepared using deionized water. Rich media (YP) consisted of 10 g yeast extract, 10 g bactopeptone per liter. For Figure 3 A and B the YP media was buffered with 25 mM HEPES and pH-balanced as indicated using 1 M NaOH or 12.1 M HCl, to raise or lower the pH, respectively. 25 mM HEPES was also included in the media used for Additional file 1: Figure S1, and we note that addition of the HEPES buffer reduced the respiratory growth rate of yeast. All other experiments were performed using YP media without HEPES. Pre-cultures of the isogenic strains were grown overnight to saturation in rich media supplemented with 2% dextrose. These cultures were then used to inoculate YP media supplemented with carbon sources at 2% as indicated in the Figure legends. Isogenic cultures (100 μl) were inoculated at a concentration of 0.03 OD600/ml and grown in 96well microtiter plates at 30°C. The plates were sealed with adhesive plate seals (Thermo Scientific) and holes were poked in the seal for every well using a 21 gauge needle to allow sufficient aeration (cultures using non-fermentable carbon sources only). Optical density was measured every 15 min over the course of several hours (as indicated in graphs) using a GENios microplate reader (Tecan). The growth rate of a strain was calculated as follows: 1) the first 10 OD readings were averaged and subtracted from all OD readings of the corresponding curve in order to set the baseline of the growth curve to zero, 2) the area under the curve (AUC) was then calculated as the sum of all OD readings. In general, 50 and 100 reads (corresponding to 12.5 and 25 hours, respectively) were used for strains grown in fermentative conditions (dextrose and galactose) and in respiratory conditions (ethanol, glycerol, and lactate), respectively. 160 reads (40 hours) was used for Figures 4C and D (ctr1Δ/ctr1Δ). A “relative growth” value was calculated as previously described , as follows: (AUCcondition – AUCcontrol)/AUCcontrol; where AUCcontrol represents the growth rate of the reference condition (marked with an asterisk in all Figures) that was assayed on the same microtiter plate.
Deletion pool construction and growth conditions
The homozygous deletion pool was constructed as described  and stored in aliquots at −80°C. For all screening experiments, aliquots of the pool were thawed and diluted in YP media plus a carbon source (2% of dextrose, ethanol, glycerol or lactate) to a concentration of 0.04 OD600/ml. 700 μl of this cell suspension was then aliquoted into every well of a 48well plate and copper sulfate was then added (from an 500 mM stock solution in water) to a final concentration of 500 μM. The plates were sealed with adhesive plate seals and holes were poked for every well to allow sufficient aeration. The plates were incubated at 30°C with vigorous shaking and optical density was measured every 15 min over the course of the experiment. Each sample was grown for precisely 9 generations. Cells were maintained in logarithmic phase by robotically diluting cultures every three doublings using a Packard Multiprobe II four-probe liquid-handling system (PerkinElmer, Wellesley, California, United States). Experiments were performed in triplicate. After reaching 9 pool generations 600 μl of the cultures were harvested, pelleted by centrifugation and snap frozen in liquid nitrogen. The pellets were kept at −80°C until further processing (genomic DNA preparation, PCR, and microarray hybridization, see below).
To construct the pool of respiration deficient mutants we first analyzed samples from the YPD, YPE, YPG, and YPL experiments where no additional copper was added to the media. Strains with a median of log2-transformed raw fluorescence units < 7 in the combined YPE, YPG, and YPL samples and a median of log2-transformed raw fluorescence units > 8 in the YPD samples were selected. This identified 313 strains, to which we added an additional 18 strains of interest (Additional file 2: Table S1). The 331 strains were streaked from frozen stocks onto YPD agar plates, grown for 3 days at 30°C, and then pooled and stored in aliquots at −80°C. This pool was assayed as described above for the complete homozygous deletion pool.
Genomic DNA preparation, PCR, and microarray hybridization
Genomic DNA preparation, PCR amplification of molecular tags, and microarray hybridization were as described . Genomic DNA was extracted from cell pellets using the YeaStar Genomic DNA kit from Zymo Research (D2002). The relative abundance of each strain was then assessed by amplifying and hybridizing their molecular barcodes to a Genflex Tag 16 k array (Affymetrix).
Identification of strains exhibiting increased or decreased Cu-dependent growth
To quantify Cu-dependent growth of each deletion strain, we calculated a “Copper Response Score” (CRS) for each strain in each of the four respiratory pool assays; i.e. the homozygous diploid (HD) deletion pool in ethanol-, glycerol-, or lactate-containing media (YPE, YPG, and YPL), and the respiratory-deficient (RD) deletion pool in ethanol-containing medium (YPE*). The majority of strains carry two tags that hybridize to the array, an “uptag” and a “downtag” . From each array, we extracted the fluorescence intensity values for every uptag and downtag associated with the 5050 strains in the HD pool, or in the case of the RD pool, the up- and downtags associated with the 331 strains in that pool (Additional file 2: Table S1). In total, this amounted to 9937, and 675 tags, respectively. The number of tags is not exactly twice the number of strains because some strains contain only one tag. These raw fluorescence values were then log2-transformed, and quantile-normalized using the normalize.quantiles function of the preprocessCore package in R. Quantile normalization was performed on four separate groups of tags; uptags from the HD pool samples, downtags from the HD pool samples, uptags from the RD pool samples, and downtags from the RD pool samples. Eight experimental conditions (i.e. the four respiratory pool assays +/− CuSO4) were performed in triplicate, and from this set of triplicate measurements, we calculated the mean of the normalized fluorescence value for every tag. For each of the four respiratory pool assays, the mean values from CuSO4-untreated samples were then subtracted from the mean values of the CuSO4-treated samples. This value is the CRS. In cases where a strain contained two tags (i.e. the vast majority of strains), the CRS was derived from that tag having the greatest difference between Cu-untreated and -treated samples (i.e. the maximum absolute value of the Δmeans for the uptag and downtag). A moderated t-statistic was used to define differential effects of Cu-treatment in the four respiratory pools using the R package LIMMA [78, 79], and the derived p-values were further converted to q-values using Benjamini & Hochberg False Discovery Rate (FDR) correction . 105 strains that exhibited a significant (q-value < 0.05) and large (CRS > 1.5) response to copper in at least one of the four respiratory pool assays (YPG, YPL, YPE, YPE*) were defined as having an increased Cu-boost, and 79 strains that had a significant (q-value < 0.05) and small (CRS < −1.5) response to copper in at least one of these assays were defined as having a decreased Cu-boost. All instances where these criteria are met are illustrated by the filled circles in Additional file 1: Figure S3 and S4. The complete list of CRSs is provided in Additional file 2: Table S1. CEL files are available via the NCBI's Gene Expression Omnibus  under accession number GSE47175.
For the cluster analysis in Figure 2B, we calculated the Cu-induced fold change of the 184 (79 + 105) strains identified above, in each of the 12 individual replicate experiments involving the HD pool (YPE, YPG, YPL, and YPD), and applied hierarchical clustering to these data. Cu-induced fold change was calculated as (log2 (YPx + Cu)/(YPx-Cu)mean), where x is one of the 4 carbon sources (ethanol, glycerol, lactate, dextrose) tested. Fold changes of uptag and downtag were averaged. Clustering along both experiment and gene axes was performed on these values using the TIBCO Spotfire software platform.
GO term enrichment analysis
To identify enriched Gene Ontology terms among the genes that were identified in this study as enhancing or diminishing the response to copper we used the Biological Networks Gene Ontology plugin (BiNGO, version 2.4.4) for Cytoscape (version 2.8.3). Both gene lists (consisting of 93 and 73 open-reading frames, respectively), were analyzed separately using a Hypergeometric test with Benjamini & Hochberg False Discovery Rate (FDR) correction and a significance level of < 0.05. As a reference set we used the list of 4913 unique open-reading frames represented in the complete pool of 5050 homozygous deletion strains. We applied a force-directed layout to minimize the number of crossing edges and to enhance readability of node labels. Nodes were colored based on the degree of significance of overrepresentation. Uncolored nodes are not overrepresented, but they are the parents of overrepresented categories further down. The yellow and orange nodes represent terms with significant enrichment, with darker orange representing a higher degree of significance, as shown by the color legend panel in Figures 2C and Additional file 1: Figure S6. The size of each node is proportional to the number of genes with that term in the query set.
Availability of supporting data
The array data supporting the results of this article have been deposited in NCBI's Gene Expression Omnibus  and are accessible through GEO Series accession number GSE47175 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE47175).
Bathocuproine disulphonic acid
Yeast extract, peptone, dextrose
Yeast extract, peptone, ethanol
Yeast extract, peptone, glycerol
Yeast extract, peptone, lactate
Area under curve
Copper response score.
We would like to thank Joe Horecka, Patrick Flaherty, and Richard Bourgon for helpful discussion and Molly Miranda for technical assistance. This work was funded by grants from the US National Institutes of Health (P01HG000205 and R01HG003317 to R.W.D; R21HG005785 to R.W.D and R.P.S; R01EY016240 and R21HD071446 to R.W.D. and C.S.).
- Kim BE, Nevitt T, Thiele DJ: Mechanisms for copper acquisition, distribution and regulation. Nat Chem Biol. 2008, 4 (3): 176-185. 10.1038/nchembio.72.PubMedView ArticleGoogle Scholar
- Horn D, Barrientos A: Mitochondrial copper metabolism and delivery to cytochrome c oxidase. IUBMB Life. 2008, 60 (7): 421-429. 10.1002/iub.50.PubMed CentralPubMedView ArticleGoogle Scholar
- Valentine JS, Doucette PA, Zittin Potter S: Copper-zinc superoxide dismutase and amyotrophic lateral sclerosis. Annu Rev Biochem. 2005, 74: 563-593. 10.1146/annurev.biochem.72.121801.161647.PubMedView ArticleGoogle Scholar
- Furukawa Y, Torres AS, O'Halloran TV: Oxygen-induced maturation of SOD1: a key role for disulfide formation by the copper chaperone CCS. Embo J. 2004, 23 (14): 2872-2881. 10.1038/sj.emboj.7600276.PubMed CentralPubMedView ArticleGoogle Scholar
- Hellman NE, Gitlin JD: Ceruloplasmin metabolism and function. Annu Rev Nutr. 2002, 22: 439-458. 10.1146/annurev.nutr.22.012502.114457.PubMedView ArticleGoogle Scholar
- Stearman R, Yuan DS, Yamaguchi-Iwai Y, Klausner RD, Dancis A: A permease-oxidase complex involved in high-affinity iron uptake in yeast. Science. 1996, 271 (5255): 1552-1557. 10.1126/science.271.5255.1552.PubMedView ArticleGoogle Scholar
- De Silva DM, Askwith CC, Eide D, Kaplan J: The FET3 gene product required for high affinity iron transport in yeast is a cell surface ferroxidase. J Biol Chem. 1995, 270 (3): 1098-1101. 10.1074/jbc.270.3.1098.PubMedView ArticleGoogle Scholar
- Robinson NJ, Winge DR: Copper metallochaperones. Annu Rev Biochem. 2010, 79: 537-562. 10.1146/annurev-biochem-030409-143539.PubMed CentralPubMedView ArticleGoogle Scholar
- Ala A, Walker AP, Ashkan K, Dooley JS, Schilsky ML: Wilson's disease. Lancet. 2007, 369 (9559): 397-408. 10.1016/S0140-6736(07)60196-2.PubMedView ArticleGoogle Scholar
- Menkes JH, Alter M, Steigleder GK, Weakley DR, Sung JH: A sex-linked recessive disorder with retardation of growth, peculiar hair, and focal cerebral and cerebellar degeneration. Pediatrics. 1962, 29: 764-779.PubMedGoogle Scholar
- De Bie P, Muller P, Wijmenga C, Klomp LW: Molecular pathogenesis of Wilson and Menkes disease: correlation of mutations with molecular defects and disease phenotypes. J Med Genet. 2007, 44 (11): 673-688. 10.1136/jmg.2007.052746.PubMed CentralPubMedView ArticleGoogle Scholar
- Horng YC, Leary SC, Cobine PA, Young FB, George GN, Shoubridge EA, Winge DR: Human Sco1 and Sco2 function as copper-binding proteins. J Biol Chem. 2005, 280 (40): 34113-34122. 10.1074/jbc.M506801200.PubMedView ArticleGoogle Scholar
- Leary SC, Cobine PA, Kaufman BA, Guercin GH, Mattman A, Palaty J, Lockitch G, Winge DR, Rustin P, Horvath R, Shoubridge EA: The human cytochrome c oxidase assembly factors SCO1 and SCO2 have regulatory roles in the maintenance of cellular copper homeostasis. Cell Metab. 2007, 5 (1): 9-20. 10.1016/j.cmet.2006.12.001.PubMedView ArticleGoogle Scholar
- Leary SC, Kaufman BA, Pellecchia G, Guercin GH, Mattman A, Jaksch M, Shoubridge EA: Human SCO1 and SCO2 have independent, cooperative functions in copper delivery to cytochrome c oxidase. Hum Mol Genet. 2004, 13 (17): 1839-1848. 10.1093/hmg/ddh197.PubMedView ArticleGoogle Scholar
- Bestwick M, Jeong MY, Khalimonchuk O, Kim H, Winge DR: Analysis of Leigh syndrome mutations in the yeast SURF1 homolog reveals a new member of the cytochrome oxidase assembly factor family. Mol Cell Biol. 2010, 30 (18): 4480-4491. 10.1128/MCB.00228-10.PubMed CentralPubMedView ArticleGoogle Scholar
- Valnot I, Osmond S, Gigarel N, Mehaye B, Amiel J, Cormier-Daire V, Munnich A, Bonnefont JP, Rustin P, Rotig A: Mutations of the SCO1 gene in mitochondrial cytochrome c oxidase deficiency with neonatal-onset hepatic failure and encephalopathy. Am J Hum Genet. 2000, 67 (5): 1104-1109.PubMed CentralPubMedGoogle Scholar
- Horvath R, Lochmuller H, Stucka R, Yao J, Shoubridge EA, Kim SH, Gerbitz KD, Jaksch M: Characterization of human SCO1 and COX17 genes in mitochondrial cytochrome-c-oxidase deficiency. Biochem Biophys Res Commun. 2000, 276 (2): 530-533. 10.1006/bbrc.2000.3495.PubMedView ArticleGoogle Scholar
- Papadopoulou LC, Sue CM, Davidson MM, Tanji K, Nishino I, Sadlock JE, Krishna S, Walker W, Selby J, Glerum DM, Coster RV, Lyon G, Scalais E, Lebel R, Kaplan P, Shanske S, De Vivo DC, Bonilla E, Hirano M, DiMauro S, Schon EA: Fatal infantile cardioencephalomyopathy with COX deficiency and mutations in SCO2, a COX assembly gene. Nat Genet. 1999, 23 (3): 333-337. 10.1038/15513.PubMedView ArticleGoogle Scholar
- Jaksch M, Ogilvie I, Yao J, Kortenhaus G, Bresser HG, Gerbitz KD, Shoubridge EA: Mutations in SCO2 are associated with a distinct form of hypertrophic cardiomyopathy and cytochrome c oxidase deficiency. Hum Mol Genet. 2000, 9 (5): 795-801. 10.1093/hmg/9.5.795.PubMedView ArticleGoogle Scholar
- Desai V, Kaler SG: Role of copper in human neurological disorders. Am J Clin Nutr. 2008, 88 (3): 855S-858S.PubMedGoogle Scholar
- Strozyk D, Launer LJ, Adlard PA, Cherny RA, Tsatsanis A, Volitakis I, Blennow K, Petrovitch H, White LR, Bush AI: Zinc and copper modulate Alzheimer Abeta levels in human cerebrospinal fluid. Neurobiol Aging. 2009, 30 (7): 1069-1077. 10.1016/j.neurobiolaging.2007.10.012.PubMed CentralPubMedView ArticleGoogle Scholar
- Fox JH, Kama JA, Lieberman G, Chopra R, Dorsey K, Chopra V, Volitakis I, Cherny RA, Bush AI, Hersch S: Mechanisms of copper ion mediated Huntington's disease progression. PLoS One. 2007, 2 (3): e334-10.1371/journal.pone.0000334.PubMed CentralPubMedView ArticleGoogle Scholar
- Rasia RM, Bertoncini CW, Marsh D, Hoyer W, Cherny D, Zweckstetter M, Griesinger C, Jovin TM, Fernandez CO: Structural characterization of copper(II) binding to alpha-synuclein: Insights into the bioinorganic chemistry of Parkinson's disease. Proc Natl Acad Sci U S A. 2005, 102 (12): 4294-4299. 10.1073/pnas.0407881102.PubMed CentralPubMedView ArticleGoogle Scholar
- De Freitas J, Wintz H, Kim JH, Poynton H, Fox T, Vulpe C: Yeast, a model organism for iron and copper metabolism studies. Biometals. 2003, 16 (1): 185-197. 10.1023/A:1020771000746.PubMedView ArticleGoogle Scholar
- Askwith C, Kaplan J: Iron and copper transport in yeast and its relevance to human disease. Trends Biochem Sci. 1998, 23 (4): 135-138. 10.1016/S0968-0004(98)01192-X.PubMedView ArticleGoogle Scholar
- Diaz-Ruiz R, Uribe-Carvajal S, Devin A, Rigoulet M: Tumor cell energy metabolism and its common features with yeast metabolism. Biochim Biophys Acta. 2009, 1796 (2): 252-265.PubMedGoogle Scholar
- Rossignol R, Gilkerson R, Aggeler R, Yamagata K, Remington SJ, Capaldi RA: Energy substrate modulates mitochondrial structure and oxidative capacity in cancer cells. Cancer Res. 2004, 64 (3): 985-993. 10.1158/0008-5472.CAN-03-1101.PubMedView ArticleGoogle Scholar
- St Onge R, Schlecht U, Scharfe C, Evangelista M: Forward chemical genetics in yeast for discovery of chemical probes targeting metabolism. Molecules. 2012, 17 (11): 13098-13115.PubMed CentralPubMedView ArticleGoogle Scholar
- Hillenmeyer ME, Fung E, Wildenhain J, Pierce SE, Hoon S, Lee W, Proctor M, St Onge RP, Tyers M, Koller D, Altman RB, Davis RW, Nislow C, Giaever G: The chemical genomic portrait of yeast: uncovering a phenotype for all genes. Science. 2008, 320 (5874): 362-365. 10.1126/science.1150021.PubMed CentralPubMedView ArticleGoogle Scholar
- Lee W, St Onge RP, Proctor M, Flaherty P, Jordan MI, Arkin AP, Davis RW, Nislow C, Giaever G: Genome-wide requirements for resistance to functionally distinct DNA-damaging agents. PLoS Genet. 2005, 1 (2): e24-10.1371/journal.pgen.0010024.PubMed CentralPubMedView ArticleGoogle Scholar
- Steinmetz LM, Scharfe C, Deutschbauer AM, Mokranjac D, Herman ZS, Jones T, Chu AM, Giaever G, Prokisch H, Oefner PJ, Davis RW: Systematic screen for human disease genes in yeast. Nat Genet. 2002, 31 (4): 400-404.PubMedGoogle Scholar
- Giaever G, Chu AM, Ni L, Connelly C, Riles L, Veronneau S, Dow S, Lucau-Danila A, Anderson K, Andre B, Arkin AP, Astromoff A, El-Bakkoury M, Bangham R, Benito R, Brachat S, Campanaro S, Curtiss M, Davis K, Deutschbauer A, Entian KD, Flaherty P, Foury F, Garfinkel DJ, Gerstein M, Gotte D, Güldener U, Hegemann JH, Hempel S, Herman Z, et al: Functional profiling of the Saccharomyces cerevisiae genome. Nature. 2002, 418 (6896): 387-391. 10.1038/nature00935.PubMedView ArticleGoogle Scholar
- Winzeler EA, Shoemaker DD, Astromoff A, Liang H, Anderson K, Andre B, Bangham R, Benito R, Boeke JD, Bussey H, Chu AM, Connelly C, Davis K, Dietrich F, Dow SW, El Bakkoury M, Foury F, Friend SH, Gentalen E, Giaever G, Hegemann JH, Jones T, Laub M, Liao H, Liebundguth N, Lockhart DJ, Lucau-Danila A, Lussier M, M'Rabet N, Menard P, et al: Functional characterization of the S. cerevisiae genome by gene deletion and parallel analysis. Science. 1999, 285 (5429): 901-906. 10.1126/science.285.5429.901.PubMedView ArticleGoogle Scholar
- Jo WJ, Loguinov A, Chang M, Wintz H, Nislow C, Arkin AP, Giaever G, Vulpe CD: Identification of genes involved in the toxic response of Saccharomyces cerevisiae against iron and copper overload by parallel analysis of deletion mutants. Toxicol Sci. 2008, 101 (1): 140-151.PubMedView ArticleGoogle Scholar
- Edgar R, Domrachev M, Lash AE: Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 2002, 30 (1): 207-210. 10.1093/nar/30.1.207.PubMed CentralPubMedView ArticleGoogle Scholar
- Huang J, Hu N, Goldstein AM, Emmert-Buck MR, Tang ZZ, Roth MJ, Wang QH, Dawsey SM, Han XY, Ding T, Li G, Giffen C, Taylor PR: High frequency allelic loss on chromosome 17p13.3-p11.1 in esophageal squamous cell carcinomas from a high incidence area in northern China. Carcinogenesis. 2000, 21 (11): 2019-2026. 10.1093/carcin/21.11.2019.PubMedView ArticleGoogle Scholar
- Schultz DC, Vanderveer L, Berman DB, Hamilton TC, Wong AJ, Godwin AK: Identification of two candidate tumor suppressor genes on chromosome 17p13.3. Cancer Res. 1996, 56 (9): 1997-2002.PubMedGoogle Scholar
- Maere S, Heymans K, Kuiper M: BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks. Bioinformatics. 2005, 21 (16): 3448-3449. 10.1093/bioinformatics/bti551.PubMedView ArticleGoogle Scholar
- Askwith C, Eide D, Van Ho A, Bernard PS, Li L, Davis-Kaplan S, Sipe DM, Kaplan J: The FET3 gene of S. cerevisiae encodes a multicopper oxidase required for ferrous iron uptake. Cell. 1994, 76 (2): 403-410. 10.1016/0092-8674(94)90346-8.PubMedView ArticleGoogle Scholar
- Arredondo M, Nunez MT: Iron and copper metabolism. Mol Aspects Med. 2005, 26 (4–5): 313-327.PubMedView ArticleGoogle Scholar
- Dancis A, Yuan DS, Haile D, Askwith C, Eide D, Moehle C, Kaplan J, Klausner RD: Molecular characterization of a copper transport protein in S. cerevisiae: an unexpected role for copper in iron transport. Cell. 1994, 76 (2): 393-402. 10.1016/0092-8674(94)90345-X.PubMedView ArticleGoogle Scholar
- Dancis A, Haile D, Yuan DS, Klausner RD: The Saccharomyces cerevisiae copper transport protein (Ctr1p). Biochemical characterization, regulation by copper, and physiologic role in copper uptake. J Biol Chem. 1994, 269 (41): 25660-25667.PubMedGoogle Scholar
- Gaxiola RA, Yuan DS, Klausner RD, Fink GR: The yeast CLC chloride channel functions in cation homeostasis. Proc Natl Acad Sci U S A. 1998, 95 (7): 4046-4050. 10.1073/pnas.95.7.4046.PubMed CentralPubMedView ArticleGoogle Scholar
- Reinders J, Zahedi RP, Pfanner N, Meisinger C, Sickmann A: Toward the complete yeast mitochondrial proteome: multidimensional separation techniques for mitochondrial proteomics. J Proteome Res. 2006, 5 (7): 1543-1554. 10.1021/pr050477f.PubMedView ArticleGoogle Scholar
- Sickmann A, Reinders J, Wagner Y, Joppich C, Zahedi R, Meyer HE, Schonfisch B, Perschil I, Chacinska A, Guiard B, Rehling P, Pfanner N, Meisinger C: The proteome of Saccharomyces cerevisiae mitochondria. Proc Natl Acad Sci U S A. 2003, 100 (23): 13207-13212. 10.1073/pnas.2135385100.PubMed CentralPubMedView ArticleGoogle Scholar
- Cobine PA, Ojeda LD, Rigby KM, Winge DR: Yeast contain a non-proteinaceous pool of copper in the mitochondrial matrix. J Biol Chem. 2004, 279 (14): 14447-14455. 10.1074/jbc.M312693200.PubMedView ArticleGoogle Scholar
- Horng YC, Cobine PA, Maxfield AB, Carr HS, Winge DR: Specific copper transfer from the Cox17 metallochaperone to both Sco1 and Cox11 in the assembly of yeast cytochrome C oxidase. J Biol Chem. 2004, 279 (34): 35334-35340. 10.1074/jbc.M404747200.PubMedView ArticleGoogle Scholar
- Glerum DM, Shtanko A, Tzagoloff A: SCO1 and SCO2 act as high copy suppressors of a mitochondrial copper recruitment defect in Saccharomyces cerevisiae. J Biol Chem. 1996, 271 (34): 20531-20535. 10.1074/jbc.271.34.20531.PubMedView ArticleGoogle Scholar
- Glerum DM, Shtanko A, Tzagoloff A: Characterization of COX17, a yeast gene involved in copper metabolism and assembly of cytochrome oxidase. J Biol Chem. 1996, 271 (24): 14504-14509. 10.1074/jbc.271.24.14504.PubMedView ArticleGoogle Scholar
- Klionsky DJ, Herman PK, Emr SD: The fungal vacuole: composition, function, and biogenesis. Microbiol Rev. 1990, 54 (3): 266-292.PubMed CentralPubMedGoogle Scholar
- Li SC, Kane PM: The yeast lysosome-like vacuole: endpoint and crossroads. Biochim Biophys Acta. 2009, 1793 (4): 650-663. 10.1016/j.bbamcr.2008.08.003.PubMed CentralPubMedView ArticleGoogle Scholar
- Portnoy ME, Schmidt PJ, Rogers RS, Culotta VC: Metal transporters that contribute copper to metallochaperones in Saccharomyces cerevisiae. Mol Genet Genomics. 2001, 265 (5): 873-882. 10.1007/s004380100482.PubMedView ArticleGoogle Scholar
- Rees EM, Lee J, Thiele DJ: Mobilization of intracellular copper stores by the ctr2 vacuolar copper transporter. J Biol Chem. 2004, 279 (52): 54221-54229. 10.1074/jbc.M411669200.PubMedView ArticleGoogle Scholar
- Yuan DS, Dancis A, Klausner RD: Restriction of copper export in Saccharomyces cerevisiae to a late Golgi or post-Golgi compartment in the secretory pathway. J Biol Chem. 1997, 272 (41): 25787-25793. 10.1074/jbc.272.41.25787.PubMedView ArticleGoogle Scholar
- Bellemare DR, Shaner L, Morano KA, Beaudoin J, Langlois R, Labbe S: Ctr6, a vacuolar membrane copper transporter in Schizosaccharomyces pombe. J Biol Chem. 2002, 277 (48): 46676-46686. 10.1074/jbc.M206444200.PubMedView ArticleGoogle Scholar
- Bertinato J, Swist E, Plouffe LJ, Brooks SP, L'Abbe MR: Ctr2 is partially localized to the plasma membrane and stimulates copper uptake in COS-7 cells. Biochem J. 2008, 409 (3): 731-740. 10.1042/BJ20071025.PubMedView ArticleGoogle Scholar
- Qi J, Han A, Yang Z, Li C: Metal-sensing transcription factors Mac1p and Aft1p coordinately regulate vacuolar copper transporter CTR2 in Saccharomyces cerevisiae. Biochem Biophys Res Commun. 2012, 423 (2): 424-428. 10.1016/j.bbrc.2012.05.150.PubMedView ArticleGoogle Scholar
- Orij R, Urbanus ML, Vizeacoumar FJ, Giaever G, Boone C, Nislow C, Brul S, Smits GJ: Genome-wide analysis of intracellular pH reveals quantitative control of cell division rate by pH(c) in Saccharomyces cerevisiae. Genome Biol. 2012, 13 (9): R80-10.1186/gb-2012-13-9-r80.PubMed CentralPubMedView ArticleGoogle Scholar
- Brett CL, Kallay L, Hua Z, Green R, Chyou A, Zhang Y, Graham TR, Donowitz M, Rao R: Genome-wide analysis reveals the vacuolar pH-stat of Saccharomyces cerevisiae. PLoS One. 2011, 6 (3): e17619-10.1371/journal.pone.0017619.PubMed CentralPubMedView ArticleGoogle Scholar
- Serrano R, Bernal D, Simon E, Arino J: Copper and iron are the limiting factors for growth of the yeast Saccharomyces cerevisiae in an alkaline environment. J Biol Chem. 2004, 279 (19): 19698-19704. 10.1074/jbc.M313746200.PubMedView ArticleGoogle Scholar
- Huss M, Wieczorek H: Inhibitors of V-ATPases: old and new players. J Exp Biol. 2009, 212 (Pt 3): 341-346.PubMedView ArticleGoogle Scholar
- Kirchhausen T: Three ways to make a vesicle. Nat Rev Mol Cell Biol. 2000, 1 (3): 187-198. 10.1038/35043117.PubMedView ArticleGoogle Scholar
- Ishizaki H, Spitzer M, Wildenhain J, Anastasaki C, Zeng Z, Dolma S, Shaw M, Madsen E, Gitlin J, Marais R, Tyers M, Patton EE: Combined zebrafish-yeast chemical-genetic screens reveal gene-copper-nutrition interactions that modulate melanocyte pigmentation. Dis Model Mech. 2010, 3 (9–10): 639-651.PubMed CentralPubMedView ArticleGoogle Scholar
- Maglott D, Ostell J, Pruitt KD, Tatusova T: Entrez Gene: gene-centered information at NCBI. Nucleic Acids Res. 2011, 39 (Database issue): D52-D57.PubMed CentralPubMedView ArticleGoogle Scholar
- Kaler SG, Holmes CS, Goldstein DS, Tang J, Godwin SC, Donsante A, Liew CJ, Sato S, Patronas N: Neonatal diagnosis and treatment of Menkes disease. N Engl J Med. 2008, 358 (6): 605-614. 10.1056/NEJMoa070613.PubMed CentralPubMedView ArticleGoogle Scholar
- Sasvari Z, Kovalev N, Nagy PD: The GEF1 proton-chloride exchanger affects tombusvirus replication via regulation of copper metabolism in yeast. J Virol. 2013, 87 (3): 1800-1810. 10.1128/JVI.02003-12.PubMed CentralPubMedView ArticleGoogle Scholar
- Nagai M, Vo NH, Shin Ogawa L, Chimmanamada D, Inoue T, Chu J, Beaudette-Zlatanova BC, Lu R, Blackman RK, Barsoum J, Koya K, Wada Y: The oncology drug elesclomol selectively transports copper to the mitochondria to induce oxidative stress in cancer cells. Free Radic Biol Med. 2012, 52 (10): 2142-2150. 10.1016/j.freeradbiomed.2012.03.017.PubMedView ArticleGoogle Scholar
- Cen D, Brayton D, Shahandeh B, Meyskens FL, Farmer PJ: Disulfiram facilitates intracellular Cu uptake and induces apoptosis in human melanoma cells. J Med Chem. 2004, 47 (27): 6914-6920. 10.1021/jm049568z.PubMedView ArticleGoogle Scholar
- Cen D, Gonzalez RI, Buckmeier JA, Kahlon RS, Tohidian NB, Meyskens FL: Disulfiram induces apoptosis in human melanoma cells: a redox-related process. Mol Cancer Ther. 2002, 1 (3): 197-204.PubMedGoogle Scholar
- Chen D, Cui QC, Yang H, Dou QP: Disulfiram, a clinically used anti-alcoholism drug and copper-binding agent, induces apoptotic cell death in breast cancer cultures and xenografts via inhibition of the proteasome activity. Cancer Res. 2006, 66 (21): 10425-10433. 10.1158/0008-5472.CAN-06-2126.PubMedView ArticleGoogle Scholar
- Liu P, Brown S, Goktug T, Channathodiyil P, Kannappan V, Hugnot JP, Guichet PO, Bian X, Armesilla AL, Darling JL, Wang W: Cytotoxic effect of disulfiram/copper on human glioblastoma cell lines and ALDH-positive cancer-stem-like cells. Br J Cancer. 2012, 107 (9): 1488-1497. 10.1038/bjc.2012.442.PubMed CentralPubMedView ArticleGoogle Scholar
- Blackman RK, Cheung-Ong K, Gebbia M, Proia DA, He S, Kepros J, Jonneaux A, Marchetti P, Kluza J, Rao PE, Wada Y, Giaever G, Nislow C: Mitochondrial electron transport is the cellular target of the oncology drug elesclomol. PLoS One. 2012, 7 (1): e29798-10.1371/journal.pone.0029798.PubMed CentralPubMedView ArticleGoogle Scholar
- Suh JJ, Pettinati HM, Kampman KM, O'Brien CP: The status of disulfiram: a half of a century later. J Clin Psychopharmacol. 2006, 26 (3): 290-302. 10.1097/01.jcp.0000222512.25649.08.PubMedView ArticleGoogle Scholar
- Deitrich RA, Erwin VG: Mechanism of the inhibition of aldehyde dehydrogenase in vivo by disulfiram and diethyldithiocarbamate. Mol Pharmacol. 1971, 7 (3): 301-307.PubMedGoogle Scholar
- Johnson RM, Allen C, Melman SD, Waller A, Young SM, Sklar LA, Parra KJ: Identification of inhibitors of vacuolar proton-translocating ATPase pumps in yeast by high-throughput screening flow cytometry. Anal Biochem. 2010, 398 (2): 203-211. 10.1016/j.ab.2009.12.020.PubMed CentralPubMedView ArticleGoogle Scholar
- Schlecht U, Miranda M, Suresh S, Davis RW, St Onge RP: Multiplex assay for condition-dependent changes in protein-protein interactions. Proc Natl Acad Sci U S A. 2012, 109 (23): 9213-9218. 10.1073/pnas.1204952109.PubMed CentralPubMedView ArticleGoogle Scholar
- Hoon S, Smith AM, Wallace IM, Suresh S, Miranda M, Fung E, Proctor M, Shokat KM, Zhang C, Davis RW, Giaever G, St Onge RP, Nislow C: An integrated platform of genomic assays reveals small-molecule bioactivities. Nat Chem Biol. 2008, 4 (8): 498-506. 10.1038/nchembio.100.PubMedView ArticleGoogle Scholar
- Smyth GK, Yang YH, Speed T: Statistical issues in cDNA microarray data analysis. Methods Mol Biol. 2003, 224: 111-136.PubMedGoogle Scholar
- Smyth GK: Limma: linear models for microarray data. Bioinformatics and Computational Biology Solutions Using R and Bioconductor. Edited by: Gentleman R, Carey V, Huber W, Irizarry R, Dudoit S. 2005, New York, NY.: Springer, 397-420.View ArticleGoogle Scholar
- Benjamini Y, Hochberg Y: Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society SeriesB. 1995, 57: 289-300.Google Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.