BACKGROUND
in addition to the assimilation of carbon and oxygen a vital function of all living cells is to control the accumulation from the environment of various chemical elements required for numerous essential biochemical processes, including incorporation into macromolecules , as cofactors in enzymes , in cellular buffering , and as second messengers in signaling processes .
though essential for life, many of these elements are also potentially toxic.
to balance the demand of these essential elements for normal growth and reproduction with their potential toxicity living cells have evolved complex regulatory mechanisms to control their uptake and accumulation.
identification of the genes and gene networks that control these regulatory processes is a critical first step to a complete understanding of the molecular mechanisms involved.
such an understanding will have many potential benefits, including in our understanding of human disease, and in the development of more nutritious food crops with increased concentrations of essential micronutrients , lower concentrations of potentially toxic trace elements , and that are produced using cropping systems that require less mineral nutrient inputs .
the yeast saccharomyces cerevisiae has proved to be a powerful model for the study of mineral nutrient and trace element homeostasis, for recent reviews see  <cit> .
the availability of full genome deletion and open reading frame  overexpression collections  <cit>  have further enhanced the power of yeast as a model system, and these genome-wide tools have already been applied to the study of mineral nutrient and trace element homeostasis, indirectly by studying the growth effects of elevated transition metals  <cit> , b  <cit> , selenite  <cit> , and fe  <cit>  and zn  <cit>  deficiency.
studies have also been undertaken in which accumulation of fe  <cit> , cs, sr  <cit> , and p  <cit>  have been directly quantified in yeast cells.
in order to investigate the interactions between the mineral nutrient and trace element content of yeast  an investigation of the simultaneous accumulation of multi-elements  has also been performed  <cit> .
here, we build on these previous studies and extend them by directly measuring, by inductively coupled plasma-mass spectrometry , the simultaneous accumulation of as, ca, cd, cl, co, cu, fe, k, mg, mn, mo, na, ni, p, s, se, and zn in the  <dig> yeast strains in the haploid deletion collection, the  <dig> essential genes in the diploid heterozygous knockout collection, and the  <dig> genes in the open reading frame  over expression collection.
results of this study provide new data for the functional characterization of yeast genes of unknown function, provide new functional insight into genes with known functions, and provide a deeper understanding of the cellular systems and gene networks that are involved in controlling the yeast ionome.
a publically accessible database at http://www.ionomicshub.org has also been developed to facilitate broad utilization of this large data resource.
RESULTS
genome-wide scan of genes impacting the yeast ionome
we quantified the concentration of ca, cd, co, cu, fe, k, mg, mn, mo, na, ni, p, s and zn  in the  <dig> viable mutant strains of yeast in which the open reading frames  in haploid cells have been disrupted one at a time , and in the  <dig> viable mutant strains where a single copy of the orfs in diploid cells have been disrupted to produce a heterozygous knockout .
further, we also quantified the concentrations of ca, cd, co, cu, fe, k, mg, mn, mo, na, ni, p, s and zn in the  <dig> viable strains of yeast where each orf in the genome has been ectopically overexpressed one at a time .
improvements in our analytical methodologies also allowed use to additionally quantify as, se and cl in the oe collection.
the data was collected as described by danku et al.,  <cit>  and each data set  separately normalized and summarized over  <dig>   <dig> or  <dig> biological replicates.
the data was analyzed statistically using linear mixed-effect models to determine strains and elements that significantly change in abundance as compared to the median trend after manually filtering for quality control and controlling the false discovery rate   <cit> .
of the  <dig> genes tested in the haploid knockout collection the loss of function of  <dig> of these genes  had a significant effect on the concentration of at least one element in the yeast ionome.
the loss of function of  <dig> genes , out of the  <dig> tested in the diploid heterozygous knockout collection, were also found to significantly affect the concentration of at least one element in the yeast ionome.
together, this establishes that 10% of the orfs in the complete genome of yeast are involved directly or indirectly in controlling the ionome .
the ectopic over expression of  <dig> orfs  out of the  <dig> tested were also found to significantly affect the concentration of at least one element in the yeast ionome, establishing that ectopic over expression of 8% of the total orfs in yeast affect the yeast ionome .
of the genes we observed to significantly affect the yeast ionome from the ko, kod and oe sets, we observe that  <dig> occur in both the knockout  and oe sets .
using the hypergeometric test we establish that this overlap is not significant .
this supports the conclusion that on a genome-wide scale for control of the ionome in yeast loss and gain of gene function produce different, non-overlapping affects.
group a - practical significance cutoff at − <dig> to 20%, group b - practical cut off at  <dig> to 100% & - <dig> to −50%, group c - practical cut off at 100% and −50%.
groups represented in volcano plots .
to help identify those genes which have a practical impact on the yeast ionome we divided the lists of genes that have a statistically significant effect on the ionome, for each set , into three groups based on the magnitude of the percent changes from the mean of the normalized element abundance across all mutants.
group c contains genes that cause a ≥ 100% increase or ≤ −50% decrease in any of the elements we quantified, group b contains genes that cause  <dig> to 100% & - <dig> to −50% change, and group a −20% to 20% change.
the percentage change was calculated as the difference between the normalized element abundance of a mutant and the normalized mean element abundance across all mutants, divided by the normalized mean element abundance across all mutants.
to illustrate the distribution of genes in each of the groups a, b and c for each of the gene sets  we have plotted the magnitudes and statistical significance of the impact of each gene on all the measured elements in the ionome .
both the loss of function  and gain of function  gene sets have a similar range of statistical significance  but the effect size  for the knockout  and oe sets differ, with the oe set producing a larger range of effect sizes skewed towards larger positive effects.
arsenic, cl and se were included in the analysis of the oe set but not the ko and kod set.
however, of the  <dig> data elements in the oe set with an effect size >  <dig> only two were for se and one for cl.
from this we determine that the increase in the effect size of the outliers in the oe data set is not an artifact due to the addition of as, cl and se to the oe data set.
validation of the identified gene sets against existing knowledge
to help validate the loss of function set of genes we observed to have a significant effect on the yeast ionome we compared our set to that generated by eide et al.,  <cit> .
in the screen of a whole-genome homozygous diploid knockout collection, at a first pass through the collection at n =  <dig> replicate samples per yeast strain, eide and coworkers identified  <dig> genes that reproducibly affected the yeast ionome.
of these  <dig> genes we observe  <dig> to significantly affect the ionome in our ko dataset.
using the hypergeometric test we determined that this overlap is highly significant  and would not be expected to occur if the genes were selected at random.
of the overlapping  <dig> genes  <dig> fall into our middle effect group b set of genes, with only  <dig> genes in our small effect group a set of genes, and  <dig> in our large effect group c set of genes.
such a significant overlap in the knockout gene set reported by eide et al.,  <cit>  to affect the ionome and the knockout gene set we report here strongly validates our approach and gives us confidence that the more extensive high-resolution genome wide scan of the ionome reported here  will reveal novel and significant insight into the regulation of the yeast ionome.
importantly,  <dig> of the large effect genes in our ko group c are altered in mo, an element not measured by eide and co-workers, explaining why these large effect genes were not identified by eide et al.,  <cit> .
to further validate our sets of significant genes that affect the ionome in yeast we investigated if genes known to be involved in regulation of various elements in the ionome from the current literature also occurred in our gene sets.
based on the literature we generated a list of genes known to be involved in the homeostasis of the essential mineral nutrients fe, cu, zn, mn, mg, ca, k and na in yeast  <cit>  .
of this list of  <dig> genes known to be involved in mineral nutrient homeostasis in yeast we identified loss of function of  <dig> to have a significant impact on the yeast ionome .
a further  <dig> were found to have a significant effect on the ionome when overexpressed .
there are multiple explanations why we only identified about 1/3rd of the genes known to be involved in mineral nutrient homeostasis in yeast.
particularly significant is the fact that many of the  <dig> genes known to be involved in mineral nutrient homeostasis are primarily involved during growth under nutrient deficiency and not the sufficiency conditions we performed our experiments under.
further, even though a gene is known to be involved in mineral nutrient homeostasis its loss of function may be compensated for by other genes and thus might not in itself be manifest as a change in the ionome as measured in our experiment.
note 1: ygl168w that overlaps pmr <dig> also has significant increase in cd, and ygl167c is also elevated in cd but just below the significance cut off.
interestingly, we observed a high level of mo accumulation in strains with loss of function alleles of several known fe accumulation genes   even though no changes in fe accumulation are observed.
ftr <dig> and fet <dig> encode the high affinity fe transporter and ferric chelate reductase that work together for high-affinity fe uptake  <cit> .
ctr <dig> encodes the high affinity cu transporter and is responsible for cu uptake  <cit> , which is required for the function of ftr <dig>  therefore, without a functional ctr <dig> gene yeast have impaired high-affinity fe uptake.
given the critical role these genes play in fe homeostasis we might have expected to see a change in fe accumulation in loss of function mutants of these genes.
however, uptake of fe by the low affinity fet <dig> transporter may have compensated.
the connection of fe homeostasis and mo accumulation was surprising since yeast do not require mo  <cit>  unlike plants in which a connection between fe and mo has been observed  <cit> .
in the wild-type by <dig> with low fe or cu in the growth media we also observe an increase in mo accumulation , supporting the link between reduced cu uptake, diminished high-affinity fe uptake and increased mo accumulation.
also, ectopic over expression of cup <dig>  causes a specific accumulation of cu and mo .
in this situation we might expect that the elevated cu is bound to cup <dig> causing fe deficiency via inactivation of ftr1-fet <dig> high affinity uptake system.
the mo accumulation in this strain also supports the link between fe-deficiency and mo accumulation.
one speculative explanation for the connection between mo accumulation and fe-deficiency could be increased adsorption of molybdate to positively charged components of the yeast cell wall such as fe-oxides and fe-phosphate.
during fe-deficiency and growth on glucose yeast switch from respiration to fermentation, for review see  <cit> , causing enhanced acidification of the growth media which would promote increased adsorption of molybdate to fe-oxides on the cell wall.
another possibility is that in response to fe-deficiency femoo <dig> uptake is stimulated by an unidentified transporter, in a similar way to the proposed transport of mnhpo <dig> by the phosphate transporter pho <dig> reviewed in  <cit> .
over expression of the high affinity cu transporter ctr <dig> caused a significant and specific increase in cu in the yeast, suggesting that this transporter can accumulate when over expressed, even though it is known to be post-transcriptionally degraded in high cu concentrations  <cit> .
this is similar to the ca transporters pmc <dig> and the putative mg transporter alr <dig> which also cause specific increases in ca and mg  when over expressed .
however, this contrasts with fe, zn, mn, k and na for which we find that over expression of known transporters does not affect the accumulation of these elements.
this buffering is possibly explained by compensatory changes in post-transcriptional, translational or post-translational processes, or expression of other genes required for homeostasis of these elements.
we do observe an effect of over expression of genes encoding the high affinity and low affinity phosphate transporters pho <dig> and pho <dig> on the yeast ionome, causing a significant reduction in zn  and with a trend towards elevated p.
loss of function of the zn regulated transcription factor zap <dig> causes reductions in cd and co, elevated ca, and also shows a tendency for reduced zn which is just below the significance cut off.
zap <dig> is involved in activating expression of zrt <dig> and zrt <dig> genes that encode the zn transporters responsible for zn uptake across the plasma membrane.
such effects of the loss of function of zap <dig> suggest that under the conditions of our experiments one or more of these zn transporters plays an important role in transporting zn, cd and co. the connection between loss of expression of these zn transporters and increased ca is unknown.
however, both zn deficiency and loss of function of the zn transporter zip <dig> are known to cause elevated ca in mice embryos  <cit> .
further, loss of function of the zn transporter zrt <dig>  known to be involved in retrieval of zn from the vacuole, causes increased cd but no change in zn .
at the low zn concentration used in our experiments  and based on the previous data of macdiarmid et al.,  <cit>  we would not expect to see a difference in zn accumulation in zrt3Δ.
however, our observation that cd accumulates in zrt3Δ suggests that zrt <dig> may also transport cd out of the vacuole.
loss of function of zrt <dig> is also known to limit the ability of yeast to mobilize zn from the vacuole.
this is thought to cause a compensatory increase in the expression of the genes encoding the plasma membrane zn transporters zrt <dig> and zrt <dig>  <cit> .
increased activity of the zn transporters zrt <dig> and zrt <dig> in zrt3Δ may therefore also be responsible for the increased accumulation of cd we observe in zrt3Δ.
loss of function of zrt <dig> was also observed to cause an increase in the cd sensitivity of this strain compared to the control  when both were grown in liquid culture , validating the elevated cd observed in this strain.
accumulation of cd in strains with perturbed zn homeostasis suggests that cd might be a good ‘tracer’ for perturbation of zn homeostasis.
this may be due to the fact that cells can sense and respond to perturbations in zn homeostasis mechanisms in order to maintain cellular zn balance.
however, because cells do not specifically sense cd they are unable to respond to changes in cd accumulation directly.
loss of function of the genes that encode the mn influx transporters smf <dig> and smf <dig> both specifically cause low mn .
the role of smf <dig> in uptake of mn across the pm is debated since the smf1Δ null mutant showed only a small reduction in mn uptake  <cit> , reviewed in  <cit> .
however, our data suggests that both smf <dig> and smf <dig> play significant, and non-redundant, roles in mn uptake.
in contrast, loss of function of bsd <dig> involved in recycling smf <dig> and smf <dig> from the pm, for review see  <cit> , causes significant accumulation of mn and cd .
it is likely that loss of bsd <dig> causes accumulation of smf <dig> and smf <dig> at the pm driving the over accumulation of both cd and mn because these transporters transport both mn and cd.
interestingly, we also observe that loss of function of smf <dig> causes significant mn accumulation .
it has been proposed that smf <dig> functions as a transporter that retrieves fe from the yeast vacuole  <cit> .
we observe no impact of loss of function of smf <dig> on fe accumulation, though we do see a non-significant elevation of mo  consistent with a role in fe homeostasis.
however, we also see significant increases in mn and cd  in strains where smf <dig> has been deleted, suggesting smf <dig> is involved in retrieval of mn and cd from the vacuole .
it is currently unknown how mn is released from the vacuole  <cit> .
loss of function of pmr <dig>  which drives golgi/er sequestration and exocytosis of mn, causes mn over accumulation along with cd , most likely because mn and cd are now accumulating in the cytosol because they cannot be exported via exocytosis.
even though pmr <dig> is a ca2+atpase we see no changes in ca in pmr1Δ.
our data strongly supports the conclusion that both mn and cd are transported by smf <dig>  smf <dig>  smf <dig> and pmr <dig> confirming what has previously been shown for pmr <dig>  <cit> , and smf <dig>  <cit> .
the homozygous knockout of alr <dig> which encodes a plasma membrane mg transporter is lethal, establishing its absolute requirement for survival.
interestingly, in the heterozygous knockout  of alr <dig> we observe a reduction in mg accumulation, though it is just below the significance cutoff.
over expression of alr <dig> had no significant effect on mg and ni accumulation.
we observe the loss of function of cnb <dig>  encoding the regulatory subunit of calcineurin, to cause a specific elevation of ca .
the cnb <dig> protein is known to associate with calcineurin and is required for function  <cit> .
calmodulin with bound ca binds and activates the calcineurin complex which then negatively regulates the vacuole ca/h exchanger vcx <dig>  and positively regulates the vacuolar ca atpase pmc <dig> and er and golgi localized pmr <dig>  loss of function of cnb <dig> may therefore drive over accumulation of ca through the increased activity of vcx <dig>  though over expression of vcx <dig> has no effect on ca accumulation.
loss of function of either trk <dig> or trk <dig> encoding k uptake transporters has no effect on the accumulation of k. the serine/arginine-rich  protein kinase sky <dig> has been implicated in regulating k uptake via trk <dig> and  <dig>  <cit> .
interestingly, we observe a reduction in k in the sky1Δ mutant  consistent with sky <dig> playing a regulatory role in k uptake.
however, forment et al.,  <cit>  observed increased k uptake in k-starved sky1Δ cells.
the difference between these two experiments may be explained by the fact that yeast cells were k-starved in the forment and coworkers experiments whereas our experiment was performed under k replete conditions.
we also observed that the sky1Δ mutant has reduced na  and this fits with the enhanced na-tolerance and reduced uptake previously observed in this mutant  <cit> .
the snf1Δ null mutant grown with high glucose has been previously shown to have a deficiency in k uptake  <cit>  and we also see reduced k in this mutant .
under high glucose snf <dig> is dephosphorylated by reg1/glc <dig> and deactivated causing glucose-repression of many genes.
the low k observed in snf1Δ must therefore be due to a function of the non-phosphorylated form of snf <dig>  it is possibly caused by the fact that the non-phosphorylated form of snf <dig> activates trk <dig>  mediated k-uptake, thus the snf1Δ mutant has reduced trk <dig>  activity and reduced k-uptake  <cit> .
reg <dig> is known to be involved in regulating the phosphorylation of snf <dig>  in a reg1Δ mutant snf <dig> is hyperphosphorylated and we observe an increase in k in these cells, though the mechanism is unclear.
we observed that the over expression of pho <dig> encoding a cyclin-dependant kinase causes a reduction in zn, similar to that observed for the overexpression of pho <dig> and pho <dig> both encoding p transporters .
this is consistent with a role for pho <dig> in nutrient sensing  <cit> .
highlighted genes with novel function in regulation of the ionome
in table  <dig> we have selected a limited number of genes from groups b and c which show a significant and previously unknown effect on regulating accumulation of specific elements , or groups of elements we observe to be related  in the yeast ionome.
for a complete list of genes that significantly affect the yeast ionome see additional file 1: table s <dig> - s <dig>  such genes provide a source of potentially novel hypotheses regarding the way these mineral nutrients are regulated in yeast, and hopefully will lead to the development of follow up experiments to test these hypotheses.
go term enrichment in group b and group c genes
in group c of the ko dataset the most over represented biological process  go term was found to be cellular protein metabolic process  with the occurrence of vesicular trafficking and ion-transport ranking 2nd and 3rd.
this contrasts with group b of the ko dataset in which the bp terms protein localization, vesicle-mediated transport and cellular ion homeostasis predominate.
this difference suggests that disruption of protein metabolism or trafficking has the highest likelihood of overcoming the resilience of the ionomic homeostasis networks, leading to large changes in the ionome.
however, direct loss of function of ion-transport mechanisms can also have a significant impact on ionomic regulation as would be expected.
the role of vesicular trafficking and the vacuole in regulation of the ionome is also supported by the observation for group b of enrichment of the cellular component  terms golgi, endosome, vacuole and v-type atpase.
in both group c and b enrichment in the cc term mitochondrial matrix also suggests an important role for mitochondria in regulation of the ionome.
similar conclusions for the importance of the vacuole and the mitochondria in regulating the yeast ionome were also made by eide et al.,  <cit> .
enrichment in the cc terms ribonucleoprotein complex in group b and saga complex in group c also support important roles for ribosomal function and transcription, respectively.
similar trends are also observed in the kod dataset suggesting dosage of these essential genes in these processes e.g.
cellular protein metabolism and trafficking, is also important in regulating the ionome.
for a full description of all the go term enrichments for the complete ko, kod and oe data sets see additional file 3: figure s <dig> a-f.
gene clustering using ionomic profiles
in order to further uncover the functions of the genes and gene networks that are involved in controlling the yeast ionome we performed exhaustive significance clustering.
this approach allowed us to take those genes that have a significant impact on the yeast ionome in the ko, kod and oe sets and group them based on the directions of statistically significant changes in element abundance across all the elements .
for each strain and each element there can be a statistically significant increase, a statistically significant decrease, or no significant change in element abundance.
the maximum possible number of patterns is therefore  <dig> to the power of the number of elements.
we group the strains in clusters according to these patterns, and represent each cluster by its median profile of normalized element abundance.
<dig> out of  <dig> genes in the ko dataset were successfully grouped into  <dig> clusters with at least  <dig> strains.
in kod screen,  <dig> out of  <dig> strains were clustered into  <dig> groups.
in oe screen,  <dig> out of  <dig> strains were clustered into  <dig> groups.
the numbers of clusters are small as compared to the total number of possibilities, indicating that overall there is a limited number of relatively common ionomic phenotypes suggesting that the ionome only has a limited number of sets points that are consistent with cell viability.
to organize these clusters by similarity of their elemental profiles, and further identify functional patterns, their representative median elemental profiles were further subjected to hierarchical clustering for each of the ko, kod and oe gene sets to organize the clusters based on similarity .
for the ko gene data set the largest cluster cluster_ <dig> contains  <dig> genes.
loss of function of genes in this cluster specifically cause elevated cd.
cluster_ <dig> is highly enriched in genes with the bp go term establishment of localization  and cellular protein catabolic process .
our evidence supports the hypothesis that the zn transporters zrt1p, zrt2p and zrt3p play a role in cd transport in yeast, with the plasma membrane localized transporters zrt1p and zrt2p transporting cd into the cell and zrt3p possibly transporting cd out of the vacuole.
therefore, any process that either negatively affecting zrt3p function, or positively affects zrt1p and zrt2p, through modified trafficking or turnover would be expected to cause an increased accumulation of cd.
this high cd cluster_ <dig> contains multiple genes encoding proteins involved in the endosomal sorting complex required for transport  pathway which is involved in sorting ubiquitinated transmembrane proteins to the vacuole for degradation, via the formation of multivesicular bodies .
cluster_ <dig> also contains several genes involved in the formation of mvb.
to validate the high cd accumulation in strains carrying a loss of function mutation in genes encoding proteins part of the escrt or involved in the formation of mvb in cluster_ <dig> we tested for cd sensitivity in  <dig> strains with loss of function of genes  in these pathways, and that we had shown to have elevated cd abundance.
of the  <dig> strains tested  <dig> displayed increased sensitivity to cd compared to the control , and strains with loss of function of pep <dig> and ear <dig> showed no change from the control  .
other clusters showing similarity to cluster_ <dig> are cluster_ <dig> with high cd and mn, cluster_ <dig> with high cd and mo, cluster_ <dig> with high cd and ni and cluster_ <dig> with high cd and na .
cluster_ <dig> &  <dig> group together based on their median ionomic profiles  which are both low in p, mg and co but with cluster_ <dig> showing a significant reduction in co while cluster_ <dig> shows only a trend to lower co. together these two clusters contain multiple genes encoding the v-type atpase  and associated genes required for its function , along with genes encoding members of the vacuolar transport complex .
further, vma6Δ, 8Δ, 10Δ, 13Δ, 16Δ and 21Δ also all show significant reductions in co, mg and p but also have other changes such as elevated mo and na and reduced mn, though none of these six genes falls into a cluster.
in fact, all the genes known to be involved in encoding proteins for the v-type atpase are represented in the ko set of significant genes  reinforcing the critical function the v-type atpase plays in regulating the yeast ionome.
eide et al.,  <cit>  also identified half of these genes encoding v-type atpase subunits in their screen of the yeast ionome using a similar knockout collection.
however, most likely due to the initial n =  <dig> sampling 50% of these genes were not identified, suggesting a 50% false negative rate in this screen  <cit>  compared to the data reported here based on n =  <dig> replicates per strain.
this is also consistent with the lower number of genes reported by eide et al.,  <cit>  to affect the yeast ionome compared to this study .
furthermore, loss of function of the genes encoding the v-type atpase subunits that eide et al.,  <cit>  did identify caused reductions in co, p and mg as we report here.
screening of a similar set of yeast deletion strains for p accumulation  <cit> , and cs and sr accumulation  <cit>  also identified loss of function of genes encoding v-type atpase subunits, regulators and assembly factors as causing significant reductions in these elements, confirming the central role the vacuole plays in regulation of the yeast ionome.
cluster_ <dig> has low k and mn and the genes in this cluster are enriched in the cellular component  go term, ‘mitochondrion’ .
also, the related group cluster_ <dig>  showing low mn is also highly enriched in the cc go term ‘mitochondrion’ .
treatment with ethidium bromide is known to specifically destroy mitochondrial dna and block mitochondrial function  <cit> .
we observe that ethidium bromide treatment causes a significant  reduction in k  and mn   partially mimicking the ionomic phenotypes of the cluster_ <dig> and  <dig>  supporting the association of this ionomic phenotype with a disruption in mitochondrial function.
eide et al.,  <cit>  also reported that genes involved in mitochondrial function have a significant impact on the yeast ionome.
if go term enrichment is observed for the clusters for the ko, kod and oe datasets they can be explored in full in additional file 3: figure s2a-f.
ionomic interaction gene networks
to explore the interrelationships between the genes involved in regulating the ionome we constructed networks of genes based on their pair-wise physical and genetic interactions.
gene sets used to build these networks were either genes for which loss of function caused a significant change in a particular element, or genes from particular ionomic clusters.
the interaction network built from genes that cause elevated mn  identifies pmr <dig> as being at the centre of a network interacting with bsd <dig> and genes involved in protein import and sorting .
of the  <dig> genes in the two clusters in this network  <dig> of them interact genetically or through protein interactions.
of these  <dig> genes eight interact directly with pmr <dig>  three are one interaction away and one gene is two interactions away from pmr <dig>  the correlation of the ionomic profile for all genes directly interacting with pmr <dig> is >  <dig>  except for ydr503c , the highest is bsd <dig> at  <dig> .
the high mn clusters are therefore very likely driven primarily by perturbations of pmr <dig>  a protein known to drive golgi/er sequestration and exocytosis of mn.
this network therefore highlights the central role pmr <dig> plays in controlling cellular mn levels and identifies numerous genes that control the function of pmr <dig>  when all genes are included in the network that cause both increases or decreases in mn  genes encoding the mn transporters smf <dig> and smf <dig> appear in the network interacting with pmr <dig>  and also bring in smf <dig> via a genetic interaction with smf <dig>  in this network  <dig> genes interact directly with pmr <dig>  the eight genes observed in figure 8a and smf <dig> and smf <dig>  the correlation of the ionomic profile for all  <dig> genes that interact with pmr <dig> in this larger mn network is >  <dig>  except for smf <dig> and smf <dig> which are strongly negatively correlated .
this network also supports the placement of smf <dig> in the mn homeostasis network.
from this network a picture of mn homeostasis emerges.
smf <dig> and smf <dig> both play non-redundant roles in mn uptake by the cell.
pmr <dig> plays a central role in exporting mn from the cell via golgi/er sequestration and exocytosis, and smf <dig> is required for unloading of mn from the vacuole.
uptake and export of mn by smf1/smf <dig> and pmr <dig> is integrated by bsd <dig>  further, the mn export activity of pmr <dig> requires correct protein import and vesicular trafficking .
in this extended network we also now see evidence of genes involved in mitochondrial function  supporting the enrichment in genes with mitochondrial function in the low mn cluster_ <dig> and cluster_ <dig> clusters.
the network generated from the  <dig> genes that affect p in the ko dataset contains  <dig> genes that interact genetically or via protein interactions .
this network contains  <dig> genes that directly encode subunits of the v-type atpase or are involved indirectly in its functions .
it also clearly identifies a novel extended ionomic network of genes involved in p homeostasis.
this network includes genes involved in polyphosphate accumulation and vacuolar transport chaperone , protein trafficking and inositol-3-phosphate biosynthesis .
the networks generated for all genes that alter either p or mg have similar topographies  since  <dig> of the  <dig> genes in the p regulatory network also affect the mg network, suggesting a significant overlap in the regulatory networks for p and mg, and this supports the correlation of these two elements in cluster_ <dig> and  <dig> .
the interaction network of genes that affect mo accumulation  contains a set of  <dig> genes divided into two clear sub networks.
the sub network with vma <dig> appears to link vacuolar  with mitochondrial function  supporting cross-talk between these two important organelles.
further, this sub network also appears to link fe- and cu-homeostasis  with vacuolar and mitochondrial function.
the second sub network contains genes primarily involved in transcription.
mo is thought to have no biochemical function in s. cerevisiae <cit> , and we hypothesize that loss of function of genes that affect mo accumulation in yeast may be acting indirectly through modification of the ph of the media by affecting the respiratory quotient .
increased fermentation leads to increased media acidification  <cit> , and this can be caused by loss of mitochondrial viability.
within the mo interaction network we observe mgm <dig> , and fmc <dig> , supporting this hypothesis.
in fact, the mgm <dig> null mutant is known to display the petite phenotype  <cit>  due to loss of mitochondrial dna.
loss of mitochondrial dna can also be caused by ethidium bromide treatment which phenocopies the petite phenotype of mgm <dig>  and importantly were observe  that treatment with  <dig> mg/l ethidium bromide also causes a significant  increase in mo from  <dig>  mg/l/od600nm under control conditions to  <dig>  mg/l/od600nm .
this further reinforces the possible connection between mitochondrial function and mo accumulation.
fe-deficiency is also known to reduced those biochemical processes that require fe, for review see  <cit> , including respiration.
the occurrence of key genes involved in fe-homeostasis  in the mo network supports this.
further, gsh <dig> also occurs in the mo network and this might be explained by the fact that a loss of gsh biosynthesis will impair the biogenesis of fe-s cluster containing proteins required for mitochondrial function, for review see  <cit> , leading to impairment of respiration.
the mo interaction network also contains key genes required for the correct assembly and function of v-type atpase .
it is possible that disruption of these genes interferes with vacuole – mitochondria cross-talk  <cit>  leading to impaired mitochondrial function.
loss of function strains of these four genes show reduced mg/p/co but also high mo, unlike other v-type atpase genes in the cluster_ <dig> &  <dig>  in fact, the high mo and reduced k and mn of these mutants show similarities to the genes found in the mitochondria cluster_ <dig>  further supporting a connection between the vacuole and the mitochondria.
inclusion within these interacting gene networks provides further validation that those genes identified to have a significant effect on the yeast ionome are part of true functional units.
network analysis of all significant genes for each of the  <dig> elements quantified in the ko dataset  revealed networks with at least  <dig> nodes for all elements, except fe and zn.
within these networks two groups were suggested based on differences in the number of nodes in the network as a percentage of the significant genes tested for network connectivity  .
in the first group composed of networks for mn, k, na, mg, p, mo, co, ca and cd the network inclusion rate ranged from  <dig> – 54%, providing support for a functional role in regulation of the ionome in yeast for these genes.
in the second group composed of cu, s and ni, the network inclusion rate fell to  <dig> – 18% suggesting that the genes identified to have a significant effect on these elements may be less likely to be a part of functional systems.
the complete lack of network support for genes identified to significant affects on fe and zn suggests that these may not be part of systems that regulate these elements in yeast.
evaluation of the connectivity within each network using edges/node reveals large differences between the networks .
co, cd, p and mg have the highest network connectivity and this can be explained by the fact that they contain single large networks of interconnected genes.
the cd network is highly enriched in genes from cluster_ <dig> involved in protein localization including genes in the escrt pathway involving sorting of ubiquitinated transmembrane proteins to the vacuole for degradation.
the p, mg and co networks contain multiple genes from cluster_ <dig> and  <dig> which are highly enriched in genes involved in vacuolar function, including the activity of the v-type atpase.
the mn and mo networks have intermediate levels of network connectivity perhaps because these networks appear to have  <dig> independent sub networks .
for mo one sub network contains genes involved in transcription and the other is an interconnected set of genes with functions in the mitochondria, vacuole and fe homeostasis.
for mn one sub network contain genes involved in mitochondrial function, and the other genes involved in trafficking and activity of mn transporters.
these results further validate the methodologies developed to screen the ionome of yeast in high throughput using  <dig> well plates as well as the statistical methods developed to deal with the highly sensitive data.
overall, this approach appears to approximately double the ability to detect ionomic differences compared to previous studies providing a much high resolution of the genes and gene networks involved in regulating the yeast ionome.
the results presented here are however likely a small subsample of the genes affecting the ionome of a single celled eukaryote.
the lack of several known ionome altering genes in our datasets suggests that rescreening of these populations in different environments would yield another set of known and novel genes.
such full genome screens could be accomplished in approximately  <dig> months per condition and could greatly increase our understanding of the gene by environment interactions controlling elemental accumulation.
hypothesis testing using the online yeast ionomics database
a yeast ionomics database has been developed and is accessible through the ionomicshub  .
from the homepage follow the link to the yeast database.
the database contains ionomic data on the  <dig> yeast strains in the ko set,  <dig> in the kod set and  <dig> in the oe set.
the data consists of the raw solution concentration data for each element measured in each strain, and the same data normalized to the optical density  of the yeast culture just prior to preparation for icp-ms analysis.
further, the database also contains the ionomic data from the ko, kod and oe sets normalized separately with common strains analyzed in each 96-well plate using a mixed model approach, as described previously by yu et al.,  <cit> .
this normalization allows removal of plate effects and facilitates comparisons of different stains across the complete ko, kod and oe datasets.
this database can be used to rapidly retrieve, display and download ionomics data  to test if the loss or gain of function of any gene of interest in the full yeast genome has an effect on the yeast ionome.
ionomic data for any of the viable yeast strains in the ko, kod and oe collections can be retrieved from the database using the basic search feature by simply typing in the name of the mutant or gene of interest.
multiple genes can also be searched simultaneously by separating the name of each mutant/gene using a comma.
the basic search returns the 96-well plate  in which the mutant of interest was analyzed.
an individual strain, multiple strains or the complete 96-well plate can be selected using the check boxes  and data for solution concentrations  or od normalized  normalized data) downloaded as a comma-separated values  file.
the advance search also allows retrieval of data based on a specific 96-well plate or icp-ms run.
a search on a mutant/gene also returns links to other normalized datasets that contain data on the mutant/gene being search e.g.
full genome knockout haploid .
following the link for a particular dataset presents tools for viewing, plotting and downloading the normalized data on the mutant/gene of interest from that particular dataset.
a description of the data set and each type of data is presented.
for example, in the full genome knockout haploid dataset, which has been normalized following yu et al.,  <cit> , data can be viewed for percentage change of normalized values compared to the population mean, change in concentration from the population mean divided by the deviation , and the optical density adjusted concentration data after normalization across population.
the line of interest can be selected using the check boxes and data plotted or downloaded .
plots available are histogram , box plots , and z-score  depending on the type of data.
in figure  <dig> b-d data is displayed in various ways illustrating the fact that loss of function of smf <dig>  causes reduced mn accumulation whereas loss of function of smf <dig>  and pmr <dig>  causes elevated mn.
finally, complete normalized datasets for all ~ <dig>  strains tested can be accessed via the browse datasets tab and downloaded as zipped csv files.
CONCLUSIONS
here, we report a genome-wide scan of approximately  <dig> genes in yeast using icp-ms to quantify  <dig> to  <dig> different elements  in both loss of function and gain of function mutant yeast strains.
of the  <dig> knockout strains analyzed  <dig> showed a significant ionomic phenotype.
disruption of protein metabolism or trafficking has the highest likelihood of overcoming the resilience of the ionomic homeostasis networks, leading to the largest changes in the ionome.
of the genes significantly impacting the ionome  <dig> genes were lethal when knocked, but showed an ionomic phenotype when present as a single copy in diploid strains, suggesting that gene dosage can be important in ionomic regulation.
of the  <dig> yeast orfs over expressed  <dig> impacted the ionome, and as might be expected over expression tends to produce more extreme ionomic phenotypes than loss of function.
interestingly, no significant overlap between the gene sets identified from the loss and gain of function experiments was found, suggesting that on a genome-wide scale loss of function and over expression do not produce related phenotypes.
analysis of our dataset revealed numerous novel genes which significantly impact the ionome when knocked out or over expressed, and these genes could form the basis of many follow up experiments.
clustering based on the ionomic phenotype of over expression or knockout strains identified a limited number of clusters  with three or more members, and analysis of gene functions enriched within these clusters revealed that perturbation of particular cellular functions creates unique ionomic phenotypes, such as the mitochondria, vacuolar and escrt pathway, providing a robust way to predict the potential function of genes.
analysis of the protein-protein and genetic interaction of genes identified to impact the yeast ionome also revealed novel functional gene networks that illustrate the physical and genetic interactions between genes within a particular mineral nutrient regulatory network.
the high network inclusion rate  for genes impacting most elements strongly suggests that these genes are truly part of functional systems involved in ionomic regulation.
such networks help identify important hub genes that play a critical role in network function, such as pmr <dig> in mn homeostasis; novel members of mineral nutrient homeostasis networks, such as the identification of smf <dig> as a major pathway for mn uptake non-redundant with smf <dig>  and smf <dig> as the unknown gene involved in mn retrieval from the vacuole; and cross-talk between cellular functions such as the mitochondria and the vacuole.
a better understanding of such regulatory networks is also critical if we are to be able to functionally model ionomic regulation within yeast and other organisms.
to facilitate such understanding we have developed a publically accessible database  through which all the yeast ionomic data described here can be searched, downloaded and analyzed for hypothesis testing and experimental follow up.

 in addition to the assimilation of carbon and oxygen a vital function of all living cells is to control the accumulation from the environment of various chemical elements required for numerous essential biochemical processes, including incorporation into macromolecules, as cofactors in enzymes, in cellular buffering, and as second messengers in signaling processes. though essential for life, many of these elements are also potentially toxic. to balance the demand of these essential elements for normal growth and reproduction with their potential toxicity living cells have evolved complex regulatory mechanisms to control their uptake and accumulation. identification of the genes and gene networks that control these regulatory processes is a critical first step to a complete understanding of the molecular mechanisms involved. such an understanding will have many potential benefits, including in our understanding of human disease, and in the development of more nutritious food crops with increased concentrations of essential micronutrients, lower concentrations of potentially toxic trace elements, and that are produced using cropping systems that require less mineral nutrient inputs. the yeast saccharomyces cerevisiae has proved to be a powerful model for the study of mineral nutrient and trace element homeostasis, for recent reviews see. the availability of full genome deletion and open reading frame overexpression collections have further enhanced the power of yeast as a model system, and these genome-wide tools have already been applied to the study of mineral nutrient and trace element homeostasis, indirectly by studying the growth effects of elevated transition metals, b, selenite, and fe and zn deficiency. studies have also been undertaken in which accumulation of fe, cs, sr, and p have been directly quantified in yeast cells. in order to investigate the interactions between the mineral nutrient and trace element content of yeast an investigation of the simultaneous accumulation of multi-elements has also been performed. here, we build on these previous studies and extend them by directly measuring, by inductively coupled plasma-mass spectrometry, the simultaneous accumulation of as, ca, cd, cl, co, cu, fe, k, mg, mn, mo, na, ni, p, s, se, and zn in the yeast strains in the haploid deletion collection, the essential genes in the diploid heterozygous knockout collection, and the genes in the open reading frame over expression collection. results of this study provide new data for the functional characterization of yeast genes of unknown function, provide new functional insight into genes with known functions, and provide a deeper understanding of the cellular systems and gene networks that are involved in controlling the yeast ionome. a publically accessible database at http://www.ionomicshub.org has also been developed to facilitate broad utilization of this large data resource.  genome-wide scan of genes impacting the yeast ionome we quantified the concentration of ca, cd, co, cu, fe, k, mg, mn, mo, na, ni, p, s and zn in the viable mutant strains of yeast in which the open reading frames in haploid cells have been disrupted one at a time, and in the viable mutant strains where a single copy of the orfs in diploid cells have been disrupted to produce a heterozygous knockout. further, we also quantified the concentrations of ca, cd, co, cu, fe, k, mg, mn, mo, na, ni, p, s and zn in the viable strains of yeast where each orf in the genome has been ectopically overexpressed one at a time. improvements in our analytical methodologies also allowed use to additionally quantify as, se and cl in the oe collection. the data was collected as described by danku et al., and each data set separately normalized and summarized over or biological replicates. the data was analyzed statistically using linear mixed-effect models to determine strains and elements that significantly change in abundance as compared to the median trend after manually filtering for quality control and controlling the false discovery rate. of the genes tested in the haploid knockout collection the loss of function of of these genes had a significant effect on the concentration of at least one element in the yeast ionome. the loss of function of genes, out of the tested in the diploid heterozygous knockout collection, were also found to significantly affect the concentration of at least one element in the yeast ionome. together, this establishes that 10% of the orfs in the complete genome of yeast are involved directly or indirectly in controlling the ionome. the ectopic over expression of orfs out of the tested were also found to significantly affect the concentration of at least one element in the yeast ionome, establishing that ectopic over expression of 8% of the total orfs in yeast affect the yeast ionome. of the genes we observed to significantly affect the yeast ionome from the ko, kod and oe sets, we observe that occur in both the knockout and oe sets. using the hypergeometric test we establish that this overlap is not significant. this supports the conclusion that on a genome-wide scale for control of the ionome in yeast loss and gain of gene function produce different, non-overlapping affects. group a - practical significance cutoff at − to 20%, group b - practical cut off at to 100% & - to −50%, group c - practical cut off at 100% and −50%. groups represented in volcano plots. to help identify those genes which have a practical impact on the yeast ionome we divided the lists of genes that have a statistically significant effect on the ionome, for each set, into three groups based on the magnitude of the percent changes from the mean of the normalized element abundance across all mutants. group c contains genes that cause a ≥ 100% increase or ≤ −50% decrease in any of the elements we quantified, group b contains genes that cause to 100% & - to −50% change, and group a −20% to 20% change. the percentage change was calculated as the difference between the normalized element abundance of a mutant and the normalized mean element abundance across all mutants, divided by the normalized mean element abundance across all mutants. to illustrate the distribution of genes in each of the groups a, b and c for each of the gene sets we have plotted the magnitudes and statistical significance of the impact of each gene on all the measured elements in the ionome. both the loss of function and gain of function gene sets have a similar range of statistical significance but the effect size for the knockout and oe sets differ, with the oe set producing a larger range of effect sizes skewed towards larger positive effects. arsenic, cl and se were included in the analysis of the oe set but not the ko and kod set. however, of the data elements in the oe set with an effect size >  only two were for se and one for cl. from this we determine that the increase in the effect size of the outliers in the oe data set is not an artifact due to the addition of as, cl and se to the oe data set. validation of the identified gene sets against existing knowledge to help validate the loss of function set of genes we observed to have a significant effect on the yeast ionome we compared our set to that generated by eide et al.,. in the screen of a whole-genome homozygous diploid knockout collection, at a first pass through the collection at n = replicate samples per yeast strain, eide and coworkers identified genes that reproducibly affected the yeast ionome. of these genes we observe to significantly affect the ionome in our ko dataset. using the hypergeometric test we determined that this overlap is highly significant and would not be expected to occur if the genes were selected at random. of the overlapping genes fall into our middle effect group b set of genes, with only genes in our small effect group a set of genes, and in our large effect group c set of genes. such a significant overlap in the knockout gene set reported by eide et al., to affect the ionome and the knockout gene set we report here strongly validates our approach and gives us confidence that the more extensive high-resolution genome wide scan of the ionome reported here will reveal novel and significant insight into the regulation of the yeast ionome. importantly, of the large effect genes in our ko group c are altered in mo, an element not measured by eide and co-workers, explaining why these large effect genes were not identified by eide et al.,. to further validate our sets of significant genes that affect the ionome in yeast we investigated if genes known to be involved in regulation of various elements in the ionome from the current literature also occurred in our gene sets. based on the literature we generated a list of genes known to be involved in the homeostasis of the essential mineral nutrients fe, cu, zn, mn, mg, ca, k and na in yeast. of this list of genes known to be involved in mineral nutrient homeostasis in yeast we identified loss of function of to have a significant impact on the yeast ionome. a further were found to have a significant effect on the ionome when overexpressed. there are multiple explanations why we only identified about 1/3rd of the genes known to be involved in mineral nutrient homeostasis in yeast. particularly significant is the fact that many of the genes known to be involved in mineral nutrient homeostasis are primarily involved during growth under nutrient deficiency and not the sufficiency conditions we performed our experiments under. further, even though a gene is known to be involved in mineral nutrient homeostasis its loss of function may be compensated for by other genes and thus might not in itself be manifest as a change in the ionome as measured in our experiment. note 1: ygl168w that overlaps pmr also has significant increase in cd, and ygl167c is also elevated in cd but just below the significance cut off. interestingly, we observed a high level of mo accumulation in strains with loss of function alleles of several known fe accumulation genes even though no changes in fe accumulation are observed. ftr and fet encode the high affinity fe transporter and ferric chelate reductase that work together for high-affinity fe uptake. ctr encodes the high affinity cu transporter and is responsible for cu uptake, which is required for the function of ftr therefore, without a functional ctr gene yeast have impaired high-affinity fe uptake. given the critical role these genes play in fe homeostasis we might have expected to see a change in fe accumulation in loss of function mutants of these genes. however, uptake of fe by the low affinity fet transporter may have compensated. the connection of fe homeostasis and mo accumulation was surprising since yeast do not require mo unlike plants in which a connection between fe and mo has been observed. in the wild-type by with low fe or cu in the growth media we also observe an increase in mo accumulation, supporting the link between reduced cu uptake, diminished high-affinity fe uptake and increased mo accumulation. also, ectopic over expression of cup causes a specific accumulation of cu and mo. in this situation we might expect that the elevated cu is bound to cup causing fe deficiency via inactivation of ftr1-fet high affinity uptake system. the mo accumulation in this strain also supports the link between fe-deficiency and mo accumulation. one speculative explanation for the connection between mo accumulation and fe-deficiency could be increased adsorption of molybdate to positively charged components of the yeast cell wall such as fe-oxides and fe-phosphate. during fe-deficiency and growth on glucose yeast switch from respiration to fermentation, for review see, causing enhanced acidification of the growth media which would promote increased adsorption of molybdate to fe-oxides on the cell wall. another possibility is that in response to fe-deficiency femoo uptake is stimulated by an unidentified transporter, in a similar way to the proposed transport of mnhpo by the phosphate transporter pho reviewed in. over expression of the high affinity cu transporter ctr caused a significant and specific increase in cu in the yeast, suggesting that this transporter can accumulate when over expressed, even though it is known to be post-transcriptionally degraded in high cu concentrations. this is similar to the ca transporters pmc and the putative mg transporter alr which also cause specific increases in ca and mg when over expressed. however, this contrasts with fe, zn, mn, k and na for which we find that over expression of known transporters does not affect the accumulation of these elements. this buffering is possibly explained by compensatory changes in post-transcriptional, translational or post-translational processes, or expression of other genes required for homeostasis of these elements. we do observe an effect of over expression of genes encoding the high affinity and low affinity phosphate transporters pho and pho on the yeast ionome, causing a significant reduction in zn and with a trend towards elevated p. loss of function of the zn regulated transcription factor zap causes reductions in cd and co, elevated ca, and also shows a tendency for reduced zn which is just below the significance cut off. zap is involved in activating expression of zrt and zrt genes that encode the zn transporters responsible for zn uptake across the plasma membrane. such effects of the loss of function of zap suggest that under the conditions of our experiments one or more of these zn transporters plays an important role in transporting zn, cd and co. the connection between loss of expression of these zn transporters and increased ca is unknown. however, both zn deficiency and loss of function of the zn transporter zip are known to cause elevated ca in mice embryos. further, loss of function of the zn transporter zrt known to be involved in retrieval of zn from the vacuole, causes increased cd but no change in zn. at the low zn concentration used in our experiments and based on the previous data of macdiarmid et al., we would not expect to see a difference in zn accumulation in zrt3Δ. however, our observation that cd accumulates in zrt3Δ suggests that zrt may also transport cd out of the vacuole. loss of function of zrt is also known to limit the ability of yeast to mobilize zn from the vacuole. this is thought to cause a compensatory increase in the expression of the genes encoding the plasma membrane zn transporters zrt and zrt. increased activity of the zn transporters zrt and zrt in zrt3Δ may therefore also be responsible for the increased accumulation of cd we observe in zrt3Δ. loss of function of zrt was also observed to cause an increase in the cd sensitivity of this strain compared to the control when both were grown in liquid culture, validating the elevated cd observed in this strain. accumulation of cd in strains with perturbed zn homeostasis suggests that cd might be a good ‘tracer’ for perturbation of zn homeostasis. this may be due to the fact that cells can sense and respond to perturbations in zn homeostasis mechanisms in order to maintain cellular zn balance. however, because cells do not specifically sense cd they are unable to respond to changes in cd accumulation directly. loss of function of the genes that encode the mn influx transporters smf and smf both specifically cause low mn. the role of smf in uptake of mn across the pm is debated since the smf1Δ null mutant showed only a small reduction in mn uptake, reviewed in. however, our data suggests that both smf and smf play significant, and non-redundant, roles in mn uptake. in contrast, loss of function of bsd involved in recycling smf and smf from the pm, for review see, causes significant accumulation of mn and cd. it is likely that loss of bsd causes accumulation of smf and smf at the pm driving the over accumulation of both cd and mn because these transporters transport both mn and cd. interestingly, we also observe that loss of function of smf causes significant mn accumulation. it has been proposed that smf functions as a transporter that retrieves fe from the yeast vacuole. we observe no impact of loss of function of smf on fe accumulation, though we do see a non-significant elevation of mo consistent with a role in fe homeostasis. however, we also see significant increases in mn and cd in strains where smf has been deleted, suggesting smf is involved in retrieval of mn and cd from the vacuole. it is currently unknown how mn is released from the vacuole. loss of function of pmr which drives golgi/er sequestration and exocytosis of mn, causes mn over accumulation along with cd, most likely because mn and cd are now accumulating in the cytosol because they cannot be exported via exocytosis. even though pmr is a ca2+atpase we see no changes in ca in pmr1Δ. our data strongly supports the conclusion that both mn and cd are transported by smf smf smf and pmr confirming what has previously been shown for pmr, and smf. the homozygous knockout of alr which encodes a plasma membrane mg transporter is lethal, establishing its absolute requirement for survival. interestingly, in the heterozygous knockout of alr we observe a reduction in mg accumulation, though it is just below the significance cutoff. over expression of alr had no significant effect on mg and ni accumulation. we observe the loss of function of cnb encoding the regulatory subunit of calcineurin, to cause a specific elevation of ca. the cnb protein is known to associate with calcineurin and is required for function. calmodulin with bound ca binds and activates the calcineurin complex which then negatively regulates the vacuole ca/h exchanger vcx and positively regulates the vacuolar ca atpase pmc and er and golgi localized pmr loss of function of cnb may therefore drive over accumulation of ca through the increased activity of vcx though over expression of vcx has no effect on ca accumulation. loss of function of either trk or trk encoding k uptake transporters has no effect on the accumulation of k. the serine/arginine-rich protein kinase sky has been implicated in regulating k uptake via trk and. interestingly, we observe a reduction in k in the sky1Δ mutant consistent with sky playing a regulatory role in k uptake. however, forment et al., observed increased k uptake in k-starved sky1Δ cells. the difference between these two experiments may be explained by the fact that yeast cells were k-starved in the forment and coworkers experiments whereas our experiment was performed under k replete conditions. we also observed that the sky1Δ mutant has reduced na and this fits with the enhanced na-tolerance and reduced uptake previously observed in this mutant. the snf1Δ null mutant grown with high glucose has been previously shown to have a deficiency in k uptake and we also see reduced k in this mutant. under high glucose snf is dephosphorylated by reg1/glc and deactivated causing glucose-repression of many genes. the low k observed in snf1Δ must therefore be due to a function of the non-phosphorylated form of snf it is possibly caused by the fact that the non-phosphorylated form of snf activates trk mediated k-uptake, thus the snf1Δ mutant has reduced trk activity and reduced k-uptake. reg is known to be involved in regulating the phosphorylation of snf in a reg1Δ mutant snf is hyperphosphorylated and we observe an increase in k in these cells, though the mechanism is unclear. we observed that the over expression of pho encoding a cyclin-dependant kinase causes a reduction in zn, similar to that observed for the overexpression of pho and pho both encoding p transporters. this is consistent with a role for pho in nutrient sensing. highlighted genes with novel function in regulation of the ionome in table  we have selected a limited number of genes from groups b and c which show a significant and previously unknown effect on regulating accumulation of specific elements, or groups of elements we observe to be related in the yeast ionome. for a complete list of genes that significantly affect the yeast ionome see additional file 1: table s - s such genes provide a source of potentially novel hypotheses regarding the way these mineral nutrients are regulated in yeast, and hopefully will lead to the development of follow up experiments to test these hypotheses. go term enrichment in group b and group c genes in group c of the ko dataset the most over represented biological process go term was found to be cellular protein metabolic process with the occurrence of vesicular trafficking and ion-transport ranking 2nd and 3rd. this contrasts with group b of the ko dataset in which the bp terms protein localization, vesicle-mediated transport and cellular ion homeostasis predominate. this difference suggests that disruption of protein metabolism or trafficking has the highest likelihood of overcoming the resilience of the ionomic homeostasis networks, leading to large changes in the ionome. however, direct loss of function of ion-transport mechanisms can also have a significant impact on ionomic regulation as would be expected. the role of vesicular trafficking and the vacuole in regulation of the ionome is also supported by the observation for group b of enrichment of the cellular component terms golgi, endosome, vacuole and v-type atpase. in both group c and b enrichment in the cc term mitochondrial matrix also suggests an important role for mitochondria in regulation of the ionome. similar conclusions for the importance of the vacuole and the mitochondria in regulating the yeast ionome were also made by eide et al.,. enrichment in the cc terms ribonucleoprotein complex in group b and saga complex in group c also support important roles for ribosomal function and transcription, respectively. similar trends are also observed in the kod dataset suggesting dosage of these essential genes in these processes e.g. cellular protein metabolism and trafficking, is also important in regulating the ionome. for a full description of all the go term enrichments for the complete ko, kod and oe data sets see additional file 3: figure s a-f. gene clustering using ionomic profiles in order to further uncover the functions of the genes and gene networks that are involved in controlling the yeast ionome we performed exhaustive significance clustering. this approach allowed us to take those genes that have a significant impact on the yeast ionome in the ko, kod and oe sets and group them based on the directions of statistically significant changes in element abundance across all the elements. for each strain and each element there can be a statistically significant increase, a statistically significant decrease, or no significant change in element abundance. the maximum possible number of patterns is therefore to the power of the number of elements. we group the strains in clusters according to these patterns, and represent each cluster by its median profile of normalized element abundance. out of genes in the ko dataset were successfully grouped into clusters with at least strains. in kod screen, out of strains were clustered into groups. in oe screen, out of strains were clustered into groups. the numbers of clusters are small as compared to the total number of possibilities, indicating that overall there is a limited number of relatively common ionomic phenotypes suggesting that the ionome only has a limited number of sets points that are consistent with cell viability. to organize these clusters by similarity of their elemental profiles, and further identify functional patterns, their representative median elemental profiles were further subjected to hierarchical clustering for each of the ko, kod and oe gene sets to organize the clusters based on similarity. for the ko gene data set the largest cluster cluster_ contains genes. loss of function of genes in this cluster specifically cause elevated cd. cluster_ is highly enriched in genes with the bp go term establishment of localization and cellular protein catabolic process. our evidence supports the hypothesis that the zn transporters zrt1p, zrt2p and zrt3p play a role in cd transport in yeast, with the plasma membrane localized transporters zrt1p and zrt2p transporting cd into the cell and zrt3p possibly transporting cd out of the vacuole. therefore, any process that either negatively affecting zrt3p function, or positively affects zrt1p and zrt2p, through modified trafficking or turnover would be expected to cause an increased accumulation of cd. this high cd cluster_ contains multiple genes encoding proteins involved in the endosomal sorting complex required for transport pathway which is involved in sorting ubiquitinated transmembrane proteins to the vacuole for degradation, via the formation of multivesicular bodies. cluster_ also contains several genes involved in the formation of mvb. to validate the high cd accumulation in strains carrying a loss of function mutation in genes encoding proteins part of the escrt or involved in the formation of mvb in cluster_ we tested for cd sensitivity in strains with loss of function of genes in these pathways, and that we had shown to have elevated cd abundance. of the strains tested displayed increased sensitivity to cd compared to the control, and strains with loss of function of pep and ear showed no change from the control. other clusters showing similarity to cluster_ are cluster_ with high cd and mn, cluster_ with high cd and mo, cluster_ with high cd and ni and cluster_ with high cd and na. cluster_ & group together based on their median ionomic profiles which are both low in p, mg and co but with cluster_ showing a significant reduction in co while cluster_ shows only a trend to lower co. together these two clusters contain multiple genes encoding the v-type atpase and associated genes required for its function, along with genes encoding members of the vacuolar transport complex. further, vma6Δ, 8Δ, 10Δ, 13Δ, 16Δ and 21Δ also all show significant reductions in co, mg and p but also have other changes such as elevated mo and na and reduced mn, though none of these six genes falls into a cluster. in fact, all the genes known to be involved in encoding proteins for the v-type atpase are represented in the ko set of significant genes reinforcing the critical function the v-type atpase plays in regulating the yeast ionome. eide et al., also identified half of these genes encoding v-type atpase subunits in their screen of the yeast ionome using a similar knockout collection. however, most likely due to the initial n = sampling 50% of these genes were not identified, suggesting a 50% false negative rate in this screen compared to the data reported here based on n = replicates per strain. this is also consistent with the lower number of genes reported by eide et al., to affect the yeast ionome compared to this study. furthermore, loss of function of the genes encoding the v-type atpase subunits that eide et al., did identify caused reductions in co, p and mg as we report here. screening of a similar set of yeast deletion strains for p accumulation, and cs and sr accumulation also identified loss of function of genes encoding v-type atpase subunits, regulators and assembly factors as causing significant reductions in these elements, confirming the central role the vacuole plays in regulation of the yeast ionome. cluster_ has low k and mn and the genes in this cluster are enriched in the cellular component go term, ‘mitochondrion’. also, the related group cluster_ showing low mn is also highly enriched in the cc go term ‘mitochondrion’. treatment with ethidium bromide is known to specifically destroy mitochondrial dna and block mitochondrial function. we observe that ethidium bromide treatment causes a significant reduction in k and mn partially mimicking the ionomic phenotypes of the cluster_ and supporting the association of this ionomic phenotype with a disruption in mitochondrial function. eide et al., also reported that genes involved in mitochondrial function have a significant impact on the yeast ionome. if go term enrichment is observed for the clusters for the ko, kod and oe datasets they can be explored in full in additional file 3: figure s2a-f. ionomic interaction gene networks to explore the interrelationships between the genes involved in regulating the ionome we constructed networks of genes based on their pair-wise physical and genetic interactions. gene sets used to build these networks were either genes for which loss of function caused a significant change in a particular element, or genes from particular ionomic clusters. the interaction network built from genes that cause elevated mn identifies pmr as being at the centre of a network interacting with bsd and genes involved in protein import and sorting. of the genes in the two clusters in this network of them interact genetically or through protein interactions. of these genes eight interact directly with pmr three are one interaction away and one gene is two interactions away from pmr the correlation of the ionomic profile for all genes directly interacting with pmr is >  except for ydr503c, the highest is bsd at. the high mn clusters are therefore very likely driven primarily by perturbations of pmr a protein known to drive golgi/er sequestration and exocytosis of mn. this network therefore highlights the central role pmr plays in controlling cellular mn levels and identifies numerous genes that control the function of pmr when all genes are included in the network that cause both increases or decreases in mn genes encoding the mn transporters smf and smf appear in the network interacting with pmr and also bring in smf via a genetic interaction with smf in this network genes interact directly with pmr the eight genes observed in figure 8a and smf and smf the correlation of the ionomic profile for all genes that interact with pmr in this larger mn network is > except for smf and smf which are strongly negatively correlated. this network also supports the placement of smf in the mn homeostasis network. from this network a picture of mn homeostasis emerges. smf and smf both play non-redundant roles in mn uptake by the cell. pmr plays a central role in exporting mn from the cell via golgi/er sequestration and exocytosis, and smf is required for unloading of mn from the vacuole. uptake and export of mn by smf1/smf and pmr is integrated by bsd further, the mn export activity of pmr requires correct protein import and vesicular trafficking. in this extended network we also now see evidence of genes involved in mitochondrial function supporting the enrichment in genes with mitochondrial function in the low mn cluster_ and cluster_ clusters. the network generated from the genes that affect p in the ko dataset contains genes that interact genetically or via protein interactions. this network contains genes that directly encode subunits of the v-type atpase or are involved indirectly in its functions. it also clearly identifies a novel extended ionomic network of genes involved in p homeostasis. this network includes genes involved in polyphosphate accumulation and vacuolar transport chaperone, protein trafficking and inositol-3-phosphate biosynthesis. the networks generated for all genes that alter either p or mg have similar topographies since of the genes in the p regulatory network also affect the mg network, suggesting a significant overlap in the regulatory networks for p and mg, and this supports the correlation of these two elements in cluster_ and. the interaction network of genes that affect mo accumulation contains a set of genes divided into two clear sub networks. the sub network with vma appears to link vacuolar with mitochondrial function supporting cross-talk between these two important organelles. further, this sub network also appears to link fe- and cu-homeostasis with vacuolar and mitochondrial function. the second sub network contains genes primarily involved in transcription. mo is thought to have no biochemical function in s. cerevisiae, and we hypothesize that loss of function of genes that affect mo accumulation in yeast may be acting indirectly through modification of the ph of the media by affecting the respiratory quotient. increased fermentation leads to increased media acidification, and this can be caused by loss of mitochondrial viability. within the mo interaction network we observe mgm, and fmc, supporting this hypothesis. in fact, the mgm null mutant is known to display the petite phenotype due to loss of mitochondrial dna. loss of mitochondrial dna can also be caused by ethidium bromide treatment which phenocopies the petite phenotype of mgm and importantly were observe that treatment with mg/l ethidium bromide also causes a significant increase in mo from mg/l/od600nm under control conditions to mg/l/od600nm. this further reinforces the possible connection between mitochondrial function and mo accumulation. fe-deficiency is also known to reduced those biochemical processes that require fe, for review see, including respiration. the occurrence of key genes involved in fe-homeostasis in the mo network supports this. further, gsh also occurs in the mo network and this might be explained by the fact that a loss of gsh biosynthesis will impair the biogenesis of fe-s cluster containing proteins required for mitochondrial function, for review see, leading to impairment of respiration. the mo interaction network also contains key genes required for the correct assembly and function of v-type atpase. it is possible that disruption of these genes interferes with vacuole – mitochondria cross-talk leading to impaired mitochondrial function. loss of function strains of these four genes show reduced mg/p/co but also high mo, unlike other v-type atpase genes in the cluster_ & in fact, the high mo and reduced k and mn of these mutants show similarities to the genes found in the mitochondria cluster_ further supporting a connection between the vacuole and the mitochondria. inclusion within these interacting gene networks provides further validation that those genes identified to have a significant effect on the yeast ionome are part of true functional units. network analysis of all significant genes for each of the elements quantified in the ko dataset revealed networks with at least nodes for all elements, except fe and zn. within these networks two groups were suggested based on differences in the number of nodes in the network as a percentage of the significant genes tested for network connectivity. in the first group composed of networks for mn, k, na, mg, p, mo, co, ca and cd the network inclusion rate ranged from – 54%, providing support for a functional role in regulation of the ionome in yeast for these genes. in the second group composed of cu, s and ni, the network inclusion rate fell to – 18% suggesting that the genes identified to have a significant effect on these elements may be less likely to be a part of functional systems. the complete lack of network support for genes identified to significant affects on fe and zn suggests that these may not be part of systems that regulate these elements in yeast. evaluation of the connectivity within each network using edges/node reveals large differences between the networks. co, cd, p and mg have the highest network connectivity and this can be explained by the fact that they contain single large networks of interconnected genes. the cd network is highly enriched in genes from cluster_ involved in protein localization including genes in the escrt pathway involving sorting of ubiquitinated transmembrane proteins to the vacuole for degradation. the p, mg and co networks contain multiple genes from cluster_ and which are highly enriched in genes involved in vacuolar function, including the activity of the v-type atpase. the mn and mo networks have intermediate levels of network connectivity perhaps because these networks appear to have independent sub networks. for mo one sub network contains genes involved in transcription and the other is an interconnected set of genes with functions in the mitochondria, vacuole and fe homeostasis. for mn one sub network contain genes involved in mitochondrial function, and the other genes involved in trafficking and activity of mn transporters. these results further validate the methodologies developed to screen the ionome of yeast in high throughput using well plates as well as the statistical methods developed to deal with the highly sensitive data. overall, this approach appears to approximately double the ability to detect ionomic differences compared to previous studies providing a much high resolution of the genes and gene networks involved in regulating the yeast ionome. the results presented here are however likely a small subsample of the genes affecting the ionome of a single celled eukaryote. the lack of several known ionome altering genes in our datasets suggests that rescreening of these populations in different environments would yield another set of known and novel genes. such full genome screens could be accomplished in approximately months per condition and could greatly increase our understanding of the gene by environment interactions controlling elemental accumulation. hypothesis testing using the online yeast ionomics database a yeast ionomics database has been developed and is accessible through the ionomicshub. from the homepage follow the link to the yeast database. the database contains ionomic data on the yeast strains in the ko set, in the kod set and in the oe set. the data consists of the raw solution concentration data for each element measured in each strain, and the same data normalized to the optical density of the yeast culture just prior to preparation for icp-ms analysis. further, the database also contains the ionomic data from the ko, kod and oe sets normalized separately with common strains analyzed in each 96-well plate using a mixed model approach, as described previously by yu et al.,. this normalization allows removal of plate effects and facilitates comparisons of different stains across the complete ko, kod and oe datasets. this database can be used to rapidly retrieve, display and download ionomics data to test if the loss or gain of function of any gene of interest in the full yeast genome has an effect on the yeast ionome. ionomic data for any of the viable yeast strains in the ko, kod and oe collections can be retrieved from the database using the basic search feature by simply typing in the name of the mutant or gene of interest. multiple genes can also be searched simultaneously by separating the name of each mutant/gene using a comma. the basic search returns the 96-well plate in which the mutant of interest was analyzed. an individual strain, multiple strains or the complete 96-well plate can be selected using the check boxes and data for solution concentrations or od normalized normalized data) downloaded as a comma-separated values file. the advance search also allows retrieval of data based on a specific 96-well plate or icp-ms run. a search on a mutant/gene also returns links to other normalized datasets that contain data on the mutant/gene being search e.g. full genome knockout haploid. following the link for a particular dataset presents tools for viewing, plotting and downloading the normalized data on the mutant/gene of interest from that particular dataset. a description of the data set and each type of data is presented. for example, in the full genome knockout haploid dataset, which has been normalized following yu et al.,, data can be viewed for percentage change of normalized values compared to the population mean, change in concentration from the population mean divided by the deviation, and the optical density adjusted concentration data after normalization across population. the line of interest can be selected using the check boxes and data plotted or downloaded. plots available are histogram, box plots, and z-score depending on the type of data. in figure  b-d data is displayed in various ways illustrating the fact that loss of function of smf causes reduced mn accumulation whereas loss of function of smf and pmr causes elevated mn. finally, complete normalized datasets for all ~ strains tested can be accessed via the browse datasets tab and downloaded as zipped csv files.  here, we report a genome-wide scan of approximately genes in yeast using icp-ms to quantify to different elements in both loss of function and gain of function mutant yeast strains. of the knockout strains analyzed showed a significant ionomic phenotype. disruption of protein metabolism or trafficking has the highest likelihood of overcoming the resilience of the ionomic homeostasis networks, leading to the largest changes in the ionome. of the genes significantly impacting the ionome genes were lethal when knocked, but showed an ionomic phenotype when present as a single copy in diploid strains, suggesting that gene dosage can be important in ionomic regulation. of the yeast orfs over expressed impacted the ionome, and as might be expected over expression tends to produce more extreme ionomic phenotypes than loss of function. interestingly, no significant overlap between the gene sets identified from the loss and gain of function experiments was found, suggesting that on a genome-wide scale loss of function and over expression do not produce related phenotypes. analysis of our dataset revealed numerous novel genes which significantly impact the ionome when knocked out or over expressed, and these genes could form the basis of many follow up experiments. clustering based on the ionomic phenotype of over expression or knockout strains identified a limited number of clusters with three or more members, and analysis of gene functions enriched within these clusters revealed that perturbation of particular cellular functions creates unique ionomic phenotypes, such as the mitochondria, vacuolar and escrt pathway, providing a robust way to predict the potential function of genes. analysis of the protein-protein and genetic interaction of genes identified to impact the yeast ionome also revealed novel functional gene networks that illustrate the physical and genetic interactions between genes within a particular mineral nutrient regulatory network. the high network inclusion rate for genes impacting most elements strongly suggests that these genes are truly part of functional systems involved in ionomic regulation. such networks help identify important hub genes that play a critical role in network function, such as pmr in mn homeostasis; novel members of mineral nutrient homeostasis networks, such as the identification of smf as a major pathway for mn uptake non-redundant with smf and smf as the unknown gene involved in mn retrieval from the vacuole; and cross-talk between cellular functions such as the mitochondria and the vacuole. a better understanding of such regulatory networks is also critical if we are to be able to functionally model ionomic regulation within yeast and other organisms. to facilitate such understanding we have developed a publically accessible database through which all the yeast ionomic data described here can be searched, downloaded and analyzed for hypothesis testing and experimental follow up. 
network analysis identified hub genes such as pmr in mn homeostasis, novel members of ionomic networks such as smf in vacuolar retrieval of mn, and cross-talk between the mitochondria and the vacuole. disruption of protein metabolism or trafficking has the highest likelihood of causing large ionomic changes, with gene dosage also being important. here, we describe a genome-wide screen to identify genes that impact the elemental composition of yeast saccharomyces cerevisiae. to balance the demand for uptake of essential elements with their potential toxicity living cells have complex regulatory mechanisms. all yeast ionomic data can be searched and downloaded at http://www.ionomicshub.org. clustering also identified important roles for the mitochondria, vacuole and escrt pathway in regulation of the ionome. here, we demonstrate the power of high-throughput icp-ms analysis to functionally dissect the ionome on a genome-wide scale.
 to balance the demand for uptake of essential elements with their potential toxicity living cells have complex regulatory mechanisms. here, we describe a genome-wide screen to identify genes that impact the elemental composition of yeast saccharomyces cerevisiae. using inductively coupled plasma – mass spectrometry we quantify ca, cd, co, cu, fe, k, mg, mn, mo, na, ni, p, s and zn in mutant strains, including haploid and diploid deletion strains, and over expression strains.  we identified strains with an altered ionome, including haploid and diploid deletion strains, and over expression strains. disruption of protein metabolism or trafficking has the highest likelihood of causing large ionomic changes, with gene dosage also being important. gene over expression produced more extreme ionomic changes, but over expression and loss of function phenotypes are generally not related. ionomic clustering revealed the existence of only a small number of possible ionomic profiles suggesting fitness tradeoffs that constrain the ionome. clustering also identified important roles for the mitochondria, vacuole and escrt pathway in regulation of the ionome. network analysis identified hub genes such as pmr in mn homeostasis, novel members of ionomic networks such as smf in vacuolar retrieval of mn, and cross-talk between the mitochondria and the vacuole. all yeast ionomic data can be searched and downloaded at http://www.ionomicshub.org.  here, we demonstrate the power of high-throughput icp-ms analysis to functionally dissect the ionome on a genome-wide scale. the information this reveals has the potential to benefit both human health and agriculture. ionomeyeastclusteringnetwork analysismitochondriavacuoleescrtgenome-wideicp-msionomics 