Functional profiling of the yeast genome in iron deficiency identifies components of iron metabolism
The application of genome-wide expression profiling has accelerated our understanding of iron metabolism [6
]. However, transcriptional and protein profiling methods provide limited insight into the functional importance of the differentially-regulated genes and do not differentiate between primary and downstream responses. In addition, gene expression approaches provide no information on functional components whose mRNA or protein levels are not directly regulated. In the case of iron metabolism, where there are several layers of regulation, particularly at the post-transcriptional level, analysis of gene expression could then present limitations.
For the functional profiling of the yeast genome, we grew three independent pools containing 4,757 homozygous yeast deletion strains in YPD media in the presence of 75 μM (n = 1) or 100 μM (n = 2) of the iron chelator BPS for 15 generations of growth. We then identified the strains with significant alterations in growth compared to regular rich media (as described in Methods). Because there were no differences between the strains identified at the two BPS concentrations tested, we combined the results from the three experiments. In this way, we identified a total of 141 and 20 strains that were sensitive and resistant to BPS in all three experiments, respectively [see Additional file 1
]. Approximately 500 strains were affected in at least two of the treatments [see Additional file 2
We selected a number of representative strains that showed growth sensitivity in iron-limited media for individual confirmatory analysis (Fig. ). The wild type strain was modestly growth-inhibited at 50 and 100 μM of BPS, while the selected deletion strains exhibited different levels of sensitivity to treatment. Interestingly, the severity of the iron-sensitive phenotype did not always correlate between solid (agar) and liquid media for the same mutant. For example, fet4Δ exhibited a stronger growth defect on solid than in liquid media while ydr055cΔ appeared to be insensitive on solid. These discrepancies could be due to different media used in the assays (YPD for solid versus SD for liquid) or to an intrinsic feature of the growth matrix (solid versus liquid) such as nutrient availability, aeration, etc.
Figure 1 Confirmatory assays of selected BPS-sensitive deletion strains identified by functional profiling. The wild type strain and known mutants defective in iron metabolism, aft1Δ and fet4Δ (not identified in the functional studies), were included (more ...)
Among the highly required genes for optimal growth in BPS (corresponding to the 10 most sensitive strains in the screen), were genes that encode proteins known to be involved in iron metabolism (Table ). Several identified genes encode proteins involved in high affinity uptake of elemental iron (FTR1
, iron permease; and FET3
, multi copper oxidase), and components of the copper assimilatory pathway (ATX1
, vesicular chloride channel; and CCC2
, P-type ATPase transporter). CTR1
, the high-affinity transporter gene required for copper uptake, was essential for fitness in two of the three screens that we performed [see Additional file 2
]. The identification of several copper metabolism genes could be related to the documented connection between the iron and copper metabolic pathways. Alternatively, this could be due to the fact that chelators are not entirely specific to a given metal, and BPS could also chelating copper in our system.
Top 10 genes essential for optimal yeast growth in iron-deficient conditions induced by BPS treatment
In spite of its known role in the induction of iron-uptake genes in iron-limited conditions, we did not identify the transcription factor gene AFT1. We noted high variability and generally low fitness of aft1Δ when grown on agar in the absence of BPS (Fig. ). However, this mutant grew relatively well in liquid media, although slower than the wild type (Fig ), and showed a marked growth inhibition when BPS was present. The reason why AFT1 was not identified in our screen with liquid media is unclear, but may be related to the intrinsic slow growth of the deletion strain relative to other ones in the pool, the competitive growth environment, and/or to a very low starting cell number in the pool.
Other genes with relatively high requirement in low-iron media (log2
fitness < -2.00, 13% of sensitive strains), include ones encoding components of the ESCRT-I complex (STP22
, ubiquitin-dependent sorting of proteins into the endosome) and transcription factors (OPI1
) [see Additional file 1
]. The identification of genes involved in iron metabolism by functional profiling suggests that other identified genes, without any previous association to it, may play unknown roles in iron deficiency.
Differences in iron-deficiency sensitivity profiles between functional profiling methods
The use of functional profiling with yeast deletion mutants to identify novel components in iron metabolism has been reported before, although by different approaches. There was low concordance between our results and those from these previous screens [see Additional file 3
], which we attribute to the differences in BPS concentrations, growth matrixes (solid versus
liquid media), and detection methods used. Furthermore, we grew all mutants simultaneously, creating a competitive growth environment which could have added more stress to the strains, as opposed to individual growth on plates in the published studies.
Davis-Kaplan et al
] performed a screen of diploid strains on solid media with 90 μM BPS and low μM concentrations of FeSO4
, and scored growth after 24 h using a subjective scale. Strains with mutations in genes involved in high affinity iron transport, vacuolar acidification and others of diverse function were growth-inhibited. Of the 17 strains that exhibited a severe growth defect, only 4 associated with components of high affinity iron uptake(fet3Δ, ftr1Δ
) overlapped with our data.
Dudley et al
] also screened the same collection of mutants on agar plates as one of multiple chemical screens, using digital quantification of strain growth. They identified few of the known components of iron metabolism in yeast at a BPS concentration of 200 μM. Of the 35 "high confidence" sensitive strains reported in their data, only one (gcs1Δ
)was common with our study.
Lesuisse et al
] conducted a screen of haploid strains grown on standard media in the presence of labeled ferrioxamine B (a siderophore). Unlike the previous two cases, strains with altered ferrioxamine B uptake were identified using a scintillation counter. Further characterization grouped the mutants into three categories with similar alterations in ferric reductase activity, iron uptake from ferrous salts and from siderophores. We found 12 strains (aps3Δ, atx1 Δ, ccc2 Δ, rav1 Δ, rcy1 Δ, snf7 Δ, vps4 Δ, vps20 Δ, vps25 Δ, vps28 Δ, vps36 Δ
) in common between our study and the 81 mutants with abnormally high or low uptake identified by them.
As noted previously, we found discrepancies in the sensitivity phenotype of some mutants after comparing their growth between solid and liquid media (Fig. ). Together, these results support a rationale for screening in liquid media to uncover different and potentially novel components of iron metabolism in yeast.
The importance of intracellular trafficking pathways and the vacuole for optimal growth in low-iron conditions
Interestingly, most of the genes that we identified by functional profiling encoded components involved in intracellular transport (n = 53, 33% of the dataset). Among these, were genes associated with organelle organization and biogenesis (peroxisome, n = 9; endosome, n = 11; and vacuole, n = 5), protein transport, and components of the endocytic pathway (Table ) [see Additional file 4
Gene Ontology enrichment by biological process and cellular localization of genes identified by functional profiling
Although the most sensitive strains contained deletions in genes directly involved in iron uptake and metabolism, they accounted for a small fraction, as the majority of genes were involved in vacuolar function. The likely reason for an overrepresentation of vacuolar genes is that the vacuole acts as an iron reservoir in yeast [30
] and its function has been shown to be important for iron homeostasis [14
]. In these lines, vacuolar acidification was an essential biological process, and genes of the H-V-type ATPase complex (STV1
) were necessary for optimal growth. Thus, this further supports an important role of a functional vacuole in iron deficiency.
Metal transport processes were also important for yeast growth under these conditions [see Additional file 4
]. However, their relative importance given by functional enrichment was lower than the vacuole and intracellular transport, which had lower hypergeometric p-values (that is, they were more significant). Nevertheless, these results indicate an important and known role of iron uptake pathways in iron deficiency.
Gene regulatory networks essential in iron-limited conditions
We analyzed the yeast molecular interaction network to find genes potentially working in a coordinated fashion in iron-limited conditions, but not necessarily associated to a same biological process or molecular function. For this purpose, we used the Jactive modules plug in for Cytoscape, which assigns statistically-determined scores to subnetworks and identify those ones with high scores [25
]. After overlaying our functional data, the resulting high-scoring subnetworks were enriched with genes essential for growth in iron deficiency.
Using the search strategy in Jactive modules, we found 4 significant subnetworks (z
-scores > 3). The merge of these networks (totaling 199 nodes) showed many highly interconnected nodes (or hubs), namely AFT1
, STP2, SWI4
, and XBP1
(Fig. ). These genes encode transcription factors that regulate and/or physically interact with many significant genes from our data, some of which are involved in iron metabolism (Figs. ) [see Additional file 5
]. Therefore, these transcription factors are likely to mediate the cellular adaptation and response to iron deficiency, although most of them were not significant in our screen (for example AFT1
, both implicated in iron metabolism). The fact that the network analysis identified these additional functional components shows its importance as a complementary tool in genomic analysis.
Figure 2 Functional identification of transcriptional response networks in iron deficiency. A Interaction network of highly interconnected nodes, mostly representing transcription factors, associated with the response to iron deficiency in yeast. Each node interacts (more ...)
Both Aft1p and Cad1p regulate many overlapping genes and appear to work in conjunction to mediate the transcriptional response of several genes in iron deficiency (Figs. and ). Cad1p is required for stress response, growth at toxic levels of iron chelators, and thought to be involved in iron metabolism [35
]. Most notably, Cad1p regulates CTI6
which were highly required in BPS, suggesting that its role in iron deficiency may be related to these interactions. Functionally-enriched biological processes of Cad1p-regulated genes that were significant in our study include histone deacetylation/chromatin modification (SIF2
) and response to arsenic (GET3
). Thus, Cad1p may be involved in transcriptional activation in response to iron deprivation and other stressors.
Swi4p, Dot6p and Skn7p (Figs. and , respectively), on the other hand, regulate many genes with diverse functions so their relation to the regulation of specific processes is unclear. These transcription factors also showed partial overlap in regulated genes, indicating the existence of multiple transcriptional regulators for the genes that we identified as essential for optimal grow in BPS. This redundancy at the regulatory level could be the reason why several of these transcription factors were not identified in our functional screen (Fig ), as the lost of any of them in the deletion mutants could be compensated by the function of the remaining ones. Information about Swi4p, Dot6p and Skn7p, and their regulated genes, can be found at YEASTRACT http://www.yeastract.com
The function of the ESCRT complexes and peroxisome are required in iron deficiency
We also searched for essential subnetworks using the annealing strategy in JActive modules and identified one large subnetwork (n = 370, z-score = 16.633) (Fig. ). A second application of the search algorithm revealed several subnetworks of interest with predominantly physical interactions; one associated with the peroxisome (Fig. ) and three with the ESCRT complexes (Figs. ). Most genes in these subnetworks were essential, showing an important role of these cellular components in iron-deficient conditions.
Figure 3 Subnetworks with essential components for optimal yeast growth in iron deficiency. The majority of proteins interact physically (solid lines) and form molecular complexes that include the A peroxisome, as well as B, C, D ESCRT I, II and III. Deletion (more ...)
Our findings for the peroxisome suggest that this organelle may play a previously unsuspected role in iron metabolism. We speculate that iron deficiency may impair mitochondrial β-oxidation due to the significant iron requirements of the mitochondrial electron transport chain. Under these conditions, peroxisomal β-oxidation may play a greater role in energy metabolism and disruption of the peroxisome may prevent the utilization of this alternative energy source.
Similarly, the requirement of many genes encoding subunits of the ESCRT complexes I, II and III is a strong indication of their involvement in iron-deficient conditions. The ESCRT complexes have been associated with metal resistance including cadmium and iron overload [22
]. These results support the role of the ESCRT complexes and intracellular transport in metal homeostasis in general.
Specific genetic requirements of yeast for optimal growth in iron deficiency
We compared the genes that we identified after BPS treatments to the ones previously identified under growth in galactose, sorbitol, pH 8, NaCl, minimal media, nystatin, and iron and copper overload. We performed a cluster analysis with the 161 genes identified in our BPS treatments, as our goal was to provide insight into the genetic requirements in this condition and its specificity compared to other stressors (Fig. ) [see Additional file 6
]. Most genes required in iron deficiency were specific to it, although several ones involved in high affinity iron uptake (FTR1, CCC2
)were also required for optimal growth in other conditions including galactose and high pH.
Figure 4 Hierarchical clustering analysis of the genes identified by functional profiling in iron deficiency under diverse growth conditions. Genes identified in iron deficiency were compared for functional requirement across different conditions from previously-published (more ...)
There were distinct groups of genes with similar and opposite requirement patterns in the different growth conditions (Fig. ) [see Additional file 6
]. Among the conditions that we compared, growth at pH 8 exhibited the closest similarity in the genetic requirements to BPS treatment, particularly in genes associated with the intracellular trafficking pathway and transport (p < 0.001). The presence of genes required in iron deficiency (FTR1
) suggest low-iron conditions in pH 8 and could be associated to the low solubility of iron at high pH. However, because the genes involved in vacuolar/intracellular trafficking play diverse roles in yeast metabolism, it is not possible to establish whether the observed similarity between the pH 8 and BPS treatments is associated to iron deficiency. On the other hand, several genes with diverse functions including growth (TPK1
) and protein targeting (EPS1
), showed an opposite requirement in pH 8.
Not unexpectedly, iron overload and deficiency showed very little overlap in their genetic requirements, which may implicate different homeostatic mechanisms under these two conditions. Interestingly, CIN2
displayed opposite requirements, being essential in iron overload but detrimental in iron deficiency. Cin2p is a GTPase-activating protein involved in microtubule stability. In mammalian cells, microtubules interact with the iron-storing protein ferritin, playing a role in its cytoplasmic distribution and possibly increasing its iron-binding capacity relative to microtubule-associated ferritin [38
]. The role of Cin2p in yeast could be associated to iron homeostasis through its role in microtubule function.
Interestingly, copper overload exhibited concordance in the requirement of several genes associated with intracellular trafficking (for example,VPS27 and VPS21) and iron transport (FTR1), suggesting that excess copper (in addition to its deficiency) alters iron homeostasis.
Our results show a specific genetic requirement profile in iron deficiency as opposed to other environmental stressors. Few components of iron metabolism form part of yeast's response to other growth conditions, suggesting multiple functions for them or that these conditions can also alter iron homeostasis.
Differential gene expression in iron deficiency indicates a metabolic reprogramming in yeast
We evaluated the transcriptional response of yeast in iron deficiency by gene expression profiling after treatment with 100 μM BPS for 1 hour. We conducted three independent experiments and considered for analysis those genes that were differentially-expressed in at least two of them. In this way, we identified a total of 100 and 42 up- and down-regulated genes, respectively [see Additional files 7
]. Most of the up-regulated genes corresponded to iron (n = 17) and nucleotide (n = 15) metabolism. Among these two groups, iron metabolism genes had, on average, higher expression levels than those for nucleotide metabolism. This last group included transcription factor and chromatin remodeling genes and its presence indicate that nuclear changes precede and/or accompany adaptation to iron deficiency. On the other side, genes associated with energy (n = 5, all localized to the mitochondria), protein (n = 5), and nucleotide (n = 5) metabolism were down-regulated.
GO enrichment analysis showed that genes that were up-regulated were mainly associated with metal transport (iron, n = 11; copper, n = 4; and zinc, n = 3) and their products localized to the membrane (n = 38) and extracellular space (n = 6). On the other hand, down-regulated genes were associated with components of the TCA cycle (ACO1
) and most of their products localized to the mitochondria (CYT2, CCP1
) (Table ) [see Additional file 9
Gene Ontology enrichment by biological process for differentially-expressed genes in BPS
We also observed in BPS a time-dependent increase in the number of up-regulated genes involved in high affinity iron transport and glycolysis, which occurred in parallel to an increase in the number of down-regulated genes associated with the TCA cycle, respiratory chain and biosynthesis of certain amino acids (data not shown). Up-regulation of genes in the glycolytic pathway probably occurs to compensate for the decreased energy production as a consequence of the down-regulation of components involved in aerobic energy synthesis.
Altogether, our data supports that iron deficiency induces metabolic changes that aims to preserve iron from non-essential cellular processes (reviewed by Kaplan et al
]). The down-regulation of several mitochondrial/energy metabolism genes suggests that during anaerobic growth in plain YPD, when glucose remains in the media, respiration genes are not entirely down-regulated (or not down-regulated at all) even though they are not required at that point of growth. In BPS, maintaining the expression of these genes is expensive in terms of iron usage and can be detrimental; therefore, yeast can afford to down-regulate them if glucose is still present. On the other side, up-regulation of iron uptake mechanisms aims to increase intracellular iron levels. Most of the up-regulated genes were associated with these processes, suggesting that iron uptake is mainly regulated at the transcriptional level. Shakoury-Elizeh et al
] also showed that yeast subjected to iron deprivation undergo a transcriptional remodeling, resulting in a metabolic shift from iron-dependent to iron-independent pathways, which includes biotin uptake and biosynthesis, nitrogen assimilation, and purine biosynthesis.
Functional and expression profiling provide complementary views of yeast's response in iron deficiency
Of the 161 genes that we identified with functional profiling, only 11 were differentially-expressed (Table ). Both functional and expression profiling of yeast grown in limited-iron conditions identified few known components of the iron regulon (FET3, FRE1, MRS4 and CCC2) as functionally essential and up-regulated, respectively. YCR007C, encoding a putative plasma membrane protein, was also essential and up-regulated in iron deficiency, and could be involved in iron uptake or a related process. DAP1 and YTA7 were also essential but down-regulated, although their requirement with decreased expression levels in iron deficiency is not clear. The aconitase gene ACO1, which product is a component of the TCA cycle, was down-regulated and its presence was detrimental for growth, thus further supporting the fact that reduction in aerobic respiration helps preserve iron for other vital processes.
Overlapping genes identified by expression and fitness profiling approaches under iron-limited conditions
Although the number of identified genes was about the same, functional profiling identified primarily components of the intracellular trafficking pathway and vacuole (Table ), while expression profiling identified most components in iron and metal metabolism (Table ). Therefore, these approaches identified components that are functionally distinct but both important for iron homeostasis.
Low affinity- and siderophore-iron transport systems (FET4, ARN and FIT genes) are important for iron uptake and the fact that they were differentially-expressed after BPS treatment in our experiments, confirms a role for them in iron deficiency. However, we did not identify these same genes in our functional studies, which we attribute to functional redundancy. Additionally, deletion of the ARN and FIT genes would probably not be detrimental for growth because the pathway in which they are involved requires the presence of siderophores not produce by yeast itself but by other microorganisms. Therefore, the presence or absence of these genes would not have an impact on fitness under the growth conditions of our study, despite the fact that these genes were up-regulated. Conversely, the identification of several vacuolar-sorting defective mutants as sensitive suggests that intracellular trafficking pathways have components with specialized functions and low degree of functional redundancy. However, the encoded genes are non essential under regular conditions, as homozygous deletion mutants are viable in rich media. Intracellular transport and related processes are also required in a variety of cellular processes including detoxification of diverse heavy metals, so many of the genes involved may be constitutively expressed due to this continuous requirement and not differentially-expressed in iron deficiency.
Our analysis revealed two groups of genes essential for yeast in iron deficiency, with few overlapping members. One group that is inducible in response to low iron and is directly implicated in the metabolism of iron and other metals, with some degree of functional redundancy among components. The other group is not transcriptionally-regulated and forms part of regular metabolism and response to multiple stressors in yeast, and includes components associated with intracellular transport pathways.
The lack of correlation between genes identified by functional and expression profiling approaches has been reported previously [18
], and may reflect a fundamental aspect of how cells respond to stress [41
]. Haugen et al
] showed that genes that confer sensitivity to arsenic are in pathways that are upstream of the genes that are differentially-expressed in arsenic and that share redundant functions. This is also the case in iron deficiency, where some genes associated with intracellular trafficking function upstream of the ones involved in iron uptake. For example, copper loading onto Fet3p and assembly of functional Fet3p-Ftr1p in the plasma membrane for high-affinity iron uptake is dependent on these transport pathways. However, our results show that functional profiling does not necessarily identify genes in upstream pathways. Some other genes in intracellular transport pathways that we identified are associated to vacuolar iron storage and/or mobilization and hence, downstream of iron uptake. As such, these genes are not directly related to iron uptake but one that works in parallel to maintain iron homeostasis through the vacuole.
Expression profiling of selected BPS-sensitive deletion strains confirms genes with roles in iron metabolism
The high requirement in BPS of the genes DAP1
suggested important roles for them, at the time of this study, in iron metabolism (Table ) [see Additional file 1
]. We expression profiled the mutants with deletion in these genes to gain insight into their functions under normal growth conditions [see Additional file 10
]. While this study was in progress, transcriptional data for cti6Δ
grown in the presence of BPS was published by Puig et al
]. Alterations in the expression of known iron metabolism genes in these strains compared to the wild type (both grown in rich media, YPD), as discussed below, implicates DAP1
in iron metabolism.
encodes an Rpd3p-Sin3p histone deacetylase-associated protein involved in derepression of promoters which are repressed by Ssn6p-Tup1p complexes [43
], and required for growth in iron deficiency [42
]. Cti6p is recruited to iron-responsive promoters in an Aft1p-dependent manner and mediates the expression of ARN1
under heme-deficient conditions [44
]. The cti6Δ
mutant showed up-regulation of multiple genes, most notably ones involved in carbohydrate, nucleotide, metal and protein metabolism [see Additional file 11
]. The most up-regulated gene was MET17
= 4.51), encoding an O-acetylhomoserine sulfhydrylase. Interestingly, met17Δ
exhibits high levels of H2
S and is resistant to lead and methylmercury, while moderate overexpression leads to decreased H2
S levels [45
]. Perhaps decreased levels of H2
S in cti6Δ
contribute to iron sensitivity. On the other hand, cti6Δ
showed a dramatic down-regulation of a whole series of genes involved in response to pheromone and chemosensory perception, suggesting that these pathways are important in sensing or responding to iron deficiency.
, for da
mage resistance p
rotein, encodes a 152 amino acid protein that belongs to the membrane-associated progesterone receptor (MAPR) family. The dap1Δ
strain exhibits increased DNA damage particularly to methylating agents, telomere elongation, partial loss of ergosterol synthesis, and defect in mitochondrial biogenesis [46
]. Dap1p functions in iron deficiency probably through the regulation of vacuolar structure via sterol synthesis, which is achieved by activation of Erg11p [47
]. We found that DAP1
is down-regulated in iron deficiency and in its absence, some members of the iron regulon, particularly siderophore iron transporters, have decreased transcript levels (Table ) [see Additional file 12
]. In particular, dap1Δ
showed decreased transcript levels of FIT2-3
, encoding siderophore transporters, and FET3
involved in high affinity iron transport systems. Taken together, these results suggest a specific role of Dap1p in iron metabolism.
List of iron homeostasis genes that are down-regulated in dap1Δ
encodes a mitochondrial iron transporter that functions under low-iron conditions [48
], cooperating with its homologous MRS3
to provide iron for Fe-S clusters and heme biosynthesis in mitochondria [49
]. The mrs4Δ
strain showed up-regulation of an increased number of genes involved in carbohydrate and energy metabolism, and high affinity and siderophore-mediated iron uptake [see Additional file 13
]. These results indicate a loss of mitochondrial functionality and that this mutant has to rely on other pathways, such as glycolysis, for energy production. Moreover, they suggest that mitochondria constitutes part of the iron-sensing mechanism in yeast, as low mitochondrial iron due to MRS4
deletion is perceived as an iron deficient-state despite growth in normal-iron conditions. The fact that mrs4Δ
exhibited disturbances in iron metabolism shows that the functions performed by MRS4
are not fully redundant to that MRS3
as thought [48
is an ORF of uncharacterized function. The yhr045wΔ
mutant showed increased transcript levels of several genes involved in iron homeostasis such as ARN3-4, FIT2-3
(but curiously, not the entire iron regulon), as well as multiple genes involved in energy metabolism including amino acid and carbohydrate metabolism. On the other hand, the majority of genes with decreased transcript levels encode ribosomal proteins [see Additional file 14
]. In contrast to cti6Δ
, we did not observe a decrease in transcript levels of chemosensory perception in yhr045wΔ
, suggesting that this mutant is sensitive to low-iron media because of a specific defect in iron metabolism rather than general external stimuli sensory system.
The iron metabolism map in yeast
Using information from known molecular interactions associated to iron metabolism, we created a network to further understand the interactions between its different components. We first constructed a network with all interactions and organized it with the force-directed algorithm in Cytoscape [see Additional file 15
]. Here, nodes in the network behave as electrons that repulse each other while edges behave as springs pulling connected nodes closer to each other. The result is a graphic where all components in the system are in equilibrium, that is, the sum of forces is decreased to a minimum. By applying this layout, we found a cluster of nodes near of the center of the network that were highly interconnected and enriched with known iron metabolism genes including AFT1
), which protein product targets degradation of mRNAs from iron metabolism-related genes, is closer to the cluster, while its homolog CTH1
targeting mitochondrial genes, is located towards the outside of the network. Among the genes that we studied by expression profiling of deletion strains, DAP1
was the closest to it followed by MRS4
, indicating a close functional relationship of these genes to iron metabolism. CTI6
were farther away from the iron metabolism cluster, suggesting less specialized functions but nonetheless important to iron metabolism.
We also constructed a second network that excluded molecular interactions derived from genomics data from this and other studies [11
] [see Additional file 16
]. A discrete number of genes in iron-protein utilizing pathways showed differential expression and/or functional requirement, suggesting that most of yeast's response in iron deficiency involve different pathways other than these. Iron metabolism is highly conserved in yeast and humans. In this network containing genes directly associated with iron metabolism, as well as iron related pathways, 44% of proteins have homologs in humans (SGD Model Organism BLASTP Best Hits). This value is higher than the estimated 33% of conservation between the human and yeast genomes (at a BLAST E-value of 10-12
, which means highly conserved homologous genes) [51
]. Therefore, these conserved genes and pathways associated to iron in yeast could help to better understand iron metabolism in humans.