Novel insights into iron metabolism by integrating deletome and transcriptome analysis in an iron deficiency model of the yeast Saccharomyces cerevisiae

Department of Nutritional Sciences and Toxicology, University of California, Berkeley, California 94720, USA.
BMC Genomics (Impact Factor: 3.99). 04/2009; 10(1):130. DOI: 10.1186/1471-2164-10-130
Source: PubMed


Iron-deficiency anemia is the most prevalent form of anemia world-wide. The yeast Saccharomyces cerevisiae has been used as a model of cellular iron deficiency, in part because many of its cellular pathways are conserved. To better understand how cells respond to changes in iron availability, we profiled the yeast genome with a parallel analysis of homozygous deletion mutants to identify essential components and cellular processes required for optimal growth under iron-limited conditions. To complement this analysis, we compared those genes identified as important for fitness to those that were differentially-expressed in the same conditions. The resulting analysis provides a global perspective on the cellular processes involved in iron metabolism.
Using functional profiling, we identified several genes known to be involved in high affinity iron uptake, in addition to novel genes that may play a role in iron metabolism. Our results provide support for the primary involvement in iron homeostasis of vacuolar and endosomal compartments, as well as vesicular transport to and from these compartments. We also observed an unexpected importance of the peroxisome for growth in iron-limited media. Although these components were essential for growth in low-iron conditions, most of them were not differentially-expressed. Genes with altered expression in iron deficiency were mainly associated with iron uptake and transport mechanisms, with little overlap with those that were functionally required. To better understand this relationship, we used expression-profiling of selected mutants that exhibited slow growth in iron-deficient conditions, and as a result, obtained additional insight into the roles of CTI6, DAP1, MRS4 and YHR045W in iron metabolism.
Comparison between functional and gene expression data in iron deficiency highlighted the complementary utility of these two approaches to identify important functional components. This should be taken into consideration when designing and analyzing data from these type of studies. We used this and other published data to develop a molecular interaction network of iron metabolism in yeast.

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Available from: Adam P Arkin, Oct 05, 2015
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    • "The first is to limit the available iron in the medium by chelators. For work with yeasts like S. cerevisiae and Schizosaccharomyces pombe, iron-chelators such as 2,2′-dipyridyl and bathophenanthroline disulfonic acid, are often used to generate a state of poor iron nutrition in vivo (Eide et al., 1996; Pelletier et al., 2005; Mercier et al., 2006; Jo et al., 2009). Some studies with plants like Arabidopsis thaliana have combined the use of chelators like ferrozine with the strategy of creating iron deficiency by omitting iron from the media (Vert et al., 2002; Lanquar et al., 2005; Yang et al., 2010). "
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    ABSTRACT: While research on iron nutrition in plants has largely focused on iron-uptake pathways, photosynthetic microbes such as the unicellular green alga Chlamydomonas reinhardtii provide excellent experimental systems for understanding iron metabolism at the subcellular level. Several paradigms in iron homeostasis have been established in this alga, including photosystem remodeling in the chloroplast and preferential retention of some pathways and key iron-dependent proteins in response to suboptimal iron supply. This review presents our current understanding of iron homeostasis in Chlamydomonas, with specific attention on characterized responses to changes in iron supply, like iron-deficiency. An overview of frequently used methods for the investigation of iron-responsive gene expression, physiology and metabolism is also provided, including preparation of media, the effect of cell size, cell density and strain choice on quantitative measurements and methods for the determination of metal content and assessing the effect of iron supply on photosynthetic performance.
    Frontiers in Plant Science 09/2013; 4:337. DOI:10.3389/fpls.2013.00337 · 3.95 Impact Factor
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    • "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 [1-4]. The availability of full genome deletion and open reading frame (ORF) overexpression collections [5-7] 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 [2,8], B [9], selenite [10], and Fe [11] and Zn [12] deficiency. Studies have also been undertaken in which accumulation of Fe [13], Cs, Sr [14], and P [15] have been directly quantified in yeast cells. "
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    ABSTRACT: Background 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 (‘ionome’) of yeast Saccharomyces cerevisiae. Using inductively coupled plasma – mass spectrometry (ICP-MS) we quantify Ca, Cd, Co, Cu, Fe, K, Mg, Mn, Mo, Na, Ni, P, S and Zn in 11890 mutant strains, including 4940 haploid and 1127 diploid deletion strains, and 5798 over expression strains. Results We identified 1065 strains with an altered ionome, including 584 haploid and 35 diploid deletion strains, and 446 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 PMR1 in Mn homeostasis, novel members of ionomic networks such as SMF3 in vacuolar retrieval of Mn, and cross-talk between the mitochondria and the vacuole. All yeast ionomic data can be searched and downloaded at Conclusions 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.
    BMC Genomics 11/2012; 13(1):623. DOI:10.1186/1471-2164-13-623 · 3.99 Impact Factor
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    • "Also, conventional growth assays (on elevated calcium or zinc) do not differentiate between wild-type yeast and yeast lacking STV1, as the vacuolar isoform compensates for a loss of the Stv1p-containing complex (Figure 3A). However, a recent report described a phenotypic difference between wild-type yeast and stv1∆ mutant yeast on media containing the iron chelator, BPS (Jo et al., 2009). "
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    ABSTRACT: The vacuolar-type, proton-translocating ATPase (V-ATPase) is a multisubunit enzyme responsible for organelle acidification in eukaryotic cells. Many organisms have evolved V-ATPase subunit isoforms that allow for increased specialization of this critical enzyme. Differential targeting of the V-ATPase to specific subcellular organelles occurs in eukaryotes from humans to budding yeast. In Saccharomyces cerevisiae, the two subunit a isoforms are the only difference between the two V-ATPase populations. Incorporation of Vph1p or Stv1p into the V-ATPase dictates the localization of the V-ATPase to the vacuole or late Golgi/endosome, respectively. A duplication event within fungi gave rise to two subunit a genes. We used ancestral gene reconstruction to generate the most recent common ancestor of Vph1p and Stv1p (Anc.a) and tested its function in yeast. Anc.a localized to both the Golgi/endosomal network and vacuolar membrane and acidified these compartments as part of a hybrid V-ATPase complex. Trafficking of Anc.a did not require retrograde transport from the late endosome to the Golgi that has evolved for retrieval of the Stv1p isoform. Rather, Anc.a localized to both structures through slowed anterograde transport en route to the vacuole. Our results suggest an evolutionary model that describes the differential localization of the two yeast V-ATPase isoforms.
    Molecular biology of the cell 07/2011; 22(17):3176-91. DOI:10.1091/mbc.E11-03-0244 · 4.47 Impact Factor
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