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

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• 作者：William J Jo (1)
  JeungHyoun Kim (1)
  Eric Oh (1)
  Daniel Jaramillo (2)
  Patricia Holman (1)
  Alex V Loguinov (1)
  Adam P Arkin (3) (4)
  Corey Nislow (5) (6) (8)
  Guri Giaever (5) (7) (8)
  Chris D Vulpe (1)
  
• 刊名：BMC Genomics
• 出版年：2009
• 出版时间：December 2009
• 年：2009
• 卷：10
• 期：1
• 全文大小：2396KB
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• 作者单位：William J Jo (1)
  JeungHyoun Kim (1)
  Eric Oh (1)
  Daniel Jaramillo (2)
  Patricia Holman (1)
  Alex V Loguinov (1)
  Adam P Arkin (3) (4)
  Corey Nislow (5) (6) (8)
  Guri Giaever (5) (7) (8)
  Chris D Vulpe (1)
  
  1. Department of Nutritional Sciences and Toxicology, University of California, 94720, Berkeley, California, USA
  2. Stanford Genome Technology Center, Stanford University, 94304, Palo Alto, California, USA
  3. Department of Bioengineering, University of California, 94720, Berkeley, California, USA
  4. Physical Biosciences Division, Lawrence Berkeley National Laboratory, 94720, Berkeley, California, USA
  5. University of Toronto, Department of Molecular Genetics, M5S3E1, Ontario, Toronto, Canada
  6. Banting and Best Department of Medical Research, University of Toronto, M5S3E1, Ontario, Toronto, Canada
  8. Donnelley Centre for Cellular and Biomolecular Research, University of Toronto, M5S3E1, Ontario, Toronto, Canada
  7. Department of Pharmaceutical Sciences, University of Toronto, M5S3E1, Ontario, Toronto, Canada
  

文摘

Background 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. Results 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. Conclusion 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.