4.7 Article

High-resolution genome-wide scan of genes, gene-networks and cellular systems impacting the yeast ionome

Journal

BMC GENOMICS
Volume 13, Issue -, Pages -

Publisher

BMC
DOI: 10.1186/1471-2164-13-623

Keywords

Ionome; Yeast; Clustering; Network analysis; Mitochondria; Vacuole; ESCRT; Genome-wide; ICP-MS; Ionomics

Funding

  1. National Institutes of Health [4 R33 DK070290-02]
  2. National Science Foundation Advanced Biological Infrastructure award [0953433]
  3. National Science Foundation Plant Genome Research Program award [0701119]
  4. Direct For Biological Sciences
  5. Division Of Integrative Organismal Systems [0701119] Funding Source: National Science Foundation
  6. Direct For Biological Sciences
  7. Div Of Biological Infrastructure [0953433] Funding Source: National Science Foundation
  8. Div Of Molecular and Cellular Bioscience
  9. Direct For Biological Sciences [0923731] Funding Source: National Science Foundation

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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 www.ionomicshub.org. 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.

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