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Mapping condition-dependent regulation of lipid metabolism in Saccharomyces cerevisiae.

Jewett MC, Workman CT, Nookaew I, Pizarro FA, Agosin E, Hellgren LI, Nielsen J - G3 (Bethesda) (2013)

Bottom Line: Here, we map condition-dependent regulation controlling lipid metabolism in Saccharomyces cerevisiae by measuring 5636 mRNAs, 50 metabolites, 97 lipids, and 57 (13)C-reaction fluxes in yeast using a three-factor full-factorial design.To query this network, we developed integrative methods for correlation of multi-omics datasets that elucidate global regulatory signatures.Our data highlight many characterized regulators of lipid metabolism and reveal that sterols are regulated more at the transcriptional level than are amino acids.

View Article: PubMed Central - PubMed

Affiliation: Center for Microbial Biotechnology, DTU Systems Biology, Technical University of Denmark, DK-2800 Kongens Lyngby, Denmark.

ABSTRACT
Lipids play a central role in cellular function as constituents of membranes, as signaling molecules, and as storage materials. Although much is known about the role of lipids in regulating specific steps of metabolism, comprehensive studies integrating genome-wide expression data, metabolite levels, and lipid levels are currently lacking. Here, we map condition-dependent regulation controlling lipid metabolism in Saccharomyces cerevisiae by measuring 5636 mRNAs, 50 metabolites, 97 lipids, and 57 (13)C-reaction fluxes in yeast using a three-factor full-factorial design. Correlation analysis across eight environmental conditions revealed 2279 gene expression level-metabolite/lipid relationships that characterize the extent of transcriptional regulation in lipid metabolism relative to major metabolic hubs within the cell. To query this network, we developed integrative methods for correlation of multi-omics datasets that elucidate global regulatory signatures. Our data highlight many characterized regulators of lipid metabolism and reveal that sterols are regulated more at the transcriptional level than are amino acids. Beyond providing insights into the systems-level organization of lipid metabolism, we anticipate that our dataset and approach can join an emerging number of studies to be widely used for interrogating cellular systems through the combination of mathematical modeling and experimental biology.

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Transcription factor associations with genes correlated to lipid or metabolite levels. The Fisher exact test was used to identify significant overlaps between transcription factor target sets and genes significantly correlated (blue arrows) or anti-correlated (red arrows) to the implicated lipid or metabolite. The relative thickness of each arrow represents the −log10(P value) from the Fisher exact test.
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fig6: Transcription factor associations with genes correlated to lipid or metabolite levels. The Fisher exact test was used to identify significant overlaps between transcription factor target sets and genes significantly correlated (blue arrows) or anti-correlated (red arrows) to the implicated lipid or metabolite. The relative thickness of each arrow represents the −log10(P value) from the Fisher exact test.

Mentions: In an effort to identify factors controlling co-regulated correlation networks, smaller sets of significantly changing genes identified as significantly correlated to specific metabolites or lipids were analyzed for enrichment of TF targets (Figure 1F). This analysis identified 16 TFs significantly associated with four metabolites and 15 different lipid species through the gene sets levels to which they were significantly correlated. Positively and negatively correlated gene expression level–lipid and gene expression level–metabolite sets were analyzed separately. Figure 6 shows the significant (hypergeometric P ≤ 0.01) TF gene expression level–lipid and TF gene expression level–metabolite enrichments capture a global regulatory model of lipid metabolism. The Hap family of TFs and, particularly, Hap4p and Hap1p were found associated with genes negatively correlated to a number of lipid levels. Interestingly, Upc2p and Rox1p targets were enriched for genes positively correlated to PINS, PINSS, PC, and PCS, and were negatively correlated to ergosterol. These regulators are known players in sterol regulation (Espenshade and Hughes 2007; Nielsen 2009).


Mapping condition-dependent regulation of lipid metabolism in Saccharomyces cerevisiae.

Jewett MC, Workman CT, Nookaew I, Pizarro FA, Agosin E, Hellgren LI, Nielsen J - G3 (Bethesda) (2013)

Transcription factor associations with genes correlated to lipid or metabolite levels. The Fisher exact test was used to identify significant overlaps between transcription factor target sets and genes significantly correlated (blue arrows) or anti-correlated (red arrows) to the implicated lipid or metabolite. The relative thickness of each arrow represents the −log10(P value) from the Fisher exact test.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3815060&req=5

fig6: Transcription factor associations with genes correlated to lipid or metabolite levels. The Fisher exact test was used to identify significant overlaps between transcription factor target sets and genes significantly correlated (blue arrows) or anti-correlated (red arrows) to the implicated lipid or metabolite. The relative thickness of each arrow represents the −log10(P value) from the Fisher exact test.
Mentions: In an effort to identify factors controlling co-regulated correlation networks, smaller sets of significantly changing genes identified as significantly correlated to specific metabolites or lipids were analyzed for enrichment of TF targets (Figure 1F). This analysis identified 16 TFs significantly associated with four metabolites and 15 different lipid species through the gene sets levels to which they were significantly correlated. Positively and negatively correlated gene expression level–lipid and gene expression level–metabolite sets were analyzed separately. Figure 6 shows the significant (hypergeometric P ≤ 0.01) TF gene expression level–lipid and TF gene expression level–metabolite enrichments capture a global regulatory model of lipid metabolism. The Hap family of TFs and, particularly, Hap4p and Hap1p were found associated with genes negatively correlated to a number of lipid levels. Interestingly, Upc2p and Rox1p targets were enriched for genes positively correlated to PINS, PINSS, PC, and PCS, and were negatively correlated to ergosterol. These regulators are known players in sterol regulation (Espenshade and Hughes 2007; Nielsen 2009).

Bottom Line: Here, we map condition-dependent regulation controlling lipid metabolism in Saccharomyces cerevisiae by measuring 5636 mRNAs, 50 metabolites, 97 lipids, and 57 (13)C-reaction fluxes in yeast using a three-factor full-factorial design.To query this network, we developed integrative methods for correlation of multi-omics datasets that elucidate global regulatory signatures.Our data highlight many characterized regulators of lipid metabolism and reveal that sterols are regulated more at the transcriptional level than are amino acids.

View Article: PubMed Central - PubMed

Affiliation: Center for Microbial Biotechnology, DTU Systems Biology, Technical University of Denmark, DK-2800 Kongens Lyngby, Denmark.

ABSTRACT
Lipids play a central role in cellular function as constituents of membranes, as signaling molecules, and as storage materials. Although much is known about the role of lipids in regulating specific steps of metabolism, comprehensive studies integrating genome-wide expression data, metabolite levels, and lipid levels are currently lacking. Here, we map condition-dependent regulation controlling lipid metabolism in Saccharomyces cerevisiae by measuring 5636 mRNAs, 50 metabolites, 97 lipids, and 57 (13)C-reaction fluxes in yeast using a three-factor full-factorial design. Correlation analysis across eight environmental conditions revealed 2279 gene expression level-metabolite/lipid relationships that characterize the extent of transcriptional regulation in lipid metabolism relative to major metabolic hubs within the cell. To query this network, we developed integrative methods for correlation of multi-omics datasets that elucidate global regulatory signatures. Our data highlight many characterized regulators of lipid metabolism and reveal that sterols are regulated more at the transcriptional level than are amino acids. Beyond providing insights into the systems-level organization of lipid metabolism, we anticipate that our dataset and approach can join an emerging number of studies to be widely used for interrogating cellular systems through the combination of mathematical modeling and experimental biology.

Show MeSH
Related in: MedlinePlus