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.
n class="Chemical">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 n>n class="Chemical">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.
Entities:
Keywords:
integrated systems biology; lipid metabolism; metabolome; omics; regulation
Authors: Melissa S Cline; Michael Smoot; Ethan Cerami; Allan Kuchinsky; Nerius Landys; Chris Workman; Rowan Christmas; Iliana Avila-Campilo; Michael Creech; Benjamin Gross; Kristina Hanspers; Ruth Isserlin; Ryan Kelley; Sarah Killcoyne; Samad Lotia; Steven Maere; John Morris; Keiichiro Ono; Vuk Pavlovic; Alexander R Pico; Aditya Vailaya; Peng-Liang Wang; Annette Adler; Bruce R Conklin; Leroy Hood; Martin Kuiper; Chris Sander; Ilya Schmulevich; Benno Schwikowski; Guy J Warner; Trey Ideker; Gary D Bader Journal: Nat Protoc Date: 2007 Impact factor: 13.491
Authors: Bin Jia; Yi Wu; Bing-Zhi Li; Leslie A Mitchell; Hong Liu; Shuo Pan; Juan Wang; Hao-Ran Zhang; Nan Jia; Bo Li; Michael Shen; Ze-Xiong Xie; Duo Liu; Ying-Xiu Cao; Xia Li; Xiao Zhou; Hao Qi; Jef D Boeke; Ying-Jin Yuan Journal: Nat Commun Date: 2018-05-22 Impact factor: 14.919
Authors: Stephan O Adler; Thomas W Spiesser; Friedemann Uschner; Ulrike Münzner; Jens Hahn; Marcus Krantz; Edda Klipp Journal: FEMS Yeast Res Date: 2022-06-30 Impact factor: 2.923