505f Flux and Transcriptome Alterations in Mammalian Glycerol Kinase Disorders

Ganesh Sriram¹, Lola Rahib², Jian-Sen He, Allison Campos, Lilly Parr, James C. Liao³, and Katrina M. Dipple⁴. (1) Human Genetics & Chemical Engineering, University of California, Los Angeles, 695 Charles E. Young Dr. S. #5335, Los Angeles, CA 90095, (2) Bioengineering, University of California, Los Angeles, 695 Charles E. Young Dr. S. #5335, Los Angeles, CA 90095, (3) Chemical and Biomolecular Engineering, University of California, Los Angeles, 5531 Boelter Hall, 420 Westwood Plaza, Los Angeles, CA 90095, (4) Human Genetics & Pediatrics - David Geffen School of Medicine, University of California, Los Angeles, 695 Charles E. Young Dr. S. #5335, Los Angeles, CA 90095

We will present flux and transcriptome alterations due to glycerol kinase (GK) overexpression or deficiency in mammalian cells, to understand the role played by flux and systems dynamics in glycerol kinase deficiency (GKD), an X-linked, single-gene inherited disorder of metabolism.

Glycerol kinase (GK) is an important lipogenic enzyme in mammalian liver, adipose tissue, and other organs. It also performs several activities unrelated to its biochemical function of phosphorylating glycerol [1]. For instance, GK functions as ATP-stimulated translocation protein (ASTP), which enhances the nuclear binding of the activated glucocorticoid-receptor complex, a transcription factor [2]. Studies have also suggested links between GK and improved insulin sensitivity – GK is overexpressed in response to thiazolidinediones [3], a common drug to treat type 2 diabetes, and this overexpression relieves insulin resistance [4]. The hereditary disorder GKD exhibits complexities that are not trivially explained by lack of the biochemical activity of GK. Thus far, there has been no correlation between genotype and phenotype in patients with this disorder. We have previously hypothesized that systems dynamics, including flux through metabolic pathways, can play a significant role in imparting a phenotype that is not easily deduced from the genotype [5]. In this presentation we will report flux, microarray, and network component analysis of tissue cell lines overexpressing GK or that are deficient in GK, to investigate the function of flux and systems dynamics in GKD.

We cultured wild type and GK-overexpressing H4IIE rat hepatoma cells on a mathematically designed mixture of U-¹³C, 1-¹³C and naturally abundant glucose. Gas chromatography-mass spectrometry was used to measure mass isotopomer abundances in protein hydrolysates from the cells. Fluxes were evaluated from the isotopomer data by using a mathematical metabolic pathway model that incorporated isotopomer balancing. The GK-overexpressing cell lines exhibited significantly reduced cell growth and lactate production rates compared to the wild type, while consuming carbon sources at nearly the same rates as the wild type. Unsupervised principal component analysis of these measurements and mass isotopomer abundances revealed that fluxes of carbohydrate metabolism differ between the GK-overexpressing cell lines and the wild type. Flux evaluation by comprehensive isotopomer balancing and global optimization revealed that the GK-overexpressing cell lines exhibited a substantially higher flux through the pentose phosphate pathway. This is likely due to increased NADPH requirement in the cytosol, and may be mediated by glycerol kinase or its network partners.

Furthermore, we will report a microarray analysis of the wild type and GK-overexpressing cell lines, followed by a network component analysis (NCA) of the microarray data. This is expected to reveal the transcription factor activities altered due to GK overexpression, and together with the flux results, would shed light on network interactions involving GK and the role of systems dynamics in GKD.

The results in this presentation will highlight the multifaceted role of glycerol kinase, and such investigations can be valuable toward dissecting the biochemistry and elucidating the pathology of this and other metabolic disorders.

Keywords: Glycerol kinase, glycerol kinase deficiency, microarray, network component analysis, metabolic flux, pentose phosphate pathway, isotopomer, moonlighting enzyme.

References

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