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![Effect of glutamine depletion/repletion on the glycolytic flux indicator ratios. The average experimental glycolytic flux indicator was normalized by a 12-h averaged control glycolytic flux indicator to yield the ratio. The hexose isomerase indicator assay used [2-3 H]glucose. The triose-phosphate isomerase indicator assay used [3-3 H]glucose. *Time points where the average experimental value was significantly different from the average control value (n 3, P 0.05).](profile/R-Raab/publication/9012599/figure/fig1/AS:339770946408461@1458019114589/Effect-of-glutamine-depletion-repletion-on-the-glycolytic-flux-indicator-ratios-The.png)
Effect of glutamine depletion/repletion on the glycolytic flux indicator ratios. The average experimental glycolytic flux indicator was normalized by a 12-h averaged control glycolytic flux indicator to yield the ratio. The hexose isomerase indicator assay used [2-3 H]glucose. The triose-phosphate isomerase indicator assay used [3-3 H]glucose. *Time points where the average experimental value was significantly different from the average control value (n 3, P 0.05).
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An important objective in postgenomic biology is to link gene expression to function by developing physiological networks that include data from the genomic and functional levels. Here, we develop a model for the analysis of time-dependent changes in metabolites, fluxes, and gene expression in a hepatic model system. The experimental framework chos...
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... alterations during glutamine depletion and reple- tion. The effect of glutamine depletion/repletion on the glyco- lytic flux was examined using 3 (Fig. 1). The glycolytic flux at time 0 was 0.30 0.03 nmol/h per 10 4 cells and did not differ for the two 3 H tracers. This indicates that the flux through triose-phosphate isomerase did not differ from that through hexose phosphate isomerase. This agreement is expected in view of the high glycolytic rate in the absence of significant ...
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... in view of the high glycolytic rate in the absence of significant glucose-6-phosphatase activity reported in Hepa1-6 cells (25). Removal of glutamine from the medium led to a gradual decline in the glycolytic rate to values 50% of the control. Restoring glutamine to the medium returned the rates to near the starting values after a delay of 12 h (Fig. 1), demonstrating a reversible change in flux upon glutamine depletion and ...
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... detected nine correlated genes with a correlation coefficient 0.90 (Fig. 9A). However, 22 anticorrelated genes were detected with a correlation coef- ficient less than or equal to 0.90 (Fig. 9B). Analysis of gene expression data with the autoscaled glutamine input signal found 16 anticorrelated genes with a correlation coefficient less than 0.90 (Fig. 10). Yet, no correlated genes were found with a correlation coefficient greater than 0.90. Finally, the gene expression data were analyzed by a pattern discovery algo- rithm, Teiresias (23). The data set of log2 ratios at time points was converted into a binary data set of positive or negative derivatives between time points. Teiresias ...
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... rithm, Teiresias (23). The data set of log2 ratios at time points was converted into a binary data set of positive or negative derivatives between time points. Teiresias was then used to discover patterns within this binary data set. Twelve genes were found to have the pattern of three positive derivatives followed by three negative derivatives (Fig. 11). Using the The "T 24 h" values reflect the log2 ratio comparing experimental and control cells at the 24-h time point with the glutamine concentration at 0 mM. "T 36 h" values reflect the log2 ratio comparing experimental and control cells at the 36-h time point, 12 h after glutamine repletion to 4 mM. same criteria, Teiresias did not ...
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... of fluxes comparable to those in human and rat hepatoma cell lines have been lacking. The present study demonstrated that mouse Hepa1-6 cells share metabolic flux characteristics with other transformed cell lines with regard to glutamine metabolism. Consistent with previous findings (1,20), glutamine is required for high rates of glycolytic flux (Fig. 1). Glutamine is also a major source of carbon for de novo lipogenesis (Table 1), as found with rat hepatoma cells (10). Thus the Hepa1-6 mouse cell line is well-suited for the investigation of physiological regulatory networks that integrate gene expression and functional ...
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... of the six metabolites correlated with the flux changes (Fig. 5) provides a mechanism for changes in flux as a result of changes in substrate concentration. Although maintenance of glycolytic flux did not require de novo mRNA synthesis, the requirement for mRNA synthesis to effect the changes in flux during glutamine depletion/repletion clearly Fig. 10. Gene expression profiles anticorrelated to auto- scaled glutamine concentration with a correlation coeffi- cient less than or equal to 0.90. Fig. 11. Gene expression profiles discovered by Teiresias to have a pattern of 3 positive derivatives followed by 3 negative ...
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... Although maintenance of glycolytic flux did not require de novo mRNA synthesis, the requirement for mRNA synthesis to effect the changes in flux during glutamine depletion/repletion clearly Fig. 10. Gene expression profiles anticorrelated to auto- scaled glutamine concentration with a correlation coeffi- cient less than or equal to 0.90. Fig. 11. Gene expression profiles discovered by Teiresias to have a pattern of 3 positive derivatives followed by 3 negative ...
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... in gene expression monitored with DNA microarrays indicated activation of gene expression accompanied the decline in metabolic fluxes observed upon glutamine depletion (Figs. 9 and 10). This finding brings into focus the fact that increased transcription of some genes was required to allow cells to respond to the new metabolic conditions created by removing glutamine from the medium. Activation of gene expression in the absence of glutamine was also supported by the finding that actinomycin D prevented, at least ...
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Citations
... [13] The prominent utilization of glucose by tumor cells to generate energy through aerobic glycolysis, as opposed to mitochondrial oxidative phosphorylation (OXPHOS), is the well-described "Warburg effect" which is responsible for rapid adenosine triphosphate (ATP) generation as well as adaption to the hypoxic tumor environment. [26,27] However, the impact of glutamine deprivation stress on glycolysis is controversial, with both reduction [28,29] and enhancement of glycolytic flux reported, the latter resulting from increases in the expression of glycolytic enzymes. [30] Nonetheless, it is clear that glutamine starvation effects may vary among tumor types, oncogene or tumor suppressor status, epigenetic alterations, and stages of tumor development and tumor environment. ...
... [53] Indeed, increased glycolysis itself is instrumental in establishing TME characteristics such as acidosis which results from the export of its end-products lactate and H + ions. It is known that aerobic glycolysis is impacted by glutamine deprivation stress [28,29] where enhanced glycolytic flux can increase the expression of glycolytic enzymes. [30] However, the actions of DDIT3 were not leveled at individual glycolytic enzymes, rather indirectly through transcriptional inhibition of the negative glycolytic pathway regulator, TIGAR. ...
Extracellular glutamine represents an important energy source for many cancer cells and its metabolism is intimately involved in maintaining redox homeostasis. The heightened metabolic activity within tumor tissues can result in glutamine deficiency, necessitating metabolic reprogramming responses. Here, dual mechanisms involving the stress‐responsive transcription factor DDIT3 (DNA damage induced transcript 3) that establishes an interrelationship between glycolysis and mitochondrial respiration are revealed. DDIT3 is induced during glutamine deprivation to promote glycolysis and adenosine triphosphate production via suppression of the negative glycolytic regulator TIGAR. In concert, a proportion of the DDIT3 pool translocates to the mitochondria and suppresses oxidative phosphorylation through LONP1‐mediated down‐regulation of COQ9 and COX4. This in turn dampens the sustained levels of reactive oxygen species that follow glutamine withdrawal. Together these mechanisms constitute an adaptive survival mechanism permitting tumor cells to survive metabolic stress induced by glutamine starvation. Glutamine shortages within the tumor microenvironment necessitate adaptive survival mechanisms in cancer cells. Activation of the transcription factor DNA damage induced transcript 3 under prolonged glutamine deficiency serves to balance cellular adenosine triphosphate energy production and enable cell survival by upregulating glycolysis via transcriptional effects while also dampening oxidative phosphorylation through direct interactions with mitochondrial respiratory chain components.
... Most certainly, neoplastic cells with a hypoxia-like metabolic phenotype or with ETC defects primarily utilize glutamine to produce AcCoA from RC of α-KG [10][11]. Notably, an aberrant increase in RC of glutamine-derived αKG for de novo lipogenesis was observed in hepatoma cells [8,[41][42] and conferred resistance to sorafenib, which was significantly associated with worse disease outcome [39]. Therefore, it is of utmost importance to investigate the oncogenic molecules involved in ...
Background & aims:
Mitochondrial dysfunction and subsequent metabolic deregulation are commonly observed in cancers including hepatocellular carcinoma (HCC). When mitochondrial function is impaired, reductive glutamine metabolism is a major cellular carbon source for de novo lipogenesis to support cancer cell growth. The underlying regulators of reductively metabolized glutamine in mitochondrial dysfunction are not completely understood in tumorigenesis including in HCC.
Methods:
We systematically investigated the role of oxoglutarate dehydrogenase-like (OGDHL), one of the rate-limiting components of the key mitochondrial multi-enzyme OGDH complex (OGDHC), in the regulation of lipid metabolism in hepatoma cells and explored the underlying molecular mechanisms.
Results:
Lower expression of OGDHL was associated with advanced tumor stage, significantly worse survival and more frequent tumor recurrence in three independent cohorts totaling 681 postoperative HCC patients. Promoter hypermethylation and DNA copy deletion of OGDHL were independently correlated with reduced OGDHL expression in HCC specimens. Additionally, OGDHL overexpression significantly inhibited the growth of hepatoma cells as mouse xenografts while knockdown of OGDHL promoted proliferation in hepatoma cells. Mechanistically, OGDHL downregulation upregulated the α-ketoglutarate (αKG):citrate ratio by reducing OGDHC activity, which subsequently drove reductive carboxylation (RC) of glutamine-derived αKG for lipogenesis via retrograde TCA cycling in hepatoma cells. Notably, silencing of OGDHL activated the mTORC1 signaling pathway in an α-KG-dependent manner, which in turn transcriptionally induced expression of SCD1 and FASN, thus, enhancing de novo lipogenesis. Meanwhile, metabolic reprogramming in OGDHL-negative hepatoma cells provided an abundant supply of NADPH and GSH to support the cellular antioxidant system. The reduction of reductive glutamine metabolism through OGDHL overexpression or through use of glutaminase inhibitors sensitized tumor cells to sorafenib, a molecular-targeted therapy for HCC.
Conclusion:
Our findings established that silencing of OGDHL contributed to HCC development and survival by regulating glutamine metabolic pathways, and suggest OGDHL as a promising prognostic biomarker and therapeutic target for HCC.
... Recently, the coordination between cellular levels of glutamine metabolism and glycolysis was reported. For example, elevated glutamine levels support cell growth by stimulating aerobic glycolysis 31 , but depletion of glutamine levels in the medium significantly reduces the glycolytic flux 24,32 . In support of this, metabolomic analysis using PDAC patient samples indicate that glycolysis intermediates, including Glycerol-3-Phosphate, Glucose-6-Phosphate, and Fructose-6-Phosphate are significantly decreased in tumors compared with normal tissue 10 . ...
Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal human cancers. It thrives in a nutrient-poor environment; however, the mechanisms by which PDAC cells undergo metabolic reprogramming to adapt to metabolic stress are still poorly understood. Here, we show that microRNA-135 is significantly increased in PDAC patient samples compared to adjacent normal tissue. Mechanistically, miR-135 accumulates specifically in response to glutamine deprivation and requires ROS-dependent activation of mutant p53, which directly promotes miR-135 expression. Functionally, we found miR-135 targets phosphofructokinase-1 (PFK1) and inhibits aerobic glycolysis, thereby promoting the utilization of glucose to support the tricarboxylic acid (TCA) cycle. Consistently, miR-135 silencing sensitizes PDAC cells to glutamine deprivation and represses tumor growth in vivo. Together, these results identify a mechanism used by PDAC cells to survive the nutrient-poor tumor microenvironment, and also provide insight regarding the role of mutant p53 and miRNA in pancreatic cancer cell adaptation to metabolic stresses.
... For example, a recent report showed that, in highly glycolytic cells, the majority of TCA cycle carbons is derived from glutamine, but, when aerobic glycolysis was reduced, less glutamine contributed to TCA cycle intermediates, which decreased glutamine dependence (Le et al. 2012). Of particular interest, glutamine starvation reduces glycolytic flux; however, the molecular mechanisms mediating this remain unknown (Wong et al. 2004). Thus, inhibition of glycolytic flux may decrease glutamine dependence and contribute to cell survival under low-glutamine conditions. ...
... Intriguingly, it has been shown that high glutamine concentrations and glutamine-dependent anaplerosis led to increased glucose uptake and aerobic glycolysis (Kaadige et al. 2009). Moreover, glutamine depletion/repletion studies found that aerobic glycolysis is decreased in response to glutamine starvation (Wong et al. 2004). Our data are in agreement with these reports in that glutamine availability and aerobic glycolysis are tightly correlated, and a disconnect results in loss of cell viability. ...
Glutamine is an essential nutrient for cancer cell survival and proliferation. Enhanced utilization of glutamine often depletes its local supply, yet how cancer cells adapt to low glutamine conditions is largely unknown. Here, we report that IκB kinase β (IKKβ) is activated upon glutamine deprivation and is required for cell survival independently of NF-κB transcription. We demonstrate that IKKβ directly interacts with and phosphorylates 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase isoform 3 (PFKFB3), a major driver of aerobic glycolysis, at Ser269 upon glutamine deprivation to inhibit its activity, thereby down-regulating aerobic glycolysis when glutamine levels are low. Thus, due to lack of inhibition of PFKFB3, IKKβ-deficient cells exhibit elevated aerobic glycolysis and lactate production, leading to less glucose carbons contributing to tricarboxylic acid (TCA) cycle intermediates and the pentose phosphate pathway, which results in increased glutamine dependence for both TCA cycle intermediates and reactive oxygen species suppression. Therefore, coinhibition of IKKβ and glutamine metabolism results in dramatic synergistic killing of cancer cells both in vitro and in vivo. In all, our results uncover a previously unidentified role of IKKβ in regulating glycolysis, sensing low-glutamine-induced metabolic stress, and promoting cellular adaptation to nutrient availability.
... ISA uses equations for the probability of the appearance of each isotopomer based on test values for D and g (time). These probabilities are compared with the fractional abundance determined for each malonyl-CoA and acetyl-Spd isotopomer to obtain the best-fit solution (Kharroubi et al. 1992;Wong et al. 2004). The isotopomers of acetyl-CoA, acetylspermidine and malonyl-CoA were extracted from the primary cells as previously described (Kee et al. 2004) and subjected to mass spectrometry analysis to observe the fate of the 13 C atoms. ...
... SSAT-ko, SSAT-wt and SSAT-tg). ISA (D) value calculations using ISA model equations and Metran software (Kharroubi et al. 1992;Wong et al. 2004) indicated that glucose from the adipose tissue of SSAT-ko, SSAT-wt and SSAT-tg mice provided 15, 32 and 49 % of the acetyl-CoA for acetyl-Spd and malonyl-CoA, respectively. We also used the ISA model to determine the g (6 h), and these results indicated that 1, 16 and 90 % of the acetyl-Spd was synthesized de novo across the genotype gradient. ...
The continued rise in obesity despite public education, awareness and policies indicates the need for mechanism-based therapeutic approaches to help control the disease. Our data, in conjunction with other studies, suggest an unexpected role for the polyamine catabolic enzyme spermidine/spermine-N1-acetyltransferase (SSAT) in fat homeostasis. Our previous studies showed that deletion of SSAT greatly exaggerates weight gain and that the transgenic overexpression suppresses weight gain in mice on a high-fat diet. This discovery is substantial but the underlying molecular linkages are only vaguely understood. Here, we used a comprehensive systems biology approach, on white adipose tissue (WAT), to discover that the partition of acetyl-CoA towards polyamine catabolism alters glucose homeostasis and hence, fat accumulation. Comparative proteomics and antibody-based expression studies of WAT in SSAT knockout, wild type and transgenic mice identified nine proteins with an increasing gradient across the genotypes, all of which correlate with acetyl-CoA consumption in polyamine acetylation. Adipose-specific SSAT knockout mice and global SSAT knockout mice on a high-fat diet exhibited similar growth curves and proteomic patterns in their WAT, confirming that attenuated consumption of acetyl-CoA in acetylation of polyamines in adipose tissue drives the obese phenotype of these mice. Analysis of protein expression indicated that the identified changes in the levels of proteins regulating acetyl-CoA consumption occur via the AMP-activated protein kinase pathway. Together, our data suggest that differential expression of SSAT markedly alters acetyl-CoA levels, which in turn trigger a global shift in glucose metabolism in adipose tissue, thus affecting the accumulation of body fat.
... Naturally, since transcription measurements have become increasingly easy during the last decades, relating an enzyme's transcription change with the corresponding flux change has become an common method (e.g. [99], [55], [35]). Transcription -flux correlation may be a satisfactory, and for genome-scale metabolic studies it is often the only (easily) available, experimentally accessible regulatory level for flux redistribution. ...
Ziel dieser Arbeit war es, den zentralen Kohlenstoffwechsel mit besonderem Fokus auf Regulation zu untersuchen, insbesondere durch die Auftrennung von zwei Regulationsebenen: metabolische Regulation, assoziiert mit direkten Wech- selwirkungen zwischen Metaboliten und Enzymen, sowie hierarchische Regulation, assoziiert mit Änderungen in Enzymmengenänderungen durch die Regulation von de novo Enzymproduktion. Unsere Untersuchungen basieren größtenteils auf drei Datensätzen aus glukoselimitierten Chemostatkulturen von S. cerevisiae. Im Kap. 2 wurden Extrazelluläre Bedingungen im Makroskopischen unter- sucht. Das wichtigsten Ergebnis dieser the- oretischen Analyse ist die Charakterisierung des Selektionsdruckes in einem Chemostatkultur. Im Kap. 4 wurde eine Analyse auf Systemebene des zentralen Kohlenstoffwech- sels durchgeführt. Unter Verwendung der Metaboliten- und der Flußdaten wurde ein kinetisches Modell konstruiert, welches wesentliche Teile des zentralen Kohlen- stoffwechsels umfaßt. Die meisten kinetischen Ausdrücke und Parameterwerte wurden aus einem bestehenden kinetischen Modells (Teusink-Modell) übernom- men.
... Glutamine starvation triggers a complex network of transcription factors including ATFs and C/EBP factors, and such response might be cell line-or species-dependent (See [34] for review). Indeed, our further analysis of another set of DNA microarray data [35] suggests that glutamine starvation does not cause downregulation of Myc target genes in mouse hepatoma cells (data not shown). However, for this specific B-lymphoma cell line studied by Peng et al. [29], the suppression of the MYC pathway is strongly supported by gene set overlaps and raw DNA microarray data analysis. ...
Cells must respond to various perturbations using their limited available gene repertoires. In order to study how cells coordinate various responses, we conducted a comprehensive comparison of 1,186 gene expression signatures (gene lists) associated with various genetic and chemical perturbations.
We identified 7,419 statistically significant overlaps between various published gene lists. Most (80%) of the overlaps can be represented by a highly connected network, a "molecular signature map," that highlights the correlation of various expression signatures. By dissecting this network, we identified sub-networks that define clusters of gene sets related to common biological processes (cell cycle, immune response, etc). Examination of these sub-networks has confirmed relationships among various pathways and also generated new hypotheses. For example, our result suggests that glutamine deficiency might suppress cellular growth by inhibiting the MYC pathway. Interestingly, we also observed 1,369 significant overlaps between a set of genes upregulated by factor X and a set of genes downregulated by factor Y, suggesting a repressive interaction between X and Y factors.
Our results suggest that molecular-level responses to diverse chemical and genetic perturbations are heavily interconnected in a modular fashion. Also, shared molecular pathways can be identified by comparing newly defined gene expression signatures with databases of previously published gene expression signatures.
... The next step involves estimation of intracellular fluxes using metabolic flux analysis (MFA) framework, which relies on steady-state assumptions, stoichiometric and pathway constraints of a metabolic pathway network, and on constrained nonlinear optimization technique. MFA has been used extensively for studying the metabolism of microorganisms5051525354, and has been recently applied to compare different physiological states in mammalian systems555657585960616263. Hiller et al. [64] have recently developed a nontargeted tracer fate detection technique using stable isotope tracers for quantitative detection of labeled metabolites and pathways involved in the metabolism of used tracer. In their approach, authors used lung carcinoma cell line to obtain relative flux magnitudes of each metabolite pool and found increased flux through glutaminolysis pathway using [U-13 C 5 ] labeled glutamine. ...
Metabolomics, a high-throughput global metabolite analysis, is a burgeoning field, and in recent times has shown substantial evidence to support its emerging role in cancer diagnosis, cancer recurrence, and prognosis, as well as its impact in identifying novel cancer biomarkers and developing cancer therapeutics. Newly evolving advances in disease diagnostics and therapy will further facilitate future growth in the field of metabolomics, especially in cancer, where there is a dire need for sensitive and more affordable diagnostic tools and an urgency to develop effective therapies and identify reliable biomarkers to predict accurately the response to a therapy. Here, we review the application of metabolomics in cancer and mitochondrial studies and its role in enabling the understanding of altered metabolism and malignant transformation during cancer growth and metastasis. The recent developments in the area of metabolic flux analysis may help to close the gap between clinical metabolomics research and the development of cancer metabolome. In the era of personalized medicine with more and more patient specific targeted therapies being used, we need reliable, dynamic, faster, and yet sensitive biomarkers both to track the disease and to develop and evolve therapies during the course of treatment. Recent advances in metabolomics along with the novel strategies to analyze, understand, and construct the metabolic pathways opens this window of opportunity in a very cost-effective manner.
... Accelerated aerobic glycolysis is one such correlate of malignant transformation, which was first described more than 80 years ago by Warburg (1956). Despite the dramatic upregulation of glycolysis in many cancer cells (DeBerardinis et al., 2007; Fan et al., 2005 Thornburg et al., 2008; Wong et al., 2004), this process alone is insufficient to provide the necessary precursors for anabolic metabolism; they must be supplied by additional metabolic processes. Several of the Krebs cycle metabolites, citrate, oxaloacetate/aspartate , and a-ketoglutarate/glutamate are respectively precursors for the biosynthesis of fatty acids, nucleic acids, and proteins (Nelson and Cox, 2005), all of which are required for growth. ...
... As some of these metabolites (e.g., oxaloacetate and a-ketoglutarate) are maintained at low cellular concentration, they must be replenished via anaplerosis to sustain both the Krebs cycle and biosynthetic activities . The two principal anaplerotic pathways involve pyruvate carboxylation () and glutaminolysis (DeBerardinis et al., 2008; Mazurek and Eigenbrodt, 2003; Mazurek et al., 2000 Mazurek et al., , 2005 Wong et al., 2004). The relative importance of these two pathways appears to be tissue specific (DeBerardinis et al., 2007; Fan and Lane, 2008; Fan et al., 2009; Portais et al., 1993). ...
Metabolomics provides a readout of the state of metabolism in cells or tissue and their responses to external perturbations. For this reason, the approach has great potential in clinical diagnostics. Clinical metabolomics using stable isotope resolved metabolomics (SIRM) for pathway tracing represents an important new approach to obtaining metabolic parameters in human cancer subjects in situ. Here we provide an overview of the technology development of labeling from cells in culture and mouse models. The high throughput analytical methods NMR and mass spectrometry, especially Fourier transform ion cyclotron resonance, for analyzing the resulting metabolite isotopomers and isotopologues are described with examples of applications in cancer biology. Special technical considerations for clinical applications of metabolomics using stable isotope tracers are described. The whole process from concept to analysis will be exemplified by our on-going study of nonsmall cell lung cancer (NSCLC) metabolomics. This powerful new approach has already provided important new insights into metabolic adaptations in lung cancer cells, including the upregulation of anaplerosis via pyruvate carboxylation in NSCLC.
... Metabolic flux analysis (MFA) provides a framework for the estimation of intracellular metabolic fluxes at steady-state based on stoichiometric constraints of a metabolic pathway network. This technique, which has been extensively used for studying the metabolism of microorganisms (Antoniewicz et al., 2007aAntoniewicz et al., , 2007bStafford et al., 2002;Wong et al., 2004;Young et al., 2008), has been recently applied to characterize and compare different physiological states in mammalian systems (Banta et al., 2004;Chan et al., 2003aChan et al., , 2003bChan et al., , 2003cChan et al., , 2002Ghosh et al., 2006;Lee et al., 2004;Nolan et al., 2006;Vo et al., 2004). For validation of the MFA obtained intracellular metabolite fluxes, tracer based methods that commonly use 13-C labeling is used for quantifying in vivo fluxes (Maier et al., 2008;Yoo et al., 2008). ...
The current state of the art for linear optimization in Flux Balance Analysis has been limited to single objective functions. Since mammalian systems perform various functions, a multiobjective approach is needed when seeking optimal flux distributions in these systems. In most of the available multiobjective optimization methods, there is a lack of understanding of when to use a particular objective, and how to combine and/or prioritize mutually competing objectives to achieve a truly optimal solution. To address these limitations we developed a soft constraints based linear physical programming-based flux balance analysis (LPPFBA) framework to obtain a multiobjective optimal solutions. The developed framework was first applied to compute a set of multiobjective optimal solutions for various pairs of objectives relevant to hepatocyte function (urea secretion, albumin, NADPH, and glutathione syntheses) in bioartificial liver systems. Next, simultaneous analysis of the optimal solutions for three objectives was carried out. Further, this framework was utilized to obtain true optimal conditions to improve the hepatic functions in a simulated bioartificial liver system. The combined quantitative and visualization framework of LPPFBA is applicable to any large-scale metabolic network system, including those derived by genomic analyses.
