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Typically, C flux analysis relies on assumptions of both metabolic and isotopic steady state. If metabolism is steady but isotope labeling is not allowed to fully equilibrate, isotopically nonstationary metabolic flux analysis (INST-MFA) can be used to estimate fluxes. This requires solution of differential equations that describe the time-dependent labeling of network metabolites, while iteratively adjusting the flux and pool size parameters to match the transient labeling measurements. INST-MFA holds a number of unique advantages over approaches that rely solely upon steady-state isotope enrichments. First, INST-MFA can be applied to estimate fluxes in autotrophic systems, which consume only single-carbon substrates. Second, INST-MFA is ideally suited to systems that label slowly due to the presence of large intermediate pools or pathway bottlenecks. Finally, INST-MFA provides increased measurement sensitivity to estimate reversible exchange fluxes and metabolite pool sizes, which represents a potential framework for integrating metabolomic analysis with C flux analysis. This review highlights the unique capabilities of INST-MFA, describes newly available software tools that automate INST-MFA calculations, presents several practical examples of recent INST-MFA applications, and discusses the technical challenges that lie ahead.
Copyright © 2018 Elsevier Ltd. All rights reserved.
Pathologies including diabetes and conditions such as exercise place an unusual demand on liver energy metabolism, and this demand induces a state of energy discharge. Hepatic AMP-activated protein kinase (AMPK) has been proposed to inhibit anabolic processes such as gluconeogenesis in response to cellular energy stress. However, both AMPK activation and glucose release from the liver are increased during exercise. Here, we sought to test the role of hepatic AMPK in the regulation of glucose-producing and citric acid cycle-related fluxes during an acute bout of muscular work. We used H/C metabolic flux analysis to quantify intermediary metabolism fluxes in both sedentary and treadmill-running mice. Additionally, liver-specific AMPK α1 and α2 subunit KO and WT mice were utilized. Exercise caused an increase in endogenous glucose production, glycogenolysis, and gluconeogenesis from phosphoenolpyruvate. Citric acid cycle fluxes, pyruvate cycling, anaplerosis, and cataplerosis were also elevated during this exercise. Sedentary nutrient fluxes in the postabsorptive state were comparable for the WT and KO mice. However, the increment in the endogenous rate of glucose appearance during exercise was blunted in the KO mice because of a diminished glycogenolytic flux. This lower rate of glycogenolysis was associated with lower hepatic glycogen content before the onset of exercise and prompted a reduction in arterial glucose during exercise. These results indicate that liver AMPKα1α2 is required for maintaining glucose homeostasis during an acute bout of exercise.
© 2017 by The American Society for Biochemistry and Molecular Biology, Inc.
Photorespiration is a central component of photosynthesis; however to better understand its role it should be viewed in the context of an integrated metabolic network rather than a series of individual reactions that operate independently. Isotopically nonstationary C metabolic flux analysis (INST-MFA), which is based on transient labeling studies at metabolic steady state, offers a comprehensive platform to quantify plant central metabolism. In this chapter, we describe the application of INST-MFA to investigate metabolism in leaves. Leaves are an autotrophic tissue, assimilating CO over a diurnal period implying that the metabolic steady state is limited to less than 12 h and thus requiring an INST-MFA approach. This strategy results in a comprehensive unified description of photorespiration, Calvin cycle, sucrose and starch synthesis, tricarboxylic acid (TCA) cycle, and amino acid biosynthetic fluxes. We present protocols of the experimental aspects for labeling studies: transient CO labeling of leaf tissue, sample quenching and extraction, mass spectrometry (MS) analysis of isotopic labeling data, measurement of sucrose and amino acids in vascular exudates, and provide details on the computational flux estimation using INST-MFA.
Industrial bioprocesses place high demands on the energy metabolism of host cells to meet biosynthetic requirements for maximal protein expression. Identifying metabolic phenotypes that promote high expression is therefore a major goal of the biotech industry. We conducted a series of C flux analysis studies to examine the metabolic response to IgG expression during early stationary phase of CHO cell cultures grown in 3L fed-batch bioreactors. We examined eight clones expressing four different IgGs and compared with three non-expressing host-cell controls. Some clones were genetically manipulated to be apoptosis-resistant by expressing Bcl-2Δ, which correlated with increased IgG production and elevated glucose metabolism. The metabolic phenotypes of the non-expressing, IgG-expressing, and Bcl-2Δ/IgG-expressing clones were fully segregated by hierarchical clustering analysis. Lactate consumption and citric acid cycle fluxes were most strongly associated with specific IgG productivity. These studies indicate that enhanced oxidative metabolism is a characteristic of high-producing CHO cell lines.
Copyright © 2017 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.
The enzyme cytochrome P450 11A1 cleaves the C20-C22 carbon-carbon bond of cholesterol to form pregnenolone, the first 21-carbon precursor of all steroid hormones. Various reaction mechanisms are possible for the carbon-carbon bond cleavage step of P450 11A1, and most current proposals involve the oxoferryl active species, Compound I (FeO(3+)). Compound I can either (i) abstract an O-H hydrogen atom or (ii) be attacked by a nucleophilic hydroxy group of its substrate, 20R,22R-dihydroxycholesterol. The mechanism of this carbon-carbon bond cleavage step was tested using (18)O-labeled molecular oxygen and purified P450 11A1. P450 11A1 was incubated with 20R,22R-dihydroxycholesterol in the presence of molecular oxygen ((18)O2), and coupled assays were used to trap the labile (18)O atoms in the enzymatic products (i.e., isocaproaldehyde and pregnenolone). The resulting products were derivatized and the (18)O content was analyzed by high-resolution mass spectrometry. P450 11A1 showed no incorporation of an (18)O atom into either of its carbon-carbon bond cleavage products, pregnenolone and isocaproaldehyde . The positive control experiments established retention of the carbonyl oxygens in the enzymatic products during the trapping and derivatization processes. These results reveal a mechanism involving an electrophilic Compound I species that reacts with nucleophilic hydroxy groups in the 20R,22R-dihydroxycholesterol intermediate of the P450 11A1 reaction to produce the key steroid pregnenolone.
Cytochrome P450 (P450) reactions can involve C-C bond cleavage, and several of these are critical in steroid and sterol biosynthesis. The mechanisms of P450s 11A1, 17A1, 19A1, and 51A1 have been controversial, in the context of the role of ferric peroxide (FeO2 (-)) versus perferryl (FeO(3+), compound I) chemistry. We reinvestigated the 17α-hydroxyprogesterone and 17α-hydroxypregnenolone 17α,20-lyase reactions of human P450 17A1 and found incorporation of one (18)O atom (from (18)O2) into acetic acid, consonant with proposals for a ferric peroxide mechanism (Akhtar, M., Lee-Robichaud, P., Akhtar, M. E., and Wright, J. N. (1997) J. Steroid Biochem. Mol. Biol. 61, 127-132; Akhtar, M., Wright, J. N., and Lee-Robichaud, P. (2011) J. Steroid Biochem. Mol. Biol. 125, 2-12). However, the reactions were supported by iodosylbenzene (a precursor of the FeO(3+) species) but not by H2O2 We propose three mechanisms that can involve the FeO(3+) entity and that explain the (18)O label in the acetic acid, two involving the intermediacy of an acetyl radical and one a steroid 17,20-dioxetane. P450 17A1 was found to perform 16-hydroxylation reactions on its 17α-hydroxylated products to yield 16,17α-dihydroxypregnenolone and progesterone, suggesting the presence of an active perferryloxo active species of P450 17A1 when its lyase substrate is bound. The 6β-hydroxylation of 16α,17α-dihydroxyprogesterone and the oxidation of both 16α,17α-dihydroxyprogesterone and 16α,17α-dihydroxypregnenolone to 16-hydroxy lyase products were also observed. We provide evidence for the contribution of a compound I mechanism, although contribution of a ferric peroxide pathway in the 17α,20-lyase reaction cannot be excluded.
© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.
Apoptosis signal-regulating kinase 1 (ASK1) is a key sensor kinase in the mitogen-activated protein kinase pathway that transduces cellular responses to oxidants and electrophiles. ASK1 is regulated by a large, dynamic multiprotein signalosome complex, potentially including over 90 reported ASK1-interacting proteins. We employed both shotgun and targeted mass spectrometry assays to catalogue the ASK1 protein-protein interactions in HEK-293 cells treated with the prototypical lipid electrophile 4-hydroxy-2-nonenal (HNE). Using both epitope-tagged overexpression and endogenous expression cell systems, we verified most of the previously reported ASK1 protein-protein interactions and identified 14 proteins that exhibited dynamic shifts in association with ASK1 in response to HNE stress. We used precise stable isotope dilution assays to quantify protein stoichiometry in the ASK signalosome complex and identified ASK2 at a 1:1 stoichiometric ratio with ASK1 and 14-3-3 proteins (YWHAQ, YWHAB, YWHAH, and YWHAE) collectively at a 0.5:1 ratio with ASK1 as the main components. Several other proteins, including ASK3, PARK7, PRDX1, and USP9X were detected with stoichiometries of 0.1:1 or less. These data support an ASK signalosome comprising a multimeric core complex of ASK1, ASK2, and 14-3-3 proteins, which dynamically engages other binding partners needed to mediate diverse stress-response signaling events. This study further demonstrates the value of combining global and targeted MS approaches to interrogate multiprotein complex composition and dynamics.
© 2016 by The American Society for Biochemistry and Molecular Biology, Inc.
The analytical challenges to acquire accurate isotopic data of intracellular metabolic intermediates for stationary, nonstationary, and dynamic metabolic flux analysis (MFA) are numerous. This work presents MID Max, a novel LC-MS/MS workflow, acquisition, and isotopomer deconvolution method for MFA that takes advantage of additional scan types that maximizes the number of mass isotopomer distributions (MIDs) that can be acquired in a given experiment. The analytical method was found to measure the MIDs of 97 metabolites, corresponding to 74 unique metabolite-fragment pairs (32 precursor spectra and 42 product spectra) with accuracy and precision. The compounds measured included metabolic intermediates in central carbohydrate metabolism and cofactors of peripheral metabolism (e.g., ATP). Using only a subset of the acquired MIDs, the method was found to improve the precision of flux estimations and number of resolved exchange fluxes for wild-type E. coli compared to traditional methods and previously published data sets.
Isotope labeling experiments (ILEs) and (13)C flux analysis provide actionable information for metabolic engineers to identify knockout, overexpression, and/or media optimization targets. ILEs have been used in both academic and industrial labs to increase product formation, discover novel metabolic functions in previously uncharacterized organisms, and enhance the metabolic efficiency of host cell factories. This review highlights specific examples of how ILEs have been used in conjunction with enzyme or metabolic engineering to elucidate host cell metabolism and improve product titer, rate, or yield in a directed manner. We discuss recent progress and future opportunities involving the use of ILEs and (13)C flux analysis to characterize non-model host organisms and to identify and subsequently eliminate wasteful byproduct pathways or metabolic bottlenecks.
Copyright © 2015 Elsevier Ltd. All rights reserved.
Mouse models designed to examine hepatic metabolism are critical to diabetes and obesity research. Thus, a microscale method to quantitatively assess hepatic glucose and intermediary metabolism in conscious, unrestrained mice was developed. [(13)C3]propionate, [(2)H2]water, and [6,6-(2)H2]glucose isotopes were delivered intravenously in short- (9 h) and long-term-fasted (19 h) C57BL/6J mice. GC-MS and mass isotopomer distribution (MID) analysis were performed on three 40-μl arterial plasma glucose samples obtained during the euglycemic isotopic steady state. Model-based regression of hepatic glucose and citric acid cycle (CAC)-related fluxes was performed using a comprehensive isotopomer model to track carbon and hydrogen atom transitions through the network and thereby simulate the MIDs of measured fragment ions. Glucose-6-phosphate production from glycogen diminished, and endogenous glucose production was exclusively gluconeogenic with prolonged fasting. Gluconeogenic flux from phosphoenolpyruvate (PEP) remained stable, whereas that from glycerol modestly increased from short- to long-term fasting. CAC flux [i.e., citrate synthase (VCS)] was reduced with long-term fasting. Interestingly, anaplerosis and cataplerosis increased with fast duration; accordingly, pyruvate carboxylation and the conversion of oxaloacetate to PEP were severalfold higher than VCS in long-term fasted mice. This method utilizes state-of-the-art in vivo methodology and comprehensive isotopomer modeling to quantify hepatic glucose and intermediary fluxes during physiological stress in mice. The small plasma requirements permit serial sampling without stress and the affirmation of steady-state glucose kinetics. Furthermore, the approach can accommodate a broad range of modeling assumptions, isotope tracers, and measurement inputs without the need to introduce ad hoc mathematical approximations.
Copyright © 2015 the American Physiological Society.