scholarly journals Comprehensive metabolic modeling of multiple 13C-isotopomer data sets to study metabolism in perfused working hearts

2016 ◽  
Vol 311 (4) ◽  
pp. H881-H891 ◽  
Author(s):  
Scott B. Crown ◽  
Joanne K. Kelleher ◽  
Rosanne Rouf ◽  
Deborah M. Muoio ◽  
Maciek R. Antoniewicz
Keyword(s):  
Network Model ◽  
Metabolic Flux ◽  
Parameter Determination ◽  
Algebraic Equations ◽  
Acetyl Coa ◽  
Energy Substrate ◽  
Substrate Metabolism ◽  
Metabolic Fluxes ◽  
Heart Perfusion ◽  
Tracer Experiments

In many forms of cardiomyopathy, alterations in energy substrate metabolism play a key role in disease pathogenesis. Stable isotope tracing in rodent heart perfusion systems can be used to determine cardiac metabolic fluxes, namely those relative fluxes that contribute to pyruvate, the acetyl-CoA pool, and pyruvate anaplerosis, which are critical to cardiac homeostasis. Methods have previously been developed to interrogate these relative fluxes using isotopomer enrichments of measured metabolites and algebraic equations to determine a predefined metabolic flux model. However, this approach is exquisitely sensitive to measurement error, thus precluding accurate relative flux parameter determination. In this study, we applied a novel mathematical approach to determine relative cardiac metabolic fluxes using 13C-metabolic flux analysis (13C-MFA) aided by multiple tracer experiments and integrated data analysis. Using 13C-MFA, we validated a metabolic network model to explain myocardial energy substrate metabolism. Four different 13C-labeled substrates were queried (i.e., glucose, lactate, pyruvate, and oleate) based on a previously published study. We integrated the analysis of the complete set of isotopomer data gathered from these mouse heart perfusion experiments into a single comprehensive network model that delineates substrate contributions to both pyruvate and acetyl-CoA pools at a greater resolution than that offered by traditional methods using algebraic equations. To our knowledge, this is the first rigorous application of 13C-MFA to interrogate data from multiple tracer experiments in the perfused heart. We anticipate that this approach can be used widely to study energy substrate metabolism in this and other similar biological systems.

scholarly journals Ivabradine reduces heart rate while preserving metabolic fluxes and energy status of healthy normoxic working hearts

2011 ◽  
Vol 300 (3) ◽  
pp. H845-H852 ◽  
Author(s):  
Benjamin Lauzier ◽  
Fanny Vaillant ◽  
Roselle Gélinas ◽  
Bertrand Bouchard ◽  
Roger Brownsey ◽  
...  
Keyword(s):  
Heart Rate ◽  
Stroke Volume ◽  
Ex Vivo ◽  
High Energy ◽  
Mouse Heart ◽  
Atrial Pacing ◽  
High Energy Phosphates ◽  
Energy Substrate ◽  
Substrate Metabolism ◽  
Metabolic Fluxes

Heart rate reduction (HRR) is an important target in the management of patients with chronic stable angina. Most available drugs for HRR, such as β-blockers, have adverse effects, including on cardiac energy substrate metabolism, a well-recognized determinant of cardiac homeostasis. This study aimed at 1) testing whether HRR by ivabradine (IVA) alters substrate metabolism in the healthy normoxic working heart and 2) comparing the effect of IVA with that of the β-blocker metoprolol (METO). This was assessed using our well-established model of ex vivo mouse heart perfusion in the working mode, which enables concomitant evaluation of myocardial contractility and metabolic fluxes using 13C-labeled substrates. Hearts were perfused in the absence (controls; n = 10) or presence of IVA ( n = 10, 3 μM) with or without atrial pacing to abolish HRR in the IVA group. IVA significantly reduced HR (35 ± 5%) and increased stroke volume (39 ± 9%) while maintaining similar cardiac output, contractility, power, and efficiency. Effects of IVA on HR and stroke volume were reversed by atrial pacing. At the metabolic level, IVA did not impact on substrate selection to citrate formation, rates of glycolysis, or tissue levels of high-energy phosphates. In contrast, METO, at concentrations up to 40 μM, decreased markedly cardiac function (flow: 25 ± 6%; stroke volume: 30 ± 10%; contractility: 31 ± 9%) as well as glycolysis (2.9-fold) but marginally affected HR. Collectively, these results demonstrate that IVA selectively reduces HR while preserving energy substrate metabolism of normoxic healthy working mouse hearts perfused ex vivo, a model that mimics to some extent the denervated transplanted heart. Our results provide the impetus for testing selective HRR by IVA on cardiac substrate metabolism in pathological models.

scholarly journals Fine tuning the glycolytic flux ratio of EP-bifido pathway for mevalonate production by enhancing glucose-6-phosphate dehydrogenase (Zwf) and CRISPRi suppressing 6-phosphofructose kinase (PfkA) in Escherichia coli

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Ying Li ◽  
He Xian ◽  
Ya Xu ◽  
Yuan Zhu ◽  
Zhijie Sun ◽  
...  
Keyword(s):  
Pentose Phosphate Pathway ◽  
Conversion Rate ◽  
Metabolic Flux ◽  
Flux Ratio ◽  
Reducing Power ◽  
Pentose Phosphate ◽  
Fine Tuning ◽  
High Yield ◽  
Glycolytic Flux ◽  
Acetyl Coa

Abstract Background Natural glycolysis encounters the decarboxylation of glucose partial oxidation product pyruvate into acetyl-CoA, where one-third of the carbon is lost at CO2. We previously constructed a carbon saving pathway, EP-bifido pathway by combining Embden-Meyerhof-Parnas Pathway, Pentose Phosphate Pathway and “bifid shunt”, to generate high yield acetyl-CoA from glucose. However, the carbon conversion rate and reducing power of this pathway was not optimal, the flux ratio of EMP pathway and pentose phosphate pathway (PPP) needs to be precisely and dynamically adjusted to improve the production of mevalonate (MVA). Result Here, we finely tuned the glycolytic flux ratio in two ways. First, we enhanced PPP flux for NADPH supply by replacing the promoter of zwf on the genome with a set of different strength promoters. Compared with the previous EP-bifido strains, the zwf-modified strains showed obvious differences in NADPH, NADH, and ATP synthesis levels. Among them, strain BP10BF accumulated 11.2 g/L of MVA after 72 h of fermentation and the molar conversion rate from glucose reached 62.2%. Second, pfkA was finely down-regulated by the clustered regularly interspaced short palindromic repeats interference (CRISPRi) system. The MVA yield of the regulated strain BiB1F was 8.53 g/L, and the conversion rate from glucose reached 68.7%. Conclusion This is the highest MVA conversion rate reported in shaken flask fermentation. The CRISPRi and promoter fine-tuning provided an effective strategy for metabolic flux redistribution in many metabolic pathways and promotes the chemicals production.

scholarly journals Regulation of Energy Substrate Metabolism in Endurance Exercise

2021 ◽  
Vol 18 (9) ◽  
pp. 4963
Author(s):  
Abdullah F. Alghannam ◽  
Mazen M. Ghaith ◽  
Maha H. Alhussain
Keyword(s):  
Fatty Acids ◽  
Exercise Intensity ◽  
Fat Metabolism ◽  
Glycogen Storage ◽  
Regulatory Mechanisms ◽  
Critical Importance ◽  
Energy Substrate ◽  
Substrate Metabolism ◽  
Atp Turnover ◽  
Energy Demands

The human body requires energy to function. Adenosine triphosphate (ATP) is the cellular currency for energy-requiring processes including mechanical work (i.e., exercise). ATP used by the cells is ultimately derived from the catabolism of energy substrate molecules—carbohydrates, fat, and protein. In prolonged moderate to high-intensity exercise, there is a delicate interplay between carbohydrate and fat metabolism, and this bioenergetic process is tightly regulated by numerous physiological, nutritional, and environmental factors such as exercise intensity and duration, body mass and feeding state. Carbohydrate metabolism is of critical importance during prolonged endurance-type exercise, reflecting the physiological need to regulate glucose homeostasis, assuring optimal glycogen storage, proper muscle fuelling, and delaying the onset of fatigue. Fat metabolism represents a sustainable source of energy to meet energy demands and preserve the ‘limited’ carbohydrate stores. Coordinated neural, hormonal and circulatory events occur during prolonged endurance-type exercise, facilitating the delivery of fatty acids from adipose tissue to the working muscle for oxidation. However, with increasing exercise intensity, fat oxidation declines and is unable to supply ATP at the rate of the exercise demand. Protein is considered a subsidiary source of energy supporting carbohydrates and fat metabolism, contributing to approximately 10% of total ATP turnover during prolonged endurance-type exercise. In this review we present an overview of substrate metabolism during prolonged endurance-type exercise and the regulatory mechanisms involved in ATP turnover to meet the energetic demands of exercise.

scholarly journals Neuromuscular Electrical Stimulation Improves Energy Substrate Metabolism and Survival in Mice With Acute Endotoxic Shock

Shock ◽  
2020 ◽  
Vol 53 (2) ◽  
pp. 236-241
Author(s):  
Takayuki Irahara ◽  
Norio Sato ◽  
Kosuke Otake ◽  
Satoru Murata ◽  
Kazuo Inoue ◽  
...  
Keyword(s):  
Electrical Stimulation ◽  
Endotoxic Shock ◽  
Neuromuscular Electrical Stimulation ◽  
Energy Substrate ◽  
Substrate Metabolism

scholarly journals Association of the malate dehydrogenase-citrate synthase metabolon is modulated by intermediates of the Krebs tricarboxylic acid cycle

2021 ◽  
Author(s):  
Joy Omini ◽  
Izabela Wojciechowska ◽  
Aleksandra Skirycz ◽  
Hideaki Moriyama ◽  
Toshihiro Obata
Keyword(s):  
Malate Dehydrogenase ◽  
Metabolic Flux ◽  
Citrate Synthase ◽  
Tricarboxylic Acid Cycle ◽  
Feedback Regulation ◽  
Dynamic Structure ◽  
Tca Cycle ◽  
Tricarboxylic Acid ◽  
Enzyme Complex ◽  
Acetyl Coa

Mitochondrial malate dehydrogenase (MDH)-citrate synthase (CS) multi-enzyme complex is a part of the Krebs tricarboxylic acid (TCA) cycle 'metabolon' which is enzyme machinery catalyzing sequential reactions without diffusion of reaction intermediates into a bulk matrix. This complex is assumed to be a dynamic structure involved in the regulation of the cycle by enhancing metabolic flux. Microscale Thermophoresis analysis of the porcine heart MDH-CS complex revealed that substrates of the MDH and CS reactions, NAD+ and acetyl-CoA, enhance complex association while products of the reactions, NADH and citrate, weaken the affinity of the complex. Oxaloacetate enhanced the interaction only when it was presented together with acetyl-CoA. Structural modeling using published CS structures suggested that the binding of these substrates can stabilize the closed format of CS which favors the MDH-CS association. Two other TCA cycle intermediates, ATP, and low pH also enhanced the association of the complex. These results suggest that dynamic formation of the MDH-CS multi-enzyme complex is modulated by metabolic factors responding to respiratory metabolism, and it may function in the feedback regulation of the cycle and adjacent metabolic pathways.

scholarly journals Coarse-grained modeling of mitochondrial metabolism enables subcellular flux inference from fluorescence lifetime imaging microscopy

2020 ◽  
Author(s):  
Xingbo Yang ◽  
Daniel J. Needleman
Keyword(s):  
Fluorescence Lifetime ◽  
Metabolic Flux ◽  
Living Cells ◽  
Coarse Grained ◽  
Fluorescence Lifetime Imaging Microscopy ◽  
Fluorescence Lifetime Imaging ◽  
Lifetime Imaging ◽  
Metabolic Fluxes ◽  
Subcellular Resolution

AbstractMitochondria are central to metabolism and their dysfunctions are associated with many diseases1–9. Metabolic flux, the rate of turnover of molecules through a metabolic pathway, is one of the most important quantities in metabolism, but it remains a challenge to measure spatiotemporal variations in mitochondrial metabolic fluxes in living cells. Fluorescence lifetime imaging microscopy (FLIM) of NADH is a label-free technique that is widely used to characterize the metabolic state of mitochondria in vivo10–18. However, the utility of this technique has been limited by the inability to relate FLIM measurement to the underlying metabolic activities in mitochondria. Here we show that, if properly interpreted, FLIM of NADH can be used to quantitatively measure the flux through a major mitochondrial metabolic pathway, the electron transport chain (ETC), in vivo with subcellular resolution. This result is based on the use of a coarse-grained NADH redox model, which we test in mouse oocytes subject to a wide variety of perturbations by comparing predicted fluxes to direct biochemical measurements and by self-consistency criterion. Using this method, we discovered a subcellular spatial gradient of mitochondrial metabolic flux in mouse oocytes. We showed that this subcellular variation in mitochondrial flux correlates with a corresponding subcellular variation in mitochondrial membrane potential. The developed model, and the resulting procedure for analyzing FLIM of NADH, are valid under nearly all circumstances of biological interest. Thus, this approach is a general procedure to measure metabolic fluxes dynamically in living cells, with subcellular resolution.

scholarly journals Physicochemical and metabolic constraints for thermodynamics-based stoichiometric modelling under mesophilic growth conditions

2020 ◽  
Author(s):  
Claudio Tomi-Andrino ◽  
Rupert Norman ◽  
Thomas Millat ◽  
Philippe Soucaille ◽  
Klaus Winzer ◽  
...  
Keyword(s):  
Experimental Data ◽  
Metabolic Flux Analysis ◽  
In Silico ◽  
Physicochemical Parameters ◽  
Metabolic Flux ◽  
Living Systems ◽  
Flux Analysis ◽  
Flux Balance ◽  
Metabolic Fluxes ◽  
Balance Analysis

AbstractMetabolic engineering in the post-genomic era is characterised by the development of new methods for metabolomics and fluxomics, supported by the integration of genetic engineering tools and mathematical modelling. Particularly, constraint-based stoichiometric models have been widely studied: (i) flux balance analysis (FBA) (in silico), and (ii) metabolic flux analysis (MFA) (in vivo). Recent studies have enabled the incorporation of thermodynamics and metabolomics data to improve the predictive capabilities of these approaches. However, an in-depth comparison and evaluation of these methods is lacking. This study presents a thorough analysis of two different in silico methods tested against experimental data (metabolomics and 13C-MFA) for the mesophile Escherichia coli. In particular, a modified version of the recently published matTFA toolbox was created, providing a broader range of physicochemical parameters. Validating against experimental data allowed the determination of the best physicochemical parameters to perform the TFA (Thermodynamics-based Flux Analysis). An analysis of flux pattern changes in the central carbon metabolism between 13C-MFA and TFA highlighted the limited capabilities of both approaches for elucidating the anaplerotic fluxes. In addition, a method based on centrality measures was suggested to identify important metabolites that (if quantified) would allow to further constrain the TFA. Finally, this study emphasised the need for standardisation in the fluxomics community: novel approaches are frequently released but a thorough comparison with currently accepted methods is not always performed.Author summaryBiotechnology has benefitted from the development of high throughput methods characterising living systems at different levels (e.g. concerning genes or proteins), allowing the industrial production of chemical commodities. Recently, focus has been placed on determining reaction rates (or metabolic fluxes) in the metabolic network of certain microorganisms, in order to identify bottlenecks hindering their exploitation. Two main approaches are commonly used, termed metabolic flux analysis (MFA) and flux balance analysis (FBA), based on measuring and estimating fluxes, respectively. While the influence of thermodynamics in living systems was accepted several decades ago, its application to study biochemical networks has only recently been enabled. In this sense, a multitude of different approaches constraining well-established modelling methods with thermodynamics has been suggested. However, physicochemical parameters are generally not properly adjusted to the experimental conditions, which might affect their predictive capabilities. In this study, we have explored the reliability of currently available tools by investigating the impact of varying said parameters in the simulation of metabolic fluxes and metabolite concentration values. Additionally, our in-depth analysis allowed us to highlight limitations and potential solutions that should be considered in future studies.

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