Simultaneous tracers and a unified model of positional and mass isotopomers for quantification of metabolic flux in liver

Tracking lipid synthesis using 2H2O and 2H-NMR spectroscopy in black soldier fly (Hermetia illucens) larvae fed with macroalgae

Black soldier fly (Hermetia illucens) larvae are used to upcycle biowaste into insect biomass for animal feed. Previous research on black soldier fly has explored the assimilation of dietary fatty acids (FAs), but endogenous FA synthesis and modification remain comparatively unexplored. This study presents a 1H/2H-NMR methodology for measuring lipid synthesis in black soldier fly larvae using diluted deuterated water (2H2O) as a stable isotopic tracer delivered through the feeding media. This approach was validated by measuring 2H incorporation into the larvae's body water and consequent labelling of FA esterified into triacylglycerols. A 5% 2H enrichment in the body water, adequate to label the FA, is achieved after 24 h in a substrate with 10% 2H2O. A standard feeding trial using an invasive macroalgae was designed to test this method, revealing de novo lipogenesis was lower in larvae fed with macroalgae, probably related to the poor nutritional value of the diet.

Stable Isotope Tracing Analysis in Cancer Research: Advancements and Challenges in Identifying Dysregulated Cancer Metabolism and Treatment Strategies

Metabolic reprogramming is a hallmark of cancer, driving the development of therapies targeting cancer metabolism. Stable isotope tracing has emerged as a widely adopted tool for monitoring cancer metabolism both in vitro and in vivo. Advances in instrumentation and the development of new tracers, metabolite databases, and data analysis tools have expanded the scope of cancer metabolism studies across these scales. In this review, we explore the latest advancements in metabolic analysis, spanning from experimental design in stable isotope-labeling metabolomics to sophisticated data analysis techniques. We highlight successful applications in cancer research, particularly focusing on ongoing clinical trials utilizing stable isotope tracing to characterize disease progression, treatment responses, and potential mechanisms of resistance to anticancer therapies. Furthermore, we outline key challenges and discuss potential strategies to address them, aiming to enhance our understanding of the biochemical basis of cancer metabolism.

Hepatic malonyl-CoA synthesis restrains gluconeogenesis by suppressing fat oxidation, pyruvate carboxylation, and amino acid availability

Acetyl-CoA carboxylase (ACC) promotes prandial liver metabolism by producing malonyl-CoA, a substrate for de novo lipogenesis and an inhibitor of CPT-1-mediated fat oxidation. We report that inhibition of ACC also produces unexpected secondary effects on metabolism. Liver-specific double ACC1/2 knockout (LDKO) or pharmacologic inhibition of ACC increased anaplerosis, tricarboxylic acid (TCA) cycle intermediates, and gluconeogenesis by activating hepatic CPT-1 and pyruvate carboxylase flux in the fed state. Fasting should have marginalized the role of ACC, but LDKO mice maintained elevated TCA cycle intermediates and preserved glycemia during fasting. These effects were accompanied by a compensatory induction of proteolysis and increased amino acid supply for gluconeogenesis, which was offset by increased protein synthesis during feeding. Such adaptations may be related to Nrf2 activity, which was induced by ACC inhibition and correlated with fasting amino acids. The findings reveal unexpected roles for malonyl-CoA synthesis in liver and provide insight into the broader effects of pharmacologic ACC inhibition.

Effects of hepatic mitochondrial pyruvate carrier deficiency on de novo lipogenesis and gluconeogenesis in mice

The liver coordinates the systemic response to nutrient deprivation and availability by producing glucose from gluconeogenesis during fasting and synthesizing lipids via de novo lipogenesis (DNL) when carbohydrates are abundant. Mitochondrial pyruvate metabolism is thought to play important roles in both gluconeogenesis and DNL. We examined the effects of hepatocyte-specific mitochondrial pyruvate carrier (MPC) deletion on the fasting-refeeding response. Rates of DNL during refeeding were impaired by hepatocyte MPC deletion, but this did not reduce intrahepatic lipid content. During fasting, glycerol is converted to glucose by two pathways; a direct cytosolic pathway and an indirect mitochondrial pathway requiring the MPC. Hepatocyte MPC deletion reduced the incorporation of 13C-glycerol into TCA cycle metabolites, but not into new glucose. Furthermore, suppression of glycerol and alanine metabolism did not affect glucose concentrations in fasted hepatocyte-specific MPC-deficient mice, suggesting multiple layers of redundancy in glycemic control in mice.

Endogenous renal adiponectin drives gluconeogenesis through enhancing pyruvate and fatty acid utilization

Adiponectin is a secretory protein, primarily produced in adipocytes. However, low but detectable expression of adiponectin can be observed in cell types beyond adipocytes, particularly in kidney tubular cells, but its local renal role is unknown. We assessed the impact of renal adiponectin by utilizing male inducible kidney tubular cell-specific adiponectin overexpression or knockout mice. Kidney-specific adiponectin overexpression induces a doubling of phosphoenolpyruvate carboxylase expression and enhanced pyruvate-mediated glucose production, tricarboxylic acid cycle intermediates and an upregulation of fatty acid oxidation (FAO). Inhibition of FAO reduces the adiponectin-induced enhancement of glucose production, highlighting the role of FAO in the induction of renal gluconeogenesis. In contrast, mice lacking adiponectin in the kidney exhibit enhanced glucose tolerance, lower utilization and greater accumulation of lipid species. Hence, renal adiponectin is an inducer of gluconeogenesis by driving enhanced local FAO and further underlines the important systemic contribution of renal gluconeogenesis.

Effects of hepatic mitochondrial pyruvate carrier deficiency on de novo lipogenesis and glycerol-mediated gluconeogenesis in mice

The liver coordinates the systemic response to nutrient deprivation and availability by producing glucose from gluconeogenesis during fasting and synthesizing lipids via de novo lipogenesis (DNL) when carbohydrates are abundant. Mitochondrial pyruvate metabolism is thought to play important roles in both gluconeogenesis and DNL. We examined the effects of hepatocyte-specific mitochondrial pyruvate carrier (MPC) deletion on the fasting-refeeding response. Rates of DNL during refeeding were impaired by liver MPC deletion, but this did not reduce intrahepatic lipid content. During fasting, glycerol is converted to glucose by two pathways; a direct cytosolic pathway essentially reversing glycolysis and an indirect mitochondrial pathway requiring the MPC. MPC deletion reduced the incorporation of 13C-glycerol into TCA cycle metabolites but not into newly synthesized glucose. However, suppression of glycerol metabolism did not affect glucose concentrations in fasted hepatocyte-specific MPC-deficient mice. Thus, glucose production by kidney and intestine may compensate for MPC deficiency in hepatocytes.

Hydrogen/deuterium exchange mass spectrometry in the world of small molecules

The combined use of hydrogen/deuterium exchange (HDX) and mass spectrometry (MS), referred to as HDX-MS, is a powerful tool for exploring molecular edifices and has been used for over 60 years. Initially for structural and mechanistic investigation of low-molecular weight organic compounds, then to study protein structure and dynamics, then, the craze to study small molecules by HDX-MS accelerated and has not stopped yet. The purpose of this review is to present its different facets with particular emphasis on recent developments and applications. Reversible H/D exchanges of mobilizable protons as well as stable exchanges of non-labile hydrogen are considered whether they are taking place in solution or in the gas phase, or enzymatically in a biological media. Some fundamental principles are restated, especially for gas-phase processes, and an overview of recent applications, ranging from identification to quantification through the study of metabolic pathways, is given.

A contribution of metabolic engineering to addressing medical problems: Metabolic flux analysis

Metabolic engineering has served as a systematic discipline for industrial biotechnology as it has offered systematic tools and methods for strain development and bioprocess optimization. Because these metabolic engineering tools and methods are concerned with the biological network of a cell with emphasis on metabolic network, they have also been applied to a range of medical problems where better understanding of metabolism has also been perceived to be important. Metabolic flux analysis (MFA) is a unique systematic approach initially developed in the metabolic engineering community, and has proved its usefulness and potential when addressing a range of medical problems. In this regard, this review discusses the contribution of MFA to addressing medical problems. For this, we i) provide overview of the milestones of MFA, ii) define two main branches of MFA, namely constraint-based reconstruction and analysis (COBRA) and isotope-based MFA (iMFA), and iii) present successful examples of their medical applications, including characterizing the metabolism of diseased cells and pathogens, and identifying effective drug targets. Finally, synergistic interactions between metabolic engineering and biomedical sciences are discussed with respect to MFA.

Loss of hepatic phosphoenolpyruvate carboxykinase 1 dysregulates metabolic responses to acute exercise but enhances adaptations to exercise training in mice

Acute exercise increases liver gluconeogenesis to supply glucose to working muscles. Concurrently, elevated liver lipid breakdown fuels the high energetic cost of gluconeogenesis. This functional coupling between liver gluconeogenesis and lipid oxidation has been proposed to underlie the ability of regular exercise to enhance liver mitochondrial oxidative metabolism and decrease liver steatosis in individuals with nonalcoholic fatty liver disease. Herein we tested whether repeated bouts of increased hepatic gluconeogenesis are necessary for exercise training to lower liver lipids. Experiments used diet-induced obese mice lacking hepatic phosphoenolpyruvate carboxykinase 1 (KO) to inhibit gluconeogenesis and wild-type (WT) littermates. 2H/13C metabolic flux analysis quantified glucose and mitochondrial oxidative fluxes in untrained mice at rest and during acute exercise. Circulating and tissue metabolite levels were determined during sedentary conditions, acute exercise, and refeeding postexercise. Mice also underwent 6 wk of treadmill running protocols to define hepatic and extrahepatic adaptations to exercise training. Untrained KO mice were unable to maintain euglycemia during acute exercise resulting from an inability to increase gluconeogenesis. Liver triacylglycerides were elevated after acute exercise and circulating β-hydroxybutyrate was higher during postexercise refeeding in untrained KO mice. In contrast, exercise training prevented liver triacylglyceride accumulation in KO mice. This was accompanied by pronounced increases in indices of skeletal muscle mitochondrial oxidative metabolism in KO mice. Together, these results show that hepatic gluconeogenesis is dispensable for exercise training to reduce liver lipids. This may be due to responses in ketone body metabolism and/or metabolic adaptations in skeletal muscle to exercise.NEW & NOTEWORTHY Exercise training reduces hepatic steatosis partly through enhanced hepatic terminal oxidation. During acute exercise, hepatic gluconeogenesis is elevated to match the heightened rate of muscle glucose uptake and maintain glucose homeostasis. It has been postulated that the hepatic energetic stress induced by elevating gluconeogenesis during acute exercise is a key stimulus underlying the beneficial metabolic responses to exercise training. This study shows that hepatic gluconeogenesis is not necessary for exercise training to lower liver lipids.

Isotope-Assisted Metabolic Flux Analysis: A Powerful Technique to Gain New Insights into the Human Metabolome in Health and Disease

Cell metabolism represents the coordinated changes in genes, proteins, and metabolites that occur in health and disease. The metabolic fluxome, which includes both intracellular and extracellular metabolic reaction rates (fluxes), therefore provides a powerful, integrated description of cellular phenotype. However, intracellular fluxes cannot be directly measured. Instead, flux quantification requires sophisticated mathematical and computational analysis of data from isotope labeling experiments. In this review, we describe isotope-assisted metabolic flux analysis (iMFA), a rigorous computational approach to fluxome quantification that integrates metabolic network models and experimental data to generate quantitative metabolic flux maps. We highlight practical considerations for implementing iMFA in mammalian models, as well as iMFA applications in in vitro and in vivo studies of physiology and disease. Finally, we identify promising new frontiers in iMFA which may enable us to fully unlock the potential of iMFA in biomedical research.

13C metabolic flux analysis: Classification and characterization from the perspective of mathematical modeling and application in physiological research of neural cell

¹³C metabolic flux analysis (¹³C-MFA) has emerged as a forceful tool for quantifying in vivo metabolic pathway activity of different biological systems. This technology plays an important role in understanding intracellular metabolism and revealing patho-physiology mechanism. Recently, it has evolved into a method family with great diversity in experiments, analytics, and mathematics. In this review, we classify and characterize the various branch of ¹³C-MFA from a unified perspective of mathematical modeling. By linking different parts in the model to each step of its workflow, the specific technologies of ¹³C-MFA are put into discussion, including the isotope labeling model (ILM), isotope pattern measuring technique, optimization algorithm and statistical method. Its application in physiological research in neural cell has also been reviewed.

A Flexible Tool to Correct Superimposed Mass Isotopologue Distributions in GC-APCI-MS Flux Experiments

The investigation of metabolic fluxes and metabolite distributions within cells by means of tracer molecules is a valuable tool to unravel the complexity of biological systems. Technological advances in mass spectrometry (MS) technology such as atmospheric pressure chemical ionization (APCI) coupled with high resolution (HR), not only allows for highly sensitive analyses but also broadens the usefulness of tracer-based experiments, as interesting signals can be annotated de novo when not yet present in a compound library. However, several effects in the APCI ion source, i.e., fragmentation and rearrangement, lead to superimposed mass isotopologue distributions (MID) within the mass spectra, which need to be corrected during data evaluation as they will impair enrichment calculation otherwise. Here, we present and evaluate a novel software tool to automatically perform such corrections. We discuss the different effects, explain the implemented algorithm, and show its application on several experimental datasets. This adjustable tool is available as an R package from CRAN.

Using measures of metabolic flux to align screening and clinical development: Avoiding pitfalls to enable translational studies

Screening campaigns, especially those aimed at modulating enzyme activity, often rely on measuring substrate→product conversions. Unfortunately, the presence of endogenous substrates and/or products can limit one's ability to measure conversions. As well, coupled detection systems, often used to facilitate optical readouts, are subject to interference. Stable isotope labeled substrates can overcome background contamination and yield a direct readout of enzyme activity. Not only can isotope kinetic assays enable early screening, but they can also be used to follow hit progression in translational (pre)clinical studies. Herein, we consider a case study surrounding lipid biology to exemplify how metabolic flux analyses can connect stages of drug development, caveats are highlighted to ensure reliable data interpretations. For example, when measuring enzyme activity in early biochemical screening it may be enough to quantify the formation of a labeled product. In contrast, cell-based and in vivo studies must account for variable exposure to a labeled substrate (or precursor) which occurs via tracer dilution and/or isotopic exchange. Strategies are discussed to correct for these complications. We believe that measures of metabolic flux can help connect structure-activity relationships with pharmacodynamic mechanisms of action and determine whether mechanistically differentiated biophysical interactions lead to physiologically relevant outcomes. Adoption of this logic may allow research programs to (i) build a critical bridge between primary screening and (pre)clinical development, (ii) elucidate biology in parallel with screening and (iii) suggest a strategy aimed at in vivo biomarker development.

INCA 2.0: A tool for integrated, dynamic modeling of NMR- and MS-based isotopomer measurements and rigorous metabolic flux analysis

Metabolic flux analysis (MFA) combines experimental measurements and computational modeling to determine biochemical reaction rates in live biological systems. Advancements in analytical instrumentation, such as nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), have facilitated chemical separation and quantification of isotopically enriched metabolites. However, no software packages have been previously described that can integrate isotopomer measurements from both MS and NMR analytical platforms and have the flexibility to estimate metabolic fluxes from either isotopic steady-state or dynamic labeling experiments. By applying physiologically relevant cardiac and hepatic metabolic models to assess NMR isotopomer measurements, we herein test and validate new modeling capabilities of our enhanced flux analysis software tool, INCA 2.0. We demonstrate that INCA 2.0 can simulate and regress steady-state 13C NMR datasets from perfused hearts with an accuracy comparable to other established flux assessment tools. Furthermore, by simulating the infusion of three different 13C acetate tracers, we show that MFA based on dynamic 13C NMR measurements can more precisely resolve cardiac fluxes compared to isotopically steady-state flux analysis. Finally, we show that estimation of hepatic fluxes using combined 13C NMR and MS datasets improves the precision of estimated fluxes by up to 50%. Overall, our results illustrate how the recently added NMR data modeling capabilities of INCA 2.0 can enable entirely new experimental designs that lead to improved flux resolution and can be applied to a wide range of biological systems and measurement time courses.

Ins and Outs of the TCA Cycle: The Central Role of Anaplerosis

The reactions of the tricarboxylic acid (TCA) cycle allow the controlled combustion of fat and carbohydrate. In principle, TCA cycle intermediates are regenerated on every turn and can facilitate the oxidation of an infinite number of nutrient molecules. However, TCA cycle intermediates can be lost to cataplerotic pathways that provide precursors for biosynthesis, and they must be replaced by anaplerotic pathways that regenerate these intermediates. Together, anaplerosis and cataplerosis help regulate rates of biosynthesis by dictating precursor supply, and they play underappreciated roles in catabolism and cellular energy status. They facilitate recycling pathways and nitrogen trafficking necessary for catabolism, and they influence redox state and oxidative capacity by altering TCA cycle intermediate concentrations. These functions vary widely by tissue and play emerging roles in disease. This article reviews the roles of anaplerosis and cataplerosis in various tissues and discusses how they alter carbon transitions, and highlights their contribution to mechanisms of disease. Expected final online publication date for the Annual Review of Nutrition, Volume 41 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

IsoSolve: An Integrative Framework to Improve Isotopic Coverage and Consolidate Isotopic Measurements by Mass Spectrometry and/or Nuclear Magnetic Resonance

Stable-isotope labeling experiments are widely used to investigate the topology and functioning of metabolic networks. Label incorporation into metabolites can be quantified using a broad range of mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy methods, but in general, no single approach can completely cover isotopic space, even for small metabolites. The number of quantifiable isotopic species could be increased and the coverage of isotopic space improved by integrating measurements obtained by different methods; however, this approach has remained largely unexplored because no framework able to deal with partial, heterogeneous isotopic measurements has yet been developed. Here, we present a generic computational framework based on symbolic calculus that can integrate any isotopic data set by connecting measurements to the chemical structure of the molecules. As a test case, we apply this framework to isotopic analyses of amino acids, which are ubiquitous to life, central to many biological questions, and can be analyzed by a broad range of MS and NMR methods. We demonstrate how this integrative framework helps to (i) clarify and improve the coverage of isotopic space, (ii) evaluate the complementarity and redundancy of different techniques, (iii) consolidate isotopic data sets, (iv) design experiments, and (v) guide future analytical developments. This framework, which can be applied to any labeled element, isotopic tracer, metabolite, and analytical platform, has been implemented in IsoSolve (available at https://github.com/MetaSys-LISBP/IsoSolve and https://pypi.org/project/IsoSolve), an open-source software that can be readily integrated into data analysis pipelines.

Multitissue 2H/13C flux analysis reveals reciprocal upregulation of renal gluconeogenesis in hepatic PEPCK-C-knockout mice

The liver is the major source of glucose production during fasting under normal physiological conditions. However, the kidney may also contribute to maintaining glucose homeostasis in certain circumstances. To test the ability of the kidney to compensate for impaired hepatic glucose production in vivo, we developed a stable isotope approach to simultaneously quantify gluconeogenic and oxidative metabolic fluxes in the liver and kidney. Hepatic gluconeogenesis from phosphoenolpyruvate was disrupted via liver-specific knockout of cytosolic phosphoenolpyruvate carboxykinase (PEPCK-C; KO). 2H/13C isotopes were infused in fasted KO and WT littermate mice, and fluxes were estimated from isotopic measurements of tissue and plasma metabolites using a multicompartment metabolic model. Hepatic gluconeogenesis and glucose production were reduced in KO mice, yet whole-body glucose production and arterial glucose were unaffected. Glucose homeostasis was maintained by a compensatory rise in renal glucose production and gluconeogenesis. Renal oxidative metabolic fluxes of KO mice increased to sustain the energetic and metabolic demands of elevated gluconeogenesis. These results show the reciprocity of the liver and kidney in maintaining glucose homeostasis by coordinated regulation of gluconeogenic flux through PEPCK-C. Combining stable isotopes with mathematical modeling provides a versatile platform to assess multitissue metabolism in various genetic, pathophysiological, physiological, and pharmacological settings.

Analysis of steady-state carbon tracer experiments using akaike information criteria

INTRODUCTION

Carbon isotope tracers have been used to determine relative rates of tricarboxylic acid cycle (TCA) cycle pathways since the 1950s. Steady-state experimental data are typically fit to a single mathematical model of metabolism to determine metabolic fluxes. Whether the chosen model is appropriate for the biological system has generally not been evaluated systematically. An overly-simple model omits known pathways while an overly-complex model may produce incorrect results due to overfitting.

OBJECTIVES

The objectives were to develop and study a method that systematically evaluates multiple TCA cycle mathematical models as part of the fitting process.

METHODS

The problem of choosing overly-simple or overly-complex models was approached by developing software that automatically explores all possible combinations of flux through pyruvate dehydrogenase, pyruvate kinase, pyruvate carboxylase and anaplerosis at propionyl-CoA carboxylase, and equivalent pathways, all relative to TCA cycle flux. Typical TCA cycle metabolic tracer experiments that use 13C nuclear magnetic resonance for detection and quantification of 13C-enriched glutamate products were simulated and analyzed. By evaluating the multiple model fits with both the conventional sum-of-squares residual error (SSRE) and the Akaike Information Criterion (AIC), the software helps the investigator understand the interaction between model complexity and goodness of fit.

RESULTS

When fitting alternative models of the TCA cycle metabolism, the SSRE may identify more than one model that fits the data well. Among those models, the AIC provides guidance as to which is the simplest of the candidate models is sufficient to describe the observed data. However under some conditions, AIC used alone inappropriately discriminates against necessary metabolic complexity.

CONCLUSION

In combination, the SSRE and AIC help the investigator identify the model that best describes the metabolism of a biological system.

Diminished ketone interconversion, hepatic TCA cycle flux, and glucose production in D-β-hydroxybutyrate dehydrogenase hepatocyte-deficient mice

Objective

Throughout the last decade, interest has intensified in intermittent fasting, ketogenic diets, and exogenous ketone therapies as prospective health-promoting, therapeutic, and performance-enhancing agents. However, the regulatory roles of ketogenesis and ketone metabolism on liver homeostasis remain unclear. Therefore, we sought to develop a better understanding of the metabolic consequences of hepatic ketone body metabolism by focusing on the redox-dependent interconversion of acetoacetate (AcAc) and D-β-hydroxybutyrate (D-βOHB).

Methods

Using targeted and isotope tracing high-resolution liquid chromatography-mass spectrometry, dual stable isotope tracer nuclear magnetic resonance spectroscopy-based metabolic flux modeling, and complementary physiological approaches in novel cell type-specific knockout mice, we quantified the roles of hepatocyte D-β-hydroxybutyrate dehydrogenase (BDH1), a mitochondrial enzyme required for NAD⁺/NADH-dependent oxidation/reduction of ketone bodies.

Results

Exogenously administered AcAc is reduced to D-βOHB, which increases hepatic NAD⁺/NADH ratio and reflects hepatic BDH1 activity. Livers of hepatocyte-specific BDH1-deficient mice did not produce D-βOHB, but owing to extrahepatic BDH1, these mice nonetheless remained capable of AcAc/D-βOHB interconversion. Compared to littermate controls, hepatocyte-specific BDH1 deficient mice exhibited diminished liver tricarboxylic acid (TCA) cycle flux and impaired gluconeogenesis, but normal hepatic energy charge overall. Glycemic recovery after acute insulin challenge was impaired in knockout mice, but they were not more susceptible to starvation-induced hypoglycemia.

Conclusions

Ketone bodies influence liver homeostasis. While liver BDH1 is not required for whole body equilibration of AcAc and D-βOHB, loss of the ability to interconvert these ketone bodies in hepatocytes results in impaired TCA cycle flux and glucose production. Therefore, through oxidation/reduction of ketone bodies, BDH1 is a significant contributor to hepatic mitochondrial redox, liver physiology, and organism-wide ketone body homeostasis.

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Exogenously administered acetoacetate is reduced to D-β-hydroxybutyrate, increasing hepatic NAD⁺/NADH ratio.

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Liver BDH1 is not required for whole body equilibration of acetoacetate and D-β-hydroxybutyrate.

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Hepatocyte-specific loss of BDH1 reduces hepatic TCA cycle flux, and TCA-cycle sourced gluconeogenesis.

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Hepatocyte-specific loss of BDH1 impairs glycemic recovery without provoking starvation-induced hypoglycemia.

In vivo2H/13C flux analysis in metabolism research

Identifying the factors and mechanisms that regulate metabolism under normal and diseased states requires methods to quantify metabolic fluxes of live tissues within their physiological milieu. A number of recent developments have expanded the reach and depth of isotope-based in vivo flux analysis, which have in turn challenged existing dogmas in metabolism research. First, minimally invasive techniques of intravenous isotope infusion and sampling have advanced in vivo metabolic tracer studies in animal models and human subjects. Second, recent breakthroughs in analytical instrumentation have expanded the scope of isotope labeling measurements and reduced sample volume requirements. Third, innovative modeling approaches and publicly available software tools have facilitated rigorous analysis of sophisticated experimental designs involving multiple tracers and expansive metabolomics datasets. These developments have enabled comprehensive in vivo quantification of metabolic fluxes in specific tissues and have set the stage for integrated multi-tissue flux assays.

In Vivo Estimates of Liver Metabolic Flux Assessed by 13C-Propionate and 13C-Lactate Are Impacted by Tracer Recycling and Equilibrium Assumptions

Isotope-based assessment of metabolic flux is achieved through a judicious balance of measurements and assumptions. Recent publications debate the validity of key assumptions used to model stable isotope labeling of liver metabolism in vivo. Here, we examine the controversy surrounding estimates of liver citric acid cycle and gluconeogenesis fluxes using a flexible modeling platform that enables rigorous testing of standard assumptions. Fasted C57BL/6J mice are infused with [¹³C₃]lactate or [¹³C₃]propionate isotopes, and hepatic fluxes are regressed using models with gradually increasing complexity and relaxed assumptions. We confirm that liver pyruvate cycling fluxes are incongruent between different ¹³C tracers in models with conventional assumptions. When models are expanded to include more labeling measurements and fewer constraining assumptions, however, liver pyruvate cycling is significant, and inconsistencies in hepatic flux estimates using [¹³C₃]lactate and [¹³C₃]propionate isotopes emanate, in part, from peripheral tracer recycling and incomplete isotope equilibration within the citric acid cycle.

In Vivo Estimation of Ketogenesis Using Metabolic Flux Analysis-Technical Aspects and Model Interpretation

Ketogenesis occurs in liver mitochondria where acetyl-CoA molecules, derived from lipid oxidation, are condensed into acetoacetate (AcAc) and reduced to β-hydroxybutyrate (BHB). During carbohydrate scarcity, these two ketones are released into circulation at high rates and used as oxidative fuels in peripheral tissues. Despite their physiological relevance and emerging roles in a variety of diseases, endogenous ketone production is rarely measured in vivo using tracer approaches. Accurate determination of this flux requires a two-pool model, simultaneous BHB and AcAc tracers, and special consideration for the stability of the AcAc tracer and analyte. We describe the implementation of a two-pool model using a metabolic flux analysis (MFA) approach that simultaneously regresses liquid chromatography-tandem mass spectrometry (LC-MS/MS) ketone isotopologues and tracer infusion rates. Additionally, ¹H NMR real-time reaction monitoring was used to evaluate AcAc tracer and analyte stability during infusion and sample analysis, which were critical for accurate flux calculations. The approach quantifies AcAc and BHB pool sizes and their rates of appearance, disposal, and exchange. Regression analysis provides confidence intervals and detects potential errors in experimental data. Complications for the physiological interpretation of individual ketone fluxes are discussed.

In Vivo and In Vitro Quantification of Glucose Kinetics: From Bedside to Bench

Like other substrates, plasma glucose is in a dynamic state of constant turnover (i.e., rates of glucose appearance [Ra glucose] into and disappearance [Rd glucose] from the plasma) while staying within a narrow range of normal concentrations, a physiological priority. Persistent imbalance of glucose turnover leads to elevations (i.e., hyperglycemia, Ra>Rd) or falls (i.e., hypoglycemia, Ra Collapse

Key Words

• Diabetes mellitus
• Insulin resistance
• Metabolic fluxomics
• Stable isotope tracers

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MESH Headings

• Animals
• Diabetes Mellitus/metabolism
• Gluconeogenesis
• Glucose/biosynthesis
• Glycogenolysis
• Humans
• Hyperglycemia/metabolism
• Hypoglycemia/metabolism
• Insulin Resistance
• Isotopes/administration & dosage
• Isotopes/metabolism
• Kinetics
• Liver/metabolism
• Metabolic Flux Analysis

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Grants

• 2018R1D1A1B07051053 National Research Foundation of Korea
• 2019H1D3A1A01071043 National Research Foundation of Korea
• 2020R1I1A1A01074380 National Research Foundation of Korea
• 2014M3A9D5A01073886 National Research Foundation of Korea
• 2017R1D1A1B03032988 National Research Foundation of Korea
• Ministry of Education
• Ministry of Sciences and ICT

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Affiliation(s)

Il-Young Kim Department of Molecular Medicine, College of Medicine, Gachon University, Incheon, Seoul, Korea Korea Mouse Metabolic Phenotyping Center, Lee Gil Ya Cancer and Diabetes Institute, Gachon University, Incheon, Seoul, Korea
Sanghee Park Department of Molecular Medicine, College of Medicine, Gachon University, Incheon, Seoul, Korea Korea Mouse Metabolic Phenotyping Center, Lee Gil Ya Cancer and Diabetes Institute, Gachon University, Incheon, Seoul, Korea
Yeongmin Kim Department of Health Sciences and Technology, Gachon Advanced Institute for Health Sciences & Technology (GAIHST), Gachon University, Incheon, Seoul, Korea
Yewon Chang Department of Health Sciences and Technology, Gachon Advanced Institute for Health Sciences & Technology (GAIHST), Gachon University, Incheon, Seoul, Korea
Cheol Soo Choi Department of Molecular Medicine, College of Medicine, Gachon University, Incheon, Seoul, Korea Korea Mouse Metabolic Phenotyping Center, Lee Gil Ya Cancer and Diabetes Institute, Gachon University, Incheon, Seoul, Korea
Sang-Hoon Suh Department of Physical Education, Yonsei University, Seoul, Korea
Robert R. Wolfe Department of Geriatrics, the Center for Translational Research in Aging & Longevity, Donald W. Reynolds Institute on Aging, University of Arkansas for Medical Sciences, Little Rock, AR, USA

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