Noninvasive liquid diet delivery of stable isotopes into mouse models for deep metabolic network tracing

Spatial single-cell isotope tracing reveals heterogeneity of de novo fatty acid synthesis in cancer

While heterogeneity is a key feature of cancer, understanding metabolic heterogeneity at the single-cell level remains a challenge. Here we present 13C-SpaceM, a method for spatial single-cell isotope tracing that extends the previously published SpaceM method with detection of 13C6-glucose-derived carbons in esterified fatty acids. We validated 13C-SpaceM on spatially heterogeneous models using liver cancer cells subjected to either normoxia-hypoxia or ATP citrate lyase depletion. This revealed substantial single-cell heterogeneity in labelling of the lipogenic acetyl-CoA pool and in relative fatty acid uptake versus synthesis hidden in bulk analyses. Analysing tumour-bearing brain tissue from mice fed a 13C6-glucose-containing diet, we found higher glucose-dependent synthesis of saturated fatty acids and increased elongation of essential fatty acids in tumours compared with healthy brains. Furthermore, our analysis uncovered spatial heterogeneity in lipogenic acetyl-CoA pool labelling in tumours. Our method enhances spatial probing of metabolic activities in single cells and tissues, providing insights into fatty acid metabolism in homoeostasis and disease.

Stable isotope-resolved metabolomics analyses of metabolic phenotypes reveal variable glutamine metabolism in different patient-derived models of non-small cell lung cancer from a single patient

INTRODUCTION

Stable isotope tracers have been increasingly used in preclinical cancer model systems, including cell culture and mouse xenografts, to probe the altered metabolism of a variety of cancers, such as accelerated glycolysis and glutaminolysis and generation of oncometabolites. Comparatively little has been reported on the fidelity of the different preclinical model systems in recapitulating the aberrant metabolism of tumors.

OBJECTIVES

We have been developing several different experimental model systems for systems biochemistry analyses of non-small cell lung cancer (NSCLC1) using patient-derived tissues to evaluate appropriate models for metabolic and phenotypic analyses.

METHODS

To address the issue of fidelity, we have carried out a detailed Stable Isotope-Resolved Metabolomics study of freshly resected tissue slices, mouse patient derived xenografts (PDXs), and cells derived from a single patient using both 13C6-glucose and 13C5,15N2-glutamine tracers.

RESULTS

Although we found similar glucose metabolism in the three models, glutamine utilization was markedly higher in the isolated cell culture and in cell culture-derived xenografts compared with the primary cancer tissue or direct tissue xenografts (PDX).

CONCLUSIONS

This suggests that caution is needed in interpreting cancer biochemistry using patient-derived cancer cells in vitro or in xenografts, even at very early passage, and that direct analysis of patient derived tissue slices provides the optimal model for ex vivo metabolomics. Further research is needed to determine the generality of these observations.

Challenges of Spatially Resolved Metabolism in Cancer Research

Stable isotope-resolved metabolomics comprises a critical set of technologies that can be applied to a wide variety of systems, from isolated cells to whole organisms, to define metabolic pathway usage and responses to perturbations such as drugs or mutations, as well as providing the basis for flux analysis. As the diversity of stable isotope-enriched compounds is very high, and with newer approaches to multiplexing, the coverage of metabolism is now very extensive. However, as the complexity of the model increases, including more kinds of interacting cell types and interorgan communication, the analytical complexity also increases. Further, as studies move further into spatially resolved biology, new technical problems have to be overcome owing to the small number of analytes present in the confines of a single cell or cell compartment. Here, we review the overall goals and solutions made possible by stable isotope tracing and their applications to models of increasing complexity. Finally, we discuss progress and outstanding difficulties in high-resolution spatially resolved tracer-based metabolic studies.

Exercise-induced changes in myocardial glucose utilization during periods of active cardiac growth

Exercise training can promote physiological cardiac growth, which has been suggested to involve changes in glucose metabolism to facilitate hypertrophy of cardiomyocytes. In this study, we used a dietary, in vivo isotope labeling approach to examine how exercise training influences the metabolic fate of carbon derived from dietary glucose in the heart during acute, active, and established phases of exercise-induced cardiac growth. Male and female FVB/NJ mice were subjected to treadmill running for up to 4 weeks and cardiac growth was assessed by gravimetry. Cardiac metabolic responses to exercise were assessed via in vivo tracing of [13C6]-glucose via mass spectrometry and nuclear magnetic resonance. We found that the half-maximal cardiac growth response was achieved by approximately 1 week of daily exercise training, with near maximal growth observed in male mice with 2 weeks of training; however, female mice were recalcitrant to exercise-induced cardiac growth and required a higher daily intensity of exercise training to achieve significant, albeit modest, increases in cardiac mass. We also found that increases in the energy charge of adenylate and guanylate nucleotide pools precede exercise-induced changes in cardiac size and were associated with higher glucose tracer enrichment in the TCA pool and in amino acids (aspartate, glutamate) sourced by TCA intermediates. Our data also indicate that the activity of collateral biosynthetic pathways of glucose metabolism may not be markedly altered by exercise. Overall, this study provides evidence that metabolic remodeling in the form of heightened energy charge and increased TCA cycle activity and cataplerosis precedes cardiac growth caused by exercise training in male mice.

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.

The prowess of metabolomics in cancer research: current trends, challenges and future perspectives

Cancer due to its heterogeneous nature and large prevalence has tremendous socioeconomic impacts on populations across the world. Therefore, it is crucial to discover effective panels of biomarkers for diagnosing cancer at an early stage. Cancer leads to alterations in cell growth and differentiation at the molecular level, some of which are very unique. Therefore, comprehending these alterations can aid in a better understanding of the disease pathology and identification of the biomolecules that can serve as effective biomarkers for cancer diagnosis. Metabolites, among other biomolecules of interest, play a key role in the pathophysiology of cancer whose levels are significantly altered while 'reprogramming the energy metabolism', a cellular condition favored in cancer cells which is one of the hallmarks of cancer. Metabolomics, an emerging omics technology has tremendous potential to contribute towards the goal of investigating cancer metabolites or the metabolic alterations during the development of cancer. Diverse metabolites can be screened in a variety of biofluids, and tumor tissues sampled from cancer patients against healthy controls to capture the altered metabolism. In this review, we provide an overview of different metabolomics approaches employed in cancer research and the potential of metabolites as biomarkers for cancer diagnosis. In addition, we discuss the challenges associated with metabolomics-driven cancer research and gaze upon the prospects of this emerging field.

13C-Stable isotope resolved metabolomics uncovers dynamic biochemical landscape of gut microbiome-host organ communications in mice

BACKGROUND

Gut microbiome metabolites are important modulators of host health and disease. However, the overall metabolic potential of the gut microbiome and interactions with the host organs have been underexplored.

RESULTS

Using stable isotope resolved metabolomics (SIRM) in mice orally gavaged with 13C-inulin (a tracer), we first observed dynamic enrichment of 13C-metabolites in cecum contents in the amino acids and short-chain fatty acid metabolism pathways. 13C labeled metabolites were subsequently profiled comparatively in plasma, liver, brain, and skeletal muscle collected at 6, 12, and 24 h after the tracer administration. Organ-specific and time-dependent 13C metabolite enrichments were observed. Carbons from the gut microbiome were preferably incorporated into choline metabolism and the glutamine-glutamate/GABA cycle in the liver and brain, respectively. A sex difference in 13C-lactate enrichment was observed in skeletal muscle, which highlights the sex effect on the interplay between gut microbiome and host organs. Choline was identified as an interorgan metabolite derived from the gut microbiome and fed the lipogenesis of phosphatidylcholine and lysophosphatidylcholine in host organs. In vitro and in silico studies revealed the de novo synthesis of choline in the human gut microbiome via the ethanolamine pathway, and Enterococcus faecalis was identified as a major choline synthesis species. These results revealed a previously underappreciated role for gut microorganisms in choline biosynthesis.

CONCLUSIONS

Multicompartmental SIRM analyses provided new insights into the current understanding of dynamic interorgan metabolite transport between the gut microbiome and host at the whole-body level in mice. Moreover, this study singled out microbiota-derived metabolites that are potentially involved in the gut-liver, gut-brain, and gut-skeletal muscle axes. Video Abstract.

A simple 1H (12C/13C) filtered experiment to quantify and trace isotope enrichment in complex environmental and biological samples

Nuclear magnetic resonance (NMR) based 13C tracing has broad applications across medical and environmental research. As many biological and environmental samples are heterogeneous, they experience considerable spectral overlap and relatively low signal. Here a 1D 1H-12C/13C is introduced that uses "in-phase/opposite-phase" encoding to simultaneously detect and discriminate both protons attached to 12C and 13C at full 1H sensitivity in every scan. Unlike traditional approaches that focus on the 12C/13C satellite ratios in a 1H spectrum, this approach creates separate sub-spectra for the 12C and 13C bound protons. These spectra can be used for both quantitative and qualitative analysis of complex samples with significant spectral overlap. Due to the presence of the 13C dipole, faster relaxation of the 1H-13C pairs results in slight underestimation compared to the 1H-12C pairs. However, this is easily compensated for, by collecting an additional reference spectrum, from which the absolute percentage of 13C can be calculated by difference. When combined with the result, 12C and 13C percent enrichment in both 1H-12C and 1H-13C fractions are obtained. As the approach uses isotope filtered 1H NMR for detection, it retains nearly the same sensitivity as a standard 1H spectrum. Here, a proof-of-concept is performed using simple mixtures of 12C and 13C glucose, followed by suspended algal cells with varying 12C /13C ratios representing a complex mixture. The results consistently return 12C/13C ratios that deviate less than 1 % on average from the expected. Finally, the sequence was used to monitor and quantify 13C% enrichment in Daphnia magna neonates which were fed a 13C diet over 1 week. The approach helped reveal how the organisms utilized the 12C lipids they are born with vs. the 13C lipids they assimilate from their diet during growth. Given the experiments simplicity, versatility, and sensitivity, we anticipate it should find broad application in a wide range of tracer studies, such as fluxomics, with applications spanning various disciplines.

13C-SpaceM: Spatial single-cell isotope tracing reveals heterogeneity of de novo fatty acid synthesis in cancer

Metabolism has emerged as a key factor in homeostasis and disease including cancer. Yet, little is known about the heterogeneity of metabolic activity of cancer cells due to the lack of tools to directly probe it. Here, we present a novel method, 13C-SpaceM for spatial single-cell isotope tracing of glucose-dependent de novo lipogenesis. The method combines imaging mass spectrometry for spatially-resolved detection of 13C6-glucose-derived 13C label incorporated into esterified fatty acids with microscopy and computational methods for data integration and analysis. We validated 13C-SpaceM on a spatially-heterogeneous normoxia-hypoxia model of liver cancer cells. Investigating cultured cells, we revealed single-cell heterogeneity of lipogenic acetyl-CoA pool labelling degree upon ACLY knockdown that is hidden in the bulk analysis and its effect on synthesis of individual fatty acids. Next, we adapted 13C-SpaceM to analyze tissue sections of mice harboring isocitrate dehydrogenase (IDH)-mutant gliomas. We found a strong induction of de novo fatty acid synthesis in the tumor tissue compared to the surrounding brain. Comparison of fatty acid isotopologue patterns revealed elevated uptake of mono-unsaturated and essential fatty acids in the tumor. Furthermore, our analysis uncovered substantial spatial heterogeneity in the labelling of the lipogenic acetyl-CoA pool indicative of metabolic reprogramming during microenvironmental adaptation. Overall, 13C-SpaceM enables novel ways for spatial probing of metabolic activity at the single cell level. Additionally, this methodology provides unprecedented insight into fatty acid uptake, synthesis and modification in normal and cancerous tissues.

Assessment of metabolic responses following silica nanoparticles in zebrafish models using 1H NMR analysis

Silica nanoparticles (SNPs) are widely explored as drug carriers, gene delivery vehicles, and as nanoparticles intended for bone and tissue engineering. SNPs are highly evident through various clinical trials for a wide range of biomedical applications. SNPs are biocompatible and promising nanoparticles for next-generation therapeutics. However, despite the well-established importance of SNPs, metabolomics methods for the SNPs remain elusive which renders its maximal clinical translation. We applied 1H nuclear magnetic resonance (1H NMR) spectroscopy to investigate the metabolomics profile in Zebrafish (Danio rerio) exposed to SNPs. Zebrafish were exposed to the SNPs (10.0, 25.0, and 50.0 μg/mL) for 72 h and whole-body samples were subjected for targeted profiling. Pattern recognition of 1H NMR spectral data depicted alterations in the metabolomic profiles between control and SNPs exposed zebrafish. We found that tryptophane, lysine, methionine, phenylalanine, tyrosine, sn-glycero-3-phosphocholine (G3PC), and o-phosphocholine were decreased. The metabolic expression of niacinamide, nicotinamide adenine dinucleotide (NAD+), citrate, adenosine triphosphate (ATP), and xanthine were increased in zebrafish with SNPs treatment. We are report for the first time on metabolite alterations and phenotypic expression in zebrafish via 1H NMR. These results demonstrate that SNPs can adversely affect the significant metabolic pathways involved in energy, amino acids, cellular membrane, lipids, and fatty acid metabolisms. Metabolomics profiling may be able to detect metabolic dysregulation in SNPs-treated zebrafish and establish a foundation for further toxicological studies.

Interpreting metabolic complexity via isotope-assisted metabolic flux analysis

Isotope-assisted metabolic flux analysis (iMFA) is a powerful method to mathematically determine the metabolic fluxome from experimental isotope labeling data and a metabolic network model. While iMFA was originally developed for industrial biotechnological applications, it is increasingly used to analyze eukaryotic cell metabolism in physiological and pathological states. In this review, we explain how iMFA estimates the intracellular fluxome, including data and network model (inputs), the optimization-based data fitting (process), and the flux map (output). We then describe how iMFA enables analysis of metabolic complexities and discovery of metabolic pathways. Our goal is to expand the use of iMFA in metabolism research, which is essential to maximizing the impact of metabolic experiments and continuing to advance iMFA and biocomputational techniques.

Using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem

Tumors are comprised of a multitude of cell types spanning different microenvironments. Mass spectrometry imaging (MSI) has the potential to identify metabolic patterns within the tumor ecosystem and surrounding tissues, but conventional workflows have not yet fully integrated the breadth of experimental techniques in metabolomics. Here, we combine MSI, stable isotope labeling, and a spatial variant of Isotopologue Spectral Analysis to map distributions of metabolite abundances, nutrient contributions, and metabolic turnover fluxes across the brains of mice harboring GL261 glioma, a widely used model for glioblastoma. When integrated with MSI, the combination of ion mobility, desorption electrospray ionization, and matrix assisted laser desorption ionization reveals alterations in multiple anabolic pathways. De novo fatty acid synthesis flux is increased by approximately 3-fold in glioma relative to surrounding healthy tissue. Fatty acid elongation flux is elevated even higher at 8-fold relative to surrounding healthy tissue and highlights the importance of elongase activity in glioma.

In situ microwave fixation provides an instantaneous snapshot of the brain metabolome

Brain glucose metabolism is highly heterogeneous among brain regions and continues postmortem. In particular, we demonstrate exhaustion of glycogen and glucose and an increase in lactate production during conventional rapid brain resection and preservation by liquid nitrogen. In contrast, we show that these postmortem changes are not observed with simultaneous animal sacrifice and in situ fixation with focused, high-power microwave. We further employ microwave fixation to define brain glucose metabolism in the mouse model of streptozotocin-induced type 1 diabetes. Using both total pool and isotope tracing analyses, we identified global glucose hypometabolism in multiple brain regions, evidenced by reduced 13C enrichment into glycogen, glycolysis, and the tricarboxylic acid (TCA) cycle. Reduced glucose metabolism correlated with a marked decrease in GLUT2 expression and several metabolic enzymes in unique brain regions. In conclusion, our study supports the incorporation of microwave fixation for more accurate studies of brain metabolism in rodent models.

Bayesian kinetic modeling for tracer-based metabolomic data

BACKGROUND

Stable Isotope Resolved Metabolomics (SIRM) is a new biological approach that uses stable isotope tracers such as uniformly [Formula: see text]-enriched glucose ([Formula: see text]-Glc) to trace metabolic pathways or networks at the atomic level in complex biological systems. Non-steady-state kinetic modeling based on SIRM data uses sets of simultaneous ordinary differential equations (ODEs) to quantitatively characterize the dynamic behavior of metabolic networks. It has been increasingly used to understand the regulation of normal metabolism and dysregulation in the development of diseases. However, fitting a kinetic model is challenging because there are usually multiple sets of parameter values that fit the data equally well, especially for large-scale kinetic models. In addition, there is a lack of statistically rigorous methods to compare kinetic model parameters between different experimental groups.

RESULTS

We propose a new Bayesian statistical framework to enhance parameter estimation and hypothesis testing for non-steady-state kinetic modeling of SIRM data. For estimating kinetic model parameters, we leverage the prior distribution not only to allow incorporation of experts' knowledge but also to provide robust parameter estimation. We also introduce a shrinkage approach for borrowing information across the ensemble of metabolites to stably estimate the variance of an individual isotopomer. In addition, we use a component-wise adaptive Metropolis algorithm with delayed rejection to perform efficient Monte Carlo sampling of the posterior distribution over high-dimensional parameter space. For comparing kinetic model parameters between experimental groups, we propose a new reparameterization method that converts the complex hypothesis testing problem into a more tractable parameter estimation problem. We also propose an inference procedure based on credible interval and credible value. Our method is freely available for academic use at https://github.com/xuzhang0131/MCMCFlux .

CONCLUSIONS

Our new Bayesian framework provides robust estimation of kinetic model parameters and enables rigorous comparison of model parameters between experimental groups. Simulation studies and application to a lung cancer study demonstrate that our framework performs well for non-steady-state kinetic modeling of SIRM data.

Ultrahigh resolution MS1/MS2-based reconstruction of metabolic networks in mammalian cells reveals changes for selenite and arsenite action

Metabolic networks are complex, intersecting, and composed of numerous enzyme-catalyzed biochemical reactions that transfer various molecular moieties among metabolites. Thus, robust reconstruction of metabolic networks requires metabolite moieties to be tracked, which cannot be readily achieved with mass spectrometry (MS) alone. We previously developed an Ion Chromatography-ultrahigh resolution-MS1/data independent-MS2 method to track the simultaneous incorporation of the heavy isotopes 13C and 15N into the moieties of purine/pyrimidine nucleotides in mammalian cells. Ultrahigh resolution-MS1 resolves and counts multiple tracer atoms in intact metabolites, while data independent-tandem MS (MS2) determines isotopic enrichment in their moieties without concern for the numerous mass isotopologue source ions to be fragmented. Together, they enabled rigorous MS-based reconstruction of metabolic networks at specific enzyme levels. We have expanded this approach to trace the labeled atom fate of [13C6]-glucose in 3D A549 spheroids in response to the anticancer agent selenite and that of [13C5,15N2]-glutamine in 2D BEAS-2B cells in response to arsenite transformation. We deduced altered activities of specific enzymes in the Krebs cycle, pentose phosphate pathway, gluconeogenesis, and UDP-GlcNAc synthesis pathways elicited by the stressors. These metabolic details help elucidate the resistance mechanism of 3D versus 2D A549 cultures to selenite and metabolic reprogramming that can mediate the transformation of BEAS-2B cells by arsenite.

Emerging metabolomic tools to study cancer metastasis

Metastasis is responsible for 90% of deaths in patients with cancer. Understanding the role of metabolism during metastasis has been limited by the development of robust and sensitive technologies that capture metabolic processes in metastasizing cancer cells. We discuss the current technologies available to study (i) metabolism in primary and metastatic cancer cells and (ii) metabolic interactions between cancer cells and the tumor microenvironment (TME) at different stages of the metastatic cascade. We identify advantages and disadvantages of each method and discuss how these tools and technologies will further improve our understanding of metastasis. Studies investigating the complex metabolic rewiring of different cells using state-of-the-art metabolomic technologies have the potential to reveal novel biological processes and therapeutic interventions for human cancers.

In situ spatial glycomic imaging of mouse and human Alzheimer's disease brains

N-linked protein glycosylation in the brain is an understudied facet of glucose utilization that impacts a myriad of cellular processes including resting membrane potential, axon firing, and synaptic vesicle trafficking. Currently, a spatial map of N-linked glycans within the normal and Alzheimer's disease (AD) human brain does not exist. A comprehensive analysis of the spatial N-linked glycome would improve our understanding of brain energy metabolism, linking metabolism to signaling events perturbed during AD progression, and could illuminate new therapeutic strategies. Herein we report an optimized in situ workflow for enzyme-assisted, matrix-assisted laser desorption and ionization (MALDI) mass spectrometry imaging (MSI) of brain N-linked glycans. Using this workflow, we spatially interrogated N-linked glycan heterogeneity in both mouse and human AD brains and their respective age-matched controls. We identified robust regional-specific N-linked glycan changes associated with AD in mice and humans. These data suggest that N-linked glycan dysregulation could be an underpinning of AD pathologies.

A Micro-Scale Analytical Method for Determining Glycogen Turnover by NMR and FTMS

Glycogen is a readily deployed intracellular energy storage macromolecule composed of branched chains of glucose anchored to the protein glycogenin. Although glycogen primarily occurs in the liver and muscle, it is found in most tissues, and its metabolism has been shown to be important in cancers and immune cells. Robust analysis of glycogen turnover requires stable isotope tracing plus a reliable means of quantifying total and labeled glycogen derived from precursors such as 13C6-glucose. Current methods for analyzing glycogen are time- and sample-consuming, at best semi-quantitative, and unable to measure stable isotope enrichment. Here we describe a microscale method for quantifying both intact and acid-hydrolyzed glycogen by ultra-high-resolution Fourier transform mass spectrometric (UHR-FTMS) and/or NMR analysis in stable isotope resolved metabolomics (SIRM) studies. Polar metabolites, including intact glycogen and their 13C positional isotopomer distributions, are first measured in crude biological extracts by high resolution NMR, followed by rapid and efficient acid hydrolysis to glucose under N2 in a focused beam microwave reactor, with subsequent analysis by UHR-FTMS and/or NMR. We optimized the microwave digestion time, temperature, and oxygen purging in terms of recovery versus degradation and found 10 min at 110−115 °C to give >90% recovery. The method was applied to track the fate of 13C6-glucose in primary human lung BEAS-2B cells, human macrophages, murine liver and patient-derived tumor xenograft (PDTX) in vivo, and the fate of 2H7-glucose in ex vivo lung organotypic tissue cultures of a lung cancer patient. We measured the incorporation of 13C6-glucose into glycogen and its metabolic intermediates, UDP-Glucose and glucose-1-phosphate, to demonstrate the utility of the method in tracing glycogen turnover in cells and tissues. The method offers a quantitative, sensitive, and convenient means to analyze glycogen turnover in mg amounts of complex biological materials.

A multidimensional metabolomics workflow to image biodistribution and evaluate pharmacodynamics in adult zebrafish

An integrated evaluation of the tissue distribution and pharmacodynamic properties of a therapeutic is essential for successful translation to the clinic. To date, however, cost-effective methods to measure these parameters at the systems level in model organisms are lacking. Here, we introduce a multidimensional workflow to evaluate drug activity that combines mass spectrometry-based imaging, absolute drug quantitation across different biological matrices, in vivo isotope tracing and global metabolome analysis in the adult zebrafish. As a proof of concept, we quantitatively determined the whole-body distribution of the anti-rheumatic agent hydroxychloroquine sulfate (HCQ) and measured the systemic metabolic impacts of drug treatment. We found that HCQ distributed to most organs in the adult zebrafish 24 h after addition of the drug to water, with the highest accumulation of both the drug and its metabolites being in the liver, intestine and kidney. Interestingly, HCQ treatment induced organ-specific alterations in metabolism. In the brain, for example, HCQ uniquely elevated pyruvate carboxylase activity to support increased synthesis of the neuronal metabolite, N-acetylaspartate. Taken together, this work validates a multidimensional metabolomics platform for evaluating the mode of action of a drug and its potential off-target effects in the adult zebrafish. This article has an associated First Person interview with the first author of the paper.

13C tracer analysis suggests extensive recycling of endogenous CO2 in vivo

Background

¹³C tracer analysis is increasingly used to monitor cellular metabolism in vivo and in intact cells, but data interpretation is still the key element to unveil the complexity of metabolic activities. The distinct ¹³C labeling patterns (e.g., M + 1 species in vivo but not in vitro) of metabolites from [U-¹³C]-glucose or [U-¹³C]-glutamine tracing in vivo and in vitro have been previously reported by multiple groups. However, the reason for the difference in the M + 1 species between in vivo and in vitro experiments remains poorly understood.

Methods

We have performed [U-¹³C]-glucose and [U-¹³C]-glutamine tracing in sarcoma-bearing mice (in vivo) and in cancer cell lines (in vitro). ¹³C enrichment of metabolites in cultured cells and tissues was determined by LC coupled with high-resolution mass spectrometry (LC-HRMS). All p-values are obtained from the Student’s t-test two-tailed using GraphPad Prism 8 unless otherwise noted.

Results

We observed distinct enrichment patterns of tricarboxylic acid cycle intermediates in vivo and in vitro. As expected, citrate M + 2 or M + 4 was the dominant mass isotopologue in vitro. However, citrate M + 1 was unexpectedly the dominant isotopologue in mice receiving [U-¹³C]-glucose or [U-¹³C]-glutamine infusion, but not in cultured cells. Our results are consistent with a model where the difference in M + 1 species is due to the different sources of CO₂ in vivo and in vitro, which was largely overlooked in the past. In addition, a time course study shows the generation of high abundance citrate M + 1 in plasma of mice as early as few minutes after [U-¹³C]-glucose infusion.

Conclusions

Altogether, our results show that recycling of endogenous CO₂ is substantial in vivo. The production and recycling of ¹³CO₂ from the decarboxylation of [U-¹³C]-glucose or [U-¹³C]-glutamine is negligible in vitro partially due to dilution by the exogenous HCO₃⁻/CO₂ source, but in vivo incorporation of endogenous ¹³CO₂ into M + 1 metabolites is substantial and should be considered. These findings provide a new paradigm to understand carbon atom transformations in vivo and should be taken into account when developing mathematical models to better reflect carbon flux.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40170-022-00287-8.

Deciphering Metabolic Adaptability of Leukemic Stem Cells

Therapeutic targeting of leukemic stem cells is widely studied to control leukemia. An emerging approach gaining popularity is altering metabolism as a potential therapeutic opportunity. Studies have been carried out on hematopoietic and leukemic stem cells to identify vulnerable pathways without impacting the non-transformed, healthy counterparts. While many metabolic studies have been conducted using stem cells, most have been carried out in vitro or on a larger population of progenitor cells due to challenges imposed by the low frequency of stem cells found in vivo. This creates artifacts in the studies carried out, making it difficult to interpret and correlate the findings to stem cells directly. This review discusses the metabolic difference seen between hematopoietic stem cells and leukemic stem cells across different leukemic models. Moreover, we also shed light on the advancements of metabolic techniques and current limitations and areas for additional research of the field to study stem cell metabolism.

Stable isotope tracing to assess tumor metabolism in vivo

Cancer cells undergo diverse metabolic adaptations to meet the energetic demands imposed by dysregulated growth and proliferation. Assessing metabolism in intact tumors allows the investigator to observe the combined metabolic effects of numerous cancer cell-intrinsic and -extrinsic factors that cannot be fully captured in culture models. We have developed methods to use stable isotope-labeled nutrients (e.g., [13C]glucose) to probe metabolic activity within intact tumors in vivo, in mice and humans. In these methods, the labeled nutrient is introduced to the circulation through an intravenous catheter prior to surgical resection of the tumor and adjacent nonmalignant tissue. Metabolism within these tissues during the infusion transfers the isotope label into metabolic intermediates from pathways supplied by the infused nutrient. Extracting metabolites from surgical specimens and analyzing their isotope labeling patterns provides information about metabolism in the tissue. We provide detailed information about this technique, from introduction of the labeled tracer through data analysis and interpretation, including streamlined approaches to quantify isotope labeling in informative metabolites extracted from tissue samples. We focus on infusions with [13C]glucose and the application of mass spectrometry to assess isotope labeling in intermediates from central metabolic pathways, including glycolysis, the tricarboxylic acid cycle and nonessential amino acid synthesis. We outline practical considerations to apply these methods to human subjects undergoing surgical resections of solid tumors. We also discuss the method's versatility and consider the relative advantages and limitations of alternative approaches to introduce the tracer, harvest the tissue and analyze the data.

Rapid analysis of S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) isotopologues in stable isotope-resolved metabolomics (SIRM) using direct infusion nanoelectrospray ultra-high-resolution Fourier transform mass spectrometry (DI-nESI-UHR-FTMS)

S-Adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH) are important metabolites in the one-carbon cycle that modulates cellular methylation required for proliferation and epigenetic regulation. Their concentrations, synthesis, and turnover are difficult to determine conveniently and reliably. We have developed such a method by coupling a simple and rapid purification scheme that efficiently captures both compounds, with high sensitivity, sample throughput direct infusion nanoelectrospray ultra-high-resolution Fourier transform mass spectrometry (DI-nESI-UHR-FTMS). This method is compatible with Stable Isotope-Resolved Metabolomic (SIRM) analysis of numerous other metabolites. The limits of detection for both SAM and SAH were <1 nM, and the linearity range was up to 1000 nM. The method was first illustrated for SAM/SAH analysis of mouse livers, and lung adenocarcinoma A549 cells. We then applied the method to track ¹³C₁-CH₃-Met incorporation into SAM and ¹³C₆-glucose transformation into SAM and SAH via de novo synthesis. We further used the method to show the distinct effects on A549 and H1299 cells with treatment of anti-cancer methylseleninic acid (MSA), selenite, and selenomethionine, notably SAM depletion and increased SAM to SAH ratio by MSA, which implicates altered epigenetic regulation.

In vivo deep network tracing reveals phosphofructokinase-mediated coordination of biosynthetic pathway activity in the myocardium

Glucose metabolism comprises numerous amphibolic metabolites that provide precursors for not only the synthesis of cellular building blocks but also for ATP production. In this study, we tested how phosphofructokinase-1 (PFK1) activity controls the fate of glucose-derived carbon in murine hearts in vivo. PFK1 activity was regulated by cardiac-specific overexpression of kinase- or phosphatase-deficient 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase transgenes in mice (termed Glyco^Lo or Glyco^Hi mice, respectively). Dietary delivery of ¹³C₆-glucose to these mice, followed by deep network metabolic tracing, revealed that low rates of PFK1 activity promote selective routing of glucose-derived carbon to the purine synthesis pathway to form 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR). Consistent with a mechanism of physical channeling, we found multimeric protein complexes that contained phosphoribosylaminoimidazole carboxylase (PAICS)—an enzyme important for AICAR biosynthesis, as well as chaperone proteins such as Hsp90 and other metabolic enzymes. We also observed that PFK1 influenced glucose-derived carbon deposition in glycogen, but did not affect hexosamine biosynthetic pathway activity. These studies demonstrate the utility of deep network tracing to identify metabolic channeling and changes in biosynthetic pathway activity in the heart in vivo and present new potential mechanisms by which metabolic branchpoint reactions modulate biosynthetic pathways.

Interrogating in vivo T-cell metabolism in mice using stable isotope labeling metabolomics and rapid cell sorting

T cells are integral players in the adaptive immune system that readily adapt their metabolism to meet their energetic and biosynthetic needs. A major hurdle to understand physiologic T-cell metabolism has been the differences between in vitro cell culture conditions and the complex in vivo milieu. To address this, we have developed a protocol that merges traditional immunology infection models with whole-body metabolite infusion and mass-spectrometry-based metabolomic profiling to assess T-cell metabolism in vivo. In this protocol, pathogen-infected mice are infused via the tail vein with an isotopically labeled metabolite (2-6 h), followed by rapid magnetic bead isolation to purify T-cell populations (<1 h) and then stable isotope labeling analysis conducted by mass spectrometry (~1-2 d). This procedure enables researchers to evaluate metabolic substrate utilization into central carbon metabolic pathways (i.e., glycolysis and the tricarboxylic acid cycle) by specific T-cell subpopulations in the context of physiological immune responses in vivo.

Physiological impact of in vivo stable isotope tracing on cancer metabolism

Background

There is growing interest in the analysis of tumor metabolism to identify cancer-specific metabolic vulnerabilities and therapeutic targets. Finding of such candidate metabolic pathways mainly relies on the highly sensitive identification and quantitation of numerous metabolites and metabolic fluxes using metabolomics and isotope tracing analyses. However, nutritional requirements and metabolic routes used by cancer cells cultivated in vitro do not always reflect the metabolic demands of malignant cells within the tumor milieu. Therefore, to understand how the metabolism of tumor cells in its physiological environment differs from that of normal cells, these analyses must be performed in vivo.

Scope of Review

This review covers the physiological impact of the exogenous administration of a stable isotope tracer into cancer animal models. We discuss specific aspects of in vivo isotope tracing protocols based on discrete bolus injections of a labeled metabolite: the tracer administration per se and the fasting period prior to it. In addition, we illustrate the complex physiological scenarios that arise when studying tumor metabolism – by isotopic labeling in animal models fed with a specific amino acid restricted diet. Finally, we provide strategies to minimize these limitations.

Major Conclusions

There is growing evidence that metabolic dependencies in cancers are influenced by tissue environment, cancer lineage, and genetic events. An increasing number of studies describe discrepancies in tumor metabolic dependencies when studied in in vitro settings or in vivo models, including cancer patients. Therefore, in-depth in vivo profiling of tumor metabolic routes within the appropriate pathophysiological environment will be key to identify relevant alterations that contribute to cancer onset and progression.

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In vivo isotope tracing is the state-of-the-art approach to study tumor metabolism.

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In vivo tracer administration challenges the physiological metabolism of mice.

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Interorgan conversion of the tracer might confound tumor labeling patterns.

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Mouse fasting before in vivo tracing impacts on systemic and tumor metabolism.

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Optimization is key to minimize physiological alterations linked to in vivo tracing.

Brain glycogen serves as a critical glucosamine cache required for protein glycosylation

Glycosylation defects are a hallmark of many nervous system diseases. However, the molecular and metabolic basis for this pathology is not fully understood. In this study, we found that N-linked protein glycosylation in the brain is metabolically channeled to glucosamine metabolism through glycogenolysis. We discovered that glucosamine is an abundant constituent of brain glycogen, which functions as a glucosamine reservoir for multiple glycoconjugates. We demonstrated the enzymatic incorporation of glucosamine into glycogen by glycogen synthase, and the release by glycogen phosphorylase by biochemical and structural methodologies, in primary astrocytes, and in vivo by isotopic tracing and mass spectrometry. Using two mouse models of glycogen storage diseases, we showed that disruption of brain glycogen metabolism causes global decreases in free pools of UDP-N-acetylglucosamine and N-linked protein glycosylation. These findings revealed fundamental biological roles of brain glycogen in protein glycosylation with direct relevance to multiple human diseases of the central nervous system.

Very long chain fatty acid metabolism is required in acute myeloid leukemia

Acute myeloid leukemia (AML) cells have an atypical metabolic phenotype characterized by increased mitochondrial mass, as well as a greater reliance on oxidative phosphorylation and fatty acid oxidation (FAO) for survival. To exploit this altered metabolism, we assessed publicly available databases to identify FAO enzyme overexpression. Very long chain acyl-CoA dehydrogenase (VLCAD; ACADVL) was found to be overexpressed and critical to leukemia cell mitochondrial metabolism. Genetic attenuation or pharmacological inhibition of VLCAD hindered mitochondrial respiration and FAO contribution to the tricarboxylic acid cycle, resulting in decreased viability, proliferation, clonogenic growth, and AML cell engraftment. Suppression of FAO at VLCAD triggered an increase in pyruvate dehydrogenase activity that was insufficient to increase glycolysis but resulted in adenosine triphosphate depletion and AML cell death, with no effect on normal hematopoietic cells. Together, these results demonstrate the importance of VLCAD in AML cell biology and highlight a novel metabolic vulnerability for this devastating disease.

Stable Isotope-Resolved Metabolomics Reveals the Abnormal Brain Glucose Catabolism in Depression Based on Chronic Unpredictable Mild Stress Rats

The severe harm of depression to human life has attracted great attention to neurologists, but its pathogenesis is extremely complicated and has not yet been fully elaborated. Here, we provided a new strategy for revealing the specific pathways of abnormal brain glucose catabolism in depression, based on the supply of energy substrates and the evaluation of the mitochondrial structure and function. By using stable isotope-resolved metabolomics, we discovered that the tricarboxylic acid cycle (TCA cycle) is blocked and gluconeogenesis is abnormally activated in chronic unpredictable mild stress (CUMS) rats. In addition, our results showed an interesting phenomenon that the brain attempted to activate all possible metabolic enzymes in energy-producing pathways, but CUMS rats still exhibited a low TCA cycle activity due to impaired mitochondria. Depression caused the mitochondrial structure and function to be impaired and then led to abnormal brain glucose catabolism. The combination of the stable isotope-resolved metabolomics and mitochondrial structure and function analysis can accurately clarify the mechanism of depression. The mitochondrial pyruvate carrier and acetyl-CoA may be the key targets for depression treatment. The strategy provides a unique insight for exploring the mechanism of depression, the discovery of new targets, and the development of ideal novel antidepressants. Data are available via ProteomeXchange with identifier PXD025548.

Capillary Electrophoresis-High Resolution Mass Spectrometry for Measuring In Vivo Arginine Isotope Incorporation in Alzheimer's Disease Mouse Models

Immune-based metabolic reprogramming of arginine utilization in the brain contributes to the neuronal pathology associated with Alzheimer's disease (AD). To enable our long-term goals of differentiation of AD mouse model genotypes, ages, and sexes based on activity of this pathway, we describe here the novel dosing (using uniformly labeled (¹³C₆¹⁵N₄) arginine) and analysis methods using capillary electrophoresis high-resolution accurate-mass mass spectrometry for isotope tracing of metabolic products of arginine. We developed a pseudoprimed infusion-dosing regimen, using repeated injections, to achieve a steady state of uniformly labeled arginine in 135-195 min post bolus dose. Incorporation of stable isotope labeled carbon and nitrogen from uniformly labeled arginine into a host of downstream metabolites was measured in vivo in mice using serially sampled dried blood spots from the tail. In addition to the dried blood spot time course samples, total isotope incorporation into arginine-related metabolites was measured in the whole brain and plasma after 285 min. Preliminary demonstration of the technique identified differences isotope incorporation in arginine metabolites between male and female mice in a mouse-model of sporadic Alzheimer's disease (APOE4/huNOS2). The technique described herein will permit arginine pathway activity differentiation between mouse genotypes, ages, sexes, or drug treatments in order to elucidate the contribution of this pathway to Alzheimer's disease.

NMR Analysis of Carboxylate Isotopomers of 13C-Metabolites by Chemoselective Derivatization with 15N-Cholamine

A substantial fraction of common metabolites contains carboxyl functional groups. Their ¹³C isotopomer analysis by nuclear magnetic resonance (NMR) is hampered by the low sensitivity of the ¹³C nucleus, the slow longitudinal relaxation for the lack of an attached proton, and the relatively low chemical shift dispersion of carboxylates. Chemoselective (CS) derivatization is a means of tagging compounds in a complex mixture via a specific functional group. ¹⁵N₁-cholamine has been shown to be a useful CS agent for carboxylates, producing a peptide bond that can be detected via ¹⁵N-attached H with high sensitivity in heteronuclear single quantum coherence experiments. Here, we report an improved method of derivatization and show how ¹³C-enrichment at the carboxylate and/or the adjacent carbon can be determined via one- and two-bond coupling of the carbons adjacent to the cholamine ¹⁵N atom in the derivatives. We have applied this method for the determination of ¹³C isotopomer distribution in the extracts of A549 cell culture and liver tissue from a patient-derived xenograft mouse.

Untargeted Stable Isotope Probing of the Gut Microbiota Metabolome Using 13C-Labeled Dietary Fibers

The gut microbiome generates numerous metabolites that exert local effects and enter the circulation to affect the functions of many organs. Despite extensive sequencing-based characterization of the gut microbiome, there remains a lack of understanding of microbial metabolism. Here, we developed an untargeted stable isotope-resolved metabolomics (SIRM) approach for the holistic study of gut microbial metabolites. Viable microbial cells were extracted from fresh mice feces and incubated anaerobically with ¹³C-labeled dietary fibers including inulin or cellulose. High-resolution mass spectrometry was used to monitor ¹³C enrichment in metabolites associated with glycolysis, the Krebs cycle, the pentose phosphate pathway, nucleotide synthesis, and pyruvate catabolism in both microbial cells and the culture medium. We observed the differential use of inulin and cellulose as substrates for biosynthesis of essential and non-essential amino acids, neurotransmitters, vitamin B5, and other coenzymes. Specifically, the use of inulin for these biosynthetic pathways was markedly more efficient than the use of cellulose, reflecting distinct metabolic pathways of dietary fibers in the gut microbiome, which could be related with host effects. This technology facilitates deeper and holistic insights into the metabolic function of the gut microbiome (Metabolomic Workbench Study ID: ST001651).

NMR Methods for Determining Lipid Turnover via Stable Isotope Resolved Metabolomics

Lipids comprise diverse classes of compounds that are important for the structure and properties of membranes, as high-energy fuel sources and as signaling molecules. Therefore, the turnover rates of these varied classes of lipids are fundamental to cellular function. However, their enormous chemical diversity and dynamic range in cells makes detailed analysis very complex. Furthermore, although stable isotope tracers enable the determination of synthesis and degradation of complex lipids, the numbers of distinguishable molecules increase enormously, which exacerbates the problem. Although LC-MS-MS (Liquid Chromatography-Tandem Mass Spectrometry) is the standard for lipidomics, NMR can add value in global lipid analysis and isotopomer distributions of intact lipids. Here, we describe new developments in NMR analysis for assessing global lipid content and isotopic enrichment of mixtures of complex lipids for two cell lines (PC3 and UMUC3) using both 13C6 glucose and 13C5 glutamine tracers.

An Ion Chromatography-Ultrahigh-Resolution-MS1/Data-Independent High-Resolution MS2 Method for Stable Isotope-Resolved Metabolomics Reconstruction of Central Metabolic Networks

The metabolome comprises a complex network of interconnecting enzyme-catalyzed reactions that involve transfers of numerous molecular subunits. Thus, the reconstruction of metabolic networks requires metabolite substructures to be tracked. Subunit tracking can be achieved by tracing stable isotopes through metabolic transformations using NMR and ultrahigh -resolution (UHR)-mass spectrometry (MS). UHR-MS¹ readily resolves and counts isotopic labels in metabolites but requires tandem MS to help identify isotopic enrichment in substructures. However, it is challenging to perform chromatography-based UHR-MS¹ with its long acquisition time, while acquiring MS² data on many coeluting labeled isotopologues for each metabolite. We have developed an ion chromatography (IC)-UHR-MS¹/data-independent(DI)-HR-MS² method to trace the fate of ¹³C atoms from [¹³C₆]-glucose ([¹³C₆]-Glc) in 3D A549 spheroids in response to anticancer selenite and simultaneously ¹³C/¹⁵N atoms from [¹³C₅,¹⁵N₂]-glutamine ([¹³C₅,¹⁵N₂]-Gln) in 2D BEAS-2B cells in response to arsenite transformation. This method retains the complete isotopologue distributions of metabolites via UHR-MS¹ while simultaneously acquiring substructure label information via DI-MS². These details in metabolite labeling patterns greatly facilitate rigorous reconstruction of multiple, intersecting metabolic pathways of central metabolism, which are illustrated here for the purine/pyrimidine nucleotide biosynthesis. The pathways reconstructed based on subunit-level isotopologue analysis further reveal specific enzyme-catalyzed reactions that are impacted by selenite or arsenite treatments.

Mitochondrial DNA alterations underlie an irreversible shift to aerobic glycolysis in fumarate hydratase-deficient renal cancer

Understanding the mechanisms of the Warburg shift to aerobic glycolysis is critical to defining the metabolic basis of cancer. Hereditary leiomyomatosis and renal cell carcinoma (HLRCC) is an aggressive cancer characterized by biallelic inactivation of the gene encoding the Krebs cycle enzyme fumarate hydratase, an early shift to aerobic glycolysis, and rapid metastasis. We observed impairment of the mitochondrial respiratory chain in tumors from patients with HLRCC. Biochemical and transcriptomic analyses revealed that respiratory chain dysfunction in the tumors was due to loss of expression of mitochondrial DNA (mtDNA)-encoded subunits of respiratory chain complexes, caused by a marked decrease in mtDNA content and increased mtDNA mutations. We demonstrated that accumulation of fumarate in HLRCC tumors inactivated the core factors responsible for replication and proofreading of mtDNA, leading to loss of respiratory chain components, thereby promoting the shift to aerobic glycolysis and disease progression in this prototypic model of glucose-dependent human cancer.

Multifocal Renal Cell Carcinomas With Somatic IDH2 Mutation: Report of a Previously Undescribed Neoplasm

Renal cell carcinoma (RCC) is a heterogenous disease composed of several different cancer types characterized by distinct histologies and genetic alterations, including mutation of the Krebs cycle enzyme genes for fumarate hydratase and succinate dehydrogenase (SDH). This report describes a patient with multifocal renal tumors that presented with a novel, biphasic histologic morphology with one component consisting of small cells growing in a diffuse pattern occasionally forming glandular and cystic structures, reminiscent of type 1 papillary RCC, and the other component having larger cells with abundant eosinophilic and clear cytoplasm and appearing in a solid pattern of growth. Genetic analysis of multiple tumors showed that all had a somatic mutation of the IDH2 gene that created the known pathogenic, gain-of-function p.R172M alteration that results in abnormal accumulation of the oncometabolite 2-hydroxyglutarate (2-HG). Analysis of multiple tumors demonstrated highly elevated levels of 2-HG and a CpG island methylator phenotype that is characteristic of 2-HG-related inhibition of the Ten-eleven translocation (TET) family of DNA demethylases. In combination with fumarate hydratase-deficient and succinate dehydrogenase-deficient RCCs that have increased levels of the fumarate and succinate oncometabolites, respectively, the mutation of isocitrate dehydrogenase 2 represents the third Krebs cycle enzyme alteration to be associated with oncometabolite-induced RCC tumorigenesis. This study associates the discovery of a new histologic presentation of RCC with the first report of an IDH2 gain-of-function mutation in RCC.

Oral Gavage Delivery of Stable Isotope Tracer for In Vivo Metabolomics

Stable isotope-resolved metabolomics (SIRM) is a powerful tool for understanding disease. Advances in SIRM techniques have improved isotopic delivery and expanded the workflow from exclusively in vitro applications to in vivo methodologies to study systemic metabolism. Here, we report a simple, minimally-invasive and cost-effective method of tracer delivery to study SIRM in vivo in laboratory mice. Following a brief fasting period, we orally administered a solution of [U-13C] glucose through a blunt gavage needle without anesthesia, at a physiological dose commonly used for glucose tolerance tests (2 g/kg bodyweight). We defined isotopic enrichment in plasma and tissue at 15, 30, 120, and 240 min post-gavage. 13C-labeled glucose peaked in plasma around 15 min post-gavage, followed by period of metabolic decay and clearance until 4 h. We demonstrate robust enrichment of a variety of central carbon metabolites in the plasma, brain and liver of C57/BL6 mice, including amino acids, neurotransmitters, and glycolytic and tricarboxylic acid (TCA) cycle intermediates. We then applied this method to study in vivo metabolism in two distinct mouse models of diseases known to involve dysregulation of glucose metabolism: Alzheimer's disease and type II diabetes. By delivering [U-13C] glucose via oral gavage to the 5XFAD Alzheimer's disease model and the Lepob/ob type II diabetes model, we were able to resolve significant differences in multiple central carbon pathways in both model systems, thus providing evidence of the utility of this method to study diseases with metabolic components. Together, these data clearly demonstrate the efficacy and efficiency of an oral gavage delivery method, and present a clear time course for 13C enrichment in plasma, liver and brain of mice following oral gavage of [U-13C] glucose-data we hope will aid other researchers in their own 13C-glucose metabolomics study design.

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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Using stable isotope tracers to monitor membrane dynamics in C. elegans

Membranes within an animal are composed of phospholipids, cholesterol, and proteins that together form a dynamic barrier. The types of lipids that are found within a membrane bilayer impact its biophysical properties including its fluidity, permeability, and susceptibility to damage. While membrane composition is very stable in healthy adults, aberrant membrane structure is seen in a wide and varied array of diseases as well as during natural aging. Despite the wide-reaching impacts of membrane composition, there is relatively little known about how membrane landscape is established and maintained over time. In vivo biochemical modeling of membrane lipids is needed to understand how these molecules interact in their natural configurations. Here, we have described analytical methods that increase the capacity to map the dynamics of individual membrane phospholipids using different types of mass spectrometry. Specifically, we describe novel stable isotope (¹³C and ¹⁵N) strategies to quantify the turnover of dozens of fatty acid tails and intact phospholipids simultaneously.

Loss of CLN3, the gene mutated in juvenile neuronal ceroid lipofuscinosis, leads to metabolic impairment and autophagy induction in retinal pigment epithelium

Juvenile neuronal ceroid lipofuscinosis (JNCL, aka. juvenile Batten disease or CLN3 disease) is a lysosomal storage disease characterized by progressive blindness, seizures, cognitive and motor failures, and premature death. JNCL is caused by mutations in the Ceroid Lipofuscinosis, Neuronal 3 (CLN3) gene, whose function is unclear. Although traditionally considered a neurodegenerative disease, CLN3 disease displays eye-specific effects: Vision loss not only is often one of the earliest symptoms of JNCL, but also has been reported in non-syndromic CLN3 disease. Here we described the roles of CLN3 protein in maintaining healthy retinal pigment epithelium (RPE) and normal vision. Using electroretinogram, fundoscopy and microscopy, we showed impaired visual function, retinal autofluorescent lesions, and RPE disintegration and metaplasia/hyperplasia in a Cln3 ~ 1 kb-deletion mouse model [1] on C57BL/6J background. Utilizing a combination of biochemical analyses, RNA-Seq, Seahorse XF bioenergetic analysis, and Stable Isotope Resolved Metabolomics (SIRM), we further demonstrated that loss of CLN3 increased autophagic flux, suppressed mTORC1 and Akt activities, enhanced AMPK activity, and up-regulated gene expression of the autophagy-lysosomal system in RPE-1 cells, suggesting autophagy induction. This CLN3 deficiency induced autophagy induction coincided with decreased mitochondrial oxygen consumption, glycolysis, the tricarboxylic acid (TCA) cycle, and ATP production. We also reported for the first time that loss of CLN3 led to glycogen accumulation despite of impaired glycogen synthesis. Our comprehensive analyses shed light on how loss of CLN3 affect autophagy and metabolism. This work suggests possible links among metabolic impairment, autophagy induction and lysosomal storage, as well as between RPE atrophy/degeneration and vision loss in JNCL.

Resolving Metabolic Heterogeneity in Experimental Models of the Tumor Microenvironment from a Stable Isotope Resolved Metabolomics Perspective

The tumor microenvironment (TME) comprises complex interactions of multiple cell types that determines cell behavior and metabolism such as nutrient competition and immune suppression. We discuss the various types of heterogeneity that exist in solid tumors, and the complications this invokes for studies of TME. As human subjects and in vivo model systems are complex and difficult to manipulate, simpler 3D model systems that are compatible with flexible experimental control are necessary for studying metabolic regulation in TME. Stable Isotope Resolved Metabolomics (SIRM) is a valuable tool for tracing metabolic networks in complex systems, but at present does not directly address heterogeneous metabolism at the individual cell level. We compare the advantages and disadvantages of different model systems for SIRM experiments, with a focus on lung cancer cells, their interactions with macrophages and T cells, and their response to modulators in the immune microenvironment. We describe the experimental set up, illustrate results from 3D cultures and co-cultures of lung cancer cells with human macrophages, and outline strategies to address the heterogeneous TME.

Metabolic reprogramming in tumors: Contributions of the tumor microenvironment

The genetic alterations associated with cell transformation are in large measure expressed in the metabolic phenotype as cancer cells proliferate and change their local environment, and prepare for metastasis. Qualitatively, the fundamental biochemistry of cancer cells is generally the same as in the untransformed cells, but the cancer cells produce a local environment, the TME, that is hostile to the stromal cells, and compete for nutrients. In order to proliferate, cells need sufficient nutrients, either those that cannot be made by the cells themselves, or must be made from simpler precursors. However, in solid tumors, the nutrient supply is often limiting given the potential for rapid proliferation, and the poor quality of the vasculature. Thus, cancer cells may employ a variety of strategies to obtain nutrients for survival, growth and metastasis. Although much has been learned using established cell lines in standard culture conditions, it is becoming clear from in vivo metabolic studies that this can also be misleading, and which nutrients are used for energy production versus building blocks for synthesis of macromolecules can vary greatly from tumor to tumor, and even within the same tumor. Here we review the operation of metabolic networks, and how recent understanding of nutrient supply in the TME and utilization are being revealed using stable isotope tracers in vivo as well as in vitro.

Metabolic flux analysis and fluxomics-driven determination of reaction free energy using multiple isotopes

Metabolite concentrations, fluxes, and free energies constitute the basis for understanding and controlling metabolism. Mass spectrometry and stable isotopes are integral tools in quantifying these metabolic features. For absolute metabolite concentration and flux measurement, ¹³C internal standards and tracers have been the gold standard. In contrast, no established methods exist for comprehensive thermodynamic quantitation under physiological environments. Recently, using high-resolution mass spectrometry and multi-isotope tracing, flux quantitation has been increasingly adopted in broader metabolism. The improved flux quantitation led to determination of Gibbs free energy of reaction (ΔG) in central carbon metabolism using a relationship between reaction reversibility and thermodynamic driving force. Here we highlight recent advances in multi-isotope tracing for metabolic flux and free energy analysis.

Glutaminase-1 (GLS1) inhibition limits metastatic progression in osteosarcoma

BACKGROUND

Osteosarcoma (OS) is a malignant bone tumor that often develops during the period of rapid growth associated with adolescence. Despite successful primary tumor control accompanied by adjuvant chemotherapy, death from pulmonary metastases occurs in approximately 30% of patients within 5 years. As overall survival in patients remains unchanged over the last 30 years, urgent needs for novel therapeutic strategies exist. Cancer metastasis is characterized by complex molecular events which result from alterations in gene and protein expression/function. Recent studies suggest that metabolic adaptations, or "metabolic reprogramming," may similarly contribute to cancer metastasis. The goal of this study was to specifically interrogate the metabolic vulnerabilities of highly metastatic OS cell lines in a series of in vitro and in vivo experiments, in order to identify a tractable metabolically targeted therapeutic strategy for patients.

METHODS

Nutrient deprivation and drug treatment experiments were performed in MG63.3, 143B, and K7M2 OS cell lines to identify the impact of glutaminase-1 (GLS1) inhibition and metformin treatment on cell proliferation. We functionally validated the impact of drug treatment with extracellular flux analysis, nuclear magnetic resonance (NMR) spectroscopy, and mass spectrometry. 13C-glucose and 13C-glutamine tracing was employed to identify specific contributions of these nutrients to the global metabolic profiles generated with GLS1 inhibition and metformin treatment in vivo.

RESULTS

Highly metastatic OS cell lines require glutamine for proliferation, and exposure to CB-839, in combination with metformin, induces both primary tumor growth inhibition and a distinct reduction in metastatic outgrowth in vivo. Further, combination-treated OS cells showed a reduction in cellular mitochondrial respiration, while NMR confirmed the pharmacodynamic effects of glutaminase inhibition in tumor tissues. We observed global decreases in glycolysis and tricarboxylic acid (TCA) cycle functionality, alongside an increase in fatty acid oxidation and pyrimidine catabolism.

CONCLUSIONS

This data suggests combination-treated cells cannot compensate for metformin-induced electron transport chain inhibition by upregulating glutaminolysis to generate TCA cycle intermediates required for cell proliferation, translating into significant reductions in tumor growth and metastatic progression. This therapeutic approach could be considered for future clinical development for OS patients presenting with or at high risk of developing metastasis.

Functional Genomics Reveals Synthetic Lethality between Phosphogluconate Dehydrogenase and Oxidative Phosphorylation

The plasticity of a preexisting regulatory circuit compromises the effectiveness of targeted therapies, and leveraging genetic vulnerabilities in cancer cells may overcome such adaptations. Hereditary leiomyomatosis renal cell carcinoma (HLRCC) is characterized by oxidative phosphorylation (OXPHOS) deficiency caused by fumarate hydratase (FH) nullizyogosity. To identify metabolic genes that are synthetically lethal with OXPHOS deficiency, we conducted a genetic loss-of-function screen and found that phosphogluconate dehydrogenase (PGD) inhibition robustly blocks the proliferation of FH mutant cancer cells both in vitro and in vivo. Mechanistically, PGD inhibition blocks glycolysis, suppresses reductive carboxylation of glutamine, and increases the NADP⁺/NADPH ratio to disrupt redox homeostasis. Furthermore, in the OXPHOS-proficient context, blocking OXPHOS using the small-molecule inhibitor IACS-010759 enhances sensitivity to PGD inhibition in vitro and in vivo. Together, our study reveals a dependency on PGD in OXPHOS-deficient tumors that might inform therapeutic intervention in specific patient populations.

Applications of Chromatography-Ultra High-Resolution MS for Stable Isotope-Resolved Metabolomics (SIRM) Reconstruction of Metabolic Networks

Metabolism is a complex network of compartmentalized and coupled chemical reactions, which often involve transfers of substructures of biomolecules, thus requiring metabolite substructures to be tracked. Stable isotope resolved metabolomics (SIRM) enables pathways reconstruction, even among chemically identical metabolites, by tracking the provenance of stable isotope-labeled substructures using NMR and ultrahigh resolution (UHR) MS. The latter can resolve and count isotopic labels in metabolites and can identify isotopic enrichment in substructures when operated in tandem MS mode. However, MS2 is difficult to implement with chromatography-based UHR-MS due to lengthy MS1 acquisition time that is required to obtain the molecular isotopologue count, which is further exacerbated by the numerous isotopologue source ions to fragment. We review here recent developments in tandem MS applications of SIRM to obtain more detailed information about isotopologue distributions in metabolites and their substructures.

Improved workflow for mass spectrometry-based metabolomics analysis of the heart

MS-based metabolomics methods are powerful techniques to map the complex and interconnected metabolic pathways of the heart; however, normalization of metabolite abundance to sample input in heart tissues remains a technical challenge. Herein, we describe an improved GC-MS-based metabolomics workflow that uses insoluble protein-derived glutamate for the normalization of metabolites within each sample and includes normalization to protein-derived amino acids to reduce biological variation and detect small metabolic changes. Moreover, glycogen is measured within the metabolomics workflow. We applied this workflow to study heart metabolism by first comparing two different methods of heart removal: the Langendorff heart method (reverse aortic perfusion) and in situ freezing of mouse heart with a modified tissue freeze-clamp approach. We then used the in situ freezing method to study the effects of acute β-adrenergic receptor stimulation (through isoproterenol (ISO) treatment) on heart metabolism. Using our workflow and within minutes, ISO reduced the levels of metabolites involved in glycogen metabolism, glycolysis, and the Krebs cycle, but the levels of pentose phosphate pathway metabolites and of many free amino acids remained unchanged. This observation was coupled to a 6-fold increase in phosphorylated adenosine nucleotide abundance. These results support the notion that ISO acutely accelerates oxidative metabolism of glucose to meet the ATP demand required to support increased heart rate and cardiac output. In summary, our MS-based metabolomics workflow enables improved quantification of cardiac metabolites and may also be compatible with other methods such as LC or capillary electrophoresis.

Stable Isotopes for Tracing Mammalian-Cell Metabolism In Vivo

Metabolism is at the cornerstone of all cellular functions and mounting evidence of its deregulation in different diseases emphasizes the importance of a comprehensive understanding of metabolic regulation at the whole-organism level. Stable-isotope measurements are a powerful tool for probing cellular metabolism and, as a result, are increasingly used to study metabolism in in vivo settings. The additional complexity of in vivo metabolic measurements requires paying special attention to experimental design and data interpretation. Here, we review recent work where in vivo stable-isotope measurements have been used to address relevant biological questions within an in vivo context, summarize different experimental and data interpretation approaches and their limitations, and discuss future opportunities in the field.