Quantifying reductive carboxylation flux of glutamine to lipid in a brown adipocyte cell line

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.

A Lacticaseibacillus rhamnosus secretome induces immunoregulatory transcriptional, functional and immunometabolic signatures in human THP-1 monocytes

Macrophage responses to activation are fluid and dynamic in their ability to respond appropriately to challenges, a role integral to host defence. While bacteria can influence macrophage differentiation and polarization into pro-inflammatory and alternatively activated phenotypes through direct interactions, many questions surround indirect communication mechanisms mediated through secretomes derived from gut bacteria, such as lactobacilli. We examined effects of secretome-mediated conditioning on THP-1 human monocytes, focusing on the ability of the Lacticaseibacillus rhamnosus R0011 secretome (LrS) to drive macrophage differentiation and polarization and prime immune responses to subsequent challenge with lipopolysaccharide (LPS). Genome-wide transcriptional profiling revealed increased M2-associated gene transcription in response to LrS conditioning in THP-1 cells. Cytokine and chemokine profiling confirmed these results, indicating increased M2-associated chemokine and cytokine production (IL-1Ra, IL-10). These cells had increased cell-surface marker expression of CD11b, CD86, and CX3CR1, coupled with reduced expression of the M1 macrophage-associated marker CD64. Mitochondrial substrate utilization assays indicated diminished reliance on glycolytic substrates, coupled with increased utilization of citric acid cycle intermediates, characteristics of functional M2 activity. LPS challenge of LrS-conditioned THP-1s revealed heightened responsiveness, indicative of innate immune priming. Resting stage THP-1 macrophages co-conditioned with LrS and retinoic acid also displayed an immunoregulatory phenotype with expression of CD83, CD11c and CD103 and production of regulatory cytokines. Secretome-mediated conditioning of macrophages into an immunoregulatory phenotype is an uncharacterized and potentially important route through which lactic acid bacteria and the gut microbiota may train and shape innate immunity at the gut-mucosal interface.

A citric acid cycle-deficient Escherichia coli as an efficient chassis for aerobic fermentations

Tricarboxylic acid cycle (TCA cycle) plays an important role for aerobic growth of heterotrophic bacteria. Theoretically, eliminating TCA cycle would decrease carbon dissipation and facilitate chemicals biosynthesis. Here, we construct an E. coli strain without a functional TCA cycle that can serve as a versatile chassis for chemicals biosynthesis. We first use adaptive laboratory evolution to recover aerobic growth in minimal medium of TCA cycle-deficient E. coli. Inactivation of succinate dehydrogenase is a key event in the evolutionary trajectory. Supply of succinyl-CoA is identified as the growth limiting factor. By replacing endogenous succinyl-CoA dependent enzymes, we obtain an optimized TCA cycle-deficient E. coli strain. As a proof of concept, the strain is engineered for high-yield production of four separate products. This work enhances our understanding of the role of the TCA cycle in E. coli metabolism and demonstrates the advantages of using TCA cycle-deficient E. coli strain for biotechnological applications.

Boundary flux analysis: an emerging strategy for investigating metabolic pathway activity in large cohorts

Many biological phenotypes are rooted in metabolic pathway activity rather than the concentrations of individual metabolites. Despite this, most metabolomics studies only capture steady-state metabolism - not metabolic flux. Although sophisticated metabolic flux analysis strategies have been developed, these methods are technically challenging and difficult to implement in large-cohort studies. Recently, a new boundary flux analysis (BFA) approach has emerged that captures large-scale metabolic flux phenotypes by quantifying changes in metabolite levels in the media of cultured cells. This approach is advantageous because it is relatively easy to implement yet captures complex metabolic flux phenotypes. We describe the opportunities and challenges of BFA and illustrate how it can be harnessed to investigate a wide transect of biological phenomena.

Metabolic flux analysis in adipose tissue reprogramming

Obesity is a growing epidemic in the United States and worldwide and is associated with insulin resistance and cardiovascular disease, among other comorbidities. Understanding of the pathology that links overnutrition to these disease processes is ongoing. Adipose tissue is a heterogeneous organ comprised of multiple different cell types and it is likely that dysregulated metabolism within these cell populations disrupts both inter- and intracellular interactions and is a key driver of human disease. In recent years, metabolic flux analysis, which offers a precise quantification of metabolic pathway fluxes in biological systems, has emerged as a candidate strategy for uncovering the metabolic changes that stoke these disease processes. In this mini review, we discuss metabolic flux analysis as an experimental tool, with a specific emphasis on mass spectrometry with isotope tracing as this is the technique most frequently used for metabolic flux analysis in adipocytes. Furthermore, we examine existing literature that uses metabolic flux analysis to further our understanding of adipose tissue biology. Our group has a specific interest in understanding the role of white adipose tissue inflammation in the progression of cardiometabolic disease, as we know that in obesity the accumulation of pro-inflammatory adipose tissue macrophages is associated with significant morbidity, so we use this as a paradigm throughout our review for framing the application of these experimental techniques. However, there are many other biological applications to which they can be applied to further understanding of not only adipose tissue biology but also systemic homeostasis.

Toward Systems-Level Metabolic Analysis in Endocrine Disorders and Cancer

Metabolism is a dynamic network of biochemical reactions that support systemic homeostasis amidst changing nutritional, environmental, and physical activity factors. The circulatory system facilitates metabolite exchange among organs, while the endocrine system finely tunes metabolism through hormone release. Endocrine disorders like obesity, diabetes, and Cushing's syndrome disrupt this balance, contributing to systemic inflammation and global health burdens. They accompany metabolic changes on multiple levels from molecular interactions to individual organs to the whole body. Understanding how metabolic fluxes relate to endocrine disorders illuminates the underlying dysregulation. Cancer is increasingly considered a systemic disorder because it not only affects cells in localized tumors but also the whole body, especially in metastasis. In tumorigenesis, cancer-specific mutations and nutrient availability in the tumor microenvironment reprogram cellular metabolism to meet increased energy and biosynthesis needs. Cancer cachexia results in metabolic changes to other organs like muscle, adipose tissue, and liver. This review explores the interplay between the endocrine system and systems-level metabolism in health and disease. We highlight metabolic fluxes in conditions like obesity, diabetes, Cushing's syndrome, and cancers. Recent advances in metabolomics, fluxomics, and systems biology promise new insights into dynamic metabolism, offering potential biomarkers, therapeutic targets, and personalized medicine.

Determination of Metabolic Fluxes by Deep Learning of Isotope Labeling Patterns

Fluxomics offers a direct readout of metabolic state but relies on indirect measurement. Stable isotope tracers imprint flux-dependent isotope labeling patterns on metabolites we measure; however, the relationship between labeling patterns and fluxes remains elusive. Here we innovate a two-stage machine learning framework termed ML-Flux that streamlines metabolic flux quantitation from isotope tracing. We train machine learning models by simulating atom transitions across five universal metabolic models starting from 26 13C-glucose, 2H-glucose, and 13C-glutamine tracers within feasible flux space. ML-Flux employs deep-learning-based imputation to take variable measurements of labeling patterns as input and successive neural networks to convert the ensuing comprehensive labeling information into metabolic fluxes. Using ML-Flux with multi-isotope tracing, we obtain fluxes through central carbon metabolism that are comparable to those from a least-squares method but orders-of-magnitude faster. ML-Flux is deployed as a webtool to expand the accessibility of metabolic flux quantitation and afford actionable information on metabolism.

Cell-culture process optimization via model-based predictions of metabolism and protein glycosylation

In order to meet the rising demand for biologics and become competitive on the developing biosimilar market, there is a need for process intensification of biomanufacturing processes. Process development of biologics has historically relied on extensive experimentation to develop and optimize biopharmaceutical manufacturing. Experimentation to optimize media formulations, feeding schedules, bioreactor operations and bioreactor scale up is expensive, labor intensive and time consuming. Mathematical modeling frameworks have the potential to enable process intensification while reducing the experimental burden. This review focuses on mathematical modeling of cellular metabolism and N-linked glycosylation as applied to upstream manufacturing of biologics. We review developments in the field of modeling cellular metabolism of mammalian cells using kinetic and stoichiometric modeling frameworks along with their applications to simulate, optimize and improve mechanistic understanding of the process. Interest in modeling N-linked glycosylation has led to the creation of various types of parametric and non-parametric models. Most published studies on mammalian cell metabolism have performed experiments in shake flasks where the pH and dissolved oxygen cannot be controlled. Efforts to understand and model the effect of bioreactor-specific parameters such as pH, dissolved oxygen, temperature, and bioreactor heterogeneity are critically reviewed. Most modeling efforts have focused on the Chinese Hamster Ovary (CHO) cells, which are most commonly used to produce monoclonal antibodies (mAbs). However, these modeling approaches can be generalized and applied to any mammalian cell-based manufacturing platform. Current and potential future applications of these models for Vero cell-based vaccine manufacturing, CAR-T cell therapies, and viral vector manufacturing are also discussed. We offer specific recommendations for improving the applicability of these models to industrially relevant processes.

Mitochondrial Metabolism in the Spotlight: Maintaining Balanced RNAP III Activity Ensures Cellular Homeostasis

RNA polymerase III (RNAP III) holoenzyme activity and the processing of its products have been linked to several metabolic dysfunctions in lower and higher eukaryotes. Alterations in the activity of RNAP III-driven synthesis of non-coding RNA cause extensive changes in glucose metabolism. Increased RNAP III activity in the S. cerevisiae maf1Δ strain is lethal when grown on a non-fermentable carbon source. This lethal phenotype is suppressed by reducing tRNA synthesis. Neither the cause of the lack of growth nor the underlying molecular mechanism have been deciphered, and this area has been awaiting scientific explanation for a decade. Our previous proteomics data suggested mitochondrial dysfunction in the strain. Using model mutant strains maf1Δ (with increased tRNA abundance) and rpc128-1007 (with reduced tRNA abundance), we collected data showing major changes in the TCA cycle metabolism of the mutants that explain the phenotypic observations. Based on 13C flux data and analysis of TCA enzyme activities, the present study identifies the flux constraints in the mitochondrial metabolic network. The lack of growth is associated with a decrease in TCA cycle activity and downregulation of the flux towards glutamate, aspartate and phosphoenolpyruvate (PEP), the metabolic intermediate feeding the gluconeogenic pathway. rpc128-1007, the strain that is unable to increase tRNA synthesis due to a mutation in the C128 subunit, has increased TCA cycle activity under non-fermentable conditions. To summarize, cells with non-optimal activity of RNAP III undergo substantial adaptation to a new metabolic state, which makes them vulnerable under specific growth conditions. Our results strongly suggest that balanced, non-coding RNA synthesis that is coupled to glucose signaling is a fundamental requirement to sustain a cell's intracellular homeostasis and flexibility under changing growth conditions. The presented results provide insight into the possible role of RNAP III in the mitochondrial metabolism of other cell types.

FreeFlux: A Python Package for Time-Efficient Isotopically Nonstationary Metabolic Flux Analysis

13C metabolic flux analysis is a powerful tool for metabolism characterization in metabolic engineering and synthetic biology. However, the widespread adoption of this tool is hindered by limited software availability and computational efficiency. Currently, the most widely accepted 13C-flux tools, such as INCA and 13CFLUX2, are developed in a closed-source environment. While several open-source packages or software are available, they are either computationally inefficient or only suitable for flux estimation at isotopic steady state. To address the need for a time-efficient computational tool for the more complicated flux analysis at an isotopically nonstationary state, especially for understanding the single-carbon substrate metabolism, we present FreeFlux. FreeFlux is an open-source Python package that performs labeling pattern simulation and flux analysis at both isotopic steady state and transient state, enabling a more comprehensive analysis of cellular metabolism. FreeFlux provides a set of interfaces to manipulate the objects abstracted from a labeling experiment and computational process, making it easy to integrate into other programs or pipelines. The flux estimation by FreeFlux is fast and reliable, and its validity has been confirmed by comparison with results from other computational tools using both synthetic and experimental data. FreeFlux is freely available at https://github.com/Chaowu88/freeflux with a detailed online tutorial and documentation provided at https://freeflux.readthedocs.io/en/latest/index.html.

FASN deficiency induces a cytosol-to-mitochondria citrate flux to mitigate detachment-induced oxidative stress

Fatty acid synthase (FASN) maintains de novo lipogenesis (DNL) to support rapid growth in most proliferating cancer cells. Lipogenic acetyl-coenzyme A (CoA) is primarily produced from carbohydrates but can arise from glutamine-dependent reductive carboxylation. Here, we show that reductive carboxylation also occurs in the absence of DNL. In FASN-deficient cells, reductive carboxylation is mainly catalyzed by isocitrate dehydrogenase-1 (IDH1), but IDH1-generated cytosolic citrate is not utilized for supplying DNL. Metabolic flux analysis (MFA) shows that FASN deficiency induces a net cytosol-to-mitochondria citrate flux through mitochondrial citrate transport protein (CTP). Previously, a similar pathway has been shown to mitigate detachment-induced oxidative stress in anchorage-independent tumor spheroids. We further report that tumor spheroids show reduced FASN activity and that FASN-deficient cells acquire resistance to oxidative stress in a CTP- and IDH1-dependent manner. Collectively, these data indicate that by inducing a cytosol-to-mitochondria citrate flux, anchorage-independent malignant cells can gain redox capacity by trading off FASN-supported rapid growth.

Complex I deficiency in m.3243A>G fibroblasts is alleviated by reducing NADH accumulation

Introduction: Mitochondrial disease is a spectrum of debilitating disorders caused by mutations in the mitochondrial DNA (mtDNA) or nuclear DNA that compromises the respiratory chain. Mitochondrial 3243A>G (m.3243 A>G) is the most common mutation showing great heterogeneity in phenotype. Previous studies have indicated that NADH: ubiquinone oxidoreductase (complex I) deficiency accompanied by a decreased nicotinamide adenine dinucleotide (NAD+)/reduced NAD+ (NADH) ratio may play a pivotal role in the pathogenesis of m.3243A>G mutation. Methods: To evaluate the potential effects of strategies targeting the imbalanced NAD+/NADH ratio in m.3243A>G mutation, we treated fibroblasts derived from patients with the m.3243 A>G mutation using nicotinamide riboside (NR) or mitochondria-targeted H2O-forming NADH oxidase (mitoLbNOX). Results: M.3243 A>G fibroblasts showed a significant reduction in complex I core subunit 6, complex I enzymatic activity, complex I-dependent oxygen consumption rate (OCR), and adenosine triphosphate (ATP) production compared to the controls. The NAD+/NADH ratio was also significantly reduced in m.3243 A>G fibroblasts, and, using fluorescence lifetime imaging microscopy, we also found that the NADH level was elevated in m.3243 A>G fibroblasts. After NR treatment, the NAD+/NADH ratio, complex I-dependent OCR, and ATP levels increased, whereas NADH levels remained unchanged. More excitingly, after treatment with mitoLbNOX, the NAD+/NADH ratio, complex I-independent OCR, and ATP levels increased more pronouncedly compared with the NR treatment group, accompanied by significantly reduced NADH levels. Discussion: The present study suggests that compared with repletion of NAD+ alone, the combination of this therapeutic modality with alleviation of NADH overload may amplify the treatment effect of restoring NAD+/NADH balance in m.3243A>G fibroblasts.

Impaired BCAA catabolism in adipose tissues promotes age-associated metabolic derangement

Adipose tissues are central in controlling metabolic homeostasis and failure in their preservation is associated with age-related metabolic disorders. The exact role of mature adipocytes in this phenomenon remains elusive. Here we describe the role of adipose branched-chain amino acid (BCAA) catabolism in this process. We found that adipocyte-specific Crtc2 knockout protected mice from age-associated metabolic decline. Multiomics analysis revealed that BCAA catabolism was impaired in aged visceral adipose tissues, leading to the activation of mechanistic target of rapamycin complex (mTORC1) signaling and the resultant cellular senescence, which was restored by Crtc2 knockout in adipocytes. Using single-cell RNA sequencing analysis, we found that age-associated decline in adipogenic potential of visceral adipose tissues was reinstated by Crtc2 knockout, via the reduction of BCAA-mTORC1 senescence-associated secretory phenotype axis. Collectively, we propose that perturbation of BCAA catabolism by CRTC2 is critical in instigating age-associated remodeling of adipose tissue and the resultant metabolic decline in vivo.

Quantitative analysis of metabolic fluxes in brown fat and skeletal muscle during thermogenesis

Adaptive thermogenesis by brown adipose tissue (BAT) dissipates calories as heat, making it an attractive anti-obesity target. Yet how BAT contributes to circulating metabolite exchange remains unclear. Here, we quantified metabolite exchange in BAT and skeletal muscle by arteriovenous metabolomics during cold exposure in fed male mice. This identified unexpected metabolites consumed, released and shared between organs. Quantitative analysis of tissue fluxes showed that glucose and lactate provide ~85% of carbon for adaptive thermogenesis and that cold and CL316,243 trigger markedly divergent fuel utilization profiles. In cold adaptation, BAT also dramatically increases nitrogen uptake by net consuming amino acids, except glutamine. Isotope tracing and functional studies suggest glutamine catabolism concurrent with synthesis via glutamine synthetase, which avoids ammonia buildup and boosts fuel oxidation. These data underscore the ability of BAT to function as a glucose and amino acid sink and provide a quantitative and comprehensive landscape of BAT fuel utilization to guide translational studies.

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.

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.

Targeting glutaminase 1 (GLS1) by small molecules for anticancer therapeutics

Glutaminase-1 (GLS1) is a critical enzyme involved in several cellular processes, and its overexpression has been linked to the development and progression of cancer. Based on existing research, GLS1 plays a crucial role in the metabolic activities of cancer cells, promoting rapid proliferation, cell survival, and immune evasion. Therefore, targeting GLS1 has been proposed as a promising cancer therapy strategy, with several GLS1 inhibitors currently under development. To date, several GLS1 inhibitors have been identified, which can be broadly classified into two types: active site and allosteric inhibitors. Despite their pre-clinical effectiveness, only a few number of these inhibitors have advanced to initial clinical trials. Hence, the present medical research emphasizes the need for developing small molecule inhibitors of GLS1 possessing significantly high potency and selectivity. In this manuscript, we aim to summarize the regulatory role of GLS1 in physiological and pathophysiological processes. We also provide a comprehensive overview of the development of GLS1 inhibitors, focusing on multiple aspects such as target selectivity, in vitro and in vivo potency and structure-activity relationships.

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.

FAMetA: a mass isotopologue-based tool for the comprehensive analysis of fatty acid metabolism

The use of stable isotope tracers and mass spectrometry (MS) is the gold standard method for the analysis of fatty acid (FA) metabolism. Yet, current state-of-the-art tools provide limited and difficult-to-interpret information about FA biosynthetic routes. Here we present FAMetA, an R package and a web-based application (www.fameta.es) that uses 13C mass isotopologue profiles to estimate FA import, de novo lipogenesis, elongation and desaturation in a user-friendly platform. The FAMetA workflow covers the required functionalities needed for MS data analyses. To illustrate its utility, different in vitro and in vivo experimental settings are used in which FA metabolism is modified. Thanks to the comprehensive characterization of FA biosynthesis and the easy-to-interpret graphical representations compared to previous tools, FAMetA discloses unnoticed insights into how cells reprogram their FA metabolism and, when combined with FASN, SCD1 and FADS2 inhibitors, it enables the identification of new FAs by the metabolic reconstruction of their synthesis route.

FASN-deficiency induces a cytosol-to-mitochondria citrate flux to mitigate detachment-induced oxidative stress

Fatty acid synthase (FASN) maintains de novo lipogenesis (DNL) to support rapid growth in most proliferating cancer cells. Lipogenic acetyl-CoA is primarily produced from carbohydrates but can arise from glutamine-dependent reductive carboxylation under hypoxia. Here we show that reductive carboxylation also occurs in the absence of DNL in cells with defective FASN. In this state, reductive carboxylation was mainly catalyzed by isocitrate dehydrogenase-1 (IDH1) in the cytosol, but IDH1-generated citrate was not used for DNL. Metabolic flux analysis (MFA) revealed that FASN-deficiency induced a net cytosol-to-mitochondria citrate flux through citrate transport protein (CTP). A similar pathway was previously shown to mitigate detachment-induced mitochondrial reactive oxygen species (mtROS) in anchorage-independent tumor spheroids. We further demonstrate that FASN-deficient cells acquire resistance to oxidative stress in a CTP- and IDH1-dependent manner. Together with the reduced FASN activity in tumor spheroids, these data indicate that anchorage-independent malignant cells trade FASN-supported rapid growth for a cytosol-to-mitochondria citrate flux to gain redox capacity against detachment-induced oxidative stress.

13C-Metabolic flux analysis of 3T3-L1 adipocytes illuminates its core metabolism under hypoxia

Hypoxia has been identified as a major factor in the pathogenesis of adipose tissue inflammation, which is a hallmark of obesity and obesity-linked type 2 diabetes mellitus. In this study, we have investigated the impact of hypoxia (1% oxygen) on the physiology and metabolism of 3T3-L1 adipocytes, a widely used cell culture model of adipose. Specifically, we applied parallel labeling experiments, isotopomer spectral analysis, and ¹³C-metabolic flux analysis to quantify the impact of hypoxia on adipogenesis, de novo lipogenesis and metabolic flux reprogramming in adipocytes. We found that 3T3-L1 cells can successfully differentiate into lipid-accumulating adipocytes under hypoxia, although the production of lipids was reduced by about 40%. Quantitative flux analysis demonstrated that short-term (1 day) and long-term (7 days) exposure to hypoxia resulted in similar reprogramming of cellular metabolism. Overall, we found that hypoxia: 1) reduced redox and energy generation by more than 2-fold and altered the patterns of metabolic pathway contributions to production and consumption of energy and redox cofactors; 2) redirected glucose metabolism from pentose phosphate pathway and citric acid cycle to lactate production; 3) rewired glutamine metabolism, from net glutamine production to net glutamine catabolism; 4) suppressed branched chain amino acid consumption; and 5) reduced biosynthesis of odd-chain fatty acids and mono-unsaturated fatty acids, while synthesis of saturated even-chain fatty acids was not affected. Together, these results highlight the profound impact of extracellular microenvironment on adipocyte metabolic activity and function.

The Interleukin-11/IL-11 Receptor Promotes Glioblastoma Survival and Invasion under Glucose-Starved Conditions through Enhanced Glutaminolysis

Glioblastoma cells adapt to changes in glucose availability through metabolic plasticity allowing for cell survival and continued progression in low-glucose concentrations. However, the regulatory cytokine networks that govern the ability to survive in glucose-starved conditions are not fully defined. In the present study, we define a critical role for the IL-11/IL-11Rα signalling axis in glioblastoma survival, proliferation and invasion when cells are starved of glucose. We identified enhanced IL-11/IL-11Rα expression correlated with reduced overall survival in glioblastoma patients. Glioblastoma cell lines over-expressing IL-11Rα displayed greater survival, proliferation, migration and invasion in glucose-free conditions compared to their low-IL-11Rα-expressing counterparts, while knockdown of IL-11Rα reversed these pro-tumorigenic characteristics. In addition, these IL-11Rα-over-expressing cells displayed enhanced glutamine oxidation and glutamate production compared to their low-IL-11Rα-expressing counterparts, while knockdown of IL-11Rα or the pharmacological inhibition of several members of the glutaminolysis pathway resulted in reduced survival (enhanced apoptosis) and reduced migration and invasion. Furthermore, IL-11Rα expression in glioblastoma patient samples correlated with enhanced gene expression of the glutaminolysis pathway genes GLUD1, GSS and c-Myc. Overall, our study identified that the IL-11/IL-11Rα pathway promotes glioblastoma cell survival and enhances cell migration and invasion in environments of glucose starvation via glutaminolysis.

Dysregulated Lipid Synthesis by Oncogenic IDH1 Mutation Is a Targetable Synthetic Lethal Vulnerability

Isocitrate dehydrogenase 1 and 2 (IDH) are mutated in multiple cancers and drive production of (R)-2-hydroxyglutarate (2HG). We identified a lipid synthesis enzyme [acetyl CoA carboxylase 1 (ACC1)] as a synthetic lethal target in mutant IDH1 (mIDH1), but not mIDH2, cancers. Here, we analyzed the metabolome of primary acute myeloid leukemia (AML) blasts and identified an mIDH1-specific reduction in fatty acids. mIDH1 also induced a switch to b-oxidation indicating reprogramming of metabolism toward a reliance on fatty acids. Compared with mIDH2, mIDH1 AML displayed depletion of NADPH with defective reductive carboxylation that was not rescued by the mIDH1-specific inhibitor ivosidenib. In xenograft models, a lipid-free diet markedly slowed the growth of mIDH1 AML, but not healthy CD34+ hematopoietic stem/progenitor cells or mIDH2 AML. Genetic and pharmacologic targeting of ACC1 resulted in the growth inhibition of mIDH1 cancers not reversible by ivosidenib. Critically, the pharmacologic targeting of ACC1 improved the sensitivity of mIDH1 AML to venetoclax.

SIGNIFICANCE

Oncogenic mutations in both IDH1 and IDH2 produce 2-hydroxyglutarate and are generally considered equivalent in terms of pathogenesis and targeting. Using comprehensive metabolomic analysis, we demonstrate unexpected metabolic differences in fatty acid metabolism between mutant IDH1 and IDH2 in patient samples with targetable metabolic interventions. See related commentary by Robinson and Levine, p. 266. This article is highlighted in the In This Issue feature, p. 247.

Lipid droplets and ferroptosis as new players in brain cancer glioblastoma progression and therapeutic resistance

A primary brain tumor glioblastoma is the most lethal of all cancers and remains an extremely challenging disease. Apparent oncogenic signaling in glioblastoma is genetically complex and raised at any stage of the disease's progression. Many clinical trials have shown that anticancer drugs for any specific oncogene aberrantly expressed in glioblastoma show very limited activity. Recent discoveries have highlighted that alterations in tumor metabolism also contribute to disease progression and resistance to current therapeutics for glioblastoma, implicating an alternative avenue to improve outcomes in glioblastoma patients. The roles of glucose, glutamine and tryptophan metabolism in glioblastoma pathogenesis have previously been described. This article provides an overview of the metabolic network and regulatory changes associated with lipid droplets that suppress ferroptosis. Ferroptosis is a newly discovered type of nonapoptotic programmed cell death induced by excessive lipid peroxidation. Although few studies have focused on potential correlations between tumor progression and lipid droplet abundance, there has recently been increasing interest in identifying key players in lipid droplet biology that suppress ferroptosis and whether these dependencies can be effectively exploited in cancer treatment. This article discusses how lipid droplet metabolism, including lipid synthesis, storage, and use modulates ferroptosis sensitivity or tolerance in different cancer models, focusing on glioblastoma.

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.

De novo pyrimidine synthesis is a targetable vulnerability in IDH mutant glioma

Mutations affecting isocitrate dehydrogenase (IDH) enzymes are prevalent in glioma, leukemia, and other cancers. Although mutant IDH inhibitors are effective against leukemia, they seem to be less active in aggressive glioma, underscoring the need for alternative treatment strategies. Through a chemical synthetic lethality screen, we discovered that IDH1-mutant glioma cells are hypersensitive to drugs targeting enzymes in the de novo pyrimidine nucleotide synthesis pathway, including dihydroorotate dehydrogenase (DHODH). We developed a genetically engineered mouse model of mutant IDH1-driven astrocytoma and used it and multiple patient-derived models to show that the brain-penetrant DHODH inhibitor BAY 2402234 displays monotherapy efficacy against IDH-mutant gliomas. Mechanistically, this reflects an obligate dependence of glioma cells on the de novo pyrimidine synthesis pathway and mutant IDH's ability to sensitize to DNA damage upon nucleotide pool imbalance. Our work outlines a tumor-selective, biomarker-guided therapeutic strategy that is poised for clinical translation.

Metabolic flux analysis: a comprehensive review on sample preparation, analytical techniques, data analysis, computational modelling, and main application areas

Metabolic flux analysis (MFA) quantitatively describes cellular fluxes to understand metabolic phenotypes and functional behaviour after environmental and/or genetic perturbations. In the last decade, the application of stable isotopes became extremely important to determine and integrate in vivo measurements of metabolic reactions in systems biology. 13C-MFA is one of the most informative methods used to study central metabolism of biological systems. This review aims to outline the current experimental procedure adopted in 13C-MFA, starting from the preparation of cell cultures and labelled tracers to the quenching and extraction of metabolites and their subsequent analysis performed with very powerful software. Here, the limitations and advantages of nuclear magnetic resonance spectroscopy and mass spectrometry techniques used in carbon labelled experiments are elucidated by reviewing the most recent published papers. Furthermore, we summarise the most successful approaches used for computational modelling in flux analysis and the main application areas with a particular focus in metabolic engineering.

Amino acid metabolism: challenges and opportunities for the therapeutic treatment of leukemia and lymphoma

Leukemia and lymphoma-the most common hematological malignant diseases-are often accompanied by complications such as drug resistance, refractory diseases and relapse. Amino acids (AAs) are important energy sources for malignant cells. Tumor-mediated AA metabolism is associated with the immunosuppressive properties of the tumor microenvironment, thereby assisting malignant cells to evade immune surveillance. Targeting abnormal AA metabolism in the tumor microenvironment may be an effective therapeutic approach to address the therapeutic challenges of leukemia and lymphoma. Here, we review the effects of glutamine, arginine and tryptophan metabolism on tumorigenesis and immunomodulation, and define the differences between tumor cells and immune effector cells. We also comment on treatments targeting these AA metabolism pathways in lymphoma and leukemia and discuss how these treatments have profound adverse effects on tumor cells, but leave the immune cells unaffected or mildly affected.

Hyperpolarized [5-13C,4,4-2H2,5-15N]-L-glutamine provides a means of annotating in vivo metabolic utilization of glutamine

Glutamine is the most abundant amino acid in human plasma, although it is challenging to determine glutamine’s metabolic fate noninvasively. In this work, we utilize established chemical methods to develop a platform for imaging glutamine metabolism using hyperpolarized magnetic resonance imaging. Using this strategy, we are able to spatially measure glutaminolysis in vivo as well as develop a biomarker for the inhibition of glutaminase. Combining this biomarker with isotope tracing metabolomics connects this inhibition to reduced glutamine contribution to the tricarboxylic acid cycle. This provides an approach for future imaging of glutamine metabolism in humans.

Glutamine is consumed by rapidly proliferating cells and can provide the carbon and nitrogen required for growth through various metabolic pathways. However, delineating the metabolic fate of glutamine is challenging to interrogate in vivo. Hyperpolarized magnetic resonance, by providing high transient nuclear magnetic resonance signals, provides an approach to measure fast biochemical processes in vivo. Aminohydrolysis of glutamine at carbon-5 plays an important role in providing nitrogen and carbon for multiple pathways. Here, we provide a synthetic strategy for isotope-enriched forms of glutamine that prolongs glutamine-C5 relaxation times and thereby reveals in vivo reactions involving carbon-5. We investigate multiple enrichment states, finding [5-¹³C,4,4-²H₂,5-¹⁵N]-L-glutamine to be optimal for hyperpolarized measurement of glutamine conversion to glutamate in vivo. Leveraging this compound, we explore pancreatic cancer glutamine metabolism in vivo. Taken together, this work provides a means for studying glutamine metabolic flux in vivo and demonstrates on-target effects of metabolic enzyme inhibitors.

Hot isopropanol quenching procedure for automated microtiter plate scale 13C-labeling experiments

Background

Currently, the generation of genetic diversity for microbial cell factories outpaces the screening of strain variants with omics-based phenotyping methods. Especially isotopic labeling experiments, which constitute techniques aimed at elucidating cellular phenotypes and supporting rational strain design by growing microorganisms on substrates enriched with heavy isotopes, suffer from comparably low throughput and the high cost of labeled substrates.

Results

We present a miniaturized, parallelized, and automated approach to ¹³C-isotopic labeling experiments by establishing and validating a hot isopropanol quenching method on a robotic platform coupled with a microbioreactor cultivation system. This allows for the first time to conduct automated labeling experiments at a microtiter plate scale in up to 48 parallel batches. A further innovation enabled by the automated quenching method is the analysis of free amino acids instead of proteinogenic ones on said microliter scale. Capitalizing on the latter point and as a proof of concept, we present an isotopically instationary labeling experiment in Corynebacterium glutamicum ATCC 13032, generating dynamic labeling data of free amino acids in the process.

Conclusions

Our results show that a robotic liquid handler is sufficiently fast to generate informative isotopically transient labeling data. Furthermore, the amount of biomass obtained from a sub-milliliter cultivation in a microbioreactor is adequate for the detection of labeling patterns of free amino acids. Combining the innovations presented in this study, isotopically stationary and instationary automated labeling experiments can be conducted, thus fulfilling the prerequisites for ¹³C-metabolic flux analyses in high-throughput.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-022-01806-4.

Carbon sources and pathways for citrate secreted by human prostate cancer cells determined by NMR tracing and metabolic modeling

The human prostate accumulates high luminal citrate levels to serve sperm viability. There is only indirect qualitative evidence about metabolic pathways and carbon sources maintaining these levels. Human citrate-secreting prostate cancer cells were supplied with ¹³C-labeled substrates, and NMR spectra of extracellular fluid were recorded. We report absolute citrate production rates of prostate cells and direct evidence that glucose is the main carbon source for secreted citrate. Pyruvate carboxylase provides sufficient anaplerotic carbons to support citrate secretion. Glutamine carbons exchange with carbons for secreted citrate but are likely not involved in its net synthesis. Moreover, we developed metabolic models employing the ¹³C distribution in extracellular citrate as input to assess intracellular pathways followed by carbons toward citrate.

Prostate epithelial cells have the unique capacity to secrete large amounts of citrate, but the carbon sources and metabolic pathways that maintain this production are not well known. We mapped potential pathways for citrate carbons in the human prostate cancer metastasis cell lines LNCaP and VCaP, for which we first established that they secrete citrate (For LNCaP 5.6 ± 0.9 nmol/h per 10⁶ cells). Using ¹³C-labeled substrates, we traced the incorporation of ¹³C into citrate by NMR of extracellular fluid. Our results provide direct evidence that glucose is a main carbon source for secreted citrate. We also demonstrate that carbons from supplied glutamine flow via oxidative Krebs cycle and reductive carboxylation routes to positions in secreted citrate but likely do not contribute to its net synthesis. The potential anaplerotic carbon sources aspartate and asparagine did not contribute to citrate carbons. We developed a quantitative metabolic model employing the ¹³C distribution in extracellular citrate after ¹³C glucose and pyruvate application to assess intracellular pathways of carbons for secreted citrate. From this model, it was estimated that in LNCaP about 21% of pyruvate entering the Krebs cycle is converted via pyruvate carboxylase as an anaplerotic route at a rate more than sufficient to compensate carbon loss of this cycle by citrate secretion. This model provides an estimation of the fraction of molecules, including citrate, leaving the Krebs cycle at every turn. The measured ratios of ¹³C atoms at different positions in extracellular citrate may serve as biomarkers for (malignant) epithelial cell metabolism.

The mTOR/PGC-1α/SIRT3 Pathway Drives Reductive Glutamine Metabolism to Reduce Oxidative Stress Caused by ISKNV in CPB Cells

Under oxidative stress, viruses prefer glycolysis as an ATP source, and glutamine is required as an anaplerotic substrate to replenish the TCA cycle. Infectious spleen and kidney necrosis virus (ISKNV) induces reductive glutamine metabolism in the host cells. Here we report that ISKNV infection the increased NAD+/NADH ratio and the gene expression of glutaminase 1 (GLS1), glutamate dehydrogenase (GDH), and isocitrate dehydrogenase (IDH2) resulted in the phosphorylation and activation of mammalian target of rapamycin (mTOR) in CPB cells. Inhibition of mTOR signaling attenuates ISKNV-induced the upregulation of GLS1, GDH, and IDH2 genes expression, and exhibits significant antiviral activity. Moreover, the expression of silent information regulation 2 homolog 3 (SIRT3) in mRNA level is increased to enhance the reductive glutamine metabolism in ISKNV-infected cells. And those were verified by the expression levels of metabolic genes and the activities of metabolic enzymes in SIRT3-overexpressed or SIRT3-knocked down cells. Remarkably, activation of mTOR signaling upregulates the expression of the peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α) gene, leading to increased expression of SIRT3 and metabolic genes. These results indicate that mTOR signaling manipulates reductive glutamine metabolism in ISKNV-infected cells through PGC-1α-dependent regulation of SIRT3. Our findings reveal new insights on ISKNV-host interactions and will contribute new cellular targets to antiviral therapy. IMPORTANCE Infectious spleen and kidney necrosis virus (ISKNV) is the causative agent of farmed fish disease that has caused huge economic losses in fresh and marine fish aquaculture. The redox state of cells is shaped by virus into a favorable microenvironment for virus replication and proliferation. Our previous study demonstrated that ISKNV replication induced glutamine metabolism reprogramming, and it is necessary for the ISKNV multiplication. In this study, the mechanistic link between the mTOR/PGC-1α/SIRT3 pathway and reductive glutamine metabolism in the ISKNV-infected cells was provided, which will contribute new insights into the pathogenesis of ISKNV and antiviral treatment strategies.

Adapting isotopic tracer and metabolic flux analysis approaches to study C1 metabolism

Single-carbon (C1, or one-carbon) substrates are promising feedstocks for sustainable biofuel and biochemical production. Crucial to the goal of engineering C1-utilizing strains for improved production is a quantitative understanding of the organization, regulation and rates of the reactions that underpin C1 metabolism. ¹³C Metabolic flux analysis (MFA) is a well-established platform for interrogating these questions with multi-carbon substrates, and uses the differential labeling of metabolites that results from feeding a substrate with position-specific incorporation of ¹³C in order to infer quantitative fluxes and pathway topology. Adapting isotopic tracer approaches to C1 metabolism, where position-specific substrate labeling is impossible, requires additional experimental considerations. Here we review recent studies that have developed isotopic tracer approaches to overcome the challenge of uniform metabolite labeling and provide quantitative insight into C1 metabolism.

Advancing Cancer Treatment by Targeting Glutamine Metabolism—A Roadmap

Simple Summary

Dysregulated glutamine metabolism is one of the metabolic features evident in cancer cells when compared to normal cells. Cancer cells utilize glutamine for energy generation as well as the synthesis of other molecules that are critical for cancer growth and progression. Therefore, drugs targeting glutamine metabolism have been extensively investigated. However, inhibition of glutamine metabolism in cancer cells results in the activation of other metabolic pathways enabling cancer cells to survive. In this review, we summarize and discuss the targets in glutamine metabolism, which has been probed in the development of anticancer drugs in preclinical and clinical studies. We further discuss pathways activated in response to glutamine metabolism inhibition, enabling cancer cells to survive the challenge. Finally, we put into perspective combined treatment strategies targeting glutamine metabolism along with other pathways as potential treatment options.

Abstract

Tumor growth and metastasis strongly depend on adapted cell metabolism. Cancer cells adjust their metabolic program to their specific energy needs and in response to an often challenging tumor microenvironment. Glutamine metabolism is one of the metabolic pathways that can be successfully targeted in cancer treatment. The dependence of many hematological and solid tumors on glutamine is associated with mitochondrial glutaminase (GLS) activity that enables channeling of glutamine into the tricarboxylic acid (TCA) cycle, generation of ATP and NADPH, and regulation of glutathione homeostasis and reactive oxygen species (ROS). Small molecules that target glutamine metabolism through inhibition of GLS therefore simultaneously limit energy availability and increase oxidative stress. However, some cancers can reprogram their metabolism to evade this metabolic trap. Therefore, the effectiveness of treatment strategies that rely solely on glutamine inhibition is limited. In this review, we discuss the metabolic and molecular pathways that are linked to dysregulated glutamine metabolism in multiple cancer types. We further summarize and review current clinical trials of glutaminolysis inhibition in cancer patients. Finally, we put into perspective strategies that deploy a combined treatment targeting glutamine metabolism along with other molecular or metabolic pathways and discuss their potential for clinical applications.

Wild-type isocitrate dehydrogenase under the spotlight in glioblastoma

Brain tumors actively reprogram their cellular metabolism to survive and proliferate, thus offering potential therapeutic opportunities. Over the past decade, extensive research has been done on mutant IDH enzymes as markers of good prognosis in glioblastoma, a highly aggressive brain tumor in adults with dismal prognosis. Yet, 95% of glioblastoma are IDH wild-type. Here, we review current knowledge about IDH wild-type enzymes and their putative role in mechanisms driving tumor progression. After a brief overview on tumor metabolic adaptation, we present the diverse metabolic function of IDH enzymes and their roles in glioblastoma initiation, progression and response to treatments. Finally, we will discuss wild-type IDH targeting in primary glioblastoma.

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.

Hypoxia Induces Saturated Fatty Acids Accumulation and Reduces Unsaturated Fatty Acids Independently of Reverse Tricarboxylic Acid Cycle in L6 Myotubes

Obstructive sleep apnea syndrome, characterized by repetitive episodes of tissue hypoxia, is associated with several metabolic impairments. Role of fatty acids and lipids attracts attention in its pathogenesis for their metabolic effects. Parallelly, hypoxia-induced activation of reverse tricarboxylic acid cycle (rTCA) with reductive glutamine metabolism provides precursor molecules for de novo lipogenesis. Gas-permeable cultureware was used to culture L6-myotubes in chronic hypoxia (12%, 4% and 1% O₂) with ¹³C labelled glutamine and inhibitors of glutamine uptake or rTCA-mediated lipogenesis. We investigated changes in lipidomic profile, ¹³C appearance in rTCA-related metabolites, gene and protein expression of rTCA-related proteins and glutamine transporters, glucose uptake and lactate production. Lipid content increased by 308% at 1% O_2, predominantly composed of saturated fatty acids, while triacylglyceroles containing unsaturated fatty acids and membrane lipids (phosphatidylcholines, phosphatidylethanolamines, phosphatidylinositol) decreased by 20-70%. rTCA labelling of malate, citrate and 2-hydroxyglutarate increased by 4.7-fold, 2.2-fold and 1.9-fold in 1% O₂, respectively. ATP-dependent citrate lyase inhibition in 1% O₂ decreased lipid amount by 23% and increased intensity of triacylglyceroles containing unsaturated fatty acids by 56-80%. Lactate production increased with hypoxia. Glucose uptake dropped by 75% with progression of hypoxia from 4% to 1% O₂. Protein expression remained unchanged. Altogether, hypoxia modified cell metabolism leading to lipid composition alteration and rTCA activation.

Coordinated reprogramming of metabolism and cell function in adipocytes from proliferation to differentiation

Adipose tissue plays a major role in regulating lipid and energy homeostasis by storing excess nutrients, releasing energetic substrates through lipolysis, and regulating metabolism of other tissues and organs through endocrine and paracrine signaling. Adipocytes within fat tissues store excess nutrients through increased cell number (hyperplasia), increased cell size (hypertrophy), or both. The differentiation of pre-adipocytes into mature lipid-accumulating adipocytes requires a complex interaction of metabolic pathways that is still incompletely understood. Here, we applied parallel labeling experiments and ¹³C-metabolic flux analysis to quantify precise metabolic fluxes in proliferating and differentiated 3T3-L1 cells, a widely used model to study adipogenesis. We found that morphological and biomass composition changes in adipocytes were accompanied by significant shifts in metabolic fluxes, encompassing all major metabolic pathways. In contrast to proliferating cells, differentiated adipocytes 1) increased glucose uptake and redirected glucose utilization from lactate production to lipogenesis and energy generation; 2) increased pathway fluxes through glycolysis, oxidative pentose phosphate pathway and citric acid cycle; 3) reduced lactate secretion, resulting in increased ATP generation via oxidative phosphorylation; 4) rewired glutamine metabolism, from glutaminolysis to de novo glutamine synthesis; 5) increased cytosolic NADPH production, driven mostly by increased cytosolic malic enzyme flux; 6) increased production of monounsaturated C16:1; and 7) activated a mitochondrial pyruvate cycle through simultaneous activity of pyruvate carboxylase, malate dehydrogenase and malic enzyme. Taken together, these results quantitatively highlight the complex interplay between pathway fluxes and cell function in adipocytes, and suggest a functional role for metabolic reprogramming in adipose differentiation and lipogenesis.

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.

Glutamine Homeostasis and Its Role in the Adaptive Strategies of the Blind Mole Rat, Spalax

Oxidative metabolism is fine-tuned machinery that combines two tightly coupled fluxes of glucose and glutamine-derived carbons. Hypoxia interrupts the coordination between the metabolism of these two nutrients and leads to a decrease of the system efficacy and may eventually cause cell death. The subterranean blind mole rat, Spalax, is an underexplored, underground, hypoxia-tolerant mammalian group which spends its life under sharply fluctuating oxygen levels. Primary Spalax cells are an exceptional model to study the metabolic strategies that have evolved in mammals inhabiting low-oxygen niches. In this study we explored the metabolic frame of glutamine (Gln) homeostasis in Spalax skin cells under normoxic and hypoxic conditions and their impacts on the metabolism of rat cells. Targeted metabolomics employing liquid chromatography and mass spectrometry (LC-MS) was used to track the fate of heavy glutamine carbons (¹³C₅ Gln) after 24 h under normoxia or hypoxia (1% O₂). Our results indicated that large amounts of glutamine-originated carbons were detected as proline (Pro) and hydroxyproline (HPro) in normoxic Spalax cells with a further increase under hypoxia, suggesting a strategy for reduced Gln carbons storage in proteins. The intensity of the flux and the presence of HPro suggests collagen as a candidate protein that is most abundant in animals, and as the primary source of HPro. An increased conversion of αKG to 2 HG that was indicated in hypoxic Spalax cells prevents the degradation of hypoxia-inducible factor 1α (HIF-1α) and, consequently, maintains cytosolic and mitochondrial carbons fluxes that were uncoupled via inhibition of the pyruvate dehydrogenase complex. A strong antioxidant defense in Spalax cells can be attributed, at least in part, to the massive usage of glutamine-derived glutamate for glutathione (GSH) production. The present study uncovers additional strategies that have evolved in this unique mammal to support its hypoxia tolerance, and probably contribute to its cancer resistance, longevity, and healthy aging.

mfapy: An open-source Python package for 13C-based metabolic flux analysis

¹³C-based metabolic flux analysis (¹³C-MFA) is an essential tool for estimating intracellular metabolic flux levels in metabolic engineering and biology. In ¹³C-MFA, a metabolic flux distribution that explains the observed isotope labeling data was computationally estimated using a non-linear optimization method. Herein, we report the development of mfapy, an open-source Python package developed for more flexibility and extensibility for ¹³C-MFA. mfapy compels users to write a customized Python code by describing each step in the data analysis procedures of the isotope labeling experiments. The flexibility and extensibility provided by mfapy can support trial-and-error performance in the routine estimation of metabolic flux distributions, experimental design by computer simulations of ¹³C-MFA experiments, and development of new data analysis techniques for stable isotope labeling experiments. mfapy is available to the public from the Github repository (https://github.com/fumiomatsuda/mfapy).

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An open-source Python package, mfapy, is developed for ¹³C-MFA.

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mfapy enables users to write Python codes for data analysis procedures of ¹³C-MFA.

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mfapy has a flexibility and extensibility to support various data analysis procedures.

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Computer simulations of ¹³C-MFA experiments is supported for experimental design.

In vivo isotope tracing reveals the versatility of glucose as a brown adipose tissue substrate

Active brown adipose tissue (BAT) consumes copious amounts of glucose, yet how glucose metabolism supports thermogenesis is unclear. By combining transcriptomics, metabolomics, and stable isotope tracing in vivo, we systematically analyze BAT glucose utilization in mice during acute and chronic cold exposure. Metabolite profiling reveals extensive temperature-dependent changes in the BAT metabolome and transcriptome upon cold adaptation, discovering unexpected metabolite markers of thermogenesis, including increased N-acetyl-amino acid production. Time-course stable isotope tracing further reveals rapid incorporation of glucose carbons into glycolysis and TCA cycle, as well as several auxiliary pathways, including NADPH, nucleotide, and phospholipid synthesis pathways. Gene expression differences inconsistently predict glucose fluxes, indicating that posttranscriptional mechanisms also govern glucose utilization. Surprisingly, BAT swiftly generates fatty acids and acyl-carnitines from glucose, suggesting that lipids are rapidly synthesized and immediately oxidized. These data reveal versatility in BAT glucose utilization, highlighting the value of an integrative-omics approach to understanding organ metabolism.

Pyruvate carboxylase supports basal ATP-linked respiration in human pluripotent stem cell-derived brown adipocytes

Brown adipocytes (BA) are a specialized fat cell which possesses a high capacity for fuel oxidation combined with heat production. The maintenance of high metabolic activity in BA requires elevated oxidation of fuel through the tricarboxylic acid cycle. Pyruvate carboxylase (PC) was previously proposed to be essential for coordination between fuel oxidation and thermogenesis. By differentiating human pluripotent stem cells to mature BA in vitro, we showed that ablation of PC gene by CRISPR Cas9 genome engineering did not impair the ability of stem cells to generate mature BA. However, brown adipocytes deficient for PC expression displayed a 35% reduction in ATP-linked respiration, but not thermogenesis under both basal and isoproterenol-stimulated conditions. This relatively mild impairment of ATP-link respiration in PC knockout BA was protected by increased spare mitochondrial respiratory capacity. Taken together, this study highlights the role of PC in supporting fuel oxidation rather than thermogenesis in human BA.

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.

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.

Preclinical techniques to investigate exercise training in vascular pathophysiology

Atherosclerosis is a dynamic process starting with endothelial dysfunction and inflammation and eventually leading to life-threatening arterial plaques. Exercise generally improves endothelial function in a dose-dependent manner by altering hemodynamics, specifically by increased arterial pressure, pulsatility, and shear stress. However, athletes who regularly participate in high-intensity training can develop arterial plaques, suggesting alternative mechanisms through which excessive exercise promotes vascular disease. Understanding the mechanisms that drive atherosclerosis in sedentary versus exercise states may lead to novel rehabilitative methods aimed at improving exercise compliance and physical activity. Preclinical tools, including in vitro cell assays, in vivo animal models, and in silico computational methods, broaden our capabilities to study the mechanisms through which exercise impacts atherogenesis, from molecular maladaptation to vascular remodeling. Here, we describe how preclinical research tools have and can be used to study exercise effects on atherosclerosis. We then propose how advanced bioengineering techniques can be used to address gaps in our current understanding of vascular pathophysiology, including integrating in vitro, in vivo, and in silico studies across multiple tissue systems and size scales. Improving our understanding of the antiatherogenic exercise effects will enable engaging, targeted, and individualized exercise recommendations to promote cardiovascular health rather than treating cardiovascular disease that results from a sedentary lifestyle.

Deuterium Tracing to Interrogate Compartment-Specific NAD(P)H Metabolism in Cultured Mammalian Cells

Oxidation-reduction (redox) reactions are ubiquitous in biology and typically occur in specific subcellular compartments. In cells, the electron transfer between molecules and organelles is commonly facilitated by pyridine nucleotides such as nicotinamide adenine dinucleotide phosphate (NADPH) and nicotinamide adenine dinucleotide (NADH). While often taken for granted, these metabolic reactions are critically important for maintaining redox homeostasis and biochemical potentials across membranes. While ¹³C tracing and metabolic flux analysis (MFA) have emerged as powerful tools to study intracellular metabolism, this approach is limited when applied to pathways catalyzed in multiple cellular compartments. To address this issue, we and others have applied ²H (deuterium) tracers to observe transfer of labeled hydride anions, which accompanies electron transfer. Furthermore, we have developed a reporter system for indirectly quantifying NADPH enrichment in specific subcellular compartments. Here, we provide a detailed description of ²H tracing applications and the interrogation of mitochondrial versus cytosolic NAD(P)H metabolism in cultured mammalian cells. Specifically, we describe the generation of reporter cell lines that express epitope-tagged R132H-IDH1 or R172K-IDH2 and produce (D)2-hydroxyglutarate in a doxycycline-dependent manner. These tools and methods allow for quantitation of reducing equivalent turnover rates, the directionality of pathways present in multiple compartments, and the estimation of pathway contributions to NADPH pools.

Cancer Cell Metabolites: Updates on Current Tracing Methods

Cancer is the second leading cause of death-1 in 6 deaths globally is due to cancer. Cancer metabolism is a complex and one of the most actively researched area in cancer biology. Metabolic reprogramming in cancer cells entails activities that involve several enzymes and metabolites to convert nutrient into building blocks that alter energy metabolism to fuel rapid cell division. Metabolic dependencies in cancer generate signature metabolites that have key regulatory roles in tumorigenesis. In this minireview, we highlight recent advances in the popular methods ingrained in biochemistry research such as stable and flux isotope analysis, as well as radioisotope labeling, which are valuable in elucidating cancer metabolites. These methods together with analytical tools such as chromatography, nuclear magnetic resonance spectroscopy and mass spectrometry have helped to bring about exploratory work in understanding the role of important as well as obscure metabolites in cancer cells. Information obtained from these analyses significantly contribute in the diagnosis and prognosis of tumors leading to potential therapeutic targets for cancer therapy.