A guide to 13C metabolic flux analysis for the cancer biologist. Exp Mol Med. 2018;50:1-13. [PMID: 29657327 PMCID: PMC5938039 DOI: 10.1038/s12276-018-0060-y]

Quantitative metabolic fluxes regulated by trans-omic networks

Cells change their metabolism in response to internal and external conditions by regulating the trans-omic network, which is a global biochemical network with multiple omic layers. Metabolic flux is a direct measure of the activity of a metabolic reaction that provides valuable information for understanding complex trans-omic networks. Over the past decades, techniques to determine metabolic fluxes, including 13C-metabolic flux analysis (13C-MFA), flux balance analysis (FBA), and kinetic modeling, have been developed. Recent studies that acquire quantitative metabolic flux and multi-omic data have greatly advanced the quantitative understanding and prediction of metabolism-centric trans-omic networks. In this review, we present an overview of 13C-MFA, FBA, and kinetic modeling as the main techniques to determine quantitative metabolic fluxes, and discuss their advantages and disadvantages. We also introduce case studies with the aim of understanding complex metabolism-centric trans-omic networks based on the determination of metabolic fluxes.

Multi-omics-based label-free metabolic flux inference reveals obesity-associated dysregulatory mechanisms in liver glucose metabolism

Glucose homeostasis is maintained by modulation of metabolic flux. Enzymes and metabolites regulate the involved metabolic pathways. Dysregulation of glucose homeostasis is a pathological event in obesity. Analyzing metabolic pathways and the mechanisms contributing to obesity-associated dysregulation in vivo is challenging. Here, we introduce OMELET: Omics-Based Metabolic Flux Estimation without Labeling for Extended Trans-omic Analysis. OMELET uses metabolomic, proteomic, and transcriptomic data to identify relative changes in metabolic flux, and to calculate contributions of metabolites, enzymes, and transcripts to the changes in metabolic flux. By evaluating the livers of fasting ob/ob mice, we found that increased metabolic flux through gluconeogenesis resulted primarily from increased transcripts, whereas that through the pyruvate cycle resulted from both increased transcripts and changes in substrates of metabolic enzymes. With OMELET, we identified mechanisms underlying the obesity-associated dysregulation of metabolic flux in the liver.

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We developed OMELET to infer metabolic flux from label-free multi-omic data

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Contributions of metabolites, enzymes, and transcripts for flux were inferred

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Gluconeogenic flux increased in fasting ob/ob mice by increased transcripts

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Increased pyruvate cycle fluxes were led by increased transcripts and substrates

Glucose-6-phosphatase catalytic subunit 2 negatively regulates glucose oxidation and insulin secretion in pancreatic β-cells

Elevated fasting blood glucose (FBG) is associated with increased risks of developing type 2 diabetes (T2D) and cardiovascular-associated mortality. G6PC2 is predominantly expressed in islets, encodes a glucose-6-phosphatase catalytic subunit that converts glucose-6-phosphate (G6P) to glucose, and has been linked with variations in FBG in genome-wide association studies. Deletion of G6pc2 in mice has been shown to lower FBG without affecting fasting plasma insulin levels in vivo. At 5 mM glucose, pancreatic islets from G6pc2 knockout (KO) mice exhibit no glucose cycling, increased glycolytic flux, and enhanced glucose-stimulated insulin secretion (GSIS). However, the broader effects of G6pc2 KO on β-cell metabolism and redox regulation are unknown. Here we used CRISPR/Cas9 gene editing and metabolic flux analysis in βTC3 cells, a murine pancreatic β-cell line, to examine the role of G6pc2 in regulating glycolytic and mitochondrial fluxes. We found that deletion of G6pc2 led to ∼60% increases in glycolytic and citric acid cycle (CAC) fluxes at both 5 and 11 mM glucose concentrations. Furthermore, intracellular insulin content and GSIS were enhanced by approximately two-fold, along with increased cytosolic redox potential and reductive carboxylation flux. Normalization of fluxes relative to net glucose uptake revealed upregulation in two NADPH-producing pathways in the CAC. These results demonstrate that G6pc2 regulates GSIS by modulating not only glycolysis but also, independently, citric acid cycle activity in β-cells. Overall, our findings implicate G6PC2 as a potential therapeutic target for enhancing insulin secretion and lowering FBG, which could benefit individuals with prediabetes, T2D, and obesity.

MetAMDB: Metabolic Atom Mapping Database

MetAMDB is an open-source metabolic atom mapping database, providing atom mappings for around 43,000 metabolic reactions. Each atom mapping can be inspected and downloaded either as an RXN file or as a graphic in SVG format. In addition, MetAMDB offers the possibility of automatically creating atom mapping models based on user-specified metabolic networks. These models can be of any size (small to genome-scale) and can subsequently be used in standard 13C metabolic flux analysis software.

Enrichment of the exocytosis protein STX4 in skeletal muscle remediates peripheral insulin resistance and alters mitochondrial dynamics via Drp1

Mitochondrial dysfunction is implicated in skeletal muscle insulin resistance. Syntaxin 4 (STX4) levels are reduced in human diabetic skeletal muscle, and global transgenic enrichment of STX4 expression improves insulin sensitivity in mice. Here, we show that transgenic skeletal muscle-specific STX4 enrichment (skmSTX4tg) in mice reverses established insulin resistance and improves mitochondrial function in the context of diabetogenic stress. Specifically, skmSTX4tg reversed insulin resistance caused by high-fat diet (HFD) without altering body weight or food consumption. Electron microscopy of wild-type mouse muscle revealed STX4 localisation at or proximal to the mitochondrial membrane. STX4 enrichment prevented HFD-induced mitochondrial fragmentation and dysfunction through a mechanism involving STX4-Drp1 interaction and elevated AMPK-mediated phosphorylation at Drp1 S637, which favors fusion. Our findings challenge the dogma that STX4 acts solely at the plasma membrane, revealing that STX4 localises at/proximal to and regulates the function of mitochondria in muscle. These results establish skeletal muscle STX4 enrichment as a candidate therapeutic strategy to reverse peripheral insulin resistance.

Impaired tricarboxylic acid cycle flux and mitochondrial aerobic respiration during isoproterenol induced myocardial ischemia is rescued by bilobalide

There is an urgent need to elucidate the pathogenesis of myocardial ischemia (MI) and potential drug treatments. Here, the anti-MI mechanism and material basis of Ginkgo biloba L. extract (GBE) were studied from the perspective of energy metabolism flux regulation. Metabolic flux analysis (MFA) was performed to investigate energy metabolism flux disorder and the regulatory nodes of GBE components in isoproterenol (ISO)-induced ischemia-like cardiomyocytes. It showed that [U–¹³C] glucose derived m+2 isotopologues from the upstream tricarboxylic acid (TCA) cycle metabolites were markedly accumulated in ISO-injured cardiomyocytes, but the opposite was seen for the downstream metabolites, while their total cellular concentrations were increased. This indicates a blockage of carbon flow from glycolysis and enhanced anaplerosis from other carbon sources. A Seahorse test was used to screen for GBE components with regulatory effects on mitochondrial aerobic respiratory dysfunction. It showed that bilobalide protected against impaired mitochondrial aerobic respiration. MFA also showed that bilobalide significantly modulated the TCA cycle flux, reduced abnormal metabolite accumulation, and balanced the demand of different carbon sources. Western blotting and PCR analysis showed that bilobalide decreased the enhanced expression of key metabolic enzymes in injured cells. Bilobalide's efficacy was verified by in vivo experiments in rats. This is the first report to show that bilobalide, the active ingredient of GBE, protects against MI by rescuing impaired TCA cycle flux. This provides a new mechanism and potential drug treatment for MI. It also shows the potential of MFA/Seahorse combination as a powerful strategy for pharmacological research on herbal medicine.

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A strategy for herbal medicine research by stable isotopic tracing metabolic flux analysis combined with Seahorse test.

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A blockage of carbon flow from glycolysis and enhanced anaplerosis in TCA cycle during myocardial ischemia.

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Bilobalide is against myocardial ischemia by rescuing impaired TCA cycle flux and mitochondrial aerobic respiration.

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.

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.

Elucidating tumor-stromal metabolic crosstalk in colorectal cancer through integration of constraint-based models and LC-MS metabolomics

Colorectal cancer (CRC) is a major cause of morbidity and mortality in the United States. Tumor-stromal metabolic crosstalk in the tumor microenvironment promotes CRC development and progression, but exactly how stromal cells, in particular cancer-associated fibroblasts (CAFs), affect the metabolism of tumor cells remains unknown. Here we take a data-driven approach to investigate the metabolic interactions between CRC cells and CAFs, integrating constraint-based modeling and metabolomic profiling. Using metabolomics data, we perform unsteady-state parsimonious flux balance analysis to infer flux distributions for central carbon metabolism in CRC cells treated with or without CAF-conditioned media. We find that CAFs reprogram CRC metabolism through stimulation of glycolysis, the oxidative arm of the pentose phosphate pathway (PPP), and glutaminolysis, as well as inhibition of the tricarboxylic acid cycle. To identify potential therapeutic targets, we simulate enzyme knockouts and find that CAF-treated CRC cells are especially sensitive to inhibitions of hexokinase and glucose-6-phosphate, the rate limiting steps of glycolysis and oxidative PPP. Our work gives mechanistic insights into the metabolic interactions between CRC cells and CAFs and provides a framework for testing hypotheses towards CRC-targeted therapies.

Dissecting Host-Pathogen Interactions in TB Using Systems-Based Omic Approaches

Tuberculosis (TB) is a devastating infectious disease that kills over a million people every year. There is an increasing burden of multi drug resistance (MDR) and extensively drug resistance (XDR) TB. New and improved therapies are urgently needed to overcome the limitations of current treatment. The causative agent, Mycobacterium tuberculosis (Mtb) is one of the most successful pathogens that can manipulate host cell environment for adaptation, evading immune defences, virulence, and pathogenesis of TB infection. Host-pathogen interaction is important to establish infection and it involves a complex set of processes. Metabolic cross talk between the host and pathogen is a facet of TB infection and has been an important topic of research where there is growing interest in developing therapies and drugs that target these interactions and metabolism of the pathogen in the host. Mtb scavenges multiple nutrient sources from the host and has adapted its metabolism to survive in the intracellular niche. Advancements in systems-based omic technologies have been successful to unravel host-pathogen interactions in TB. In this review we discuss the application and usefulness of omics in TB research that provides promising interventions for developing anti-TB therapies.

Comprehensive Analysis of 13C6 Glucose Fate in the Hypoxia-Tolerant Blind Mole Rat Skin Fibroblasts

The bioenergetics of the vast majority of terrestrial mammals evolved to consuming glucose (Glc) for energy production under regular atmosphere (about 21% oxygen). However, some vertebrate species, such as aquatic turtles, seals, naked mole rat, and blind mole rat, Spalax, have adjusted their homeostasis to continuous function under severe hypoxic environment. The exploration of hypoxia-tolerant species metabolic strategies provides a better understanding of the adaptation to hypoxia. In this study, we compared Glc homeostasis in primary Spalax and rat skin cells under normoxic and hypoxic conditions. We used the targeted-metabolomics approach, utilizing liquid chromatography and mass spectrometry (LC-MS) to track the fate of heavy Glc carbons (¹³C₆ Glc), as well as other methodologies to assist the interpretation of the metabolic landscape, such as bioenergetics profiling, Western blotting, and gene expression analysis. The metabolic profile was recorded under steady-state (after 24 h) of the experiment. Glc-originated carbons were unequally distributed between the cytosolic and mitochondrial domains in Spalax cells compared to the rat. The cytosolic domain is dominant apparently due to the hypoxia-inducible factor-1 alpha (HIF-1α) mastering, since its level is higher under normoxia and hypoxia in Spalax cells. Consumed Glc in Spalax cells is utilized for the pentose phosphate pathway maintaining the NADPH pool, and is finally harbored as glutathione (GSH) and UDP-GlcNAc. The cytosolic domain in Spalax cells works in the semi-uncoupled mode that limits the consumed Glc-derived carbons flux to the tricarboxylic acid (TCA) cycle and reduces pyruvate delivery; however, it maintains the NAD⁺ pool via lactate dehydrogenase upregulation. Both normoxic and hypoxic mitochondrial homeostasis of Glc-originated carbons in Spalax are characterized by their massive cataplerotic flux along with the axis αKG→Glu→Pro→hydroxyproline (HPro). The product of collagen degradation, HPro, as well as free Pro are apparently involved in the bioenergetics of Spalax under both normoxia and hypoxia. The upregulation of 2-hydroxyglutarate production detected in Spalax cells may be involved in modulating the levels of HIF-1α. Collectively, these data suggest that Spalax cells utilize similar metabolic frame for both normoxia and hypoxia, where glucose metabolism is switched from oxidative pathways (conversion of pyruvate to Acetyl-CoA and further TCA cycle processes) to (i) pentose phosphate pathway, (ii) lactate production, and (iii) cataplerotic pathways leading to hexosamine, GSH, and HPro production.

Liquid Chromatography-Mass Spectrometry for Clinical Metabolomics: An Overview

Metabolomics is a discipline that offers a comprehensive analysis of metabolites in biological samples. In the last decades, the notable evolution in liquid chromatography and mass spectrometry technologies has driven an exponential progress in LC-MS-based metabolomics. Targeted and untargeted metabolomics strategies are important tools in health and medical science, especially in the study of disease-related biomarkers, drug discovery and development, toxicology, diet, physical exercise, and precision medicine. Clinical and biological problems can now be understood in terms of metabolic phenotyping. This overview highlights the current approaches to LC-MS-based metabolomics analysis and its applications in the clinical research.

Analysis of Leukemia Cell Metabolism through Stable Isotope Tracing in Mice

Once thought to be a mere consequence of the state of a cell, intermediary metabolism is now recognized as a key regulator of mammalian cell fate and function. In addition, cell metabolism is often disturbed in malignancies such as cancer, and targeting metabolic pathways can provide new therapeutic options. Cell metabolism is mostly studied in cell cultures in vitro, using techniques such as metabolomics, stable isotope tracing, and biochemical assays. Increasing evidence however shows that the metabolic profile of cells is highly dependent on the microenvironment, and metabolic vulnerabilities identified in vitro do not always translate to in vivo settings. Here, we provide a detailed protocol on how to perform in vivo stable isotope tracing in leukemia cells in mice, focusing on glutamine metabolism in acute myeloid leukemia (AML) cells. This method allows studying the metabolic profile of leukemia cells in their native bone marrow niche.

From OCR and ECAR to energy: Perspectives on the design and interpretation of bioenergetics studies

Biological energy transduction underlies all physiological phenomena in cells. The metabolic systems that support energy transduction have been of great interest due to their association with numerous pathologies including diabetes, cancer, rare genetic diseases, and aberrant cell death. Commercially available bioenergetics technologies (e.g., extracellular flux analysis, high-resolution respirometry, fluorescent dye kits, etc.) have made practical assessment of metabolic parameters widely accessible. This has facilitated an explosion in the number of studies exploring, in particular, the biological implications of oxygen consumption rate (OCR) and substrate level phosphorylation via glycolysis (i.e., via extracellular acidification rate (ECAR)). Though these technologies have demonstrated substantial utility and broad applicability to cell biology research, they are also susceptible to historical assumptions, experimental limitations, and other caveats that have led to premature and/or erroneous interpretations. This review enumerates various important considerations for designing and interpreting cellular and mitochondrial bioenergetics experiments, some common challenges and pitfalls in data interpretation, and some potential "next steps" to be taken that can address these highlighted challenges.

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.

Listening in on the conversation between the human gut microbiome and its host

The gut microbiome is an ecosystem. Natural selection favored microbes fit for the gut, which can utilize and convert molecules produced by the host for their own benefit. But natural selection also favored the host's mechanisms to sense and respond to the microbial ecosystem for its own benefit. We can listen in on the host-microbiome 'conversation' in the simultaneous responses of the microbiome and the host to strong perturbations. In laboratory animals a perturbation can be done for research; in human patients a perturbation can be caused by disease or therapy. Advances in metagenomics, metabolomics and computation amplify our means to listen in on the conversation between the gut microbiome and its host.

Investigation of energy metabolic dynamism in hyperthermia-resistant ovarian and uterine cancer cells under heat stress

Despite progress in the use of hyperthermia in clinical practice, the thermosensitivity of cancer cells is poorly understood. In a previous study, we found that sensitivity to hyperthermia varied between ovarian and uterine cancer cell lines. Upon hyperthermia, glycolytic enzymes decreased in hyperthermia-resistant SKOV3 cells. However, the mechanisms of glycolysis inhibition and their relationship with thermoresistance remain to be explored. In this study, metabolomic analysis indicated the downregulation of glycolytic metabolites in SKOV3 cells after hyperthermia. Proteomic and pathway analyses predicted that the ubiquitin pathway was explicitly activated in resistant SKOV3 cells, compared with hyperthermia-sensitive A2780 cells, and STUB1, a ubiquitin ligase, potentially targeted PKM, a glycolytic rate-limiting enzyme. PKM is degraded via ubiquitination upon hyperthermia. Although glycolysis is inactivated by hyperthermia, ATP production is maintained. We observed that oxygen consumption and mitochondrial membrane potential were activated in SKOV3 cells but suppressed in A2780 cells. The activation of mitochondria could compensate for the loss of ATP production due to the suppression of glycolysis by hyperthermia. Although the physiological significance has not yet been elucidated, our results demonstrated that metabolomic adaptation from the Warburg effect to mitochondrial oxidative phosphorylation could contribute to thermoresistance in ovarian and uterine cancer cells.

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.

Immunometabolic Endothelial Phenotypes: Integrating Inflammation and Glucose Metabolism

[Figure: see text].

A Systems Approach to Brain Tumor Treatment

Brain tumors are among the most lethal tumors. Glioblastoma, the most frequent primary brain tumor in adults, has a median survival time of approximately 15 months after diagnosis or a five-year survival rate of 10%; the recurrence rate is nearly 90%. Unfortunately, this prognosis has not improved for several decades. The lack of progress in the treatment of brain tumors has been attributed to their high rate of primary therapy resistance. Challenges such as pronounced inter-patient variability, intratumoral heterogeneity, and drug delivery across the blood-brain barrier hinder progress. A comprehensive, multiscale understanding of the disease, from the molecular to the whole tumor level, is needed to address the intratumor heterogeneity resulting from the coexistence of a diversity of neoplastic and non-neoplastic cell types in the tumor tissue. By contrast, inter-patient variability must be addressed by subtyping brain tumors to stratify patients and identify the best-matched drug(s) and therapies for a particular patient or cohort of patients. Accomplishing these diverse tasks will require a new framework, one involving a systems perspective in assessing the immense complexity of brain tumors. This would in turn entail a shift in how clinical medicine interfaces with the rapidly advancing high-throughput (HTP) technologies that have enabled the omics-scale profiling of molecular features of brain tumors from the single-cell to the tissue level. However, several gaps must be closed before such a framework can fulfill the promise of precision and personalized medicine for brain tumors. Ultimately, the goal is to integrate seamlessly multiscale systems analyses of patient tumors and clinical medicine. Accomplishing this goal would facilitate the rational design of therapeutic strategies matched to the characteristics of patients and their tumors. Here, we discuss some of the technologies, methodologies, and computational tools that will facilitate the realization of this vision to practice.

Application of metabolomics in clinical and laboratory gastrointestinal oncology

Metabolites are versatile bioactive molecules. They are not only the substrates and/or the products of enzymatic reactions but also act as the regulators in the systemic metabolism. Metabolomics is a high-throughput analytical strategy to qualify or quantify as many metabolites as possible in the metabolomes. It is an indispensable part of systems biology. The leading techniques in this field are mainly based on mass spectrometry and nuclear magnetic resonance spectroscopy. The metabolomic analysis has gained wide use in bioscience fields. In the tumor research arena, metabolomics can be employed to identify biomarkers for prediction, diagnosis, and prognosis. Chemotherapeutic effect evaluation and personalized medicine decision-making can also benefit from metabolomic analysis of patient biofluid or biopsy samples. Many cell-level studies can help in disease exploration. In this review, the basic features and principles of varied metabolomic analysis are introduced. The value of metabolomics in clinical and laboratory gastrointestinal cancer studies is discussed, especially for mass spectrometry applications. Besides, combined use of metabolomics and other tools to solve problems in cancer practice is briefly illustrated. In summary, metabolomics paves a new way to explore cancerous diseases in the light of small molecules.

Fueling Cell Invasion through Extracellular Matrix

Cell invasion through extracellular matrix (ECM) has pivotal roles in cell dispersal during development, immune cell trafficking, and cancer metastasis. Many elegant studies have revealed the specialized cellular protrusions, proteases, and distinct modes of migration invasive cells use to overcome ECM barriers. Less clear, however, is how invasive cells provide energy, specifically ATP, to power the energetically demanding membrane trafficking, F-actin polymerization, and actomyosin machinery that mediate break down, remodeling, and movement through ECMs. Here, we provide an overview of the challenges of examining ATP generation and delivery within invading cells and how recent studies using diverse invasion models, experimental approaches, and energy biosensors are revealing that energy metabolism is an integral component of cell invasive behavior that is dynamically tuned to overcome the ECM environment.

Loss of mitochondrial aconitase promotes colorectal cancer progression via SCD1-mediated lipid remodeling

OBJECTIVE

Mitochondrial aconitase (ACO2) is an essential enzyme that bridges the TCA cycle and lipid metabolism. However, its role in cancer development remains to be elucidated. The metabolic subtype of colorectal cancer (CRC) was recently established. We investigated ACO2's potential role in CRC progression through mediating metabolic alterations.

METHODS

We compared the mRNA and protein expression of ACO2 between paired CRC and non-tumor tissues from 353 patients. Correlations between ACO2 levels and clinicopathological features were examined. CRC cell lines with knockdown or overexpression of ACO2 were analyzed for cell proliferation and tumor growth. Metabolomics and stable isotope tracing analyses were used to study the metabolic alterations induced by loss of ACO2.

RESULTS

ACO2 decreased in >50% of CRC samples compared with matched non-tumor tissues. Decreased ACO2 levels correlated with advanced disease stage (P < 0.001) and shorter patient survival (P < 0.001). Knockdown of ACO2 in CRC cells promoted cell proliferation and tumor formation, while ectopic expression of ACO2 restrained tumor growth. Specifically, blockade of ACO2 caused a reduction in TCA cycle intermediates and suppression of mitochondrial oxidative phosphorylation, resulting in an increase in glycolysis and elevated citrate flux for fatty acid and lipid synthesis. Increased citrate flux induced upregulation of stearoyl-CoA desaturase (SCD1), which enhanced lipid desaturation in ACO2-deficent cells to favor colorectal cancer growth. Pharmacological inhibition of SCD selectively reduced tumor formation of CRC with ACO2 deficiency.

CONCLUSIONS

Our study demonstrated that the rewiring metabolic pathway maintains CRC survival during compromised TCA cycles and characterized the therapeutic vulnerability of lipid desaturation in a meaningful subset of CRC with mitochondrial dysfunction.

Simultaneous Quantification of the Concentration and Carbon Isotopologue Distribution of Polar Metabolites in a Single Analysis by Gas Chromatography and Mass Spectrometry

¹³C-isotope tracing is a frequently employed approach to study metabolic pathway activity. When combined with the subsequent quantification of absolute metabolite concentrations, this enables detailed characterization of the metabolome in biological specimens and facilitates computational time-resolved flux quantification. Classically, a ¹³C-isotopically labeled sample is required to quantify ¹³C-isotope enrichments and a second unlabeled sample for the quantification of metabolite concentrations. The rationale for a second unlabeled sample is that the current methods for metabolite quantification rely mostly on isotope dilution mass spectrometry (IDMS) and thus isotopically labeled internal standards are added to the unlabeled sample. This excludes the absolute quantification of metabolite concentrations in ¹³C-isotopically labeled samples. To address this issue, we have developed and validated a new strategy using an unlabeled internal standard to simultaneously quantify metabolite concentrations and ¹³C-isotope enrichments in a single ¹³C-labeled sample based on gas chromatography-mass spectrometry (GC/MS). The method was optimized for amino acids and citric acid cycle intermediates and was shown to have high analytical precision and accuracy. Metabolite concentrations could be quantified in small tissue samples (≥20 mg). Also, we applied the method on ¹³C-isotopically labeled mammalian cells treated with and without a metabolic inhibitor. We proved that we can quantify absolute metabolite concentrations and ¹³C-isotope enrichments in a single ¹³C-isotopically labeled sample.

13C isotope-based metabolic flux analysis revealing cellular landscape of glucose metabolism in human liver cells exposed to perfluorooctanoic acid

Perfluorooctanoic acid (PFOA) is well known to break glucose homeostasis. However, the effects of PFOA on glucose metabolism are difficult to be evaluated because related metabolites may be synthesized from other nutritional substrates. Here, the relative contribution of glucose to metabolites (e.g., pyruvate and citrate) in the PFOA-treated human liver cells (HepG2) was determined using the ¹³C isotope-based metabolic flux analysis (MFA), i.e., pathway activities. The relative percentage of [U-¹³C₆] glucose-derived pyruvate in cells exposed to PFOA was not significantly different from that in the controls, indicating that the metabolic pattern of glycolysis was not substantially changed by PFOA. The pathway activity of [U-¹³C₆] glucose-driven tricarboxylic acid (TCA) cycle was dramatically inhibited by PFOA. Consequently, mitochondrial respiratory function was phenotypically impaired by PFOA, as observed from the decreasing basal oxygen consumption rate (OCR), ATP-linked OCR and spare respiratory capacity. This study suggests that PFOA may cause the abnormal glucose metabolism via altering the metabolic pattern of TCA cycle instead of glycolysis. The MFA is strongly recommended as a promising and robust tool to address the toxicity mechanisms of contaminants associated with glucose metabolism.

Challenges in Studying Stem Cell Metabolism

The expanding field of stem cell metabolism has been supported by technical advances in metabolite profiling and novel functional analyses. While use of these methodologies has been fruitful, many challenges are posed by the intricacies of culturing stem cells in vitro, along with the distinctive scarcity of adult tissue stem cells and the complexities of their niches in vivo. This review provides an examination of the methodologies used to characterize stem cell metabolism, highlighting their utility while placing a sharper focus on their limitations and hurdles the field needs to overcome for the optimal study of stem cell metabolic networks.

Gas chromatography-mass spectrometry based 18O stable isotope labeling of Krebs cycle intermediates

New technologies permit determining metabolomic profiles of human diseases by fingerprinting metabolites levels. However, to fully understand metabolomic phenotypes, metabolite levels and turnover rates are necessary to know. Krebs cycle is the major hub of energy metabolism and cell signaling. Traditionally, ¹³C stable isotope labeled substrates were used to track the carbon turnover rates in Krebs cycle metabolites. In this study, for the first time we introduce H₂[¹⁸O] based stable isotope marker that permit tracking oxygen exchange rates in separate segments of Krebs cycle. The chromatographic and non-chromatographic parameters were systematically tested on the effect of labeling ratio of Krebs cycle mediators to increase selectivity and sensitivity of the method. We have developed a rapid, precise, and robust GC-MS method for determining the percentage of ¹⁸O incorporation to Krebs cycle metabolites. The developed method was applied to track the cancer-induced shift in the Krebs cycle dynamics of Caco-2 cells as compared to the control FHC cells revealing Warburg effects in Caco-2 cells. We demonstrate that unique information could be obtained using this newly developed ¹⁸O-labeling analytical technology by following the oxygen exchange rates of Krebs cycle metabolites. Thus, ¹⁸O-labeling of Krebs cycle metabolites expands the arsenal of techniques for monitoring the dynamics of cellular metabolism. Moreover, the developed method will allow to apply the ¹⁸O-labeling technique to numerous other metabolic pathways where oxygen exchange with water takes place.

13C Metabolic Flux Analysis Indicates Endothelial Cells Attenuate Metabolic Perturbations by Modulating TCA Activity

Disrupted endothelial metabolism is linked to endothelial dysfunction and cardiovascular disease. Targeted metabolic inhibitors are potential therapeutics; however, their systemic impact on endothelial metabolism remains unknown. In this study, we combined stable isotope labeling with ¹³C metabolic flux analysis (¹³C MFA) to determine how targeted inhibition of the polyol (fidarestat), pentose phosphate (DHEA), and hexosamine biosynthetic (azaserine) pathways alters endothelial metabolism. Glucose, glutamine, and a four-carbon input to the malate shuttle were important carbon sources in the baseline human umbilical vein endothelial cell (HUVEC) ¹³C MFA model. We observed two to three times higher glutamine uptake in fidarestat and azaserine-treated cells. Fidarestat and DHEA-treated HUVEC showed decreased ¹³C enrichment of glycolytic and TCA metabolites and amino acids. Azaserine-treated HUVEC primarily showed ¹³C enrichment differences in UDP-GlcNAc. ¹³C MFA estimated decreased pentose phosphate pathway flux and increased TCA activity with reversed malate shuttle direction in fidarestat and DHEA-treated HUVEC. In contrast, ¹³C MFA estimated increases in both pentose phosphate pathway and TCA activity in azaserine-treated cells. These data show the potential importance of endothelial malate shuttle activity and suggest that inhibiting glycolytic side branch pathways can change the metabolic network, highlighting the need to study systemic metabolic therapeutic effects.

Vitamin D regulation of energy metabolism in cancer

Vitamin D exerts anti-cancer effects in recent clinical trials and preclinical models. The actions of vitamin D are primarily mediated through its hormonal form, 1,25-dihydroxyvitamin D (1,25(OH)₂ D). Previous literature describing in vitro studies has predominantly focused on the anti-tumourigenic effects of the hormone, such as proliferation and apoptosis. However, recent evidence has identified 1,25(OH)₂ D as a regulator of energy metabolism in cancer cells, where requirements for specific energy sources at different stages of progression are dramatically altered. The literature suggests that 1,25(OH)₂ D regulates energy metabolism, including glucose, glutamine and lipid metabolism during cancer progression, as well as oxidative stress protection, as it is closely associated with energy metabolism. Mechanisms involved in energy metabolism regulation are an emerging area in which vitamin D may inhibit multiple stages of cancer progression.

Mapping the Metabolic Networks of Tumor Cells and Cancer-Associated Fibroblasts

Metabolism is considered to be the core of all cellular activity. Thus, extensive studies of metabolic processes are ongoing in various fields of biology, including cancer research. Cancer cells are known to adapt their metabolism to sustain high proliferation rates and survive in unfavorable environments with low oxygen and nutrient concentrations. Hence, targeting cancer cell metabolism is a promising therapeutic strategy in cancer research. However, cancers consist not only of genetically altered tumor cells but are interwoven with endothelial cells, immune cells and fibroblasts, which together with the extracellular matrix (ECM) constitute the tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs), which are linked to poor prognosis in different cancer types, are one important component of the TME. CAFs play a significant role in reprogramming the metabolic landscape of tumor cells, but how, and in what manner, this interaction takes place remains rather unclear. This review aims to highlight the metabolic landscape of tumor cells and CAFs, including their recently identified subtypes, in different tumor types. In addition, we discuss various in vitro and in vivo metabolic techniques as well as different in silico computational tools that can be used to identify and characterize CAF-tumor cell interactions. Finally, we provide our view on how mapping the complex metabolic networks of stromal-tumor metabolism will help in finding novel metabolic targets for cancer treatment.

Cysteine and Folate Metabolism Are Targetable Vulnerabilities of Metastatic Colorectal Cancer

Simple Summary

In this work, we studied the metabolic reprogramming of same-patient-derived cell lines with increasing metastatic potential to develop new therapeutic approaches against metastatic colorectal cancer. Using a novel systems biology approach to integrate multiple layers of omics data, we predicted and validated that cystine uptake and folate metabolism, two key pathways related to redox metabolism, are potential targets against metastatic colorectal cancer. Our findings indicate that metastatic cell lines are selectively dependent on redox homeostasis, paving the way for new targeted therapies.

Abstract

With most cancer-related deaths resulting from metastasis, the development of new therapeutic approaches against metastatic colorectal cancer (mCRC) is essential to increasing patient survival. The metabolic adaptations that support mCRC remain undefined and their elucidation is crucial to identify potential therapeutic targets. Here, we employed a strategy for the rational identification of targetable metabolic vulnerabilities. This strategy involved first a thorough metabolic characterisation of same-patient-derived cell lines from primary colon adenocarcinoma (SW480), its lymph node metastasis (SW620) and a liver metastatic derivative (SW620-LiM2), and second, using a novel multi-omics integration workflow, identification of metabolic vulnerabilities specific to the metastatic cell lines. We discovered that the metastatic cell lines are selectively vulnerable to the inhibition of cystine import and folate metabolism, two key pathways in redox homeostasis. Specifically, we identified the system xCT and MTHFD1 genes as potential therapeutic targets, both individually and combined, for combating mCRC.

Insights into the Roles of the Sideroflexins/SLC56 Family in Iron Homeostasis and Iron-Sulfur Biogenesis

Sideroflexins (SLC56 family) are highly conserved multi-spanning transmembrane proteins inserted in the inner mitochondrial membrane in eukaryotes. Few data are available on their molecular function, but since their first description, they were thought to be metabolite transporters probably required for iron utilization inside the mitochondrion. Such as numerous mitochondrial transporters, sideroflexins remain poorly characterized. The prototypic member SFXN1 has been recently identified as the previously unknown mitochondrial transporter of serine. Nevertheless, pending questions on the molecular function of sideroflexins remain unsolved, especially their link with iron metabolism. Here, we review the current knowledge on sideroflexins, their presumed mitochondrial functions and the sparse-but growing-evidence linking sideroflexins to iron homeostasis and iron-sulfur cluster biogenesis. Since an imbalance in iron homeostasis can be detrimental at the cellular and organismal levels, we also investigate the relationship between sideroflexins, iron and physiological disorders. Investigating Sideroflexins' functions constitutes an emerging research field of great interest and will certainly lead to the main discoveries of mitochondrial physio-pathology.

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.

Investigating metabolism by mass spectrometry: From steady state to dynamic view

Metabolism is the set of life-sustaining reactions in organisms. These biochemical reactions are organized in metabolic pathways, in which one metabolite is converted through a series of steps catalyzed by enzymes in another chemical compound. Metabolic reactions are categorized as catabolic, the breaking down of metabolites to produce energy, and/or anabolic, the synthesis of compounds that consume energy. The balance between catabolism of the preferential fuel substrate and anabolism defines the overall metabolism of a cell or tissue. Metabolomics is a powerful tool to gain new insights contributing to the identification of complex molecular mechanisms in the field of biomedical research, both basic and translational. The enormous potential of this kind of analyses consists of two key aspects: (i) the possibility of performing so-called targeted and untargeted experiments through which it is feasible to verify or formulate a hypothesis, respectively, and (ii) the opportunity to run either steady-state analyses to have snapshots of the metabolome at a given time under different experimental conditions or dynamic analyses through the use of labeled tracers. In this review, we will highlight the most important practical (e.g., different sample extraction approaches) and conceptual steps to consider for metabolomic analysis, describing also the main application contexts in which it is used. In addition, we will provide some insights into the most innovative approaches and progress in the field of data analysis and processing, highlighting how this part is essential for the proper extrapolation and interpretation of data.

Chemical Isotope Labeling LC-MS for Metabolomics

Due to the great diversity of chemical and physical properties of metabolites as well as a wide range of concentrations of metabolites present in metabolomic samples, performing comprehensive and quantitative metabolome analysis is a major analytical challenge. Conventional approach of combining various techniques and methods with each detecting a fraction of the metabolome can lead to the increase in overall metabolomic coverage. However, this approach requires extensive investment in equipment and analytical expertise with still relatively low coverage and low sample throughput. Chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) offers an alternative means of increasing metabolomic coverage while maintaining high quantification precision and accuracy. This chapter describes the CIL LC-MS method and its key features for metabolomic analysis.

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.

Metabolic Regulation of Neocortical Expansion in Development and Evolution

The neocortex, the seat of our higher cognitive abilities, has expanded in size during the evolution of certain mammals such as primates, including humans. This expansion occurs during development and is linked to the proliferative capacity of neural stem and progenitor cells (NPCs) in the neocortex. A number of cell-intrinsic and cell-extrinsic factors have been implicated in increasing NPC proliferative capacity. However, NPC metabolism has only recently emerged as major regulator of NPC proliferation. In this Perspective, we summarize recent insights into the role of NPC metabolism in neocortical development and neurodevelopmental disorders and its relevance for neocortex evolution. We discuss certain human-specific genes and microcephaly-implicated genes that operate in, or at, the mitochondria of NPCs and stimulate their proliferation by promoting glutaminolysis. We also discuss other metabolic pathways and develop a perspective on how metabolism mechanistically regulates NPC proliferation in neocortical development and how this contributed to neocortex evolution.

Metabolic regulation of prostate cancer heterogeneity and plasticity

Metabolic reprogramming is one of the main hallmarks of cancer cells. It refers to the metabolic adaptations of tumor cells in response to nutrient deficiency, microenvironmental insults, and anti-cancer therapies. Metabolic transformation during tumor development plays a critical role in the continued tumor growth and progression and is driven by a complex interplay between the tumor mutational landscape, epigenetic modifications, and microenvironmental influences. Understanding the tumor metabolic vulnerabilities might open novel diagnostic and therapeutic approaches with the potential to improve the efficacy of current tumor treatments. Prostate cancer is a highly heterogeneous disease harboring different mutations and tumor cell phenotypes. While the increase of intra-tumor genetic and epigenetic heterogeneity is associated with tumor progression, less is known about metabolic regulation of prostate cancer cell heterogeneity and plasticity. This review summarizes the central metabolic adaptations in prostate tumors, state-of-the-art technologies for metabolic analysis, and the perspectives for metabolic targeting and diagnostic implications.

Cell culture bioprocessing - the road taken and the path forward

Cell culture processes are used to produce the vast majority of protein therapeutics, valued at over US$180 billion per annum worldwide. For more than a decade now, these processes have become highly productive. To further enhance capital efficiency, there has been an increase in the adoption of disposable apparatus and continuous processing, as well as a greater exploration of in-line sensing, various -omic tools, and cell engineering to enhance process controllability and product quality consistency. These feats in cell culture processing for protein biologics will help accelerate the bioprocess advancements for virus and cell therapy applications.

Metabolic Flux Analysis-Linking Isotope Labeling and Metabolic Fluxes

Metabolic flux analysis (MFA) is an increasingly important tool to study metabolism quantitatively. Unlike the concentrations of metabolites, the fluxes, which are the rates at which intracellular metabolites interconvert, are not directly measurable. MFA uses stable isotope labeled tracers to reveal information related to the fluxes. The conceptual idea of MFA is that in tracer experiments the isotope labeling patterns of intracellular metabolites are determined by the fluxes, therefore by measuring the labeling patterns we can infer the fluxes in the network. In this review, we will discuss the basic concept of MFA using a simplified upper glycolysis network as an example. We will show how the fluxes are reflected in the isotope labeling patterns. The central idea we wish to deliver is that under metabolic and isotopic steady-state the labeling pattern of a metabolite is the flux-weighted average of the substrates’ labeling patterns. As a result, MFA can tell the relative contributions of converging metabolic pathways only when these pathways make substrates in different labeling patterns for the shared product. This is the fundamental principle guiding the design of isotope labeling experiment for MFA including tracer selection. In addition, we will also discuss the basic biochemical assumptions of MFA, and we will show the flux-solving procedure and result evaluation. Finally, we will highlight the link between isotopically stationary and nonstationary flux analysis.

A guide to metabolic flux analysis in metabolic engineering: Methods, tools and applications

The field of metabolic engineering is primarily concerned with improving the biological production of value-added chemicals, fuels and pharmaceuticals through the design, construction and optimization of metabolic pathways, redirection of intracellular fluxes, and refinement of cellular properties relevant for industrial bioprocess implementation. Metabolic network models and metabolic fluxes are central concepts in metabolic engineering, as was emphasized in the first paper published in this journal, "Metabolic fluxes and metabolic engineering" (Metabolic Engineering, 1: 1-11, 1999). In the past two decades, a wide range of computational, analytical and experimental approaches have been developed to interrogate the capabilities of biological systems through analysis of metabolic network models using techniques such as flux balance analysis (FBA), and quantify metabolic fluxes using constrained-based modeling approaches such as metabolic flux analysis (MFA) and more advanced experimental techniques based on the use of stable-isotope tracers, i.e. ¹³C-metabolic flux analysis (¹³C-MFA). In this review, we describe the basic principles of metabolic flux analysis, discuss current best practices in flux quantification, highlight potential pitfalls and alternative approaches in the application of these tools, and give a broad overview of pragmatic applications of flux analysis in metabolic engineering practice.

Forces, fluxes, and fuels: tracking mitochondrial metabolism by integrating measurements of membrane potential, respiration, and metabolites

Assessing mitochondrial function in cell-based systems is a central component of metabolism research. However, the selection of an initial measurement technique may be complicated given the range of parameters that can be studied and the need to define the mitochondrial (dys)function of interest. This methods-focused review compares and contrasts the use of mitochondrial membrane potential measurements, plate-based respirometry, and metabolomics and stable isotope tracing. We demonstrate how measurements of 1) cellular substrate preference, 2) respiratory chain activity, 3) cell activation, and 4) mitochondrial biogenesis are enriched by integrating information from multiple methods. This manuscript is meant to serve as a perspective to help choose which technique might be an appropriate initial method to answer a given question, as well as provide a broad "roadmap" for designing follow-up assays to enrich datasets or resolve ambiguous results.

HIFs, angiogenesis, and metabolism: elusive enemies in breast cancer

Hypoxia-inducible factors (HIFs) and the HIF-dependent cancer hallmarks angiogenesis and metabolic rewiring are well-established drivers of breast cancer aggressiveness, therapy resistance, and poor prognosis. Targeting of HIF and its downstream targets in angiogenesis and metabolism has been unsuccessful so far in the breast cancer clinical setting, with major unresolved challenges residing in target selection, development of robust biomarkers for response prediction, and understanding and harnessing of escape mechanisms. This Review discusses the pathophysiological role of HIFs, angiogenesis, and metabolism in breast cancer and the challenges of targeting these features in patients with breast cancer. Rational therapeutic combinations, especially with immunotherapy and endocrine therapy, seem most promising in the clinical exploitation of the intricate interplay of HIFs, angiogenesis, and metabolism in breast cancer cells and the tumor microenvironment.

Regulation of Metabolic Homeostasis in Cell Culture Bioprocesses

Mammalian cells are the main tool for the production of therapeutic proteins, viruses for gene therapy, and cells for cell therapy. In production processes cell metabolism is the main driver that causes changes in the growth environment and affects productivity and product quality. Of all nutrients, glucose has the most prominent impact on bioprocesses. We summarize recent findings on the regulation of glucose and energy metabolism in cultured cells. Local allosteric regulations and post-translational modifications of enzymes in metabolic networks interplay with global signaling and transcriptional regulation. These regulatory networks sustain homeostasis across the cytosolic and mitochondrial compartments. Understanding the regulation of glucose metabolism and metabolic state is crucial for enhancing process productivity and product quality.

Disruption of redox homeostasis for combinatorial drug efficacy in K-Ras tumors as revealed by metabolic connectivity profiling

Abstract

Background

Rewiring of metabolism induced by oncogenic K-Ras in cancer cells involves both glucose and glutamine utilization sustaining enhanced, unrestricted growth. The development of effective anti-cancer treatments targeting metabolism may be facilitated by the identification and rational combinatorial targeting of metabolic pathways.

Methods

We performed mass spectrometric metabolomics analysis in vitro and in vivo experiments to evaluate the efficacy of drugs and identify metabolic connectivity.

Results

We show that K-Ras-mutant lung and colon cancer cells exhibit a distinct metabolic rewiring, the latter being more dependent on respiration. Combined treatment with the glutaminase inhibitor CB-839 and the PI3K/aldolase inhibitor NVP-BKM120 more consistently reduces cell growth of tumor xenografts. Maximal growth inhibition correlates with the disruption of redox homeostasis, involving loss of reduced glutathione regeneration, redox cofactors, and a decreased connectivity among metabolites primarily involved in nucleic acid metabolism.

Conclusions

Our findings open the way to develop metabolic connectivity profiling as a tool for a selective strategy of combined drug repositioning in precision oncology.

Comprehensive Isotopic Targeted Mass Spectrometry: Reliable Metabolic Flux Analysis with Broad Coverage

Metabolic flux analysis (MFA) is highly relevant to understanding metabolic mechanisms of various biological processes. While the pace of methodology development in MFA has been rapid, a major challenge the field continues to witness is limited metabolite coverage, often restricted to a small to moderate number of well-known compounds. In addition, isotopic peaks from an enriched metabolite tend to have low abundances, which makes liquid chromatography tandem mass spectrometry (LC-MS/MS) highly useful in MFA due to its high sensitivity and specificity. Previously we have built large-scale LC-MS/MS approaches that can be routinely used for measurement of up to ∼1,900 metabolite/feature levels [Gu et al. Anal. Chem. 2015, 87, 12355-12362. Shi et al. Anal. Chem. 2019, 91, 13737-13745.]. In this study, we aim to expand our previous studies focused on metabolite level measurements to flux analysis and establish a novel comprehensive isotopic targeted mass spectrometry (CIT-MS) method for reliable MFA analysis with broad coverage. As a proof-of-principle, we have applied CIT-MS to compare the steady-state enrichment of metabolites between Myc(oncogene)-On and Myc-Off Tet21N human neuroblastoma cells cultured with U-13C6-glucose medium. CIT-MS is operationalized using multiple reaction monitoring (MRM) mode and is able to perform MFA of 310 identified metabolites (142 reliably detected, 46 kinetically profiled) selected from >35 metabolic pathways of strong biological significance. Further, we developed a novel concept of relative flux, which eliminates the requirement of absolute quantitation in traditional MFA and thus enables comparative MFA under the pseudosteady state. As a result, CIT-MS was shown to possess the advantages of broad coverage, easy implementation, fast throughput, and more importantly, high fidelity and accuracy in MFA. In principle, CIT-MS can be easily adapted to track the flux of other labeled tracers (such as 15N-tracers) in any metabolite detectable by LC-MS/MS and in various biological models (such as mice). Therefore, CIT-MS has great potential to bring new insights to both basic and clinical metabolism research.

Nutrient Sensing by Histone Marks: Reading the Metabolic Histone Code Using Tracing, Omics, and Modeling

Several metabolites serve as substrates for histone modifications and communicate changes in the metabolic environment to the epigenome. Technologies such as metabolomics and proteomics have allowed us to reconstruct the interactions between metabolic pathways and histones. These technologies have shed light on how nutrient availability can have a dramatic effect on various histone modifications. This metabolism-epigenome cross talk plays a fundamental role in development, immune function, and diseases like cancer. Yet, major challenges remain in understanding the interactions between cellular metabolism and the epigenome. How the levels and fluxes of various metabolites impact epigenetic marks is still unclear. Discussed herein are recent applications and the potential of systems biology methods such as flux tracing and metabolic modeling to address these challenges and to uncover new metabolic-epigenetic interactions. These systems approaches can ultimately help elucidate how nutrients shape the epigenome of microbes and mammalian cells.