Review of metabolic pathways activated in cancer cells as determined through isotopic labeling and network analysis

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

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

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.

3D Chemical Imaging by Fluorescence-detected Mid-Infrared Photothermal Fourier Light Field Microscopy

Three-dimensional molecular imaging of living organisms and cells plays a significant role in modern biology. Yet, current volumetric imaging modalities are largely fluorescence-based and thus lack chemical content information. Mid-infrared photothermal microscopy as a chemical imaging technology provides infrared spectroscopic information at submicrometer spatial resolution. Here, by harnessing thermosensitive fluorescent dyes to sense the mid-infrared photothermal effect, we demonstrate 3D fluorescence-detected mid-infrared photothermal Fourier light field (FMIP-FLF) microscopy at the speed of 8 volumes per second and submicron spatial resolution. Protein contents in bacteria and lipid droplets in living pancreatic cancer cells are visualized. Altered lipid metabolism in drug-resistant pancreatic cancer cells is observed with the FMIP-FLF microscope.

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.

In-phase simultaneous spectral editing of lactate and alanine with suppression of J-coupled lipids by the modified selective multiple quantum coherence sequences

¹H magnetic resonance spectroscopy (MRS) with the multiple quantum coherence (MQC) technique allows for the detection of lactate, an end product of glycolysis, in the environment of lipids. The method can also be used to detect alanine, a byproduct of glutaminolysis. An issue is that when both lactate and alanine are detected together by the MQC technique, a phase mismatch arises between lactate and alanine signals due to off-resonance rotations and the difference in double quantum coherence frequencies between the two molecules. Such phase mismatch can cause errors in spectral fitting and metabolite quantification. In this study, we designed two pulse sequences that eliminate such phase differences of lactate and alanine while suppressing lipid signals by modifications of the Selective Multiple Quantum Coherence (Sel-MQC) sequence, a well-known MQC technique. Using the product operator formalism and the off-resonance rotation matrices, the phase evolutions of lactate and alanine during the spectrally selective pulses and the free precession times of the sequence at the single quantum, double quantum and zero quantum coherence states of these molecules were calculated. The multiple quantum (MQ) evolution time t₁ that can remove the phase difference of lactate and alanine at the echo was calculated and fine-tuned with experiments. The lactate and alanine signal intensities and the editing efficiencies from the two modified Sel-MQC sequences were theoretically predicted by using the product operator evolutions and compared with the experimental data. The J-coupled lipid signals were successfully suppressed by both sequences. One of the two developed sequences was applied to a human body with a phantom of lactate and alanine, which resulted in successful in-phase editing of lactate and alanine and suppression of the lipid signals from the body. The study sets an important foundation for the noninvasive detection of lactate and alanine from tumors of cancer patients.

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.

Isotope tracing in health and disease

Biochemical characterization of metabolism provides molecular insights for understanding biology in health and disease. Over the past decades, metabolic perturbations have been implicated in cancer, neurodegeneration, and diabetes, among others. Isotope tracing is a technique that allows tracking of labeled atoms within metabolites through biochemical reactions. This technique has become an integral component of the contemporary metabolic research. Isotope tracing measures substrate contribution to downstream metabolites and indicates its utilization in cellular metabolic networks. In addition, isotopic labeling data are necessary for quantitative metabolic flux analysis. Here, we review recent work utilizing metabolic tracing to study health and disease, and highlight its application to interrogate subcellular, intercellular, and in vivo metabolism. We further discuss the current challenges and opportunities to expand the utility of isotope tracing to new research areas.

Iron Transporters and Ferroptosis in Malignant Brain Tumors

Malignant brain tumors represent approximately 1.5% of all malignant tumors. The survival rate among patients is relatively low and the mortality rate of pediatric brain tumors ranks first among all childhood malignant tumors. At present malignant brain tumors remain incurable. Although some tumors can be treated with surgery and chemotherapy, new treatment strategies are urgent owing to the poor clinical prognosis. Iron is an essential trace element in many biological processes of the human body. Iron transporters play a crucial role in iron absorption and transport. Ferroptosis, an iron-dependent form of nonapoptotic cell death, is characterized by the accumulation of lipid peroxidation products and lethal reactive oxygen species (ROS) derived from iron metabolism. Recently, compelling evidence has shown that inducing ferroptosis of tumor cells is a potential therapeutic strategy. In this review, we will briefly describe the significant regulatory factors of ferroptosis, iron, its absorption and transport under physiological conditions, especially the function of iron transporters. Then we will summarize the relevant mechanisms of ferroptosis and its role in malignant brain tumors, wherein the role of transporters is not to be ignored. Finally, we will introduce the current research progress in the treatment of malignant brain tumors by inducing ferroptosis in order to explain the current biological principles of potential treatment targets and treatment strategies for malignant brain tumors.

Insulin resistance rewires the metabolic gene program and glucose utilization in human white adipocytes

BACKGROUND

In obesity, adipose tissue dysfunction resulting from excessive fat accumulation leads to systemic insulin resistance (IR), the underlying alteration of Type 2 Diabetes. The specific pathways dysregulated in dysfunctional adipocytes and the extent to which it affects adipose metabolic functions remain incompletely characterized.

METHODS

We interrogated the transcriptional adaptation to increased adiposity in association with insulin resistance in visceral white adipose tissue from lean men, or men presenting overweight/obesity (BMI from 19 to 33) and discordant for insulin sensitivity. In human adipocytes in vitro, we investigated the direct contribution of IR in altering metabolic gene programming and glucose utilization using ¹³C-isotopic glucose tracing.

RESULTS

We found that gene expression associated with impaired glucose and lipid metabolism and inflammation represented the strongest association with systemic insulin resistance, independently of BMI. In addition, we showed that inducing IR in mature human white adipocytes was sufficient to reprogram the transcriptional profile of genes involved in important metabolic functions such as glycolysis, the pentose phosphate pathway and de novo lipogenesis. Finally, we found that IR induced a rewiring of glucose metabolism, with higher incorporation of glucose into citrate, but not into downstream metabolites within the TCA cycle.

CONCLUSIONS

Collectively, our data highlight the importance of obesity-derived insulin resistance in impacting the expression of key metabolic genes and impairing the metabolic processes of glucose utilization, and reveal a role for metabolic adaptation in adipose dysfunction in humans.

The emerging role of selenium metabolic pathways in cancer: New therapeutic targets for cancer

Selenium (Se) is incorporated into the body via the selenocysteine (Sec) biosynthesis pathway, which is critical in the synthesis of selenoproteins, such as glutathione peroxidases and thioredoxin reductases. Selenoproteins, which play a key role in several biological processes, including ferroptosis, drug resistance, endoplasmic reticulum stress, and epigenetic processes, are guided by Se uptake. In this review, we critically analyze the molecular mechanisms of Se metabolism and its potential as a therapeutic target for cancer. Sec insertion sequence binding protein 2 (SECISBP2), which is a positive regulator for the expression of selenoproteins, would be a novel prognostic predictor and an alternate target for cancer. We highlight strategies that attempt to develop a novel Se metabolism-based approach to uncover a new metabolic drug target for cancer therapy. Moreover, we expect extensive clinical use of SECISBP2 as a specific biomarker in cancer therapy in the near future. Of note, scientists face additional challenges in conducting successful research, including investigations on anticancer peptides to target SECISBP2 intracellular protein.

Proton export alkalinizes intracellular pH and reprograms carbon metabolism to drive normal and malignant cell growth

Proton export is often considered a detoxifying process in animal cells, with monocarboxylate symporters coexporting excessive lactate and protons during glycolysis or the Warburg effect. We report a novel mechanism by which lactate/H+ export is sufficient to induce cell growth. Increased intracellular pH selectively activates catalysis by key metabolic gatekeeper enzymes HK1/PKM2/G6PDH, thereby enhancing glycolytic and pentose phosphate pathway carbon flux. The result is increased nucleotide levels, NADPH/NADP+ ratio, and cell proliferation. Simply increasing the lactate/proton symporter monocarboxylate transporter 4 (MCT4) or the sodium-proton antiporter NHE1 was sufficient to increase intracellular pH and give normal hematopoietic cells a significant competitive growth advantage in vivo. This process does not require additional cytokine triggers and is exploited in malignancy, where leukemogenic mutations epigenetically increase MCT4. Inhibiting MCT4 decreased intracellular pH and carbon flux and eliminated acute myeloid leukemia-initiating cells in mice without cytotoxic chemotherapy. Intracellular alkalization is a primitive mechanism by which proton partitioning can directly reprogram carbon metabolism for cell growth.

Metabolic therapy and bioenergetic analysis: The missing piece of the puzzle

BACKGROUND

Aberrant metabolism is recognized as a hallmark of cancer, a pillar necessary for cellular proliferation. Regarding bioenergetics (ATP generation), most cancers display a preference not only toward aerobic glycolysis ("Warburg effect") and glutaminolysis (mitochondrial substrate level-phosphorylation) but also toward other metabolites such as lactate, pyruvate, and fat-derived sources. These secondary metabolites can assist in proliferation but cannot fully cover ATP demands.

SCOPE OF REVIEW

The concept of a static metabolic profile is challenged by instances of heterogeneity and flexibility to meet fuel/anaplerotic demands. Although metabolic therapies are a promising tool to improve therapeutic outcomes, either via pharmacological targets or press-pulse interventions, metabolic plasticity is rarely considered. Lack of bioenergetic analysis in vitro and patient-derived models is hindering translational potential. Here, we review the bioenergetics of cancer and propose a simple analysis of major metabolic pathways, encompassing both affordable and advanced techniques. A comprehensive compendium of Seahorse XF bioenergetic measurements is presented for the first time.

MAJOR CONCLUSIONS

Standardization of principal readouts might help researchers to collect a complete metabolic picture of cancer using the most appropriate methods depending on the sample of interest.

Identification and Validation of a PPP1R12A-Related Five-Gene Signature Associated With Metabolism to Predict the Prognosis of Patients With Prostate Cancer

Background

Prostate cancer (PCa) is the most common malignant male neoplasm in the American male population. Our prior studies have demonstrated that protein phosphatase 1 regulatory subunit 12A (PPP1R12A) could be an efficient prognostic factor in patients with PCa, promoting further investigation. The present study attempted to construct a gene signature based on PPP1R12A and metabolism-related genes to predict the prognosis of PCa patients.

Methods

The mRNA expression profiles of 499 tumor and 52 normal tissues were extracted from The Cancer Genome Atlas (TCGA) database. We selected differentially expressed PPP1R12A-related genes among these mRNAs. Tandem affinity purification-mass spectrometry was used to identify the proteins that directly interact with PPP1R12A. Gene set enrichment analysis (GSEA) was used to extract metabolism-related genes. Univariate Cox regression analysis and a random survival forest algorithm were used to confirm optimal genes to build a prognostic risk model.

Results

We identified a five-gene signature (PPP1R12A, PTGS2, GGCT, AOX1, and NT5E) that was associated with PPP1R12A and metabolism in PCa, which effectively predicted disease-free survival (DFS) and biochemical relapse-free survival (BRFS). Moreover, the signature was validated by two internal datasets from TCGA and one external dataset from the Gene Expression Omnibus (GEO).

Conclusion

The five-gene signature is an effective potential factor to predict the prognosis of PCa, classifying PCa patients into high- and low-risk groups, which might provide potential novel treatment strategies for these patients.

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.

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.

Matrix-driven changes in metabolism support cytoskeletal activity to promote cell migration

The microenvironment provides both active and passive mechanical cues that regulate cell morphology, adhesion, migration, and metabolism. Although the cellular response to those mechanical cues often requires energy-intensive actin cytoskeletal remodeling and actomyosin contractility, it remains unclear how cells dynamically adapt their metabolic activity to altered mechanical cues to support migration. Here, we investigated the changes in cellular metabolic activity in response to different two-dimensional and three-dimensional microenvironmental conditions and how these changes relate to cytoskeletal activity and migration. Utilizing collagen micropatterning on polyacrylamide gels, intracellular energy levels and oxidative phosphorylation were found to be correlated with cell elongation and spreading and necessary for membrane ruffling. To determine whether this relationship holds in more physiological three-dimensional matrices, collagen matrices were used to show that intracellular energy state was also correlated with protrusive activity and increased with matrix density. Pharmacological inhibition of oxidative phosphorylation revealed that cancer cells rely on oxidative phosphorylation to meet the elevated energy requirements for protrusive activity and migration in denser matrices. Together, these findings suggest that mechanical regulation of cytoskeletal activity during spreading and migration by the physical microenvironment is driven by an altered metabolic profile.

Genomic adaptation of Pseudomonas strains to acidity and antibiotics in hydrothermal vents at Kolumbo submarine volcano, Greece

Although the rise of antibiotic and multidrug resistant bacteria is one of the biggest current threats to human health, our understanding of the mechanisms involved in antibiotic resistance selection remains scarce. We performed whole genome sequencing of 21 Pseudomonas strains, previously isolated from an active submarine volcano of Greece, the Kolumbo volcano. Our goal was to identify the genetic basis of the enhanced co-tolerance to antibiotics and acidity of these Pseudomonas strains. Pangenome analysis identified 10,908 Gene Clusters (GCs). It revealed that the numbers of phage-related GCs and sigma factors, which both provide the mechanisms of adaptation to environmental stressors, were much higher in the high tolerant Pseudomonas strains compared to the rest ones. All identified GCs of these strains were associated with antimicrobial and multidrug resistance. The present study provides strong evidence that the CO2-rich seawater of the volcano associated with low pH might be a reservoir of microorganisms carrying multidrug efflux-mediated systems and pumps. We, therefore, suggest further studies of other extreme environments (or ecosystems) and their associated physicochemical parameters (or factors) in the rise of antibiotic resistance.

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.

Metabolic Constants and Plasticity of Cancer Cells in a Limiting Glucose and Glutamine Microenvironment-A Pyruvate Perspective

The metabolism of cancer cells is an issue of dealing with fluctuating and limiting levels of nutrients in a precarious microenvironment to ensure their vitality and propagation. Glucose and glutamine are central metabolites for catabolic and anabolic metabolism, which is in the limelight of numerous diagnostic methods and therapeutic targeting. Understanding tumor metabolism in conditions of nutrient depletion is important for such applications and for interpreting the readouts. To exemplify the metabolic network of tumor cells in a model system, the fate ¹³C₆-glucose was tracked in a breast cancer cell line growing in variable low glucose/low glutamine conditions. ¹³C-glucose-derived metabolites allowed to deduce the engagement of metabolic pathways, namely glycolysis, the TCA-cycle including glutamine and pyruvate anaplerosis, amino acid synthesis (serine, glycine, aspartate, glutamate), gluconeogenesis, and pyruvate replenishment. While the metabolic program did not change, limiting glucose and glutamine supply reduced cellular metabolite levels and enhanced pyruvate recycling as well as pyruvate carboxylation for entry into the TCA-cycle. Otherwise, the same metabolic pathways, including gluconeogenesis, were similarly engaged with physiologically saturating as with limiting glucose and glutamine. Therefore, the metabolic plasticity in precarious nutritional microenvironment does not require metabolic reprogramming, but is based on dynamic changes in metabolite quantity, reaction rates, and directions of the existing metabolic network.

Glutamine-β-cyclodextrin for targeted doxorubicin delivery to triple-negative breast cancer tumors via the transporter ASCT2

Chemotherapy is the primary therapy for triple-negative breast cancer (TNBC) and the tumor-targeted delivery of chemotherapeutic drugs is necessary to minimize their side effects on normal tissues. TNBC cells display addictions to glutamine in culture, and the levels of the glutamine transporter, alanine-serine-cysteine transporter 2 (ASCT2), are elevated in many types of cancer. However, glutamine- or ASCT2-based carriers have not been used in tumor-targeted drug delivery. In this study, a novel derivative of β-cyclodextrin (β-CD), glutamine-β-cyclodextrin (GLN-CD), was developed by conjugating glutamine with the 6-hydroxy of β-CD, and GLN-CD was then used to prepare doxorubicin (DOX) inclusion complexes (DOX@GLN-CD) for TNBC treatment. GLN-CD and glutamine have similar ASCT2-binding sites, and GLN-CD has the potential to enter cells through ASCT2-dependent facilitated diffusion. An increase in the degree of substitution did not promote binding between GLN-CD and ASCT2. GLN-CD and DOX formed inclusion complexes at a molar ratio of 1 : 1. DOX@GLN-CD specifically accumulated in TNBC cells, including MDA-MB-231 and BT549 cells, where it subsequently induced G2/M blockade and apoptosis, but hardly affected nontumorigenic MCF10A cells. l-γ-Glutamyl-p-nitroanilide (GPNA), which is a specific inhibitor of ASCT2, antagonistically decreased the cellular uptake of DOX@GLN-CD by TNBC cells, which further confirmed the role of ASCT2 in DOX@GLN-CD transport. In vivo, DOX@GLN-CD accumulated specifically in tumors, achieved improved outcomes and minimized the toxic effects on main organs at the same dose as DOX. As a novel derivative of β-CD, GLN-CD is an effective carrier that can specifically deliver DOX to TNBC cells via targeting ASCT2 and minimize its uptake by normal cells.

Oxidative pentose phosphate pathway and glucose anaplerosis support maintenance of mitochondrial NADPH pool under mitochondrial oxidative stress

Mitochondrial NADPH protects cells against mitochondrial oxidative stress by serving as an electron donor to antioxidant defense systems. However, due to technical challenges, it still remains unknown as to the pool size of mitochondrial NADPH, its dynamics, and NADPH/NADP+ ratio. Here, we have systemically modulated production rates of H2O2 in mitochondria and assessed mitochondrial NADPH metabolism using iNap sensors, 13C glucose isotopic tracers, and a mathematical model. Using sensors, we observed decreases in mitochondrial NADPH caused by excessive generation of mitochondrial H2O2, whereas the cytosolic NADPH was maintained upon perturbation. We further quantified the extent of mitochondrial NADPH/NADP+ based on the mathematical analysis. Utilizing 13C glucose isotopic tracers, we found increased activity in the pentose phosphate pathway (PPP) accompanied small decreases in the mitochondrial NADPH pool, whereas larger decreases induced both PPP activity and glucose anaplerosis. Thus, our integrative and quantitative approach provides insight into mitochondrial NADPH metabolism during mitochondrial oxidative stress.

Metabolic cell communication within tumour microenvironment: models, methods and perspectives

Environmental cues are essential in defining tumour malignancy, by promoting tumour initiation, progression and metastatic spreading. Stromal cells may metabolically cooperate or compete with cancer cells, playing a mandatory role in defining cancer metabolic plasticity, potentially dictating the final tumour outcome. Assessing shared nutrients between different tumoural or stromal compartments is essential to understand the impact of environmental nutrients on the metabolic plasticity of tumours. Here, we review analytical and computational approaches for studying the tumour metabolic microenvironment, the destiny of nutrients shared among tumour and stromal populations, as well as the molecular modules of these metabolic relationships.

Hyperpolarized product selective saturating-excitations for determination of changes in metabolic reaction rates in real-time

Investigation of hyperpolarized substrate metabolism has been showing utility in real-time determination of in-cell and in vivo enzymatic activities. Intracellular reaction rates may vary during the course of a measurement, even on the very short time scales of visibility on hyperpolarized MR, due to many factors such as the availability of the substrate and co-factors in the intracellular space. Despite this potential variation, the kinetic analysis of hyperpolarized signals typically assumes that the same rate constant (and in many cases, the same rate) applies throughout the course of the reaction as observed via the build-up and decay of the hyperpolarized signals. We demonstrate here an acquisition approach that can null the need for such an assumption and enable the detection of instantaneous changes in the rate of the reaction during an ex vivo hyperpolarized investigation, (i.e. in the course of the decay of one hyperpolarized substrate dose administered to a viable tissue sample ex vivo). This approach utilizes hyperpolarized product selective saturating-excitation pulses. Similar pulses have been previously utilized in vivo for spectroscopic imaging. However, we show here favorable consequences to kinetic rate determinations in the preparations used. We implement this acquisition strategy for studies on perfused tissue slices and develop a theory that explains why this particular approach enables the determination of changes in enzymatic rates that are monitored via the chemical conversions of hyperpolarized substrates. Real-time changes in intracellular reaction rates are demonstrated in perfused brain, liver, and xenograft breast cancer tissue slices and provide another potential differentiation parameter for tissue characterization.

Carbamazepine, cadmium chloride and polybrominated diphenyl ether-47, synergistically modulate the expression of antioxidants and cell cycle biomarkers, in the marine fish cell line SAF-1

A wide range of contaminants, industrial by-products, plastics, and pharmaceutics belonging to various categories, have been found in sea water. Although these compounds are detected at concentrations that might be considered as sub-lethal, under certain conditions they could act synergistically producing unexpected effects in term of toxicity or perturbation of biochemical markers leading to standard pathway. In this study, the Sparus aurata fibroblast cell line SAF-1, was exposed to increasing concentrations of carbamazepine (CBZ), polybrominated diphenyl ether 47 (BDE-47) and cadmium chloride (CdCl₂) until 72 h, to evaluate the cytotoxicity and the expression of genes related to antioxidant defense, cell cycle and energetic balance. In general, both vitality and gene expression were affected by the exposure to the different toxicants, in terms of antioxidant defense and cell cycle control, showing the most significant effects in cells exposed to the mixture of the three compounds, respect to the single compounds separately. The synergic effect of the compounds on the analyzed biomarkers, underlie the potential negative impact of the contaminants on health of marine organisms.

Computational data mining method for isotopomer analysis in the quantitative assessment of metabolic reprogramming

Measurement of metabolic flux levels using stable isotope labeling has been successfully used to investigate metabolic redirection and reprogramming in living cells or tissues. The metabolic flux ratio between two reactions can be estimated from the ¹³C-labeling patterns of a few metabolites combined with the knowledge of atom mapping in the complicated metabolic network. However, it remains unclear whether an observed change in the labeling pattern of the metabolites is sufficient evidence of a shift in flux ratio between two metabolic states. In this study, a data analysis method was developed for the quantitative assessment of metabolic reprogramming. The Metropolis-Hastings algorithm was used with an in silico metabolic model to generate a probability distribution of metabolic flux levels under a condition in which the ¹³C-labeling pattern was observed. Reanalysis of literature data demonstrated that the developed method enables analysis of metabolic redirection using whole ¹³C-labeling pattern data. Quantitative assessment by Cohen’s effect size (d) enables a more detailed read-out of metabolic reprogramming information. The developed method will enable future applications of the metabolic isotopomer analysis to various targets, including cultured cells, whole tissues, and organs.

Diverse Roads Taken by 13C-Glucose-Derived Metabolites in Breast Cancer Cells Exposed to Limiting Glucose and Glutamine Conditions

In cancers, tumor cells are exposed to fluctuating nutrient microenvironments with limiting supplies of glucose and glutamine. While the metabolic program has been related to the expression of oncogenes, only fractional information is available on how variable precarious nutrient concentrations modulate the cellular levels of metabolites and their metabolic pathways. We thus sought to obtain an overview of the metabolic routes taken by ¹³C-glucose-derived metabolites in breast cancer MCF-7 cells growing in combinations of limiting glucose and glutamine concentrations. Isotopologue profiles of key metabolites were obtained by gas chromatography/mass spectrometry (GC/MS). They revealed that in limiting and standard saturating medium conditions, the same metabolic routes were engaged, including glycolysis, gluconeogenesis, as well as the TCA cycle with glutamine and pyruvate anaplerosis. However, the cellular levels of ¹³C-metabolites, for example, serine, alanine, glutamate, malate, and aspartate, were highly sensitive to the available concentrations and the ratios of glucose and glutamine. Notably, intracellular lactate concentrations did not reflect the Warburg effect. Also, isotopologue profiles of ¹³C-serine as well as ¹³C-alanine show that the same glucose-derived metabolites are involved in gluconeogenesis and pyruvate replenishment. Thus, anaplerosis and the bidirectional flow of central metabolic pathways ensure metabolic plasticity for adjusting to precarious nutrient conditions.

p13CMFA: Parsimonious 13C metabolic flux analysis

Deciphering the mechanisms of regulation of metabolic networks subjected to perturbations, including disease states and drug-induced stress, relies on tracing metabolic fluxes. One of the most informative data to predict metabolic fluxes are ¹³C based metabolomics, which provide information about how carbons are redistributed along central carbon metabolism. Such data can be integrated using ¹³C Metabolic Flux Analysis (¹³C MFA) to provide quantitative metabolic maps of flux distributions. However, ¹³C MFA might be unable to reduce the solution space towards a unique solution either in large metabolic networks or when small sets of measurements are integrated. Here we present parsimonious ¹³C MFA (p¹³CMFA), an approach that runs a secondary optimization in the ¹³C MFA solution space to identify the solution that minimizes the total reaction flux. Furthermore, flux minimization can be weighted by gene expression measurements allowing seamless integration of gene expression data with ¹³C data. As proof of concept, we demonstrate how p¹³CMFA can be used to estimate intracellular flux distributions from ¹³C measurements and transcriptomics data. We have implemented p¹³CMFA in Iso2Flux, our in-house developed isotopic steady-state ¹³C MFA software. The source code is freely available on GitHub (https://github.com/cfoguet/iso2flux/releases/tag/0.7.2).

¹³C Metabolic Flux Analysis (¹³C MFA) is a well-established technique that has proven to be a valuable tool in quantifying the metabolic flux profile of central carbon metabolism. When a biological system is incubated with a ¹³C-labeled substrate, ¹³C propagates to metabolites throughout the metabolic network in a flux and pathway-dependent manner. ¹³C MFA integrates measurements of ¹³C enrichment in metabolites to identify the flux distributions consistent with the measured ¹³C propagation. However, there is often a range of flux values that can lead to the observed ¹³C distribution. Indeed, either when the metabolic network is large or a small set of measurements are integrated, the range of valid solutions can be too wide to accurately estimate part of the underlying flux distribution. Here we propose to use flux minimization to select the best flux solution in the¹³C MFA solution space. Furthermore, this approach can integrate gene expression data to give greater weight to the minimization of fluxes through enzymes with low gene expression evidence in order to ensure that the selected solution is biologically relevant. The concept of using flux minimization to select the best solution is widely used in flux balance analysis, but it had never been applied in the framework of ¹³C MFA. We have termed this new approach parsimonious ¹³C MFA (p¹³CMFA).

Identification of potential diagnostic and prognostic biomarkers for prostate cancer

Prostate cancer (PCa) is one of the most common malignant tumors worldwide. The aim of the present study was to determine potential diagnostic and prognostic biomarkers for PCa. The GSE103512 dataset was downloaded, and the differentially expressed genes (DEGs) were screened. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction (PPI) analyses of DEGs were performed. The result of GO analysis suggested that the DEGs were mostly enriched in ‘carboxylic acid catabolic process’, ‘cell apoptosis’, ‘cell proliferation’ and ‘cell migration’. KEGG analysis results indicated that the DEGs were mostly concentrated in ‘metabolic pathways’, ‘ECM-receptor interaction’, the ‘PI3K-Akt pathway’ and ‘focal adhesion’. The PPI analysis results showed that Golgi membrane protein 1 (GOLM1), melanoma inhibitory activity member 3 (MIA3), ATP citrate lyase (ACLY) and G protein subunit β2 (GNB2) were the key genes in PCa, and the Module analysis revealed that they were associated with ‘ECM-receptor interaction’, ‘focal adhesion’, the ‘PI3K-Akt pathway’ and the ‘metabolic pathway’. Subsequently, the gene expression was confirmed using Gene Expression Profiling Interactive Analysis and the Human Protein Atlas. The results demonstrated that GOLM1 and ACLY expression was significantly upregulated (P<0.05) in PCa compared with that in normal tissues. Receiver operating characteristic and survival analyses were performed. The results showed that area under the curve values of these genes all exceeded 0.85, and high expression of these genes was associated with poor survival in patients with PCa. In conclusion, this study identified GOLM1 and ACLY in PCa, which may be potential diagnostic and prognostic biomarker of PCa.

Characterization of Cell Glycocalyx with Mass Spectrometry Methods

The cell membrane plays an important role in protecting the cell from its extracellular environment. As such, extensive work has been devoted to studying its structure and function. Crucial intercellular processes, such as signal transduction and immune protection, are mediated by cell surface glycosylation, which is comprised of large biomolecules, including glycoproteins and glycosphingolipids. Because perturbations in glycosylation could result in dysfunction of cells and are related to diseases, the analysis of surface glycosylation is critical for understanding pathogenic mechanisms and can further lead to biomarker discovery. Different mass spectrometry-based techniques have been developed for glycan analysis, ranging from highly specific, targeted approaches to more comprehensive profiling studies. In this review, we summarized the work conducted for extensive analysis of cell membrane glycosylation, particularly those employing liquid chromatography with mass spectrometry (LC-MS) in combination with various sample preparation techniques.

Sub-lethal doses of polybrominated diphenyl ethers affect some biomarkers involved in energy balance and cell cycle, via oxidative stress in the marine fish cell line SAF-1

Polybrominated diphenyl ethers (PBDEs) are a class of persistent contaminants which are found all over the world in the marine environment. Sparus aurata fibroblast cell line (SAF-1) was exposed to increasing concentrations of PBDEs 47 and 99, until 72 h to evaluate the cytotoxicity, reactive oxygen species (ROS) production and the expression of some selected molecular markers related to cell cycle, cell signaling, energetic balance and oxidative stress (p53, erk-1, hif-1α and nrf-2), by real-time PCR. Furthermore, SAF-1 cells were exposed for 7 and 15 days to sub-lethal concentrations, in order to evaluate the response of some biomarkers by immunoblotting (p53, ERK-1, AMPK, HIF-1α and NRF-2). After 48 and 72 h, the cells showed a significant decrease of cell vitality as well as an increase of intracellular ROS production. Gene expression analysis showed that sub-lethal concentrations of BDE-99 and 47, after 72 h, up-regulated cell cycle and oxidative stress biomarkers, although exposure to 100 μmol L^-1 down-regulated the selected markers related to cell cycle, cell signaling, energetic balance. After 7 and 15 days of sub-lethal doses exposure, all the analyzed markers resulted affected by the contaminants. Our results suggest that PBDEs influence the cells homeostasis first of all via oxidative stress, reducing the cell response and defense capacity and affecting its energetic levels. This situation of stress and energy imbalance could represents a condition that, modifying some of the analyzed biochemical pathways, would predispose to cellular transformation.

Sub-lethal Doses of Polybrominated Diphenyl Ethers, in Vitro, Promote Oxidative Stress and Modulate Molecular Markers Related to Cell Cycle, Antioxidant Balance and Cellular Energy Management

In the present study, we evaluated the effects of different concentrations of the polybrominated diphenyl ethers (PBDEs) BDE-209, BDE-47 and BDE-99, on the vitality and oxidative stress of a HS-68 human cell culture exposed to the compounds for three days. The results showed that for this exposure time, only the highest concentrations produced a significant vitality reduction and oxidative stress induction (p < 0.05), measured as reactive oxygen species (ROS). Subsequently, in order to verify the effects of sub-lethal doses, cells were exposed for a longer time and data collected, after 12 and 20 days, to study ROS production and some molecular markers related to cell cycle and stress (p53, pRB, PARP, c-Jun and c-Fos), antioxidant status and proliferation (ERK, c-Jun and c-Fos), energy balance (NRF2, AMPK, HIF). Most of the biomarkers were influenced by the treatments, indicating that sub-lethal doses of PBDEs, for longer time, can enhance the production of ROS, altering the energetic metabolism, cell cycle and antioxidant balance, determining possible negative effects on the cell proliferation equilibrium.

Recent advances and future directions in mantle cell lymphoma research: report of the 2018 mantle cell lymphoma consortium workshop

Mantle cell lymphoma (MCL) is an aggressive B-cell non-Hodgkin lymphoma characterized by the t(11;14) chromosomal translocation. This translocation most often results in overexpression of cyclin D1. MCL is clinically heterogeneous, outcomes are generally poor, and no standard treatment has been established. The recent approvals of ibrutinib and acalabrutinib have provided an additional therapeutic option; however, resistance has emerged as a significant issue and presents the need for more detailed studies of resistance mechanisms. Recent clinical trials have provided new perspectives on the relative efficacy and safety of various approaches for both transplant-eligible and transplant-ineligible patients. Multiple novel strategies are being evaluated in the treatment of MCL, including both targeted agents and cellular immunotherapies. At the Lymphoma Research Foundation's 13th MCL Workshop, researchers gathered to discuss research findings, clinical trial results, and future directions related to MCL, its biology, and its treatment. This report, which includes a summary of each presentation, aims to review recent findings in MCL research and highlight potential areas for future study.

Deep Transcriptomic Analysis of Black Rockfish (Sebastes schlegelii) Provides New Insights on Responses to Acute Temperature Stress

In the present study, we conducted an RNA-Seq analysis to characterize the genes and pathways involved in acute thermal and cold stress responses in the liver of black rockfish, a viviparous teleost that has the ability to cope with a wide range of temperature changes. A total of 584 annotated differentially expressed genes (DEGs) were identified in all three comparisons (HT vs NT, HT vs LT and LT vs NT). Based on an enrichment analysis, DEGs with a potential role in stress accommodation were classified into several categories, including protein folding, metabolism, immune response, signal transduction, molecule transport, membrane, and cell proliferation/apoptosis. Considering that thermal stress has a greater effect than cold stress in black rockfish, 24 shared DEGs in the intersection of the HT vs LT and HT vs NT groups were enriched in 2 oxidation-related gene ontology (GO) terms. Nine important heat-stress-reducing pathways were significantly identified and classified into 3 classes: immune and infectious diseases, organismal immune system and endocrine system. Eight DEGs (early growth response protein 1, bile salt export pump, abcb11, hsp70a, rtp3, 1,25-dihydroxyvitamin d(3) 24-hydroxylase, apoa4, transcription factor jun-b-like and an uncharacterized gene) were observed among all three comparisons, strongly implying their potentially important roles in temperature stress responses.

A guide to 13C metabolic flux analysis for the cancer biologist

Cancer metabolism is significantly altered from normal cellular metabolism allowing cancer cells to adapt to changing microenvironments and maintain high rates of proliferation. In the past decade, stable-isotope tracing and network analysis have become powerful tools for uncovering metabolic pathways that are differentially activated in cancer cells. In particular, ¹³C metabolic flux analysis (¹³C-MFA) has emerged as the primary technique for quantifying intracellular fluxes in cancer cells. In this review, we provide a practical guide for investigators interested in getting started with ¹³C-MFA. We describe best practices in ¹³C-MFA, highlight potential pitfalls and alternative approaches, and conclude with new developments that can further enhance our understanding of cancer metabolism.

Tracing tagged molecules can help researchers understand the altered metabolism of cancer cells. The abilities of cancer cells to multiply rapidly and invade new tissues are supported by metabolic alterations, which can be investigated by feeding tagged molecules to cells and tracing how they are metabolized. These techniques, such as ¹³C metabolic flux analysis (¹³C-MFA), have been perceived as difficult to use, but recent advances are making them more accessible. Maciek Antoniewicz, University of Delaware, Newark, USA, has published a practical guide for researchers wanting to use 13C-MFA. The review includes best practices, pitfalls, alternative approaches, and new developments, especially new user-friendly software that allows researchers without extensive training in mathematics, statistics, or coding to perform 13C-MFA. Broadening access to tools for investigating altered metabolic pathways may spur development of new cancer therapies targeting these pathways.

From correlation to causation: analysis of metabolomics data using systems biology approaches

INTRODUCTION

Metabolomics is a well-established tool in systems biology, especially in the top-down approach. Metabolomics experiments often results in discovery studies that provide intriguing biological hypotheses but rarely offer mechanistic explanation of such findings. In this light, the interpretation of metabolomics data can be boosted by deploying systems biology approaches.

OBJECTIVES

This review aims to provide an overview of systems biology approaches that are relevant to metabolomics and to discuss some successful applications of these methods.

METHODS

We review the most recent applications of systems biology tools in the field of metabolomics, such as network inference and analysis, metabolic modelling and pathways analysis.

RESULTS

We offer an ample overview of systems biology tools that can be applied to address metabolomics problems. The characteristics and application results of these tools are discussed also in a comparative manner.

CONCLUSIONS

Systems biology-enhanced analysis of metabolomics data can provide insights into the molecular mechanisms originating the observed metabolic profiles and enhance the scientific impact of metabolomics studies.

Targeting of stress response pathways in the prevention and treatment of cancer

The hallmarks of tumor tissue are not only genetic aberrations but also the presence of metabolic and oxidative stress as a result of hypoxia and lactic acidosis. The stress activates several prosurvival pathways including metabolic remodeling, autophagy, antioxidant response, mitohormesis, and glutaminolysis, whose upregulation in tumors is associated with a poor survival of patients, while their activation in healthy tissue with statins, metformin, physical activity, and natural compounds prevents carcinogenesis. This review emphasizes the dual role of stress response pathways in cancer and suggests the integrative understanding as a basis for the development of rational therapy targeting the stress response.

Overexpression of hypoxia-inducible factor and metabolic pathways: possible targets of cancer

Cancer, the main cause of human deaths in the modern world is a group of diseases. Anticancer drug discovery is a challenge for scientists because of involvement of multiple survival pathways of cancer cells. An extensive study on the regulation of each step of these pathways may help find a potential cancer target. Up-regulated HIF-1 expression and altered metabolic pathways are two classical characteristics of cancer. Oxygen-dependent (through pVHL, PHDs, calcium-mediated) and independent (through growth factor signaling pathway, mdm2 pathway, HSP90) regulation of HIF-1α leads to angiogenesis, metastasis, and cell survival. The two subunits of HIF-1 regulates in the same fashion through different mechanisms. HIF-1α translation upregulates via mammalian target of rapamycin and mitogen-activated protein kinase signaling pathways, whereas HIF-1β through calmodulin kinase. Further, the stabilized interactions of these two subunits are important for proper functioning. Also, metabolic pathways crucial for the formation of building blocks (pentose phosphate pathway) and energy generation (glycolysis, TCA cycle and catabolism of glutamine) are altered in cancer cells to protect them from oxidative stress and to meet the reduced oxygen and nutrient supply. Up-regulated anaerobic metabolism occurs through enhanced expression of hexokinase, phosphofructokinase, triosephosphate isomerase, glucose 6-phosphate dehydrogenase and down-regulation of aerobic metabolism via pyruvate dehydrogenase kinase and lactate dehydrogenase which compensate energy requirements along with high glucose intake. Controlled expression of these two pathways through their common intermediate may serve as potent cancer target in future.

Positional stable isotope tracer analysis reveals carbon routes during ammonia metabolism of Aedes aegypti mosquitoes

In Aedes aegypti females, the ammonia released during blood meal digestion is partially metabolized to facilitate the disposal of excess nitrogen. In this study, we used low- and high-resolution liquid chromatography-mass spectrometry (LC/MS) techniques to investigate the role of glucose during ammonia detoxification. Mosquitoes were fed a blood meal supplemented with [1,2-¹³C₂]glucose, and downstream metabolites were measured for 24 h. Quantification of [¹³C] amino acids in the entire mosquito body was conducted without sample derivatization using selected reaction monitoring of mass transitions that are indicative of the structural position of [¹³C] atom incorporation. Identification of unlabeled and [¹³C] isotopologs of 43 compounds, including amino acids, amino acid derivatives, and organic acids, was performed by high-resolution LC/MS techniques. Blood-fed mosquitoes synthesized [¹³C] metabolites in mainly 2 carbon positions from [1,2-¹³C₂]glucose. [¹³C₂]Ala and [¹³C₂]Pro were the most abundant and rapidly labeled amino acids synthesized. Additional [¹³C] amino acids, [¹³C] amino acid derivatives, and [¹³C] organic acids in 1 or 2 carbon positions were also identified. Two kinetic routes were proposed based on the incorporation of a [¹³C] atom at position 1 in specific amino acids. Our findings provide evidence that glucose is used for ammonia detoxification and [¹³C] uric acid synthesis through multiple metabolic pathways, uncovering a metabolic link at the carbon atomic level in ammonia metabolism of A. aegypti-Horvath, T. D., Dagan, S., Lorenzi, P. L., Hawke, D. H., Scaraffia, P. Y. Positional stable isotope tracer analysis reveals carbon routes during ammonia metabolism of Aedes aegypti mosquitoes.