Analysis of Stable Isotope Assisted Metabolomics Data Acquired by High Resolution Mass Spectrometry

Untangling the web of glioblastoma treatment resistance using a multi-omic and multidisciplinary approach

Glioblastoma (GBM), the most common human brain tumor, has been notoriously resistant to treatment. As a result, the dismal overall survival of GBM patients has not changed over the past three decades. GBM has been stubbornly resistant to checkpoint inhibitor immunotherapies, which have been remarkably effective in the treatment of other tumors. It is clear that GBM resistance to therapy is multifactorial. Although therapeutic transport into brain tumors is inhibited by the blood brain barrier, there is evolving evidence that overcoming this barrier is not the predominant factor. GBMs generally have a low mutation burden, exist in an immunosuppressed environment and they are inherently resistant to immune stimulation, all of which contribute to treatment resistance. In this review, we evaluate the contribution of multi-omic approaches (genomic and metabolomic) along with analyzing immune cell populations and tumor biophysical characteristics to better understand and overcome GBM multifactorial resistance to treatment.

Stable Isotope Tracing Reveals an Altered Fate of Glucose in N-Acetyltransferase 1 Knockout Breast Cancer Cells

Breast cancer is one of the leading causes of cancer death. Recent studies found that arylamine N-acetyltransferase 1 (NAT1) is frequently upregulated in breast cancer, further suggesting NAT1 could be a potential therapeutic target for breast cancer. Previous publications have established that NAT1 knockout (KO) in breast cancer cell lines leads to growth reduction both in vitro and in vivo and metabolic changes. These reports suggest that NAT1 contributes to the energy metabolism of breast cancer cells. Proteomic analysis and non-targeted metabolomics suggested that NAT1 KO may change the fate of glucose as it relates to the TCA/KREB cycle of the mitochondria of breast cancer cells. In this current study, we used [U-13C]-glucose stable isotope resolved metabolomics to determine the effect of NAT1 KO on the metabolic profile of MDA-MB-231 breast cancer cells. We incubated breast cancer cells (MDA-MB-231 cells) and NAT1 Crispr KO cells (KO#2 and KO#5) with [U-13C]-glucose for 24 h. Tracer incubation polar metabolites from the cells were extracted and analyzed by 2DLC-MS, and metabolite differences were compared between the parental and NAT1 KO cells. Differences consistent between the two KO cells were considered changes due to the loss of NAT1. The data revealed decreases in the 13C enrichment of TCA/Krebs cycle intermediates in NAT1 KO cells compared to the MDA-MB-231 cells. Specifically, 13C-labeled citrate, isocitrate, a-ketoglutarate, fumarate, and malate were all decreased in NAT1 KO cells. We also detected increased 13C-labeled L-lactate levels in the NAT1 KO cells and decreased 13C enrichment in some nucleotides. Pathway analysis showed that arginine biosynthesis, alanine, aspartate and glutamate metabolism, and the TCA cycle were most affected. These data provide additional evidence supporting the impacts of NAT1 knockout on cellular energy metabolism. The data suggest that NAT1 expression is important for the proper functioning of mitochondria and the flux of glucose through the TCA/Krebs cycle in breast cancer cells. The metabolism changes in the fate of glucose in NAT1 KO breast cancer cells offer more insight into the role of NAT1 in energy metabolism and the growth of breast cancer cells. These data provide additional evidence that NAT1 may be a useful therapeutic target for breast cancer.

Development of Pseudo-targeted Profiling of Isotopic Metabolomics using Combined Platform of High Resolution Mass Spectrometry and Triple Quadrupole Mass Spectrometry with Application of 13C6-Glucose Tracing in HepG2 Cells

Isotope tracing assisted metabolic analysis is becoming a unique tool to understand metabolic regulation in cell biology and biomedical research. Targeted mass spectrometry analysis based on selected reaction monitoring (SRM) has been widely applied in isotope tracing experiment with the advantages of high sensitivity and broad linearity. However, its application for new pathway discovery is largely restrained by molecular coverage. To overcome this limitation, we describe a strategy called pseudo-targeted profiling of isotopic metabolomics (PtPIM) to expand the analysis of isotope labeled metabolites beyond the limit of known pathways and chemical standards. Pseudo-targeted metabolomics was first established with ion transitions and retention times transformed from high resolution (orbitrap) mass spectrometry. Isotope labeled MRM transitions were then generated according to chemical formulas of fragments, which were derived from accurate ion masses acquired by HRMS. An in-house software "PseudoIsoMRM" was developed to simulate isotope labeled ion transitions in batch mode and correct the interference of natural isotopologues. This PtPIM strategy was successfully applied to study ¹³C₆-glucose traced HepG2 cells. As 313 molecules determined as analysis targets, a total of 4104 ion transitions were simulated to monitor ¹³C labeled metabolites in positive-negative switching mode of QQQ mass spectrometer with minimum dwell time of 0.3 ms achieved. A total of 68 metabolites covering glycolysis, TCA cycle, nucleotide biosynthesis, one-carbon metabolism and related derivatives were found to be labeled (> 2%) in HepG2 cells. Active pentose phosphate pathway was observed with diverse labeling status of glycolysis intermediates. Meanwhile, our PtPIM strategy revealed that rotenone severely suppressed mitochondrial function e.g. oxidative phosphorylation and fatty acid beta-oxidation. In this case, anaerobic respiration became the major source of energy metabolism by producing abundant lactate. Conclusively, the simulation based PtPIM method demonstrates a strategy to broaden metabolite coverage in isotope tracing analysis independent of standard chemicals.

Glutamine uptake and catabolism is required for myofibroblast formation and persistence

BACKGROUND

Fibrosis and extracellular matrix remodeling are mediated by resident cardiac fibroblasts (CFs). In response to injury, fibroblasts activate, differentiating into specialized synthetic and contractile myofibroblasts producing copious extracellular matrix proteins (e.g., collagens). Myofibroblast persistence in chronic diseases, such as HF, leads to progressive cardiac dysfunction and maladaptive remodeling. We recently reported that an increase in αKG (alpha-ketoglutarate) bioavailability, which contributes to enhanced αKG-dependent lysine demethylase activity and chromatin remodeling, is required for myofibroblast formation. Therefore, we aimed to determine the substrates and metabolic pathways contributing to αKG biosynthesis and their requirement for myofibroblast formation.

METHODS

Stable isotope metabolomics identified glutaminolysis as a key metabolic pathway required for αKG biosynthesis and myofibroblast formation, therefore we tested the effects of pharmacologic inhibition (CB-839) or genetic deletion of glutaminase (Gls1-/-) on myofibroblast formation in both murine and human cardiac fibroblasts. We employed immunofluorescence staining, functional gel contraction, western blotting, and bioenergetic assays to determine the myofibroblast phenotype.

RESULTS

Carbon tracing indicated enhanced glutaminolysis mediating increased αKG abundance. Pharmacological and genetic inhibition of glutaminolysis prevented myofibroblast formation indicated by a reduction in αSMA+ cells, collagen gel contraction, collagen abundance, and the bioenergetic response. Inhibition of glutaminolysis also prevented TGFβ-mediated histone demethylation and supplementation with cell-permeable αKG rescued the myofibroblast phenotype. Importantly, inhibition of glutaminolysis was sufficient to prevent myofibroblast formation in CFs isolated from the human failing heart.

CONCLUSIONS

These results define glutaminolysis as necessary for myofibroblast formation and persistence, providing substantial rationale to evaluate several new therapeutic targets to treat cardiac fibrosis.

Differential metabolic requirement governed by transcription factor c-Maf dictates innate γδT17 effector functionality in mice and humans

Cellular metabolism has been proposed to govern distinct γδ T cell effector functions, but the underlying molecular mechanisms remain unclear. We show that interleukin-17 (IL-17)-producing γδ T (γδT17) and interferon-γ (IFN-γ)-producing γδ T (γδT1) cells have differential metabolic requirements and that the rate-limiting enzyme isocitrate dehydrogenase 2 (IDH2) acts as a metabolic checkpoint for their effector functions. Intriguingly, the transcription factor c-Maf regulates γδT17 effector function through direct regulation of IDH2 promoter activity. Moreover, mTORC2 affects the expression of c-Maf and IDH2 and subsequent IL-17 production in γδ T cells. Deletion of c-Maf in γδ T cells reduces metastatic lung cancer development, suggesting c-Maf as a potential target for cancer immune therapy. We show that c-Maf also controls IL-17 production in human γδ T cells from peripheral blood and in oral cancers. These results demonstrate a critical role of the transcription factor c-Maf in regulating γδT17 effector function through IDH2-mediated metabolic reprogramming.

Cell cycle induction in human cardiomyocytes is dependent on biosynthetic pathway activation

AIMS

The coordinated gene and metabolic programs that facilitate cardiomyocyte entry and progression in the cell cycle are poorly understood. The purpose of this study was to identify the metabolic changes that influence myocyte proliferation.

METHODS AND RESULTS

In adult mouse cardiomyocytes and human induced pluripotent stem cell cardiomyocytes (hiPS-CMs), cell cycle initiation by ectopic expression of Cyclin B1, Cyclin D1, CDK1, and CDK4 (termed 4F) downregulated oxidative phosphorylation genes and upregulated genes that regulate ancillary biosynthetic pathways of glucose metabolism. Results from metabolic analyses and stable isotope tracing experiments indicate that 4F-mediated cell cycle induction in hiPS-CMs decreases glucose oxidation and oxidative phosphorylation and augments NAD+, glycogen, hexosamine, phospholipid, and serine biosynthetic pathway activity. Interventions that diminish NAD+ synthesis, serine synthesis, or protein O-GlcNAcylation decreased 4F-mediated cell cycle entry. In a gain of function approach, we overexpressed phosphoenolpyruvate carboxykinase 2 (PCK2), which can drive carbon from the Krebs cycle to the glycolytic intermediate pool, and found that PCK2 augments 4F-mediated cell cycle entry.

CONCLUSIONS

These findings suggest that a metabolic shift from catabolic to anabolic activity is a critical step for cardiomyocyte cell cycle entry and is required to facilitate proliferation.

Bioengineered Models to Study Microenvironmental Regulation of Glioblastoma Metabolism

Despite extensive research and aggressive therapies, glioblastoma (GBM) remains a central nervous system malignancy with poor prognosis. The varied histopathology of GBM suggests a landscape of differing microenvironments and clonal expansions, which may influence metabolism, driving tumor progression. Indeed, GBM metabolic plasticity in response to differing nutrient supply within these microenvironments has emerged as a key driver of aggressiveness. Additionally, emergent biophysical and biochemical interactions in the tumor microenvironment (TME) are offering new perspectives on GBM metabolism. Perivascular and hypoxic niches exert crucial roles in tumor maintenance and progression, facilitating metabolic relationships between stromal and tumor cells. Alterations in extracellular matrix and its biophysical characteristics, such as rigidity and topography, regulate GBM metabolism through mechanotransductive mechanisms. This review highlights insights gained from deployment of bioengineering models, including engineered cell culture and mathematical models, to study the microenvironmental regulation of GBM metabolism. Bioengineered approaches building upon histopathology measurements may uncover potential therapeutic strategies that target both TME-dependent mechanotransductive and biomolecular drivers of metabolism to tackle this challenging disease. Longer term, a concerted effort integrating in vitro and in silico models predictive of patient therapy response may offer a powerful advance toward tailoring of treatment to patient-specific GBM characteristics.

Understanding the fundamentals of microbial remediation with emphasize on metabolomics

The post-genomic tool metabolomics is a great advancement in science and technology which acquires novel strategies and pathways to analyze various biological compounds. Metabolomics aids in retrieving the qualitative and quantitative data from the various biological system. The current review is focused on the application of metabolomics in bioremediation and helps to focus on the xenobiotic compounds which are discharged into the environment and have long term impact. The microbial based biodegradation can be effectively used along with the combination of metabolomic approach for a better understanding of the breakdown of certain recalcitrant. Additionally, this review also discusses the candidate gene approach which helps to comprehend the functional analysis of microbial genes in response to different contaminants. Therefore, this review intends to discuss the metabolomics in bioremediation by studying the complete set of metabolites involved during the process of degradation and their interaction with the environment.

Evaluation of disease staging and chemotherapeutic response in non-small cell lung cancer from patient tumor-derived metabolomic data

OBJECTIVES

Despite extensive effort, the search for clinically-relevant metabolite biomarkers for early detection, disease monitoring, and outcome prediction in lung cancer remains unfulfilled. Although biofluid evaluation has been explored, the complexity inherent in metabolite data and the dynamic discrepancy between metabolites in biofluids vs. tumor tissue have prevented conclusive results. This proof-of-concept study explored models predictive of staging and chemotherapy response based on metabolomic analysis of fresh, patient-derived non-small cell lung cancer (NSCLC) core biopsies.

MATERIALS AND METHODS

Samples (n = 36) were evaluated with high-resolution 2DLC-MS/MS and ¹³C-glucose enrichment, and the data were comprehensively analyzed with machine learning techniques. Patients were categorized as Disease-Control (DC) [encompassing complete-response (CR), partial-response (PR), and stable-disease (SD)] and Progressive-Disease (PD) in terms of first-line chemotherapy. Four major types of learning methods (partial least squares discriminant analysis (PLS-DA), support vector machines (SVM), artificial neural networks, and random forests (RF)) were applied to differentiate between positive (DC and CR/PR) and poor (PD and SD/PD) responses, and between stage I/II/III and stage IV disease. Models were trained with forward feature selection based on variable importance and tested on validation subsets.

RESULTS

The models predicted patient classifications in the validation subsets with AUC (95 % CI): DC vs. PD (SVM), 0.970(0.961-0.979); CR/PR vs. SD/PD (PLS-DA), 0.880(0.865-0.895); stage I/II/III vs. IV (SVM), 0.902(0.880-0.924). Highest performing model was SVM for DC vs. PD (balanced accuracy = 0.92; kappa = 0.74).

CONCLUSION

This study illustrates a comprehensive evaluation of patient tumor-specific metabolic profiles, with the potential to identify disease stage and predict response to first-line chemotherapy.

Considerations for using isolated cell systems to understand cardiac metabolism and biology

Changes in myocardial metabolic activity are fundamentally linked to cardiac health and remodeling. Primary cardiomyocytes, induced pluripotent stem cell-derived cardiomyocytes, and transformed cardiomyocyte cell lines are common models used to understand how (patho)physiological conditions or stimuli contribute to changes in cardiac metabolism. These cell models are helpful also for defining metabolic mechanisms of cardiac dysfunction and remodeling. Although technical advances have improved our capacity to measure cardiomyocyte metabolism, there is often heterogeneity in metabolic assay protocols and cell models, which could hinder data interpretation and discernment of the mechanisms of cardiac (patho)physiology. In this review, we discuss considerations for integrating cardiomyocyte cell models with techniques that have become relatively common in the field, such as respirometry and extracellular flux analysis. Furthermore, we provide overviews of metabolic assays that complement XF analyses and that provide information on not only catabolic pathway activity, but biosynthetic pathway activity and redox status as well. Cultivating a more widespread understanding of the advantages and limitations of metabolic measurements in cardiomyocyte cell models will continue to be essential for the development of coherent metabolic mechanisms of cardiac health and pathophysiology.

Palbociclib treatment alters nucleotide biosynthesis and glutamine dependency in A549 cells

BACKGROUND

Aberrant activity of cell cycle proteins is one of the key somatic events in non-small cell lung cancer (NSCLC) pathogenesis. In most NSCLC cases, the retinoblastoma protein tumor suppressor (RB) becomes inactivated via constitutive phosphorylation by cyclin dependent kinase (CDK) 4/6, leading to uncontrolled cell proliferation. Palbociclib, a small molecule inhibitor of CDK4/6, has shown anti-tumor activity in vitro and in vivo, with recent studies demonstrating a functional role for palbociclib in reprogramming cellular metabolism. While palbociclib has shown efficacy in preclinical models of NSCLC, the metabolic consequences of CDK4/6 inhibition in this context are largely unknown.

METHODS

In our study, we used a combination of stable isotope resolved metabolomics using [U-13C]-glucose and multiple in vitro metabolic assays, to interrogate the metabolic perturbations induced by palbociclib in A549 lung adenocarcinoma cells. Specifically, we assessed changes in glycolytic activity, the pentose phosphate pathway (PPP), and glutamine utilization. We performed these studies following palbociclib treatment with simultaneous silencing of RB1 to define the pRB-dependent changes in metabolism.

RESULTS

Our studies revealed palbociclib does not affect glycolytic activity in A549 cells but decreases glucose metabolism through the PPP. This is in part via reducing activity of glucose 6-phosphate dehydrogenase, the rate limiting enzyme in the PPP. Additionally, palbociclib enhances glutaminolysis to maintain mitochondrial respiration and sensitizes A549 cells to the glutaminase inhibitor, CB-839. Notably, the effects of palbociclib on both the PPP and glutamine utilization occur in an RB-dependent manner.

CONCLUSIONS

Together, our data define the metabolic impact of palbociclib treatment in A549 cells and may support the targeting CDK4/6 inhibition in combination with glutaminase inhibitors in NSCLC patients with RB-proficient tumors.

Transcription factor c-Maf is a checkpoint that programs macrophages in lung cancer

Macrophages have been linked to tumor initiation, progression, metastasis, and treatment resistance. However, the transcriptional regulation of macrophages driving the protumor function remains elusive. Here, we demonstrate that the transcription factor c-Maf is a critical controller for immunosuppressive macrophage polarization and function in cancer. c-Maf controls many M2-related genes and has direct binding sites within a conserved noncoding sequence of the Csf-1r gene and promotes M2-like macrophage-mediated T cell suppression and tumor progression. c-Maf also serves as a metabolic checkpoint regulating the TCA cycle and UDP-GlcNAc biosynthesis, thus promoting M2-like macrophage polarization and activation. Additionally, c-Maf is highly expressed in tumor-associated macrophages (TAMs) and regulates TAM immunosuppressive function. Deletion of c-Maf specifically in myeloid cells results in reduced tumor burden with enhanced antitumor T cell immunity. Inhibition of c-Maf partly overcomes resistance to anti-PD-1 therapy in a subcutaneous LLC tumor model. Similarly, c-Maf is expressed in human M2 and tumor-infiltrating macrophages/monocytes as well as circulating monocytes of human non-small cell lung carcinoma (NSCLC) patients and critically regulates their immunosuppressive activity. The natural compound β-glucan downregulates c-Maf expression on macrophages, leading to enhanced antitumor immunity in mice. These findings establish a paradigm for immunosuppressive macrophage polarization and transcriptional regulation by c-Maf and suggest that c-Maf is a potential target for effective tumor immunotherapy.

Loss of Rb1 Enhances Glycolytic Metabolism in Kras-Driven Lung Tumors In Vivo

Dysregulated metabolism is a hallmark of cancer cells and is driven in part by specific genetic alterations in various oncogenes or tumor suppressors. The retinoblastoma protein (pRb) is a tumor suppressor that canonically regulates cell cycle progression; however, recent studies have highlighted a functional role for pRb in controlling cellular metabolism. Here, we report that loss of the gene encoding pRb (Rb1) in a transgenic mutant Kras-driven model of lung cancer results in metabolic reprogramming. Our tracer studies using bolus dosing of [U-¹³C]-glucose revealed an increase in glucose carbon incorporation into select glycolytic intermediates. Consistent with this result, Rb1-depleted tumors exhibited increased expression of key glycolytic enzymes. Interestingly, loss of Rb1 did not alter mitochondrial pyruvate oxidation compared to lung tumors with intact Rb1. Additional tracer studies using [U-¹³C,¹⁵N]-glutamine and [U-¹³C]-lactate demonstrated that loss of Rb1 did not alter glutaminolysis or utilization of circulating lactate within the tricarboxylic acid cycle (TCA) in vivo. Taken together, these data suggest that the loss of Rb1 promotes a glycolytic phenotype, while not altering pyruvate oxidative metabolism or glutamine anaplerosis in Kras-driven lung tumors.

Integration of flux measurements and pharmacological controls to optimize stable isotope-resolved metabolomics workflows and interpretation

Stable isotope-resolved metabolomics (SIRM) provides information regarding the relative activity of numerous metabolic pathways and the contribution of nutrients to specific metabolite pools; however, SIRM experiments can be difficult to execute, and data interpretation is challenging. Furthermore, standardization of analytical procedures and workflows remain significant obstacles for widespread reproducibility. Here, we demonstrate the workflow of a typical SIRM experiment and suggest experimental controls and measures of cross-validation that improve data interpretation. Inhibitors of glycolysis and oxidative phosphorylation as well as mitochondrial uncouplers serve as pharmacological controls, which help define metabolic flux configurations that occur under well-controlled metabolic states. We demonstrate how such controls and time course labeling experiments improve confidence in metabolite assignments as well as delineate metabolic pathway relationships. Moreover, we demonstrate how radiolabeled tracers and extracellular flux analyses integrate with SIRM to improve data interpretation. Collectively, these results show how integration of flux methodologies and use of pharmacological controls increase confidence in SIRM data and provide new biological insights.

Integrating comprehensive two-dimensional gas chromatography mass spectrometry and parallel two-dimensional liquid chromatography mass spectrometry for untargeted metabolomics

The diverse characteristics and large number of entities make metabolite separation challenging in metabolomics. To date, there is not a singular instrument capable of analyzing all types of metabolites. In order to achieve a better separation for higher peak capacity and accurate metabolite identification and quantification, we integrated GC × GC-MS and parallel 2DLC-MS for analysis of polar metabolites. To test the performance of the developed system, 13 rats were fed different diets to form two animal groups. Polar metabolites extracted from rat livers were analyzed by GC × GC-MS, parallel 2DLC-MS (-) and parallel 2DLC-MS (+), respectively. By integrating all data together, 58 metabolites were detected with significant change in their abundance levels between groups (p≤ 0.05). Of the 58 metabolites, three metabolites were detected in two platforms and two in all three platforms. Manual examination showed that discrepancy of metabolite regulation measured by different platforms was mainly caused by the poor shape of chromatographic peaks resulting from low instrument response. Pathway analysis demonstrated that integrating the results from multiple platforms increased the confidence of metabolic pathway assignment.

Profiling of Polar Metabolites in Mouse Feces Using Four Analytical Platforms to Study the Effects Of Cathelicidin-Related Antimicrobial Peptide in Alcoholic Liver Disease

Alterations in gut bacterial homeostasis result in changes in intestinal metabolites. To investigate the effects of alcohol on fecal metabolites and the role of cathelicidin-related antimicrobial peptide (CRAMP) in alcoholic liver disease (ALD), CRAMP knockout (KO) and their control wild type (WT) mice were fed a Lieber-DeCarli liquid diet with or without alcohol. Polar metabolites in mouse feces were analyzed by GC × GC-MS and 2DLC-MS, and the concentrations of short chain fatty acids (SCFAs) were measured by GC-MS. A total of 95 and 190 metabolites were detected by GC × GC-MS and 2DLC-MS, respectively. Among the significantly changed metabolites, taurine and nicotinic acid were decreased in WT mice fed alcohol, which were also down-regulated in KO mice fed without alcohol. Interestingly, these two metabolites were increased in KO mice fed alcohol compared to them in WT controls. Additionally, SCFAs were significantly decreased in WT mice fed alcohol and in KO mice fed without alcohol, whereas two branched-chain SCFAs were increased by alcohol treatment in KO mice. In summary, the analytical platforms employed in this study successfully dissected the alterations of polar metabolites and SCFAs in fecal samples, which helped understand the effects of alcohol consumption and CRAMP in intestinal metabolism and alcohol-induced liver injury.

Cardiac mesenchymal cells from diabetic mice are ineffective for cell therapy-mediated myocardial repair

Although cell therapy improves cardiac function after myocardial infarction, highly variable results and limited understanding of the underlying mechanisms preclude its clinical translation. Because many heart failure patients are diabetic, we examined how diabetic conditions affect the characteristics of cardiac mesenchymal cells (CMC) and their ability to promote myocardial repair in mice. To examine how diabetes affects CMC function, we isolated CMCs from non-diabetic C57BL/6J (CMCWT) or diabetic B6.BKS(D)-Leprdb/J (CMCdb/db) mice. When CMCs were grown in 17.5 mM glucose, CMCdb/db cells showed > twofold higher glycolytic activity and a threefold higher expression of Pfkfb3 compared with CMCWT cells; however, culture of CMCdb/db cells in 5.5 mM glucose led to metabolic remodeling characterized by normalization of metabolism, a higher NAD+/NADH ratio, and a sixfold upregulation of Sirt1. These changes were associated with altered extracellular vesicle miRNA content as well as proliferation and cytotoxicity parameters comparable to CMCWT cells. To test whether this metabolic improvement of CMCdb/db cells renders them suitable for cell therapy, we cultured CMCWT or CMCdb/db cells in 5.5 mM glucose and then injected them into infarcted hearts of non-diabetic mice (CMCWT, n = 17; CMCdb/db, n = 13; Veh, n = 14). Hemodynamic measurements performed 35 days after transplantation showed that, despite normalization of their properties in vitro, and unlike CMCWT cells, CMCdb/db cells did not improve load-dependent and -independent parameters of left ventricular function. These results suggest that diabetes adversely affects the reparative capacity of CMCs and that modulating CMC characteristics via culture in lower glucose does not render them efficacious for cell therapy.

Integration of flux measurements to resolve changes in anabolic and catabolic metabolism in cardiac myocytes

Although ancillary pathways of glucose metabolism are critical for synthesizing cellular building blocks and modulating stress responses, how they are regulated remains unclear. In the present study, we used radiometric glycolysis assays, [¹³C₆]-glucose isotope tracing, and extracellular flux analysis to understand how phosphofructokinase (PFK)-mediated changes in glycolysis regulate glucose carbon partitioning into catabolic and anabolic pathways. Expression of kinase-deficient or phosphatase-deficient 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase in rat neonatal cardiomyocytes co-ordinately regulated glycolytic rate and lactate production. Nevertheless, in all groups, >40% of glucose consumed by the cells was unaccounted for via catabolism to pyruvate, which suggests entry of glucose carbons into ancillary pathways branching from metabolites formed in the preparatory phase of glycolysis. Analysis of ¹³C fractional enrichment patterns suggests that PFK activity regulates glucose carbon incorporation directly into the ribose and the glycerol moieties of purines and phospholipids, respectively. Pyrimidines, UDP-N-acetylhexosamine, and the fatty acyl chains of phosphatidylinositol and triglycerides showed lower ¹³C incorporation under conditions of high PFK activity; the isotopologue ¹³C enrichment pattern of each metabolite indicated limitations in mitochondria-engendered aspartate, acetyl CoA and fatty acids. Consistent with this notion, high glycolytic rate diminished mitochondrial activity and the coupling of glycolysis to glucose oxidation. These findings suggest that a major portion of intracellular glucose in cardiac myocytes is apportioned for ancillary biosynthetic reactions and that PFK co-ordinates the activities of the pentose phosphate, hexosamine biosynthetic, and glycerolipid synthesis pathways by directly modulating glycolytic intermediate entry into auxiliary glucose metabolism pathways and by indirectly regulating mitochondrial cataplerosis.

Analysis of stable isotope assisted metabolomics data acquired by GC-MS

Stable isotope assisted metabolomics (SIAM) measures the abundance levels of metabolites in a particular pathway using stable isotope tracers (e.g., ¹³C, ¹⁸O and/or ¹⁵N). We report a method termed signature ion approach for analysis of SIAM data acquired on a GC-MS system equipped with an electron ionization (EI) ion source. The signature ion is a fragment ion in EI mass spectrum of a derivatized metabolite that contains all atoms of the underivatized metabolite, except the hydrogen atoms lost during derivatization. In this approach, GC-MS data of metabolite standards were used to recognize the signature ion from the EI mass spectra acquired from stable isotope labeled samples, and a linear regression model was used to deconvolute the intensity of overlapping isotopologues. A mixture score function was also employed for cross-sample chromatographic peak list alignment to recognize the chromatographic peaks generated by the same metabolite in different samples, by simultaneously evaluating the similarity of retention time and EI mass spectrum of two chromatographic peaks. Analysis of a mixture of 16 ¹³C-labeled and 16 unlabeled amino acids showed that the signature ion approach accurately identified and quantified all isotopologues. Analysis of polar metabolite extracts from cells respectively fed with uniform ¹³C-glucose and ¹³C-glutamine further demonstrated that this method can also be used to analyze the complex data acquired from biological samples.