Stable Isotope Resolved Metabolomics Studies \u3cem\u3ein ex vivo\u3c/em\u3e Tissue Slices

An important component of this methodology is to assess the role of the tumor microenvironment on tumor growth and survival. To tackle this problem, we have adapted the original approach of Warburg (Warburg, 1923), by combining thin tissue slices with Stable Isotope Resolved Metabolomics (SIRM) to determine detailed metabolic activity of human tissues. SIRM enables the tracing of metabolic transformations of source molecules such as glucose or glutamine over defined time periods, and is a requirement for detailed pathway tracing and flux analysis. In our approach, we maintain freshly resected tissue slices (both cancerous and non- cancerous from the same organ of the same subject) in cell culture media, and treat with appropriate stable isotope-enriched nutrients, e.g. 13C6-glucose or 13C5, 15N2 -glutamine. These slices are viable for at least 24 h, and make it possible to eliminate systemic influence on the target tissue metabolism while maintaining the original 3D cellular architecture. It is therefore an excellent pre-clinical platform for assessing the effect of therapeutic agents on target tissue metabolism and their therapeutic efficacy on individual patients (Xie et al., 2014; Sellers et al., 2015)

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

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

Chloroformate Derivatization for Tracing the Fate of Amino Acids in Cells and Tissues by Multiple Stable Isotope Resolved Metabolomics (mSIRM)

Amino acids have crucial roles in central metabolism, both anabolic and catabolic. To elucidate these roles, steady-state concentrations of amino acids alone are insufficient, as each amino acid participates in multiple pathways and functions in a complex network, which can also be compartmentalized. Stable Isotope-Resolved Metabolomics (SIRM) is an approach that uses atom-resolved tracking of metabolites through biochemical transformations in cells, tissues, or whole organisms. Using different elemental stable isotopes to label multiple metabolite precursors makes it possible to resolve simultaneously the utilization of these precursors in a single experiment. Conversely, a single precursor labeled with two (or more) different elemental isotopes can trace the allocation of e.g. C and N atoms through the network. Such dual-label experiments however challenge the resolution of conventional mass spectrometers, which must distinguish the neutron mass differences among different elemental isotopes. This requires ultrahigh resolution Fourier transform mass spectrometry (UHR-FTMS). When combined with direct infusion nano-electrospray ion source (nano-ESI), UHR-FTMS can provide rapid, global, and quantitative analysis of all possible mass isotopologues of metabolites. Unfortunately, very low mass polar metabolites such as amino acids can be difficult to analyze by current models of UHR-FTMS, plus the high salt content present in typical cell or tissue polar extracts may cause unacceptable ion suppression for sources such as nano-ESI. Here we describe a modified method of ethyl chloroformate (ECF) derivatization of amino acids to enable rapid quantitative analysis of stable isotope labeled amino acids using nano-ESI UHR-FTMS. This method showed excellent linearity with quantifiable limits in the low nanomolar range represented in microgram quantities of biological specimens, which results in extracts with total analyte abundances in the low to sub-femtomole range. We have applied this method to profile amino acids and their labeling patterns in 13C and 2H doubly labeled PC9 cell extracts, cancerous and non-cancerous tissue extracts from a lung cancer patient and their protein hydrolysates as well as plasma extracts from mice fed with a liquid diet containing 13C6-glucose. The multi-element isotopologue distributions provided key insights into amino acid metabolism and intracellular pools in human lung cancer tissues in high detail. The 13C labeling of Asp and Glu revealed de novo synthesis of these amino acids from 13C6-glucose via the Krebs cycle, specifically the elevated level of 13C3-labeled Asp and Glu in cancerous versus non-cancerous lung tissues was consistent with enhanced pyruvate carboxylation. In addition, tracking the fate of double tracers, (13C6-Glc + 2H2-Gly or 13C6-Glc + 2H3-Ser) in PC9 cells clearly resolved pools of Ser and Gly synthesized de novo from 13C6-Glc (13C3-Ser and 13C2-Gly) versus Ser and Gly derived from external sources (2H3-Ser, 2H2-Gly). Moreover the complex 2H labeling patterns of the latter were results of Ser and Gly exchange through active Ser-Gly one-carbon metabolic pathway in PC9 cells

Exploring Cancer Metabolism Using Stable Isotope-Resolved Metabolomics (SIRM)

Metabolic reprogramming is a hallmark of cancer. The changes in metabolism are adaptive to permit proliferation, survival, and eventually metastasis in a harsh environment. Stable isotope-resolved metabolomics (SIRM) is an approach that uses advanced approaches of NMR and mass spectrometry to analyze the fate of individual atoms from stable isotope-enriched precursors to products to deduce metabolic pathways and networks. The approach can be applied to a wide range of biological systems, including human subjects. This review focuses on the applications of SIRM to cancer metabolism and its use in understanding drug actions

Probing the Metabolic Phenotype of Breast Cancer Cells by Multiple Tracer Stable Isotope Resolved Metabolomics

Breast cancers vary by their origin and specific set of genetic lesions, which gives rise to distinct phenotypes and differential response to targeted and untargeted chemotherapies. To explore the functional differences of different breast cell types, we performed Stable Isotope Resolved Metabolomics (SIRM) studies of one primary breast (HMEC) and three breast cancer cells (MCF-7, MDAMB-231, and ZR75-1) having distinct genotypes and growth characteristics, using 13C6-glucose, 13C-1+2-glucose, 13C5,15N2-Gln, 13C3-glycerol, and 13C8-octanoate as tracers. These tracers were designed to probe the central energy producing and anabolic pathways (glycolysis, pentose phosphate pathway, Krebs Cycle, glutaminolysis, nucleotide synthesis and lipid turnover). We found that glycolysis was not associated with the rate of breast cancer cell proliferation, glutaminolysis did not support lipid synthesis in primary breast or breast cancer cells, but was a major contributor to pyrimidine ring synthesis in all cell types; anaplerotic pyruvate carboxylation was activated in breast cancer versus primary cells. We also found that glucose metabolism in individual breast cancer cell lines differed between in vitro cultures and tumor xenografts, but not the metabolic distinctions between cell lines, which may reflect the influence of tumor architecture/microenvironment

A novel deconvolution method for modeling UDP-N-acetyl-D-glucosamine biosynthetic pathways based on 13C mass isotopologue profiles under non-steady-state conditions

<p>Abstract</p> <p>Background</p> <p>Stable isotope tracing is a powerful technique for following the fate of individual atoms through metabolic pathways. Measuring isotopic enrichment in metabolites provides quantitative insights into the biosynthetic network and enables flux analysis as a function of external perturbations. NMR and mass spectrometry are the techniques of choice for global profiling of stable isotope labeling patterns in cellular metabolites. However, meaningful biochemical interpretation of the labeling data requires both quantitative analysis and complex modeling. Here, we demonstrate a novel approach that involved acquiring and modeling the timecourses of ¹³C isotopologue data for UDP-<it>N</it>-acetyl-<smcaps>D</smcaps>-glucosamine (UDP-GlcNAc) synthesized from [U-¹³C]-glucose in human prostate cancer LnCaP-LN3 cells. UDP-GlcNAc is an activated building block for protein glycosylation, which is an important regulatory mechanism in the development of many prominent human diseases including cancer and diabetes.</p> <p>Results</p> <p>We utilized a stable isotope resolved metabolomics (SIRM) approach to determine the timecourse of ¹³C incorporation from [U-¹³C]-glucose into UDP-GlcNAc in LnCaP-LN3 cells. ¹³C Positional isotopomers and isotopologues of UDP-GlcNAc were determined by high resolution NMR and Fourier transform-ion cyclotron resonance-mass spectrometry. A novel simulated annealing/genetic algorithm, called 'Genetic Algorithm for Isotopologues in Metabolic Systems' (GAIMS) was developed to find the optimal solutions to a set of simultaneous equations that represent the isotopologue compositions, which is a mixture of isotopomer species. The best model was selected based on information theory. The output comprises the timecourse of the individual labeled species, which was deconvoluted into labeled metabolic units, namely glucose, ribose, acetyl and uracil. The performance of the algorithm was demonstrated by validating the computed fractional ¹³C enrichment in these subunits against experimental data. The reproducibility and robustness of the deconvolution were verified by replicate experiments, extensive statistical analyses, and cross-validation against NMR data.</p> <p>Conclusions</p> <p>This computational approach revealed the relative fluxes through the different biosynthetic pathways of UDP-GlcNAc, which comprises simultaneous sequential and parallel reactions, providing new insight into the regulation of UDP-GlcNAc levels and <it>O</it>-linked protein glycosylation. This is the first such analysis of UDP-GlcNAc dynamics, and the approach is generally applicable to other complex metabolites comprising distinct metabolic subunits, where sufficient numbers of isotopologues can be unambiguously resolved and accurately measured.</p

NMR Methods for Determining Lipid Turnover via Stable Isotope Resolved Metabolomics

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

Altered regulation of metabolic pathways in human lung cancer discerned by 13C stable isotope-resolved metabolomics (SIRM)

<p>Abstract</p> <p>Background</p> <p>Metabolic perturbations arising from malignant transformation have not been systematically characterized in human lung cancers <it>in situ</it>. Stable isotope resolved metabolomic analysis (SIRM) enables functional analysis of gene dysregulations in lung cancer. To this purpose, metabolic changes were investigated by infusing uniformly labeled ¹³C-glucose into human lung cancer patients, followed by resection and processing of paired non-cancerous lung and non small cell carcinoma tissues. NMR and GC-MS were used for ¹³C-isotopomer-based metabolomic analysis of the extracts of tissues and blood plasma.</p> <p>Results</p> <p>Many primary metabolites were consistently found at higher levels in lung cancer tissues than their surrounding non-cancerous tissues. ¹³C-enrichment in lactate, Ala, succinate, Glu, Asp, and citrate was also higher in the tumors, suggesting more active glycolysis and Krebs cycle in the tumor tissues. Particularly notable were the enhanced production of the Asp isotopomer with three ¹³C-labeled carbons and the buildup of ¹³C-2,3-Glu isotopomer in lung tumor tissues. This is consistent with the transformations of glucose into Asp or Glu via glycolysis, anaplerotic pyruvate carboxylation (PC), and the Krebs cycle. PC activation in tumor tissues was also shown by an increased level of pyruvate carboxylase mRNA and protein.</p> <p>Conclusion</p> <p>PC activation – revealed here for the first time in human subjects – may be important for replenishing the Krebs cycle intermediates which can be diverted to lipid, protein, and nucleic acid biosynthesis to fulfill the high anabolic demands for growth in lung tumor tissues. We hypothesize that this is an important event in non-small cell lung cancer and possibly in other tumor development.</p

Rhabdomyosarcoma cells show an energy producing anabolic metabolic phenotype compared with primary myocytes

<p>Abstract</p> <p>Background</p> <p>The functional status of a cell is expressed in its metabolic activity. We have applied stable isotope tracing methods to determine the differences in metabolic pathways in proliferating Rhabdomysarcoma cells (Rh30) and human primary myocytes in culture. Uniformly ¹³C-labeled glucose was used as a source molecule to follow the incorporation of ¹³C into more than 40 marker metabolites using NMR and GC-MS. These include metabolites that report on the activity of glycolysis, Krebs' cycle, pentose phosphate pathway and pyrimidine biosynthesis.</p> <p>Results</p> <p>The Rh30 cells proliferated faster than the myocytes. Major differences in flux through glycolysis were evident from incorporation of label into secreted lactate, which accounts for a substantial fraction of the glucose carbon utilized by the cells. Krebs' cycle activity as determined by ¹³C isotopomer distributions in glutamate, aspartate, malate and pyrimidine rings was considerably higher in the cancer cells than in the primary myocytes. Large differences were also evident in de novo biosynthesis of riboses in the free nucleotide pools, as well as entry of glucose carbon into the pyrimidine rings in the free nucleotide pool. Specific labeling patterns in these metabolites show the increased importance of anaplerotic reactions in the cancer cells to maintain the high demand for anabolic and energy metabolism compared with the slower growing primary myocytes. Serum-stimulated Rh30 cells showed higher degrees of labeling than serum starved cells, but they retained their characteristic anabolic metabolism profile. The myocytes showed evidence of de novo synthesis of glycogen, which was absent in the Rh30 cells.</p> <p>Conclusion</p> <p>The specific ¹³C isotopomer patterns showed that the major difference between the transformed and the primary cells is the shift from energy and maintenance metabolism in the myocytes toward increased energy and anabolic metabolism for proliferation in the Rh30 cells. The data further show that the mitochondria remain functional in Krebs' cycle activity and respiratory electron transfer that enables continued accelerated glycolysis. This may be a common adaptive strategy in cancer cells.</p

Profiling Thiol Metabolites and Quantification of Cellular Glutathione Using FT-ICR-MS Spectrometry

We describe preparation and use of the quaternary ammonium-based α-iodoacetamide QDE and its isotopologue *QDE as reagents for chemoselective derivatization of cellular thiols. Direct addition of the reagents to live cells followed by adduct extraction into n-butanol and analysis by FT-ICR-MS provided a registry of matched isotope peaks from which molecular formulae of thiol metabolites were derived. Acidification to pH 4 during cell lysis and adduct formation further improves the chemoselectivity for thiol derivatization. Examination of A549 human lung adenocarcinoma cells using this approach revealed cysteine, cysteinylglycine, glutathione, and homocysteine as principal thiol metabolites as well as the sulfinic acid hypotaurine. The method is also readily applied to quantify the thiol metabolites, as demonstrated here by the quantification of both glutathione and glutathione disulfide in A549 cells at concentrations of 34.4 ± 11.5 and 10.1 ± 4.0 nmol/mg protein, respectively