Metabolomics Analysis of Hormone-Responsive and Triple-Negative Breast Cancer Cell Responses to Paclitaxel Identify Key Metabolic Differences.

To date, no targeted therapies are available to treat triple negative breast cancer (TNBC), while other breast cancer subtypes are responsive to current therapeutic treatment. Metabolomics was conducted to reveal differences in two hormone receptor-negative TNBC cell lines and two hormone receptor-positive Luminal A cell lines. Studies were conducted in the presence and absence of paclitaxel (Taxol). TNBC cell lines had higher levels of amino acids, branched-chain amino acids, nucleotides, and nucleotide sugars and lower levels of proliferation-related metabolites like choline compared with Luminal A cell lines. In the presence of paclitaxel, each cell line showed unique metabolic responses, with some similarities by type. For example, in the Luminal A cell lines, levels of lactate and creatine decreased while certain choline metabolites and myo-inositol increased with paclitaxel. In the TNBC cell lines levels of glutamine, glutamate, and glutathione increased, whereas lysine, proline, and valine decreased in the presence of drug. Profiling secreted inflammatory cytokines in the conditioned media demonstrated a greater response to paclitaxel in the hormone-positive Luminal cells compared with a secretion profile that suggested greater drug resistance in the TNBC cells. The most significant differences distinguishing the cell types based on pathway enrichment analyses were related to amino acid, lipid and carbohydrate metabolism pathways, whereas several biological pathways were differentiated between the cell lines following treatment.

Comparison of GC-MS and GC×GC-MS in the analysis of human serum samples for biomarker discovery.

We compared the performance of gas chromatography time-of-flight mass spectrometry (GC-MS) and comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-MS) for metabolite biomarker discovery. Metabolite extracts from 109 human serum samples were analyzed on both platforms with a pooled serum sample analyzed after every 9 biological samples for the purpose of quality control (QC). The experimental data derived from the pooled QC samples showed that the GC×GC-MS platform detected about three times as many peaks as the GC-MS platform at a signal-to-noise ratio SNR ≥ 50, and three times the number of metabolites were identified by mass spectrum matching with a spectral similarity score Rsim ≥ 600. Twenty-three metabolites had statistically significant abundance changes between the patient samples and the control samples in the GC-MS data set while 34 metabolites in the GC×GC-MS data set showed statistically significant differences. Among these two groups of metabolite biomarkers, nine metabolites were detected in both the GC-MS and GC×GC-MS data sets with the same direction and similar magnitude of abundance changes between the control and patient sample groups. Manual verification indicated that the difference in the number of the biomarkers discovered using these two platforms was mainly due to the limited resolution of chromatographic peaks by the GC-MS platform, which can result in severe peak overlap making subsequent spectrum deconvolution for metabolite identification and quantification difficult.

Genetic basis and selection of glyceollin elicitation in wild soybean.

Glyceollins, a family of phytoalexins elicited in legume species, play crucial roles in environmental stress response (e.g., defending against pathogens) and human health. However, little is known about the genetic basis of glyceollin elicitation. In the present study, we employed a metabolite-based genome-wide association (mGWA) approach to identify candidate genes involved in glyceollin elicitation in genetically diverse and understudied wild soybeans subjected to soybean cyst nematode. In total, eight SNPs on chromosomes 3, 9, 13, 15, and 20 showed significant associations with glyceollin elicitation. Six genes fell into two gene clusters that encode glycosyltransferases in the phenylpropanoid pathway and were physically close to one of the significant SNPs (ss715603454) on chromosome 9. Additionally, transcription factors (TFs) genes such as MYB and WRKY were also found as promising candidate genes within close linkage to significant SNPs on chromosome 9. Notably, four significant SNPs on chromosome 9 show epistasis and a strong signal for selection. The findings describe the genetic foundation of glyceollin biosynthesis in wild soybeans; the identified genes are predicted to play a significant role in glyceollin elicitation regulation in wild soybeans. Additionally, how the epistatic interactions and selection influence glyceollin variation in natural populations deserves further investigation to elucidate the molecular mechanism of glyceollin biosynthesis.

Differential Inhibition of Anaplerotic Pyruvate Carboxylation and Glutaminolysis-Fueled Anabolism Underlies Distinct Toxicity of Selenium Agents in Human Lung Cancer.

Past chemopreventive human trials on dietary selenium supplements produced controversial outcomes. They largely employed selenomethionine (SeM)-based diets. SeM was less toxic than selenite or methylseleninic acid (MSeA) to lung cancer cells. We thus investigated the toxic action of these Se agents in two non-small cell lung cancer (NSCLC) cell lines and ex vivo organotypic cultures (OTC) of NSCLC patient lung tissues. Stable isotope-resolved metabolomics (SIRM) using 13C6-glucose and 13C5,15N2-glutamine tracers with gene knockdowns were employed to examine metabolic dysregulations associated with cell type- and treatment-dependent phenotypic changes. Inhibition of key anaplerotic processes, pyruvate carboxylation (PyC) and glutaminolysis were elicited by exposure to MSeA and selenite but not by SeM. They were accompanied by distinct anabolic dysregulation and reflected cell type-dependent changes in proliferation/death/cell cycle arrest. NSCLC OTC showed similar responses of PyC and/or glutaminolysis to the three agents, which correlated with tissue damages. Altogether, we found differential perturbations in anaplerosis-fueled anabolic pathways to underlie the distinct anti-cancer actions of the three Se agents, which could also explain the failure of SeM-based chemoprevention trials.

Acetaminophen dosing of humans results in blood transcriptome and metabolome changes consistent with impaired oxidative phosphorylation.

UNLABELLED: The diagnosis and management of drug-induced liver injury (DILI) is hindered by the limited utility of traditional clinical chemistries. It has recently been shown that hepatotoxicants can produce compound-specific changes in the peripheral blood (PB) transcriptome in rodents, suggesting that the blood transcriptome might provide new biomarkers of DILI. To investigate in humans, we used DNA microarrays as well as serum metabolomic methods to characterize changes in the transcriptome and metabolome in serial PB samples obtained from six healthy adults treated with a 4-g bolus dose of acetaminophen (APAP) and from three receiving placebo. Treatment did not cause liver injury as assessed by traditional liver chemistries. However, 48 hours after exposure, treated subjects showed marked down-regulation of genes involved in oxidative phosphorylation/mitochondrial function that was not observed in the placebos (P < 1.66E-19). The magnitude of down-regulation was positively correlated with the percent of APAP converted to the reactive metabolite N-acetyl-p-benzoquinone-imide (NAPQI) (r= 0.739;P= 0.058). In addition, unbiased analysis of the serum metabolome revealed an increase in serum lactate from 24 to 72 hours postdosing in the treated subjects alone (P< 0.005). Similar PB transcriptome changes were observed in human overdose patients and rats receiving toxic doses. CONCLUSION: The single 4-g APAP dose produced a transcriptome signature in PB cells characterized by down-regulation of oxidative phosphorylation genes accompanied by increased serum lactate. Similar gene expression changes were observed in rats and several patients after consuming hepatotoxic doses of APAP. The timing of the changes and the correlation with NAPQI production are consistent with mechanisms known to underlie APAP hepatoxicity. These studies support the further exploration of the blood transcriptome for biomarkers of DILI.

Microbial modulation of host body composition and plasma metabolic profile.

The gut microbiota is a critical mediator of nutrition and disease risk. Like most complex traits, the microbiome is under genetic regulation and differs between inbred strains of mice. We tested the effect of fecal microbiota transplantation (FMT) on obesity, and plasma glucose. For this study, we collected microbiota from 2 inbred strains of mice which differ in adiposity and glucose tolerance, C57BL/6J and WSB/EiJ. C57BL/6J female mice (n = 18) were first treated with antibiotics for 4 weeks to ablate the microbiota. Following ablation, the mice were transplanted with microbiota from a C57BL/6J or a WSB/EiJ mouse and clinical traits and plasma metabolomic profiles were interrogated at 2- and 4-weeks post-transplantation. Unexpectedly, the mice receiving WSB/EiJ microbiota increased adiposity but decreased plasma glucose. Metabolomic and 16S microbiota profiling indicated broad metabolic changes occurred during and after FMT. Detailed analysis of these interactions demonstrated specific microbiota-host metabolite interactions which may alter disease susceptibility.

Metabolomic profiling of a modified alcohol liquid diet model for liver injury in the mouse uncovers new markers of disease.

Metabolomic evaluation of urine and liver was conducted to assess the biochemical changes that occur as a result of alcohol-induced liver injury. Male C57BL/6J mice were fed an isocaloric control- or alcohol-containing liquid diet with 35% of calories from corn oil, 18% protein and 47% carbohydrate/alcohol for up to 36 days ad libitum. Alcohol treatment was initiated at 7 g/kg/day and gradually reached a final dose of 21 g/kg/day. Urine samples were collected at 22, 30 and 36 days and, in additional treatment groups, liver and serum samples were harvested at 28 days. Steatohepatitis was induced in the alcohol-fed group since a 5-fold increase in serum alanine aminotransferase activity, a 6-fold increase in liver injury score (necrosis, inflammation and steatosis) and an increase in lipid peroxidation in liver were observed. Liver and urine samples were analyzed by nuclear magnetic resonance spectroscopy and electrospray infusion/Fourier transform ion cyclotron resonance-mass spectrometry. In livers of alcohol-treated mice the following changes were noted. Hypoxia and glycolysis were activated as evidenced by elevated levels of alanine and lactate. Tyrosine, which is required for l-DOPA and dopamine as well as thyroid hormones, was elevated possibly reflecting alterations of basal metabolism by alcohol. A 4-fold increase in the prostacyclin inhibitor 7,10,13,16-docosatetraenoic acid, a molecule important for regulation of platelet formation and blood clotting, may explain why chronic drinking causes serious bleeding problems. Metabolomic analysis of the urine revealed that alcohol treatment leads to decreased excretion of taurine, a metabolite of glutathione, and an increase in lactate, n-acetylglutamine and n-acetylglycine. Changes in the latter two metabolites suggest an inhibition of the kidney enzyme aminoacylase I and may be useful as markers for alcohol consumption.

Stable Isotope-Resolved Metabolomic Differences between Hormone-Responsive and Triple-Negative Breast Cancer Cell Lines.

PURPOSE: To conduct an exploratory study to identify mechanisms that differentiate Luminal A (BT474 and MCF-7) and triple-negative (MDA-MB-231 and MDA-MB-468) breast cancer (BCa) cell lines to potentially provide novel therapeutic targets based on differences in energy utilization. METHODS: Cells were cultured in media containing either [U-13C]-glucose or [U-13C]-glutamine for 48 hours. Conditioned media and cellular extracts were analyzed by 1H and 13C NMR spectroscopy. RESULTS: MCF-7 cells consumed the most glucose, producing the most lactate, demonstrating the greatest Warburg effect-associated energy utilization. BT474 cells had the highest tricarboxylic acid cycle (TCA) activity. The majority of energy utilization patterns in MCF-7 cells were more similar to MDA-MB-468 cells, while the patterns for BT474 cells were more similar to MDA-MB-231 cells. Compared to the Luminal A cell lines, TNBC cell lines consumed more glutamine and less glucose. BT474 and MDA-MB-468 cells produced high amounts of 13C-glycine from media [U-13C]-glucose which was integrated into glutathione, indicating de novo synthesis. CONCLUSIONS: Stable isotopic resolved metabolomics using 13C substrates provided mechanistic information about energy utilization that was difficult to interpret using 1H data alone. Overall, cell lines that have different hormone receptor status have different energy utilization requirements, even if they are classified by the same clinical BCa subtype; and these differences offer clues about optimizing treatment strategies.

Effects of a prolonged standardized diet on normalizing the human metabolome.

BACKGROUND: Although the effects of acute dietary interventions on the human metabolome have been studied, the extent to which the metabolome can be normalized by extended dietary standardization has not yet been examined. OBJECTIVE: We examined the metabolic profiles of healthy human subjects after extended dietary standardization to see whether the inherent variation in the human metabolome could be decreased. DESIGN: A cohort of 10 healthy volunteers was admitted to a clinical research center for 2 wk of dietary standardization. Daily serum and urine samples and serum samples at a 2-wk follow-up visit were collected. The samples were analyzed by (1)H nuclear magnetic resonance (NMR) spectroscopy and multivariate statistical analyses. RESULTS: NMR spectra were collected to globally profile the higher-concentration metabolites (>micromol/L concentrations). Metabolic changes were observed in some serum samples after day 1 or the 2-wk follow-up visit. For each subject, the samples from all other days had similar profiles. The urinary metabolome reflected no effects from dietary standardization. Pooled 24-h urine samples were studied, which indicated that any normalization that does occur would do so in <24 h. CONCLUSIONS: For both the urinary and serum metabolome, a single day of dietary standardization appears to provide all of the normalization that is achievable within the strict controls implemented in a clinical research setting. After 24 h, the subjects remain in their metabolic space; the remaining intra- and intersubject variations appear to be influenced by variables such as genetics, age, and lifestyle.

High-throughput nuclear magnetic resonance metabolomic footprinting for tissue engineering.

We report a high-throughput (HTP) nuclear magnetic resonance (NMR) method for analysis of media components and a metabolic schematic to help easily interpret the data. Spin-lattice relaxation values and concentrations were measured for 19 components and 2 internal referencing agents in pure and 2-day conditioned, hormonally defined media from a 3-dimensional (3D) multicoaxial human bioartificial liver (BAL). The (1)H NMR spectral signal-to-noise ratio is 21 for 0.16 mM alanine in medium and is obtained in 12 min using a 400 MHz NMR spectrometer. For comparison, 2D gel cultures and 3D multicoaxial BALs were batch cultured, with medium changed every day for 15 days after inoculation with human liver cells in Matrigel-collagen type 1 gels. Glutamine consumption was higher by day 8 in the BAL than in 2D culture; lactate production was lower through the 15-day culture period. Alanine was the primary amino acid produced and tracked with lactate or urea production. Glucose and pyruvate consumption were similar in the BAL and 2D cultures. NMR analysis permits quality assurance of the bioreactor by identifying contaminants. Ethanol was observed because of a bioreactor membrane "wetting" procedure. A biochemical scheme is presented illustrating bioreactor metabolomic footprint results and demonstrating how this can be translated to modify bioreactor operational parameters or quality assurance issues.