Ion-Pairing Chromatography and Amine Derivatization Provide Complementary Approaches for the Targeted LC-MS Analysis of the Polar Metabolome.

Liquid chromatography coupled to mass spectrometry is a key metabolomics/metabonomics technology. Reversed-phase liquid chromatography (RPLC) is very widely used as a separation step, but typically has poor retention of highly polar metabolites. Here, we evaluated the combination of two alternative methods for improving retention of polar metabolites based on 6-aminoquinoloyl-N-hydroxysuccinidimyl carbamate derivatization for amine groups, and ion-pairing chromatography (IPC) using tributylamine as an ion-pairing agent to retain acids. We compared both of these methods to RPLC and also to each other, for targeted analysis using a triple-quadrupole mass spectrometer, applied to a library of ca. 500 polar metabolites. IPC and derivatization were complementary in terms of their coverage: combined, they improved the proportion of metabolites with good retention to 91%, compared to just 39% for RPLC alone. The combined method was assessed by analyzing a set of liver extracts from aged male and female mice that had been treated with the polyphenol compound ampelopsin. Not only were a number of significantly changed metabolites detected, but also it could be shown that there was a clear interaction between ampelopsin treatment and sex, in that the direction of metabolite change was opposite for males and females.

Indisulam targets RNA splicing and metabolism to serve as a therapeutic strategy for high-risk neuroblastoma.

Neuroblastoma is the most common paediatric solid tumour and prognosis remains poor for high-risk cases despite the use of multimodal treatment. Analysis of public drug sensitivity data showed neuroblastoma lines to be sensitive to indisulam, a molecular glue that selectively targets RNA splicing factor RBM39 for proteosomal degradation via DCAF15-E3-ubiquitin ligase. In neuroblastoma models, indisulam induces rapid loss of RBM39, accumulation of splicing errors and growth inhibition in a DCAF15-dependent manner. Integrative analysis of RNAseq and proteomics data highlight a distinct disruption to cell cycle and metabolism. Metabolic profiling demonstrates metabolome perturbations and mitochondrial dysfunction resulting from indisulam. Complete tumour regression without relapse was observed in both xenograft and the Th-MYCN transgenic model of neuroblastoma after indisulam treatment, with RBM39 loss, RNA splicing and metabolic changes confirmed in vivo. Our data show that dual-targeting of metabolism and RNA splicing with anticancer indisulam is a promising therapeutic approach for high-risk neuroblastoma.

Automated Annotation of Untargeted All-Ion Fragmentation LC-MS Metabolomics Data with MetaboAnnotatoR.

Untargeted metabolomics and lipidomics LC-MS experiments produce complex datasets, usually containing tens of thousands of features from thousands of metabolites whose annotation requires additional MS/MS experiments and expert knowledge. All-ion fragmentation (AIF) LC-MS/MS acquisition provides fragmentation data at no additional experimental time cost. However, analysis of such datasets requires reconstruction of parent-fragment relationships and annotation of the resulting pseudo-MS/MS spectra. Here, we propose a novel approach for automated annotation of isotopologues, adducts, and in-source fragments from AIF LC-MS datasets by combining correlation-based parent-fragment linking with molecular fragment matching. Our workflow focuses on a subset of features rather than trying to annotate the full dataset, saving time and simplifying the process. We demonstrate the workflow in three human serum datasets containing 599 features manually annotated by experts. Precision and recall values of 82-92% and 82-85%, respectively, were obtained for features found in the highest-rank scores (1-5). These results equal or outperform those obtained using MS-DIAL software, the current state of the art for AIF data annotation. Further validation for other biological matrices and different instrument types showed variable precision (60-89%) and recall (10-88%) particularly for datasets dominated by nonlipid metabolites. The workflow is freely available as an open-source R package, MetaboAnnotatoR, together with the fragment libraries from Github (https://github.com/gggraca/MetaboAnnotatoR).

The Effects of a Ketogenic Medium-Chain Triglyceride Diet on the Feces in Dogs With Idiopathic Epilepsy.

Consumption of diets containing medium chain triglycerides have been shown to confer neuroprotective and behavior modulating effects. We aimed to identify metabolic and microbiome perturbations in feces that are associated with consumption of a medium chain triglyceride ketogenic diet (MCT-KD) in dogs with idiopathic epilepsy. We used 16S rRNA gene sequencing to generate microbiome profiles and ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) to generate lipidomic profiles of canine feces. We made comparisons between the MCT-KD, standardized placebo diet and baseline pre-trial diet phases. Consumption of the MCT-KD resulted in a significant increase in the species richness (α-diversity) of bacterial communities found in the feces when compared to the baseline diet. However, phylogenetical diversity between samples (beta-diversity) was not affected by diet. An unnamed Bacteroidaceae species within genus 5-7N15 was identified by LEfSe as a potential biomarker associated with consumption of the MCT-KD, showing an increased abundance (p = 0.005, q = 0.230) during consumption of MCT-KD. In addition, unclassified members of families Erysipelotrichaceae (p = 0.013, q = 0.335) and Fusobacteriaceae (p = 0.022, q = 0.358) were significantly increased during MCT-KD consumption compared to baseline. Blautia sp. and Megamonas sp. instead were decreased during consumption of either placebo or MCT-KD (p = 0.045, q = 0.449, and p = 0.039, q = 0.449, respectively). Bacteroidaceae, including genus 5-7N15, have previously been associated with non-aggressive behavior in dogs. In addition, 5-7N15 is correlated in humans with Akkermansia, a genus known to be involved in the neuroprotective effect of ketogenic diets in mice models of seizures. Five metabolite features, tentatively identified as long chain triglycerides, were significantly higher after consumption of the placebo diet, but no unique features were identified after consumption of the MCT-KD. The data presented in this study highlight significant changes shown in both the fecal microbiome and lipidome as a result of consumption of the MCT-KD. Elucidating the global canine gut response to MCT consumption will improve our understanding of the potential mechanisms which confer anti-seizure and behavior modulating effects. Further studies should aim to characterize the gut microbiome of both dogs with epilepsy and healthy controls.

From Samples to Insights into Metabolism: Uncovering Biologically Relevant Information in LC-HRMS Metabolomics Data.

Untargeted metabolomics (including lipidomics) is a holistic approach to biomarker discovery and mechanistic insights into disease onset and progression, and response to intervention. Each step of the analytical and statistical pipeline is crucial for the generation of high-quality, robust data. Metabolite identification remains the bottleneck in these studies; therefore, confidence in the data produced is paramount in order to maximize the biological output. Here, we outline the key steps of the metabolomics workflow and provide details on important parameters and considerations. Studies should be designed carefully to ensure appropriate statistical power and adequate controls. Subsequent sample handling and preparation should avoid the introduction of bias, which can significantly affect downstream data interpretation. It is not possible to cover the entire metabolome with a single platform; therefore, the analytical platform should reflect the biological sample under investigation and the question(s) under consideration. The large, complex datasets produced need to be pre-processed in order to extract meaningful information. Finally, the most time-consuming steps are metabolite identification, as well as metabolic pathway and network analysis. Here we discuss some widely used tools and the pitfalls of each step of the workflow, with the ultimate aim of guiding the reader towards the most efficient pipeline for their metabolomics studies.

Microdialysis Workflow for Metabotyping Superficial Pathologies: Application to Burn Injury.

Burn injury can be a devastating traumatic injury, with long-term personal and social implications for the patient. The many complex local and disseminating pathological processes underlying burn injury's clinical challenges are orchestrated from the site of injury and develop over time, yet few studies of the molecular basis of these mechanisms specifically explore the local signaling environment. Those that do are typically destructive in nature and preclude the collection of longitudinal temporal data. Burn injury therefore exemplifies a superficial temporally dynamic pathology for which experimental sampling typically prioritizes either specificity to the local burn site or continuous collection from circulation. Here, we present an exploratory approach to the targeted elucidation of complex, local, acutely temporally dynamic interstitia through its application to burn injury. Subcutaneous microdialysis is coupled with ultraperformance liquid chromatography-mass spectrometry (UPLC-MS) analysis, permitting the application of high-throughput metabolomic profiling to samples collected both continuously and specifically from the burn site. We demonstrate this workflow's high yield of burn-altered metabolites including the complete structural elucidation of niacinamide and uric acid, two compounds potentially involved in the pathology of burn injury. Further understanding the metabolic changes induced by burn injury will help to guide therapeutic intervention in the future. This approach is equally applicable to the analysis of other tissues and pathological conditions, so it may further improve our understanding of the metabolic changes underlying a wide variety of pathological processes.

Determinants of the urinary and serum metabolome in children from six European populations.

BACKGROUND: Environment and diet in early life can affect development and health throughout the life course. Metabolic phenotyping of urine and serum represents a complementary systems-wide approach to elucidate environment-health interactions. However, large-scale metabolome studies in children combining analyses of these biological fluids are lacking. Here, we sought to characterise the major determinants of the child metabolome and to define metabolite associations with age, sex, BMI and dietary habits in European children, by exploiting a unique biobank established as part of the Human Early-Life Exposome project ( http://www.projecthelix.eu ). METHODS: Metabolic phenotypes of matched urine and serum samples from 1192 children (aged 6-11) recruited from birth cohorts in six European countries were measured using high-throughput 1H nuclear magnetic resonance (NMR) spectroscopy and a targeted LC-MS/MS metabolomic assay (Biocrates AbsoluteIDQ p180 kit). RESULTS: We identified both urinary and serum creatinine to be positively associated with age. Metabolic associations to BMI z-score included a novel association with urinary 4-deoxyerythreonic acid in addition to valine, serum carnitine, short-chain acylcarnitines (C3, C5), glutamate, BCAAs, lysophosphatidylcholines (lysoPC a C14:0, lysoPC a C16:1, lysoPC a C18:1, lysoPC a C18:2) and sphingolipids (SM C16:0, SM C16:1, SM C18:1). Dietary-metabolite associations included urinary creatine and serum phosphatidylcholines (4) with meat intake, serum phosphatidylcholines (12) with fish, urinary hippurate with vegetables, and urinary proline betaine and hippurate with fruit intake. Population-specific variance (age, sex, BMI, ethnicity, dietary and country of origin) was better captured in the serum than in the urine profile; these factors explained a median of 9.0% variance amongst serum metabolites versus a median of 5.1% amongst urinary metabolites. Metabolic pathway correlations were identified, and concentrations of corresponding metabolites were significantly correlated (r > 0.18) between urine and serum. CONCLUSIONS: We have established a pan-European reference metabolome for urine and serum of healthy children and gathered critical resources not previously available for future investigations into the influence of the metabolome on child health. The six European cohort populations studied share common metabolic associations with age, sex, BMI z-score and main dietary habits. Furthermore, we have identified a novel metabolic association between threonine catabolism and BMI of children.

Development of a novel UHPLC-MS/MS-based platform to quantify amines, amino acids and methylarginines for applications in human disease phenotyping.

Amine quantification is an important strategy in patient stratification and personalised medicine. This is because amines, including amino acids and methylarginines impact on many homeostatic processes. One important pathway regulated by amine levels is nitric oxide synthase (NOS). NOS is regulated by levels of (i) the substrate, arginine, (ii) amino acids which cycle with arginine and (iii) methylarginine inhibitors of NOS. However, biomarker research in this area is hindered by the lack of a unified analytical platform. Thus, the development of a common metabolomics platform, where a wide range of amino acids and methylarginines can be measured constitutes an important unmet need. Here we report a novel high-throughput ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) platform where ≈40 amine analytes, including arginine and methylarginines can be detected and quantified on a molar basis, in a single sample of human plasma. To validate the platform and to generate biomarkers, human plasma from a well-defined cohort of patients before and after coronary artery bypass surgery, who developed systemic inflammatory response syndrome (SIRS), were analysed. Bypass surgery with SIRS significantly altered 26 amine analytes, including arginine and ADMA. Consequently, pathway analysis revealed significant changes in a range of pathways including those associated with NOS.

Metabolic perturbations associated with the consumption of a ketogenic medium-chain TAG diet in dogs with idiopathic epilepsy.

Consumption of diets containing medium-chain TAG (MCT) has been shown to confer neuroprotective effects. We aim to identify the global metabolic perturbations associated with consumption of a ketogenic diet (medium-chain TAG diet (MCTD)) in dogs with idiopathic epilepsy. We used ultra-performance liquid chromatography-MS (UPLC-MS) to generate metabolic and lipidomic profiles of fasted canine serum and made comparisons between the MCTD and standardised placebo diet phases. We identified metabolites that differed significantly between diet phases using metabolite fragmentation profiles generated by tandem MS (UPLC-MS/MS). Consumption of the MCTD resulted in significant differences in serum metabolic profiles when compared with the placebo diet, where sixteen altered lipid metabolites were identified. Consumption of the MCTD resulted in reduced abundances of palmitoylcarnitine, octadecenoylcarnitine, stearoylcarnitine and significant changes, both reduced and increased abundances, of phosphatidylcholine (PC) metabolites. There was a significant increase in abundance of the saturated C17 : 0 fatty acyl moieties during the MCTD phase. Lysophosphatidylcholine (17 : 0) (P=0·01) and PC (17:0/20:4) (P=0·03) were both significantly higher in abundance during the MCTD. The data presented in this study highlight global changes in lipid metabolism, and, of particular interest, in the C17 : 0 moieties, as a result of MCT consumption. Elucidating the global metabolic response of MCT consumption will not only improve the administration of current ketogenic diets for neurological disease models but also provides new avenues for research to develop better diet therapies with improved neuroprotective efficacies. Future studies should clarify the involvement and importance of C17 : 0 moieties in endogenous MCT metabolic pathways.

LC-MS Untargeted Analysis.

LC-MS untargeted analysis is a valuable tool in the field of metabolic profiling (metabonomics/metabolomics), and the applications of this technology have grown rapidly over the past decade. LC-MS offers advantages over other analytical platforms such as speed, sensitivity, relative ease of sample preparation, and large dynamic range. As with any analytical approach, there are still drawbacks and challenges to overcome, but advances are constantly being made regarding both column chemistries and instrumentation. There are numerous untargeted LC-MS approaches which can be used in this ever-growing research field; these can be optimized depending on sample type and the nature of the study or biological question. Some of the main LC-MS approaches for the untargeted analysis of biological samples will be described in detail in the following protocol.

Assessment of metabolic phenotypic variability in children's urine using 1H NMR spectroscopy.

The application of metabolic phenotyping in clinical and epidemiological studies is limited by a poor understanding of inter-individual, intra-individual and temporal variability in metabolic phenotypes. Using 1H NMR spectroscopy we characterised short-term variability in urinary metabolites measured from 20 children aged 8-9 years old. Daily spot morning, night-time and pooled (50:50 morning and night-time) urine samples across six days (18 samples per child) were analysed, and 44 metabolites quantified. Intraclass correlation coefficients (ICC) and mixed effect models were applied to assess the reproducibility and biological variance of metabolic phenotypes. Excellent analytical reproducibility and precision was demonstrated for the 1H NMR spectroscopic platform (median CV 7.2%). Pooled samples captured the best inter-individual variability with an ICC of 0.40 (median). Trimethylamine, N-acetyl neuraminic acid, 3-hydroxyisobutyrate, 3-hydroxybutyrate/3-aminoisobutyrate, tyrosine, valine and 3-hydroxyisovalerate exhibited the highest stability with over 50% of variance specific to the child. The pooled sample was shown to capture the most inter-individual variance in the metabolic phenotype, which is of importance for molecular epidemiology study design. A substantial proportion of the variation in the urinary metabolome of children is specific to the individual, underlining the potential of such data to inform clinical and exposome studies conducted early in life.

Multivariate metabotyping of plasma predicts survival in patients with decompensated cirrhosis.

BACKGROUND & AIMS: Predicting survival in decompensated cirrhosis (DC) is important in decision making for liver transplantation and resource allocation. We investigated whether high-resolution metabolic profiling can determine a metabolic phenotype associated with 90-day survival. METHODS: Two hundred and forty-eight subjects underwent plasma metabotyping by (1)H nuclear magnetic resonance (NMR) spectroscopy and reversed-phase ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry (UPLC-TOF-MS; DC: 80-derivation set, 101-validation; stable cirrhosis (CLD) 20 and 47 healthy controls (HC)). RESULTS: (1)H NMR metabotyping accurately discriminated between surviving and non-surviving patients with DC. The NMR plasma profiles of non-survivors were attributed to reduced phosphatidylcholines and lipid resonances, with increased lactate, tyrosine, methionine and phenylalanine signal intensities. This was confirmed on external validation (area under the receiver operating curve [AUROC]=0.96 (95% CI 0.90-1.00, sensitivity 98%, specificity 89%). UPLC-TOF-MS confirmed that lysophosphatidylcholines and phosphatidylcholines [LPC/PC] were downregulated in non-survivors (UPLC-TOF-MS profiles AUROC of 0.94 (95% CI 0.89-0.98, sensitivity 100%, specificity 85% [positive ion detection])). LPC concentrations negatively correlated with circulating markers of cell death (M30 and M65) levels in DC. Histological examination of liver tissue from DC patients confirmed increased hepatocyte cell death compared to controls. Cross liver sampling at time of liver transplantation demonstrated that hepatic endothelial beds are a source of increased circulating total cytokeratin-18 in DC. CONCLUSION: Plasma metabotyping accurately predicts mortality in DC. LPC and amino acid dysregulation is associated with increased mortality and severity of disease reflecting hepatocyte cell death.

Optimization of metabolite extraction of human vein tissue for ultra performance liquid chromatography-mass spectrometry and nuclear magnetic resonance-based untargeted metabolic profiling.

Human vein tissue is an important matrix to examine when investigating vascular diseases with respect to understanding underlying disease mechanisms. Here, we report the development of an extraction protocol for multi-platform metabolic profiling of human vein tissue. For the first stage of the optimization, two different ratios of methanol/water and 5 organic solvents--namely dichloromethane, chloroform, isopropanol, hexane and methyl tert-butyl ether (MTBE) solutions with methanol--were tested for polar and organic compound extraction, respectively. The extraction output was assessed using (1)H Nuclear Magnetic Resonance (NMR) spectroscopy and a panel of Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS) methodologies. On the basis of the reproducibility of extraction replicates and metabolic coverage, the optimal aqueous (methanol/water) and organic (MTBE/methanol) solvents identified from the first stage were used in a sequential approach for metabolite extraction, altering the order of solvent-mixture addition. The combination of organic metabolite extraction with MTBE/methanol (3 : 1) followed by extraction of polar compounds with methanol/water (1 : 1) was shown to be the best method for extracting metabolites from human vein tissue in terms of reproducibility and number of signals detected and could be used as a single extraction procedure to serve both NMR and UPLC-MS analyses. Molecular classes such as triacylglycerols, phosphatidylcholines, phosphatidylethanolamines, sphingolipids, purines, and pyrimidines were reproducibly extracted. This study enabled an optimal extraction protocol for robust and more comprehensive metabolome coverage for human vein tissue. Many of the physiological and pathological processes affecting the composition of human vein tissue are common to other tissues and hence the extraction method developed in this study can be generically applied.

Perturbations in fatty acid metabolism and apoptosis are manifested in calcific coronary artery disease: An exploratory lipidomic study.

BACKGROUND: Controversy exists concerning the beneficial or harmful effects of the presence of ectopic calcification in the coronary arteries. Additionally, further elucidation of the exact pathophysiological mechanism is needed. In this study, we sought to identify metabolic markers of vascular calcification that could assist in understanding the disease, monitoring its progress and generating hypotheses describing its pathophysiology. METHODS: Untargeted lipid profiling and complementary modeling strategies were employed to compare serum samples from patients with different levels of calcific coronary artery disease (CCAD) based on their calcium score (CS). Subsequently, patients were divided into three groups: no calcification (NC; CS=0; n=26), mild calcification (MC; CS:1-250; n=27) and severe (SC; CS>250; n=17). RESULTS: Phosphatidylcholine levels were found to be significantly altered in the disease states (p=0.001-0.04). Specifically, 18-carbon fatty acyl chain (FAC) phosphatidylcholines were detected in lower levels in the SC group, while 20:4 FAC lipid species were detected in higher concentrations. A statistical trend was observed with phosphatidylcholine lipids in the MC group, showing the same tendency as with the SC group. We also observed several sphingomyelin signals present at lower intensities in SC when compared with NC or MC groups (p=0.000001-0.01). CONCLUSIONS: This is the first lipid profiling study reported in CCAD. Our data demonstrate dysregulations of phosphatidylcholine lipid species, which suggest perturbations in fatty acid elongation/desaturation. The altered levels of the 18-carbon and 20:4 FAC lipids may be indicative of disturbed inflammation homeostasis. The marked sphingomyelin dysregulation in SC is consistent with profound apoptosis as a potential mechanism of CCAD.

Hippocampal Proteomic and Metabonomic Abnormalities in Neurotransmission, Oxidative Stress, and Apoptotic Pathways in a Chronic Phencyclidine Rat Model.

Schizophrenia is a neuropsychiatric disorder affecting 1% of the world's population. Due to both a broad range of symptoms and disease heterogeneity, current therapeutic approaches to treat schizophrenia fail to address all symptomatic manifestations of the disease. Therefore, disease models that reproduce core pathological features of schizophrenia are needed for the elucidation of pathological disease mechanisms. Here, we employ a comprehensive global label-free liquid chromatography-mass spectrometry proteomic (LC-MS(E)) and metabonomic (LC-MS) profiling analysis combined with the targeted proteomics (selected reaction monitoring and multiplex immunoassay) of serum and brain tissues to investigate a chronic phencyclidine (PCP) rat model in which glutamatergic hypofunction is induced through noncompetitive NMDAR-receptor antagonism. Using a multiplex immunoassay, we identified alterations in the levels of several cytokines (IL-5, IL-2, and IL-1ß) and fibroblast growth factor-2. Extensive proteomic and metabonomic brain tissue profiling revealed a more prominent effect of chronic PCP treatment on both the hippocampal proteome and metabonome compared to the effect on the frontal cortex. Bioinformatic pathway analysis confirmed prominent abnormalities in NMDA-receptor-associated pathways in both brain regions, as well as alterations in other neurotransmitter systems such as kainate, AMPA, and GABAergic signaling in the hippocampus and in proteins associated with neurodegeneration. We further identified abundance changes in the level of the superoxide dismutase enzyme (SODC) in both the frontal cortex and hippocampus, which indicates alterations in oxidative stress and substantiates the apoptotic pathway alterations. The present study could lead to an increased understanding of how perturbed glutamate receptor signaling affects other relevant biological pathways in schizophrenia and, therefore, support drug discovery efforts for the improved treatment of patients suffering from this debilitating psychiatric disorder.

Untargeted UPLC-MS profiling pipeline to expand tissue metabolome coverage: application to cardiovascular disease.

Metabolic profiling studies aim to achieve broad metabolome coverage in specific biological samples. However, wide metabolome coverage has proven difficult to achieve, mostly because of the diverse physicochemical properties of small molecules, obligating analysts to seek multiplatform and multimethod approaches. Challenges are even greater when it comes to applications to tissue samples, where tissue lysis and metabolite extraction can induce significant systematic variation in composition. We have developed a pipeline for obtaining the aqueous and organic compounds from diseased arterial tissue using two consecutive extractions, followed by a different untargeted UPLC-MS analysis method for each extract. Methods were rationally chosen and optimized to address the different physicochemical properties of each extract: hydrophilic interaction liquid chromatography (HILIC) for the aqueous extract and reversed-phase chromatography for the organic. This pipeline can be generic for tissue analysis as demonstrated by applications to different tissue types. The experimental setup and fast turnaround time of the two methods contributed toward obtaining highly reproducible features with exceptional chromatographic performance (CV % < 0.5%), making this pipeline suitable for metabolic profiling applications. We structurally assigned 226 metabolites from a range of chemical classes (e.g., carnitines, α-amino acids, purines, pyrimidines, phospholipids, sphingolipids, free fatty acids, and glycerolipids) which were mapped to their corresponding pathways, biological functions and known disease mechanisms. The combination of the two untargeted UPLC-MS methods showed high metabolite complementarity. We demonstrate the application of this pipeline to cardiovascular disease, where we show that the analyzed diseased groups (n = 120) of arterial tissue could be distinguished based on their metabolic profiles.

Metabolic phenotyping of atherosclerotic plaques reveals latent associations between free cholesterol and ceramide metabolism in atherogenesis.

Current optimum medical treatments have had limited success in the primary prevention of cardiovascular events, underscoring the need for new pharmaceutical targets and enhanced understanding of mechanistic metabolic dysregulation. Here, we use a combination of novel metabolic profiling methodologies, based on ultra-performance liquid chromatography coupled to mass spectrometry (UPLC-MS) followed by chemometric modeling, data integration, and pathway mapping, to create a systems-level metabolic atlas of atherogenesis. We apply this workflow to compare arterial tissue incorporating plaque lesions to intimal thickening tissue (immediate preplaque stage). We find changes in several metabolite species consistent with well-established pathways in atherosclerosis, such as the cholesterol, purine, pyrimidine, and ceramide pathways. We then illustrate differential levels of previously unassociated lipids to atherogenesis, namely, phosphatidylethanolamine-ceramides (t-test p-values: 3.8 × 10(-6) to 9.8 × 10(-12)). Most importantly, these molecules appear to be interfacing two pathways recognized for their involvement in atherosclerosis: ceramide and cholesterol. Furthermore, we show that ß-oxidation intermediates (i.e., acylcarnitines) manifest a pattern indicating truncation of the process and overall dysregulation of fatty acid metabolism and mitochondrial dysfunction. We develop a metabolic framework that offers the ability to map significant statistical associations between detected biomarkers. These dysregulated molecules and consequent pathway modulations may provide novel targets for pharmacotherapeutic intervention.

Plasma Lipid Profiling in a Rat Model of Hepatocellular Carcinoma: Potential Modulation Through Quinolone Administration.

BACKGROUND/AIMS: The primary aim of this study was to characterise the blood metabolic profile of hepatocellular carcinoma (HCC) in a rat model, and the secondary aim was to evaluate the effect of the quinolone, norfloxacin on metabolic profiles and exploring the role that gut sterilisation may have on HCC development. METHODS: HCC was induced in 10 Fischer rats by administration of intra-peritoneal diethylnitrosamine (DEN) and oral N-nitrosomorpholine. Plasma was collected upon sacrifice. Five of these rats were concomitantly administered oral norfloxacin. Six Fischer non-treated rats acted as healthy controls. Proton nuclear magnetic resonance (NMR) spectra were acquired using a 600 MHz NMR system. RESULTS: Control animals were 120 g heavier than diseased counterparts. Proton NMR spectra from diseased rats displayed significant decreases in lipoproteins, unsaturated fatty acids, acetyl-glycoprotein, acetoacetate, and glucose (P ≤ 0.001). Plasma citrate and formate levels were increased (P = 0.02). Norfloxacin appeared to abrogate this effect slightly. CONCLUSION: The spectral profiles of plasma in rats with HCC display marked changes with relation to lipid metabolism and cellular turnover. Norfloxacin appears to moderate these metabolic alterations to a small degree.

Plasma metabolomic profiles of breast cancer patients after short-term limonene intervention.

Limonene is a lipophilic monoterpene found in high levels in citrus peel. Limonene demonstrates anticancer properties in preclinical models with effects on multiple cellular targets at varying potency. While of interest as a cancer chemopreventive, the biologic activity of limonene in humans is poorly understood. We conducted metabolite profiling in 39 paired (pre/postintervention) plasma samples from early-stage breast cancer patients receiving limonene treatment (2 g QD) before surgical resection of their tumor. Metabolite profiling was conducted using ultra-performance liquid chromatography coupled to a linear trap quadrupole system and gas chromatography-mass spectrometry. Metabolites were identified by comparison of ion features in samples to a standard reference library. Pathway-based interpretation was conducted using the human metabolome database and the MetaCyc database. Of the 397 named metabolites identified, 72 changed significantly with limonene intervention. Class-based changes included significant decreases in adrenal steroids (P < 0.01), and significant increases in bile acids (P ≤ 0.05) and multiple collagen breakdown products (P < 0.001). The pattern of changes also suggested alterations in glucose metabolism. There were 47 metabolites whose change with intervention was significantly correlated to a decrease in cyclin D1, a cell-cycle regulatory protein, in patient tumor tissues (P ≤ 0.05). Here, oral administration of limonene resulted in significant changes in several metabolic pathways. Furthermore, pathway-based changes were related to the change in tissue level cyclin D1 expression. Future controlled clinical trials with limonene are necessary to determine the potential role and mechanisms of limonene in the breast cancer prevention setting.