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.

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).

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.

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.

Sexual transfer of the steroid hormone 20E induces the postmating switch in Anopheles gambiae.

Female insects generally mate multiple times during their lives. A notable exception is the female malaria mosquito Anopheles gambiae, which after sex loses her susceptibility to further copulation. Sex in this species also renders females competent to lay eggs developed after blood feeding. Despite intense research efforts, the identity of the molecular triggers that cause the postmating switch in females, inducing a permanent refractoriness to further mating and triggering egg-laying, remains elusive. Here we show that the male-transferred steroid hormone 20-hydroxyecdysone (20E) is a key regulator of monandry and oviposition in An. gambiae. When sexual transfer of 20E is impaired by partial inactivation of the hormone and inhibition of its biosynthesis in males, oviposition and refractoriness to further mating in the female are strongly reduced. Conversely, mimicking sexual delivery by injecting 20E into virgin females switches them to an artificial mated status, triggering egg-laying and reducing susceptibility to copulation. Sexual transfer of 20E appears to incapacitate females physically from receiving seminal fluids by a second male. Comparative analysis of microarray data from females after mating and after 20E treatment indicates that 20E-regulated molecular pathways likely are implicated in the postmating switch, including cytoskeleton and musculature-associated genes that may render the atrium impenetrable to additional mates. By revealing signals and pathways shaping key processes in the An. gambiae reproductive biology, our data offer new opportunities for the control of natural populations of malaria vectors.

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.

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.

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.

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.

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.

Systemic gut microbial modulation of bile acid metabolism in host tissue compartments.

We elucidate the detailed effects of gut microbial depletion on the bile acid sub-metabolome of multiple body compartments (liver, kidney, heart, and blood plasma) in rats. We use a targeted ultra-performance liquid chromatography with time of flight mass-spectrometry assay to characterize the differential primary and secondary bile acid profiles in each tissue and show a major increase in the proportion of taurine-conjugated bile acids in germ-free (GF) and antibiotic (streptomycin/penicillin)-treated rats. Although conjugated bile acids dominate the hepatic profile (97.0 ± 1.5%) of conventional animals, unconjugated bile acids comprise the largest proportion of the total measured bile acid profile in kidney (60.0 ± 10.4%) and heart (53.0 ± 18.5%) tissues. In contrast, in the GF animal, taurine-conjugated bile acids (especially taurocholic acid and tauro-ß-muricholic acid) dominated the bile acid profiles (liver: 96.0 ± 14.5%; kidney: 96 ± 1%; heart: 93 ± 1%; plasma: 93.0 ± 2.3%), with unconjugated and glycine-conjugated species representing a small proportion of the profile. Higher free taurine levels were found in GF livers compared with the conventional liver (5.1-fold; P < 0.001). Bile acid diversity was also lower in GF and antibiotic-treated tissues compared with conventional animals. Because bile acids perform important signaling functions, it is clear that these chemical communication networks are strongly influenced by microbial activities or modulation, as evidenced by farnesoid X receptor-regulated pathway transcripts. The presence of specific microbial bile acid co-metabolite patterns in peripheral tissues (including heart and kidney) implies a broader signaling role for these compounds and emphasizes the extent of symbiotic microbial influences in mammalian homeostasis.

Optimizing the use of quality control samples for signal drift correction in large-scale urine metabolic profiling studies.

The evident importance of metabolic profiling for biomarker discovery and hypothesis generation has led to interest in incorporating this technique into large-scale studies, e.g., clinical and molecular phenotyping studies. Nevertheless, these lengthy studies mandate the use of analytical methods with proven reproducibility. An integrated experimental plan for LC-MS profiling of urine, involving sample sequence design and postacquisition correction routines, has been developed. This plan is based on the optimization of the frequency of analyzing identical quality control (QC) specimen injections and using the QC intensities of each metabolite feature to construct a correction trace for all the samples. The QC-based methods were tested against other current correction practices, such as total intensity normalization. The evaluation was based on the reproducibility obtained from technical replicates of 46 samples and showed the feature-based signal correction (FBSC) methods to be superior to other methods, resulting in ~1000 and 600 metabolite features with coefficient of variation (CV) < 15% within and between two blocks, respectively. Additionally, the required frequency of QC sample injection was investigated and the best signal correction results were achieved with at least one QC injection every 2 h of urine sample injections (n = 10). Higher rates of QC injections (1 QC/h) resulted in slightly better correction but at the expense of longer total analysis time.

Systematic evaluation of extraction methods for multiplatform-based metabotyping: application to the Fasciola hepatica metabolome.

Combining data from multiple analytical platforms is essential for comprehensive study of the molecular phenotype (metabotype) of a given biological sample. The metabolite profiles generated are intrinsically dependent on the analytical platforms, each requiring optimization of instrumental parameters, separation conditions, and sample extraction to deliver maximal biological information. An in-depth evaluation of extraction protocols for characterizing the metabolome of the hepatobiliary fluke Fasciola hepatica , using ultra performance liquid chromatography and capillary electrophoresis coupled with mass spectroscopy is presented. The spectrometric methods were characterized by performance, and metrics of merit were established, including precision, mass accuracy, selectivity, sensitivity, and platform stability. Although a core group of molecules was common to all methods, each platform contributed a unique set, whereby 142 metabolites out of 14,724 features were identified. A mixture design revealed that the chloroform:methanol:water proportion of 15:59:26 was globally the best composition for metabolite extraction across UPLC-MS and CE-MS platforms accommodating different columns and ionization modes. Despite the general assumption of the necessity of platform-adapted protocols for achieving effective metabotype characterization, we show that an appropriately designed single extraction procedure is able to fit the requirements of all technologies. This may constitute a paradigm shift in developing efficient protocols for high-throughput metabolite profiling with more-general analytical applicability.

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.

Technical and biological variation in UPLC-MS-based untargeted metabolic profiling of liver extracts: application in an experimental toxicity study on galactosamine.

The relative importance of technical versus bio-logical variation in UPLC-MS liver metabolic profiling studies was assessed on liver samples collected as part of an in vivo hepatotoxicity study. Biological variability within and between two treatment groups (three rats treated with galactosamine and three with galactosamine+uridine) was compared with sampling/extraction variability (three portions extracted from each rat liver section) and UPLC-MS platform variability (triplicate injections of each extract) for aqueous and organic extracts. The impact of scaling on error measurement was investigated on replicate injections of a quality control sample, and consequently started log-transformation was used to stabilize the variance across the ion intensity range. For aqueous extracts, technical variability was two to four times lower than within group interanimal variability. Similar results were obtained for organic extracts for the galactosamine group, sampling/extraction variability being more elevated in the galactosamine+uridine group. For both extract types, differences between treatment groups were the principal source of observed variation, and triplicate injections clustered closely in PCA plots and in HCA dendrograms, indicating small instrument variability compared to observed biological variation. This protocol can be applied to investigate differences in liver metabolic profiles between animal groups in toxicology studies and clinical investigations of liver disease.

Cross-platform comparison of Caenorhabditis elegans tissue extraction strategies for comprehensive metabolome coverage.

The nematode Caenorhabditis elegans is widely used as a model organism in many areas of the life sciences. Metabolite profiling (metabolomics/metabonomics) is a powerful means of assigning phenotypes to experimentally perturbed C. elegans samples (e.g., mutants, RNAi, or chemical treatments). Tissue extraction is a key step, and high-quality and reproducible extractions are essential to the success of metabolomics studies. We have performed an extensive comparison of different tissue extraction techniques with C. elegans, comparing two different solvent systems (chloroform/methanol and aqueous methanol) and six different tissue disruption techniques (including manual grinding in a cooled mortar, homogenization, and various grinding media in both reciprocating and orbital tissue mills). All twelve combinations were then compared by GC/MS, (1)H NMR spectroscopy, and UPLC-MS, and the results were evaluated by both overall multivariate clustering approaches as well as distributions over individual metabolites/metabolite features of coefficient of variation and yield. The choice of solvent had more influence than the disruption method used, although the homogenizer results were clearly outliers. Overall, we concluded that bead-beating with 80% methanol solution was a good trade-off, although it is important to note that the definition of the apparent "best" method depended on which analytical platform was used to evaluate the results.

HILIC-UPLC-MS for exploratory urinary metabolic profiling in toxicological studies.

Hydrophilic interaction ultra performance liquid chromatography (HILIC-UPLC) permits the analysis of highly polar metabolites, providing complementary information to reversed-phase (RP) chromatography. HILIC-UPLC-TOF-MS was investigated for the global metabolic profiling of rat urine samples generated in an experimental hepatotoxicity study of galactosamine (galN) and the concomitant investigation of the protective effect of glycine. Within-run repeatability and stability over a large sample batch (>200 samples, 60 h run-time) was assessed through the repeat analysis of a quality control sample. Following system equilibration, excellent repeatability was observed in terms of retention time (CV < 1.7%), signal intensity (CV < 14%), and mass variability (<0.005 amu), providing a good measure of reproducibility. Classification of urinary metabolic profiles according to treatment was observed, with significant changes in specific metabolites after galN exposure, including increased urocanic acid, N-acetylglucosamine, and decreased 2-oxoglutarate. A novel finding from this HILIC-UPLC-MS approach was elevated urinary tyramine in galN-treated rats, reflecting disturbed amino acid metabolism. These results show HILIC-UPLC-MS to be a promising method for global metabolic profiling, demonstrating high within-run repeatability, even over an extended run time. Retention of polar endogenous analytes and xenobiotic metabolites was improved compared with RP studies, including galN, N-acetylglucosamine, oxoglutarate, and urocanic acid, enhancing metabolome coverage and potentially improving biomarker discovery.

Correction of mass calibration gaps in liquid chromatography-mass spectrometry metabolomics data.

MOTIVATION: High mass accuracy is an important goal in liquid chromatography-mass spectrometry experiments. Some manufacturers employ a mass calibration system that regularly switches between the analyte and a standard reference compound, and leads to gaps in the analyte data. We present a method for correction of such gaps in global molecular profiling applications such as metabolomics. We demonstrate that it improves peak detection and quantification, successfully recovering the expected number of peaks and intensity distribution in an example metabolomics dataset. AVAILABILITY AND IMPLEMENTATION: Available in XCMS versions 1.23.3 and higher. Distributed via Bioconductor under GNU General Public License. (http://www.bioconductor.org/packages//2.7/bioc/html/xcms.html).

Construction of confidence regions for isotopic abundance patterns in LC/MS data sets for rigorous determination of molecular formulas.

It has long been recognized that estimates of isotopic abundance patterns may be instrumental in identifying the many unknown compounds encountered when conducting untargeted metabolic profiling using liquid chromatography/mass spectrometry. While numerous methods have been developed for assigning heuristic scores to rank the degree of fit of the observed abundance patterns with theoretical ones, little work has been done to quantify the errors that are associated with the measurements made. Thus, it is generally not possible to determine, in a statistically meaningful manner, whether a given chemical formula would likely be capable of producing the observed data. In this paper, we present a method for constructing confidence regions for the isotopic abundance patterns based on the fundamental distribution of the ion arrivals. Moreover, we develop a method for doing so that makes use of the information pooled together from the measurements obtained across an entire chromatographic peak, as well as from any adducts, dimers, and fragments observed in the mass spectra. This greatly increases the statistical power, thus enabling the analyst to rule out a potentially much larger number of candidate formulas while explicitly guarding against false positives. In practice, small departures from the model assumptions are possible due to detector saturation and interferences between adjacent isotopologues. While these factors form impediments to statistical rigor, they can to a large extent be overcome by restricting the analysis to moderate ion counts and by applying robust statistical methods. Using real metabolic data, we demonstrate that the method is capable of reducing the number of candidate formulas by a substantial amount, even when no bromine or chlorine atoms are present. We argue that further developments in our ability to characterize the data mathematically could enable much more powerful statistical analyses.