Differential 12C-/13C-Isotope Dansylation Labeling and Fast Liquid Chromatography/Mass Spectrometry for Absolute and Relative Quantification of the Metabolome

Deuterium- and Tritium-Labelled Compounds: Applications in the Life Sciences

Hydrogen isotopes are unique tools for identifying and understanding biological and chemical processes. Hydrogen isotope labelling allows for the traceless and direct incorporation of an additional mass or radioactive tag into an organic molecule with almost no changes in its chemical structure, physical properties, or biological activity. Using deuterium-labelled isotopologues to study the unique mass-spectrometric patterns generated from mixtures of biologically relevant molecules drastically simplifies analysis. Such methods are now providing unprecedented levels of insight in a wide and continuously growing range of applications in the life sciences and beyond. Tritium (³ H), in particular, has seen an increase in utilization, especially in pharmaceutical drug discovery. The efforts and costs associated with the synthesis of labelled compounds are more than compensated for by the enhanced molecular sensitivity during analysis and the high reliability of the data obtained. In this Review, advances in the application of hydrogen isotopes in the life sciences are described.

Metabolomics: A High-Throughput Platform for Metabolite Profile Exploration

Metabolomics aims to quantitatively measure small-molecule metabolites in biological samples, such as bodily fluids (e.g., urine, blood, and saliva), tissues, and breathe exhalation, which reflects metabolic responses of a living system to pathophysiological stimuli or genetic modification. In the past decade, metabolomics has made notable progresses in providing useful systematic insights into the underlying mechanisms and offering potential biomarkers of many diseases. Metabolomics is a complementary manner of genomics and transcriptomics, and bridges the gap between genotype and phenotype, which reflects the functional output of a biological system interplaying with environmental factors. Recently, the technology of metabolomics study has been developed quickly. This review will discuss the whole pipeline of metabolomics study, including experimental design, sample collection and preparation, sample detection and data analysis, as well as mechanism interpretation, which can help understand metabolic effects and metabolite function for living organism in system level.

Chemical Isotope Labeling LC-MS for Human Blood Metabolome Analysis

Blood is a widely used biofluid in discovery metabolomic research to search for clinical metabolite biomarkers of diseases. Analyzing the entire human blood metabolome is a major analytical challenge, as blood, after being processed into serum or plasma, contains thousands of metabolites with diverse chemical and physical properties as well as a wide range of concentrations. We describe an enabling method based on high-performance chemical isotope labeling (CIL) liquid chromatography-mass spectrometry (LC-MS) for in-depth quantification of the metabolomic differences in comparative blood samples with high accuracy and precision.

Metabolomic analysis of oxidative stress: Superoxide dismutase mutation and paraquat induced stress in Drosophila melanogaster

Oxidative stress results in substantial biochemical and physiological perturbations in essentially all organisms. To determine the broad metabolic effects of oxidative stress, we have quantified the response in Drosophila melanogaster to both genetically and environmentally derived oxidative stress. Flies were challenged with loss of Superoxide dismutase activity or chronic or acute exposure to the oxidizing chemical paraquat. Metabolic changes were then quantified using a recently developed chemical isotope labeling (CIL) liquid chromatography - mass spectrometry (LC-MS) platform that targets the carboxylic acid and amine/phenol submetabolomes with high metabolic coverage. We discovered wide spread changes in both submetabolomes in response to all three types of stresses including: changes to the urea cycle, tryptophan metabolism, porphyrin metabolism, as well as a series of metabolic pathways involved in glutathione synthesis. Strikingly, while there are commonalities across the conditions, all three resulted in different metabolomic responses, with the greatest difference between the genetic and environmental responses. Genetic oxidative stress resulted in substantially more widespread effects, both in terms of the percent of the metabolome altered, and the magnitude of changes in individual metabolites. Chronic and acute environmental stress resulted in more similar responses although both were distinct from genetic stress. Overall, these results indicate that the metabolomic response to oxidative stress is complex, reaching across multiple metabolic pathways, with some shared features but with more features unique to different, specific stressors.

Metabolic reprogramming of hydrogenosomal amino acids in Trichomonas vaginalis under glucose restriction

BACKGROUND

Glucose is the major energy source that is converted to pyruvate for ATP generation in the trichomonad hydrogenosome. Under glucose restriction (GR), the regulation of amino acids metabolism is crucial for trichomonad growth and survival. RNA-sequencing (RNA-seq) analysis has been used to identify differentially expressed genes in Trichomonas vaginalis under GR, leading to significant advances in understanding adaptive responses of amino acid metabolism to GR. However, the levels of amino acid metabolites modulated by GR are unknown in T. vaginalis.

METHODS

Herein, we describe a comprehensive metabolomic analysis of amino acid metabolites in the hydrogenosome using liquid chromatography Fourier transform ion cyclotron resonance mass spectrometry (LC-FT MS). The relative abundance of 17 hydrogenosomal amino acids was analyzed under GR and high-glucose (HG) conditions.

RESULTS

Levels of most amino acids were higher in GR culture. Arginine was not detectable in either HG or GR cultures; however, its metabolic end-product proline was slightly increased under GR, suggesting that the arginine dihydrolase pathway was more activated by GR. Additionally, methionine catabolism was less stimulated under GR because of greater methionine accumulation. Furthermore, branched chain amino acids (BCAA), including leucine, isoleucine and valine, as well as phenylalanine and alanine, markedly accumulated under GR, indicating that glutamate-related metabolic pathways were remarkably enhanced in this setting. Our metabolomic analysis combined with previous RNA-seq data confirm the existence of several amino acid metabolic pathways in the hydrogenosome and highlight their potentially important roles in T. vaginalis under glucose deprivation.

Profiling novel metabolic biomarkers for Parkinson's disease using in-depth metabolomic analysis

OBJECTIVE

To profile the amine/phenol submetabolome to determine potential metabolite biomarkers associated with Parkinson's disease (PD) and PD with incipient dementia.

METHODS

At baseline of a 3-wave (18-month intervals) longitudinal study, serum samples were collected from 42 healthy controls and 43 PD patients. By wave 3 (year 3), 16 PD patients were diagnosed with dementia and were classified as PD with incipient dementia at baseline. Metabolomic profiling using dansylation isotope labeling liquid chromatography mass spectrometry was conducted to compare controls with the full PD, PD with no dementia, and PD with incipient dementia groups.

RESULTS

Metabolomic analyses detected 719 common metabolites in 80% of the samples. Some were significantly altered in pairwise comparison of different groups (fold change of >1.2 or <0.83 with q < 0.05). We discriminated PD and controls by using a 5-metabolite panel, vanillic acid, 3-hydroxykynurenine, isoleucyl-alanine, 5-acetylamino-6-amino-3-methyluracil, and theophylline. The receiver operating characteristic curve produced an area-under-the-curve value of 0.955 with 87.5% sensitivity and 93.0% specificity. In comparing PD with no dementia with PD with incipient dementia, we used an 8-metabolite panel, His-Asn-Asp-Ser, 3,4-dihydroxyphenylacetone, desaminotyrosine, hydroxy-isoleucine, alanyl-alanine, putrescine [-2H], purine [+O] and its riboside. This produced an area-under-the-curve value of 0.862 with 80.0% sensitivity and 77.0% specificity.

CONCLUSIONS

The significantly altered metabolites can be used to differentiate (1) PD patients from healthy controls with high accuracy and (2) the stable PD with no dementia group from those with incipient dementia. Following further validation in larger cohorts, these metabolites could be used for both discrimination and establishing prognosis in PD. © 2017 International Parkinson and Movement Disorder Society.

Reductive amination derivatization for the quantification of garlic components by isotope dilution analysis

In this work, we synthesized internal standards for four garlic organosulfur compounds (OSCs) by reductive amination with ¹³C, D₂-formaldehyde, and developed an isotope dilution analysis method to quantitate these organosulfur components in garlic samples. Internal standards were synthesized for internal absolute quantification of S-allylcysteine (SAC), S-allylcysteine sulfoxide (alliin), S-methylcysteine (SMC), and S-ethylcysteine (SEC). We used a multiple reaction monitoring (MRM) to detect ¹³C, D₂-formaldehyde-modified OSCs by ultrahigh-performance liquid phase chromatography coupled with tandem mass spectrometry (UHPLC-MS/MS) and obtained MS spectra showing different ratios of ¹³C, D₂-formaldehyde-modified and H₂-formaldehyde-modified compounds. The resulting labeled and unlabeled OSCs were exhibited correlation coefficient (R²) ranged from 0.9989 to 0.9994, respectively. The average recoveries for four OSCs at three concentration levels ranged from 89% to 105%. By ¹³C, D₂-formaldehyde and sodium cyanoborohydride, the reductive amination-based method can be utilized to generate novel internal standard for isotope dilution and to extend the quantitative application.

Overcoming Sample Matrix Effect in Quantitative Blood Metabolomics Using Chemical Isotope Labeling Liquid Chromatography Mass Spectrometry

Blood is widely used for discovery metabolomics to search for disease biomarkers. However, blood sample matrix can have a profound effect on metabolome analysis, which can impose an undesirable restriction on the type of blood collection tubes that can be used for blood metabolomics. We investigated the effect of blood sample matrix on metabolome analysis using a high-coverage and quantitative metabolome profiling technique based on differential chemical isotope labeling (CIL) LC-MS. We used ¹²C-/¹³C-dansylation LC-MS to perform relative quantification of the amine/phenol submetabolomes of four types of samples (i.e., serum, EDTA plasma, heparin plasma, and citrate plasma) collected from healthy individuals and compare their metabolomic results. From the analysis of 80 plasma and serum samples in experimental triplicate, we detected a total of 3651 metabolites with an average of 1818 metabolites per run (n = 240). The number of metabolites detected and the precision and accuracy of relative quantification were found to be independent of the sample type. Within each sample type, the metabolome data set could reveal biological variation (e.g., sex separation). Although the relative concentrations of some individual metabolites might be different in the four types of samples, for sex separation, all 66 significant metabolites with larger fold-changes (FC ≥ 2 and p < 0.05) found in at least one sample type could be found in the other types of samples with similar or somewhat reduced, but still significant, fold-changes. Our results indicate that CIL LC-MS could overcome the sample matrix effect, thereby greatly broadening the scope of blood metabolomics; any blood samples properly collected in routine clinical settings, including those in biobanks originally used for other purposes, can potentially be used for discovery metabolomics.

Development of a validated LC- MS/MS method for the quantification of 19 endogenous asthma/COPD potential urinary biomarkers

Obstructive airways inflammatory diseases sometimes show overlapping symptoms that hinder their early and correct diagnosis. Current clinical tests are tedious and are of inadequate specificity in special population such as the elderly and children. Therefore, we are developing tandem mass spectrometric (MS/MS) methods for targeted analysis of urine biomarkers. Recently, proton-nuclear magnetic resonance (¹H-NMR) analysis proposed 50 urinary metabolites as potential diagnostic biomarkers among asthma and chronic obstructive pulmonary disease (COPD) patients. Metabolites are divided into 3 groups based on chemical nature. For group 1 (amines and phenols, 19 urinary metabolites), we developed and validated a high performance liquid chromatographic (HPLC)-MS/MS method using differential isotope labeling (DIL) with dansyl chloride. Method development included the optimization of the derivatization reaction, the MS/MS conditions, and the chromatographic separation. Linearity varied from 2 to 4800 ng/mL and the use of ¹³C₂-labeled derivatives allowed for the correction of matrix effects as well as the unambiguous confirmation of the identity of each metabolite in the presence of interfering isomers in urine. Despite the challenges associated with method validation, the method was fully validated as per the food and drug administration (FDA) and the European medicines agency (EMA) recommendations. Validation criteria included linearity, precision, accuracy, dilution integrity, selectivity, carryover, and stability. Challenges in selectivity experiments included the isotopic contributions of the analyte towards its internal standard (IS), that was addressed via the optimization of the IS concentration. In addition, incurred sample analysis was performed to ensure that results from patient samples are accurate and reliable. The method was robust and reproducible and is currently being applied in a cohort of asthma and COPD patient urine samples for biomarker discovery purposes.

Nonocclusive Sweat Collection Combined with Chemical Isotope Labeling LC-MS for Human Sweat Metabolomics and Mapping the Sweat Metabolomes at Different Skin Locations

Human sweat is an excellent biofluid candidate for metabolomics due to its noninvasive sample collection and relatively simple matrix. We report a simple and inexpensive method for sweat collection over a defined period (e.g., 24 h) based on the use of a nonocclusive style sweat patch adhered to a skin. This method was combined with differential chemical isotope labeling (CIL) LC-MS for mapping the metabolome profiles of sweat samples collected from skins of the left forearm, lower back, and neck of 20 healthy volunteers. Three 24-h sweat samples were collected at three different days from each subject for examining day-to-day metabolome variations. A total of 342 LC-MS runs were carried out (two runs were discarded due to instrumental issue), resulting in the detection and relative quantification of 3140 sweat metabolites with 84 metabolites identified and 2716 metabolites mass-matched to metabolome databases. Multivariate and univariate analyses of the metabolome data revealed a location-dependence characteristic of the sweat metabolome, offering a possibility of mapping the sweat metabolic differences according to skin locations. Significant differences in male and female sweat metabolomes could be detected, demonstrating the possibility of using the sweat metabolome to reveal biological variations among different comparative groups. Thus, the combination of noninvasive sweat collection and CIL LC-MS is a robust analytical tool for sweat metabolomics with potential applications including daily monitoring of the sweat metabolome as health indicators, discovering sweat-based disease biomarkers, and metabolomic mapping of sweat collected from different areas of skin with and without injuries or diseases.

Metabolite Measurement: Pitfalls to Avoid and Practices to Follow

Metabolites are the small biological molecules involved in energy conversion and biosynthesis. Studying metabolism is inherently challenging due to metabolites' reactivity, structural diversity, and broad concentration range. Herein, we review the common pitfalls encountered in metabolomics and provide concrete guidelines for obtaining accurate metabolite measurements, focusing on water-soluble primary metabolites. We show how seemingly straightforward sample preparation methods can introduce systematic errors (e.g., owing to interconversion among metabolites) and how proper selection of quenching solvent (e.g., acidic acetonitrile:methanol:water) can mitigate such problems. We discuss the specific strengths, pitfalls, and best practices for each common analytical platform: liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS), nuclear magnetic resonance (NMR), and enzyme assays. Together this information provides a pragmatic knowledge base for carrying out biologically informative metabolite measurements.

Gut microbiota, metabolome and immune signatures in patients with uncomplicated diverticular disease

OBJECTIVE

The engagement of the gut microbiota in the development of symptoms and complications of diverticular disease has been frequently hypothesised. Our aim was to explore colonic immunocytes, gut microbiota and the metabolome in patients with diverticular disease in a descriptive, cross-sectional, pilot study.

DESIGN

Following colonoscopy with biopsy and questionnaire phenotyping, patients were classified into diverticulosis or symptomatic uncomplicated diverticular disease; asymptomatic subjects served as controls. Mucosal immunocytes, in the diverticular region and in unaffected sites, were quantified with immunohistochemistry. Mucosa and faecal microbiota were analysed by the phylogenetic platform high taxonomic fingerprint (HTF)-Microbi.Array, while the metabolome was assessed by ¹H nuclear magnetic resonance.

RESULTS

Compared with controls, patients with diverticula, regardless of symptoms, had a >70% increase in colonic macrophages. Their faecal microbiota showed depletion of Clostridium cluster IV. Clostridium cluster IX, Fusobacterium and Lactobacillaceae were reduced in symptomatic versus asymptomatic patients. A negative correlation was found between macrophages and mucosal Clostridium cluster IV and Akkermansia. Urinary and faecal metabolome changes in diverticular disease involved the hippurate and kynurenine pathways. Six urinary molecules allowed to discriminate diverticular disease and control groups with >95% accuracy.

CONCLUSIONS

Patients with colonic diverticular disease show depletion of microbiota members with anti-inflammatory activity associated with mucosal macrophage infiltration. Metabolome profiles were linked to inflammatory pathways and gut neuromotor dysfunction and showed the ability to discriminate diverticular subgroups and controls. These data pave the way for further large-scale studies specifically aimed at identifying microbiota signatures with a potential diagnostic value in patients with diverticular disease.

Development of a Data-Independent Targeted Metabolomics Method for Relative Quantification Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

Quantitative metabolomics approaches can significantly improve the repeatability and reliability of metabolomics investigations but face critical technical challenges, owing to the vast number of unknown endogenous metabolites and the lack of authentic standards. The present study contributes to the development of a novel method known as "data-independent targeted quantitative metabolomics" (DITQM), which was used to investigate the label-free quantitative metabolomics of multiple known and unknown metabolites in biofluid samples. This approach initially involved the acquisition of MS/MS data for all metabolites in biosamples using a sequentially stepped targeted MS/MS (sst-MS/MS) method, in which multiple product ion scans were performed by selecting all ions in the targeted mass ranges as the precursor ions. Subsequently, scheduled multiple reaction monitoring (MRM) by LC-MS/MS of the metabolome was established for 1658 characteristic ion pairs of 1324 metabolites. For sensitive and accurate quantification of these metabolites, mixed calibration curves were generated using sequentially diluted standard reference plasma samples using established MRM methods. Relative concentrations of all metabolites in each sample were calculated without using individual authentic standards. To evaluate the reliability and applicability of this new method, the performance of DITQM was validated by comparison to absolute quantification of 12 acylcarnitines using authentic standards and traditional metabolomics analysis for lung cancer. The results proved that the DITQM protocol is more reliable and can significantly improve clustering effects and repeatability in biomarker discovery. In this study, we established a novel methodology to standardize and quantify large-scale metabolome, providing a new choice for metabolomics research and its clinical applications.

Development of High-Performance Chemical Isotope Labeling LC-MS for Profiling the Carbonyl Submetabolome

Metabolites containing a carbonyl group represent several important classes of molecules including various forms of ketones and aldehydes such as steroids and sugars. We report a high-performance chemical isotope labeling (CIL) LC-MS method for profiling the carbonyl submetabolome with high coverage and high accuracy and precision of relative quantification. This method is based on the use of dansylhydrazine (DnsHz) labeling of carbonyl metabolites to change their chemical and physical properties to such an extent that the labeled metabolites can be efficiently separated by reversed phase LC and ionized by electrospray ionization MS. In the analysis of six standards representing different carbonyl classes, acetaldehyde could be ionized only after labeling and MS signals were significantly increased for other 5 standards with an enhancement factor ranging from ∼15-fold for androsterone to ∼940-fold for 2-butanone. Differential ¹²C- and ¹³C-DnsHz labeling was developed for quantifying metabolic differences in comparative samples where individual samples were separately labeled with ¹²C-labeling and spiked with a ¹³C-labeled pooled sample, followed by LC-MS analysis, peak pair picking, and peak intensity ratio measurement. In the replicate analysis of a 1:1 ¹²C-/¹³C-labeled human urine mixture (n = 6), an average of 2030 ± 39 pairs per run were detected with 1737 pairs in common, indicating the possibility of detecting a large number of carbonyl metabolites as well as high reproducibility of peak pair detection. The average RSD of the peak pair ratios was 7.6%, and 95.6% of the pairs had a RSD value of less than 20%, demonstrating high precision for peak ratio measurement. In addition, the ratios of most peak pairs were close to the expected value of 1.0 (e.g., 95.5% of them had ratios of between 0.67 and 1.5), showing the high accuracy of the method. For metabolite identification, a library of DnsHz-labeled standards was constructed, including 78 carbonyl metabolites with each containing MS, retention time (RT), and MS/MS information. This library and an online search program for labeled carbonyl metabolite identification based on MS, RT, and MS/MS matches have been implemented in a freely available Website, www.mycompoundid.org . Using this library, out of the 1737 peak pairs detected in urine, 33 metabolites were positively identified. In addition, 1333 peak pairs could be matched to the metabolome databases with most of them belonging to the carbonyl metabolites. These results show that ¹²C-/¹³C-DnsHz labeling LC-MS is a useful tool for profiling the carbonyl submetabolome of complex samples with high coverage.

Simultaneous Quantification of Amino Metabolites in Multiple Metabolic Pathways Using Ultra-High Performance Liquid Chromatography with Tandem-mass Spectrometry

Metabolites containing amino groups cover multiple pathways and play important roles in redox homeostasis and biosyntheses of proteins, nucleotides and neurotransmitters. Here, we report a new method for simultaneous quantification of 124 such metabolites. This is achieved by derivatization-assisted sensitivity enhancement with 5-aminoisoquinolyl-N-hydroxysuccinimidyl carbamate (5-AIQC) followed with comprehensive analysis using ultra-high performance liquid chromatography and electrospray ionization tandem mass spectrometry (UHPLC-MS/MS). In an one-pot manner, this quantification method enables simultaneous coverage of 20 important metabolic pathways including protein biosynthesis/degradation, biosyntheses of catecholamines, arginine and glutathione, metabolisms of homocysteine, taurine-hypotaurine etc. Compared with the reported ones, this method is capable of simultaneously quantifying thiols, disulfides and other oxidation-prone analytes in a single run and suitable for quantifying aromatic amino metabolites. This method is also much more sensitive for all tested metabolites with LODs well below 50 fmol (at sub-fmol for most tested analytes) and shows good precision for retention time and quantitation with inter-day and intra-day relative standard deviations (RSDs) below 15% and good recovery from renal cancer tissue, rat urine and plasma. The method was further applied to quantify the amino metabolites in silkworm hemolymph from multiple developmental stages showing its applicability in metabolomics and perhaps some clinical chemistry studies.

Elevated acetyl-CoA by amino acid recycling fuels microalgal neutral lipid accumulation in exponential growth phase for biofuel production

Microalgal neutral lipids [mainly in the form of triacylglycerols (TAGs)], feasible substrates for biofuel, are typically accumulated during the stationary growth phase. To make microalgal biofuels economically competitive with fossil fuels, generating strains that trigger TAG accumulation from the exponential growth phase is a promising biological approach. The regulatory mechanisms to trigger TAG accumulation from the exponential growth phase (TAEP) are important to be uncovered for advancing economic feasibility. Through the inhibition of pyruvate dehydrogenase kinase by sodium dichloroacetate, acetyl-CoA level increased, resulting in TAEP in microalga Dunaliella tertiolecta. We further reported refilling of acetyl-CoA pool through branched-chain amino acid catabolism contributed to an overall sixfold TAEP with marginal compromise (4%) on growth in a TAG-rich D. tertiolecta mutant from targeted screening. Herein, a three-step α loop-integrated metabolic model is introduced to shed lights on the neutral lipid regulatory mechanism. This article provides novel approaches to compress lipid production phase and heightens lipid productivity and photosynthetic carbon capture via enhancing acetyl-CoA level, which would optimize renewable microalgal biofuel to fulfil the demanding fuel market.

Development of Chemical Isotope Labeling LC-MS for Milk Metabolomics: Comprehensive and Quantitative Profiling of the Amine/Phenol Submetabolome

Milk is a complex sample containing a variety of proteins, lipids, and metabolites. Studying the milk metabolome represents an important application of metabolomics in the general area of nutritional research. However, comprehensive and quantitative analysis of milk metabolites is a challenging task due to the wide range of variations in chemical/physical properties and concentrations of these metabolites. We report an analytical workflow for in-depth profiling of the milk metabolome based on chemical isotope labeling (CIL) and liquid chromatography mass spectrometry (LC-MS) with a focus of using dansylation labeling to target the amine/phenol submetabolome. An optimal sample preparation method, including the use of methanol at a 3:1 ratio of solvent to milk for protein precipitation and dichloromethane for lipid removal, was developed to detect and quantify as many metabolites as possible. This workflow was found to be generally applicable to profile milk metabolomes of different species (cow, goat, and human) and types. Results from experimental replicate analysis (n = 5) of 1:1, 2:1, and 1:2 ¹²C-/¹³C-labeled cow milk samples showed that 95.7%, 94.3%, and 93.2% of peak pairs, respectively, had ratio values within ±50% accuracy range and 90.7%, 92.6%, and 90.8% peak pairs had RSD values of less than 20%. In the metabolomic analysis of 36 samples from different categories of cow milk (brands, batches, and fat percentages) with experimental triplicates, a total of 7104 peak pairs or metabolites could be detected with an average of 4573 ± 505 (n = 108) pairs detected per LC-MS run. Among them, 3820 peak pairs were commonly detected in over 80% of the samples with 70 metabolites positively identified by mass and retention time matches to the dansyl standard library and 2988 pairs with their masses matched to the human metabolome libraries. This unprecedentedly high coverage of the amine/phenol submetabolome illustrates the complexity of the milk metabolome. Since milk and milk products are consumed in large quantities on a daily basis, the intake of these milk metabolites even at low concentrations can be cumulatively high. The high-coverage analysis of the milk metabolome using CIL LC-MS should be very useful in future research involving the study of the effects of these metabolites on human health. It should also be useful in the dairy industry in areas such as improving milk production, developing new processing technologies, developing improved nutritional products, quality control, and milk product authentication.

Mass spectrometric based approaches in urine metabolomics and biomarker discovery

Urine metabolomics has recently emerged as a prominent field for the discovery of non-invasive biomarkers that can detect subtle metabolic discrepancies in response to a specific disease or therapeutic intervention. Urine, compared to other biofluids, is characterized by its ease of collection, richness in metabolites and its ability to reflect imbalances of all biochemical pathways within the body. Following urine collection for metabolomic analysis, samples must be immediately frozen to quench any biogenic and/or non-biogenic chemical reactions. According to the aim of the experiment; sample preparation can vary from simple procedures such as filtration to more specific extraction protocols such as liquid-liquid extraction. Due to the lack of comprehensive studies on urine metabolome stability, higher storage temperatures (i.e. 4°C) and repetitive freeze-thaw cycles should be avoided. To date, among all analytical techniques, mass spectrometry (MS) provides the best sensitivity, selectivity and identification capabilities to analyze the majority of the metabolite composition in the urine. Combined with the qualitative and quantitative capabilities of MS, and due to the continuous improvements in its related technologies (i.e. ultra high-performance liquid chromatography [UPLC] and hydrophilic interaction liquid chromatography [HILIC]), liquid chromatography (LC)-MS is unequivocally the most utilized and the most informative analytical tool employed in urine metabolomics. Furthermore, differential isotope tagging techniques has provided a solution to ion suppression from urine matrix thus allowing for quantitative analysis. In addition to LC-MS, other MS-based technologies have been utilized in urine metabolomics. These include direct injection (infusion)-MS, capillary electrophoresis-MS and gas chromatography-MS. In this article, the current progresses of different MS-based techniques in exploring the urine metabolome as well as the recent findings in providing potentially diagnostic urinary biomarkers are discussed. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:115-134, 2017.

High-Speed Quantitative UPLC-MS Analysis of Multiple Amines in Human Plasma and Serum via Precolumn Derivatization with 6-Aminoquinolyl-N-hydroxysuccinimidyl Carbamate: Application to Acetaminophen-Induced Liver Failure

A targeted reversed-phase gradient UPLC-MS/MS assay has been developed for the quantification /monitoring of 66 amino acids and amino-containing compounds in human plasma and serum using precolumn derivatization with 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AccQTag Ultra). Derivatization of the target amines required minimal sample preparation and resulted in analytes with excellent chromatographic and mass spectrometric detection properties. The resulting method, which requires only 10 μL of sample, provides the reproducible and robust separation of 66 analytes in 7.5 min, including baseline resolution of isomers such as leucine and isoleucine. The assay has been validated for the quantification of 33 amino compounds (predominantly amino acids) over a concentration range from 2 to 20 and 800 μM. Intra- and interday accuracy of between 0.05 and 15.6 and 0.78-13.7% and precision between 0.91 and 16.9% and 2.12-15.9% were obtained. A further 33 biogenic amines can be monitored in samples for relative changes in concentration rather than quantification. Application of the assay to samples derived from healthy controls and patients suffering from acetaminophen (APAP, paracetamol)-induced acute liver failure (ALF) showed significant differences in the amounts of aromatic and branched chain amino acids between the groups as well as a number of other analytes, including the novel observation of increased concentrations of sarcosine in ALF patients. The properties of the developed assay, including short analysis time, make it suitable for high-throughput targeted UPLC-ESI-MS/MS metabonomic analysis in clinical and epidemiological environments.

Profiling of Selected Functional Metabolites in the Central Nervous System of Marine Medaka (Oryzias melastigma) for Environmental Neurotoxicological Assessments

The simultaneous profiling of 43 functional metabolites in the brain of the small model vertebrate organism, marine medaka (Oryzais melastigma), has been accomplished via dansyl chloride derivatization and LC-MS/MS quantification. This technique was applied to examine effects of 2,2',4,4'-tetrabromodiphenyl ether (BDE-47), one of the most abundant polybrominated diphenyl ether flame retardants in the natural environment, on the central nervous system (CNS) of vertebrates. The model teleosts were fed with bioencapsulated Artemia nauplii for up to 21 days. Multivariate statistical analysis has demonstrated that levels of numerous classical neurotransmitters and their metabolites in the CNS of the fish were perturbed even at the early phase of dietary exposure. Subsequent metabolic pathway analysis further implied potential impairment of the arginine and proline metabolism; glycine, serine and threonine metabolism; D-glutamine and D-glutamate metabolism; alanine, aspartate, and glutamate metabolism; valine, leucine, and isoleucine biosynthesis, and the cysteine and methionine metabolism in the brain of the test organism. Our results demonstrate that targeted profiling of functional metabolites in the CNS may shed light on how the various neurological pathways of vertebrates, including humans, are affected by toxicant/stress exposure.

Chemical Isotope Labeling LC-MS for Monitoring Disease Progression and Treatment in Animal Models: Plasma Metabolomics Study of Osteoarthritis Rat Model

We report a chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) method generally applicable for tracking metabolomic changes from samples collected in an animal model for studying disease development and treatment. A rat model of surgically induced osteoarthritis (OA) was used as an example to illustrate the workflow and technical performance. Experimental duplicate analyses of 234 plasma samples were carried out using dansylation labeling LC-MS targeting the amine/phenol submetabolome. These samples composed of 39 groups (6 rats per group) were collected at multiple time points with sham operation, OA control group, and OA rats with treatment, separately, using glucosamine/Celecoxib and three traditional Chinese medicines (Epimedii folium, Chuanxiong Rhizoma and Bushen-Huoxue). In total, 3893 metabolites could be detected and 2923 of them were consistently detected in more than 50% of the runs. This high-coverage submetabolome dataset could be used to track OA progression and treatment. Many differentiating metabolites were found and 11 metabolites including 2-aminoadipic acid, saccharopine and GABA were selected as potential biomarkers of OA progression and OA treatment. This study illustrates that CIL LC-MS is a very useful technique for monitoring incremental metabolomic changes with high coverage and accuracy for studying disease progression and treatment in animal models.

Mass Defect-Based N,N-Dimethyl Leucine Labels for Quantitative Proteomics and Amine Metabolomics of Pancreatic Cancer Cells

Mass spectrometry-based stable isotope labeling has become a key technology for protein and small-molecule analyses. We developed a multiplexed quantification method for simultaneous proteomics and amine metabolomics analyses via nano reversed-phase liquid chromatography-tandem mass spectrometry (nanoRPLC-MS/MS), called mass defect-based N,N-dimethyl leucine (mdDiLeu) labeling. The duplex mdDiLeu reagents were custom-synthesized with a mass difference of 20.5 mDa, arising from the subtle variation in nuclear binding energy between the two DiLeu isotopologues. Optimal MS resolving powers were determined to be 240K for labeled peptides and 120K for labeled metabolites on the Orbitrap Fusion Lumos instrument. The mdDiLeu labeling does not suffer from precursor interference and dynamic range compression, providing excellent accuracy for MS¹-centric quantification. Quantitative information is only revealed at high MS resolution without increasing spectrum complexity and overlapping isotope distribution. Chromatographic performance of polar metabolites was dramatically improved by mdDiLeu labeling with modified hydrophobicity, enhanced ionization efficiency, and picomole levels of detection limits. Paralleled proteomics and amine metabolomics analyses using mdDiLeu were systematically evaluated and then applied to pancreatic cancer cells.

Parallel Metabolomic Profiling of Cerebrospinal Fluid and Serum for Identifying Biomarkers of Injury Severity after Acute Human Spinal Cord Injury

Suffering an acute spinal cord injury (SCI) can result in catastrophic physical and emotional loss. Efforts to translate novel therapies in acute clinical trials are impeded by the SCI community's singular dependence upon functional outcome measures. Therefore, a compelling rationale exists to establish neurochemical biomarkers for the objective classification of injury severity. In this study, CSF and serum samples were obtained at 3 time points (~24, 48, and 72 hours post-injury) from 30 acute SCI patients (10 AIS A, 12 AIS B, and 8 AIS C). A differential chemical isotope labeling liquid chromatography mass spectrometry (CIL LC-MS) with a universal metabolome standard (UMS) was applied to the metabolomic profiling of these samples. This method provided enhanced detection of the amine- and phenol-containing submetabolome. Metabolic pathway analysis revealed dysregulations in arginine-proline metabolism following SCI. Six CSF metabolites were identified as potential biomarkers of baseline injury severity, and good classification performance (AUC > 0.869) was achieved by using combinations of these metabolites in pair-wise comparisons of AIS A, B and C patients. Using the UMS strategy, the current data set can be expanded to a larger cohort for biomarker validation, as well as discovering biomarkers for predicting neurologic outcome.

Nitric oxide participates in plant flowering repression by ascorbate

In Oncidium, redox homeostasis involved in flowering is mainly due to ascorbic acid (AsA). Here, we discovered that Oncidium floral repression is caused by an increase in AsA-mediated NO levels, which is directed by the enzymatic activities of nitrate reductase (NaR) and nitrite reducatase (NiR). Through Solexa transcriptomic analysis of two libraries, ‘pseudobulb with inflorescent bud’ (PIB) and ‘pseudobulb with axillary bud’ (PAB), we identified differentially expressed genes related to NO metabolism. Subsequently, we showed a significant reduction of NaR enzymatic activities and NO levels during bolting and blooming stage, suggesting that NO controlled the phase transition and flowering process. Applying AsA to Oncidium PLB (protocorm-like bodies) significantly elevated the NO content and enzyme activities. Application of sodium nitroprusside (-NO donor) on Arabidopsis vtc1 mutant caused late flowering and expression level of flowering-associated genes (CO, FT and LFY) were reduced, suggesting NO signaling is vital for flowering repression. Conversely, the flowering time of noa1, an Arabidopsis NO-deficient mutant, was not altered after treatment with L-galacturonate, a precursor of AsA, suggesting AsA is required for NO-biosynthesis involved in the NO-mediated flowering-repression pathway. Altogether, Oncidium bolting is tightly regulated by AsA-mediated NO level and downregulation of transcriptional levels of NO metabolism genes.

Metabolite Analysis and Histology on the Exact Same Tissue: Comprehensive Metabolomic Profiling and Metabolic Classification of Prostate Cancer

We report a method of metabolomic profiling of intact tissue based on molecular preservation by extraction and fixation (mPREF) and high-performance chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS). mPREF extracts metabolites by aqueous methanol from tissue biopsies without altering tissue architecture and thus conventional histology can be performed on the same tissue. In a proof-of-principle study, we applied dansylation LC-MS to profile the amine/phenol submetabolome of prostate needle biopsies from 25 patient samples derived from 16 subjects. 2900 metabolites were consistently detected in more than 50% of the samples. This unprecedented coverage allowed us to identify significant metabolites for differentiating tumor and normal tissues. The panel of significant metabolites was refined using 36 additional samples from 18 subjects. Receiver Operating Characteristic (ROC) analysis showed area-under-the-curve (AUC) of 0.896 with sensitivity of 84.6% and specificity of 83.3% using 7 metabolites. A blind study of 24 additional validation samples gave a specificity of 90.9% at the same sensitivity of 84.6%. The mPREF extraction can be readily implemented into the existing clinical workflow. Our method of combining mPREF with CIL LC-MS offers a powerful and convenient means of performing histopathology and discovering or detecting metabolite biomarkers in the same tissue biopsy.

The effects of bupropion on hybrid striped bass brain chemistry and predatory behavior

Increased use of antidepressants has led to an increase in their detection in final treated wastewater effluents and receiving streams. Antidepressants are intended to modify human behavior by altering brain chemistry, and because of the high functional conservation of antidepressant target receptors in vertebrates, aquatic organisms may be at risk. The antidepressant bupropion is designed to alter brain norepinephrine and dopamine concentrations in humans. The objective of the present study was to understand if alteration of dopaminergic neurotransmitter concentrations in the hybrid striped bass (Morone saxatilis × Morone chrysops) brain by bupropion would alter this predator's ability to capture prey. The authors exposed hybrid striped bass to bupropion in a static system for 6 d, followed by a 6-d recovery period. During the present study's 12-d experiment, each hybrid striped bass was fed 4 unexposed fathead minnows every 3 d, and the time it took the hybrid striped bass to consume each of those 4 fathead minnows was quantified. After each feeding event, hybrid striped bass brains were harvested and analyzed for changes in several brain neurotransmitter concentrations, including serotonin, norepinephrine, dopamine, and many of their metabolites. Although bupropion altered the concentration of dopamine and many of the dopaminergic neurotransmitter metabolite concentrations in the brains on day 3 of the exposure, it did not alter the time to capture prey. This suggests that alteration of dopaminergic neurotransmitter concentrations in the hybrid striped bass brain does not alter a predator's ability to capture prey. Environ Toxicol Chem 2016;35:2058-2065. © 2016 SETAC.

In situ derivatization-ultrasound-assisted dispersive liquid-liquid microextraction for the determination of neurotransmitters in Parkinson's rat brain microdialysates by ultra high performance liquid chromatography-tandem mass spectrometry

Simultaneous monitoring of several neurotransmitters (NTs) linked to Parkinson's disease (PD) has important scientific significance for PD related pathology, pharmacology and drug screening. A new simple, fast and sensitive analytical method, based on in situ derivatization-ultrasound-assisted dispersive liquid-liquid microextraction (in situ DUADLLME) in a single step, has been proposed for the quantitative determination of catecholamines and their biosynthesis precursors and metabolites in rat brain microdialysates. The method involved the rapid injection of the mixture of low toxic bromobenzene (extractant) and acetonitrile (dispersant), which containing commercial Lissamine rhodamine B sulfonyl chloride (LRSC) as derivatization reagent, into the aqueous phase of sample and buffer, and the following in situ DUADLLME procedure. After centrifugation, 50μL of the sedimented phase (bromobenzene) was directly injected for ultra high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) detection in multiple reaction monitoring (MRM) mode. This interesting combination brought the advantages of speediness, simpleness, low matrix effects and high sensitivity in an effective way. Parameters of in situ DUADLLME and UHPLC-MS/MS conditions were all optimized in detail. The optimum conditions of in situ DUADLLME were found to be 30μL of microdialysates, 150μL of acetonitrile containing LRSC, 50μL of bromobenzene and 800μL of NaHCO3-Na2CO3 buffer (pH 10.5) for 3.0min at 37°C. Under the optimized conditions, good linearity was observed with LODs (S/N>3) and LOQs (S/N>10) of LRSC derivatized-NTs in the range of 0.002-0.004 and 0.007-0.015 nmol/L, respectively. It also brought good precision (3.2-12.8%, peak area CVs%), accuracy (94.2-108.6%), recovery (94.5-105.5%) and stability (3.8-8.1%, peak area CVs%) results. Moreover, LRSC derivatization significantly improved chromatographic resolution and MS detection sensitivity of NTs when compared with the reported studies through the introduction of a permanent charged moiety from LRSC into NTs. Taken together, this in situ DUADLLME method was successfully applied for the simultaneous determination of six NTs in biological samples.

Benzoyl chloride derivatization with liquid chromatography-mass spectrometry for targeted metabolomics of neurochemicals in biological samples

Widely targeted metabolomic assays are useful because they provide quantitative data on large groups of related compounds. We report a high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method that utilizes benzoyl chloride labeling for 70 neurologically relevant compounds, including catecholamines, indoleamines, amino acids, polyamines, trace amines, antioxidants, energy compounds, and their metabolites. The method includes neurotransmitters and metabolites found in both vertebrates and insects. This method was applied to analyze microdialysate from rats, human cerebrospinal fluid, human serum, fly tissue homogenate, and fly hemolymph, demonstrating its broad versatility for multiple physiological contexts and model systems. Limits of detection for most assayed compounds were below 10nM, relative standard deviations were below 10%, and carryover was less than 5% for 70 compounds separated in 20min, with a total analysis time of 33min. This broadly applicable method provides robust monitoring of multiple analytes, utilizes small sample sizes, and can be applied to diverse matrices. The assay will be of value for evaluating normal physiological changes in metabolism in neurochemical systems. The results demonstrate the utility of benzoyl chloride labeling with HPLC-MS/MS for widely targeted metabolomics assays.

High-Performance Chemical Isotope Labeling Liquid Chromatography-Mass Spectrometry for Profiling the Metabolomic Reprogramming Elicited by Ammonium Limitation in Yeast

Information about how yeast metabolism is rewired in response to internal and external cues can inform the development of metabolic engineering strategies for food, fuel, and chemical production in this organism. We report a new metabolomics workflow for the characterization of such metabolic rewiring. The workflow combines efficient cell lysis without using chemicals that may interfere with downstream sample analysis and differential chemical isotope labeling liquid chromatography mass spectrometry (CIL LC-MS) for in-depth yeast metabolome profiling. Using (12)C- and (13)C-dansylation (Dns) labeling to analyze the amine/phenol submetabolome, we detected and quantified a total of 5719 peak pairs or metabolites. Among them, 120 metabolites were positively identified using a library of 275 Dns-metabolite standards, and 2980 metabolites were putatively identified based on accurate mass matches to metabolome databases. We also applied (12)C- and (13)C-dimethylaminophenacyl (DmPA) labeling to profile the carboxylic acid submetabolome and detected over 2286 peak pairs, from which 33 metabolites were positively identified using a library of 188 DmPA-metabolite standards, and 1595 metabolites were putatively identified. Using this workflow for metabolomic profiling of cells challenged by ammonium limitation revealed unexpected links between ammonium assimilation and pantothenate accumulation that might be amenable to engineering for better acetyl-CoA production in yeast. We anticipate that efforts to improve other schemes of metabolic engineering will benefit from application of this workflow to multiple cell types.