Ultra-high performance liquid chromatography tandem mass spectrometry for comprehensive analysis of urinary acylcarnitines

Isomer-resolved characterization of acylcarnitines reveals alterations in type 2 diabetes

BACKGROUND

Acylcarnitines (CARs) are metabolites of fatty acids that play crucial roles in various cellular energy metabolism pathways. The structural diversity of CAR species arises from several modifications localized on the fatty acyl chain and there is currently a lack of reports characterizing these detailed structures. High-performance liquid chromatography (HPLC)-electrospray mass spectrometry (ESI-MS) is the common tool for CARs analysis.

RESULTS

In this study, we improved the MS detection signals of CARs by adding NH4HCO3 as buffer in the mobile phase of LC system. We demonstrated that electron activated dissociation (EAD) on the ZenoTOF 7600 system is capable of localizing the hydroxyl group and methyl branching position in CARs. The benzophenone Paternò-Büchi (PB) reaction was used for derivatizing the carbon-carbon double bond (CC). The capability of profiling CARs with detailed structural information was demonstrated by analyzing complex lipid extracts from mouse plasma. Our results also provided visualization of isomers composition, including branched chain isomers of CAR 4:0 and CAR 5:0 and CC location isomers of unsaturated CARs. Notably, we observed significant changes in the relative compositions of branched-chain isomers of CAR 5:0 and CC location isomers of several unsaturated CARs in mouse plasma samples from type 2 diabetes (T2D) compared to normal controls, suggesting their potential as diagnostic indicators for T2D.

SIGNIFICANCE

In this work, we enhanced the limit of detection for acylcarnitine species by incorporating ammonium bicarbonate into the LC system. The CC positions in the acyl chain of CARs were identified using Paternò-Büchi (PB) derivatization coupled with tandem mass spectrometry. Modifications such as methyl branching and hydroxyl groups along the acyl chain were localized through Electron-Activated Dissociation (EAD) on the Zeno-TOF 7600 system.

Simultaneously quantifying hundreds of acylcarnitines in multiple biological matrices within ten minutes using ultrahigh-performance liquid-chromatography and tandem mass spectrometry

Acylcarnitines are metabolic intermediates of fatty acids and branched-chain amino acids having vital biofunctions and pathophysiological significances. Here, we developed a high-throughput method for quantifying hundreds of acylcarnitines in one run using ultrahigh performance liquid chromatography and tandem mass spectrometry (UPLC-MS/MS). This enabled simultaneous quantification of 1136 acylcarnitines (C0-C26) within 10-min with good sensitivity (limit of detection < 0.7 fmol), linearity (correlation coefficient > 0.992), accuracy (relative error < 20%), precision (coefficient of variation (CV), CV < 15%), stability (CV < 15%), and inter-technician consistency (CV < 20%, n = 6). We also established a quantitative structure-retention relationship (goodness of fit > 0.998) for predicting retention time (tR) of acylcarnitines with no standards and built a database of their multiple reaction monitoring parameters (tR, ion-pairs, and collision energy). Furthermore, we quantified 514 acylcarnitines in human plasma and urine, mouse kidney, liver, heart, lung, and muscle. This provides a rapid method for quantifying acylcarnitines in multiple biological matrices.

Open access repository-scale propagated nearest neighbor suspect spectral library for untargeted metabolomics

Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of MS/MS spectra originating from published untargeted metabolomics experiments. Entries in this library, or "suspects," were derived from unannotated spectra that could be linked in a molecular network to an annotated spectrum. Annotations were propagated to unknowns based on structural relationships to reference molecules using MS/MS-based spectrum alignment. We demonstrate the broad relevance of the nearest neighbor suspect spectral library through representative examples of propagation-based annotation of acylcarnitines, bacterial and plant natural products, and drug metabolism. Our results also highlight how the library can help to better understand an Alzheimer's brain phenotype. The nearest neighbor suspect spectral library is openly available for download or for data analysis through the GNPS platform to help investigators hypothesize candidate structures for unknown MS/MS spectra in untargeted metabolomics data.

Sample multiplexing-based targeted pathway proteomics with real-time analytics reveals the impact of genetic variation on protein expression

Targeted proteomics enables hypothesis-driven research by measuring the cellular expression of protein cohorts related by function, disease, or class after perturbation. Here, we present a pathway-centric approach and an assay builder resource for targeting entire pathways of up to 200 proteins selected from >10,000 expressed proteins to directly measure their abundances, exploiting sample multiplexing to increase throughput by 16-fold. The strategy, termed GoDig, requires only a single-shot LC-MS analysis, ~1 µg combined peptide material, a list of up to 200 proteins, and real-time analytics to trigger simultaneous quantification of up to 16 samples for hundreds of analytes. We apply GoDig to quantify the impact of genetic variation on protein expression in mice fed a high-fat diet. We create several GoDig assays to quantify the expression of multiple protein families (kinases, lipid metabolism- and lipid droplet-associated proteins) across 480 fully-genotyped Diversity Outbred mice, revealing protein quantitative trait loci and establishing potential linkages between specific proteins and lipid homeostasis.

HPLC–(Q)-TOF-MS-Based Study of Plasma Metabolic Profile Differences Associated with Age in Pediatric Population Using an Animal Model

A deep knowledge about the biological development of children is essential for appropriate drug administration and dosage in pediatrics. In this sense, the best approximation to study organ maturation is the analysis of tissue samples, but it requires invasive methods. For this reason, surrogate matrices should be explored. Among them, plasma emerges as a potential alternative since it represents a snapshot of global organ metabolism. In this work, plasma metabolic profiles from piglets of different ages (newborns, infants, and children) obtained by HPLC–(Q)-TOF-MS at positive and negative ionization modes were studied. Improved clustering within groups was achieved using multiblock principal component analysis compared to classical principal component analysis. Furthermore, the separation observed among groups was better resolved by using partial least squares-discriminant analysis, which was validated by bootstrapping and permutation testing. Thanks to univariate analysis, 13 metabolites in positive and 21 in negative ionization modes were found to be significant to discriminate the three groups of piglets. From these features, an acylcarnitine and eight glycerophospholipids were annotated and identified as metabolites of interest. The findings indicate that there is a relevant change with age in lipid metabolism in which lysophosphatidylcholines and lysophoshatidylethanolamines play an important role.

Acylcarnitines: Nomenclature, Biomarkers, Therapeutic Potential, Drug Targets, and Clinical Trials

Acylcarnitines are fatty acid metabolites that play important roles in many cellular energy metabolism pathways. They have historically been used as important diagnostic markers for inborn errors of fatty acid oxidation and are being intensively studied as markers of energy metabolism, deficits in mitochondrial and peroxisomal β -oxidation activity, insulin resistance, and physical activity. Acylcarnitines are increasingly being identified as important indicators in metabolic studies of many diseases, including metabolic disorders, cardiovascular diseases, diabetes, depression, neurologic disorders, and certain cancers. The US Food and Drug Administration-approved drug L-carnitine, along with short-chain acylcarnitines (acetylcarnitine and propionylcarnitine), is now widely used as a dietary supplement. In light of their growing importance, we have undertaken an extensive review of acylcarnitines and provided a detailed description of their identity, nomenclature, classification, biochemistry, pathophysiology, supplementary use, potential drug targets, and clinical trials. We also summarize these updates in the Human Metabolome Database, which now includes information on the structures, chemical formulae, chemical/spectral properties, descriptions, and pathways for 1240 acylcarnitines. This work lays a solid foundation for identifying, characterizing, and understanding acylcarnitines in human biosamples. We also discuss the emerging opportunities for using acylcarnitines as biomarkers and as dietary interventions or supplements for many wide-ranging indications. The opportunity to identify new drug targets involved in controlling acylcarnitine levels is also discussed. SIGNIFICANCE STATEMENT: This review provides a comprehensive overview of acylcarnitines, including their nomenclature, structure and biochemistry, and use as disease biomarkers and pharmaceutical agents. We present updated information contained in the Human Metabolome Database website as well as substantial mapping of the known biochemical pathways associated with acylcarnitines, thereby providing a strong foundation for further clarification of their physiological roles.

Novel Strategy for Mining and Identification of Acylcarnitines Using Data-Independent-Acquisition-Based Retention Time Prediction Modeling and Pseudo-Characteristic Fragmentation Ion Matching

It is a challenging work to screen, identify, and quantify acylcarnitines in complex biological samples. A method, based on the retention time (RT) prediction and data-independent acquisition strategies, was proposed for the large-scale identification of acylcarnitines using liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS). Relative cumulative eluotropic strength was introduced as a novel descriptor in building a linear prediction model, which not only solves the problem that acylcarnitines with long carbon chains cannot be well predicted in traditional models but also proves its robustness and transferability across instruments in two data sets that were acquired in distinct chromatography conditions. The accessibility of both predictive RT and MS² spectra of suspect features effectively reduced about 30% false-positive results, and consequently, 150 and 186 acylcarnitines were identified in the rat liver and human plasma (NIST SRM 1950), respectively. This method provides a new approach in large-scale analysis of acylcarnitine in lipidomic studies and can also be extended to the analysis of other lipids.

Mass Spectral Library of Acylcarnitines Derived from Human Urine

We describe the creation of a mass spectral library of acylcarnitines and conjugated acylcarnitines from the LC-MS/MS analysis of six NIST urine reference materials. To recognize acylcarnitines, we conducted in-depth analyses of fragmentation patterns of acylcarnitines and developed a set of rules, derived from spectra in the NIST17 Tandem MS Library and those identified in urine, using the newly developed hybrid search method. Acylcarnitine tandem spectra were annotated with fragments from carnitine and acyl moieties as well as neutral loss peaks from precursors. Consensus spectra were derived from spectra having similar retention time, fragmentation pattern, and the same precursor m/z and collision energy. The library contains 157 different precursor masses, 586 unique acylcarnitines, and 4 332 acylcarnitine consensus spectra. Furthermore, from spectra that partially satisfied the fragmentation rules of acylcarnitines, we identified 125 conjugated acylcarnitines represented by 987 consensus spectra, which appear to originate from Phase II biotransformation reactions. To our knowledge, this is the first report of conjugated acylcarnitines. The mass spectra provided by this work may be useful for clinical screening of acylcarnitines as well as for studying relationships among fragmentation patterns, collision energies, structures, and retention times of acylcarnitines. Further, these methods are extensible to other classes of metabolites.

Perspective: Dietary Biomarkers of Intake and Exposure-Exploration with Omics Approaches

While conventional nutrition research has yielded biomarkers such as doubly labeled water for energy metabolism and 24-h urinary nitrogen for protein intake, a critical need exists for additional, equally robust biomarkers that allow for objective assessment of specific food intake and dietary exposure. Recent advances in high-throughput MS combined with improved metabolomics techniques and bioinformatic tools provide new opportunities for dietary biomarker development. In September 2018, the NIH organized a 2-d workshop to engage nutrition and omics researchers and explore the potential of multiomics approaches in nutritional biomarker research. The current Perspective summarizes key gaps and challenges identified, as well as the recommendations from the workshop that could serve as a guide for scientists interested in dietary biomarkers research. Topics addressed included study designs for biomarker development, analytical and bioinformatic considerations, and integration of dietary biomarkers with other omics techniques. Several clear needs were identified, including larger controlled feeding studies, testing a variety of foods and dietary patterns across diverse populations, improved reporting standards to support study replication, more chemical standards covering a broader range of food constituents and human metabolites, standardized approaches for biomarker validation, comprehensive and accessible food composition databases, a common ontology for dietary biomarker literature, and methodologic work on statistical procedures for intake biomarker discovery. Multidisciplinary research teams with appropriate expertise are critical to moving forward the field of dietary biomarkers and producing robust, reproducible biomarkers that can be used in public health and clinical research.

Mass Spectrometry Fingerprints of Small-Molecule Metabolites in Biofluids: Building a Spectral Library of Recurrent Spectra for Urine Analysis

A large fraction of ions observed in electrospray liquid chromatography-mass spectrometry (LC-ESI-MS) experiments of biological samples remain unidentified. One of the main reasons for this is that spectral libraries of pure compounds fail to account for the complexity of the metabolite profiling of complex materials. Recently, the NIST Mass Spectrometry Data Center has been developing a novel type of searchable mass spectral library that includes all recurrent unidentified spectra found in the sample profile. These libraries, in conjunction with the NIST tandem mass spectral library, allow analysts to explore most of the chemical space accessible to LC-MS analysis. In this work, we demonstrate how these libraries can provide a reliable fingerprint of the material by applying them to a variety of urine samples, including an extremely altered urine from cancer patients undergoing total body irradiation. The same workflow is applicable to any other biological fluid. The selected class of acylcarnitines is examined in detail, and derived libraries and related software are freely available. They are intended to serve as online resources for continuing community review and improvement.

Acylcarnitine profiling by low-resolution LC-MS

Acylcarnitines are fatty acyl esters of L-carnitine and facilitate the entry of long-chain fatty acids into mitochondria via the carnitine shuttle, where they are metabolized via ß-oxidation. Alterations of acylcarnitine species can be diagnostic for fatty acid oxidation disorders and organic aciduria and are thus frequently used to screen newborns. Only a subfraction of all known acylcarnitines is thereby monitored and quantified. Therefore, a method for the simultaneous fast and robust detection of all known acylcarnitines was developed using a single concise liquid chromatography mass spectrometry (LC-MS) approach. Derivatization by 3-nitrophenylhydrazine increased the signal intensity of the acylcarnitines and a linear elution from a reversed phase column was observed that was dependent on the length of the carbon chain. This allowed a precise prediction of the exact elution time for each acylcarnitine class, which depended solely on the chemical nature of the carbon chain. This method can be further used to screen for yet unknown acylcarnitine species and adds a layer of confidence for their correct identification. Altogether 123 acylcarnitines species were used to establish a targeted low-resolution LC-MS method. The method was applied to acylcarnitine profiling in several mouse tissues and fluids, in order to identify large differences in the quantity and composition of acylcarnitines.

Identification of new urinary gamma-hydroxybutyric acid markers applying untargeted metabolomics analysis following placebo-controlled administration to humans

Gamma-hydroxybutyrate (GHB) is a short-chain fatty acid that occurs naturally in the mammalian brain and is prescribed as a medication against narcolepsy or used as a drug of abuse. Particularly, its use as a knock-out drug in cases of drug-facilitated crimes is of major importance in forensic toxicology. Because of its rapid metabolism and resulting narrow detection windows (<12 hours in urine), detection of GHB remains challenging. Thus, there is an urgent call for new markers to improve the reliable detection of GHB use. In the framework of a randomized, placebo-controlled, crossover study in 20 healthy male volunteers, urine samples obtained 4.5 hours post-administration were submitted to untargeted mass spectrometry [MS, quadrupole time of flight (QTOF)] analysis to identify possible new markers of GHB intake. MS data from four different analytical methods (reversed phase and hydrophilic interaction liquid chromatography; positive and negative electrospray ionization) were filtered for significantly changed features applying univariate and multivariate statistics. From the resulting 42 compounds of interest, 8 were finally identified including conjugates of GHB with carnitine, glutamate, and glycine as well as the endogenous compounds glycolate and succinylcarnitine. While GHB conjugates were only detectable in the GHB, but not in the placebo group, glycolate and succinylcarnitine were present in both groups albeit significantly increased through GHB intake. Untargeted metabolomics proved as a suitable tool for the non-hypothesis driven identification of new GHB markers. However, more studies on actual concentrations, detection windows, and stability will be necessary to assess the suitability of these markers for routine application.

Function, Detection and Alteration of Acylcarnitine Metabolism in Hepatocellular Carcinoma

Acylcarnitines play an essential role in regulating the balance of intracellular sugar and lipid metabolism. They serve as carriers to transport activated long-chain fatty acids into mitochondria for β-oxidation as a major source of energy for cell activities. The liver is the most important organ for endogenous carnitine synthesis and metabolism. Hepatocellular carcinoma (HCC), a primary malignancy of the live with poor prognosis, may strongly influence the level of acylcarnitines. In this paper, the function, detection and alteration of acylcarnitine metabolism in HCC were briefly reviewed. An overview was provided to introduce the metabolic roles of acylcarnitines involved in fatty acid β-oxidation. Then different analytical platforms and methodologies were also briefly summarised. The relationship between HCC and acylcarnitine metabolism was described. Many of the studies reported that short, medium and long-chain acylcarnitines were altered in HCC patients. These findings presented current evidence in support of acylcarnitines as new candidate biomarkers for studies on the pathogenesis and development of HCC. Finally we discussed the challenges and perspectives of exploiting acylcarnitine metabolism and its related metabolic pathways as a target for HCC diagnosis and prognosis.

Metabolic profiling analysis upon acylcarnitines in tissues of hepatocellular carcinoma revealed the inhibited carnitine shuttle system caused by the downregulated carnitine palmitoyltransferase 2

The carnitine shuttle system (CSS) plays a crucial role in the transportation of fatty acyls during fatty acid β-oxidation for energy supplementation, especially in cases of high energy demand, such as in cancer. In this study, to systematically characterize alterations of the CSS in hepatocellular carcinoma (HCC), acylcarnitine metabolic profiling was carried out on 80 pairs of HCC tissues and adjacent noncancerous tissues (ANTs) by using ultra-performance liquid chromatography coupled to mass spectrometry. Twenty-four acylcarnitines classified into five categories were identified and characterized between HCCs and ANTs. Notably, increased saturated long-chain acylcarnitines (LCACs) and decreased short- and medium-chain acylcarnitines (S/MCACs) were simultaneously observed in HCC samples. Subsequent correlation network and heatmap analysis indicated low correlations between LCACs and S/MCACs. The mRNA and protein expressions of carnitine palmitoyltransferase 2 (CPT2) was significantly downregulated in HCC samples, whereas CPT1A expression was not significantly changed. Correspondingly, the relative levels of S/MCACs were reduced and those of LCACs were increased in BEL-7402/CPT2-knockdown cells compared to negative controls. Both results suggested that decreased shuttling efficiency in HCC might be associated with downregulation of CPT2. In addition, decreases in the mRNA expression of acetyl-CoA acyltransferase 2 were also observed in HCC tissues and BEL-7402/CPT2-knockdown cells, suggesting potential low β-oxidation efficiency, which was consistent with the increased expression of stearoyl-CoA desaturase 1 in both samples. The systematic strategy applied in our study illustrated decreased shuttling efficiency of the carnitine shuttle system in HCC and can provide biologists with an in-depth understanding of β-oxidation in HCC.

Effect of Toxicants on Fatty Acid Metabolism in HepG2 Cells

Impairment of hepatic fatty acid metabolism can lead to liver steatosis and injury. Testing drugs for interference with hepatic fatty acid metabolism is therefore important. To find out whether HepG2 cells are suitable for this purpose, we investigated the effect of three established fatty acid metabolism inhibitors and of three test compounds on triglyceride accumulation, palmitate metabolism, the acylcarnitine pool and dicarboxylic acid accumulation in the cell supernatant and on ApoB-100 excretion in HepG2 cells. The three established inhibitors [etomoxir, methylenecyclopropylacetic acid (MCPA), and 4-bromocrotonic acid (4-BCA)] depleted mitochondrial ATP at lower concentrations than cytotoxicity occurred, suggesting mitochondrial toxicity. They inhibited palmitate metabolism at similar or lower concentrations than ATP depletion, and 4-BCA was associated with cellular fat accumulation. They caused specific changes in the acylcarnitine pattern and etomoxir an increase of thapsic (C18 dicarboxylic) acid in the cell supernatant, and did not interfere with ApoB-100 excretion (marker of VLDL export). The three test compounds (amiodarone, tamoxifen, and the cannabinoid WIN 55,212-2) depleted the cellular ATP content at lower concentrations than cytotoxicity occurred. They all caused cellular fat accumulation and inhibited palmitate metabolism at similar or higher concentrations than ATP depletion. They suppressed medium-chain acylcarnitines in the cell supernatant and amiodarone and tamoxifen impaired thapsic acid production. Tamoxifen and WIN 55,212-2 decreased cellular ApoB-100 excretion. In conclusion, the established inhibitors of fatty acid metabolism caused the expected effects in HepG2 cells. HepG cells proved to be useful for the detection of drug-associated toxicities on hepatocellular fatty acid metabolism.

Urinary Metabolomics Profiles Associated to Bovine Meat Ingestion in Humans

SCOPE

The impact of meat consumption on human health is widely examined in nutritional epidemiological studies, especially due to the connection between the consumption of red and processed meat and the risk of colon cancer. Food questionnaires do not assess the exposure to different methods of meat cooking. This study aimed to identify biomarkers of the acute ingestion of bovine meat cooked with two different processes.

METHODS AND RESULTS

Non-targeted UPLC-MS metabolite profiling was done on urine samples obtained from 24 healthy volunteers before and 8 h after the ingestion of a single meal composed of intrinsically ¹⁵ N labelled bovine meat, either cooked at 55 °C for 5 min or at 90 °C for 30 min. A discriminant analysis extension of independent components analysis was applied to the mass spectral data. After meat ingestion, the urinary excretion of 1-methylhistidine, phenylacetylglutamine, and short- and medium-chained acylcarnitines was observed. ¹⁵ N labelling was detected in these metabolites, thus confirming their origin from ingested meat. However, no difference was observed in urinary metabolomic profiles according to the meat cooking process used.

CONCLUSION

Meat ingestion led to the excretion of several nitrogen-containing compounds, but although a metabolic signature was detected for meat ingestion, the impact of the cooking process was not detectable at the level of urinary metabolic signature in our experimental conditions.

Comprehensive Analysis of Acylcarnitine Species in db/db Mouse Using a Novel Method of High-Resolution Parallel Reaction Monitoring Reveals Widespread Metabolic Dysfunction Induced by Diabetes

Acylcarnitines are exerting a variety of biological functions depending on the differences in lengths, saturation levels, and conjugation groups, which to a great extent contribute to the challenges of acylcarnitines quantifications due to various kinds of isomers. Here, we describe a novel method by using high-resolution parallel reaction monitoring (PRM) liquid chromatography-tandem mass spectrometry (LC-MS/MS). Both reversed-phase and normal-phase column were used in order to get accurate, reliable, widespread quantification of acylcarnitines, and without tedious sample preparation procedure. The method provided the most comprehensive acylcarnitine profile with high-resolution MS and MS/MS confirmation to date. A total of 117 acylcarnitines were detected from plasma and urine samples. The application of targeted profiling of acylcarnitines in db/m+ control and db/db diabetic mice indicated incomplete amino acid and fatty acid oxidation on diabetic mice. Interestingly, the reduction of medium odd-numbered chain acylcarnitines in urine samples was first observed between db/m+ and db/db mice. The high-resolution PRM method makes it possible to monitor the widespread metabolic changes of the acylcarnitines in response to stimuli. Besides, the accurate MS and MS/MS spectra data of the 117 acylcarnitines could be used as mass spectrometric resources for the identification of acylcarnitines.

Simultaneous metabolomics and lipidomics analysis based on novel heart-cutting two-dimensional liquid chromatography-mass spectrometry

Increasing metabolite coverage by combining data from different platforms or methods can improve understanding of related metabolic mechanisms and the identification of biomarkers. However, no one method can obtain metabolomic and lipidomic information in a single analysis. In this work, aiming at collecting comprehensive information on metabolome and lipidome in a single analytical run, we developed an on-line heart-cutting two-dimensional liquid chromatography-mass spectrometry (2D-LC-MS) method. Complex metabolites from biological samples are divided into two fractions by using a precolumn. The first fraction is directly transferred and subjected to metabolomics analysis. Most lipids are retained on the precolumn until the mobile phases for lipidomics flow through; then they are subjected to lipidomics analysis. Up to 447 and 289 metabolites in plasma, including amino acids, carnitines, bile acids, free fatty acids, lyso-phospholipids, phospholipids, sphingomyelins etc. were identified within 30 min in the positive mode and negative mode, respectively. A comparison of the newly developed method with the conventional metabolomic and lipidomic approaches showed that approximately 99% features obtained by the two conventional methods can be covered with this 2D-LC method. Analytical characteristics evaluation showed the method had a wide linearity range, high sensitivity, satisfactory recovery and repeatability. These results demonstrate that this method is reliable, stable and well qualified in metabolomics analysis, particularly for large-scale metabolomics studies with small amount of samples.

Methods used to increase the comprehensive coverage of urinary and plasma metabolomes by MS

Metabolomics, focusing on comprehensive analysis of all the metabolites in a biological system, provides a direct signature of biochemical activity. Using emerging technologies in MS, it is possible to simultaneously and rapidly analyze thousands of metabolites. However, due to the chemical and physical diversity of metabolites, it is difficult to acquire a comprehensive and reliable profiling of the whole metabolome. Here, we summarize the state of the art in metabolomics research, focusing on efforts to provide a more comprehensive metabolome coverage via improvements in two fundamental processes: sample preparation and MS analysis. Additionally, the reliable analysis is also highlighted via the combinations of multiple methods (e.g., targeted and untargeted approaches), and analytical quality control and calibration methods.

Enhanced acylcarnitine annotation in high-resolution mass spectrometry data: fragmentation analysis for the classification and annotation of acylcarnitines

Metabolite annotation and identification are primary challenges in untargeted metabolomics experiments. Rigorous workflows for reliable annotation of mass features with chemical structures or compound classes are needed to enhance the power of untargeted mass spectrometry. High-resolution mass spectrometry considerably improves the confidence in assigning elemental formulas to mass features in comparison to nominal mass spectrometry, and embedding of fragmentation methods enables more reliable metabolite annotations and facilitates metabolite classification. However, the analysis of mass fragmentation spectra can be a time-consuming step and requires expert knowledge. This study demonstrates how characteristic fragmentations, specific to compound classes, can be used to systematically analyze their presence in complex biological extracts like urine that have undergone untargeted mass spectrometry combined with data dependent or targeted fragmentation. Human urine extracts were analyzed using normal phase liquid chromatography (hydrophilic interaction chromatography) coupled to an Ion Trap-Orbitrap hybrid instrument. Subsequently, mass chromatograms and collision-induced dissociation and higher-energy collisional dissociation (HCD) fragments were annotated using the freely available MAGMa software¹. Acylcarnitines play a central role in energy metabolism by transporting fatty acids into the mitochondrial matrix. By filtering on a combination of a mass fragment and neutral loss designed based on the MAGMa fragment annotations, we were able to classify and annotate 50 acylcarnitines in human urine extracts, based on high-resolution mass spectrometry HCD fragmentation spectra at different energies for all of them. Of these annotated acylcarnitines, 31 are not described in HMDB yet and for only 4 annotated acylcarnitines the fragmentation spectra could be matched to reference spectra. Therefore, we conclude that the use of mass fragmentation filters within the context of untargeted metabolomics experiments is a valuable tool to enhance the annotation of small metabolites.

A metabolomics-driven approach to predict cocoa product consumption by designing a multimetabolite biomarker model in free-living subjects from the PREDIMED study

SCOPE

The aim of the current study was to apply an untargeted metabolomics strategy to characterize a model of cocoa intake biomarkers in a free-living population.

METHODS AND RESULTS

An untargeted HPLC-q-ToF-MS based metabolomics approach was applied to human urine from 32 consumers of cocoa or derived products (CC) and 32 matched control subjects with no consumption of cocoa products (NC). The multivariate statistical analysis (OSC-PLS-DA) showed clear differences between CC and NC groups. The discriminant biomarkers identified were mainly related to the metabolic pathways of theobromine and polyphenols, as well as to cocoa processing. Consumption of cocoa products was also associated with reduced urinary excretions of methylglutarylcarnitine, which could be related to effects of cocoa exposure on insulin resistance. To improve the prediction of cocoa consumption, a combined urinary metabolite model was constructed. ROC curves were performed to evaluate the model and individual metabolites. The AUC values (95% CI) for the model were 95.7% (89.8-100%) and 92.6% (81.9-100%) in training and validation sets, respectively, whereas the AUCs for individual metabolites were <90%.

CONCLUSIONS

The metabolic signature of cocoa consumption in free-living subjects reveals that combining different metabolites as biomarker models improves prediction of dietary exposure to cocoa.

A generic multiple reaction monitoring based approach for plant flavonoids profiling using a triple quadrupole linear ion trap mass spectrometry

Flavonoids are one of the largest classes of plant secondary metabolites serving a variety of functions in plants and associating with a number of health benefits for humans. Typically, they are co-identified with many other secondary metabolites using untargeted metabolomics. The limited data quality of untargeted workflow calls for a shift from the breadth-first to the depth-first screening strategy when a specific biosynthetic pathway is focused on. Here we introduce a generic multiple reaction monitoring (MRM)-based approach for flavonoids profiling in plants using a hybrid triple quadrupole linear ion trap (QTrap) mass spectrometer. The approach includes four steps: (1) preliminary profiling of major aglycones by multiple ion monitoring triggered enhanced product ion scan (MIM-EPI); (2) glycones profiling by precursor ion triggered EPI scan (PI-EPI) of major aglycones; (3) comprehensive aglycones profiling by combining MIM-EPI and neutral loss triggered EPI scan (NL-EPI) of major glycone; (4) in-depth flavonoids profiling by MRM-EPI with elaborated MRM transitions. Particularly, incorporation of the NH3 loss and sugar elimination proved to be very informative and confirmative for flavonoids screening. This approach was applied for profiling flavonoids in Astragali radix (Huangqi), a famous herb widely used for medicinal and nutritional purposes in China. In total, 421 flavonoids were tentatively characterized, among which less than 40 have been previously reported in this medicinal plant. This MRM-based approach provides versatility and sensitivity that required for flavonoids profiling in plants and serves as a useful tool for plant metabolomics.

Fish oil omega-3 fatty acids partially prevent lipid-induced insulin resistance in human skeletal muscle without limiting acylcarnitine accumulation

Intravenous infusion of lipid into healthy males caused insulin resistance. Addition of fish oil omega-3 polyunsaturated fatty acids to the lipid infusion partially prevented the insulin resistance. This effect was not due to differences in muscle acylcarnitine content.

Effect of Allium macrostemon on a rat model of depression studied by using plasma lipid and acylcarnitine profiles from liquid chromatography/mass spectrometry

The present study aimed to investigate the anti-depressive effect of the traditional Chinese medicine Allium macrostemon in a rat model of depression induced by exposure to chronic immobilization stress. Lipid and acylcarnitine metabolism were set into the focus of this study due to their key role in the pathogenesis of depression. Plasma lipid profiling was performed by ultra fast liquid chromatography/ion trap-time of flight mass spectrometry. Ultra-high performance liquid chromatography/triple quadrupole mass spectrometry was used to characterize the plasma acylcarnitine profile. Principal component analysis (PCA) revealed distinct differences in plasma lipid and acylcarnitine profiles of depressed rats from those in the control rats, which were also validated by univariate analysis. Several lysophosphatidylcholines (LPC (18:1→:2), LPC (20:1), LPC (O-16:2), and LPC (O-18:3)) as well as most medium- and long-chain acylcarnitines were elevated, while some phosphatidylcholines (PC (32:1), PC (36:4→:5), PC (37:4), PC (38:4→:6), PC (40:6), PC (O-36:4), and PC (O-38:5)) and triglycerides (TG (58:12), TG (60:12), and TG (62:13→:14)) were decreased in the plasma of depressed rats. These changes indicate that depressed rats were associated with inflammatory conditions and an incomplete β-oxidation of fatty acids. Most of these dysregulated metabolites were returned to their normal levels after treatment with A. macrostemon according to PCA and univariate analysis, highlighting the anti-depressive effect of this traditional Chinese medicine. These results show that liquid chromatography/mass spectrometry-based quantitative metabolic profiling method is a useful tool to investigate the metabolic changes in depression and the anti-depressive effect of traditional Chinese medicine.

Development of urinary biomarkers for internal exposure by cesium-137 using a metabolomics approach in mice

Cesium-137 is a fission product of uranium and plutonium in nuclear reactors and is released in large quantities during nuclear explosions or detonation of an improvised device containing this isotope. This environmentally persistent radionuclide undergoes radioactive decay with the emission of beta particles as well as gamma radiation. Exposure to (137)Cs at high doses can cause acute radiation sickness and increase risk for cancer and death. The serious health risks associated with (137)Cs exposure makes it critical to understand how it affects human metabolism and whether minimally invasive and easily accessible samples such as urine and serum can be used to triage patients in case of a nuclear disaster or a radiologic event. In this study, we have focused on establishing a time-dependent metabolomic profile for urine collected from mice injected with (137)CsCl. The samples were collected from control and exposed mice on days 2, 5, 20 and 30 after injection. The samples were then analyzed by ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry (UPLC/TOFMS) and processed by an array of informatics and statistical tools. A total of 1,412 features were identified in ESI(+) and ESI(-) modes from which 200 were determined to contribute significantly to the separation of metabolomic profiles of controls from those of the different treatment time points. The results of this study highlight the ease of use of the UPLC/TOFMS platform in finding urinary biomarkers for (137)Cs exposure. Pathway analysis of the statistically significant metabolites suggests perturbations in several amino acid and fatty acid metabolism pathways. The results also indicate that (137)Cs exposure causes: similar changes in the urinary excretion levels of taurine and citrate as seen with external-beam gamma radiation; causes no attenuation in the levels of hexanoylglycine and N-acetylspermidine; and has unique effects on the levels of isovalerylglycine and tiglylglycine.

A sensitive UPLC-MS/MS method for simultaneous determination of eleven bioactive components of Tong-Xie-Yao-Fang decoction in rat biological matrices

There is a growing concern for the sensitive quantification of multiple components using advanced data acquisition method in herbal medicines (HMs). An improved and rugged UPLC-MS/MS method has been developed and validated for sensitive and rapid determination of multiply analytes from Tong-Xie-Yao-Fang (TXYF) decoction in three biological matrices (plasma/brain tissue/urine) using geniposide and formononetin as internal standards. After solid-phase extraction, chromatographic separation was performed on a C18 column using gradient elution. Quantifier and qualifier transitions were monitored using novel Triggered Dynamic multiple reaction monitoring (TdMRM) in the positive ionization mode. A significant peak symmetry and sensitivity improvement in the TdMRM mode was achieved as compared to conventional MRM. The reproducibility (RSD%) was ≤7.9% by applying TdMRM transition while the values were 6.8-20.6% for MRM. Excellent linear calibration curves were obtained under TdMRM transitions over the tested concentration ranges. Intra- and inter-day precisions (RSD%) were ≤14.2% and accuracies (RE%) ranged from -9.6% to 10.6%. The validation data of specificity, carryover, recovery, matrix effect and stability were within the required limits. The method was effectively applied to simultaneously detect and quantify 1 lactone, 2 monoterpene glucosides, 1 alkaloid, 5 flavonoids and 2 chromones in plasma, brain tissue and urine after oral administration of TXYF decoction. In conclusion, this new and reliable method is beneficial for quantification and confirmation assays of multiply components in complex biological samples.

Separation and identification of underivatized plasma acylcarnitine isomers using liquid chromatography-tandem mass spectrometry for the differential diagnosis of organic acidemias and fatty acid oxidation defects

A simple HPLC-MS/MS method has been established to separate and identify underivatized acylcarnitine isomers. Human plasma samples were deproteinized and concentrated. Acylcarnitines were separated on a reverse phase column and detected with triple quadrupole linear ion trap mass spectrometry. Deuterium-labeled internal standards were used for quantitation. To identify acylcarnitines without pure standards, information-dependent acquisition linking to enhanced product ion scan mode was used. 112 acylcarnitines, including stereoisomers, were found in samples of patients. Dicarboxylic acylcarnitines, such as methylmalonylcarnitine and glutarylcarnitine, were detected with high sensitivity. Three stereoisomers of (R,S)2-methyl-3-hydroxy butyrylcarnitine were detected in samples of patients with β-ketothiolase deficiency. Validation results revealed excellent precision and accuracy of the method. In general the within- and between-run coefficients of variation (CV%) were less than 15%, and recoveries were in the range of 92.7-117.5%. In addition, the reference intervals of acylcarnitines for children aged 3-day to13-year old were established. Using the new method and reference intervals, we have correctly diagnosed 49 patients with fatty acid oxidation defects or organic acidemias in 176 high-risk patients.

Serum metabolome and lipidome changes in adult patients with primary dengue infection

Background

Dengue virus (DENV) is the most widespread arbovirus with an estimated 100 million infections occurring every year. Endemic in the tropical and subtropical areas of the world, dengue fever/dengue hemorrhagic fever (DF/DHF) is emerging as a major public health concern. The complex array of concurrent host physiologic changes has hampered a complete understanding of underlying molecular mechanisms of dengue pathogenesis.

Methodology/Principle Findings

Systems level characterization of serum metabolome and lipidome of adult DF patients at early febrile, defervescence, and convalescent stages of DENV infection was performed using liquid chromatography- and gas chromatography-mass spectrometry. The tractability of following metabolite and lipid changes in a relatively large sample size (n = 44) across three prominent infection stages allowed the identification of critical physiologic changes that coincided with the different stages. Sixty differential metabolites were identified in our metabolomics analysis and the main metabolite classes were free fatty acids, acylcarnitines, phospholipids, and amino acids. Major perturbed metabolic pathways included fatty acid biosynthesis and β-oxidation, phospholipid catabolism, steroid hormone pathway, etc., suggesting the multifactorial nature of human host responses. Analysis of phospholipids and sphingolipids verified the temporal trends and revealed association with lymphocytes and platelets numbers. These metabolites were significantly perturbed during the early stages, and normalized to control levels at convalescent stage, suggesting their potential utility as prognostic markers.

Conclusions/Significance

DENV infection causes temporally distinct serum metabolome and lipidome changes, and many of the differential metabolites are involved in acute inflammatory responses. Our global analyses revealed early anti-inflammatory responses working in concert to modulate early pro-inflammatory processes, thus preventing the host from development of pathologies by excessive or prolonged inflammation. This study is the first example of how an omic- approach can divulge the extensive, concurrent, and dynamic host responses elicited by DENV and offers plausible physiological insights to why DF is self limiting.

Dengue virus is the most widespread arbovirus and a major public health threat in the tropical and subtropical areas of the world. As yet, little is known about the molecular mechanisms underlying infection, and there is no specific treatment or vaccine that is currently effective against the disease. Metabolomics and lipidomics provide global views of metabolome and lipidome landscapes and implicate metabolic to disease phenotype. We performed serum metabolic and lipidomic profiling on a cohort of dengue patients with three sampling time points at early febrile, defervescence, and convalescent stages via mass spectrometry-based analytical platforms. Compared with healthy subjects, approximately two hundred metabolites showed significant difference in dengue patients, and 60 were identified. This study revealed that in primary dengue infection, the host metabolome is tightly regulated, with active, early anti-inflammatory processes modulating the pro-inflammatory processes, suggesting the self-limiting phenotype of dengue fever. Major perturbed metabolic pathways included fatty acid biosynthesis, fatty acid β-oxidation, phospholipid catabolism, steroid hormone pathway, etc. This represents a first report on the characterization of the serum metabolome and significantly advances our understanding on host and dengue virus interactions. These differential metabolites have the potential as biomarkers for disease monitoring and evaluation of therapeutic interventions.

Simultaneous determination of multiveterinary drug residues in pork meat by liquid chromatography-tandem mass spectrometry combined with solid phase extraction

An LC-MS/MS method developed for simultaneous analysis of 54 veterinary drug residues of six families in pork meat samples, including sulfanilamide, nitroimidazoles, quinolones, macrolide antibiotics, lincosamides, and praziquantel. The pork meat sample was prepared by extraction with ACN, and clean-up on a C(18) SPE cartridge. The sample was separated on a C(8) column and eluted with ACN, methanol, and formic acid. The MS/MS detector is operated in the multiple reaction monitoring mode, acquiring two specific precursor-product ion transitions per target compound. The method showed excellent linearity (R(2) ≥ 0.99) and high precision (relative SD, RSD ≤ 19.8%) for all compounds. The method quantification limits of 54 veterinary drug residues were in the range of 0.3-3.0 μg/kg. Recoveries for most analytes based on matrix-matched calibration in matrices were 20.9-121.0%. This method has been successfully applied for analysis of more than 100 pork meat samples from the local market; five of the 54 drugs were detected.

Sensitive and reliable multianalyte quantitation of herbal medicine in rat plasma using dynamic triggered multiple reaction monitoring

There is a growing need both clinically and experimentally to improve the determination of the blood levels of multiple chemical constituents in herbal medicines. The conventional multiple reaction monitoring (cMRM), however, is not well suited for multi-component determination and could not provide qualitative information for identity confirmation. Here we apply a dynamic triggered MRM (DtMRM) algorithm for the quantification of 20 constituents in an herbal prescription Bu-Zhong-Yi-Qi-Tang (BZYQT) in rat plasma. Dynamic MRM (DMRM) dramatically reduced the number of concurrent MRM transitions that are monitored during each MS scan. This advantage has been enhanced with the addition of triggered MRM (tMRM) for simultaneous confirmation, which maximizes the dwell time in the primary MRM quantitation phase, and also acquires sufficient MRM data to create a composite product ion spectrum. By allowing optimized collision energy for each product ion and maximizing dwell times, tMRM is significantly more sensitive and reliable than conventional product ion scanning. The DtMRM approach provides much higher sensitivity and reproducibility than cMRM.

Annotation of the human adult urinary metabolome and metabolite identification using ultra high performance liquid chromatography coupled to a linear quadrupole ion trap-Orbitrap mass spectrometer

Metabolic profiles of biofluids obtained by atmospheric pressure ionization mass spectrometry-based technologies contain hundreds to thousands of features, most of them remaining unknown or at least not characterized in analytical systems. We report here on the annotation of the human adult urinary metabolome and metabolite identification from electrospray ionization mass spectrometry (ESI-MS)-based metabolomics data sets. Features of biological interest were first of all annotated using the ESI-MS database of the laboratory. They were also grouped, thanks to software tools, and annotated using public databases. Metabolite identification was achieved using two complementary approaches: (i) formal identification by matching chromatographic retention times, mass spectra, and also product ion spectra (if required) of metabolites to be characterized in biological data sets to those of reference compounds and (ii) putative identification from biological data thanks to MS/MS experiments for metabolites not available in our chemical library. By these means, 384 metabolites corresponding to 1484 annotated features (659 in negative ion mode and 825 in positive ion mode) were characterized in human urine samples. Of these metabolites, 192 and 66 were formally and putatively identified, respectively, and 54 are reported in human urine for the first time. These lists of features could be used by other laboratories to annotate their ESI-MS metabolomics data sets.

Identification of metabolites of Si-Ni-San, a traditional Chinese medicine formula, in rat plasma and urine using liquid chromatography/diode array detection/triple-quadrupole spectrometry

Si-Ni-San (SNS) is a widely used traditional Chinese medicine formula (TCMF) in treating various diseases. However, the in vivo integrated metabolism of its multiple components remains unknown. In this paper, a liquid chromatography coupled with diode array detection and triple-quadrupole spectrometry (LC-DAD-MS/MS) method was developed for detection and identification of SNS metabolites in rat plasma and urine at a normal clinical dosage. Accurate structural elucidation was performed using MS/MS, UV data and n-octanol/water partition coefficient. Based on the proposed strategy, 36 absorbed compounds and 29 metabolites in plasma and 33 metabolites in urine were detected by a highly sensitive MRM method. Our results indicated that phase II reactions (e.g., methylation, glucuronidation and sulfation) were the main metabolic pathways of gallic acid and flavanones, while phase I reactions (e.g., hydroxylation) were the major metabolic reaction for triterpenoid saponins. The metabolite profile analysis of SNS provided a comprehensive understanding of the in vivo metabolic fates of constituents in SNS. Moreover, the results in this work demonstrated the present strategy based on the combination of chromatographic, spectrophotometric, mass-spectrometric, and software prediction to detect and identify metabolites was effective and reliable. And such a strategy may also be extended to investigate the metabolism of other TCMF.

Advances in metabolite identification

One of the central challenges to metabolomics is metabolite identification. Regardless of whether one uses so-called 'targeted' or 'untargeted' metabolomics, eventually all paths lead to the requirement of identifying (and quantifying) certain key metabolites. Indeed, without metabolite identification, the results of any metabolomic analysis are biologically and chemically uninterpretable. Given the chemical diversity of most metabolomes and the character of most metabolomic data, metabolite identification is intrinsically difficult. Consequently a great deal of effort in metabolomics over the past decade has been focused on making metabolite identification better, faster and cheaper. This review describes some of the newly emerging techniques or technologies in metabolomics that are making metabolite identification easier and more robust. In particular, it focuses on advances in metabolite identification that have occurred over the past 2 to 3 years concerning the technologies, methodologies and software as applied to NMR, MS and separation science. The strengths and limitations of some of these approaches are discussed along with some of the important trends in metabolite identification.

Liquid chromatography-mass spectrometry based global metabolite profiling: a review

Untargeted, global metabolite profiling (often described as metabonomics or metabolomics) represents an expanding research topic and is, potentially, a major pillar for systems biology studies. To obtain holistic metabolic profiles from complex samples, such as biological fluids or tissue extracts, requires powerful, high resolution and information-rich analytical methods and for this spectroscopic technologies are generally used. Mass spectrometry, coupled to liquid chromatography (LC-MS), is increasingly being used for such investigations as a result of the significant advances in both technologies over the past decade. Here we try to critically review the topic of LC-MS-based global metabolic profiling and describe and compare the results offered by different analytical strategies and technologies. This review highlights the current challenges, limitations and opportunities of the current methodology.