High-Throughput and Multiplexed LC/MS/MRM Method for Targeted Metabolomics

DnsID in MyCompoundID for rapid identification of dansylated amine- and phenol-containing metabolites in LC-MS-based metabolomics

High-performance chemical isotope labeling (CIL) liquid chromatography-mass spectrometry (LC-MS) is an enabling technology based on rational design of labeling reagents to target a class of metabolites sharing the same functional group (e.g., all the amine-containing metabolites or the amine submetabolome) to provide concomitant improvements in metabolite separation, detection, and quantification. However, identification of labeled metabolites remains to be an analytical challenge. In this work, we describe a library of labeled standards and a search method for metabolite identification in CIL LC-MS. The current library consists of 273 unique metabolites, mainly amines and phenols that are individually labeled by dansylation (Dns). Some of them produced more than one Dns-derivative (isomers or multiple labeled products), resulting in a total of 315 dansyl compounds in the library. These metabolites cover 42 metabolic pathways, allowing the possibility of probing their changes in metabolomics studies. Each labeled metabolite contains three searchable parameters: molecular ion mass, MS/MS spectrum, and retention time (RT). To overcome RT variations caused by experimental conditions used, we have developed a calibration method to normalize RTs of labeled metabolites using a mixture of RT calibrants. A search program, DnsID, has been developed in www.MyCompoundID.org for automated identification of dansyl labeled metabolites in a sample based on matching one or more of the three parameters with those of the library standards. Using human urine as an example, we illustrate the workflow and analytical performance of this method for metabolite identification. This freely accessible resource is expandable by adding more amine and phenol standards in the future. In addition, the same strategy should be applicable for developing other labeled standards libraries to cover different classes of metabolites for comprehensive metabolomics using CIL LC-MS.

Development and validation of a HILIC-MS/MS multitargeted method for metabolomics applications

The paper reports the development of a multianalyte method and its application in metabolic profiling of biological fluids. The initial aim of the method was the quantification of metabolites existing in cell culture medium used in in-vitro fertilization (IVF) and in other biological fluids related to embryo growth. Since most of these analytes are polar primary metabolites a hydrophilic interaction liquid chromatography system was selected. The analytical system comprised Ultra-HPLC with detection on a triple quadrupole mass spectrometer operating in both positive and negative modes. Mobile phase and gradient elution conditions were studied with the aim to achieve the highest coverage of metabolic space in a single injection namely the largest number of analytes that could be detected and quantified. The developed method provides absolute quantitation of ca. 100 metabolites belonging to key metabolite classes such as sugars, aminoacids, nucleotides, organic acids, and amines. Following validation, the method was applied for the metabolic profiling of hundreds of samples of spent culture medium originating from human IVF procedures and several hundreds of biological samples such as amniotic fluid, human urine and blood serum from pregnant women. The bioanalytical end-point was to provide assistance in the process of embryo transfer and improving IVF success rates but also to provide insight in complications related to the subsequent embryo growth during pregnancy.

Targeted plasma metabolome response to variations in dietary glycemic load in a randomized, controlled, crossover feeding trial in healthy adults

Low versus high glycemic load (GL) diet patterns are inversely associated with obesity and chronic diseases such as cancer and cardiovascular disease. These associations persist beyond the protection afforded by increased fiber alone, representing an important gap in our understanding of the metabolic effects of GL. We conducted a randomized, controlled, crossover feeding trial of two 28-day diet periods of high and low GL. Using LC-MS, targeted metabolomics analysis of 155 metabolites was performed on plasma samples from 19 healthy adults aged 18-45 years. Fourteen metabolites differed significantly between diets (P < 0.05), with kynurenate remaining significant after Bonferroni correction (P < 4 × 10(-4)). Metabolites with the largest difference in abundance were kynurenate and trimethylamine-N-oxide (TMAO), both significantly higher after consumption of the low GL diet. Partial least squares-discriminant analysis showed clear separation between the two diets; however no specific pathway was identified in pathway analyses. We found significant differences in 14 plasma metabolites suggesting a differing metabolic response to low and high GL diets. Kynurenate is associated with reduced inflammation, and may be one mechanism through which protective effects of a low GL diet are manifested and warrants further evaluation. This trial was registered at clinicaltrials.gov as NCT00622661.

Metabolomics and its potential in diagnosis, prognosis and treatment of rheumatic diseases

The main aim of metabolomics is to make a comprehensive study of metabolites, the intermediates of biochemical processes in living organisms. Any pathophysiological mechanism caused by disease will inevitably lead to related changes in the concentrations of specific metabolites. In line with this, metabolomics offers a promising laboratory tool for the analysis of potential diagnostic biomarkers that may be used to assess susceptibility to a disease and to evaluate the prognosis and therapeutic response to treatment. Recent data have shown that metabolomics analysis in rheumatoid arthritis has made possible more efficient diagnosis, discrimination between patients with regard to disease activity, prediction of the response to a particular treatment approach, differentiation between rheumatic disease subtypes and greater understanding of the pathophysiology of this disease. Here we characterize metabolomics as a comprehensive laboratory tool and review its potential in the diagnosis, prognosis and treatment of rheumatic diseases such as rheumatoid arthritis.

Metabolomics techniques for nanotoxicity investigations

Nanomaterials are commonly defined as engineered structures with at least one dimension of 100 nm or less. Investigations of their potential toxicological impact on biological systems and the environment have yet to catch up with the rapid development of nanotechnology and extensive production of nanoparticles. High-throughput methods are necessary to assess the potential toxicity of nanoparticles. The omics techniques are well suited to evaluate toxicity in both in vitro and in vivo systems. Besides genomic, transcriptomic and proteomic profiling, metabolomics holds great promises for globally evaluating and understanding the molecular mechanism of nanoparticle–organism interaction. This manuscript presents a general overview of metabolomics techniques, summarizes its early application in nanotoxicology and finally discusses opportunities and challenges faced in nanotoxicology.

Mechanism study of alachlor biodegradation by Paecilomyces marquandii with proteomic and metabolomic methods

Alachlor is an herbicide that is widely used worldwide to protect plant crops against broadleaf weeds and annual grasses. However, due to its endocrine-disrupting activity, its application had been banned in the European Union. As described in our earlier work, Paecilomyces marquandii is a microscopic fungus capable of alachlor removal by N-acetyl oxidation. Our current work uses proteomics and metabolomics to gain a better understanding of alachlor biodegradation by the microscopic fungus P. marquandii. The data revealed that the addition of alachlor reduced the culture growth and glucose consumption rates. Moreover, the rates of glycolysis and the tricarboxylic acids (TCA) cycle increased during the initial stage of growth, and there was a shift toward the formation of supplementary materials (UDP-glucose/galactose) and reactive oxygen species (ROS) scavengers (ascorbate). Proteomic analysis revealed that the presence of xenobiotics resulted in a strong upregulation of enzymes related to energy, sugar metabolism and ROS production. However, the unique overexpression of cyanide hydratase in alachlor-containing cultures may implicate this enzyme as the key protein involved in the alachlor biodegradation pathway. The characterization of P. marquandii-mediated alachlor removal in terms of cell structure and function provides a deeper insight into the strategies of microorganisms toward xenobiotic biodegradation.

Large-scale qualitative and quantitative characterization of components in Shenfu injection by integrating hydrophilic interaction chromatography, reversed phase liquid chromatography, and tandem mass spectrometry

It is of great importance to clarify in depth the chemical composition, including qualitative and quantitative aspects, of traditional Chinese medicine (TCM) injection that contains a great number of hydrophilic and hydrophobic ingredients to guarantee its safe medication in clinic. Column-switching hydrophilic interaction liquid chromatography-reversed phase liquid chromatography coupled with tandem mass spectrometry (HILIC-RPLC-MS/MS) has been revealed to be advantageous at simultaneous measurement of compounds covering a broad polarity range. Previous studies have profiled the hydrophobic components, mainly aconite alkaloids and ginsenosides, in Shenfu Injection (SFI); however, the hydrophilic substances haven't been taken into account. In the present study, we aim to holistically characterize the hydrophilic constituents and to simultaneously quantitate both hydrophilic and hydrophobic components in SFI. A strategy integrating predefined multiple reaction monitoring, step-wise multiple ion monitoring, and enhanced product ion scans was proposed to universally screen the hydrophilic substances using a hybrid triple quadrupole-linear ion trap mass spectrometer. Structural identification was carried out by comparing with authentic compounds, analyzing MS(2) spectra, and referring to accessible databases (e.g., MassBank, METLIN and HMDB). A total of 157 hydrophilic compounds were detected from SFI, and 154 ones were identified as amino acids, nucleosides, organic acid, carbohydrates, etc. A column-switching HILIC-RPLC-MS/MS system was developed and validated for simultaneously quantitative analysis of 40 primary hydrophilic and hydrophobic ingredients in SFI, including eleven amino acids, nine nucleosides, nine aconite alkaloids, and eleven ginsenosides. Taken together, the findings obtained could provide meaningful information for comprehensively understanding the chemical composition and offer a reliable approach for the quality control of SFI.

Screening, verification, and optimization of biomarkers for early prediction of cardiotoxicity based on metabolomics

Drug-induced cardiotoxicity seriously affects human health and drug development. However, many conventional detection indicators of cardiotoxicity exhibit significant changes only after the occurrence of severe heart injuries. Therefore, we investigated more sensitive and reliable indicators for the evaluation and prediction of cardiotoxicity. We created rat cardiotoxicity models in which the toxicity was caused by doxorubicin (20 mg/kg), isoproterenol (5 mg/kg), and 5-fluorouracil (125 mg/kg). We collected data from rat plasma samples based on metabolomics using ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry. Following multivariate statistical and integration analyses, we selected 39 biomarker ions of cardiotoxicity that predict cardiotoxicity earlier than biochemical analysis and histopathological assessment. Because drugs with different toxicities may cause similar metabolic changes compared with other noncardiotoxic models (hepatotoxic and nephrotoxic models), we obtained 10 highly specific biomarkers of cardiotoxicity. We subsequently used a support vector machine (SVM) to develop a predictive model to verify and optimize the exclusive biomarkers. l-Carnitine, 19-hydroxydeoxycorticosterone, LPC (14:0), and LPC (20:2) exhibited the strongest specificities. The prediction rate of the SVM model is as high as 90.0%. This research provides a better understanding of drug-induced cardiotoxicity in drug safety evaluations and secondary development and demonstrates novel ideas for verification and optimization of biomarkers via metabolomics.

Multiple reaction monitoring-ion pair finder: a systematic approach to transform nontargeted mode to pseudotargeted mode for metabolomics study based on liquid chromatography-mass spectrometry

Pseudotargeted metabolic profiling is a novel strategy combining the advantages of both targeted and untargeted methods. The strategy obtains metabolites and their product ions from quadrupole time-of-flight (Q-TOF) MS by information-dependent acquisition (IDA) and then picks targeted ion pairs and measures them on a triple-quadrupole MS by multiple reaction monitoring (MRM). The picking of ion pairs from thousands of candidates is the most time-consuming step of the pseudotargeted strategy. Herein, a systematic and automated approach and software (MRM-Ion Pair Finder) were developed to acquire characteristic MRM ion pairs by precursor ions alignment, MS(2) spectrum extraction and reduction, characteristic product ion selection, and ion fusion. To test the reliability of the approach, a mixture of 15 metabolite standards was first analyzed; the representative ion pairs were correctly picked out. Then, pooled serum samples were further studied, and the results were confirmed by the manual selection. Finally, a comparison with a commercial peak alignment software was performed, and a good characteristic ion coverage of metabolites was obtained. As a proof of concept, the proposed approach was applied to a metabolomics study of liver cancer; 854 metabolite ion pairs were defined in the positive ion mode from serum. Our approach provides a high throughput method which is reliable to acquire MRM ion pairs for pseudotargeted metabolomics with improved metabolite coverage and facilitate more reliable biomarkers discoveries.

Cancer metabolomics in basic science perspective

As metabolomics investigates metabolic pathways with the focus on metabolites, it is a suitable approach to address the complex metabolic alteration in cancer. In addition, metabolic profiles are affected by environmental and post-natal changes, and therefore, directly measuring many metabolites may provide epigenetically relevant information in cancer. Despite much development in our understanding of cancer metabolism, focus is often directed to signaling or metabolic proteins that modulate the metabolite levels. In this review, we discuss the "metabolite-oriented view" on cancer metabolism. We cover how metabolomics research contributed to our current insights into the basic mechanism of metabolic alterations leading to cancer. Then, we discuss specific metabolites and related enzymatic pathways directly related with tumorigenesis. We particularly pay attention to how metabolites regulate signaling proteins and metabolic enzymes ultimately leading to cancer phenotypes. Finally, we address future prospects and challenges of metabolomics in cancer research.

Challenges of analyzing different classes of metabolites by a single analytical method

Complex biological samples include thousands of metabolites that range widely in both physiochemical properties and concentration. Simultaneously analyzing metabolites with different properties using a single analytical method is very challenging. The analytical process for metabolites comprises multiple steps including sampling, quenching, sample preparation, separation and detection. Each step can have a significant effect on the reliability and precision of ultimate analytic results. The aim of review is a discussion of considerations and challenges for the simultaneous analysis of metabolites using LC– and GC–MS systems. The review discusses available methodology for each analytical step, and presents the limitations and advantages of each method for the large-scale targeted metabolomics analysis of human and animal biological samples.

Applications of Multiple Reaction Monitoring to Clinical Glycomics

Multiple reaction monitoring or MRM is widely acknowledged for its accuracy of quantitation. The applications have mostly been in the analysis of small molecules and proteins, but its utility is expanding. Protein glycosylation was recently identified as a new paradigm in biomarker discovery for health and disease. A number of recent studies have now identified differential glycosylation patterns associated with health and disease states, including aging, pregnancy, rheumatoid arthritis and different types of cancer. While the use of MRM in clinical glycomics is still in its infancy, it can likely play a role in the quantitation of protein glycosylation in the clinical setting. Here, we aim to review the current advances in the nascent application of MRM in the field of glycomics.

High resolution mass spectrometry based techniques at the crossroads of metabolic pathways

The metabolome is the set of small molecular mass compounds found in biological media, and metabolomics, which refers to as the analysis of metabolome in a given biological condition, deals with the large scale detection and quantification of metabolites in biological media. It is a data driven and multidisciplinary approach combining analytical chemistry for data acquisition, and biostatistics, informatics and biochemistry for mining and interpretation of these data. Since the middle of the 2000s, high resolution mass spectrometry is widely used in metabolomics, mainly because the detection and identification of metabolites are improved compared to low resolution instruments. As the field of HRMS is quickly and permanently evolving, the aim of this work is to review its use in different aspects of metabolomics, including data acquisition, metabolite annotation, identification and quantification. At last, we would like to show that, thanks to their versatility, HRMS instruments are the most appropriate to achieve optimal metabolome coverage, at the border of other omics fields such as lipidomics and glycomics.

Colorectal cancer detection using targeted serum metabolic profiling

Colorectal cancer (CRC) is one of the most prevalent and deadly cancers in the world. Despite an expanding knowledge of its molecular pathogenesis during the past two decades, robust biomarkers to enable screening, surveillance, and therapy monitoring of CRC are still lacking. In this study, we present a targeted liquid chromatography-tandem mass spectrometry-based metabolic profiling approach for identifying biomarker candidates that could enable highly sensitive and specific CRC detection using human serum samples. In this targeted approach, 158 metabolites from 25 metabolic pathways of potential significance were monitored in 234 serum samples from three groups of patients (66 CRC patients, 76 polyp patients, and 92 healthy controls). Partial least-squares-discriminant analysis (PLS-DA) models were established, which proved to be powerful for distinguishing CRC patients from both healthy controls and polyp patients. Receiver operating characteristic curves generated based on these PLS-DA models showed high sensitivities (0.96 and 0.89, respectively, for differentiating CRC patients from healthy controls or polyp patients), good specificities (0.80 and 0.88), and excellent areas under the curve (0.93 and 0.95). Monte Carlo cross validation was also applied, demonstrating the robust diagnostic power of this metabolic profiling approach.

Simultaneous quantification of trans-resveratrol and its sulfate and glucuronide metabolites in rat tissues by stable isotope-dilution UPLC-MS/MS analysis

A rapid, sensitive, and selective ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) in the multiple reaction monitoring (MRM) mode has been developed and validated to investigate the distribution of trans-Resveratrol (Resv) and its metabolites in rats following intravenous (IV) administration at 20mg/kg body weight (BW). Resv and Resv metabolites were analyzed in the negative electrospray ionization mode and eluted with retention times of about 0.69-2.22min with a runtime of 7min. Stable deuterium-labeled Resv and its metabolites were used as the internal standards to correct for matrix effects and to allow for accurate quantification of Resv and its metabolites in a complex biological system. The method was validated with respect to linearity, within- and between-day precision, limit of quantification, recovery, and accuracy for all analytes. Upon examination at 0.5, 1, 2, and 4h post-administration, concentrations of Resv and its metabolites were the highest in the kidney, followed by plasma; specifically, the glucuronidated forms were the most abundant. In the liver and the brain, the predominant forms were the sulfated derivatives. In contrast, heart tissue contained the highest concentration of unmodified Resv at 0.5h post IV administration. The combined use of UPLC-MS/MS and isotope-dilution analysis, proved to be accurate and reliable in identifying and quantifying Resv and its various metabolites in biological samples at the nanomolar range. This technology is potentially applicable for other pharmacokinetic studies.

Metabolic profiling of plasma amino acids shows that histidine increases following the consumption of pork

Amino acid (AA) status is determined by factors including nutrition, metabolic rate, and interactions between the metabolism of AA, carbohydrates, and lipids. Analysis of the plasma AA profile, together with markers of glucose and lipid metabolism, will shed light on metabolic regulation. The objectives of this study were to investigate the acute responses to the consumption of meals containing either pork (PM) or chicken (CM), and to identify relationships between plasma AA and markers of glycemic and lipemic control. A secondary aim was to explore AA predictors of plasma zinc concentrations. Ten healthy adults participated in a postprandial study on two separate occasions. In a randomized cross-over design, participants consumed PM or CM. The concentrations of 21 AA, glucose, insulin, triglycerides, nonesterified fatty acids, and zinc were determined over 5 hours postprandially. The meal composition did not influence glucose, insulin, triglyceride, nonesterified fatty acid, or zinc concentrations. Plasma histidine was higher following the consumption of PM (P=0.014), with consistently higher changes observed after 60 minutes (P<0.001). Greater percentage increases were noted at limited time points for valine and leucine + isoleucine in those who consumed CM compared to PM. In linear regression, some AAs emerged as predictors of the metabolic responses, irrespective of the meal that was consumed. The present study demonstrates that a single meal of PM or CM produces a differential profile of AA in the postprandial state. The sustained increase in histidine following the consumption of a PM is consistent with the reported effects of lean pork on cardiometabolic risk factors.

Multiplexed, quantitative, and targeted metabolite profiling by LC-MS/MRM

Targeted metabolomics, which focuses on a subset of known metabolites representative of biologically relevant metabolic pathways, is a valuable tool to discover biomarkers and link disease phenotypes to underlying mechanisms or therapeutic modes of action. A key advantage of targeted metabolomics, compared to discovery metabolomics, is its immediate readiness for extracting biological information derived from known metabolites and quantitative measurements. However, simultaneously analyzing hundreds of endogenous metabolites presents a challenge due to their diverse chemical structures and properties. Here we report a method which combines different chromatographic separation conditions, optimal ionization polarities, and the most sensitive triple-quadrupole MS-based data acquisition mode, multiple reaction monitoring (MRM), to quantitatively profile 205 endogenous metabolites in 10 min.

Multiplexed analysis of cage and cage free chicken egg fatty acids using stable isotope labeling and mass spectrometry

Binary stable isotope labeling couple with LC-ESI-MS has been used as a powerful non-targeted approach for the relative quantification of lipids, amino acids, and many other important metabolite classes. A multiplexed approach using three or more isotopic labeling reagents greatly reduces analytical run-time while maintaining excellent sensitivity and reproducibility. Three isotopic cholamine labeling reagents have been developed to take advantage of the pre-ionized character of cholamine, for ESI, and the ease by which stable isotopes can be incorporated into the cholamine structure. These three cholamine labeling reagents have been used to relatively quantify three fatty acid samples simultaneously. The quantification resulted in the observation of 12 fatty acids that had an average absolute error of 0.9% and an average coefficient of variation of 6.1%. Caged versus cage-free isotope labeling experiments showed that cage-free eggs have an increased level of omega-3 fatty acids as compared to caged eggs. This multiplexed fatty acid analysis provides an inexpensive and expedited tool for broad-based lipid profiling that will further aid discoveries in the mechanisms of fatty acid action in cells.

Enhanced data-independent analysis of lipids using ion mobility-TOFMSE to unravel quantitative and qualitative information in human plasma

RATIONALE

Lipids are involved in various biochemical and signaling pathways, cell structure and function, and the pathophysiology of many diseases. We took advantage of ion mobility spectrometry (IMS) in conjunction with ultra-performance liquid chromatography (UPLC) and high-resolution mass spectrometry to gain quantitative and deeper qualitative structural insight within a single experiment.

METHODS

Human plasma lipid extracts were analyzed using an Acquity UPLC system coupled to a Synapt G2-HDMS mass spectrometer system. The ion mobility gas employed was helium for the helium cell (150 mL/min) and nitrogen (80 mL/min) for the T-wave drift tube. The wave height for the T-wave cell was ramped in a linear fashion between 5-40 V. The mass spectra were acquired in an electrospray positive ionization mode.

RESULTS

We resolved chromatographically co-eluting lipids further by ion mobility tube drift time and then subjected them to low- and high-energy fragmentation without pre-selecting respective precursor species. The fragment ions produced in a high-energy mode were aligned with their precursor ions in a low-energy mode. By aligning intact molecular spectra and fragment spectra for these lipids at a given ion mobility drift time and chromatographic retention time, we were able to obtain much cleaner fragment ion spectra for structural elucidation. For quantitative analysis we obtained a dynamic linear range from 0.002 to 2 µg/mL with and without an additional dimension of IMS.

CONCLUSIONS

The additional dimension of IMS allowed us to perform quantitative and qualitative analysis within a single experiment in a relatively high-throughput manner thus providing deeper structural insights into lipids of biological interest and resulting in an information-rich dataset.

Electron Ionization-Induced Release of Coded Isotopic Reporter Ions in an m/z Zone of Minimal Interference for Quantifiable, Multiplexed GC-MS Analyses

We describe an isotope coding strategy that enables simultaneous GC-MS analysis of multiple samples for substrate identification and quantification. The method relies on direct measurement of isotopic ethyl carbenium ions serving as mass spectral tags in a zone of minimal interference (ZMI) at m/z 31-37. Sample aldehyde and ketone mixtures were reacted with isotopic 2-aminooxyethyl propionates to illustrate the method, which determined the relative abundance of the mixed compounds with an average 95% accuracy. ZMI reporter ion detection also enables chemoselective substrate profiling and absolute quantification, as demonstrated using a biologically derived sample.

Targeted metabolic profiling of hepatocellular carcinoma and hepatitis C using LC-MS/MS

Hepatitis C virus (HCV) infection of the liver is a global health problem and a major risk factor for the development of hepatocellular carcinoma (HCC). Sensitive methods are needed for the improved and earlier detection of HCC, which would provide better therapy options. Metabolic profiling of the high-risk population (HCV patients) and those with HCC provides insights into the process of liver carcinogenesis and possible biomarkers for earlier cancer detection. Seventy-three blood metabolites were quantitatively profiled in HCC (n = 30) and cirrhotic HCV (n = 22) patients using a targeted approach based on LC-MS/MS. Sixteen of 73 targeted metabolites differed significantly (p < 0.05) and their levels varied up to a factor of 3.3 between HCC and HCV. Four of these 16 metabolites (methionine, 5-hydroxymethyl-2'-deoxyuridine, N2,N2-dimethylguanosine, and uric acid) that showed the lowest p values were used to develop and internally validate a classification model using partial least squares discriminant analysis. The model exhibited high classification accuracy for distinguishing the two groups with sensitivity, specificity, and area under the receiver operating characteristic curve of 97%, 95%, and 0.98, respectively. A number of perturbed metabolic pathways, including amino acid, purine, and nucleotide metabolism, were identified based on the 16 biomarker candidates. These results provide a promising methodology to distinguish cirrhotic HCV patients, who are at high risk to develop HCC, from those who have already progressed to HCC. The results also provide insights into the altered metabolism between HCC and HCV.

Biomarker Discovery and Translation in Metabolomics

The multifaceted field of metabolomics has witnessed exponential growth in both methods development and applications. Owing to the urgent need, a significant fraction of research investigations in the field is focused on understanding, diagnosing and preventing human diseases; hence, the field of biomedicine has been the major beneficiary of metabolomics research. A large body of literature now documents the discovery of numerous potential biomarkers and provides greater insights into pathogeneses of numerous human diseases. A sizable number of findings have been tested for translational applications focusing on disease diagnostics ranging from early detection, to therapy prediction and prognosis, monitoring treatment and recurrence detection, as well as the important area of therapeutic target discovery. Current advances in analytical technologies promise quantitation of biomarkers from even small amounts of bio-specimens using non-invasive or minimally invasive approaches, and facilitate high-throughput analysis required for real time applications in clinical settings. Nevertheless, a number of challenges exist that have thus far delayed the translation of a majority of promising biomarker discoveries to the clinic. This article presents advances in the field of metabolomics with emphasis on biomarker discovery and translational efforts, highlighting the current status, challenges and future directions.

Pseudotargeted metabolomics method and its application in serum biomarker discovery for hepatocellular carcinoma based on ultra high-performance liquid chromatography/triple quadrupole mass spectrometry

Untargeted analysis performed using full-scan mass spectrometry (MS) coupled with liquid chromatography (LC) is commonly used in metabolomics. Although they are commonly employed, full-scan MS methods such as quadrupole-time-of-flight (Q-TOF) MS have been restricted by various factors including their limited linear range and complicated data processing. LC coupled with triple quadrupole (QQQ) MS operated in the multiple reaction monitoring (MRM) mode is the gold standard for metabolite quantification; however, only known metabolites are generally quantified, limiting its applications in metabolomic analysis. In this study, a pseudotargeted approach was proposed to perform serum metabolomic analysis using an ultra high-performance liquid chromatography (UHPLC)/QQQ MS system operated in the MRM mode, for which the MRM ion pairs were acquired from the serum samples through untargeted tandem MS using UHPLC/Q-TOF MS. The UHPLC/QQQ MRM MS-based pseudotargeted method displayed better repeatability and wider linear range than the traditional UHPLC/Q-TOF MS-based untargeted metabolomics method, and no complicated peak alignment was required. The developed method was applied to discover serum biomarkers for patients with hepatocellular carcinoma (HCC). Patients with HCC had decreased lysophosphatidylcholine, increased long-chain and decreased medium-chain acylcarnitines, and increased aromatic and decreased branched-chain amino acid levels compared to healthy controls. The novelty of this work is that it provides an approach to acquire MRM ion pairs from real samples, is not limited to metabolite standards, and it provides a foundation to achieve pseudotargeted metabolomic analysis on the widely used LC/QQQ MS platform.

Highly sensitive and selective analysis of widely targeted metabolomics using gas chromatography/triple-quadrupole mass spectrometry

In metabolomics studies, gas chromatography coupled with time-of-flight or quadrupole mass spectrometry has frequently been used for the non-targeted analysis of hydrophilic metabolites. However, because the analytical platform employs the deconvolution method to extract single-metabolite information from co-eluted peaks and background noise, the extracted peak is artificial product depending on the mathematical parameters and is not completely compatible with the pure component obtained by analyzing a standard compound. Moreover, it has insufficient ability for quantitative metabolomics. Therefore, highly sensitive and selective methods capable of pure peak extraction without any complicated mathematical techniques are needed. For this purpose, we have developed a novel analytical method using gas chromatography coupled with triple-quadrupole mass spectrometry (GC-QqQ/MS). We developed a selected reaction monitoring (SRM) method to analyze the trimethylsilyl derivatives of 110 metabolites, using electron ionization. This methodology enables us to utilize two complementary techniques-non-targeted and widely targeted metabolomics in the same sample preparation protocol, which would facilitate the formulation or verification of novel hypotheses in biological sciences. The GC-QqQ/MS analysis can accurately identify a metabolite using multichannel SRM transitions and intensity ratios in the analysis of living organisms. In addition, our methodology offers a wide dynamic range, high sensitivity, and highly reproducible metabolite profiles, which will contribute to the biomarker discoveries and quality evaluations in biology, medicine, and food sciences.

A rough guide to metabolite identification using high resolution liquid chromatography mass spectrometry in metabolomic profiling in metazoans

Compound identification in mass spectrometry based metabolomics can be a problem but sometimes the problem seems to be presented in an over complicated way. The current review focuses on metazoans where the range of metabolites is more restricted than for example in plants. The focus is on liquid chromatography with high resolution mass spectrometry where it is proposed that most of the problems in compound identification relate to structural isomers rather than to isobaric compounds. Thus many of the problems faced relate to separation of isomers, which is usually required even if fragmentation is used to support structural identification. Many papers report the use of MS/MS or MS² as an adjunct to the identification of known metabolites but there a few examples in metabolomics studies of metazoans of complete structure elucidation of novel metabolites or metabolites where no authentic standards are available for comparison.

Detoxification of aldehydes by histidine-containing dipeptides: from chemistry to clinical implications

Aldehydes are generated by oxidized lipids and carbohydrates at increased levels under conditions of metabolic imbalance and oxidative stress during atherosclerosis, myocardial and cerebral ischemia, diabetes, neurodegenerative diseases and trauma. In most tissues, aldehydes are detoxified by oxidoreductases that catalyze the oxidation or the reduction of aldehydes or enzymatic and nonenzymatic conjugation with low molecular weight thiols and amines, such as glutathione and histidine dipeptides. Histidine dipeptides are present in micromolar to millimolar range in the tissues of vertebrates, where they are involved in a variety of physiological functions such as pH buffering, metal chelation, oxidant and aldehyde scavenging. Histidine dipeptides such as carnosine form Michael adducts with lipid-derived unsaturated aldehydes, and react with carbohydrate-derived oxo- and hydroxy-aldehydes forming products of unknown structure. Although these peptides react with electrophilic molecules at lower rate than glutathione, they can protect glutathione from modification by oxidant and they may be important for aldehyde quenching in glutathione-depleted cells or extracellular space where glutathione is scarce. Consistent with in vitro findings, treatment with carnosine has been shown to diminish ischemic injury, improve glucose control, ameliorate the development of complications in animal models of diabetes and obesity, promote wound healing and decrease atherosclerosis. The protective effects of carnosine have been linked to its anti-oxidant properties, its ability to promote glycolysis, detoxify reactive aldehydes and enhance histamine levels. Thus, treatment with carnosine and related histidine dipeptides may be a promising strategy for the prevention and treatment of diseases associated with high carbonyl load.

Use of a multicomponent reaction for chemoselective derivatization of multiple classes of metabolites

We demonstrate that the Ugi reaction enables chemoselective derivatization of biological amines, carboxylic acids, aldehydes, or ketones with a chromophore under one set of reaction conditions, even in the presence of water. Derivatization of neurotransmitters, hormones, disease biomarkers and other metabolites bodes well for systems biology and diagnostic medicine.

Metabolite identification and quantitation in LC-MS/MS-based metabolomics

Metabolomics aims at detection and quantitation of all metabolites in biological samples. The presence of metabolites with a wide variety of physicochemical properties and different levels of abundance challenges existing analytical platforms used for identification and quantitation of metabolites. Significant efforts have been made to improve analytical and computational methods for metabolomics studies.This review focuses on the use of liquid chromatography with tandem mass spectrometry (LC-MS/MS) for quantitative and qualitative metabolomics studies. It illustrates recent developments in computational methods for metabolite identification, including ion annotation, spectral interpretation and spectral matching. We also review selected reaction monitoring and high-resolution MS for metabolite quantitation. We discuss current challenges in metabolite identification and quantitation as well as potential solutions.

Imitation of drug metabolism in human liver and cytotoxicity assay using a microfluidic device coupled to mass spectrometric detection

In this work, we developed a microfluidic device for the imitation of drug metabolism in human liver and its cytotoxicity on cells. The integrated microfluidic device consists of three sections: (1) bioreactors containing poly(ethylene) glycol (PEG) hydrogel encapsulated human liver microsomes (HLMs); (2) cell culture chambers for cytotoxicity assay; and (3) integrated micro solid-phase extraction (SPE) columns to desalt and concentrate the products of enzymatic reaction. To verify the feasibility of the integrated microchip, we studied uridine 5'-diphosphate-glucuronosyltransferase (UGT) metabolism of acetaminophen (AP) and the cytotoxicity of products on HepG2 cells. The products of the reaction in one region of the device were injected into the cell culture chamber for cytotoxicity assay, while those in another region were directly detected online with an electrospray ionization quadrupole time-of-flight mass spectrometer (ESI-Q-TOF MS) after micro-SPE pre-treatment. Semiquantitative analysis achieved in the experiments could be related to the drug-induced HepG2 cell cytotoxicity. Total analysis time for one product was about 30 min and only less than 4 μg HLM protein was required for one reaction region. The results demonstrated that the established platform could be used to imitate drug metabolism occurring in the human liver, thereby replacing animal experiments in the near future. In addition, the integrated microchip will be a useful tool for drug metabolism studies and cytotoxicity assays, which are pivotal in drug development.

Multiplexed quantification of 63 proteins in human urine by multiple reaction monitoring-based mass spectrometry for discovery of potential bladder cancer biomarkers

Three common urological diseases are bladder cancer, urinary tract infection, and hematuria. Seventeen bladder cancer biomarkers were previously discovered using iTRAQ - these findings were verified by MRM-MS in this current study. Urine samples from 156 patients with hernia (n=57, control), bladder cancer (n=76), or urinary tract infection/hematuria (n=23) were collected and subjected to multiplexed LC-MRM/MS to determine the concentrations of 63 proteins that are normally considered to be plasma proteins, but which include proteins found in our earlier iTRAQ study. Sixty-five stable isotope-labeled standard proteotypic peptides were used as internal standards for 63 targeted proteins. Twelve proteins showed higher concentrations in the bladder cancer group than in the hernia and the urinary tract infection/hematuria groups, and thus represent potential urinary biomarkers for detection of bladder cancer. Prothrombin had the highest AUC (0.796), with 71.1% sensitivity and 75.0% specificity for differentiating bladder cancer (n=76) from non-cancerous (n=80) patients. The multiplexed MRM-MS data was used to generate a six-peptide marker panel. This six-peptide panel (afamin, adiponectin, complement C4 gamma chain, apolipoprotein A-II precursor, ceruloplasmin, and prothrombin) can discriminate bladder cancer subjects from non-cancerous subjects with an AUC of 0.814, with a 76.3% positive predictive value, and a 77.5% negative predictive value. This article is part of a Special Section entitled: Understanding genome regulation and genetic diversity by mass spectrometry.

A personalized life: biomarker monitoring from cradle to grave

Considering the holy grail of future medical treatment being personalized medicines, biomarker research will become more and more the focus for attention not only to develop new medical treatment regimes, based on changes in biomarker patterns, but also for nutritional advice to guarantee a lifelong optimized health condition. The current review gives an outline of how personalized medicine can become established for actual medical treatment using new biomarker concepts. Starting from the development of biomarker research using mainly immunological techniques, the review gives an overview about biomarkers of prediction evolved and focuses on new methodology for the identification of biomarkers using hyphenated analytical techniques like metabolomics and lipidomics. The actual use of multivariate statistical methods in combination with metabolomics and lipidomics is discussed not only for medical treatment but also for precautionary risk identification in human biomonitoring studies.

Metabolomic investigation of cholestasis in a rat model using ultra-performance liquid chromatography/tandem mass spectrometry

Metabolomics follows the changes in concentrations of endogenous metabolites, which may reflect various disease states as well as systemic responses to environmental, therapeutic, or genetic interventions. In this study, we applied metabolomic approaches to monitor dynamic changes in plasma and urine metabolites, and compared these metabolite profiles in Eisai hyperbilirubinemic rats (EHBR, an animal model of cholestasis) with those in the parent strain of EHBR - Sprague-Dawley (SD) rats - in order to characterize cholestasis pathophysiologically. Ultra-performance liquid chromatography/tandem mass spectrometry-based analytical methods were used to assay metabolite levels. More than 250 metabolites were detected in both plasma and urine, and metabolite profiles of EHBR differed from those of SD rats. The levels of antioxidative and cytoprotective metabolites, taurine and hypotaurine, were markedly increased in urine of EHBR. The levels of many bile acids were also elevated in plasma and urine of EHBR, but the extent of elevation depended on the particular bile acid. The levels of cytoprotective ursodeoxycholic acid and its conjugates were markedly elevated, while that of cytotoxic chenodeoxycholic acid remained unchanged, suggesting the balance of bile acids had shifted resulting in decreased toxicity. In EHBR, reduced biliary excretion leads to increased systemic exposure to harmful compounds including some endogenous metabolites. Our metabolomic data suggest that mechanisms exist in EHBR that compensate for cholestasis-related damage.

Polyomic profiling reveals significant hepatic metabolic alterations in glucagon-receptor (GCGR) knockout mice: implications on anti-glucagon therapies for diabetes

Background

Glucagon is an important hormone in the regulation of glucose homeostasis, particularly in the maintenance of euglycemia and prevention of hypoglycemia. In type 2 Diabetes Mellitus (T2DM), glucagon levels are elevated in both the fasted and postprandial states, which contributes to inappropriate hyperglycemia through excessive hepatic glucose production. Efforts to discover and evaluate glucagon receptor antagonists for the treatment of T2DM have been ongoing for approximately two decades, with the challenge being to identify an agent with appropriate pharmaceutical properties and efficacy relative to potential side effects. We sought to determine the hepatic & systemic consequence of full glucagon receptor antagonism through the study of the glucagon receptor knock-out mouse (Gcgr^-/-) compared to wild-type littermates.

Results

Liver transcriptomics was performed using Affymetric expression array profiling, and liver proteomics was performed by iTRAQ global protein analysis. To complement the transcriptomic and proteomic analyses, we also conducted metabolite profiling (~200 analytes) using mass spectrometry in plasma. Overall, there was excellent concordance (R = 0.88) for changes associated with receptor knock-out between the transcript and protein analysis. Pathway analysis tools were used to map the metabolic processes in liver altered by glucagon receptor ablation, the most notable being significant down-regulation of gluconeogenesis, amino acid catabolism, and fatty acid oxidation processes, with significant up-regulation of glycolysis, fatty acid synthesis, and cholesterol biosynthetic processes. These changes at the level of the liver were manifested through an altered plasma metabolite profile in the receptor knock-out mice, e.g. decreased glucose and glucose-derived metabolites, and increased amino acids, cholesterol, and bile acid levels.

Conclusions

In sum, the results of this study suggest that the complete ablation of hepatic glucagon receptor function results in major metabolic alterations in the liver, which, while promoting improved glycemic control, may be associated with adverse lipid changes.

Metabolomics reveals target and off-target toxicities of a model organophosphate pesticide to roach (Rutilus rutilus): implications for biomonitoring

The ability of targeted and nontargeted metabolomics to discover chronic ecotoxicological effects is largely unexplored. Fenitrothion, an organophosphate pesticide, is categorized as a "red list" pollutant, being particularly hazardous to aquatic life. It acts primarily as a cholinesterase inhibitor, but evidence suggests it can also act as an androgen receptor antagonist. Whole-organism fenitrothion-induced toxicity is well-established, but information regarding target and off-target molecular toxicities is limited. Here we study the molecular responses of male roach ( Rutilus rutilus ) exposed to fenitrothion, including environmentally realistic concentrations, for 28 days. Acetylcholine was assessed in brain; steroid metabolism was measured in testes and plasma; and NMR and mass spectrometry-based metabolomics were conducted on testes and liver to discover off-target toxicity. O-demethylation was confirmed as a major route of pesticide degradation. Fenitrothion significantly depleted acetylcholine, confirming its primary mode of action, and 11-ketotestosterone in plasma and cortisone in testes, showing disruption of steroid metabolism. Metabolomics revealed significant perturbations to the hepatic phosphagen system and previously undocumented effects on phenylalanine metabolism in liver and testes. On the basis of several unexpected molecular responses that were opposite to the anticipated acute toxicity, we propose that chronic pesticide exposure induces an adapting phenotype in roach, which may have considerable implications for interpreting molecular biomarker responses in field-sampled fish.

LC-MS based serum metabonomic analysis for renal cell carcinoma diagnosis, staging, and biomarker discovery

A LC-MS based method, which utilizes both reversed-performance (RP) chromatography and hydrophilic interaction chromatography (HILIC) separations, has been carried out in conjunction with multivariate data analysis to discriminate the global serum profiles of renal cell carcinoma (RCC) patients and healthy controls. The HILIC was found necessary for a comprehensive serum metabonomic profiling as well as RP separation. The feasibility of using serum metabonomics for the diagnosis and staging of RCC has been evaluated. One-hundred percent sensitivity in detection has been achieved, and a satisfactory clustering between the early stage and advanced-stage patients is observed. The results suggest that the combination of LC-MS analysis with multivariate statistical analysis can be used for RCC diagnosis and has potential in the staging of RCC. The MS/MS experiments have been carried out to identify the biomarker patterns that made great contribution to the discrimination. As a result, 30 potential biomarkers for RCC are identified. It is possible that the current biomarker patterns are not unique to RCC but just the result of any malignancy disease. To further elucidate the pathophysiology of RCC, related metabolic pathways have been studied. RCC is found to be closely related to disturbed phospholipid catabolism, sphingolipid metabolism, phenylalanine metabolism, tryptophan metabolism, fatty acid beta-oxidation, cholesterol metabolism, and arachidonic acid metabolism.

Advances in mass spectrometry applied to pharmaceutical metabolomics

Metabolomics, also referred to in the literature as metabonomics, is a relatively new systems biology tool for drug discovery and development and is increasingly being used to obtain a detailed picture of a drug's effect on the body. Metabolomics is the qualitative assessment and relative or absolute quantitative measurement of the endogenous metabolome, defined as the complement of all native small molecules (metabolites less than 1,500 Da). A metabolomics study frequently involves the comparative analysis of sample sets from a normal state and a perturbed state, where the perturbation can be of any nature, such as genetic knockout, administration of a drug, or change in diet or lifestyle. Advances in mass spectrometry (MS) technologies including direct introduction or in-line chromatographic separation modes, ionization techniques, mass analyzers, and detection methods have provided powerful tools to assess the molecular changes in the metabolome. This review focuses on advances in MS pertaining to the analytical data generation for the main metabolomics methods, namely, fingerprinting, nontargeted, and targeted approaches, as they are applied to pharmaceutical drug discovery and development.

Discriminating between different acute chemical toxicities via changes in the daphnid metabolome

Currently, there is widespread interest in exploiting "omics" approaches to screen the toxicity of chemicals, potentially enabling their rapid categorization into classes of defined mode of action (MOA). Direct infusion Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) metabolomics provides a sensitive and nontargeted analysis of potentially a thousand endogenous metabolites. Our previous work has shown that mass spectra can be recorded from whole-organism homogenate or hemolymph of single adult Daphnia magna. Here we develop multivariate models and discover perturbations to specific metabolic pathways that can discriminate between the acute toxicities of four chemicals to D. magna using FT-ICR MS metabolomics. We focus on model toxicants (cadmium, fenvalerate, dinitrophenol, and propranolol) with different MOAs. First, we confirmed that a toxicant-induced metabolic effect could be determined for each chemical in both the hemolymph and the whole-organism metabolome, with between 9 and 660 mass spectral peaks changing intensities significantly, dependent upon toxicant and sample type. Subsequently, supervised multivariate models were built that discriminated significantly all four acute metabolic toxicities, yielding mean classification error rates (across all classes) of 3.9 and 6.9% for whole-organism homogenates and hemolymph, respectively. Following extensive peak annotation, we discovered toxicant-specific perturbations to putatively identified metabolic pathways, including propranolol-induced disruption of fatty acid metabolism and eicosanoid biosynthesis and fenvalerate-induced disruption of amino sugar metabolism. We conclude that the metabolic profiles of whole-daphnid homogenates are more discriminatory for toxicant action than hemolymph. Furthermore, our findings highlight the capability of metabolomics to discover early-event metabolic responses that can discriminate between the acute toxicities of chemicals.