Untargeted Tumor Metabolomics with Liquid Chromatography–Surface-Enhanced Raman Spectroscopy

Metabolomics is a powerful systems biology approach that monitors changes in biomolecule concentrations to diagnose and monitor health and disease. However, leading metabolomics technologies, such as NMR and mass spectrometry (MS), access only a small portion of the metabolome. Now an approach is presented that uses the high sensitivity and chemical specificity of surface-enhanced Raman scattering (SERS) for online detection of metabolites from tumor lysates following liquid chromatography (LC). The results demonstrate that this LC-SERS approach has metabolite detection capabilities comparable to the state-of-art LC-MS but suggest a selectivity for the detection of a different subset of metabolites. Analysis of replicate LC-SERS experiments exhibit reproducible metabolite patterns that can be converted into barcodes, which can differentiate different tumor models. Our work demonstrates the potential of LC-SERS technology for metabolomics-based diagnosis and treatment of cancer.     

Mass defect filter technique and its applications to drug metabolite identification by high‐resolution mass spectrometry

Identification of drug metabolites by liquid chromatography/mass spectrometry (LC/MS) involves metabolite detection in biological matrixes and structural characterization based on product ion spectra. Traditionally, metabolite detection is accomplished primarily on the basis of predicted molecular masses or fragmentation patterns of metabolites using triple‐quadrupole and ion trap mass spectrometers. Recently, a novel mass defect filter (MDF) technique has been developed, which enables high‐resolution mass spectrometers to be utilized for detecting both predicted and unexpected drug metabolites based on narrow, well‐defined mass defect ranges for these metabolites. This is a new approach that is completely different from, but complementary to, traditional molecular mass‐ or MS/MS fragmentation‐based LC/MS approaches. This article reviews the mass defect patterns of various classes of drug metabolites and the basic principles of the MDF approach. Examples are given on the applications of the MDF technique to the detection of stable and chemically reactive metabolites in vitro and in vivo. Advantages, limitations, and future applications are also discussed on MDF and its combinations with other data mining techniques for the detection and identification of drug metabolites. Copyright © 2009 John Wiley & Sons, Ltd.     

Quantification of homocysteine‐related metabolites and the role of betaine–homocysteine S‐methyltransferase in HepG2 cells

We optimized and validated a rapid and sensitive liquid chromatography–tandem mass spectrometry (LC‐MS/MS) method for the quantification of six metabolites of homocysteine metabolism: homocysteine, methionine, cysteine, S‐adenosylmethionine, S‐adenosylhomocysteine and betaine. The detection limits for these metabolites were in the nanomolar range, and the intra‐ and inter‐day precisions were lower than 20% of the relative standard deviations. The method was specifically designed for the determination of the intracellular concentrations of the metabolites in cultured cells. To study the role of betaine–homocysteine S‐methyltransferase (BHMT), HepG2 cells and HepG2 cells that were stably transfected with BHMT (^BHMTHepG2) were treated with homocysteine or with a specific inhibitor of BHMT, and metabolite levels were subsequently measured. Severely compromised methyl group metabolism in the HepG2 cells, which is typical of cancer‐derived cells, prevented clear evaluation of the changes caused by the external manipulations of homocysteine metabolism. However, the ease of handling these cells and the almost unlimited source of experimental material supplied by cells in permanent culture allowed us to develop a reliable methodology. The precautions concerning intracellular metabolite determinations using LC‐MS/MS in cultured cells that are expressed in this work will have global validity for future metabolomics studies. Copyright © 2012 John Wiley & Sons, Ltd.     

Phosphonium labeling for increasing metabolomic coverage of neutral lipids using electrospray ionization mass spectrometry

Mass spectrometry has become an indispensable tool for the global study of metabolites (metabolomics), primarily using electrospray ionization mass spectrometry (ESI‐MS). However, many important classes of molecules such as neutral lipids do not ionize well by ESI and go undetected. Chemical derivatization of metabolites can enhance ionization for increased sensitivity and metabolomic coverage. Here we describe the use of tris(2,4,6,‐trimethoxyphenyl)phosphonium acetic acid (TMPP‐AA) to improve liquid chromatography (LC)/ESI‐MS detection of hydroxylated metabolites (i.e. lipids) from serum extracts. Cholesterol which is not normally detected from serum using ESI is observed with attomole sensitivity. This approach was applied to identify four endogenous lipids (hexadecanoyl‐sn‐glycerol, dihydrotachysterol, octadecanol, and alpha‐tocopherol) from human serum. Overall, this approach extends the types of metabolites which can be detected using standard ESI‐MS instrumentation and demonstrates the potential for targeted metabolomics analysis. Published in 2009 by John Wiley & Sons, Ltd.     

Metabolic profile of glyburide in human liver microsomes using LC‐DAD‐Q‐TRAP‐MS/MS

The sulfonylurea urea drug glyburide (glibenclamide) is widely used for the treatment of diabetes milletus and gestational diabetes. In previous studies monohydroxylated metabolites were identified and characterized for glyburide in different species, but the metabolite owing to the loss of cyclohexyl ring was identified only in mouse. Glyburide upon incubation with hepatic microsomes resulted in 10 metabolites for human. The current study identifies new metabolites of glyburide along with the hydroxylated metabolites that were reported earlier. The newly identified drug metabolites are dihydroxylated metabolites, a metabolite owing to the loss of cyclohexyl ring and one owing to hydroxylation with dehydrogenation. Among the 10 identified metabolites, there were six monohydroxylated metabolites, one dihydroxylated metabolite, two metabolites owing to hydroxylation and dehydrogenation, and one metabolite owing to the loss of cyclohexyl ring. New metabolites of glyburide were identified and characterized using liquid chromatography–diode array detector–quadruple‐ion trap–mass spectrometry/mass spectrometry (LC‐DAD‐Q‐TRAP‐MS/MS). An enhanced mass scan–enhanced product ion scan with information‐dependent acquisition mode in a Q‐TRAP‐MS/MS system was used to characterize the metabolites. Liquid chromatography with diode array detection was used as a complimentary technique to confirm and identify the metabolites. Metabolites formed in higher amounts were detected in both diode array detection and mass spectrometry detection. Copyright © 2012 John Wiley & Sons, Ltd.     

An introduction to hybrid ion trap/time‐of‐flight mass spectrometry coupled with liquid chromatography applied to drug metabolism studies

Metabolism studies play an important role at various stages of drug discovery and development. Liquid chromatography combined with mass spectrometry (LC/MS) has become a most powerful and widely used analytical tool for identifying drug metabolites. The suitability of different types of mass spectrometers for metabolite profiling differs widely, and therefore, the data quality and reliability of the results also depend on which instrumentation is used. As one of the latest LC/MS instrumentation designs, hybrid ion trap/time‐of‐flight MS coupled with LC (LC‐IT‐TOF‐MS) has successfully integrated ease of operation, compatibility with LC flow rates and data‐dependent MSⁿ with high mass accuracy and mass resolving power. The MSⁿ and accurate mass capabilities are routinely utilized to rapidly confirm the identification of expected metabolites or to elucidate the structures of uncommon or unexpected metabolites. These features make the LC‐IT‐TOF‐MS a very powerful analytical tool for metabolite identification. This paper begins with a brief introduction to some basic principles and main properties of a hybrid IT‐TOF instrument. Then, a general workflow for metabolite profiling using LC‐IT‐TOF‐MS, starting from sample collection and preparation to final identification of the metabolite structures, is discussed in detail. The data extraction and mining techniques to find and confirm metabolites are discussed and illustrated with some examples. This paper is directed to readers with no prior experience with LC‐IT‐TOF‐MS and will provide a broad understanding of the development and utility of this instrument for drug metabolism studies. Copyright © 2012 John Wiley & Sons, Ltd.     

Metabolomics analysis reveals variation in Schisandra chinensis metabolites from different origins

Wu Wei Zi (Schisandra chinensis), an important herbal medicine, is mainly distributed in the northeast of China. Its phytochemical compositions, which depend on geographical origin, climatic conditions and cultural practices, may vary largely among Wu Wei Zi from different areas. In this study, we applied a comprehensive metabolite profiling approach using GC–TOF‐MS, ultra‐performance LC (UPLC) quadrupole TOF (QTOF) MS and inductively coupled plasma MS to systematically investigate the metabolite variations of S. chinensis from four different areas including Heilongjiang, Liaoning, Jilin, and Shanxi of China. A total of 65 primary metabolites, 35 secondary metabolites and 64 inorganic elements were identified. Several primary metabolites, including shikimic acid and tricarboxylic acid cycle intermediates, were abundant in those located in Heilongjiang, Jilin, and Liaoning. Besides, bioactive lignans are also highly abundant in those from northeastern China than those from northwestern China. Inorganic elements varied significantly among the different locations. Our results suggested that the metabolite profiling approach using GC–TOF‐MS, ultra‐performance LC quadrupole TOF MS, and inductively coupled plasma MS is a robust and reliable method that can be effectively used to explore subtle variations among plants from different geographical locations.     

Metabolomics study of cured tobacco using liquid chromatography with mass spectrometry: Method development and its application in investigating the chemical differences of tobacco from three growing regions

Cured tobacco is an important plant material. Component studies are a big challenge for its significantly diverse chemical properties and vastly different concentrations. In this work, liquid chromatography with quadrupole time‐of‐flight mass spectrometry was used to perform a metabolomics study of cured tobacco owing to its efficient separation and detection of semipolar metabolites. A solvent of methanol/water (8:2, v/v) and 30 min of ultrasound time were found to be optimal to perform extraction. 95, 92, and 93% of metabolite features had within 20% of coefficient of variation for repeatability, intraday and interday precision analysis, respectively, indicating a good stability of the method developed. 113 metabolites were identified in cured tobacco based on accurate mass, retention time, and MS/MS fragments. The developed method was applied to a metabolomics study of cured tobacco from three growing regions. Forty three metabolites were found to be contributed to the classification. It is shown that the developed method can be applied to metabolomics analysis of plant materials.     

Feasibility of electroextraction as versatile sample preconcentration for fast and sensitive analysis of urine metabolites,demonstrated on acylcarnitines

In this work, we demonstrate the applicability of electroextraction (EE) to urine metabolites. To investigate which urine metabolite classes are susceptible to EE, off‐line EE experiments were carried out with a prototype device, in which urine metabolites were electroextracted from ethyl acetate into water. The obtained extracts were examined with direct infusion MS and the results demonstrated that several compound classes could be extracted, amongst which amino acids and acylcarnitines. Acylcarnitines were selected for evaluation of the performance of EE. For this, the EE setup was adapted to capillary EE (cEE) to be able to analyze large urine sample series, and it was coupled online to LC‐MS. cEE‐LC‐MS of acylcarnitines was optimized and characterized. The recovery, linearity, repeatability, and detection limit of the cEE‐LC‐MS method was good to excellent. To demonstrate the versatility of EE for sample preparation in analytical procedures, extracts were injected into a CZE‐MS system, resulting in detection of the acylcarnitines along with more than 100 presumed metabolite peaks. The results presented here indicate that EE can be used as a fast sample preconcentration technique of low abundant urine metabolites, in combination with both LC and CZE.     

Rapid screening and characterization of drug metabolites using multiple ion monitoring dependent product ion scan and postacquisition data mining on a hybrid triple quadrupole‐linear ion trap mass spectrometer

Multiple ion monitoring (MIM)‐dependent acquisition with a triple quadrupole‐linear ion trap mass spectrometer (Q‐trap) was previously developed for drug metabolite profiling. In the analysis, multiple predicted metabolite ions are monitored in both Q1 and Q3 regardless of their fragmentations. The collision energy in Q2 is set to a low value to minimize fragmentation. Once an expected metabolite is detected by MIM, enhanced product ion (EPI) spectral acquisition of the metabolite is triggered. To analyze in vitro metabolites, MIM‐EPI retains the sensitivity and selectivity similar to that of multiple reaction monitoring (MRM)‐EPI in the analysis of in vitro metabolites. Here we present an improved approach utilizing MIM‐EPI for data acquisition and multiple data mining techniques for detection of metabolite ions and recovery of their MS/MS spectra. The postacquisition data processing tools included extracted ion chromatographic analysis, product ion filtering and neutral loss filtering. The effectiveness of this approach was evaluated by analyzing oxidative metabolites of indinavir and glutathione (GSH) conjugates of clozapine and 4‐ethylphenol in liver microsome incubations. Results showed that the MIM‐EPI‐based data mining approach allowed for comprehensive detection of metabolites based on predicted protonated molecules, product ions or neutral losses without predetermination of the parent drug MS/MS spectra. Additionally, it enabled metabolite detection and MS/MS acquisition in a single injection. This approach is potentially useful in high‐throughout screening of metabolic soft spots and reactive metabolites at the drug discovery stage. Copyright © 2009 John Wiley & Sons, Ltd.     

Metabolomics profiling of extracellular metabolites in recombinant Chinese Hamster Ovary fed‐batch culture

A metabolomics‐based approach was used to time profile extracellular metabolites in duplicate fed‐batch bioreactor cultures of recombinant Chinese Hamster Ovary (CHO) cells producing monoclonal IgG antibody. Culture medium was collected and analysed using a high‐performance liquid chromatography (HPLC) system in tandem with an LTQ‐Orbitrap mass spectrometer. An in‐house software was developed to pre‐process the LC/MS data in terms of filtering and peak detection. This was followed by principal component analysis (PCA) to assess variance amongst the samples, and hierarchical clustering to categorize mass peaks by their time profiles. Finally, LC/MS² experiments using the LTQ‐Orbitrap (where standard was available) and SYNAPT? HDMS (where standard was unavailable) were performed to confirm the identities of the metabolites. Two groups of identified metabolites were of particular interest; the first consisted of metabolites that began to accumulate when the culture entered stationary phase. The majority of them were amino acid derivatives and they were likely to be derived from the amino acids in the feed media. Examples included acetylphenylalanine and dimethylarginine which are known to be detrimental to cell growth. The second group of metabolites showed a downward trend as the culture progressed. Two of them were medium components – tryptophan and choline, and these became depleted midway into the culture despite the addition of feed media. The findings demonstrated the potential of utilizing metabolomics to guide medium design for fed‐batch culture to potentially improve cell growth and product titer. Copyright © 2009 John Wiley & Sons, Ltd.     

Urinary metabolomics analysis reveals the effect of volatile oil from Angelica sinensis on LPS‐induced inflammation rats

Lipopolysaccharide (LPS)‐induced inflammation occurs commonly and volatile oil from Angelica sinensis (VOAS) can be used as an anti‐inflammatory agent. The molecular mechanisms that allow the anti‐inflammatory factors to be expressed are still unknown. In this paper, we applied gas chromatography–mass spectrometry (GC–MS) and high‐performance liquid chromatography–time‐of‐flight mass spectrometry (LC‐Q/TOF–MS) based on a metabolomics platform coupled with a network approach to analyze urine samples in three groups of rats: one with LPS‐induced inflammation (MI); one with intervention with VOAS; and normal controls (NC). Our study found definite metabolic footprints of inflammation and showed that all three groups of rats, MI, intervention with VOAS and NC have distinct metabolic profiles in urine. The concentrations of 48 metabolites differed significantly among the three groups. The metabolites in urine were screened by the GC–MS and LC‐Q/TOF–MS methods. The significantly changed metabolites (p < 0.05, variable importance in projection > 1.5) between MI, NC and VOAS were included in the metabolic networks. Finally, hub metabolites were screened, including glycine, arachidonic acid, l ‐glutamate, pyruvate and succinate, which have high values of degree (k). the Results suggest that disorders of glycine, arachidonic acid, l ‐glutamate, pyruvate and succinate metabolism might play an important part in the predisposition and development of LPS‐induced inflammation. By applying metabolomics with network methods, the mechanisms of diseases are clearly elucidated.     

MASSyPup — an ‘Out of the Box’ solution for the analysis of mass spectrometry data

Mass spectrometry has evolved to a key technology in the areas of metabolomics and proteomics. Centralized facilities generate vast amount of data, which frequently need to be processed off‐site. Therefore, the distribution of data and software, as well as the training of personnel in the analysis of mass spectrometry data, becomes increasingly important. Thus, we created a comprehensive collection of mass spectrometry software which can be run directly from different media such as DVD or USB without local installation. MASSyPup is based on a Linux Live distribution and was complemented with programs for conversion, visualization and analysis of mass spectrometry (MS) data. A special emphasis was put on protein analysis and proteomics, encompassing the measurement of complete proteins, the identification of proteins based on Peptide Mass Fingerprints (PMF) or LC‐MS/MS data, and de novo sequencing. Another focus was directed to the study of metabolites and metabolomics, covering the detection, identification and quantification of compounds, as well as subsequent statistical analyses. Additionally, we added software for Mass Spectrometry Imaging (MSI), including hardware support for self‐made MSI devices. MASSyPup represents a ‘ready to work’ system for teaching or MS data analysis, but also represents an ideal platform for the distribution of MS data and the development of related software. The current Live DVD version can be downloaded free of charge from http://www.bioprocess.org/massypup . Copyright © 2014 John Wiley & Sons, Ltd.     

In silico methods for predicting metabolism and mass fragmentation applied to quetiapine in liquid chromatography/time‐of‐flight mass spectrometry urine drug screening

Current in silico tools were evaluated for their ability to predict metabolism and mass spectral fragmentation in the context of analytical toxicology practice. A metabolite prediction program (Lhasa Meteor), a metabolite detection program (Bruker MetaboliteDetect), and a fragmentation prediction program (ACD/MS Fragmenter) were used to assign phase I metabolites of the antipsychotic drug quetiapine in the liquid chromatography/time‐of‐flight mass spectrometry (LC/TOFMS) accurate mass data from ten autopsy urine samples. In the literature, the main metabolic routes of quetiapine have been reported to be sulfoxidation, oxidation to the corresponding carboxylic acid, N‐ and O‐dealkylation and hydroxylation. Of the 14 metabolites predicted by Meteor, eight were detected by LC/TOFMS in the urine samples with use of MetaboliteDetect software and manual inspection. An additional five hydroxy derivatives were detected, but not predicted by Meteor. The fragment structures provided by ACD/MS Fragmenter software confirmed the identification of the metabolites. Mean mass accuracy and isotopic pattern match (SigmaFit) values for the fragments were 2.40 ppm (0.62 mDa) and 0.010, respectively. ACD/MS Fragmenter, in particular, allowed metabolites with identical molecular formulae to be differentiated without a need to access the respective reference standards or reference spectra. This was well exemplified with the hydroxy/sulfoxy metabolites of quetiapine and their N‐ and O‐dealkylated forms. The procedure resulted in assigning 13 quetiapine metabolites in urine. The present approach is instrumental in developing an extensive database containing exact monoisotopic masses and verified retention times of drugs and their urinary metabolites for LC/TOFMS drug screening. Copyright © 2009 John Wiley & Sons, Ltd.     

Rapid detection and characterization of reactive drug metabolites in vitro using several isotope‐labeled trapping agents and ultra‐performance liquid chromatography/time‐of‐flight mass spectrometry

Reactive metabolites are believed to be one of the main reasons for unexpected drug‐induced toxicity issues, by forming covalent adducts with cell proteins or DNA. Due to their high reactivity and short lifespan they are not directly detected by traditional analytical methods, but are most traditionally analyzed by liquid chromatography/tandem mass spectrometry (LC/MS/MS) after chemical trapping with nucleophilic agents such as glutathione. Here, a simple but very efficient assay was built up for screening reactive drug metabolites, utilizing stable isotope labeled glutathione, potassium cyanide and semicarbazide as trapping agents and highly sensitive ultra‐performance liquid chromatography/time‐of‐flight mass spectrometry (UPLC/TOFMS) as an analytical tool. A group of twelve structurally different compounds was used as a test set, and a large number of trapped metabolites were detected for most of them, including many conjugates not reported previously. Glutathione‐trapped metabolites were detected for nine of the twelve test compounds, whereas cyanide‐trapped metabolites were found for eight and semicarbazide‐trapped for three test compounds. The high mass accuracy of TOFMS provided unambiguous identification of change in molecular formula by formation of a reactive metabolite. In addition, use of a mass defect filter was found to be a usable tool when mining the trapped conjugates from the acquired data. The approach was shown to provide superior detection sensitivity in comparison to traditional methods based on neutral loss or precursor ion scanning with a triple quadrupole mass spectrometer, and clearly more efficient detection and characterization of reactive drug metabolites with a simpler test setup. Copyright © 2009 John Wiley & Sons, Ltd.     

Liquid chromatography/mass spectrometry‐based plasma metabolic profiling study of escitalopram in subjects with major depressive disorder

Liquid chromatography‐mass spectrometry (LC‐MS) method revealed the plasma metabolite profiles in major depressive disorder patients treated with escitalopram (ECTP) (n = 7). Depression severity was assessed according to the 17‐item Hamilton Depression Rating Scale. Metabolic profiles were derived from major depressive disorder subject blood samples collected after ECTP treatment. Blood plasma was separated and processed in order to effectively extract metabolites, which were then analyzed using LC‐MS. We identified 19 metabolites and elucidated their structures using LC‐tandem MS (LC‐MS/MS) combined with elemental compositions derived from accurate mass measurements. We further used online H/D exchange experiments to verify the structural elucidations of each metabolite. Identifying molecular metabolites may provide critical insights into the pharmacological and clinical effects of ECTP treatment and may also provide useful information informing the development of new antidepressant treatments. These detailed plasma metabolite analyses may also be used to identify optimal dose concentrations in psychopharmacotherapeutic treatment through drug monitoring, as well as forming the basis for response predictions in depressed subjects.     

HILIC‐MS‐based shotgun metabolomic profiling of maternal urine at 9–23 weeks of gestation – establishing the baseline changes in the maternal metabolome

In this data‐rich age it is no longer necessary to methodically isolate, characterize and measure specific molecules. What is important is to identify which of the hundreds or thousands of resolved and measured ‘unknown’ molecules are potentially associated with the pathophysiology of interest. We have taken LC‐MS data from pregnancy urine and applied SIMCA P+ data analysis software in shotgun metabolomics to search the large amount of data for significant metabolite changes that occur in the transition from the first to early second trimester of pregnancy. Seventy‐two individual urine samples were examined spanning 9–23 weeks of gestation. Three‐hundred and eighty‐three ions were identified and variations were mapped between profiles of different gestational age and the significance quantified. In urine collected during pregnancy, the transition from first to early second trimester revealed a relatively steady pattern of metabolites except for four that showed a dramatic fall in abundance as pregnancy progressed from the first to second trimester. The pattern of changes in urinary metabolites identified by Zwitterionic Hydrophilic Liquid Interaction Chromatography (ZIC‐HILIC) coupled to mass spectrometry was evaluated and we established a baseline of changes from which a search for metabolomic markers associated with clinical pathologies of pregnancy can be made as a part of wider ultraomics study. Copyright © 2014 John Wiley & Sons, Ltd.     

Characterization and tentative identification of new flunitrazepam metabolites in authentic human urine specimens using liquid chromatography‐Q exactive‐HF hybrid quadrupole‐Orbitrap‐mass spectrometry (LC‐QE‐HF‐MS)

Flunitrazepam (FNZ) is a potent hypnotic, sedative, and amnestic drug used to treat severe insomnia. In our recent study, FNZ metabolic profiles were investigated carefully. Six authentic human urine samples were purified using solid phase extraction (SPE) without enzymatic hydrolysis, and urine extracts were then analyzed by liquid chromatography‐Q exactive‐HF hybrid quadrupole‐Orbitrap‐mass spectrometry (LC‐QE‐HF‐MS), using the full scan positive ion mode and targeted MS/MS (ddms2) technique to make accurate mass measurements. There were 25 metabolites, including 13 phase I and 12 phase II metabolites, which were detected and tentatively identified by LC‐QE‐HF‐MS. In addition, nine previously unreported phase II glucuronide conjugates and four phase I metabolites are reported here for the first time. Eight metabolic pathways, including N‐reduction and O‐reduction, N‐glucuronidation, O‐glucuronidation, mono‐hydroxylation and di‐hydroxylation, demethylation, acetylation, and combinations, were implicated in this work, and 2‐O‐reduction together with dihydroxylation were two novel metabolic pathways for FNZ that were identified tentatively. Although 7‐amino FNZ is widely considered to be the primary metabolite, a previously unreported metabolites (M12) can also serve as a potential biomarker for FNZ misuse.     

Evaluation of analytical performance and reliability of direct nanoLC‐nanoESI‐high resolution mass spectrometry for profiling the (xeno)metabolome

Mass spectrometry (MS) profiling techniques are used for analysing metabolites and xenobiotics in biofluids; however, detection of low abundance compounds using conventional MS techniques is poor. To counter this, nanoflow ultra‐high‐pressure liquid chromatography‐nanoelectrospray ionization‐time‐of‐flight MS (nUHPLC‐nESI‐TOFMS), which has been used primarily for proteomics, offers an innovative prospect for profiling small molecules. Compared to conventional UHPLC‐ESI‐TOFMS, nUHPLC‐nESI‐TOFMS enhanced detection limits of a variety of (xeno)metabolites by between 2 and 2000‐fold. In addition, this study demonstrates for the first time excellent repeatability and reproducibility for analysis of urine and plasma samples using nUHPLC‐nESI‐TOFMS, supporting implementation of this platform as a novel approach for high‐throughput (xeno)metabolomics. Copyright © 2014 John Wiley & Sons, Ltd.