An approach to enhancing coverage of the urinary metabonome using liquid chromatography–ion mobility–mass spectrometry

The Pharmacometabodynamics of Gefitinib after Intravenous Administration to Mice: A Preliminary UPLC-IM-MS Study

The effects of intravenous gefitinib (10 mg/kg), an anilinoquinazoline thymidylate kinase inhibitor (TKI), selective for the epidermal growth factor receptor (EGFR), on the urinary metabotypes of mice were studied. We hypothesized that, in response to the administration of gefitinib, there might be significant changes in the excretion of many endogenous metabolites in the urine, which could be correlated with the plasma pharmacokinetics (PK) of the drug. In order to investigate this conjecture, urine from male C57 BL6 mice was collected before IV dosing (10 mg/kg) and at 0–3, 3–8, and 8–24 h post-dose. The samples were profiled by UPLC/IM/MS and compared with the profiles obtained from undosed control mice with the data analyzed using multivariate statistical analysis (MVA). This process identified changes in endogenous metabolites over time and these were compared with drug and drug metabolite PK and excretion. While the MVA of these UPLC/IM/MS data did indeed reveal time-related changes for endogenous metabolites that appeared to be linked to drug administration, this analysis did not highlight the presence of either the drug or its metabolites in urine. Endogenous metabolites affected by gefitinib administration were identified by comparison of mass spectral, retention time and ion mobility-derived collision cross section data (compared to authentic standards wherever possible). The changes in endogenous metabolites resulting from gefitinib administration showed both increases (e.g., tryptophan, taurocholic acid, and the dipeptide lysyl-arginine) and decreases (e.g., deoxyguanosine, 8-hydroxydeoxyguanosine, and asparaginyl-histidine) relative to the control animals. By 8–24 h, the post-dose concentrations of most metabolites had returned to near control values. From these studies, we conclude that changes in the amounts of endogenous metabolites excreted in the urine mirrored, to some extent, the plasma pharmacokinetics of the drug. This phenomenon is similar to pharmacodynamics, where the pharmacological effects are related to the drug concentrations, and by analogy, we have termed this effect “pharmacometabodynamics”.

A systematic approach to development of analytical scale and microflow-based liquid chromatography coupled to mass spectrometry metabolomics methods to support drug discovery and development

As the reliance on metabolic biomarkers within drug discovery and development increases, there is also an increased demand for global metabolomics methods to provide broad metabolome coverage and sensitivity towards differences in metabolite expression and reproducibility. A systematic approach is necessary for the development, and evaluation, of metabolomics methods using either conventional techniques or when establishing new methods that allow for additional gains in sensitivity and a reduction in requirements for amounts of a biological sample, such as those seen with methods based on microseparations. We developed a novel standard mixture and used a systematic approach for the development and optimization of optimal, ion-pair free, liquid chromatography-mass spectrometry (LC-MS) global profiling methods. These methods were scaled-down to microflow-based LC separations and compared with analytical flow ion-pairing reagent containing methods. Average peak volume improvements of 7- and 22-fold were observed in the positive and negative ionization mode microflow methods as compared to the ion-pairing reagent analytical flow methods, respectively. The linear range of the newly developed microflow methods showed up to a 10-fold increase in the lower limit of detection in the negative ionization mode. The developed microflow LC-MS methods were further evaluated using wild-type mouse plasma where up to a 9-fold increase in peak volume was observed.

Metabolic Phenotyping Using UPLC–MS and Rapid Microbore UPLC–IM–MS: Determination of the Effect of Different Dietary Regimes on the Urinary Metabolome of the Rat

A rapid reversed-phase gradient method employing a 50 mm × 1 mm i.d., C18 microbore column, combined with ion mobility and high-resolution mass spectrometry, was applied to the metabolic phenotyping of urine samples obtained from rats receiving different diets. This method was directly compared to a “conventional” method employing a 150 × 2.1 mm i.d. column packed with the same C18 bonded phase using the same samples. Multivariate statistical analysis of the resulting data showed similar class discrimination for both microbore and conventional methods, despite the detection of fewer mass/retention time features by the former. Multivariate statistical analysis highlighted a number of ions that represented diet-specific markers in the samples. Several of these were then identified using the combination of mass, ion-mobility-derived collision cross section and retention time including N-acetylglutamate, urocanic acid, and xanthurenic acid. Kynurenic acid was tentatively identified based on mass and ion mobility data.

Combined hydrophilic interaction liquid chromatography-scanning field asymmetric waveform ion mobility spectrometry-time-of-flight mass spectrometry for untargeted metabolomics

Untargeted metabolite profiling of biological samples is a challenge for analytical science due to the high degree of complexity of biofluids. Isobaric species may also not be resolved using mass spectrometry alone. As a result of these factors, many potential biomarkers may not be detected or are masked by co-eluting interferences in conventional LC-MS metabolomic analyses. In this study, a comprehensive liquid chromatography-mass spectrometry workflow incorporating a fast-scanning miniaturised high-field asymmetric waveform ion mobility spectrometry separation (LC-FAIMS-MS) is applied to the untargeted metabolomic analysis of human urine. The time-of-flight mass spectrometer used in the study was scanned at a rate of 20 scans s^-1 enabling a FAIMS CF spectrum to be acquired within a 1-s scan time, maintaining an adequate number of data points across each LC peak. The developed method is demonstrated to be able to resolve co-eluting isomeric species and shows good reproducibility (%RSD < 4.9%). The nested datasets obtained for fresh, aged, and QC urine samples were submitted for multivariate statistical analysis. Seventy unique biomarker ions showing a statistically significant difference between fresh and aged urine were identified with optimal transmission CF values obtained across the full CF spectrum. The potential of using FAIMS to select ions for in-source collision-induced dissociation is demonstrated for FAIMS-selected methylxanthine ions yielding characteristic fragment ion species indicative of the precursor. Graphical abstract.

Untargeted LC/MS-based metabolic phenotyping (metabonomics/metabolomics): The state of the art

Liquid chromatography (LC) hyphenated to mass spectrometry is currently the most widely used means of determining metabolic phenotypes via both untargeted and targeted analysis. At present a range of analytical separations, including reversed-phase, hydrophilic interaction and ion-pair LC are employed to maximise metabolome coverage with ultra (high) performance liquid chromatography (UHPLC) increasingly displacing conventional high performance liquid chromatography because of the need for short analysis times and high peak capacity in such applications. However, it is widely recognized that these methodologies do not entirely solve the problems facing researchers trying to perform comprehensive metabolic phenotyping and in addition to these "routine" approaches there are continuing investigations of alternative separation methods including 2-dimensional/multi column approaches. These involve either new stationary phases or multidimensional combinations of the more conventional materials currently used, as well as application of miniaturization or "new" approaches such as supercritical HP and UHP- chromatographic separations. There is also a considerable amount of interest in the combination of chromatographic and ion mobility separations, with the latter providing both an increase in resolution and the potential to provide additional structural information via the determination of molecular collision cross section data. However, key problems remain to be solved including ensuring quality, comparability across different laboratories and the ever present difficulty of identifying unknowns.

Development of a rapid profiling method for the analysis of polar analytes in urine using HILIC-MS and ion mobility enabled HILIC-MS

INTRODUCTION

As large scale metabolic phenotyping is increasingly employed in preclinical studies and in the investigation of human health and disease the current LC-MS/MS profiling methodologies adopted for large sample sets can result in lengthy analysis times, putting strain on available resources. As a result of these pressures rapid methods of untargeted analysis may have value where large numbers of samples require screening.

OBJECTIVES

To develop, characterise and evaluate a rapid UHP-HILIC-MS-based method for the analysis of polar metabolites in rat urine and then extend the capabilities of this approach by the addition of IMS to the system.

METHODS

A rapid untargeted HILIC LC-MS/MS profiling method for the analysis of small polar molecules has been developed. The 3.3 min separation used a Waters BEH amide (1 mm ID) analytical column on a Waters Synapt G2-Si Q-Tof enabled with ion mobility spectrometry (IMS). The methodology, was applied to the metabolic profiling of a series of rodent urine samples from vehicle-treated control rats and animals administered tienilic acid. The same separation was subsequently linked to IMS and MS to evaluate the benefits that IMS might provide for metabolome characterisation.

RESULTS

The rapid HILIC-MS method was successfully applied to rapid analysis of rat urine and found, based on the data generated from the data acquired for the pooled quality control samples analysed at regular intervals throughout the analysis, to be robust. Peak area and retention times for the compounds detected in these samples showed good reproducibility across the batch. When used to profile the urine samples obtained from vehicle-dosed control and those administered tienilic acid the HILIC-MS method detected 3007 mass/retention time features. Analysis of the same samples using HILIC-IMS-MS enabled the detection of 6711 features. Provisional metabolite identification for a number of compounds was performed using the high collision energy MS/MS information compared against the Metlin MS/MS database and, in addition, both calculated and measured CCS values from an experimentally derived CCS database.

CONCLUSION

A rapid metabolic profiling method for the analysis of polar metabolites has been developed. The method has the advantages of speed and both reducing sample and solvent consumption compared to conventional profiling methods. The addition of IMS added an additional dimension for feature detection and the identification of metabolites.

Adding a new separation dimension to MS and LC-MS: What is the utility of ion mobility spectrometry?

Ion mobility spectrometry is an analytical technique known for more than 100 years, which entails separating ions in the gas phase based on their size, shape, and charge. While ion mobility spectrometry alone can be useful for some applications (mostly security analysis for detecting certain classes of narcotics and explosives), it becomes even more powerful in combination with mass spectrometry and high-performance liquid chromatography. Indeed, the limited resolving power of ion mobility spectrometry alone can be tackled when combining this analytical strategy with mass spectrometry or liquid chromatography with mass spectrometry. Over the last few years, the hyphenation of ion mobility spectrometry to mass spectrometry or liquid chromatography with mass spectrometry has attracted more and more interest, with significant progresses in both technical advances and pioneering applications. This review describes the theoretical background, available technologies, and future capabilities of these techniques. It also highlights a wide range of applications, from small molecules (natural products, metabolites, glycans, lipids) to large biomolecules (proteins, protein complexes, biopharmaceuticals, oligonucleotides).

The potential of ion mobility-mass spectrometry for non-targeted metabolomics

Non-targeted analysis of metabolites in hypothesis-generating workflows has proven its potential to answer essential questions that arise when dealing with complex biological systems. Nevertheless, tracking changes in perturbed systems via accurate quantification and the identification process itself represent the most critical challenges in these workflows. Recent advances in ion mobility-mass spectrometry have enabled this technique to increase the confidence of metabolite annotation by introducing a complementary conditional molecular descriptor, that is collision cross section.

Ion mobility spectrometry combined with ultra performance liquid chromatography/mass spectrometry for metabolic phenotyping of urine: Effects of column length, gradient duration and ion mobility spectrometry on metabolite detection

The need for rapid and efficient high throughput metabolic phenotyping (metabotyping) in metabolomic/metabonomic studies often requires compromises to be made between analytical speed and metabolome coverage. Here the effect of column length (150, 75 and 30 mm) and gradient duration (15, 7.5 and 3 min respectively) on the number of features detected when untargeted metabolic profiling of human urine using reversed-phase gradient ultra performance chromatography with, and without, ion mobility spectrometry, has been examined. As would be expected, reducing column length from 150 to 30 mm, and gradient duration, from 15 to 3 min, resulted in a reduction in peak capacity from 311 to 63 and a similar reduction in the number of features detected from over ca. 16,000 to ca. 6500. Under the same chromatographic conditions employing UPLC/IMS/MS to provide an additional orthogonal separation resulted in an increase in the number of MS features detected to nearly 20,000 and ca. 7500 for the 150 mm and the 30 mm columns respectively. Based on this limited study the potential of LC/IMS/MS as a tool for improving throughput and increasing metabolome coverage clearly merits further in depth study.

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Ion mobility spectrometry (IMS) significantly increased the number of analytes detected during the LC-MS of urine.

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Nearly ca. 20,000 features were seen for urine using LC-IMS-MS in a 15 min analysis compared to ca. 16,000 by LC-MS alone.

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In a 3 min analysis using a 30 mm column nearly 7600 features were detected with combined IMS and MS.

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For high throughput analysis a 75 mm column and a 3 min analysis was a good compromise between speed and features detected.

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The use of IMS also improved the quality of the mass spectra obtained.

Metabolomics and lipidomics using traveling-wave ion mobility mass spectrometry

Metabolomics and lipidomics aim to profile the wide range of metabolites and lipids that are present in biological samples. Recently, ion mobility spectrometry (IMS) has been used to support metabolomics and lipidomics applications to facilitate the separation and the identification of complex mixtures of analytes. IMS is a gas-phase electrophoretic technique that enables the separation of ions in the gas phase according to their charge, shape and size. Occurring within milliseconds, IMS separation is compatible with modern mass spectrometry (MS) operating with microsecond scan speeds. Thus, the time required for acquiring IMS data does not affect the overall run time of traditional liquid chromatography (LC)-MS-based metabolomics and lipidomics experiments. The addition of IMS to conventional LC-MS-based metabolomics and lipidomics workflows has been shown to enhance peak capacity, spectral clarity and fragmentation specificity. Moreover, by enabling determination of a collision cross-section (CCS) value-a parameter related to the shape of ions-IMS can improve the accuracy of metabolite identification. In this protocol, we describe how to integrate traveling-wave ion mobility spectrometry (TWIMS) into traditional LC-MS-based metabolomic and lipidomic workflows. In particular, we describe procedures for the following: tuning and calibrating a SYNAPT High-Definition MS (HDMS) System (Waters) specifically for metabolomics and lipidomics applications; extracting polar metabolites and lipids from brain samples; setting up appropriate chromatographic conditions; acquiring simultaneously m/z, retention time and CCS values for each analyte; processing and analyzing data using dedicated software solutions, such as Progenesis QI (Nonlinear Dynamics); and, finally, performing metabolite and lipid identification using CCS databases and TWIMS-derived fragmentation information.

Metabolome analyses in exposome studies: Profiling methods for a vast chemical space

Metabolic profiling (metabonomics/metabolomics) is now used routinely as a tool to provide information-rich datasets for biomarker discovery, prompting and augmenting detailed mechanistic studies. The experimental design and focus of any individual study will be reflected in the types of biomarkers that can be detected; toxicological studies will likely focus on markers of response to insult, whereas clinical case-control studies may yield diagnostic markers of disease. Population studies can make use of omics analyses, including metabonomics, to provide mechanistically-relevant markers that link environmental exposures to chronic disease endpoints. In this article, examples of how metabolic profiling has played a key role in molecular epidemiological analyses of chronic disease are presented, and how these reflect different aspects of the causal pathway. A commentary on the nature of metabolome analysis as a complex mixture problem as opposed to a coded, sequence or template problem is provided, alongside an overview of current and future analytical platforms that are being applied to meet this analytical challenge. Epidemiological studies are an important nexus for integrating various measures of the human exposome, and the ubiquity, diversity and functions of small molecule metabolites, represent an important way to link individual exposures, genetics and phenotype.

Metabolic profiling in human exposome studies

The human metabolome-the complement of small molecule metabolites present in biofluids and tissues-represents a significant part of the internal chemical milieu and is therefore an important aspect of the human exposome. Metabolic profiling approaches, commonly referred to as metabonomics or metabolomics, permit detailed and efficient characterisation of human biospecimens; application to population studies holds great promise for uncovering new associations and causal relationships between environmental factors and chronic disease. In addition to the insight metabolic information can provide, metabolic phenotypes anchor other molecular readouts and help formulate a systems-level interpretation of biological phenomena. In this commentary, we discuss the general approach for applying metabolic profiling in exposome studies, alongside recent exemplars. We also comment on the complexity and dynamism of the metabolome and highlight both the limitations such properties impart and the requirements for dealing with such issues in real-world phenotyping studies. Given that several large-scale exposome studies are now underway, we offer a perspective on current and future challenges that will need to be addressed to maximise their utility in environmental health research.

Applications of ion-mobility mass spectrometry for lipid analysis

The high chemical complexity of the lipidome is one of the major challenges in lipidomics research. Ion-mobility spectrometry (IMS), a gas-phase electrophoretic technique, makes possible the separation of ions in the gas phase according to their charge, shape, and size. IMS can be combined with mass spectrometry (MS), adding three major benefits to traditional lipidomic approaches. First, IMS-MS allows the determination of the collision cross section (CCS), a physicochemical measure related to the conformational structure of lipid ions. The CCS is used to improve the confidence of lipid identification. Second, IMS-MS provides a new set of hybrid fragmentation experiments. These experiments, which combine collision-induced dissociation with ion-mobility separation, improve the specificity of MS/MS-based approaches. Third, IMS-MS improves the peak capacity and signal-to-noise ratio of traditional analytical approaches. In doing so, it allows the separation of complex lipid extracts from interfering isobaric species. Developing in parallel with advances in instrumentation, informatics solutions enable analysts to process and exploit IMS-MS data for qualitative and quantitative applications. Here we review the current approaches for lipidomics research based on IMS-MS, including liquid chromatography-MS and direct-MS analyses of "shotgun" lipidomics and MS imaging.

Multiple enzymatic digestions and ion mobility separation improve quantification of bacterial ribosomal proteins by data independent acquisition liquid chromatography-mass spectrometry

Mass spectrometry-based quantification of ribosomal proteins (r-proteins) associated with mature ribosomes and ribosome assembly complexes is typically accomplished by relative quantification strategies. These strategies provide information on the relative stoichiometry of proteins within the complex compared to a wild-type strain. Here we have evaluated the applicability of a label-free approach, enhanced liquid chromatography–mass spectrometry (LC–MS^E), for absolute “ribosome-centric” quantification of r-proteins in Escherichia coli mature ribosomes. Because the information obtained in this experiment is related to the number of peptides identified per protein, experimental conditions that allow accurate and reproducible quantification of r-proteins were found. Using an additional dimension of gas-phase separation through ion mobility and the use of multiple endoproteinase digestion significantly improved quantification of proteins associated with mature ribosomes. The actively translating ribosomes (polysomes) contain amounts of proteins consistent with their known stoichiometry within the complex. These measurements exhibited technical and biological reproducibilities at %CV less than 15% and 35%, respectively. The improved LC–MS^E approach described here can be used to characterize in vivo ribosome assembly complexes captured during ribosome biogenesis and assembly under different perturbations (e.g., antibiotics, deletion mutants of assembly factors, oxidative stress, nutrient deprivation). Quantitative analysis of these captured complexes will provide information relating to the interplay and dynamics of how these perturbations interfere with the assembly process.

Ion mobility derived collision cross sections to support metabolomics applications

Metabolomics is a rapidly evolving analytical approach in life and health sciences. The structural elucidation of the metabolites of interest remains a major analytical challenge in the metabolomics workflow. Here, we investigate the use of ion mobility as a tool to aid metabolite identification. Ion mobility allows for the measurement of the rotationally averaged collision cross-section (CCS), which gives information about the ionic shape of a molecule in the gas phase. We measured the CCSs of 125 common metabolites using traveling-wave ion mobility-mass spectrometry (TW-IM-MS). CCS measurements were highly reproducible on instruments located in three independent laboratories (RSD < 5% for 99%). We also determined the reproducibility of CCS measurements in various biological matrixes including urine, plasma, platelets, and red blood cells using ultra performance liquid chromatography (UPLC) coupled with TW-IM-MS. The mean RSD was < 2% for 97% of the CCS values, compared to 80% of retention times. Finally, as proof of concept, we used UPLC-TW-IM-MS to compare the cellular metabolome of epithelial and mesenchymal cells, an in vitro model used to study cancer development. Experimentally determined and computationally derived CCS values were used as orthogonal analytical parameters in combination with retention time and accurate mass information to confirm the identity of key metabolites potentially involved in cancer. Thus, our results indicate that adding CCS data to searchable databases and to routine metabolomics workflows will increase the identification confidence compared to traditional analytical approaches.

Prediction of peptide drift time in ion mobility mass spectrometry from sequence-based features

Background

Ion mobility-mass spectrometry (IMMS), an analytical technique which combines the features of ion mobility spectrometry (IMS) and mass spectrometry (MS), can rapidly separates ions on a millisecond time-scale. IMMS becomes a powerful tool to analyzing complex mixtures, especially for the analysis of peptides in proteomics. The high-throughput nature of this technique provides a challenge for the identification of peptides in complex biological samples. As an important parameter, peptide drift time can be used for enhancing downstream data analysis in IMMS-based proteomics.

Results

In this paper, a model is presented based on least square support vectors regression (LS-SVR) method to predict peptide ion drift time in IMMS from the sequence-based features of peptide. Four descriptors were extracted from peptide sequence to represent peptide ions by a 34-component vector. The parameters of LS-SVR were selected by a grid searching strategy, and a 10-fold cross-validation approach was employed for the model training and testing. Our proposed method was tested on three datasets with different charge states. The high prediction performance achieve demonstrate the effectiveness and efficiency of the prediction model.

Conclusions

Our proposed LS-SVR model can predict peptide drift time from sequence information in relative high prediction accuracy by a test on a dataset of 595 peptides. This work can enhance the confidence of protein identification by combining with current protein searching techniques.

Direct extraction of urinary analytes from undeveloped reversed-phase thin layer chromatography plates using a solvent gradient combined with on-line electrospray ionisation ion mobility-mass spectrometry

The direct extraction of urinary analytes deposited on reversed-phase thin-layer chromatography (RP-TLC) plates is demonstrated using a solvent gradient extraction procedure without prior chromatographic development. The surface sample probe TLC-MS interface used for the gradient extraction is compared to direct loop injection into the electrospray ion source for biofluid profiling. The gradient elution is shown to enhance ion intensities, as urinary salts are eluted in aqueous formic acid in the early part of the gradient reducing ion suppression. The retention of urinary components on the C18 RP-TLC plate was confirmed by monitoring analyte responses with, and without, an aqueous wash phase prior to the solvent gradient extraction. The use of gradient elution allows fractionation of the complex biological matrix as a result of differential retention of urine components on the undeveloped RP-TLC plate. The direct gradient analysis of TLC plates has also been combined with ion mobility-mass spectrometry to further resolve the complex urinary profile and identify co-eluting compounds.

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.

Comprehensive two-dimensional separation of hydroxylated polybrominated diphenyl ethers by ultra-performance liquid chromatography coupled with ion mobility-mass spectrometry

A comprehensive two-dimensional system coupling ultra-performance liquid chromatography (UPLC) and ion mobility-mass spectrometry (IM-MS) has been applied for the separation and analysis of hydroxylated polybrominated diphenyl ethers (OH-PBDEs). A complex mixture containing 23 OH-PBDE congeners ranging from hydroxylated monobromodiphenyl ether (OH-monoBDE) to hydroxylated octabromodiphenyl ether (OH-octaBDE) was satisfactorily separated within 16 min of analysis time. The first-dimensional reversed-phase UPLC was performed on a sub-2 μm BEH C(18) chromatographic column using acetonitrile-water gradient elution program with a flow rate ramp. It enabled excellent chromatographic separation for both between-class and within-class OH-PBDEs based on their differences in hydrophobicity. Following the pre-ionization resolution in the first dimension, the second-dimensional IM-MS employed a hybrid electrospray quadrupole ion mobility time-of-flight mass spectrometer and added an extra post-ionization separation for between-class OH-PBDE congeners on account of their relative mobility disparity during a very short period of 8.80 ms. The orthogonality of the developed two-dimensional system was evaluated with the correlation coefficient of 0.9665 and peak spreading angle of 14.87°. The peak capacity of the system was calculated to be approximately 2 and 15 times higher than that of the two dimensions used alone, respectively. The two-dimensional separation plane also contributed to the removal of background interference ions and the enhanced confidence in the characterization of OH-PBDEs of interest.

Mass spectrometry-based holistic analytical approaches for metabolite profiling in systems biology studies

Metabonomics and metabolomics represent one of the three major platforms in systems biology. To perform metabolomics it is necessary to generate comprehensive "global" metabolite profiles from complex samples, for example, biological fluids or tissue extracts. Analytical technologies based on mass spectrometry (MS), and in particular on liquid chromatography-MS (LC-MS), have become a major tool providing a significant source of global metabolite profiling data. In the present review we describe and compare the utility of the different analytical strategies and technologies used for MS-based metabolomics with a particular focus on LC-MS. Both the advantages offered by the technology and also the challenges and limitations that need to be addressed for the successful application of LC-MS in metabolite analysis are described. Data treatment and approaches resulting in the detection and identification of biomarkers are considered. Special emphasis is given to validation issues, instrument stability, and QA/quality control (QC) procedures.