Ion-pairing reversed-phase liquid chromatography fractionation in combination with isotope labeling reversed-phase liquid chromatography-mass spectrometry for comprehensive metabolome profiling

Impact of ion-pairing systems choice on diastereomeric selectivity of phosphorothioated oligonucleotides in reversed-phase liquid chromatography

Ion-pairing reversed-phase liquid chromatography was utilized for the analysis of native and phosphorothioated oligonucleotides differing in the length (2-6mers and 21mer) and the number and position of phosphorothioate modifications. We investigated the influence of counterion (acetate vs. hexafluoroisopropanol) on the adsorption of eleven alkylamines on the stationary phases. A stronger adsorption of charged alkylamines on octadecyl- and phenyl-based stationary phases led to greater retention of oligonucleotides, and the adsorption of alkylamines was promoted with greater concentration of hexafluoroisopropanol in the mobile phase. Selected amines (triethylamine, dipropylamine, hexylamine) were used to study the resolution of n and n-x mers (main peak and its impurities shortened at 5´end), and diastereomeric separation of phosphorothioated oligonucleotides. The results confirmed a crucial role of alkylamine and counterion choice on the diastereomeric separation. The increasing hydrophobicity of alkylamine led to diminished diastereomeric selectivity which produced narrower phosphorothioated oligonucleotides peaks and led to improved n/n-x separation. Using hexafluoroisopropanol instead of acetate as counterion further enhances this effect (except for 100 mM concentration of hexafluoroisopropanol in combination with highly hydrophobic hexylamine). The elevated column temperature led to suppression of the diastereomeric resolution and improved resolution of n and n-x mers oligonucleotides. Baseline separation of oligonucleotides with different number of phosphorothioate linkages was achieved; this may be useful for therapeutic oligonucleotide analysis.

Offline Two-Dimensional Liquid Chromatography-Mass Spectrometry for Deep Annotation of the Fecal Metabolome Following Fecal Microbiota Transplantation

Biological interpretation of untargeted LC-MS-based metabolomics data depends on accurate compound identification, but current techniques fall short of identifying most features that can be detected. The human fecal metabolome is complex, variable, incompletely annotated, and serves as an ideal matrix to evaluate novel compound identification methods. We devised an experimental strategy for compound annotation using multidimensional chromatography and semiautomated feature alignment and applied these methods to study the fecal metabolome in the context of fecal microbiota transplantation (FMT) for recurrent C. difficile infection. Pooled fecal samples were fractionated using semipreparative liquid chromatography and analyzed by an orthogonal LC-MS/MS method. The resulting spectra were searched against commercial, public, and local spectral libraries, and annotations were vetted using retention time alignment and prediction. Multidimensional chromatography yielded more than a 2-fold improvement in identified compounds compared to conventional LC-MS/MS and successfully identified several rare and previously unreported compounds, including novel fatty-acid conjugated bile acid species. Using an automated software-based feature alignment strategy, most metabolites identified by the new approach could be matched to features that were detected but not identified in single-dimensional LC-MS/MS data. Overall, our approach represents a powerful strategy to enhance compound identification and biological insight from untargeted metabolomics data.

Enhancing Oil Solubility of BCS Class II Drug Phenytoin Through Hydrophobic Ion Pairing to Enable High Drug Load in Injectable Nanoemulsion to Prevent Precipitation at Physiological pH With a Potential to Prevent Phlebitis

This work investigates the micellar titration of phenytoin (a weakly acidic drug) with cetyltrimethylammonium hydroxide (CTAH) to form a hydrophobic ion-pair to enhance oil solubility of phenytoin, followed by an effort to formulate nanoemulsion that could potentially prevent precipitation of phenytoin at physiological pH. The ion-pair formulated in nanoemulsion was evaluated for in vitro precipitation during serial dilution at physiological pH. The formation of ion-pair during titration was explained in context of pH-solubility data. The mathematical model successfully integrated ionization and micellization equilibria to reflect on dominant mechanisms for solubilization. The micellar phenomenon during titration was confirmed using Dynamic Light Scattering (DLS). The phase changes of the excess undissolved solids during titration were evident from X-Ray Powder Diffraction (XRPD) and Fourier Transform Infrared Spectroscopy (FTIR). This analysis confirmed the conversion of phenytoin into ionized state and its subsequent ionic interaction with CTAH forming hydrophobic ion-pair complex (HIP). The complete ion pair formation was evident at pHmax (8.8 to 9.2), and its 1:1 stoichiometry was confirmed using HPLC (Phenytoin and CTAH) and H1 NMR, hence could also be called as a lipophilic salt. The ion-pair (salt) was insoluble in water and showed remarkably high partition coefficient (log P) in octanol/water. As characterized by Hot Stage Microscopy (HSM), the melting point of the ion-pair complex was lowered to 150.8⁰C compared to the free acid (> 300οC), this was even further lowered to 81.1 °C when evaluated in castor oil. This led to approximately eight-fold higher solubility of hydrophobic ion pair (HIP) in castor oil compared to the free acid form. The high miscibility in castor oil was suitable to formulate a high drug load injectable dispersed system. This was successfully achieved with lecithin and polysorbate as emulsifiers without leaching drug into continuous phase at pH 7.4. This nanoemulsion (<300 nm, and > +30 mV zeta potential) remain stable when evaluated over a period of one month. A serial dilution study of the nanoemulsion was performed in PBS buffer, microscopic observations suggested no birefringence despite incubation at 25°C for several hours. This result indicated that Phenytoin remained strongly partitioned within dispersed oily phase with a higher drug loading when ion-paired phenytoin was used. The higher drug load could enable a small volume slow bolus injection to meet 50 mg/min or lower delivery rate criteria for Phenytoin in the clinical set up. This provided a pathway to further explore potential injectable nano-emulsion formulations that could alleviate typical phlebitis issue associated with the injectable phenytoin solution administration at physiological pH.

Offline Two-dimensional Liquid Chromatography-Mass Spectrometry for Deep Annotation of the Fecal Metabolome

Compound identification is an essential task in the workflow of untargeted metabolomics since the interpretation of the data in a biological context depends on the correct assignment of chemical identities to the features it contains. Current techniques fall short of identifying all or even most observable features in untargeted metabolomics data, even after rigorous data cleaning approaches to remove degenerate features are applied. Hence, new strategies are required to annotate the metabolome more deeply and accurately. The human fecal metabolome, which is the focus of substantial biomedical interest, is a more complex, more variable, yet lesser-investigated sample matrix compared to widely studied sample types like human plasma. This manuscript describes a novel experimental strategy using multidimensional chromatography to facilitate compound identification in untargeted metabolomics. Pooled fecal metabolite extract samples were fractionated using offline semi-preparative liquid chromatography. The resulting fractions were analyzed by an orthogonal LC-MS/MS method, and the data were searched against commercial, public, and local spectral libraries. Multidimensional chromatography yielded more than a 3-fold improvement in identified compounds compared to the typical single-dimensional LC-MS/MS approach and successfully identified several rare and novel compounds, including atypical conjugated bile acid species. Most features identified by the new approach could be matched to features that were detectable but not identifiable in the original single-dimension LC-MS data. Overall, our approach represents a powerful strategy for deeper annotation of the metabolome that can be implemented with commercially-available instrumentation, and should apply to any dataset requiring deeper annotation of the metabolome.

A Comprehensive 2D-LC/MS/MS Profile of the Normal Human Urinary Metabolome

Profiling bodily fluids is crucial for monitoring and discovering metabolic markers of disease. In this study, a comprehensive analysis approach based on 1D-LC-MS/MS and 2D-LC-MS/MS was applied to profile normal human urine metabolites from 348 children and 315 adults. A total of 2357 metabolites were identified, including 1831 endogenous metabolites and 526 exogenous ones. In total, 1005 metabolites were identified in urine for the first time. The urinary metabolites were mainly involved in amino acid metabolism, small molecule biochemistry, lipid metabolism and cellular compromise. The comparison of adult’s and children’s urine metabolomes showed adults urine had more metabolites involved in immune response than children’s, but the function of binding of melatonin, which belongs to the endocrine system, showed a higher expression in children. The urine metabolites detected by the 1D-LC-MS/MS method were mainly related to amino acid metabolism and lipid metabolism, and the 2D-LC-MS/MS method not only explored metabolites from 1D-LC-MS/MS but also metabolites related to cell signaling, cell function and maintenance, etc. Our analysis comprehensively profiled and functionally annotated the metabolome of normal human urine, which would benefit the application of urinary metabolome to clinical research.

Metabolomic Profiling of Human Urine Samples Using LC-TIMS-QTOF Mass Spectrometry

The identification of metabolites in biological samples is challenging due to their chemical and structural diversity. Ion mobility spectrometry (IMS) separates ionized molecules based on their mobility in a carrier buffer gas giving information about the ionic shape by measuring the rotationally averaged collision cross-section (CCS) value. This orthogonal descriptor, in combination with the m/z, isotopic pattern distribution, and MS/MS spectrum, has the potential to improve the identification of molecular molecules in complex mixtures. Urine metabolomics can reveal metabolic differences, which arise as a result of a specific disease or in response to therapeutic intervention. It is, however, complicated by the presence of metabolic breakdown products derived from a wide range of lifestyle and diet-related byproducts, many of which are poorly characterized. In this study, we explore the use of trapped ion mobility spectrometry (TIMS) via LC parallel accumulation with serial fragmentation (PASEF) for urine metabolomics. A total of 362 urine metabolites were characterized from 80 urine samples collected from healthy volunteers using untargeted metabolomics employing HILIC and RP chromatography. Additionally, three analytes (Trp, Phe, and Tyr) were selected for targeted quantification. Both the untargeted and targeted data was highly reproducible and reported CCS measurements for identified metabolites were robust in the presence of the urine matrix. A comparison of CCS values among different laboratories was also conducted, showing less than 1.3% ΔCCS values across different platforms. This is the first report of a human urine metabolite database compiled with CCS values experimentally acquired using an LC-PASEF TIMS-qTOF platform.

Dichloroacetate-induced metabolic reprogramming improves lifespan in a Drosophila model of surviving sepsis

Sepsis is the leading cause of death in hospitalized patients and beyond the hospital stay and these long-term sequelae are due in part to unresolved inflammation. Metabolic shift from oxidative phosphorylation to aerobic glycolysis links metabolism to inflammation and such a shift is commonly observed in sepsis under normoxic conditions. By shifting the metabolic state from aerobic glycolysis to oxidative phosphorylation, we hypothesized it would reverse unresolved inflammation and subsequently improve outcome. We propose a shift from aerobic glycolysis to oxidative phosphorylation as a sepsis therapy by targeting the pathways involved in the conversion of pyruvate into acetyl-CoA via pyruvate dehydrogenase (PDH). Chemical manipulation of PDH using dichloroacetic acid (DCA) will promote oxidative phosphorylation over glycolysis and decrease inflammation. We tested our hypothesis in a Drosophila melanogaster model of surviving sepsis infected with Staphylococcus aureus. Drosophila were divided into 3 groups: unmanipulated, sham and sepsis survivors, all treated with linezolid; each group was either treated or not with DCA for one week following sepsis. We followed lifespan, measured gene expression of Toll, defensin, cecropin A, and drosomycin, and levels of lactate, pyruvate, acetyl-CoA as well as TCA metabolites. In our model, metabolic effects of sepsis are modified by DCA with normalized lactate, TCA metabolites, and was associated with improved lifespan of sepsis survivors, yet had no lifespan effects on unmanipulated and sham flies. While Drosomycin and cecropin A expression increased in sepsis survivors, DCA treatment decreased both and selectively increased defensin.

Peptidomic analysis of zebrafish embryos exposed to polychlorinated biphenyls and their impact on eye development

Polychlorinated biphenyls (PCBs), a class of persistent organic pollutant, are closely related to abnormal eye development in children. However, little is known regarding the role of peptides in the development of PCB-induced ocular dysplasia. To characterize the nature of PCB exposure on peptides involved in the development of the ocular system, we used liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) to detect differential expression of peptides between normal and PCB-exposed zebrafish embryos. A total of 7900 peptides were analyzed, 90 of which were differentially expressed, with 29 being up-regulated and 61 down-regulated. These peptides were investigated using ingenuity pathway analysis (IPA) and gene ontology (GO) analysis to explore their role in eye development. This study identified 18 peptides associated with the development of the optic nerve and ocular system in the PCB-exposure group, as well as 10 peptides that are located in the functional domain of their precursor proteins. These peptides provide potential biomarkers for the treatment of ocular dysplasia caused by PCBs and may help us understand the mechanism of abnormal eye development caused by organic pollutants.

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

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

Isotope-labeled differential profiling of metabolites using N-benzoyloxysuccinimide derivatization coupled to liquid chromatography/high-resolution tandem mass spectrometry

RATIONALE

An isotopic labeling strategy based on derivatizing amine-containing metabolites has been developed using light ((12) C6 ) and heavy ((13) C6 ) N-benzoyloxysuccinimide reagents for semi-targeted metabolomic applications.

METHODS

Differentially labeled samples were combined and analyzed simultaneously by liquid chromatography/high-resolution tandem mass spectrometry (LC/HR-MS/MS) to compare relative amounts of amine-containing metabolites. The selectivity of the reaction was determined with model metabolites and was shown to also be applicable to thiol and phenol moieties. The potential for relative quantitation was evaluated in cell extracts and the method was then applied to quantify metabolic perturbations occurring in human cultured cells under normal vs. oxidative stress conditions.

RESULTS

A total of 279 derivatized features were detected in HL60 cell extracts, 77 of which yielded significant concentration changes upon oxidative stress treatment. Based on accurate mass measurements and MS/MS spectral matching with reference standard solutions, 10 metabolites were clearly identified. Derivatized compounds were found to have diagnostic fragment ions from the reagent itself, as well as structurally informative ions useful for metabolite identification.

CONCLUSIONS

This simple derivatization reaction can be applied to the relative quantitation of amine-, thiol- and phenol-containing compounds, with improved sensitivity and chromatographic peak shapes due to the increased hydrophobicity of polar metabolites not readily amenable to reversed-phase LC/MS analysis.

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.

Quantitative metabolomic profiling using dansylation isotope labeling and liquid chromatography mass spectrometry

Differential chemical isotopic labeling (CIL) LC-MS has been used for quantifying a targeted metabolite in biological samples with high precision and accuracy. Herein we describe a high-performance CIL LC-MS method for generating quantitative and comprehensive profiles of the metabolome for metabolomics applications. After mixing two comparative samples separately labeled by light or heavy isotopic tags through chemical reactions, the peak intensity ratio of the labeled analyte pair can provide relative or absolute quantitative information on the metabolites. We describe the use of (12)C2- and (13)C2-dansyl chloride (DnsCl) as the isotope reagents to profile the metabolites containing amine and phenolic hydroxyl functional groups by LC-MS. This method can be used to compare the relative concentration changes of hundreds or thousands of amine- and phenol-containing metabolites among many comparative samples and generate absolute concentration information on metabolites for which the standards are available. Combined with statistical analysis and metabolite identification tools, this method can be used to identify key metabolites involved in differentiating comparative samples such as disease cases vs. healthy controls.

Comparative proteomic and metabolomic analysis of Staphylococcus warneri SG1 cultured in the presence and absence of butanol

The complete genome of the solvent tolerant Staphylococcus warneri SG1 was recently published. This Gram-positive bacterium is tolerant to a large spectrum of organic solvents including short-chain alcohols, alkanes, esters and cyclic aromatic compounds. In this study, we applied a two-dimensional liquid chromatography (2D-LC) mass spectrometry (MS) shotgun approach, in combination with quantitative 2-MEGA (dimethylation after guanidination) isotopic labeling, to compare the proteomes of SG1 grown under butanol-free and butanol-challenged conditions. In total, 1585 unique proteins (representing 65% of the predicted open reading frames) were identified, covering all major metabolic pathways. Of the 967 quantifiable proteins by 2-MEGA labeling, 260 were differentially expressed by at least 1.5-fold. These proteins are involved in energy metabolism, oxidative stress response, lipid and cell envelope biogenesis, or have chaperone functions. We also applied differential isotope labeling LC-MS to probe metabolite changes in key metabolic pathways upon butanol stress. This is the first comprehensive proteomic and metabolomic study of S. warneri SG1 and presents an important step toward understanding its physiology and mechanism of solvent tolerance.

The human urine metabolome

Urine has long been a "favored" biofluid among metabolomics researchers. It is sterile, easy-to-obtain in large volumes, largely free from interfering proteins or lipids and chemically complex. However, this chemical complexity has also made urine a particularly difficult substrate to fully understand. As a biological waste material, urine typically contains metabolic breakdown products from a wide range of foods, drinks, drugs, environmental contaminants, endogenous waste metabolites and bacterial by-products. Many of these compounds are poorly characterized and poorly understood. In an effort to improve our understanding of this biofluid we have undertaken a comprehensive, quantitative, metabolome-wide characterization of human urine. This involved both computer-aided literature mining and comprehensive, quantitative experimental assessment/validation. The experimental portion employed NMR spectroscopy, gas chromatography mass spectrometry (GC-MS), direct flow injection mass spectrometry (DFI/LC-MS/MS), inductively coupled plasma mass spectrometry (ICP-MS) and high performance liquid chromatography (HPLC) experiments performed on multiple human urine samples. This multi-platform metabolomic analysis allowed us to identify 445 and quantify 378 unique urine metabolites or metabolite species. The different analytical platforms were able to identify (quantify) a total of: 209 (209) by NMR, 179 (85) by GC-MS, 127 (127) by DFI/LC-MS/MS, 40 (40) by ICP-MS and 10 (10) by HPLC. Our use of multiple metabolomics platforms and technologies allowed us to identify several previously unknown urine metabolites and to substantially enhance the level of metabolome coverage. It also allowed us to critically assess the relative strengths and weaknesses of different platforms or technologies. The literature review led to the identification and annotation of another 2206 urinary compounds and was used to help guide the subsequent experimental studies. An online database containing the complete set of 2651 confirmed human urine metabolite species, their structures (3079 in total), concentrations, related literature references and links to their known disease associations are freely available at http://www.urinemetabolome.ca.

Numerous protein-bound solutes are cleared by the kidney with high efficiency

The kidney clears numerous solutes from the plasma; however, retention of these solutes causes uremic illness when the kidneys fail. We know remarkably little about which retained solutes are toxic and this limits our ability to improve dialysis therapies. To explore this we employed untargeted mass spectrometry to identify solutes that are efficiently cleared by the kidney. High resolution mass spectrometry detected 1808 features in the urine and plasma ultrafiltrate of 5 individuals with normal renal function. The estimated clearance rates of 1082 peaks were greater than the creatinine clearance indicating tubular secretion. Further analysis identified 90 features representing solutes with estimated clearance rates greater than the renal plasma flow. Quantitative mass spectrometry with stable isotope dilution confirmed that efficient clearance of these solutes is made possible by the combination of binding to plasma proteins and tubular secretion. Tandem mass spectrometry established the chemical identity of 13 solutes including hippuric acid, indoxyl sulfate, and p-cresol sulfate. These 13 efficiently cleared solutes were found to accumulate in the plasma of hemodialysis patients, with free levels rising to more than 20-fold normal for all but two of them. Thus, further analysis of solutes efficiently cleared by secretion in the native kidney may provide a potential route to the identification of uremic toxins.

Relative quantification of biomarkers using mixed-isotope labeling coupled with MS

The identification and quantification of important biomarkers is a critical first step in the elucidation of biological systems. Biomarkers take many forms as cellular responses to stimuli and can be manifested during transcription, translation, and/or metabolic processing. Increasingly, researchers have relied upon mixed-isotope labeling (MIL) coupled with MS to perform relative quantification of biomarkers between two or more biological samples. MIL effectively tags biomarkers of interest for ease of identification and quantification within the mass spectrometer by using isotopic labels that introduce a heavy and light form of the tag. In addition to MIL coupled with MS, a number of other approaches have been used to quantify biomarkers including protein gel staining, enzymatic labeling, metabolic labeling, and several label-free approaches that generate quantitative data from the MS signal response. This review focuses on MIL techniques coupled with MS for the quantification of protein and small-molecule biomarkers.

Extraction, derivatization, and determination of metabolome in human macrophages

A GC/TOF-MS was applied to the determination of metabolites in human macrophages. The extraction conditions and quenching conditions were investigated and optimized. The results indicated that 0.9% w/v sodium chloride at 4°C was the most favorable condition to quench macrophage, 1 mL 50% ACN for 2 min in ice bath was the optimal condition to extract 5 × 10(6) cells. Two hundred six peaks could be detectable with peak area over 50 using this method. Among these peaks, 45 peaks with the similarity over 700 were identified using standard compounds for endogenous metabolites. Thirty-seven out of 45 metabolites could be quantified directly by this method. Twenty metabolites were selected randomly, and 15 amino acids were used for method validation. The correlation coefficients (r) ranging from 0.9902 to 0.9977 were obtained for 15 amino acids in the range of 2.35-150.20 μg/mL. The intraday and interday precisions were lower than 19.90% for the randomly selected 20 endogenous metabolites. Using this development method and multivariate statistical technique, several potential biomarkers were found from human macrophages infected by different Mycobacterium tuberculosis (M. tuberculosis) strains. The results suggest that the method could be applied to the investigation of the pathogenicity of tuberculosis.

Determination of total concentration of chemically labeled metabolites as a means of metabolome sample normalization and sample loading optimization in mass spectrometry-based metabolomics

For mass spectrometry (MS)-based metabolomics, it is important to use the same amount of starting materials from each sample to compare the metabolome changes in two or more comparative samples. Unfortunately, for biological samples, the total amount or concentration of metabolites is difficult to determine. In this work, we report a general approach of determining the total concentration of metabolites based on the use of chemical labeling to attach a UV absorbent to the metabolites to be analyzed, followed by rapid step-gradient liquid chromatography (LC) UV detection of the labeled metabolites. It is shown that quantification of the total labeled analytes in a biological sample facilitates the preparation of an appropriate amount of starting materials for MS analysis as well as the optimization of the sample loading amount to a mass spectrometer for achieving optimal detectability. As an example, dansylation chemistry was used to label the amine- and phenol-containing metabolites in human urine samples. LC-UV quantification of the labeled metabolites could be optimally performed at the detection wavelength of 338 nm. A calibration curve established from the analysis of a mixture of 17 labeled amino acid standards was found to have the same slope as that from the analysis of the labeled urinary metabolites, suggesting that the labeled amino acid standard calibration curve could be used to determine the total concentration of the labeled urinary metabolites. A workflow incorporating this LC-UV metabolite quantification strategy was then developed in which all individual urine samples were first labeled with (12)C-dansylation and the concentration of each sample was determined by LC-UV. The volumes of urine samples taken for producing the pooled urine standard were adjusted to ensure an equal amount of labeled urine metabolites from each sample was used for the pooling. The pooled urine standard was then labeled with (13)C-dansylation. Equal amounts of the (12)C-labeled individual sample and the (13)C-labeled pooled urine standard were mixed for LC-MS analysis. This way of concentration normalization among different samples with varying concentrations of total metabolites was found to be critical for generating reliable metabolome profiles for comparison.

Current trends and challenges in sample preparation for global metabolomics using liquid chromatography-mass spectrometry

The choice of sample-preparation method is extremely important in metabolomic studies because it affects both the observed metabolite content and biological interpretation of the data. An ideal sample-preparation method for global metabolomics should (i) be as non-selective as possible to ensure adequate depth of metabolite coverage; (ii) be simple and fast to prevent metabolite loss and/or degradation during the preparation procedure and enable high-throughput; (iii) be reproducible; and (iv) incorporate a metabolism-quenching step to represent true metabolome composition at the time of sampling. Despite its importance, sample preparation is often an overlooked aspect of metabolomics, so the focus of this review is to explore the role, challenges, and trends in sample preparation specifically within the context of global metabolomics by liquid chromatography-mass spectrometry (LC-MS). This review will cover the most common methods including solvent precipitation and extraction, solid-phase extraction and ultrafiltration, and discuss how to improve analytical quality and metabolite coverage in metabolomic studies of biofluids, tissues, and mammalian cells. Recent developments in this field will also be critically examined, including in vivo methods, turbulent-flow chromatography, and dried blood spot sampling.

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.