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

Proteomic strategies in the search for novel pancreatic cancer biomarkers and drug targets: recent advances and clinical impact

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers; despite a low incidence rate it is the fourth leading cause of cancer-related death in the world. Improvement of the diagnosis, prognosis and treatment remains the main focus of pancreatic cancer research. Rapid developments in proteomic technologies has improved our understanding of the pancreatic cancer proteome. Here, the authors summarise the recent proteomic strategies undertaken in the search for: novel biomarkers for early diagnosis, pancreatic cancer-specific proteins which may be used for novel targeted therapies and proteins which may be useful for monitoring disease progression post-therapy. Recent advances and findings discussed here provide great promise of having a significant clinical impact and improving the outcome of patients with this malignancy.

Technical Challenges in Mass Spectrometry-Based Metabolomics

Metabolomics is a strategy for analysis, and quantification of the complete collection of metabolites present in biological samples. Metabolomics is an emerging area of scientific research because there are many application areas including clinical, agricultural, and medical researches for the biomarker discovery and the metabolic system analysis by employing widely targeted analysis of a few hundred preselected metabolites from 10-100 biological samples. Further improvement in technologies of mass spectrometry in terms of experimental design for larger scale analysis, computational methods for tandem mass spectrometry-based elucidation of metabolites, and specific instrumentation for advanced bioanalysis will enable more comprehensive metabolome analysis for exploring the hidden secrets of metabolism.

Sample Preparation for Bioanalytical and Pharmaceutical Analysis

Biological and pharmaceutical samples represent formidable challenges in sample preparation that hold important consequences for bioanalysis and genotoxic impurity quantification. This Feature will emphasize significant advances toward the development of rapid, sensitive, and selective sample preparation methods.

A non-targeted metabolite profiling pilot study suggests that tryptophan and lipid metabolisms are linked with ADHD-like behaviours in dogs

BACKGROUND

Attention deficit hyperactivity disorder (ADHD) is a prevalent and multifactorial neuropsychiatric disorder in the human population worldwide. Complex etiology and clinical heterogeneity have challenged the research, diagnostics and treatment of the disease. Hyperactive and impulsive behaviour has also been observed in dogs, and they could offer a physiologically relevant model for human ADHD. As a part of our ongoing study to understand the molecular etiology of canine anxiety traits, this study was aimed to pilot an approach to identify metabolic biomarkers in canine ADHD-like behaviours for research, diagnostics and treatment purposes.

METHODS

We collected fresh plasma samples from 22 German Shepherds with varying ADHD-like behaviours. All dogs were on the same controlled diet for 2 weeks prior to sampling. A liquid chromatography combined with mass spectrometry (LC-MS)-based non-targeted metabolite profiling was performed to identify plasma metabolites correlating with the ADHD-like behaviour of the dogs.

RESULTS

649 molecular features correlated with ADHD-like behavioural scores (p_raw < 0.05), and three of them [sn-1 LysoPC(18:3), PC(18:3/18:2) and sn-1 LysoPE(18:2)] had significant correlations also after FDR correction (pFDR < 0.05). Phospholipids were found to negatively correlate with ADHD-like behavioural scores, whereas tryptophan metabolites 3-indolepropionic acid (IPA) and kynurenic acid (KYNA) had negative and positive correlations with ADHD-like behavioural scores, respectively.

CONCLUSIONS

Our study identified associations between canine ADHD-like behaviours and metabolites that are involved in lipid and tryptophan metabolisms. The identified metabolites share similarity with earlier findings in human and rodent ADHD models. However, a larger replication study is warranted to validate the discoveries prior to further studies to understand the biological role of the identified metabolites in canine ADHD-like behaviours.

Establishment of Protocols for Global Metabolomics by LC-MS for Biomarker Discovery

Metabolomics is a promising avenue for biomarker discovery. Although the quality of metabolomic analyses, especially global metabolomics (G-Met) using mass spectrometry (MS), largely depends on the instrumentation, potential bottlenecks still exist at several basic levels in the metabolomics workflow. Therefore, we established a precise protocol initially for the G-Met analyses of human blood plasma to overcome some these difficulties. In our protocol, samples are deproteinized in a 96-well plate using an automated liquid-handling system, and conducted either using a UHPLC-QTOF/MS system equipped with a reverse phase column or a LC-FTMS system equipped with a normal phase column. A normalization protocol of G-Met data was also developed to compensate for intra- and inter-batch differences, and the variations were significantly reduced along with our normalization, especially for the UHPLC-QTOF/MS data with a C18 reverse-phase column for positive ions. Secondly, we examined the changes in metabolomic profiles caused by the storage of EDTA-blood specimens to identify quality markers for the evaluation of the specimens’ pre-analytical conditions. Forty quality markers, including lysophospholipids, dipeptides, fatty acids, succinic acid, amino acids, glucose, and uric acid were identified by G-Met for the evaluation of plasma sample quality and established the equation of calculating the quality score. We applied our quality markers to a small-scale study to evaluate the quality of clinical samples. The G-Met protocols and quality markers established here should prove useful for the discovery and development of biomarkers for a wider range of diseases.

Available technologies and clinical applications of targeted chemotherapy in pancreatic cancer

The incidence of pancreatic cancer, the fourth leading cause of cancer death in United States, is increasing worldwide. Even though the cure rate has doubled in 40 years, it is abysmally poor at 6-7%. As surgical resection remains the only curative treatment and less than 20% of the newly diagnosed cancers are resectable, the major burden of disease management lies in early diagnosis, good prognostication, and proper neo-adjuvant and/or adjuvant therapy. With advancing technologies and their ease of availability, researchers have better tools to understand pancreatic cancer. In the post-genetic era, proteomic, phosphoproteomic, metabolomic, and more have brought us to a multi-omics era. These newer avenues bring promises of better screening modalities, less invasive diagnostics and monitoring, subtyping of pancreatic cancer, and fine tuning the treatment modalities not only to the right stage of tumor but also to the right tumor biology. As the multitudes of technologies are generating extensive amounts of incongruous data, they are giving clinicians a lot of non-actionable information. In this paper, we wish to encompass the newer technologies, sub-classifications, and future treatment modalities in personalized care of patients with pancreatic cancer.

Bridging the gap between comprehensive extraction protocols in plant metabolomics studies and method validation

It is vital to pay much attention to the design of extraction methods developed for plant metabolomics, as any non-extracted or converted metabolites will greatly affect the overall quality of the metabolomics study. Method validation is however often omitted in plant metabolome studies, as the well-established methodologies for classical targeted analyses such as recovery optimization cannot be strictly applied. The aim of the present study is to thoroughly evaluate state-of-the-art comprehensive extraction protocols for plant metabolomics with liquid chromatography-photodiode array-accurate mass mass spectrometry (LC-PDA-amMS) by bridging the gap with method validation. Validation of an extraction protocol in untargeted plant metabolomics should ideally be accomplished by validating the protocol for all possible outcomes, i.e. for all secondary metabolites potentially present in the plant. In an effort to approach this ideal validation scenario, two plant matrices were selected based on their wide versatility of phytochemicals: meadowsweet (Filipendula ulmaria) for its polyphenols content, and spicy paprika powder (from the genus Capsicum) for its apolar phytochemicals content (carotenoids, phytosterols, capsaicinoids). These matrices were extracted with comprehensive extraction protocols adapted from literature and analysed with a generic LC-PDA-amMS characterization platform that was previously validated for broad range phytochemical analysis. The performance of the comprehensive sample preparation protocols was assessed based on extraction efficiency, repeatability and intermediate precision and on ionization suppression/enhancement evaluation. The manuscript elaborates on the finding that none of the extraction methods allowed to exhaustively extract the metabolites. Furthermore, it is shown that depending on the extraction conditions enzymatic degradation mechanisms can occur. Investigation of the fractions obtained with the different extraction methods revealed a low resolving power for phytochemicals for all methods. Nevertheless, an overall good repeatability was observed for all extraction methods, which is essential to allow direct comparison between samples. In summary, no single procedure outperforms the others and compromises will have to be made during method selection.

Profiling Reactive Metabolites via Chemical Trapping and Targeted Mass Spectrometry

Metabolomic profiling studies aim to provide a comprehensive, quantitative, and dynamic portrait of the endogenous metabolites in a biological system. While contemporary technologies permit routine profiling of many metabolites, intrinsically labile metabolites are often improperly measured or omitted from studies due to unwanted chemical transformations that occur during sample preparation or mass spectrometric analysis. The primary glycolytic metabolite 1,3-bisphosphoglyceric acid (1,3-BPG) typifies this class of metabolites, and, despite its central position in metabolism, has largely eluded analysis in profiling studies. Here we take advantage of the reactive acylphosphate group in 1,3-BPG to chemically trap the metabolite with hydroxylamine during metabolite isolation, enabling quantitative analysis by targeted LC-MS/MS. This approach is compatible with complex cellular metabolome, permits specific detection of the reactive (1,3-) instead of nonreactive (2,3-) BPG isomer, and has enabled direct analysis of dynamic 1,3-BPG levels resulting from perturbations to glucose processing. These studies confirmed that standard metabolomic methods misrepresent cellular 1,3-BPG levels in response to altered glucose metabolism and underscore the potential for chemical trapping to be used for other classes of reactive metabolites.

Amino acids in a targeted versus a non-targeted metabolomics LC-MS/MS assay. Are the results consistent?

BACKGROUND

The results of plasma amino acid patterns in samples from kidney transplant patients with good and impaired renal function using a targeted LC-MS/MS amino acid assay and a non-targeted metabolomics assay were compared.

METHODS

EDTA plasma samples were prospectively collected at baseline, 1, 2, 4 and 6months post-transplant (n=116 patients, n=398 samples). Each sample was analyzed using both a commercial amino acid LC-MS/MS assay and a non-targeted metabolomics assay also based on MS/MS ion transitions. The results of both assays were independently statistically analyzed to identify amino acids associated with estimated glomerular filtration rates using correlation and partial least squares-discriminant analysis.

RESULTS

Although there was overlap between the results of the targeted and non-targeted metabolomics assays (tryptophan, 1-methyl histidine), there were also substantial inconsistencies, with the non-targeted assay resulting in more "hits" than the targeted assay. Without further verification of the hits detected by the non-targeted discovery assay, this would have led to different interpretation of the results. There were also false negative results when the non-targeted assay was used (hydroxy proline). Several of said discrepancies could be explained by loss of sensitivity during analytical runs for selected amino acids (serine and threonine), retention time shifts, signals above the range of linear detector response and integration of peaks not separated from background and interferences (aspartate) when the non-targeted metabolomics assay was used.

CONCLUSIONS

Whenever assessment of a specific pathway such as amino acids is the focus of interest, a targeted seems preferable to a non-targeted metabolomics assay.

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.

Alterations of the exo- and endometabolite profiles in breast cancer cell lines: A mass spectrometry-based metabolomics approach

In recent years, knowledge about metabolite changes which are characteristic for the physiologic state of cancer cells has been acquired by liquid chromatography coupled to mass spectrometry. Distinct molecularly characterized breast cancer cell lines provide an unbiased and standardized in vitro tumor model reflecting the heterogeneity of the disease. Tandem mass spectrometry is a widely applied analytical platform and highly sensitive technique for analysis of complex biological samples. Endo- and exometabolite analysis of the breast cancer cell lines MDA-MB-231, -453 and BT-474 as well as the breast epithelial cell line MCF-10A has been performed using two different analytical platforms: UPLC-ESI-Q-TOF based on a scheduled precursor list has been applied for highlighting of significant differences between cell lines and HPLC-ESI-QqQ using multiple reaction monitoring has been utilized for a targeted approach focusing on RNA metabolism and interconnected pathways, respectively. Statistical analysis enabled a clear discrimination of the breast epithelial from the breast cancer cell lines. As an effect of oxidative stress, a decreased GSH/GSSG ratio has been detected in breast cancer cell lines. The triple negative breast cancer cell line MDA-MB-231 showed an elevation in nicotinamide, 1-ribosyl-nicotinamide and NAD+ reflecting the increased energy demand in triple negative breast cancer, which has a more aggressive clinical course than other forms of breast cancer. Obtained distinct metabolite pattern could be correlated with distinct molecular characteristics of breast cancer cells. Results and methodology of this preliminary in vitro study could be transferred to in vivo studies with breast cancer patients.

UHPLC-MS-based metabolomics analysis on mice bearing neoplasm (H22) for hispidulin

Although some physiological and pathological function parameters of hepatitis and liver cancer have been investigated in relation to hispidulin (5,7,4'-trihydroxy-6-methoxyflavone), the changes of small metabolites in biofluids have been reported rarely. Recent research has shown that metabolic profiling with ultra-high-performance liquid chromatography coupled to quadrupole time of flight mass spectrometry (UHPLC-QTOF/MS) coupled with multivariate statistical analysis provides a good understanding of hispidulin effects on mice vaccinated intraperitoneally with H22 tumor cells. Twenty-five potential biomarkers, up- or down-regulated (P<0.05 or 0.01), were identified, and 17 metabolic pathways were constructed. These potential biomarkers underpin the metabolic pathways, which are disturbed in the mice bearing neoplasm (H22). These pathways include pantothenate and CoA biosynthesis; glycine, serine and threonine metabolism; nicotinate and nicotinamide metabolism; steroid hormone biosynthesis; pyrimidine metabolism; and glyoxylate and dicarboxylate metabolism. Furthermore, 4-phosphopantothenoylcysteine, glycine, niacinamide, cortisol, uracil and 5-thymidylic acid are potential biomarkers that may explain the link between hispidulin and the metabolism of mice bearing neoplasm (H22). Most of the potential biomarkers related to the function of TCA (tricarboxylic acid cycle). The rise of potential biomarkers in the drug groups promoted the up-regulation of TCA cycle compared with the model group.

Non-targeted metabolite profiling reveals changes in oxidative stress, tryptophan and lipid metabolisms in fearful dogs

Background

Anxieties, such as shyness, noise phobia and separation anxiety, are common but poorly understood behavioural problems in domestic dogs, Canis familiaris. Although studies have demonstrated genetic and environmental contributions to anxiety pathogenesis, better understanding of the molecular underpinnings is needed to improve diagnostics, management and treatment plans. As a part of our ongoing canine anxiety genetics efforts, this study aimed to pilot a metabolomics approach in fearful and non-fearful dogs to identify candidate biomarkers for more objective phenotyping purposes and to refer to potential underlying biological problem.

Methods

We collected whole blood samples from 10 fearful and 10 non-fearful Great Danes and performed a liquid chromatography combined with mass spectrometry (LC–MS)-based non-targeted metabolite profiling.

Results

Non-targeted metabolomics analysis detected six 932 metabolite entities in four analytical modes [RP and HILIC; ESI(−) and ESI(+)], of which 239 differed statistically between the test groups. We identified changes in 13 metabolites (fold change ranging from 1.28 to 2.85) between fearful and non-fearful dogs, including hypoxanthine, indoxylsulfate and several phospholipids. These molecules are involved in oxidative stress, tryptophan and lipid metabolisms.

Conclusions

We identified significant alterations in the metabolism of fearful dogs, and some of these changes appear relevant to anxiety also in other species. This pilot study demonstrates the feasibility of the non-targeted metabolomics and warrants a larger replication study to confirm the role of the identified biomarkers and pathways in canine anxiety.

Applications of NMR spectroscopy to systems biochemistry

The past decades of advancements in NMR have made it a very powerful tool for metabolic research. Despite its limitations in sensitivity relative to mass spectrometric techniques, NMR has a number of unparalleled advantages for metabolic studies, most notably the rigor and versatility in structure elucidation, isotope-filtered selection of molecules, and analysis of positional isotopomer distributions in complex mixtures afforded by multinuclear and multidimensional experiments. In addition, NMR has the capacity for spatially selective in vivo imaging and dynamical analysis of metabolism in tissues of living organisms. In conjunction with the use of stable isotope tracers, NMR is a method of choice for exploring the dynamics and compartmentation of metabolic pathways and networks, for which our current understanding is grossly insufficient. In this review, we describe how various direct and isotope-edited 1D and 2D NMR methods can be employed to profile metabolites and their isotopomer distributions by stable isotope-resolved metabolomic (SIRM) analysis. We also highlight the importance of sample preparation methods including rapid cryoquenching, efficient extraction, and chemoselective derivatization to facilitate robust and reproducible NMR-based metabolomic analysis. We further illustrate how NMR has been applied in vitro, ex vivo, or in vivo in various stable isotope tracer-based metabolic studies, to gain systematic and novel metabolic insights in different biological systems, including human subjects. The pathway and network knowledge generated from NMR- and MS-based tracing of isotopically enriched substrates will be invaluable for directing functional analysis of other 'omics data to achieve understanding of regulation of biochemical systems, as demonstrated in a case study. Future developments in NMR technologies and reagents to enhance both detection sensitivity and resolution should further empower NMR in systems biochemical research.

Capillary Electrophoresis-Mass Spectrometry for Clinical Metabolomics

In clinical metabolomics, capillary electrophoresis-mass spectrometry (CE-MS) has become a very useful technique for the analysis of highly polar and charged metabolites in complex biologic samples. A comprehensive overview of recent developments in CE-MS for metabolic profiling studies is presented. This review covers theory, CE separation modes, capillary coatings, and practical aspects of CE-MS coupling. Attention is also given to sample pretreatment and data analysis strategies used for metabolomics. The applicability of CE-MS for clinical metabolomics is illustrated using samples ranging from plasma and urine to cells and tissues. CE-MS application to large-scale and quantitative clinical metabolomics is addressed. Conclusions and perspectives on this unique analytic strategy are presented.

iMet-Q: A User-Friendly Tool for Label-Free Metabolomics Quantitation Using Dynamic Peak-Width Determination

Efficient and accurate quantitation of metabolites from LC-MS data has become an important topic. Here we present an automated tool, called iMet-Q (intelligent Metabolomic Quantitation), for label-free metabolomics quantitation from high-throughput MS1 data. By performing peak detection and peak alignment, iMet-Q provides a summary of quantitation results and reports ion abundance at both replicate level and sample level. Furthermore, it gives the charge states and isotope ratios of detected metabolite peaks to facilitate metabolite identification. An in-house standard mixture and a public Arabidopsis metabolome data set were analyzed by iMet-Q. Three public quantitation tools, including XCMS, MetAlign, and MZmine 2, were used for performance comparison. From the mixture data set, seven standard metabolites were detected by the four quantitation tools, for which iMet-Q had a smaller quantitation error of 12% in both profile and centroid data sets. Our tool also correctly determined the charge states of seven standard metabolites. By searching the mass values for those standard metabolites against Human Metabolome Database, we obtained a total of 183 metabolite candidates. With the isotope ratios calculated by iMet-Q, 49% (89 out of 183) metabolite candidates were filtered out. From the public Arabidopsis data set reported with two internal standards and 167 elucidated metabolites, iMet-Q detected all of the peaks corresponding to the internal standards and 167 metabolites. Meanwhile, our tool had small abundance variation (≤ 0.19) when quantifying the two internal standards and had higher abundance correlation (≥ 0.92) when quantifying the 167 metabolites. iMet-Q provides user-friendly interfaces and is publicly available for download at http://ms.iis.sinica.edu.tw/comics/Software_iMet-Q.html.

Metabolomics for undergraduates: Identification and pathway assignment of mitochondrial metabolites

Metabolomics is a key discipline in systems biology, together with genomics, transcriptomics, and proteomics. In this omics cascade, the metabolome represents the biochemical products that arise from cellular processes and is often regarded as the final response of a biological system to environmental or genetic changes. The overall screening approach to identify all the metabolites in a given biological system is called metabolic fingerprinting. Using high-resolution and high-mass accuracy mass spectrometry, large metabolome coverage, sensitivity, and specificity can be attained. Although the theoretical concepts of this methodology are usually provided in life-science programs, hands-on laboratory experiments are not usually accessible to undergraduate students. Even if the instruments are available, there are not simple laboratory protocols created specifically for teaching metabolomics. We designed a straightforward hands-on laboratory experiment to introduce students to this methodology, relating it to biochemical knowledge through metabolic pathway mapping of the identified metabolites. This study focuses on mitochondrial metabolomics since mitochondria have a well-known, medium-sized cellular sub-metabolome. These features facilitate both data processing and pathway mapping. In this experiment, students isolate mitochondria from potatoes, extract the metabolites, and analyze them by high-resolution mass spectrometry (using an FT-ICR mass spectrometer). The resulting mass list is submitted to an online program for metabolite identification, and compounds associated with mitochondrial pathways can be highlighted in a metabolic network map.

Pure ion chromatogram extraction via optimal k-means clustering

A new method called KPIC is proposed for extracting pure ion chromatogram from raw LC-MS data accurately, which is based on optimalk-means clustering. And KPIC can reduces the number of split signals and provide higher quality chromatographic peaks.

Protocol for quality control in metabolic profiling of biological fluids by U(H)PLC-MS

The process of untargeted metabolic profiling/phenotyping of complex biological matrices, i.e., biological fluids such as blood plasma/serum, saliva, bile, and tissue extracts, provides the analyst with a wide range of challenges. Not the least of these challenges is demonstrating that the acquired data are of "good" quality and provide the basis for more detailed multivariate, and other, statistical analysis necessary to detect, and identify, potential biomarkers that might provide insight into the process under study. Here straightforward and pragmatic "quality control (QC)" procedures are described that allow investigators to monitor the analytical processes employed for global, untargeted, metabolic profiling. The use of this methodology is illustrated with an example from the analysis of human urine where an excel spreadsheet of the preprocessed LC-MS output is provided with embedded macros, calculations and visualization plots that can be used to explore the data. Whilst the use of these procedures is exemplified on human urine samples, this protocol is generally applicable to metabonomic/metabolomic profiling of biofluids, tissue and cell extracts from many sources.

The strengths and weaknesses of NMR spectroscopy and mass spectrometry with particular focus on metabolomics research

Mass spectrometry (MS) and nuclear magnetic resonance (NMR) have evolved as the most common techniques in metabolomics studies, and each brings its own advantages and limitations. Unlike MS spectrometry, NMR spectroscopy is quantitative and does not require extra steps for sample preparation, such as separation or derivatization. Although the sensitivity of NMR spectroscopy has increased enormously and improvements continue to emerge steadily, this remains a weak point for NMR compared with MS. MS-based metabolomics provides an excellent approach that can offer a combined sensitivity and selectivity platform for metabolomics research. Moreover, different MS approaches such as different ionization techniques and mass analyzer technology can be used in order to increase the number of metabolites that can be detected. In this chapter, the advantages, limitations, strengths, and weaknesses of NMR and MS as tools applicable to metabolomics research are highlighted.

Some factors that can lead to poor peak shape in hydrophilic interaction chromatography, and possibilities for their remediation

Some factors which present difficulties for obtaining good peak shape in hydrophilic interaction chromatography (HILIC) were studied. The effect of injection solvent composition and volume was systematically investigated using a selection of weak and stronger basic compounds on a hybrid bare silica phase. Increasing the mismatch between the injection solvent (range 95-0% ACNv/v) and the mobile phase (maintained at 95% ACNv/v) gave increasing deterioration in peak shape. With the 2.1mm ID columns used, injections in the mobile phase of increasing volume (1-20 μL) gave poorer peak shape, but the magnitude of the effect was considerably smaller than that of solvent mismatch over this range. Some solute structural features such as galloyl (trihydroxy benzene), catechol (benzene diol) and phosphate (in nucleotides) gave serious peak tailing, attributed to interactions with metals in the stationary phase or the chromatographic hardware. These undesirable effects can be moderated by including complexing agents in the mobile phase, by changing the stationary phase chemistry, or by altering the mobile phase pH.

Enhancing biological analyses with three dimensional field asymmetric ion mobility, low field drift tube ion mobility and mass spectrometry (μFAIMS/IMS-MS) separations

Multidimensional high throughput separations are ideal for analyzing distinct ion characteristics simultaneously in one analysis. We report on the first evaluation of a platform coupling a high speed field asymmetric ion mobility spectrometry microchip (μFAIMS) with drift tube ion mobility and mass spectrometry (IMS-MS). The μFAIMS/IMS-MS platform was used to analyze biological samples and simultaneously acquire multidimensional FAIMS compensation fields, IMS drift times, and accurate ion masses for the detected features. These separations thereby increased the overall measurement separation power, resulting in greater information content and more complete characterization of the complex samples. The separation conditions were optimized for sensitivity and resolving power by the selection of gas compositions and pressures in the FAIMS and IMS separation stages. The resulting performance provided three dimensional separations, benefitting both broad complex mixture studies and targeted analyses by improving isomeric separations and allowing detection of species obscured by interfering peaks.

Monitoring the Response of the Human Urinary Metabolome to Brief Maximal Exercise by a Combination of RP-UPLC-MS and (1)H NMR Spectroscopy

The delineation of exercise biochemistry by utilizing metabolic fingerprinting has become an established strategy. We present a combined RP-UPLC-MS and (1)H NMR strategy, supplemented by photometric assays, to monitor the response of the human urinary metabolome to short maximal exercise. Seventeen male volunteers performed two identical sprint sessions on separate days, consisting of three 80 m maximal runs. Using univariate and multivariate analyses, we followed the fluctuation of 37 metabolites at 1, 1.5, and 2 h postexercise. 2-Hydroxyisovalerate, 2-hydroxybutyrate, 2-oxoisocaproate, 3-methyl-2-oxovalerate, 3-hydroxyisobutyrate, 2-oxoisovalerate, 3-hydroxybutyrate, 2-hydroxyisobutyrate, alanine, pyruvate, and fumarate increased 1 h postexercise and then returned toward baseline. Lactate and acetate were higher than baseline at 1 and 1.5 h. Hypoxanthine and inosine remained above baseline throughout the postexercise period. Urate decreased at 1 h and increased at 1.5 h before returning to baseline. Valine, isoleucine, succinate, citrate, trimethylamine, trimethylamine N-oxide, tyrosine, and formate decreased at 1 h and/or 1.5 h postexercise and then returned to baseline. Creatinine gradually decreased over the sampling period. Glycine, 4-aminohippurate, and hippurate remained below baseline throughout the postexercise period. Our findings show that even one-half minute of maximal exercise elicited major perturbations in human metabolism, several of which persisted for at least 2 h.

Salivary metabolomics in the diagnosis of oral cancer and periodontal diseases

Metabolomics is a systemic study of metabolites, which are small molecules generated by the process of metabolism. The metabolic profile of saliva can provide an early outlook of the changes associated with a wide range of diseases, including oral cancer and periodontal diseases. It is possible to measure levels of disease-specific metabolites using different methods as presented in this study. However, many challenges exist including incomplete understanding of the complicated metabolic pathways of different oral diseases. The review concludes with the discussion on future perspectives of salivary metabolomics from a clinician point of view. Salivary metabolomics may afford a new research avenue to identify local and systemic disorders but also to aid in the design and modification of therapies. A MEDLINE search using keywords "salivary metabolomics" returned 23 results in total, of which seven were omitted for being reviews or letters to the editor. The rest of the articles were used for preparation of the review, 13 of these were published in the last 5 years.

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

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

Translational biomarkers of acetaminophen-induced acute liver injury

Acetaminophen (APAP) is a commonly used analgesic drug that can cause liver injury, liver necrosis and liver failure. APAP-induced liver injury is associated with glutathione depletion, the formation of APAP protein adducts, the generation of reactive oxygen and nitrogen species and mitochondrial injury. The systems biology omics technologies (transcriptomics, proteomics and metabolomics) have been used to discover potential translational biomarkers of liver injury. The following review provides a summary of the systems biology discovery process, analytical validation of biomarkers and translation of omics biomarkers from the nonclinical to clinical setting in APAP-induced liver injury.

Evaluation of steroidomics by liquid chromatography hyphenated to mass spectrometry as a powerful analytical strategy for measuring human steroid perturbations

This review presents the evolution of steroid analytical techniques, including gas chromatography coupled to mass spectrometry (GC-MS), immunoassay (IA) and targeted liquid chromatography coupled to mass spectrometry (LC-MS), and it evaluates the potential of extended steroid profiles by a metabolomics-based approach, namely steroidomics. Steroids regulate essential biological functions including growth and reproduction, and perturbations of the steroid homeostasis can generate serious physiological issues; therefore, specific and sensitive methods have been developed to measure steroid concentrations. GC-MS measuring several steroids simultaneously was considered the first historical standard method for analysis. Steroids were then quantified by immunoassay, allowing a higher throughput; however, major drawbacks included the measurement of a single compound instead of a panel and cross-reactivity reactions. Targeted LC-MS methods with selected reaction monitoring (SRM) were then introduced for quantifying a small steroid subset without the problems of cross-reactivity. The next step was the integration of metabolomic approaches in the context of steroid analyses. As metabolomics tends to identify and quantify all the metabolites (i.e., the metabolome) in a specific system, appropriate strategies were proposed for discovering new biomarkers. Steroidomics, defined as the untargeted analysis of the steroid content in a sample, was implemented in several fields, including doping analysis, clinical studies, in vivo or in vitro toxicology assays, and more. This review discusses the current analytical methods for assessing steroid changes and compares them to steroidomics. Steroids, their pathways, their implications in diseases and the biological matrices in which they are analysed will first be described. Then, the different analytical strategies will be presented with a focus on their ability to obtain relevant information on the steroid pattern. The future technical requirements for improving steroid analysis will also be presented.

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

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

Complementing reversed-phase selectivity with porous graphitized carbon to increase the metabolome coverage in an on-line two-dimensional LC-MS setup for metabolomics

Efficient and robust separation methods are indispensable in modern LC-MS based metabolomics, where high-resolution mass spectrometers are challenged by isomeric and isobaric metabolites. The optimization of chromatographic separation hence remains an invaluable tool in the comprehensive analysis of the chemically diverse intracellular metabolome. While it is widely accepted that a single method with comprehensive metabolome coverage does not exist, the potential of combining different chromatographic selectivities in two-dimensional liquid chromatography is underestimated in the field. Here, we introduce a novel separation system combining reversed-phase and porous graphitized carbon liquid chromatography in a heart-cut on-line two-dimensional setup for mass spectrometry. The proposed experimental setup can be readily implemented using standard HPLC equipment with only one additional HPLC pump and a two-position six-port valve. The method proved to be robust with excellent retention time stability (average 0.4%) even in the presence of biological matrix. Testing the presented approach on a test mixture of 82 relevant intracellular metabolites, the number of metabolites that are retained could be doubled as compared to reversed-phase liquid chromatography alone. The presented work further demonstrates how the distinct selectivity of porous graphitized carbon complements reversed-phase liquid chromatography and extends the metabolome coverage of conventional LC-MS based methods in metabolomics to biologically important, but analytically challenging compound groups such as sugar phosphates. Both metabolic profiling and metabolic fingerprinting benefit from this method's increased separation capabilities that enhance sample throughput and the biological information content of LC-MS data. An inter-platform comparison with GC- and LC-tandem MS analyses confirmed the validity of the presented two-dimensional approach in the analysis of yeast cell extracts from P. pastoris.

Characterization and rapid identification of chemical constituents of NaoXinTong capsules by UHPLC-linear ion trap/Orbitrap mass spectrometry

The BuChang NaoXinTong (BNC) capsule is a well-known, traditional, prescribed Chinese medication for the treatment of cardiovascular and cerebrovascular diseases. Nevertheless, the chemical profile of BNC has not been established. In the present study, ultra-high-pressure liquid chromatography coupled with linear ion trap-Orbitrap tandem mass spectrometry (UHPLC-LTQ-Orbitrap) has been developed for rapid and high-throughput screening of the preliminary chemical profile of BNC in both positive and negative ion modes. Twenty-five compounds were identified as the standard available compounds by comparing the retention time and high-resolution accurate mass. For the standard unavailable compounds, the structures were presumed based on high-accuracy protonated precursors and multi-stage mass spectrometry (MS(n)) using the proposed strategy. In particular, flavones, isoflavones, and tanshinones had the same skeleton. Therefore, the standards were utilized to characterize the fragment pathways and diagnostic fragment ions that could be applied for structural elucidation of their derivatives. Meanwhile, all the constituent groups of the compounds were detected in the individual herbs comprising BNC. Finally, a total of 178 components were identified or tentatively characterized in BNC, including 21 flavones and 6 flavone glycosides, 18 phenanthraquinones, and 22 terpenoids. The identification and structure elucidation of these chemicals provide essential data for further phytochemical studies, quality control, and pharmacological studies of BNC.

Avoiding misannotation of in-source fragmentation products as cellular metabolites in liquid chromatography-mass spectrometry-based metabolomics

Liquid chromatography-mass spectrometry (LC-MS) technology allows for rapid quantitation of cellular metabolites, with metabolites identified by mass spectrometry and chromatographic retention time. Recently, with the development of rapid scanning high-resolution high accuracy mass spectrometers and the desire for high throughput screening, minimal or no chromatographic separation has become increasingly popular. When analyzing complex cellular extracts, however, the lack of chromatographic separation could potentially result in misannotation of structurally related metabolites. Here, we show that, even using electrospray ionization, a soft ionization method, in-source fragmentation generates unwanted byproducts of identical mass to common metabolites. For example, nucleotide-triphosphates generate nucleotide-diphosphates, and hexose-phosphates generate triose-phosphates. We evaluated yeast intracellular metabolite extracts and found more than 20 cases of in-source fragments that mimic common metabolites. Accordingly, chromatographic separation is required for accurate quantitation of many common cellular metabolites.

Solvent system selectivities in countercurrent chromatography using Salicornia gaudichaudiana metabolites as practical example with off-line electrospray mass-spectrometry injection profiling

For the development of an efficient two-stage isolation process for high-speed countercurrent chromatography (HSCCC) with focus on principal metabolites from the ethyl acetate extract of the halophyte plant Salicornia gaudichaudiana, separation selectivities of two different biphasic solvent systems with similar polarities were evaluated using the elution and extrusion approach. Efficiency in isolation of target compounds is determined by the solvent system selectivity and their chronological use in multiple separation steps. The system n-hexane-ethyl acetate-methanol-water (0.5:6:0.5:6, v/v/v/v) resulted in a comprehensive separation of polyphenolic glycosides. The system n-hexane-n-butanol-water (1:1:2, v/v/v) was less universal but was highly efficient in the fractionation of positional isomers such as di-substituted cinnamic acid quinic acid derivatives. Multiple metabolite detection performed on recovered HSCCC tube fractions was done with rapid mass-spectrometry profiling by sequential off-line injections to electrospray mass-spectrometry (ESI-MS/MS). Selective ion traces of metabolites delivered reconstituted preparative HSCCC runs. Molecular weight distribution of target compounds in single HSCCC tube fractions and MS/MS fragment data were available. Chromatographic areas with strong co-elution effects and fractions of pure recoverable compounds were visualized. In total 11 metabolites have been identified and monitored. Result of this approach was a fast isolation protocol for S. gaudichaudiana metabolites using two solvent systems in a strategic sequence. The process could easily be scaled-up to larger lab-scale or industrial recovery.

LC-MS-based absolute metabolite quantification: application to metabolic flux measurement in trypanosomes

Human African trypanosomiasis is a neglected tropical disease caused by the protozoan parasite, Trypanosoma brucei. In the mammalian bloodstream, the trypanosome's metabolism differs significantly from that of its host. For example, the parasite relies exclusively on glycolysis for energy source. Recently, computational and mathematical models of trypanosome metabolism have been generated to assist in understanding the parasite metabolism with the aim of facilitating drug development. Optimisation of these models requires quantitative information, including metabolite concentrations and/or metabolic fluxes that have been hitherto unavailable on a large scale. Here, we have implemented an LC-MS-based method that allows large scale quantification of metabolite levels by using U-¹³C-labelled E.coli extracts as internal standards. Known amounts of labelled E. coli extract were added into the parasite samples, as well as calibration standards, and used to obtain calibration curves enabling us to convert intensities into concentrations. This method allowed us to reliably quantify the changes of 43 intracellular metabolites and 32 extracellular metabolites in the medium over time. Based on the absolute quantification, we were able to compute consumption and production fluxes. These quantitative data can now be used to optimise computational models of parasite metabolism.

Principles and practice of lipidomics

The technical advances in mass spectrometry, particularly the development of (ultra)-high-resolution/mass accuracy measurement capabilities in combination with refinement of soft ionization techniques, have increased the application and success of lipidomics to answer biological questions in relation to lipid metabolism. Together with other omics technologies, lipidomics has become an important tool to practice systems biology as lipids comprise a very significant part of the metabolome and play pleiotropic roles in cellular functions. As an increasing number of disorders are linked to lipid metabolism, lipidomics is used to search for biomarkers, understand disease mechanism and follow the efficacy of therapeutic options. This review provides a first introduction to the major methodological strategies currently used for mass spectrometry-based lipidomics and associated data pre-processing and analysis.

Potential of mass spectrometry metabolomics for chemical food safety

This review aims to describe the most significant applications of mass spectrometry-based metabolomics in the field of chemical food safety. A particular discussion of all the different analytical steps involved in the metabolomics workflow (sample preparation, mass spectrometry analytical platform and data processing) will be addressed.

A short review of applications of liquid chromatography mass spectrometry based metabolomics techniques to the analysis of human urine

Mass spectrometry based metabolomics profiling.