Semi-targeted analysis of metabolites using capillary-flow ion chromatography coupled to high-resolution mass spectrometry

Determination of trace chelating carboxylic acids in rice by green extraction combined with liquid chromatography-mass spectrometry analysis and its application in the evaluation of old and new rice

RATIONALE

Accurate identification of old rice samples from new ones benefits their market circulation and consumers. However, the current detection methods are still not satisfactory because of their insufficient accuracy or (and) time-consuming process.

METHODS

Chelating carboxylic acids (CCAs) were selectively extracted from rice, by stirring with chelating resin and a dilute Na2CO3 solution. The green analytical chemistry guidelines for sample preparation were investigated by using the green chemistry calculator AGREE prep. The extractant was determined by liquid chromatography-mass spectrometry (LC/MS), and statistical analysis of the analytical data was carried out to evaluate the significance of the difference by ChiPlot.

RESULTS

The limit of quantitation for the CCAs is in the range of 1 to 50 ng/mL, with a reasonable reproducibility. The CCAs in 23 rice samples were determined within a wide concentration range from 0.03 to 1174 μg/g. Intriguingly, the content of citric acid, malonic acid, α-ketoglutaric acid and cis-aconite acid in new rice was each found to be distinctively higher than that in old rice by several times. Even mixtures of old and new rice were found to show much difference in the concentration of citric acid and malic acid.

CONCLUSION

A green analytical method has been developed for the simultaneous determination of CCAs by LC/MS analysis, and the identification of old rice samples from new ones was easily carried out according to their CCA content for the first time. The results indicated that the described method has powerful potential for the accurate identification of old rice samples from new ones.

Applications of chromatographic methods in metabolomics: A review

Chromatography is a robust and reliable separation method that can use various stationary phases to separate complex mixtures commonly seen in metabolomics. This review examines the types of chromatography and stationary phases that have been used in targeted or untargeted metabolomics with methods such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. General considerations for sample pretreatment and separations in metabolomics are considered, along with the various supports and separation formats for chromatography that have been used in such work. The types of liquid chromatography (LC) that have been most extensively used in metabolomics will be examined, such as reversed-phase liquid chromatography and hydrophilic liquid interaction chromatography. In addition, other forms of LC that have been used in more limited applications for metabolomics (e.g., ion-exchange, size-exclusion, and affinity methods) will be discussed to illustrate how these techniques may be utilized for new and future research in this field. Multidimensional LC methods are also discussed, as well as the use of gas chromatography and supercritical fluid chromatography in metabolomics. In addition, the roles of chromatography in NMR- vs. MS-based metabolomics are considered. Applications are given within the field of metabolomics for each type of chromatography, along with potential advantages or limitations of these separation methods.

Toward a More Comprehensive Approach for Dissolved Organic Matter Chemical Characterization Using an Orbitrap Fusion Tribrid Mass Spectrometer Coupled with Ion and Liquid Chromatography Techniques

Dissolved organic matter (DOM) represents one of the largest active organic carbon pools in the global carbon cycle. Although extensively studied, only <10% of DOM has been chemically characterized into individual dissolved compounds due to its molecular complexity. This study introduced a more comprehensive DOM characterization method by coupling both ion chromatography (IC) and liquid chromatography (LC) with high mass accuracy and resolution mass spectrometry. We presented a new on-the-fly mass calibration of the Orbitrap technique by utilizing the "lock mass" function in the Orbitrap Fusion Tribrid mass spectrometer (OT-FTMS), which assures high mass accuracy at every scan by a postcolumn introduction of internal labeled standards. With both IC and LC, tested unlabeled standards of amino acids, small peptides, and organic acids were consistently below 1.0 ppm mass error, giving the OT-FTMS the potential of reaching mass accuracy of the Fourier-transform ion cyclotron resonance mass spectrometer. In addition to mass accuracy, a pooled quality control sample (QC) was used to increase reproducibility by applying systematic error removal using random forest (SERRF). Using an untargeted mass spectrometry approach, estuarine DOM samples were analyzed by OT-FTMS coupled to IC in negative mode and LC in positive mode detection to cover a wide range of highly cationic to highly anionic molecules. As a proof of concept, we focused on elucidating the structures of three distinct DOM compound classes with varied acidities and basicities. In UPLC-OT-FTMS, a total of 915 compounds were detected. We putatively elucidated 44 small peptides and 33 deaminated peptides of these compounds. With IC-OT-FTMS, a total of 1432 compounds were detected. We putatively elucidated 20 peptides, 268 deaminated peptides, and 188 organic acids. Except for five compounds, all putatively elucidated compounds were uniquely detected in their corresponding chromatography technique. These results highlight the need for combining these two techniques to provide a more comprehensive method for DOM characterization. Application of the combined IC and LC techniques is not limited to DOM chemical characterization. It can analyze other complex compound mixtures, such as metabolites, and anthropogenic pollutants, such as pesticides and endocrine-disrupting chemicals, in environmental and biological samples.

Targeted metabolomics reveals the aberrant energy status in diabetic peripheral neuropathy and the neuroprotective mechanism of traditional Chinese medicine JinMaiTong

Diabetic peripheral neuropathy (DPN) is a common and devastating complication of diabetes, for which effective therapies are currently lacking. Disturbed energy status plays a crucial role in DPN pathogenesis. However, the integrated profile of energy metabolism, especially the central carbohydrate metabolism, remains unclear in DPN. Here, we developed a metabolomics approach by targeting 56 metabolites using high-performance ion chromatography-tandem mass spectrometry (HPIC-MS/MS) to illustrate the integrative characteristics of central carbohydrate metabolism in patients with DPN and streptozotocin-induced DPN rats. Furthermore, JinMaiTong (JMT), a traditional Chinese medicine (TCM) formula, was found to be effective for DPN, improving the peripheral neurological function and alleviating the neuropathology of DPN rats even after demyelination and axonal degeneration. JMT ameliorated DPN by regulating the aberrant energy balance and mitochondrial functions, including excessive glycolysis restoration, tricarboxylic acid cycle improvement, and increased adenosine triphosphate (ATP) generation. Bioenergetic profile was aberrant in cultured rat Schwann cells under high-glucose conditions, which was remarkably corrected by JMT treatment. In-vivo and in-vitro studies revealed that these effects of JMT were mainly attributed to the activation of adenosine monophosphate (AMP)-activated protein kinase (AMPK) and downstream peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α). Our results expand the therapeutic framework for DPN and suggest the integrative modulation of energy metabolism using TCMs, such as JMT, as an effective strategy for its treatment.

Simultaneous Quantitation and Discovery (SQUAD) Analysis: Combining the Best of Targeted and Untargeted Mass Spectrometry-Based Metabolomics

Untargeted and targeted approaches are the traditional metabolomics workflows acquired for a wider understanding of the metabolome under focus. Both approaches have their strengths and weaknesses. The untargeted, for example, is maximizing the detection and accurate identification of thousands of metabolites, while the targeted is maximizing the linear dynamic range and quantification sensitivity. These workflows, however, are acquired separately, so researchers compromise either a low-accuracy overview of total molecular changes (i.e., untargeted analysis) or a detailed yet blinkered snapshot of a selected group of metabolites (i.e., targeted analysis) by selecting one of the workflows over the other. In this review, we present a novel single injection simultaneous quantitation and discovery (SQUAD) metabolomics that combines targeted and untargeted workflows. It is used to identify and accurately quantify a targeted set of metabolites. It also allows data retro-mining to look for global metabolic changes that were not part of the original focus. This offers a way to strike the balance between targeted and untargeted approaches in one single experiment and address the two approaches' limitations. This simultaneous acquisition of hypothesis-led and discovery-led datasets allows scientists to gain more knowledge about biological systems in a single experiment.

Trypanosoma brucei: Metabolomics for analysis of cellular metabolism and drug discovery

BACKGROUND

Trypanosoma brucei is the causative agent of Human African Trypanosomiasis (also known as sleeping sickness), a disease causing serious neurological disorders and fatal if left untreated. Due to its lethal pathogenicity, a variety of treatments have been developed over the years, but which have some important limitations such as acute toxicity and parasite resistance. Metabolomics is an innovative tool used to better understand the parasite's cellular metabolism, and identify new potential targets, modes of action and resistance mechanisms. The metabolomic approach is mainly associated with robust analytical techniques, such as NMR and Mass Spectrometry. Applying these tools to the trypanosome parasite is, thus, useful for providing new insights into the sleeping sickness pathology and guidance towards innovative treatments.

AIM OF REVIEW

The present review aims to comprehensively describe the T. brucei biology and identify targets for new or commercialized antitrypanosomal drugs. Recent metabolomic applications to provide a deeper knowledge about the mechanisms of action of drugs or potential drugs against T. brucei are highlighted. Additionally, the advantages of metabolomics, alone or combined with other methods, are discussed.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Compared to other parasites, only few studies employing metabolomics have to date been reported on Trypanosoma brucei. Published metabolic studies, treatments and modes of action are discussed. The main interest is to evaluate the metabolomics contribution to the understanding of T. brucei's metabolism.

Anion Exchange Chromatography Coupled to Electrospray-Mass Spectrometry: An Efficient Tool for Food, Environment, and Biological Analysis

For over 50 years, ion chromatography has been demonstrated to be a successful technique used to quantify a wide range of ions and ionizable compounds, either organic or inorganic, in various matrices using conductimetric or electrochemical detection. It was only since 1996 that ion chromatography was coupled to electrospray-mass spectrometry, opening the field to new applications in complex matrices and the detection of compounds at trace levels. This review covers the recent developments of ion exchange chromatography and mass spectrometry. It focuses on the choice of mobile phases, column geometry, suppressors, make-up solvents and type of ionization sources reported in the literature. A brief overview of a large range of applications in food analysis, environmental analysis and bioanalysis is presented, and performances are discussed.

Analytical Platforms for Mass Spectrometry-Based Metabolomics of Polar and Ionizable Metabolites

Metabolomics studies rely on the availability of suitable analytical platforms to determine a vast collection of chemically diverse metabolites in complex biospecimens. Liquid chromatography-mass spectrometry operated under reversed-phase conditions is the most commonly used platform in metabolomics, which offers extensive coverage for nonpolar and moderately polar compounds. However, complementary techniques are required to obtain adequate separation of polar and ionic metabolites, which are involved in several fundamental metabolic pathways. This chapter focuses on the main mass-spectrometry-based analytical platforms used to determine polar and/or ionizable compounds in metabolomics (GC-MS, HILIC-MS, CE-MS, IPC-MS, and IC-MS). Rather than comprehensively describing recent applications related to GC-MS, HILIC-MS, and CE-MS, which have been covered in a regular basis in the literature, a brief discussion focused on basic principles, main strengths, limitations, as well as future trends is presented in this chapter, and only key applications with the purpose of illustrating important analytical aspects of each platform are highlighted. On the other hand, due to the relative novelty of IPC-MS and IC-MS in the metabolomics field, a thorough compilation of applications for these two techniques is presented here.

Targeted Phosphoinositides Analysis Using High-Performance Ion Chromatography-Coupled Selected Reaction Monitoring Mass Spectrometry

Phosphoinositides are minor components of cell membranes, but play crucial roles in numerous signal transduction pathways. To obtain quantitative measures of phosphoinositides, sensitive, accurate, and comprehensive methods are needed. Here, we present a quantitative targeted ion chromatography-mass spectrometry-based workflow that separates phosphoinositide isomers and increases the quantitative accuracy of measured phosphoinositides. Besides testing different analytical characteristics such as extraction and separation efficiency, the reproducibility of the developed workflow was also investigated. The workflow was verified in resting and stimulated human platelets, fat cells, and rat hippocampal brain tissue, where the LOD and LOQ for phosphoinositides were at 312.5 and 625 fmol, respectively. The robustness of the workflow is shown with different applications that confirms its suitability to analyze multiple less-abundant phosphoinositides.

Ion Chromatography with Mass Spectrometry for Metabolomic Analysis

Ion chromatography (IC) represents an important technique for separation of charged and polar compounds. Traditionally, IC is often used for the analysis of small inorganic ions. Due to the development of eluent suppression technology that allows continuous online desalting and conversion of high-salt eluents into pure water, IC has been coupled with mass spectrometry (MS) for the analysis of more diverse range of anionic and cationic analytes. Recent studies have demonstrated that IC-MS is a powerful technique with exquisite detection sensitivity, high reproducibility, and quantitative capability for metabolomic analysis. In this chapter, we provide a brief overview of IC principles and IC-MS for metabolomic analysis.

An Ion Chromatography-Ultrahigh-Resolution-MS1/Data-Independent High-Resolution MS2 Method for Stable Isotope-Resolved Metabolomics Reconstruction of Central Metabolic Networks

The metabolome comprises a complex network of interconnecting enzyme-catalyzed reactions that involve transfers of numerous molecular subunits. Thus, the reconstruction of metabolic networks requires metabolite substructures to be tracked. Subunit tracking can be achieved by tracing stable isotopes through metabolic transformations using NMR and ultrahigh -resolution (UHR)-mass spectrometry (MS). UHR-MS¹ readily resolves and counts isotopic labels in metabolites but requires tandem MS to help identify isotopic enrichment in substructures. However, it is challenging to perform chromatography-based UHR-MS¹ with its long acquisition time, while acquiring MS² data on many coeluting labeled isotopologues for each metabolite. We have developed an ion chromatography (IC)-UHR-MS¹/data-independent(DI)-HR-MS² method to trace the fate of ¹³C atoms from [¹³C₆]-glucose ([¹³C₆]-Glc) in 3D A549 spheroids in response to anticancer selenite and simultaneously ¹³C/¹⁵N atoms from [¹³C₅,¹⁵N₂]-glutamine ([¹³C₅,¹⁵N₂]-Gln) in 2D BEAS-2B cells in response to arsenite transformation. This method retains the complete isotopologue distributions of metabolites via UHR-MS¹ while simultaneously acquiring substructure label information via DI-MS². These details in metabolite labeling patterns greatly facilitate rigorous reconstruction of multiple, intersecting metabolic pathways of central metabolism, which are illustrated here for the purine/pyrimidine nucleotide biosynthesis. The pathways reconstructed based on subunit-level isotopologue analysis further reveal specific enzyme-catalyzed reactions that are impacted by selenite or arsenite treatments.

Metabolite Structure Assignment Using In Silico NMR Techniques

A major challenge for metabolomic analysis is to obtain an unambiguous identification of the metabolites detected in a sample. Among metabolomics techniques, NMR spectroscopy is a sophisticated, powerful, and generally applicable spectroscopic tool that can be used to ascertain the correct structure of newly isolated biogenic molecules. However, accurate structure prediction using computational NMR techniques depends on how much of the relevant conformational space of a particular compound is considered. It is intrinsically challenging to calculate NMR chemical shifts using high-level DFT when the conformational space of a metabolite is extensive. In this work, we developed NMR chemical shift calculation protocols using a machine learning model in conjunction with standard DFT methods. The pipeline encompasses the following steps: (1) conformation generation using a force field (FF)-based method, (2) filtering the FF generated conformations using the ASE-ANI machine learning model, (3) clustering of the optimized conformations based on structural similarity to identify chemically unique conformations, (4) DFT structural optimization of the unique conformations, and (5) DFT NMR chemical shift calculation. This protocol can calculate the NMR chemical shifts of a set of molecules using any available combination of DFT theory, solvent model, and NMR-active nuclei, using both user-selected reference compounds and/or linear regression methods. Our protocol reduces the overall computational time by 2 orders of magnitude over methods that optimize the conformations using fully ab initio methods, while still producing good agreement with experimental observations. The complete protocol is designed in such a manner that makes the computation of chemical shifts tractable for a large number of conformationally flexible metabolites.

Applications of Chromatography-Ultra High-Resolution MS for Stable Isotope-Resolved Metabolomics (SIRM) Reconstruction of Metabolic Networks

Metabolism is a complex network of compartmentalized and coupled chemical reactions, which often involve transfers of substructures of biomolecules, thus requiring metabolite substructures to be tracked. Stable isotope resolved metabolomics (SIRM) enables pathways reconstruction, even among chemically identical metabolites, by tracking the provenance of stable isotope-labeled substructures using NMR and ultrahigh resolution (UHR) MS. The latter can resolve and count isotopic labels in metabolites and can identify isotopic enrichment in substructures when operated in tandem MS mode. However, MS2 is difficult to implement with chromatography-based UHR-MS due to lengthy MS1 acquisition time that is required to obtain the molecular isotopologue count, which is further exacerbated by the numerous isotopologue source ions to fragment. We review here recent developments in tandem MS applications of SIRM to obtain more detailed information about isotopologue distributions in metabolites and their substructures.

The use of a double coaxial electrospray ionization sprayer improves the peak resolutions of anionic metabolites in capillary ion chromatography-mass spectrometry

Recently, ion chromatography coupled with mass spectrometry has been used for the determination of anionic metabolites. However, connection with a mass spectrometer in this method is not straightforward because backpressure produced by the addition of a make-up solution often affects the peak resolutions of the target metabolites. To overcome this problem, we developed a capillary ion chromatography-mass spectrometry method utilizing a double coaxial electrospray ionization sprayer. This method was not affected by backpressure and the number of theoretical plates was about three times that of a conventional sprayer. Under optimized conditions, 44 anionic metabolites, including organic acids, sugar phosphates, nucleotides, and cofactors, were successfully separated and selectively detected with a Q Exactive mass spectrometer. The calibration curves of the tested metabolites showed excellent linearity within the range of 1-100,000 nmol/L and the correlation coefficient was greater than 0.991. The detection limits for these metabolites were between 1 and 500 nmol/L (0.4 and 200 fmol). The developed method was applied to the quantitation of anionic metabolites in cultured cancer cell samples with tumor necrosis factor (TNF)-α stimulation. This allowed for the successful determination of 105 metabolites. The levels of tricarboxylic acid cycle intermediates changed significantly after TNF-α stimulation. These results demonstrate that the developed method is a promising new tool for comprehensive analysis of anionic metabolites.

Targeted and non-targeted forensic profiling of black powder substitutes and gunshot residue using gradient ion chromatography - high resolution mass spectrometry (IC-HRMS)

A novel and simplified gradient IC-HRMS approach is presented in this work for forensic profiling of ionic energetic material residues, including low-order explosives and gunshot residue (GSR). This new method incorporated ethanolic eluents to facilitate direct coupling of IC and HRMS without auxiliary post-column infusion pumps that are traditionally used to assist with gas phase transfer. Ethanolic eluents also enabled better integration with an in-service protocol for direct analysis of high-order organic explosives by IC-HRMS, without requiring solvent exchange before injection. Excellent method performance was achieved, enabling both full scan qualitative and quantitative analysis, as required. In particular, linearity for 19 targeted compounds yielded R² > 0.99 across several orders of magnitude, with trace analysis possible at the low-mid pg level. Reproducibility and mass accuracies were also excellent, with peak area %RSDs <10%, t_R %RSDs <0.4% and δ_m/z < 3 ppm. The method was applied to targeted analysis of latent fingermarks and swabbed hand sweat samples to determine contact with a black-powder substitute containing nitrate, benzoate and perchlorate. When combined with principal component analysis (PCA), the effect of time since handling on recorded signals could be interpreted further in order to support forensic investigations. In a second, non-targeted application, PCA using full scan IC-HRMS data enabled classification of GSR from three different types of ammunition. An additional 20 markers of GSR were tentatively identified in silico, in addition to the 15 anions detected during targeted analysis. This new approach therefore streamlines and adds consistency and flexibility to forensic analysis of ionic energetic material. Furthermore, it also has implications for targeted, non-targeted and suspect screening applications in other fields by expanding the separation space to low molecular weight inorganic and organic anions.

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.

Absolute Quantification of ppGpp and pppGpp by Double-Spike Isotope Dilution Ion Chromatography-High-Resolution Mass Spectrometry

Guanosine 5'-diphosphate 3'-diphosphate (ppGpp) and guanosine 5'-triphosphate 3'-diphosphate (pppGpp) play a central role in the adaptation of bacterial and plant cells to nutritional and environmental stresses and in bacterial resistance to antibiotics. These compounds have historically been detected and quantified by two-dimensional thin-layer chromatography of ³²P-radiolabeled nucleotides. We report a new method to quantify ppGpp and pppGpp in complex biochemical matrix using ion chromatography coupled to high-resolution mass spectrometry. The method is based on isotopic dilution mass spectrometry (IDMS) using ¹³C to accurately quantify the nucleotides. However, the loss of a phosphate group from pppGpp during the sample preparation process results in the erroneous quantification of ppGpp. This bias was corrected by adding an extra ¹⁵N isotope dilution dimension. This double-spike IDMS method was applied to quantify the ppGpp and pppGpp in Escherichia coli and in a mutant strain deleted for gppA (encoding the ppGpp phosphohydrolase) before and after exposure of both strains to serine hydroxamate, known to trigger the accumulation of these nucleotides.

Illuminating the dark metabolome to advance the molecular characterisation of biological systems

BACKGROUND

The latest version of the Human Metabolome Database (v4.0) lists 114,100 individual entries. Typically, however, metabolomics studies identify only around 100 compounds and many features identified in mass spectra are listed only as 'unknown compounds'. The lack of ability to detect all metabolites present, and fully identify all metabolites detected (the dark metabolome) means that, despite the great contribution of metabolomics to a range of areas in the last decade, a significant amount of useful information from publically funded studies is being lost or unused each year. This loss of data limits our potential gain in knowledge and understanding of important research areas such as cell biology, environmental pollution, plant science, food chemistry and health and biomedical research. Metabolomics therefore needs to develop new tools and methods for metabolite identification to advance as a field.

AIM OF REVIEW

In this critical review, some potential issues with metabolite identification are identified and discussed. New and novel emerging technologies and tools which may contribute to expanding the number of compounds identified in metabolomics studies (thus illuminating the dark metabolome) are reviewed. The aim is to stimulate debate and research in the molecular characterisation of biological systems to drive forward metabolomic research.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The work specifically discusses dynamic nuclear polarisation nuclear magnetic resonance spectroscopy (DNP-NMR), non-proton NMR active nuclei, two-dimensional liquid chromatography (2DLC) and Raman spectroscopy (RS). It is suggested that developing new methods for metabolomics with these techniques could lead to advances in the field and better characterisation of biological systems.

Improved phosphometabolome profiling applying isotope dilution strategy and capillary ion chromatography-tandem mass spectrometry

The phosphometabolome is comprised of all phosphorylated metabolites including the major metabolite classes sugar phosphates and nucleoside phosphates. Phosphometabolites are invaluable in any cell as a part of primary- and energy- metabolism, and as building blocks in the biosynthesis of macromolecules. Here, we report quantitative profiling of the phosphometabolome by applying capillary ion chromatography-tandem mass spectrometry (capIC-MS/MS), ensuring improved chromatographic separation, robustness and quantitative precision. Baseline separation was achieved for six out of eight tested hexose phosphates. Quantitative precision and reproducibility was improved by introducing a fully uniformly (U) ¹³C-labeled biological extract and applying an isotope dilution (ID) correction strategy. A ¹³C-labeled biological extract does in principle contain internal standards (IS) for all metabolites, but low abundant metabolites pose a challenge, and solutions to this are discussed. The extreme reproducibility and reliability of this capIC-MS/MS method was demonstrated by running the instrumentation continuously for ten days.

Anion-Exchange Chromatography Coupled to High-Resolution Mass Spectrometry: A Powerful Tool for Merging Targeted and Non-targeted Metabolomics

In this work, simultaneous targeted metabolic profiling by isotope dilution and non-targeted fingerprinting is proposed for cancer cell studies. The novel streamlined metabolomics workflow was established using anion-exchange chromatography (IC) coupled to high-resolution mass spectrometry (MS). The separation time of strong anion-exchange (2 mm column, flow rate 380 μL min^-1, injection volume 5 μL) could be decreased to 25 min for a target list comprising organic acids, sugars, sugar phosphates, and nucleotides. Internal standardization by fully ¹³C labeled Pichia pastoris extracts enabled absolute quantification of the primary metabolites in adherent cancer cell models. Limits of detection (LODs) in the low nanomolar range and excellent intermediate precisions of the isotopologue ratios (on average <5%, N = 5, over 40 h) were observed. As a result of internal standardization, linear dynamic ranges over 4 orders of magnitude (5 nM-50 μM, R² > 0.99) were obtained. Experiments on drug-sensitive versus resistant SW480 cancer cells showed the feasibility of merging analytical tasks into one analytical run. Comparing fingerprinting with and without internal standard proved that the presence of the ¹³C labeled yeast extract required for absolute quantification was not detrimental to non-targeted data evaluation. Several interesting metabolites were discovered by accurate mass and comparing MS2 spectra (acquired in ddMS2 mode) with spectral libraries. Significant differences revealed distinct metabolic phenotypes of drug-sensitive and resistant SW480 cells.

Use of Ion Chromatography/Mass Spectrometry for Targeted Metabolite Profiling of Polar Organic Acids

Organic acids (OAs) serve as metabolites that play pivotal roles in a host of different metabolic and regulatory pathways. The polar nature of many OAs poses a challenge to their measurement using widely practiced analytical methods. In this study, a targeted metabolomics method was developed using ion chromatography/triple quadrupole mass spectrometry (IC/MS) to quantitate 28 polar OAs with limits of quantitation ranging from 0.25 to 50 μM. The interday assay precisions ranged from 1% to 19%, with accuracies ranging from 82% to 115%. The IC/MS assay was used to quantitate OAs in quadriceps muscle from sedentary mice compared to fatigued mice subjected to either a low intensity, long duration (LILD) or high intensity, short duration (HISD) forced treadmill regimen. Among the OAs examined, significant differences were detected for hippuric acid, malic acid, fumaric acid, and 2-ketoglutaric acid between the sedentary and fatigued mice. In conclusion, the IC/MS method enabled the separation and quantitative survey of a broad range of polar OAs that are difficult to analyze by chromatographic techniques.

Liquid chromatography/tandem mass spectrometry method for simultaneous quantification of eight endogenous nucleotides and the intracellular gemcitabine metabolite dFdCTP in human peripheral blood mononuclear cells

Quantification of endogenous nucleotides is of interest for investigation of numerous cellular biochemical processes, such as energy metabolism and signal transduction, and may also be applied in cancer and antiretroviral therapies in which nucleoside analogues are used. For these purposes we developed and validated a sensitive and high accuracy ion-pair liquid chromatography tandem mass spectrometry (IP LC-MS/MS) method for simultaneous quantification of eight endogenous nucleotides (ATP, CTP, GTP, UTP, dATP, dCTP, dGTP, dTTP) and 2',2'-difluoro-2'-deoxycytidine triphosphate (dFdCTP), an intracellular metabolite of the nucleoside analogue gemcitabine. The assay was validated using 200μL aliquots of peripheral blood mononuclear cell (20×10(6)cells/ml, 4×10(6)cells) extracts, pretreated with activated charcoal and spiked with unlabeled nucleotides, deoxynucleotides and dFdCTP. Analytes were extracted by simple precipitation with cold 60% methanol containing isotope labeled internal standards and separated on a porous graphitic carbon column. For method validation, the concentration ranges were: 0.125-20.8pmol injected for deoxynucleotides, 0.25-312.5pmol injected for dFdCTP and 5-3200pmol injected for nucleotides. The highest coefficients of variation (CV) were 12.1% for within run assay and 11.4% for between run assay, both representing the precision at the lowest analyte concentrations. The method was applied to monitor dFdCTP and changes in endogenous nucleotides in patients who were receiving gemcitabine infusions.

Systems Biology Approaches Applied to Regenerative Medicine

Systems biology is the creation of theoretical and mathematical models for the study of biological systems, as an engine for hypothesis generation and to provide context to experimental data. It is underpinned by the collection and analysis of complex datasets from different biological systems, including global gene, RNA, protein and metabolite profiles. Regenerative medicine seeks to replace or repair tissues with compromised function (for example, through injury, deficiency or pathology), in order to improve their functionality. In this paper, we will address the application of systems biology approaches to the study of regenerative medicine, with a particular focus on approaches to study modifications to the genome, transcripts and small RNAs, proteins and metabolites.

Crystal structure of an arginase-like protein from Trypanosoma brucei that evolved without a binuclear manganese cluster

The X-ray crystal structure of an arginase-like protein from the parasitic protozoan Trypanosoma brucei, designated TbARG, is reported at 1.80 and 2.38 Å resolution in its reduced and oxidized forms, respectively. The oxidized form of TbARG is a disulfide-linked hexamer that retains the overall architecture of a dimer of trimers in the reduced form. Intriguingly, TbARG does not contain metal ions in its putative active site, and amino acid sequence comparisons indicate that all but one of the residues required for coordination to the catalytically obligatory binuclear manganese cluster in other arginases are substituted here with residues incapable of metal ion coordination. Therefore, the structure of TbARG is the first of a member of the arginase/deacetylase superfamily that is not a metalloprotein. Although we show that metal binding activity is easily reconstituted in TbARG by site-directed mutagenesis and confirmed in X-ray crystal structures, it is curious that this protein and its parasitic orthologues evolved away from metal binding function. Knockout of the TbARG gene from the genome demonstrated that its function is not essential to cultured bloodstream-form T. brucei, and metabolomics analysis confirmed that the enzyme has no role in the conversion of l-arginine to l-ornithine in these cells. While the molecular function of TbARG remains enigmatic, the fact that the T. brucei genome encodes only this protein and not a functional arginase indicates that the parasite must import l-ornithine from its host to provide a source of substrate for ornithine decarboxylase in the polyamine biosynthetic pathway, an active target for the development of antiparasitic drugs.

Metabolomics – the complementary field in systems biology: a review on obesity and type 2 diabetes

This paper highlights the metabolomic roles in systems biology towards the elucidation of metabolic mechanisms in obesity and type 2 diabetes.

Hyphenation of capillary high-performance ion-exchange chromatography with mass spectrometry using sheath-flow electrospray ionization

RATIONALE

Mass spectrometry (MS) is an attractive method for extending capillary-size ion chromatography (cHPIC) to create a valuable technique for speciation analysis. For hyphenation, the aqueous effluent of cHPIC has to be transformed into a volatile mixture for MS while preserving analytical concentrations as well as peak shapes during transfer from cHPIC to MS. Finally, the approach should technically be flexible and easy-to-use. A combination of cHPIC and sheath-flow electrospray ionization (ESI)-MS offers to solve all these challenges.

METHODS

cHPIC/sheath-flow-ESI-TOFMS was used in this study for the speciation analysis of various arsenic model compounds. These model compounds were analyzed with different hyphenation setups and configurations of cHPIC/MS and their respective assets and drawbacks were examined and discussed. The parameters (flow rate and composition of sheath liquid) of sheath-flow ESI and their influence on the performance of the spray and the sensitivity of the detector were investigated and compared with those of sheathless ESI.

RESULTS

Using an injection valve to couple cHPIC and MS was found to be the best method for hyphenation, since it constitutes a flexible and dead-volume-free approach. The investigation of sheath-flow ESI revealed that the flow rate of the sheath liquid has to resemble the flow rate of the IC effluent to ensure a stable spray and that a composition of 2-propanol/water/ammonia at 50:50:0.2 (v/v/v) suits most applications without unilaterally promoting the sensitivity for either organic or inorganic compounds. The optimized setup and conditions were successfully applied to the analysis of a mixture of important arsenic species and used to determine limits of detection of organic and inorganic arsenic species (3.7 µg L(-1) elemental arsenic).

CONCLUSIONS

A method for cHPIC/sheath-flow-ESI-MS was developed. The method was shown to be a valuable tool for speciation and trace analysis. It features no dead volume, fast transfer from IC to MS, only minimal peak-widening, high reproducibility, and the ability to fine-tune the ESI spray for higher sensitivity and stability by adjusting the composition of the sheath-liquid.

Current state-of-the-art of nontargeted metabolomics based on liquid chromatography-mass spectrometry with special emphasis in clinical applications

Metabolomics, as a part of systems biology, has been widely applied in different fields of life science by studying the endogenous metabolites. The development and applications of liquid chromatography (LC) coupled with high resolution mass spectrometry (MS) greatly improve the achievable data quality in non-targeted metabolic profiling. However, there are still some emerging challenges to be covered in LC-MS based metabolomics. Here, recent approaches about sample collection and preparation, instrumental analysis, and data handling of LC-MS based metabolomics are summarized, especially in the analysis of clinical samples. Emphasis is put on the improvement of analytical techniques including the combination of different LC columns, isotope coded derivatization methods, pseudo-targeted LC-MS method, new data analysis algorithms and structural identification of important metabolites.

Assessment of capillary anion exchange ion chromatography tandem mass spectrometry for the quantitative profiling of the phosphometabolome and organic acids in biological extracts

Metabolic profiling has become an important tool in biological research, and the chromatographic separation of metabolites coupled with mass spectrometric detection is the most frequently used approach for such studies. The establishment of robust chromatographic methods for comprehensive coverage of the anionic metabolite pool is especially challenging. In this study, the development of a capillary ion exchange chromatography (capIC) - negative ESI tandem mass spectrometry (MS/MS) workflow for the quantitative profiling of the phosphometabolome (e.g., sugar phosphates and nucleotides) is presented. The chromatographic separation and MS/MS conditions were optimized, and the precision of repetitive injections and accuracy in terms of error percentage to true concentration were assessed. The precision is excellent for a capillary flow system with an average CV% of 8.5% for a 50-fmol standard injection and in the lower 2.4-4.4% range for higher concentrations (500-7,500 fmol). The limit of detection (LOD) ranges from 1 to 100 nM (5-500 fmol injected on column), and the limit of quantitation (LOQ) ranges from 1 to 500 nM (5-2,500 fmol injected on column). A fast gradient method with the injection of 50% methanol in water between analytical samples is needed to eliminate carry-over and ensure optimal re-equilibration of the column. Finally, the quantitative applicability of the system was tested on real biological matrices using the constant-volume standard addition method (SAM). Extracts of the human kidney Hek293 cell line were spiked with increasing concentrations of standards to determine the concentration of each metabolite in the sample. Forty-four metabolites were detected with an average uncertainty of 4.1%. Thus, the capIC-MS/MS method exhibits excellent selectivity, sensitivity and precision for the quantitative profiling of the phosphometabolome.

Derivatization of the tricarboxylic acid intermediates with O-benzylhydroxylamine for liquid chromatography-tandem mass spectrometry detection

The tricarboxylic acid (TCA) cycle is an interface among glycolysis, lipid metabolism, and amino acid metabolism. Increasing interest in cancer metabolism has created a demand for rapid and sensitive methods for quantifying the TCA cycle intermediates and related organic acids. We have developed a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to quantify the TCA cycle intermediates in a 96-well format after O-benzylhydroxylamine (O-BHA) derivatization under aqueous conditions. This method was validated for quantitation of all common TCA cycle intermediates with good sensitivity, including α-ketoglutarate, malate, fumarate, succinate, 2-hydroxyglutarate, citrate, oxaloacetate, pyruvate, isocitrate, and lactate using a 8-min run time in cancer cells and tissues. The method was used to detect and quantify changes in metabolite levels in cancer cells and tumor tissues treated with a pharmacological inhibitor of nicotinamide phosphoribosyl transferase (NAMPT). This method is rapid, sensitive, and reproducible, and it can be used to assess metabolic changes in cancer cells and tumor samples.

A nano ultra-performance liquid chromatography-high resolution mass spectrometry approach for global metabolomic profiling and case study on drug-resistant multiple myeloma

Global metabolomics relies on highly reproducible and sensitive detection of a wide range of metabolites in biological samples. Here we report the optimization of metabolome analysis by nanoflow ultraperformance liquid chromatography coupled to high-resolution orbitrap mass spectrometry. Reliable peak features were extracted from the LC-MS runs based on mandatory detection in duplicates and additional noise filtering according to blank injections. The run-to-run variation in peak area showed a median of 14%, and the false discovery rate during a mock comparison was evaluated. To maximize the number of peak features identified, we systematically characterized the effect of sample loading amount, gradient length, and MS resolution. The number of features initially rose and later reached a plateau as a function of sample amount, fitting a hyperbolic curve. Longer gradients improved unique feature detection in part by time-resolving isobaric species. Increasing the MS resolution up to 120000 also aided in the differentiation of near isobaric metabolites, but higher MS resolution reduced the data acquisition rate and conferred no benefits, as predicted from a theoretical simulation of possible metabolites. Moreover, a biphasic LC gradient allowed even distribution of peak features across the elution, yielding markedly more peak features than the linear gradient. Using this robust nUPLC-HRMS platform, we were able to consistently analyze ~6500 metabolite features in a single 60 min gradient from 2 mg of yeast, equivalent to ~50 million cells. We applied this optimized method in a case study of drug (bortezomib) resistant and drug-sensitive multiple myeloma cells. Overall, 18% of metabolite features were matched to KEGG identifiers, enabling pathway enrichment analysis. Principal component analysis and heat map data correctly clustered isogenic phenotypes, highlighting the potential for hundreds of small molecule biomarkers of cancer drug resistance.

Two birds with one stone: doing metabolomics with your proteomics kit

Proteomic research facilities and laboratories are facing increasing demands for the integration of biological data from multiple ‘-OMICS’ approaches. The aim to fully understand biological processes requires the integrated study of genomes, proteomes and metabolomes. While genomic and proteomic workflows are different, the study of the metabolome overlaps significantly with the latter, both in instrumentation and methodology. However, chemical diversity complicates an easy and direct access to the metabolome by mass spectrometry (MS). The present review provides an introduction into metabolomics workflows from the viewpoint of proteomic researchers. We compare the physicochemical properties of proteins and peptides with metabolites/small molecules to establish principle differences between these analyte classes based on human data. We highlight the implications this may have on sample preparation, separation, ionisation, detection and data analysis. We argue that a typical proteomic workflow (nLC-MS) can be exploited for the detection of a number of aliphatic and aromatic metabolites, including fatty acids, lipids, prostaglandins, di/tripeptides, steroids and vitamins, thereby providing a straightforward entry point for metabolomics-based studies. Limitations and requirements are discussed as well as extensions to the LC-MS workflow to expand the range of detectable molecular classes without investing in dedicated instrumentation such as GC-MS, CE-MS or NMR.

Subtoxic and toxic concentrations of benzene and toluene induce Nrf2-mediated antioxidative stress response and affect the central carbon metabolism in lung epithelial cells A549

Since people in industrialized countries spend most of their time indoors, the effects of indoor contaminants such as volatile organic compounds become more and more relevant. Benzene and toluene are among the most abundant compounds in the highly heterogeneous group of indoor volatile organic compounds. In order to understand their effects on lung epithelial cells (A549) representing lung's first line of defense, we chose a global proteome and a targeted metabolome approach in order to detect adverse outcome pathways caused by exposure to benzene and toluene. Using a DIGE approach, 93 of 469 detected protein spots were found to be differentially expressed after exposure to benzene, and 79 of these spots were identified by MS. Pathway analysis revealed an enrichment of proteins involved in Nrf2-mediated and oxidative stress response glycolysis/gluconeogenesis. The occurrence of oxidative stress at nonacute toxic concentrations of benzene and toluene was confirmed by the upregulation of the stress related proteins NQO1 and SOD1. The changes in metabolism were validated by ion chromatography MS/MS analysis revealing significant changes of glucose-6-phosphate, fructose-6-phosphate, 3-phosphoglycerate, and NADPH. The molecular alterations identified as a result of benzene and toluene exposure demonstrate the detrimental effect of nonacute toxic concentrations on lung epithelial cells. The data provided here will allow for a targeted validation in in vivo models.

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

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

LC-MS metabolomics from study design to data-analysis - using a versatile pathogen as a test case

Thanks to significant improvements in LC-MS technology, metabolomics is increasingly used as a tool to discriminate the responses of organisms to various stimuli or drugs. In this minireview we discuss all aspects of the LC-MS metabolomics pipeline, using a complex and versatile model organism, Leishmania donovani, as an illustrative example. The benefits of a hyphenated mass spectrometry platform and a detailed overview of the entire experimental pipeline from sampling, sample storage and sample list set-up to LC-MS measurements and the generation of meaningful results with state-of-the-art data-analysis software will be thoroughly discussed. Finally, we also highlight important pitfalls in the processing of LC-MS data and comment on the benefits of implementing metabolomics in a systems biology approach.

Performance evaluation of ion-exchange chromatography in capillary format

The performance of a recently introduced capillary ion-exchange chromatography system was explored. Experiments were conducted in isocratic mode with a commercial capillary anion-exchange column (id = 0.4 mm, L = 15 cm) using a five-anion standard mixture. The achieved results were compared to the performance of a standard bore ion-exchange system (id = 4 mm, L = 15 cm), which was considered as a reference. The first-generation capillary columns exhibited a minimal reduced plate-height value below two witnessing a good packing quality and system performance. However, compared to the standard bore system the capillary system displayed an increased apparent C-term which could be due to a difference in packing morphology and/or possible external band-broadening contributions. For fast separations, the standard bore system outperformed the capillary system, while for complex separations both systems performed nearly equally well. In addition, the retention characteristics of the capillary system were investigated. To illustrate the suitability of the capillary system, the analysis of real-world water samples originating from two local Belgian rivers was demonstrated.

Metabolomics: a valuable tool for stem cell monitoring in regenerative medicine

Metabolomics is a method for investigation of changes in the global metabolite profile of cells. This paper discusses the technical application of the approach, considering metabolite extraction, separation, mass spectrometry and data interpretation. A particular focus is on the application of metabolomics to the study of stem cell physiology in the context of biomaterials and regenerative medicine. Case studies are used to illustrate key points, focusing on the use of metabolomics in the examination of mesenchymal stem cell responses to titania-nanopillared substrata designed for orthopaedic applications.

Untargeted metabolomics reveals a lack of synergy between nifurtimox and eflornithine against Trypanosoma brucei

A non-targeted metabolomics-based approach is presented that enables the study of pathways in response to drug action with the aim of defining the mode of action of trypanocides. Eflornithine, a polyamine pathway inhibitor, and nifurtimox, whose mode of action involves its metabolic activation, are currently used in combination as first line treatment against stage 2, CNS-involved, human African trypanosomiasis (HAT). Drug action was assessed using an LC-MS based non-targeted metabolomics approach. Eflornithine revealed the expected changes to the polyamine pathway as well as several unexpected changes that point to pathways and metabolites not previously described in bloodstream form trypanosomes, including a lack of arginase activity and N-acetylated ornithine and putrescine. Nifurtimox was shown to be converted to a trinitrile metabolite indicative of metabolic activation, as well as inducing changes in levels of metabolites involved in carbohydrate and nucleotide metabolism. However, eflornithine and nifurtimox failed to synergise anti-trypanosomal activity in vitro, and the metabolomic changes associated with the combination are the sum of those found in each monotherapy with no indication of additional effects. The study reveals how untargeted metabolomics can yield rapid information on drug targets that could be adapted to any pharmacological situation.