Direct Introduction of Biological Samples into a LTQ-Orbitrap Hybrid Mass Spectrometer as a Tool for Fast Metabolome Analysis

A Dual-Gated Structures for Lossless Ion Manipulations-Ion Mobility Orbitrap Mass Spectrometry Platform for Combined Ultra-High-Resolution Molecular Analysis

High-resolution ion mobility spectrometry-mass spectrometry (HR-IMS-MS) instruments have enormously advanced the ability to characterize complex biological mixtures. Unfortunately, HR-IMS and HR-MS measurements are typically performed independently due to mismatches in analysis time scales. Here, we overcome this limitation by using a dual-gated ion injection approach to couple an 11 m path length structures for lossless ion manipulations (SLIM) module to a Q-Exactive Plus Orbitrap MS platform. The dual-gate setup was implemented by placing one ion gate before the SLIM module and a second ion gate after the module. The dual-gated ion injection approach allowed the new SLIM-Orbitrap platform to simultaneously perform an 11 m SLIM separation, Orbitrap mass analysis using the highest selectable mass resolution setting (up to 140 k), and high-energy collision-induced dissociation (HCD) in ∼25 min over an m/z range of ∼1500 amu. The SLIM-Orbitrap platform was initially characterized using a mixture of standard phosphazene cations and demonstrated an average SLIM CCS resolving power (Rp^CCS) of ∼218 and an SLIM peak capacity of ∼156, while simultaneously obtaining high mass resolutions. SLIM-Orbitrap analysis with fragmentation was then performed on mixtures of standard peptides and two reverse peptides (SDGRG¹⁺, GRGDS¹⁺, and Rp^CCS = 305) to demonstrate the utility of combined HR-IMS-MS/MS measurements for peptide identification. Our new HR-IMS-MS/MS capability was further demonstrated by analyzing a complex lipid mixture and showcasing SLIM separations on isobaric lipids. This new SLIM-Orbitrap platform demonstrates a critical new capability for proteomics and lipidomics applications, and the high-resolution multimodal data obtained using this system establish the foundation for reference-free identification of unknown ion structures.

Large-scale targeted metabolomics method for metabolite profiling of human samples

Targeted metabolomics has significant advantages for quantification but suffers from reduced metabolite coverage. In this study, we developed a large-scale targeted metabolomics method and expanded its applicability to various human samples. This approach initially involved unbiased identification of metabolites in human cells, tissues and body fluids using ultra high-performance liquid chromatography (UHPLC) coupled to high-resolution Orbitrap mass spectrometry (MS). Targeted metabolomics method was established with utility of UHPLC-triple quadrupole MS, which enables targeted profiling of over 400 biologically important metabolites (e.g., amino acids, sugars, nucleotides, dipeptides, coenzymes, and fatty acids), covering 92 metabolic pathways (e.g., Krebs cycle, glycolysis, amino acids metabolism, ammonia recycling, and one-carbon metabolism). The present method displayed better sensitivity, repeatability and linearity than the Orbitrap MS-based untargeted metabolomics approach and demonstrated excellent performance in lung cancer biomarker discovery, in which 107 differential metabolites were able to discriminate between carcinoma and adjacent normal tissues, implicating the Warburg effect, alteration of redox state, and nucleotide metabolism of lung cancer. This new method is flexible and expandable and offers many advantages for metabolomics analysis, such as wide metabolite coverage, good repeatability and linearity and excellent capability in biomarker discovery, making it useful for both basic and clinical metabolic research.

MetExplore: collaborative edition and exploration of metabolic networks

Metabolism of an organism is composed of hundreds to thousands of interconnected biochemical reactions responding to environmental or genetic constraints. This metabolic network provides a rich knowledge to contextualize omics data and to elaborate hypotheses on metabolic modulations. Nevertheless, performing this kind of integrative analysis is challenging for end users with not sufficiently advanced computer skills since it requires the use of various tools and web servers. MetExplore offers an all-in-one online solution composed of interactive tools for metabolic network curation, network exploration and omics data analysis. In particular, it is possible to curate and annotate metabolic networks in a collaborative environment. The network exploration is also facilitated in MetExplore by a system of interactive tables connected to a powerful network visualization module. Finally, the contextualization of metabolic elements in the network and the calculation of over-representation statistics make it possible to interpret any kind of omics data. MetExplore is a sustainable project maintained since 2010 freely available at https://metexplore.toulouse.inra.fr/metexplore2/.

Evaluation and validation of an analytical approach for high-throughput metabolomic fingerprinting using direct introduction-high-resolution mass spectrometry: Applicability to classification of urine of scrapie-infected ewes

Direct injection-mass spectrometry can be used to perform high-throughput metabolomic fingerprinting. This work aims to evaluate a global analytical workflow in terms of sample preparation (urine sample dilution), high-resolution detection (quality of generated data based on criteria such as mass measurement accuracy and detection sensitivity) and data analysis using dedicated bioinformatics tools. Investigation was performed on a large number of biological samples collected from sheep infected or not with scrapie. Direct injection-mass spectrometry approach is usually affected by matrix effects, eventually hampering detection of some relevant biomarkers. Reference compounds were spiked in biological samples to help evaluate the quality of direct injection-mass spectrometry data produced by Fourier Transform mass spectrometry. Despite the potential of high-resolution detection, some drawbacks still remain. The most critical is the presence of matrix effects, which could be minimized by optimizing the sample dilution factor. The data quality in terms of mass measurement accuracy and reproducible intensity was evaluated. Good repeatability was obtained for the chosen dilution factor (i.e., 2000). More than 150 analyses were performed in less than 16 hours using the optimized direct injection-mass spectrometry approach. Discrimination of different status of sheeps in relation to scrapie infection (i.e., scrapie-affected, preclinical scrapie or healthy) was obtained from the application of Shrinkage Discriminant Analysis to the direct injection-mass spectrometry data. The most relevant variables related to this discrimination were selected and annotated. This study demonstrated that the choice of appropriated dilution faction is indispensable for producing quality and informative direct injection-mass spectrometry data. Successful application of direct injection-mass spectrometry approach for high throughput analysis of a large number of biological samples constitutes the proof of the concept.

Promises and pitfalls of untargeted metabolomics

Metabolomics is one of the newer omics fields, and has enabled researchers to complement genomic and protein level analysis of disease with both semi-quantitative and quantitative metabolite levels, which are the chemical mediators that constitute a given phenotype. Over more than a decade, methodologies have advanced for both targeted (quantification of specific analytes) as well as untargeted metabolomics (biomarker discovery and global metabolite profiling). Untargeted metabolomics is especially useful when there is no a priori metabolic hypothesis. Liquid chromatography coupled to mass spectrometry (LC-MS) has been the preferred choice for untargeted metabolomics, given the versatility in metabolite coverage and sensitivity of these instruments. Resolving and profiling many hundreds to thousands of metabolites with varying chemical properties in a biological sample presents unique challenges, or pitfalls. In this review, we address the various obstacles and corrective measures available in four major aspects associated with an untargeted metabolomics experiment: (1) experimental design, (2) pre-analytical (sample collection and preparation), (3) analytical (chromatography and detection), and (4) post-analytical (data processing).

MetExploreViz: web component for interactive metabolic network visualization

Summary

MetExploreViz is an open source web component that can be easily embedded in any web site. It provides features dedicated to the visualization of metabolic networks and pathways and thus offers a flexible solution to analyse omics data in a biochemical context.

Availability and implementation

Documentation and link to GIT code repository (GPL 3.0 license) are available at this URL: http://metexplore.toulouse.inra.fr/metexploreViz/doc/

1H NMR Metabolic Profiling of Earthworm (Eisenia fetida) Coelomic Fluid, Coelomocytes, and Tissue: Identification of a New Metabolite-Malylglutamate

Earthworm metabolism is recognized as a useful tool for monitoring environmental insults and measuring ecotoxicity, yet extensive earthworm metabolic profiling using ¹H nuclear magnetic resonance (NMR) spectroscopy has been limited in scope. This study aims to expand the embedded metabolic material in earthworm coelomic fluid, coelomocytes, and tissue to aid systems toxicology research. Fifty-nine metabolites within Eisenia fetida were identified, with 47 detected in coelomic fluid, 41 in coelomocytes, and 54 in whole-worm samples and tissue extracts. The newly detected but known metabolites 2-aminobutyrate, nicotinurate, Nδ,Nδ,Nδ-trimethylornithine, and trigonelline are reported along with a novel compound, malylglutamate, elucidated using 2D NMR and high-resolution MS/MS. We postulate that malylglutamate acts as a glutamate/malate store, chelator, and anionic osmolyte and helps to provide electrolyte balance.

An efficient data-filtering strategy for easy metabolite detection from the direct analysis of a biological fluid using Fourier transform mass spectrometry

RATIONALE

High-throughput analyses require an overall analytical workflow including not only a robust and high-speed technical platform, but also dedicated data-processing tools able to extract the relevant information. This work aimed at evaluating post-acquisition data-mining tools for selective extraction of metabolite species from direct introduction high-resolution mass spectrometry data.

METHODS

Investigations were performed on spectral data in which seven metabolites of vinclozolin, a dicarboximide fungicide containing two chloride atoms, were previously manually identified. The spectral data obtained from direct introduction (DI) and high-resolution mass spectrometry (HRMS) detection were post-processed by plotting the mass defect profiles and applying various data-filtering methods based on accurate mass values.

RESULTS

Exploration of mass defect profiles highlighted, in a specific plotting region, the presence of compounds containing common chemical elements and pairs of conjugated and non-conjugated metabolites resulting from classical metabolic pathways. Additionally, the judicious application of mass defect and/or isotope pattern filters removed many interfering ions from DI-HRMS data, greatly facilitating the detection of vinclozolin metabolites. Compared with previous results obtained by manual data treatment, three additional metabolites of vinclozolin were detected and putatively annotated.

CONCLUSIONS

Tracking simultaneously several specific species could be efficiently performed using data-mining tools based on accurate mass values. The selectivity of the data extraction was improved when the isotope filter was used for halogenated compounds, facilitating metabolite ion detection even for low-abundance species. Copyright © 2016 John Wiley & Sons, Ltd.

The nephrologist of tomorrow: towards a kidney-omic future

Omics refers to the collective technologies used to explore the roles and relationships of the various types of molecules that make up the phenotype of an organism. Systems biology is a scientific discipline that endeavours to quantify all of the molecular elements of a biological system. Therefore, it reflects the knowledge acquired by omics in a meaningful manner by providing insights into functional pathways and regulatory networks underlying different diseases. The recent advances in biotechnological platforms and statistical tools to analyse such complex data have enabled scientists to connect the experimentally observed correlations to the underlying biochemical and pathological processes. We discuss in this review the current knowledge of different omics technologies in kidney diseases, specifically in the field of pediatric nephrology, including biomarker discovery, defining as yet unrecognized biologic therapeutic targets and linking omics to relevant standard indices and clinical outcomes. We also provide here a unique perspective on the field, taking advantage of the experience gained by the large-scale European research initiative called "Systems Biology towards Novel Chronic Kidney Disease Diagnosis and Treatment" (SysKid). Based on the integrative framework of Systems biology, SysKid demonstrated how omics are powerful yet complex tools to unravel the consequences of diabetes and hypertension on kidney function.

Development of a Rapid Microbore Metabolic Profiling Ultraperformance Liquid Chromatography-Mass Spectrometry Approach for High-Throughput Phenotyping Studies

A rapid gradient microbore ultraperformance liquid chromatography-mass spectrometry (UPLC-MS) method has been developed to provide a high-throughput analytical platform for the metabolic phenotyping of urine from large sample cohorts. The rapid microbore metabolic profiling (RAMMP) approach was based on scaling a conventional reversed-phase UPLC-MS method for urinary profiling from 2.1 mm × 100 mm columns to 1 mm × 50 mm columns, increasing the linear velocity of the solvent, and decreasing the gradient time to provide an analysis time of 2.5 min/sample. Comparison showed that conventional UPLC-MS and rapid gradient approaches provided peak capacities of 150 and 50, respectively, with the conventional method detecting approximately 19 000 features compared to the ∼6 000 found using the rapid gradient method. Similar levels of repeatability were seen for both methods. Despite the reduced peak capacity and the reduction in ions detected, the RAMMP method was able to achieve similar levels of group discrimination as conventional UPLC-MS when applied to rat urine samples obtained from investigative studies on the effects of acute 2-bromophenol and chronic acetaminophen administration. When compared to a direct infusion MS method of similar analysis time the RAMMP method provided superior selectivity. The RAMMP approach provides a robust and sensitive method that is well suited to high-throughput metabonomic analysis of complex mixtures such as urine combined with a 5-fold reduction in analysis time compared with the conventional UPLC-MS method.

Current state of the art of mass spectrometry-based metabolomics studies – a review focusing on wide coverage, high throughput and easy identification

Metabolomics aims at the comprehensive assessment of a wide range of endogenous metabolites and attempts to identify and quantify the attractive metabolites in a given biological sample.

Evolution of Orbitrap Mass Spectrometry Instrumentation

We discuss the evolution of Orbitrap mass spectrometry (MS) from its birth in the late 1990s to its current role as one of the most prominent techniques for MS. The Orbitrap mass analyzer is the first high-performance mass analyzer that employs trapping of ions in electrostatic fields. Tight integration with the ion injection process enables the high-resolution, mass accuracy, and sensitivity that have become essential for addressing analytical needs in numerous areas of research, as well as in routine analysis. We examine three major families of instruments (related to the LTQ Orbitrap, Q Exactive, and Orbitrap Fusion mass spectrometers) in the context of their historical development over the past ten eventful years. We discuss as well future trends and perspectives of Orbitrap MS. We illustrate the compelling potential of Orbitrap-based mass spectrometers as (ultra) high-resolution platforms, not only for high-end proteomic applications, but also for routine targeted analysis.

Identification of xenobiotic metabolites from biological fluids using flow injection analysis high-resolution mass spectrometry and post-acquisition data filtering

RATIONALE

Concern for public health entails the need to evaluate the degree of exposure of population to toxicants. To do this, robust high-throughput approaches are required to be able to perform a large number of analyses in cohort studies. In this study, a data-filtering procedure was applied to mass spectral data acquired by direct analysis of biological fluids leading to rapid detection of metabolites in a model xenobiotic system.

METHODS

Flow injection analysis (FIA) coupled to negative electrospray ionization (ESI)-LTQ Orbitrap Fourier transform mass spectrometry was used to directly analyze urine of rats treated with vinclozolin. Tandem mass spectrometry (MS/MS) experiments were subsequently performed for confirmation of a new metabolite structure. The isotope filtering based on the difference between accurate masses of (35)Cl and (37)Cl was applied to the raw data for the specific detection of ions containing at least one chlorine atom.

RESULTS

Seven metabolites of vinclozolin were manually identified thanks to the characteristic isotope pattern of dichlorinated compounds. A new metabolite of vinclozolin was detected for the first time and identified as a sulfate conjugate. The application of an isotope-filtering procedure allowed the selective extraction of pertinent signals from the data. The processed mass spectrum was greatly simplified, significantly facilitating the detection of the seven metabolites previously identified.

CONCLUSIONS

The use of FIA-HRMS in combination with dedicated bio-informatics data processing is shown to be an efficient approach for the rapid detection of metabolites in biological fluids. This is a very promising high-throughput approach for rapid characterization of the exposure status to xenobiotics.

High resolution mass spectrometry based techniques at the crossroads of metabolic pathways

The metabolome is the set of small molecular mass compounds found in biological media, and metabolomics, which refers to as the analysis of metabolome in a given biological condition, deals with the large scale detection and quantification of metabolites in biological media. It is a data driven and multidisciplinary approach combining analytical chemistry for data acquisition, and biostatistics, informatics and biochemistry for mining and interpretation of these data. Since the middle of the 2000s, high resolution mass spectrometry is widely used in metabolomics, mainly because the detection and identification of metabolites are improved compared to low resolution instruments. As the field of HRMS is quickly and permanently evolving, the aim of this work is to review its use in different aspects of metabolomics, including data acquisition, metabolite annotation, identification and quantification. At last, we would like to show that, thanks to their versatility, HRMS instruments are the most appropriate to achieve optimal metabolome coverage, at the border of other omics fields such as lipidomics and glycomics.

Basics of mass spectrometry based metabolomics

The emerging field of metabolomics, aiming to characterize small molecule metabolites present in biological systems, promises immense potential for different areas such as medicine, environmental sciences, agronomy, etc. The purpose of this article is to guide the reader through the history of the field, then through the main steps of the metabolomics workflow, from study design to structure elucidation, and help the reader to understand the key phases of a metabolomics investigation and the rationale underlying the protocols and techniques used. This article is not intended to give standard operating procedures as several papers related to this topic were already provided, but is designed as a tutorial aiming to help beginners understand the concept and challenges of MS-based metabolomics. A real case example is taken from the literature to illustrate the application of the metabolomics approach in the field of doping analysis. Challenges and limitations of the approach are then discussed along with future directions in research to cope with these limitations. This tutorial is part of the International Proteomics Tutorial Programme (IPTP18).

High-throughput discovery metabolomics

Non-targeted metabolomics by mass spectrometry has established as the method of choice for investigating metabolic phenotypes in basic and applied research. Compared to other omics, metabolomics provides broad scope and yet direct information on the integrated cellular response with low demand in material and sample preparation. These features render non-targeted metabolomics ideally suited for large scale screens and discovery. Here we review the achievements and potential in high-throughput, non-targeted metabolomics. We found that routine and precise analysis of thousands of small molecular features in thousands of complex samples per day and instrument is already reality, and ongoing developments in microfluidics and integrated interfaces will likely further boost throughput in the next few years.

High throughput volatile fatty acid skin metabolite profiling by thermal desorption secondary electrospray ionisation mass spectrometry

Global VOC skin metabolite profiling. Thermal desorption secondary electrospray ionisation time-of-flight mass spectrometry classifies skin odour phenotypes by targeted volatile fatty analysis. Examination of the mass spectra reveals the potential for global metabolic studies.

Telling metabolic stories to explore metabolomics data: a case study on the yeast response to cadmium exposure

Motivation: The increasing availability of metabolomics data enables to better understand the metabolic processes involved in the immediate response of an organism to environmental changes and stress. The data usually come in the form of a list of metabolites whose concentrations significantly changed under some conditions, and are thus not easy to interpret without being able to precisely visualize how such metabolites are interconnected.

Results: We present a method that enables to organize the data from any metabolomics experiment into metabolic stories. Each story corresponds to a possible scenario explaining the flow of matter between the metabolites of interest. These scenarios may then be ranked in different ways depending on which interpretation one wishes to emphasize for the causal link between two affected metabolites: enzyme activation, enzyme inhibition or domino effect on the concentration changes of substrates and products. Equally probable stories under any selected ranking scheme can be further grouped into a single anthology that summarizes, in a unique subnetwork, all equivalently plausible alternative stories. An anthology is simply a union of such stories. We detail an application of the method to the response of yeast to cadmium exposure. We use this system as a proof of concept for our method, and we show that we are able to find a story that reproduces very well the current knowledge about the yeast response to cadmium. We further show that this response is mostly based on enzyme activation. We also provide a framework for exploring the alternative pathways or side effects this local response is expected to have in the rest of the network. We discuss several interpretations for the changes we see, and we suggest hypotheses that could in principle be experimentally tested. Noticeably, our method requires simple input data and could be used in a wide variety of applications.

Availability and implementation: The code for the method presented in this article is available at http://gobbolino.gforge.inria.fr.

Contact: pvmilreu@gmail.com; vincent.lacroix@univ-lyon1.fr; marie-france.sagot@inria.fr

Supplementary information:Supplementary data are available at Bioinformatics online.

Metabolomics as a potential new approach for investigating human reproductive disorders

Metabolomics has been emerging for several years as a global chemical phenotyping approach offering fascinating descriptive capabilities for addressing life complexity. It facilitates the understanding of the mechanisms of biological and biochemical processes in complex systems and promises new insights into specific research questions. The objective of this study was to use for the first time a metabolomic approach based on liquid chromatography high resolution mass spectrometry for characterizing an alteration of the testicular function, namely impaired semen quality. Metabolomic fingerprints were generated from serum samples collected from Danish young men presenting low, intermediate, or high sperm concentrations. Serum metabolic profiles were found to be significantly different among the three groups of volunteers. The developed methodology permitted to correlate the studied clinical parameter (i.e., sperm concentration) with the metabolite profiles generated. Peptides related to the Protein Complement C3f were identified as putative markers associated with this clinical parameter. The biological interpretation and further robustness linked to this observation remain to be further investigated, in particular to address the inter- and intraindividual variabilities.

A hyphenated microLC-Q-TOF-MS platform for exosomal lipidomics investigations: application to RCC urinary exosomes

Urinary exosomes are released from every renal epithelial cell type facing the urinary space and therefore, they may carry molecular markers of renal dysfunction and structural injury. Here, we present a hyphenated microLC-Q-TOF-MS platform for lipidomics studies applied to investigate the urinary exosome lipid repertoire. Lipids were separated by reversed-phase chromatography using a linear gradient of formic acid 0.2% and tetrahydrofuran, in 40 min of analysis. Features (m/z with associated own retention time) were extracted by MarkerLynx(TM) (Waters) and processed, demonstrating good analytical performance in terms of repeatability and mass accuracy of the microLC Q-TOF MS platform. In particular, a stable retention time (RSD less than 4%) and relative intensity (RSD from 2.9% to 11%) were observed. Moreover, the method takes advantages by the use of a lock spray interface (Waters) that allows readjusting the m/z data after acquisition, obtaining inaccuracy below 6 ppm in measuring the m/z value of the reference compound during chromatographic run. The method was employed in a preliminary application to perform comparative analysis from healthy control subjects and renal cell carcinoma (RCC) patients, in order to possibly highlight differences in lipid composition to be exploited as potential tumor biomarker. Differential lipid composition in RCC urinary exosomes was achieved and tentatively identified by accurate mass, providing a preliminary indication of a relationship between lipid composition of urinary exosomes and RCC disease. Among the total features significantly different in RCC exosomes, the ion at m/z 502.3 was taken as an example for molecular confirmation by MS/MS fragmentation analysis.

Rapid narrow band elution for on-line SPE using a novel solvent plug injection technique

Determination of trace constituents in biological and environmental samples usually requires a pre-concentration step. While solid-phase extraction (SPE) has been widely used, it is slow, labor intensive and adversely affected by analytical errors from handling. On-line SPE eliminates some of the flaws but often suffers from solvent compatibility problems with the subsequent chromatography separation. In this study, we are presenting a technical solution for overcoming some of these compatibility issues, by utilizing a fully automated, focused SPE sample transfer technique utilizing narrow-band solvent plugs, for seamless hyphenation with high-performance liquid chromatography (HPLC) or flow injection mass spectrometry (MS). A wide range of pharmaceutical compounds was studied in different sample matrices. Short plugs of high elution strength solvent were generated by means of an electrically actuated sample loop and enrichment and transfer steps monitored using on-line SPE-MS. The impact of the solvent plugs on chromatographic separation was studied using hyphenated SPE-LC-MS. By carefully examining elution profiles of solvent plugs of different compositions, optimum conditions for quantitative elution within well-defined volumes were found for all substances. In addition, the highly focused elution bands resulted in excellent retention time and peak area reproducibilities when injected on-line onto HPLC columns. Finally, to demonstrate proof-of-principle, the fully integrated on-line SPE-LC-MS system was applied to the analysis of spiked urine and river water samples.

Predictive toxicology using systemic biology and liver microfluidic "on chip" approaches: application to acetaminophen injury

We have analyzed transcriptomic, proteomic and metabolomic profiles of hepatoma cells cultivated inside a microfluidic biochip with or without acetaminophen (APAP). Without APAP, the results show an adaptive cellular response to the microfluidic environment, leading to the induction of anti-oxidative stress and cytoprotective pathways. In presence of APAP, calcium homeostasis perturbation, lipid peroxidation and cell death are observed. These effects can be attributed to APAP metabolism into its highly reactive metabolite, N-acetyl-p-benzoquinone imine (NAPQI). That toxicity pathway was confirmed by the detection of GSH-APAP, the large production of 2-hydroxybutyrate and 3-hydroxybutyrate, and methionine, cystine, and histidine consumption in the treated biochips. Those metabolites have been reported as specific biomarkers of hepatotoxicity and glutathione depletion in the literature. In addition, the integration of the metabolomic, transcriptomic and proteomic collected profiles allowed a more complete reconstruction of the APAP injury pathways. To our knowledge, this work is the first example of a global integration of microfluidic biochip data in toxicity assessment. Our results demonstrate the potential of that new approach to predictive toxicology.

SILEC: a protocol for generating and using isotopically labeled coenzyme A mass spectrometry standards

Stable isotope labeling by essential nutrients in cell culture (SILEC) was recently developed to generate isotopically labeled coenzyme A (CoA) and short-chain acyl-CoA thioesters. This was accomplished by modifying the widely used technique of stable isotope labeling by amino acids in cell culture to include [(13)C(3)(15)N]-pantothenate (vitamin B(5)), a CoA precursor, instead of the isotopically labeled amino acids. The lack of a de novo pantothenate synthesis pathway allowed for efficient and near-complete labeling of the measured CoA species. This protocol provides a step-by-step approach for generating stable isotope-labeled short-chain acyl-CoA internal standards in mammalian and insect cells as well as instructions on how to use them in stable isotope dilution mass spectrometric-based analyses. Troubleshooting guidelines, as well as a list of unlabeled and labeled CoA species, are also included. This protocol represents a prototype for generating stable isotope internal standards from labeled essential nutrients such as pantothenate. The generation and use of SILEC standards takes approximately 2-3 weeks.

Use of volatile compound metabolic signatures in poultry liver to back-trace dietary exposure to rapidly metabolized xenobiotics

The study investigated the feasibility of using volatile compound signatures of liver tissues in poultry to detect previous dietary exposure to different types of xenobiotic. Six groups of broiler chickens were fed a similar diet either noncontaminated or contaminated with polychlorinated dibenzo-p-dioxins/-furans (PCDD/Fs; 3.14 pg WHO-TEQ/g feed, 12% moisture), polychlorinated biphenyls (PCBs; 0.08 pg WHO-TEQ/g feed, 12% moisture), polybrominated diphenyl ethers (PBDEs; 1.63 ng/g feed, 12% moisture), polycyclic aromatic hydrocarbons (PAHs; 0.72 μg/g fresh matter), or coccidiostats (0.5 mg/g feed, fresh matter). Each chicken liver was analyzed by solid-phase microextraction - mass spectrometry (SPME-MS) for volatile compound metabolic signature and by gas chromatography - high resolution mass spectrometry (GC-HRMS), gas chromatography - tandem mass spectrometry (GC-MS/MS), and liquid chromatography - tandem mass spectrometry (LC-MS/MS) to quantify xenobiotic residues. Volatile compound signature evidenced a liver metabolic response to PAH although these rapidly metabolized xenobiotics are undetectable in this organ by the reference methods. Similarly, the volatile compound metabolic signature enabled to differentiate the noncontaminated chickens from those contaminated with PBDEs or coccidiostats. In contrast, no clear signature was pointed out for slowly metabolized compounds such as PCDD/Fs and PCBs although their residues were found in liver at 50.93 (±6.71) and 0.67 (±0.1) pg WHO-TEQ/g fat, respectively.

Advances in mass spectrometry applied to pharmaceutical metabolomics

Metabolomics, also referred to in the literature as metabonomics, is a relatively new systems biology tool for drug discovery and development and is increasingly being used to obtain a detailed picture of a drug's effect on the body. Metabolomics is the qualitative assessment and relative or absolute quantitative measurement of the endogenous metabolome, defined as the complement of all native small molecules (metabolites less than 1,500 Da). A metabolomics study frequently involves the comparative analysis of sample sets from a normal state and a perturbed state, where the perturbation can be of any nature, such as genetic knockout, administration of a drug, or change in diet or lifestyle. Advances in mass spectrometry (MS) technologies including direct introduction or in-line chromatographic separation modes, ionization techniques, mass analyzers, and detection methods have provided powerful tools to assess the molecular changes in the metabolome. This review focuses on advances in MS pertaining to the analytical data generation for the main metabolomics methods, namely, fingerprinting, nontargeted, and targeted approaches, as they are applied to pharmaceutical drug discovery and development.

Research Spotlight: Drug bioanalysis and biomarker discovery at the Commissariat à l’énergie atomique et aux énergies alternatives

The bioanalysis group at the Saclay site of the Commissariat à l’énergie atomique et aux énergies alternatives focuses on MS for the discovery and quantification of biomarkers and drugs as well as metabolites. Key developments and achievements include intracellular pharmacokinetics of anti-HIV drugs, metabolomic studies, pioneering work in the bioanalysis of recombinant proteins, antibodies, probes for in vitro blood–brain barrier models and bioanalytical approaches to the quantification of biomarkers relevant to the threat of bioterrorism. Our activities are based on industrial collaboration and are pursued within the framework of national and international collaborations and strong partnerships with the pharmaceutical industry and clinicians.

Mass spectrometry-based methods for the determination of sulfur and related metabolite concentrations in cell extracts

The sulfur metabolic pathway plays a central role in cell metabolism. It provides the sulfur amino acids methionine and cysteine, which are essential for protein synthesis, homocysteine, which lies at a critical juncture of this pathway, S-adenosylmethionine, the universal methyl donor in the cell, and glutathione (GSH), which has many crucial functions including protection against oxidative stress and xenobiotics. The intracellular level of these metabolites, which are closely connected with other cellular metabolic pathways, is of major importance for cell physiology and health. Three mass spectrometry-based methods for the determination of sulfur metabolites and also related compounds linked to the glutathione biosynthesis pathway are presented and discussed. The first one enables absolute quantification of these metabolites in cell extracts. It is based on liquid chromatography-electrospray triple quadrupole mass spectrometry coupled to (15)N uniform metabolic labeling of the yeast Saccharomyces cerevisiae. The two other methods are global approaches to metabolite detection involving a high-resolution mass spectrometer, the LTQ-Orbitrap. Ions related to metabolites of interest are picked up from complex and information-rich metabolic fingerprints. By these means, it is possible to detect analytical information outside the initial scope of investigation.