Eric Ezan

Mass spectrometry for the identification of the discriminating signals from metabolomics: Current status and future trends

The metabolome is characterized by a large number of molecules exhibiting a high diversity of chemical structures and abundances, requiring complementary analytical platforms to reach its extensive coverage. Among them, atmospheric pressure ionization mass spectrometry (API-MS)-based technologies, and especially those using electrospray ionization are now very popular. In this context, this review deals with strengths, limitations and future trends in the identification of signals highlighted by API-MS-based metabolomics. It covers the identification process from the determination of the molecular mass and/or its elemental composition to the confirmation of structural hypotheses. Furthermore, some tools that were developed in order to address the MS signal redundancy and some approaches that could facilitate identification by improving the visualization and organization of complex data sets are also reported and discussed.

Immunopurification and Mass Spectrometric Quantification of the Active Form of a Chimeric Therapeutic Antibody in Human Serum

In this study, we show that liquid chromatography coupled with tandem mass spectrometry provides a sensitive, specific, and accurate absolute quantification of Erbitux, a human:murine chimeric mAb used for the treatment of colorectal cancer. Micrometric magnetized beads, functionalized with soluble epidermal growth factor receptor (sEGFR), the pharmacological target of Erbitux, were used for specific immunocapture of Erbitux allowing assessment of the antibodys biological potency and sample purification. Following digestion with trypsin, specific peptides from light and heavy chains were monitored in the selected reaction monitoring (SRM) mode. Assay variability below 20% was provided through optimization of the digestion step and rigorous monitoring of the whole analytical process using an appropriate internal standard. The 20 ng/mL lower limit of quantification was similar to that of ELISA methods. These results show that this mass spectrometric approach is a potential alternative for pharmacokinetic evaluation of mAbs during clinical development.

Evaluation of accurate mass and relative isotopic abundance measurements in the LTQ-orbitrap mass spectrometer for further metabolomics database building.

Recently, high-resolution mass spectrometry has been largely employed for compound identification, thanks to accurate mass measurements. As additional information, relative isotope abundance (RIA) is often needed to reduce the number of candidates prior to tandem MS(n). Here, we report on the evaluation of the LTQ-Orbitrap, in terms of accurate mass and RIA measurements for building further metabolomics spectral databases. Accurate mass measurements were achieved in the ppm range, using external calibration within 24 h, and remained at <5 ppm over a one-week period. The experimental relative abundances of (M+1) isotopic ions were evaluated in different data sets. First of all, 137 solutions of commercial compounds were analyzed by flow injection analysis in both the positive and negative ion modes. It was found that the ion abundance was the main factor impacting the accuracy of RIA measurements. It was possible to define some intensity thresholds above which errors were systematically <20% of their theoretical values. The same type of results were obtained with analyses from two biological media. Otherwise, no significant effect of ion transmission between the LTQ ion trap and the Orbitrap analyzer on RIA measurement errors was found, whereas the reliability of RIA measurements was dramatically improved by reducing the mass detection window. It was also observed that the signal integration method had a significant impact on RIA measurement errors, with the most-reliable results being obtained with peak height integrations. Finally, automatic integrations using the data preprocessing software XCMS and MZmine gave results similar to those obtained by manual integration, suggesting that it is relevant to use the RIA information in automatic elemental composition determination software from metabolomic peak tables.

Analysis of the Human Adult Urinary Metabolome Variations with Age, Body Mass Index, and Gender by Implementing a Comprehensive Workflow for Univariate and OPLS Statistical Analyses

Urine metabolomics is widely used for biomarker research in the fields of medicine and toxicology. As a consequence, characterization of the variations of the urine metabolome under basal conditions becomes critical in order to avoid confounding effects in cohort studies. Such physiological information is however very scarce in the literature and in metabolomics databases so far. Here we studied the influence of age, body mass index (BMI), and gender on metabolite concentrations in a large cohort of 183 adults by using liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS). We implemented a comprehensive statistical workflow for univariate hypothesis testing and modeling by orthogonal partial least-squares (OPLS), which we made available to the metabolomics community within the online Workflow4Metabolomics.org resource. We found 108 urine metabolites displaying concentration variations with either age, BMI, or gender, by integrating the results from univariate p-values and multivariate variable importance in projection (VIP). Several metabolite clusters were further evidenced by correlation analysis, and they allowed stratification of the cohort. In conclusion, our study highlights the impact of gender and age on the urinary metabolome, and thus it indicates that these factors should be taken into account for the design of metabolomics studies.

Investigating the plant response to cadmium exposure by proteomic and metabolomic approaches

Monitoring molecular dynamics of an organism upon stress is probably the best approach to decipher physiological mechanisms involved in the stress response. Quantitative analysis of proteins and metabolites is able to provide accurate information about molecular changes allowing the establishment of a range of more or less specific mechanisms, leading to the identification of major players in the considered pathways. Such tools have been successfully used to analyze the plant response to cadmium (Cd), a major pollutant capable of causing severe health issues as it accumulates in the food chain. We present a summary of proteomics and metabolomics works that contributed to a better understanding of the molecular aspects involved in the plant response to Cd. This work allowed us to provide a finer picture of general signaling, regulatory and metabolic pathways that appeared to be affected upon Cd stress. In particular, we conclude on the advantage of employing different approaches of global proteome‐ and metabolome‐wide techniques, combined with more targeted analysis to answer molecular questions and unravel biological networks. Finally, we propose possible directions and methodologies for future prospectives in this field, as many aspects of the plant–Cd interaction remain to be discovered.

Direct introduction of biological samples into a LTQ-Orbitrap hybrid mass spectrometer as a tool for fast metabolome analysis.

We report the direct introduction of biological samples into a high-resolution mass spectrometer, the LTQ-Orbitrap, as a fast tool for metabolomic studies. A proof of concept study was performed on yeast cell extracts that were introduced into the mass spectrometer by using flow injection analysis, with an acquisition time of 3 min. Typical mass spectra contained a few thousand m/z signals, 400 of which were found to be analytically relevant (i.e., their intensity was 3-fold higher than that of the background noise and they occurred in at least 60% of the acquisition profiles under identical experimental conditions). The method was validated by studies of the matrix effect, linearity, and intra-assay precision. Accurate mass measurements in the Orbitrap discriminated between isobaric ions and also indicated the elemental composition of the ions of interest with mass errors below 5 ppm, for identification purposes. The proposed structures were then assessed by MSn experiments via the linear ion trap, together with accurate mass determination of the product ions in the Orbitrap analyzer. When applied to the study of cadmium toxicity, the method was as effective as that initially developed by using LC/ESI-MS/MS for a targeted approach. The same metabolic fingerprints were also subjected to multivariate statistical analyses. The results highlighted a reorganization of amino acid metabolism under cadmium conditions in order to increase the biosynthesis of glutathione.

Bioanalysis of recombinant proteins and antibodies by mass spectrometry

In recent years, biotechnologically-derived drugs have been a major focus of research and development in the pharmaceutical industry. Their pharmacokinetics and pharmacokinetic/pharmacodynamic relationships impact every stage of the development process and require their assessment in the circulation in preclinical species and in humans. To this end, immunoassays are a reference, but standardisation remains an issue owing to the restricted pattern of antibody specificity and interference with endogenous components. As an alternative, we report here analytical strategies involving liquid chromatography coupled to mass spectrometry (LC-MS) for the accurate quantification of therapeutic proteins and antibodies in biological fluids.

Annotation of the human adult urinary metabolome and metabolite identification using ultra high performance liquid chromatography coupled to a linear quadrupole ion trap-Orbitrap mass spectrometer.

Metabolic profiles of biofluids obtained by atmospheric pressure ionization mass spectrometry-based technologies contain hundreds to thousands of features, most of them remaining unknown or at least not characterized in analytical systems. We report here on the annotation of the human adult urinary metabolome and metabolite identification from electrospray ionization mass spectrometry (ESI-MS)-based metabolomics data sets. Features of biological interest were first of all annotated using the ESI-MS database of the laboratory. They were also grouped, thanks to software tools, and annotated using public databases. Metabolite identification was achieved using two complementary approaches: (i) formal identification by matching chromatographic retention times, mass spectra, and also product ion spectra (if required) of metabolites to be characterized in biological data sets to those of reference compounds and (ii) putative identification from biological data thanks to MS/MS experiments for metabolites not available in our chemical library. By these means, 384 metabolites corresponding to 1484 annotated features (659 in negative ion mode and 825 in positive ion mode) were characterized in human urine samples. Of these metabolites, 192 and 66 were formally and putatively identified, respectively, and 54 are reported in human urine for the first time. These lists of features could be used by other laboratories to annotate their ESI-MS metabolomics data sets.

Mass Spectrometry-Based Metabolomics: Accelerating the Characterization of Discriminating Signals by Combining Statistical Correlations and Ultrahigh Resolution

A strategy combining autocorrelation matrices and ultrahigh resolution mass spectrometry (MS) was developed to optimize the characterization of discriminating ions highlighted by metabolomics. As an example, urine samples from rats treated with phenobarbital (PB) were analyzed by ultrahigh-pressure chromatography with two different eluting conditions coupled to time-of-flight mass spectrometric detection in both the positive and negative electrospray ionization modes. Multivariate data analyses were performed to highlight discriminating variables from several thousand detected signals: a few hundred signals were found to be affected by PB, whereas a few tenths of them were linked to its metabolism. Autocorrelation matrices were then applied to eliminate adduct and fragment ions. Finally, the characterization of the ions of interest was performed with ultrahigh-resolution mass spectrometry and sequential MS(n) experiments, by using a LC-LTQ-Orbitrap system. The use of different eluting conditions was shown to drastically impact on the chromatographic retention and ionization of compounds, thus providing a way to obtain more exhaustive metabolic fingerprints, whereas autocorrelation matrices allowed one to focus the identification work on the most relevant ions. By using such an approach, 14 PB metabolites were characterized in rat urines, some of which have not been reported in the literature.

Molecular variability of group 1 and 5 grass pollen allergens between Pooideae species: implications for immunotherapy.

Background Differences between major allergens from distinct grass species remain to be investigated, both in terms of structure and antigenicity.