PeakForest: a multi-platform digital infrastructure for interoperable metabolite spectral data and metadata management.

INTRODUCTION: Accuracy of feature annotation and metabolite identification in biological samples is a key element in metabolomics research. However, the annotation process is often hampered by the lack of spectral reference data in experimental conditions, as well as logistical difficulties in the spectral data management and exchange of annotations between laboratories. OBJECTIVES: To design an open-source infrastructure allowing hosting both nuclear magnetic resonance (NMR) and mass spectra (MS), with an ergonomic Web interface and Web services to support metabolite annotation and laboratory data management. METHODS: We developed the PeakForest infrastructure, an open-source Java tool with automatic programming interfaces that can be deployed locally to organize spectral data for metabolome annotation in laboratories. Standardized operating procedures and formats were included to ensure data quality and interoperability, in line with international recommendations and FAIR principles. RESULTS: PeakForest is able to capture and store experimental spectral MS and NMR metadata as well as collect and display signal annotations. This modular system provides a structured database with inbuilt tools to curate information, browse and reuse spectral information in data treatment. PeakForest offers data formalization and centralization at the laboratory level, facilitating shared spectral data across laboratories and integration into public databases. CONCLUSION: PeakForest is a comprehensive resource which addresses a technical bottleneck, namely large-scale spectral data annotation and metabolite identification for metabolomics laboratories with multiple instruments. PeakForest databases can be used in conjunction with bespoke data analysis pipelines in the Galaxy environment, offering the opportunity to meet the evolving needs of metabolomics research. Developed and tested by the French metabolomics community, PeakForest is freely-available at https://github.com/peakforest .

Proposal for a chemically consistent way to annotate ions arising from the analysis of reference compounds under ESI conditions: A prerequisite to proper mass spectral database constitution in metabolomics.

Nowadays, high-resolution mass spectrometry is widely used for metabolomic studies. Thanks to its high sensitivity, it enables the detection of a large range of metabolites. In metabolomics, the continuous quest for a metabolite identification as complete and accurate as possible has led during the last decade to an ever increasing development of public MS databases (including LC-MS data) concomitantly with bioinformatic tool expansion. To facilitate the annotation process of MS profiles obtained from biological samples, but also to ease data sharing, exchange, and exploitation, the standardization and harmonization of the way to describe and annotate mass spectra seemed crucial to us. Indeed, under electrospray (ESI) conditions, a single metabolite does not produce a unique ion corresponding to its protonated or deprotonated form but could lead to a complex mixture of signals. These MS signals result from the existence of different natural isotopologues of the same compound and also to the potential formation of adduct ions, homomultimeric and heteromultimeric ions, fragment ions resulting from "prompt" in-source dissociations. As a joint reflection process within the French Infrastructure for Metabolomics and Fluxomics (MetaboHUB) and with the purpose of developing a robust and exchangeable annotated MS database made from pure reference compounds (chemical standards) analysis, it appeared to us that giving the metabolomics community some clues to standardize and unambiguously annotate each MS feature was a prerequisite to data entry and further efficient querying of the mass spectral database. The use of a harmonized notation is also mandatory for interlaboratory MS data exchange. Additionally, thorough description of the variety of MS signals arising from the analysis of a unique metabolite might provide greater confidence on its annotation.

Mechanistic study of competitive releases of H2O, NH3 and CO2 from deprotonated aspartic and glutamic acids: Role of conformation.

The aims of this study were to highlight the impact of minor structural differences (e.g. an aminoacid side chain enlargement by one methylene group), on ion dissociation under collision-induced dissociation conditions, and to determine the underlying chemical mechanisms. Therefore, we compared fragmentations of deprotonated aspartic and glutamic acids generated in negative electrospray ionization. Energy-resolved mass spectrometry breakdown curves were recorded and MS3 experiments performed on an Orbitrap Fusion for high-resolution and high-mass accuracy measurements. Activated fragmentations were performed using both the resonant and non-resonant excitation modes (i.e., CID and HCD, respectively) in order to get complementary information on the competitive and consecutive dissociative pathways. These experiments showed a specific loss of ammonia from the activated aspartate but not from the activated glutamate. We mainly focused on this specific observed loss from aspartate. Two different mechanisms based on intramolecular reactions (similar to those occurring in organic chemistry) were proposed, such as intramolecular elimination (i.e. Ei-like) and nucleophilic substitution (i.e. SNi-like) reactions, respectively, yielding anions as fumarate and α lactone from a particular conformation with the lowest steric hindrance (i.e. with antiperiplanar carboxyl groups). The detected deaminated aspartate anion can then release CO2 as observed in the MS3 experimental spectra. However, quantum calculations did not indicate the formation of such a deaminated aspartate product ion without loss of carbon dioxide. Actually, calculations displayed the double neutral (NH3+CO2) loss as a concomitant pathway (from a particular conformation) with relative high activation energy instead of a consecutive process. This disagreement is apparent since the concomitant pathway may be changed into consecutive dissociations according to the collision energy i.e., at higher collision energy and at lower excitation conditions, respectively. The latter takes place by stabilization of the deaminated aspartate solvated with two residual molecules of water (present in the collision cell). This desolvated anion formed is an α lactone substituted by a methylene carboxylate group. The vibrational excitation acquired by [(D-H)-NH3]-during its isolation is enough to allow its prompt decarboxylation with a barrier lower than 8.4kJ/mol. In addition, study of glutamic acid-like diastereomers constituted by a cyclopropane, hindering any side chain rotation, confirms the impact of the three-dimensional geometry on fragmentation pathways. A significant specific loss of water is only observed for one of these diastereomers. Other experiments, such as stable isotope labeling, need to be performed to elucidate all the observed losses from activated aspartate and glutamate anions. These first mechanistic interpretations enhance understanding of this dissociative pathway and underline the necessity of studying fragmentation of a large number of various compounds to implement properly new algorithms for de novo elucidation of unknown metabolites.

Impact of collection conditions on the metabolite content of human urine samples as analyzed by liquid chromatography coupled to mass spectrometry and nuclear magnetic resonance spectroscopy.

There is a lack of comprehensive studies documenting the impact of sample collection conditions on metabolic composition of human urine. To address this issue, two experiments were performed at a 3-month interval, in which midstream urine samples from healthy individuals were collected, pooled, divided into several aliquots and kept under specific conditions (room temperature, 4 °C, with or without preservative) up to 72 h before storage at -80 °C. Samples were analyzed by high-performance liquid chromatography coupled to high-resolution mass spectrometry and bacterial contamination was monitored by turbidimetry. Multivariate analyses showed that urinary metabolic fingerprints were affected by the presence of preservatives and also by storage at room temperature from 24 to 72 h, whereas no change was observed for urine samples stored at 4 °C over a 72-h period. Investigations were then focused on 280 metabolites previously identified in urine: 19 of them were impacted by the kind of sample collection protocol in both experiments, including 12 metabolites affected by bacterial contamination and 7 exhibiting poor chemical stability. Finally, our results emphasize that the use of preservative prevents bacterial overgrowth, but does not avoid metabolite instability in solution, whereas storage at 4 °C inhibits bacterial overgrowth at least over a 72-h period and slows the chemical degradation process. Consequently, and for further LC/MS analyses, human urine samples should be kept at 4 °C if their collection is performed over 24 h.

Annotation of the human serum metabolome by coupling three liquid chromatography methods to high-resolution mass spectrometry.

This work aims at evaluating the relevance and versatility of liquid chromatography coupled to high resolution mass spectrometry (LC/HRMS) for performing a qualitative and comprehensive study of the human serum metabolome. To this end, three different chromatographic systems based on a reversed phase (RP), hydrophilic interaction chromatography (HILIC) and a pentafluorophenylpropyl (PFPP) stationary phase were used, with detection in both positive and negative electrospray modes. LC/HRMS platforms were first assessed for their ability to detect, retain and separate 657 metabolite standards representative of the chemical families occurring in biological fluids. More than 75% were efficiently retained in either one LC-condition and less than 5% were exclusively retained by the RP column. These three LC/HRMS systems were then evaluated for their coverage of serum metabolome. The combination of RP, HILIC and PFPP based LC/HRMS methods resulted in the annotation of about 1328 features in the negative ionization mode, and 1358 in the positive ionization mode on the basis of their accurate mass and precise retention time in at least one chromatographic condition. Less than 12% of these annotations were shared by the three LC systems, which highlights their complementarity. HILIC column ensured the greatest metabolome coverage in the negative ionization mode, whereas PFPP column was the most effective in the positive ionization mode. Altogether, 192 annotations were confirmed using our spectral database and 74 others by performing MS/MS experiments. This resulted in the formal or putative identification of 266 metabolites, among which 59 are reported for the first time in human serum.

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.

Pathophysiology of sickle cell disease is mirrored by the red blood cell metabolome.

Emerging metabolomic tools can now be used to establish metabolic signatures of specialized circulating hematopoietic cells in physiologic or pathologic conditions and in human hematologic diseases. To determine metabolomes of normal and sickle cell erythrocytes, we used an extraction method of erythrocytes metabolites coupled with a liquid chromatography-mass spectrometry-based metabolite profiling method. Comparison of these 2 metabolomes identified major changes in metabolites produced by (1) endogenous glycolysis characterized by accumulation of many glycolytic intermediates; (2) endogenous glutathione and ascorbate metabolisms characterized by accumulation of ascorbate metabolism intermediates, such as diketogulonic acid and decreased levels of both glutathione and glutathione disulfide; (3) membrane turnover, such as carnitine, or membrane transport characteristics, such as amino acids; and (4) exogenous arginine and NO metabolisms, such as spermine, spermidine, or citrulline. Finally, metabolomic analysis of young and old normal red blood cells indicates metabolites whose levels are directly related to sickle cell disease. These results show the relevance of metabolic profiling for the follow-up of sickle cell patients or other red blood cell diseases and pinpoint the importance of metabolomics to further depict the pathophysiology of human hematologic diseases.