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 .

Milk metabolome reveals variations on enteric methane emissions from dairy cows fed a specific inhibitor of the methanogenesis pathway.

Metabolome profiling in biological fluids is an interesting approach for exploring markers of methane emissions in ruminants. In this study, a multiplatform metabolomics approach was used for investigating changes in milk metabolic profiles related to methanogenesis in dairy cows. For this purpose, 25 primiparous Holstein cows at similar lactation stage were fed the same diet supplemented with (treated, n = 12) or without (control, n = 13) a specific antimethanogenic additive that reduced enteric methane production by 23% with no changes in intake, milk production, and health status. The study lasted 6 wk, with sampling and measures performed in wk 5 and 6. Milk samples were analyzed using 4 complementary analytical methods, including 2 untargeted (nuclear magnetic resonance and liquid chromatography coupled to a quadrupole-time-of-flight mass spectrometer) and 2 targeted (liquid chromatography-tandem mass spectrometry and gas chromatography coupled to a flame ionization detector) approaches. After filtration, variable selection and normalization data from each analytical platform were then analyzed using multivariate orthogonal partial least square discriminant analysis. All 4 analytical methods were able to differentiate cows from treated and control groups. Overall, 38 discriminant metabolites were identified, which affected 10 metabolic pathways including methane metabolism. Some of these metabolites such as dimethylsulfoxide, dimethylsulfone, and citramalic acid, detected by nuclear magnetic resonance or liquid chromatography-mass spectrometry methods, originated from the rumen microbiota or had a microbial-host animal co-metabolism that could be associated with methanogenesis. Also, discriminant milk fatty acids detected by targeted gas chromatography were mostly of ruminal microbial origin. Other metabolites and metabolic pathways significantly affected were associated with AA metabolism. These findings provide new insight on the potential role of milk metabolites as indicators of enteric methane modifications in dairy cows.

Evaluation of the High-Field Orbitrap Fusion for Compound Annotation in Metabolomics.

Annotation of signals of interest represents a key point in mass spectrometry-based metabolomics studies. The first level of investigation is the elemental composition, which can be deduced from accurately measured masses and isotope patterns. However, accuracy of these two parameters remains to be evaluated on last generation mass spectrometers to determine the level of confidence that can be used during the annotation process. In this context, we evaluated the performance of the Orbitrap Fusion mass spectrometer for the first time and demonstrated huge potential for metabolite annotation via elemental composition determination. This work was performed using a set of 50 standard compounds analyzed under LC/MS conditions in solvent and biological media. Accurate control of the number of trapped ions proved mandatory to avoid space charge effects, ensure sub-ppm mass accuracy (using external calibration), and reliable measurement of isotopic patterns at 500,000 resolution. On the basis of the results, we propose standard optimized experimental conditions for performing robust and accurate untargeted metabolomics on the Orbitrap Fusion at high mass measurement and mass spectral accuracy.

proFIA: a data preprocessing workflow for flow injection analysis coupled to high-resolution mass spectrometry.

MOTIVATION: Flow Injection Analysis coupled to High-Resolution Mass Spectrometry (FIA-HRMS) is a promising approach for high-throughput metabolomics. FIA-HRMS data, however, cannot be preprocessed with current software tools which rely on liquid chromatography separation, or handle low resolution data only. RESULTS: We thus developed the proFIA package, which implements a suite of innovative algorithms to preprocess FIA-HRMS raw files, and generates the table of peak intensities. The workflow consists of 3 steps: (i) noise estimation, peak detection and quantification, (ii) peak grouping across samples and (iii) missing value imputation. In addition, we have implemented a new indicator to quantify the potential alteration of the feature peak shape due to matrix effect. The preprocessing is fast (less than 15 s per file), and the value of the main parameters (ppm and dmz) can be easily inferred from the mass resolution of the instrument. Application to two metabolomics datasets (including spiked serum samples) showed high precision (96%) and recall (98%) compared with manual integration. These results demonstrate that proFIA achieves very efficient and robust detection and quantification of FIA-HRMS data, and opens new opportunities for high-throughput phenotyping. AVAILABILITY AND IMPLEMENTATION: The proFIA software (as well as the plasFIA dataset) is available as an R package on the Bioconductor repository (http://bioconductor.org/packages/proFIA), and as a Galaxy module on the Main Toolshed (https://toolshed.g2.bx.psu.edu), and on the Workflow4Metabolomics online infrastructure (http://workflow4metabolomics.org). CONTACT: alexis.delabriere@cea.fr or etienne.thevenot@cea.fr. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The tumor suppressor annexin A10 is a novel component of nuclear paraspeckles.

Annexin A10 is the latest identified member of the annexin family of Ca(2+)- and phospholipid-binding proteins. In previous studies, downregulation of annexin A10 was correlated with dedifferentiation, invasion, and tumor progression, pointing to a possible tumor suppressor role. However, the biochemical characteristics and functions of annexin A10 remain unknown. We show that annexin A10 displays biochemical characteristics atypical for an annexin, indicating a Ca(2+)- and membrane-binding-independent function. Annexin A10 co-localizes with the mRNA-binding proteins SFPQ and PSPC1 at paraspeckles, an only recently discovered nuclear body, and decreases paraspeckle numbers when overexpressed in HeLa cells. In addition, annexin A10 relocates to dark perinucleolar caps upon transcriptional inhibition of RNA polymerase II. We mapped the cap-binding function of annexin A10 to the proximal part of the core domain, which is missing in the short isoform of annexin A10, and show its independence from the remaining functional type II Ca(2+)-binding site. In contrast to this, paraspeckle recruitment required additional core regions and was negatively affected by the mutation of the last type II Ca(2+)-binding site. Additionally, we show that overexpression of annexin A10 in HeLa cells increases their sensitivity to apoptosis and reduces colony formation. The identification of unique nuclear and biochemical characteristics of annexin A10 points towards its membrane-independent role in paraspeckle-associated mRNA regulation or processing.

Stepchild phosphohistidine: acid-labile phosphorylation becomes accessible by functional proteomics.

Bioanalytical techniques were preferentially developed for the investigation of phosphohydroxyamino acids in the past and there is a wealth of information on the detection of serine, threonine and tyrosine phosphorylation in functional proteomics. However, similarly important for protein regulation and signalling is the phosphorylation of other amino acids such as histidine, but its detection is hampered by the sensitivity to acid. Mass spectrometry in conjunction with chromatographic methods is allowing us to start to get a handle on phosphohistidine. (32)P-labelling and amino acid analysis for phosphorylation site determination is increasingly complemented by typical proteomic approaches based on reversed-phase peptide separation and gas-phase fragmentation. Chemical phosphorylation of peptides is a valuable tool, therefore, for the generation of analytical standards for use in method development.

Investigation of space charge effects and ion trapping capacity on direct introduction ultra-high-resolution mass spectrometry workflows for metabolomics.

Ultra-high-resolution mass spectrometry, in the absence of chromatography, is finding its place for direct analyses of highly complex mixtures, such as those encountered during untargeted metabolomics screening. Advances, however, have been tempered by difficulties such as uneven signal suppression experienced during electrospray ionization. Moreover, ultra-high-resolution mass spectrometers that use Orbitrap and ICR analyzers both suffer from limited ion trapping capacities, owing principally to space-charge effects. This study has evaluated and contrasted the above two types of Fourier transform mass spectrometers for their abilities to detect and identify by accurate mass measurement, small molecule metabolites present in complex mixtures. For these direct introduction studies, the Orbitrap Fusion showed a major advantage in terms of speed of analysis, enabling detection of 218 of 440 molecules (<2 ppm error, 500 000 resolution at m/z 200) present in a complex mixture in 5 min. This approach is the most viable for high-throughput workflows, such as those used in investigations involving very large cohorts of metabolomics samples. From the same mixture, 183 unique molecules were observed by FT-ICR in the broadband mode, but this number was raised to 235 when "selected ion monitoring-stitching" (SIM-stitching) was employed (<0.1 ppm error, 7 T magnet with dynamic harmonization cell, 1.8 million resolution at m/z 200, both cases). SIM-stitching FT-ICR thus offered the most complete detection, which may be of paramount importance in situations where it is essential to obtain the most complete metabolic profile possible. This added completeness, however, came at the cost of a more lengthy analysis time (120 min including manual treatment). Compared to the data presented here, future automation of processing, plus the use of absorption mode detection, segmented ion detection (stepwise detection of smaller width m/z sections), and higher magnetic field strengths, can substantially reduce FT-ICR acquisition times.

Inhibition of enteric methanogenesis in dairy cows induces changes in plasma metabolome highlighting metabolic shifts and potential markers of emission.

There is scarce information on whether inhibition of rumen methanogenesis induces metabolic changes on the host ruminant. Understanding these possible changes is important for the acceptance of methane-reducing practices by producers. In this study we explored the changes in plasma profiles associated with the reduction of methane emissions. Plasma samples were collected from lactating primiparous Holstein cows fed the same diet with (Treated, n = 12) or without (Control, n = 13) an anti-methanogenic feed additive for six weeks. Daily methane emissions (CH4, g/d) were reduced by 23% in the Treated group with no changes in milk production, feed intake, body weight, and biochemical indicators of health status. Plasma metabolome analyses were performed using untargeted [nuclear magnetic resonance (NMR) and liquid chromatography-mass spectrometry (LC-MS)] and targeted (LC-MS/MS) approaches. We identified 48 discriminant metabolites. Some metabolites mainly of microbial origin such as dimethylsulfone, formic acid and metabolites containing methylated groups like stachydrine, can be related to rumen methanogenesis and can potentially be used as markers. The other discriminant metabolites are produced by the host or have a mixed microbial-host origin. These metabolites, which increased in treated cows, belong to general pathways of amino acids and energy metabolism suggesting a systemic non-negative effect on the animal.

Effectiveness of Interventions to Modulate the Rumen Microbiota Composition and Function in Pre-ruminant and Ruminant Lambs.

Modulating the assembly of the ruminal microbiota might have practical implications in production. We tested how an early-life dietary intervention in lambs influences the diversity and function of the ruminal microbiota during and after the intervention. Microbiota resilience during a repeated dietary intervention was also tested. The treatment, aiming to mitigate enteric methane emissions, combined garlic essential oil and linseed oil. Fifty-six lambs and their dams were allocated to two groups and treatment (T1) or placebo (C1) was drenched from birth until 10 weeks of life. Lambs were weaned at 8 weeks. From 16 to 20 weeks, lambs in each group were divided in two subgroups that received (T1-T2 and C1-T2) or not (T1-C2 and C1-C2) the same treatment. Measurements were done at 8, 14, and 20 weeks. Average daily gain was similar between groups. Methane production was reduced by treatment at 8 and 20 weeks but at 14 weeks it was similar between C1 and T1. Interestingly, early-life treated lambs displayed a numerical increase (P = 0.12) in methane emissions at 20 weeks compared with non-treated lambs. Concentration of VFA was not affected by the intervention at 8 or 14 weeks but a lower concentration was observed in T2 lambs compared with C2 at week 20. Metataxonomics (rRNA gene) revealed differences in archaeal communities between groups of lambs when treatment was applied (weeks 8 and 20); whereas, in accord with methane emissions, these differences disappeared when treatment was discontinued (week 14). Protozoal community structure was not affected by treatment. In contrast, bacterial community structure differed between treated and non-treated lambs during and after the intervention. Rumen and urine LC-MS and NMR metabolomics at week 20 separated C2 from T2 lambs and correlation analysis highlighted interactions between microbes and metabolites, notably that of methylated compounds and Methanomassiliicocceae methanogens. This study demonstrates that a long-term early-life intervention induced modifications in the composition of the rumen bacterial community that persisted after the intervention ceased with little or no effect on archaeal and protozoal communities. However, there was no persistency of the early-life intervention on methanogenesis indicating resilience for this function.

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.

Chemical phosphorylation of histidine residues in proteins using potassium phosphoramidate -- a tool for the analysis of acid-labile phosphorylation.

Histidine (His)-phosphorylation is labile at low pH and has therefore not been in the focus of proteomic analysis in the past although a few single-case studies have been performed. The systematic investigation of model substances generates confidence in experimental procedures and allows determining their limits. In order to extend earlier peptide studies to His-phosphoproteins and elucidate their behavior and recovery in proteomic procedures, potassium phosphoramidate (PPA) was used to generate model proteins, which were subsequently exposed to gel electrophoresis, enzymatic digest and mass spectrometry based protein analysis. Myoglobin having eleven His-residues was highly phosphorylated by PPA showing a distribution of modified protein forms with four phosphate-carrying His-residues in the most abundant species. Since myoglobin is a heme-binding protein it was additionally indicated that synthetic phosphorylation may retain protein folding targeting only structurally accessible His-residues. Insulin, ßcasein and cytochrome C were phosphorylated on their His-residues and the corresponding peptides were detected in protein digest mixtures and in background of tryptically digested Escherichia coli lysate. In gel electrophoresis protocols, lengthy procedures at low pH such as staining reduced recovery. Synthetic phosphorylation of proteins and peptides with PPA allows the generation of suitable standard compounds for the systematic optimization of analytical protocols. All tested proteins responded to PPA treatment, partially even preserving tertiary structure. A distribution of modified protein forms was generated which could be subjected to further separation to isolate the fully phosphorylated species.