Sympathetic nervous activation, mitochondrial dysfunction and outcome in acutely decompensated cirrhosis: the metabolomic prognostic models (CLIF-C MET).

BACKGROUND AND AIMS: Current prognostic scores of patients with acutely decompensated cirrhosis (AD), particularly those with acute-on-chronic liver failure (ACLF), underestimate the risk of mortality. This is probably because systemic inflammation (SI), the major driver of AD/ACLF, is not reflected in the scores. SI induces metabolic changes, which impair delivery of the necessary energy for the immune reaction. This investigation aimed to identify metabolites associated with short-term (28-day) death and to design metabolomic prognostic models. METHODS: Two prospective multicentre large cohorts from Europe for investigating ACLF and development of ACLF, CANONIC (discovery, n=831) and PREDICT (validation, n=851), were explored by untargeted serum metabolomics to identify and validate metabolites which could allow improved prognostic modelling. RESULTS: Three prognostic metabolites strongly associated with death were selected to build the models. 4-Hydroxy-3-methoxyphenylglycol sulfate is a norepinephrine derivative, which may be derived from the brainstem response to SI. Additionally, galacturonic acid and hexanoylcarnitine are associated with mitochondrial dysfunction. Model 1 included only these three prognostic metabolites and age. Model 2 was built around 4-hydroxy-3-methoxyphenylglycol sulfate, hexanoylcarnitine, bilirubin, international normalised ratio (INR) and age. In the discovery cohort, both models were more accurate in predicting death within 7, 14 and 28 days after admission compared with MELDNa score (C-index: 0.9267, 0.9002 and 0.8424, and 0.9369, 0.9206 and 0.8529, with model 1 and model 2, respectively). Similar results were found in the validation cohort (C-index: 0.940, 0.834 and 0.791, and 0.947, 0.857 and 0.810, with model 1 and model 2, respectively). Also, in ACLF, model 1 and model 2 outperformed MELDNa 7, 14 and 28 days after admission for prediction of mortality. CONCLUSIONS: Models including metabolites (CLIF-C MET) reflecting SI, mitochondrial dysfunction and sympathetic system activation are better predictors of short-term mortality than scores based only on organ dysfunction (eg, MELDNa), especially in patients with ACLF.

Quantification of Urine and Plasma Porphyrin Precursors Using LC-MS in Acute Hepatic Porphyrias: Improvement in Routine Diagnosis and in the Monitoring of Kidney Failure Patients.

BACKGROUND: The quantification of delta-aminolevulinic acid (ALA) and porphobilinogen (PBG) in urine are the first-line tests for diagnosis and monitoring of acute hepatic porphyrias (AHP). Ion-exchange chromatography (IEC), which is time- and staff-consuming and limited to urine, is still the preferred method in many specialized laboratories, despite the development of mass spectrometry-based methods. METHODS: We describe a new LC-MS method that allows for rapid and simple quantification of ALA and PBG in urine and plasma with an affordable instrument that was used to analyze 2260 urine samples and 309 blood samples collected in 2 years of routine activity. The results were compared to those obtained with IEC, and urine reference ranges and concentrations in asymptomatic carriers were determined. Plasma concentrations were measured in healthy subjects and subgroups of symptomatic and asymptomatic AHP carriers. RESULTS: In urine, the clinical decision limits were not impacted by the change of method despite discrepancies in low absolute concentrations, leading to lower normal values. Two-thirds of asymptomatic AHP carriers (with the exception of coproporphyria carriers) showed an increased urine PBG concentration. Urine and plasma levels showed a good correlation except in patients with kidney disease in whom the urine/plasma ratio was relatively low. CONCLUSION: We described an LC-MS based method for the routine diagnosis and monitoring of AHP that allows for the detection of more asymptomatic carriers than the historical method. Blood analysis appears to be particularly relevant for patients with kidney disease, where urine measurement underestimates the increase in ALA and PBG levels.

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 .

Metabolomics in the understanding and management of hepatic encephalopathy.

Metabolomics refers to the study of biological components below 1000 Daltons (Da) involved in metabolic pathways as substrates, products or effectors. According to the interconnected metabolic disturbances that have been described in the pathophysiology of hepatic encephalopathy (HE), this technique appears to be well adapted to study and better delineate the disease. This review will focus on recent advances in metabolomics in the field of HE. Thus, after a brief overview of the general principles of metabolomics, we will discuss metabolomics as a potentially efficient tool for unraveling new HE pathophysiological insights, biomarkers identification, or as a predicting tool for treatment response or outcome prognosis. Finally, we will give our vision on the prospects offered by metabolomics for improving care of HE patients.

Metabolomics for personalized medicine: the input of analytical chemistry from biomarker discovery to point-of-care tests.

Metabolomics refers to the large-scale detection, quantification, and analysis of small molecules (metabolites) in biological media. Although metabolomics, alone or combined with other omics data, has already demonstrated its relevance for patient stratification in the frame of research projects and clinical studies, much remains to be done to move this approach to the clinical practice. This is especially true in the perspective of being applied to personalized/precision medicine, which aims at stratifying patients according to their risk of developing diseases, and tailoring medical treatments of patients according to individual characteristics in order to improve their efficacy and limit their toxicity. In this review article, we discuss the main challenges linked to analytical chemistry that need to be addressed to foster the implementation of metabolomics in the clinics and the use of the data produced by this approach in personalized medicine. First of all, there are already well-known issues related to untargeted metabolomics workflows at the levels of data production (lack of standardization), metabolite identification (small proportion of annotated features and identified metabolites), and data processing (from automatic detection of features to multi-omic data integration) that hamper the inter-operability and reusability of metabolomics data. Furthermore, the outputs of metabolomics workflows are complex molecular signatures of few tens of metabolites, often with small abundance variations, and obtained with expensive laboratory equipment. It is thus necessary to simplify these molecular signatures so that they can be produced and used in the field. This last point, which is still poorly addressed by the metabolomics community, may be crucial in a near future with the increased availability of molecular signatures of medical relevance and the increased societal demand for participatory medicine.

Quantitative Assessment of SARS-CoV-2 Virus in Nasopharyngeal Swabs Stored in Transport Medium by a Straightforward LC-MS/MS Assay Targeting Nucleocapsid, Membrane, and Spike Proteins.

Alternative methods to RT-PCR for SARS-CoV-2 detection are investigated to provide complementary data on viral proteins, increase the number of tests performed, or identify false positive/negative results. Here, we have developed a simple mass spectrometry assay for SARS-CoV-2 in nasopharyngeal swab samples using common laboratory reagents. The method employs high sensitivity and selectivity targeted mass spectrometry detection, monitoring nine constitutive peptides representative of the three main viral proteins and a straightforward pellet digestion protocol for convenient routine applications. Absolute quantification of N, M, and S proteins was achieved by addition of isotope-labeled versions of best peptides. Limit of detection, recovery, precision, and linearity were thoroughly evaluated in four representative viral transport media (VTM) containing distinct total protein content. The protocol was sensitive in all swab media with limit of detection determined at 2 × 103 pfu/mL, corresponding to as low as 30 pfu injected into the LC-MS/MS system. When tested on VTM-stored nasopharyngeal swab samples from positive and control patients, sensitivity was similar to or better than rapid immunoassay dipsticks, revealing a corresponding RT-PCR detection threshold at Ct ∼ 24. The study represents the first thorough evaluation of sensitivity and robustness of targeted mass spectrometry in nasal swabs, constituting a promising SARS-CoV-2 antigen assay for the first-line diagnosis of COVID-19 and compatible with the constraints of clinical settings. The raw files generated in this study can be found on PASSEL (Peptide Atlas) under data set identifier PASS01646.

Assessing the role of amino acids in systemic inflammation and organ failure in patients with ACLF.

BACKGROUND & AIMS: Systemic inflammation and organ failure(s) are the hallmarks of acute-on-chronic liver failure (ACLF), yet their pathogenesis remains uncertain. Herein, we aimed to assess the role of amino acids in these processes in patients with ACLF. METHODS: The blood metabolomic database of the CANONIC study (comprising 137 metabolites, with 43% related to amino acids) - obtained in 181 patients with ACLF and 650 with acute decompensation without ACLF (AD) - was reanalyzed with a focus on amino acids, in particular 9 modules of co-regulated metabolites. We also compared blood metabolite levels between ACLF and AD. RESULTS: The main findings in ACLF were: i) Metabolite modules were increased in parallel with increased levels of markers of systemic inflammation and oxidative stress. ii) Seventy percent of proteinogenic amino acids were present and most were increased. iii) A metabolic network, comprising the amino acids aspartate, glutamate, the serine-glycine one-carbon metabolism (folate cycle), and methionine cycle, was activated, suggesting increased purine and pyrimidine nucleotide synthesis. iv) Cystathionine, L-cystine, glutamate and pyroglutamate, which are involved in the transsulfuration pathway (a methionine cycle branch) were increased, consistent with increased synthesis of the antioxidant glutathione. v) Intermediates of the catabolism of 5 out of the 6 ketogenic amino acids were increased. vi) The levels of spermidine (a polyamine inducer of autophagy with anti-inflammatory effects) were decreased. CONCLUSIONS: In ACLF, blood amino acids fueled protein and nucleotide synthesis required for the intense systemic inflammatory response. Ketogenic amino acids were extensively catabolized to produce energy substrates in peripheral organs, an effect that was insufficient because organs failed. Finally, the decrease in spermidine levels may cause a defect in autophagy contributing to the proinflammatory phenotype in ACLF. LAY SUMMARY: Systemic inflammation and organ failures are hallmarks of acute-on-chronic liver failure (ACLF). Herein, we aimed to characterize the role of amino acids in these processes. The blood metabolome of patients with acutely decompensated cirrhosis, and particularly those with ACLF, reveals evidence of intense skeletal muscle catabolism. Importantly, amino acids (along with glucose), are used for intense anabolic, energy-consuming metabolism in patients with ACLF, presumably to support de novo nucleotide and protein synthesis in the activated innate immune system.

Untargeted lipidomics uncovers lipid signatures that distinguish severe from moderate forms of acutely decompensated cirrhosis.

BACKGROUND & AIMS: Acute decompensation (AD) of cirrhosis is a heterogeneous clinical entity associated with moderate mortality. In some patients, this condition develops quickly into the more deadly acute-on-chronic liver failure (ACLF), in which other organs such as the kidneys or brain fail. The aim of this study was to characterize the blood lipidome in a large series of patients with cirrhosis and identify specific signatures associated with AD and ACLF development. METHODS: Serum untargeted lipidomics was performed in 561 patients with AD (518 without and 43 with ACLF) (discovery cohort) and in 265 patients with AD (128 without and 137 with ACLF) in whom serum samples were available to perform repeated measurements during the 28-day follow-up (validation cohort). Analyses were also performed in 78 patients with AD included in a therapeutic albumin trial (43 patients with compensated cirrhosis and 29 healthy individuals). RESULTS: The circulating lipid landscape associated with cirrhosis was characterized by a generalized suppression, which was more manifest during AD and in non-surviving patients. By computing discriminating accuracy and the variable importance projection score for each of the 223 annotated lipids, we identified a sphingomyelin fingerprint specific for AD of cirrhosis and a distinct cholesteryl ester and lysophosphatidylcholine fingerprint for ACLF. Liver dysfunction and infections were the principal net contributors to these fingerprints, which were dynamic and interchangeable between patients with AD whose condition worsened to ACLF and those who improved. Notably, blood lysophosphatidylcholine levels increased in these patients after albumin therapy. CONCLUSIONS: Our findings provide insights into the lipid landscape associated with decompensation of cirrhosis and ACLF progression and identify unique non-invasive diagnostic biomarkers of advanced cirrhosis. LAY SUMMARY: Analysis of lipids in blood from patients with advanced cirrhosis reveals a general suppression of their levels in the circulation of these patients. A specific group of lipids known as sphingomyelins are useful to distinguish between patients with compensated and decompensated cirrhosis. Another group of lipids designated cholesteryl esters further distinguishes patients with decompensated cirrhosis who are at risk of developing organ failures.

Glutathione conjugates of the mercapturic acid pathway and guanine adduct as biomarkers of exposure to CEES, a sulfur mustard analog.

Sulfur mustard (SM), a chemical warfare agent, is a strong alkylating compound that readily reacts with numerous biomolecules. The goal of the present work was to define and validate new biomarkers of exposure to SM that could be easily accessible in urine or plasma. Because investigations using SM are prohibited by the Organisation for the Prohibition of Chemical Weapons, we worked with 2-chloroethyl ethyl sulfide (CEES), a monofunctional analog of SM. We developed an ultra-high-pressure liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) approach to the conjugate of CEES to glutathione and two of its metabolites: the cysteine and the N-acetylcysteine conjugates. The N7-guanine adduct of CEES (N7Gua-CEES) was also targeted. After synthesizing the specific biomarkers, a solid-phase extraction protocol and a UHPLC-MS/MS method with isotopic dilution were optimized. We were able to quantify N7Gua-CEES in the DNA of HaCaT keratinocytes and of explants of human skin exposed to CEES. N7Gua-CEES was also detected in the culture medium of these two models, together with the glutathione and the cysteine conjugates. In contrast, the N-acetylcysteine conjugate was not detected. The method was then applied to plasma from mice cutaneously exposed to CEES. All four markers could be detected. Our present results thus validate both the analytical technique and the biological relevance of new, easily quantifiable biomarkers of exposure to CEES. Because CEES behaves very similar to SM, the results are promising for application to this toxic of interest.

Top-Down and Bottom-Up Proteomics of Circulating S100A8/S100A9 in Plasma of Septic Shock Patients.

Well-characterized prognostic biomarkers and reliable quantitative methods are key in sepsis management. Among damage-associated molecular patterns, S100A8/S100A9 complexes are reported to be markers for injured cells and to improve the prediction of death in septic shock patients. In view of the structural diversity observed for the intracellular forms, insight into circulating complexes and proteoforms is required to establish prognostic biomarkers. Here, we developed top-down and bottom-up proteomics to characterize the association of S100A8 and S100A9 in complexes and major circulating proteoforms. An antibody-free method was developed for absolute quantification of S100A8/S100A9 in a cohort of 49 patients to evaluate the prognostic value on the first day after admission for septic shock. The predominant circulating forms identified by top-down proteomics were S100A8, mono-oxidized S100A8, truncated acetylated S100A9, and S-nitrosylated S100A9. S100A8, truncated acetylated S100A9, and mono-oxidized S100A8 discriminated between survivors and nonsurvivors, along with total S100A8/S100A9 measured by the antibody-free bottom-up method. Overall, new insights into circulating S100A8/S100A9 and confirmation of its prognostic value in septic shock are crucial in qualification of this biomarker. Also, the simple antibody-free assay would support the harmonization of S100A8/S100A9 measurements.

Blood metabolomics uncovers inflammation-associated mitochondrial dysfunction as a potential mechanism underlying ACLF.

BACKGROUND & AIMS: Acute-on-chronic liver failure (ACLF), which develops in patients with cirrhosis, is characterized by intense systemic inflammation and organ failure(s). Because systemic inflammation is energetically expensive, its metabolic costs may result in organ dysfunction/failure. Therefore, we aimed to analyze the blood metabolome in patients with cirrhosis, with and without ACLF. METHODS: We performed untargeted metabolomics using liquid chromatography coupled to high-resolution mass spectrometry in serum from 650 patients with AD (acute decompensation of cirrhosis, without ACLF), 181 with ACLF, 43 with compensated cirrhosis, and 29 healthy individuals. RESULTS: Of the 137 annotated metabolites identified, 100 were increased in patients with ACLF of any grade, relative to those with AD, and 38 comprised a distinctive blood metabolite fingerprint for ACLF. Among patients with ACLF, the intensity of the fingerprint increased across ACLF grades, and was similar in patients with kidney failure and in those without, indicating that the fingerprint reflected not only decreased kidney excretion but also altered cell metabolism. The higher the ACLF-associated fingerprint intensity, the higher the plasma levels of inflammatory markers, tumor necrosis factor α, soluble CD206, and soluble CD163. ACLF was characterized by intense proteolysis and lipolysis; amino acid catabolism; extra-mitochondrial glucose metabolism through glycolysis, pentose phosphate, and D-glucuronate pathways; depressed mitochondrial ATP-producing fatty acid ß-oxidation; and extra-mitochondrial amino acid metabolism giving rise to metabotoxins. CONCLUSIONS: In ACLF, intense systemic inflammation is associated with blood metabolite accumulation and profound alterations in major metabolic pathways, in particular inhibition of mitochondrial energy production, which may contribute to the development of organ failures. LAY SUMMARY: Acute-on-chronic liver failure (ACLF), which develops in patients with cirrhosis, is characterized by intense systemic inflammation and organ failure(s). Because systemic inflammation is energetically expensive, its metabolic costs may result in organ dysfunction/failure. We identified a 38-metabolite blood fingerprint specific for ACLF that revealed mitochondrial dysfunction in peripheral organs. This may contribute to organ failures.

MetaboRank: network-based recommendation system to interpret and enrich metabolomics results.

Motivation: Metabolomics has shown great potential to improve the understanding of complex diseases, potentially leading to therapeutic target identification. However, no single analytical method allows monitoring all metabolites in a sample, resulting in incomplete metabolic fingerprints. This incompleteness constitutes a stumbling block to interpretation, raising the need for methods that can enrich those fingerprints. We propose MetaboRank, a new solution inspired by social network recommendation systems for the identification of metabolites potentially related to a metabolic fingerprint. Results: MetaboRank method had been used to enrich metabolomics data obtained on cerebrospinal fluid samples from patients suffering from hepatic encephalopathy (HE). MetaboRank successfully recommended metabolites not present in the original fingerprint. The quality of recommendations was evaluated by using literature automatic search, in order to check that recommended metabolites could be related to the disease. Complementary mass spectrometry experiments and raw data analysis were performed to confirm these suggestions. In particular, MetaboRank recommended the overlooked α-ketoglutaramate as a metabolite which should be added to the metabolic fingerprint of HE, thus suggesting that metabolic fingerprints enhancement can provide new insight on complex diseases. Availability and implementation: Method is implemented in the MetExplore server and is available at www.metexplore.fr. A tutorial is available at https://metexplore.toulouse.inra.fr/com/tutorials/MetaboRank/2017-MetaboRank.pdf. Supplementary information: Supplementary data are available at Bioinformatics online.

Orchestration of Tryptophan-Kynurenine Pathway, Acute Decompensation, and Acute-on-Chronic Liver Failure in Cirrhosis.

Systemic inflammation (SI) is involved in the pathogenesis of acute decompensation (AD) and acute-on-chronic liver failure (ACLF) in cirrhosis. In other diseases, SI activates tryptophan (Trp) degradation through the kynurenine pathway (KP), giving rise to metabolites that contribute to multiorgan/system damage and immunosuppression. In the current study, we aimed to characterize the KP in patients with cirrhosis, in whom this pathway is poorly known. The serum levels of Trp, key KP metabolites (kynurenine and kynurenic and quinolinic acids), and cytokines (SI markers) were measured at enrollment in 40 healthy subjects, 39 patients with compensated cirrhosis, 342 with AD (no ACLF) and 180 with ACLF, and repeated in 258 patients during the 28-day follow-up. Urine KP metabolites were measured in 50 patients with ACLF. Serum KP activity was normal in compensated cirrhosis, increased in AD and further increased in ACLF, in parallel with SI; it was remarkably higher in ACLF with kidney failure than in ACLF without kidney failure in the absence of differences in urine KP activity and fractional excretion of KP metabolites. The short-term course of AD and ACLF (worsening, improvement, stable) correlated closely with follow-up changes in serum KP activity. Among patients with AD at enrollment, those with the highest baseline KP activity developed ACLF during follow-up. Among patients who had ACLF at enrollment, those with immune suppression and the highest KP activity, both at baseline, developed nosocomial infections during follow-up. Finally, higher baseline KP activity independently predicted mortality in patients with AD and ACLF. Conclusion: Features of KP activation appear in patients with AD, culminate in patients with ACLF, and may be involved in the pathogenesis of ACLF, clinical course, and mortality.

Immune components of early breastmilk: Association with maternal factors and with reported food allergy in childhood.

BACKGROUND: Breastmilk (BM) may participate in driving gut barrier function and immunity in the neonate. We analyzed immune and growth factor concentrations in early BM and their association with maternal/environmental characteristics and with food allergy (FA) in childhood. METHODS: One BM sample was collected in maternity from some mothers in the EDEN birth cohort (n = 2002 mother-child dyads). A random selection was performed among available samples (subcohort, n = 272), for which all deliveries were full-term, various maternal/environmental characteristics were recorded, and parents answered yearly the question "Has a medical doctor diagnosed a FA in your child?" (26 parent-reported FA cases). Only samples collected between day 2 and day 6 post-partum were considered for descriptive analysis (n = 263). Samples for all other FA cases available were added to the subcohort (46 additional cases; "casecohort" design). Fifty cytokines, antibodies, and growth factor concentrations were determined using multiplexed kits and analyzed using robust statistical procedures. RESULTS: BM components exhibited wide concentration ranges and global day-to-day variation. Different clusters of correlated factors appeared, with components from the main cluster related to maternal diet during pregnancy. Primiparity was positively associated with eleven other components, whereas other factors (eg, maternal atopy and smoking) were related to fewer components. Finally, the casecohort design highlighted a positive association between CXCL10, TNFß, and IL-2 concentrations and reported FA in childhood. CONCLUSION: Beyond the unique description of early BM composition, we show that immune information transmitted to the neonate is related to various maternal factors and identified components associated with FA diagnosis in childhood.

Simultaneous quantification of tau and α-synuclein in cerebrospinal fluid by high-resolution mass spectrometry for differentiation of Lewy Body Dementia from Alzheimer's Disease and controls.

Tau and α-synuclein are central in several neurodegenerative diseases, including Alzheimer Disease (AD), Dementia with Lewy Bodies (DLB) and Parkinson Disease (PD). New analytical methods for precise quantification of cerebrospinal fluid (CSF) levels of both tau and α-synuclein are required to differentiate between dementias or monitor therapeutic responses. Notably, levels of total α-synuclein reported by ELISA are inconsistent among studies, impacted by antibody specificity or lack of standardization. Here, we report on the development and validation of a sensitive and robust mass spectrometry-based assay for the simultaneous quantification of tau and α-synuclein in CSF. The optimized workflow avoided any affinity reagents, and involved the combination of two enzymes, Glu-C and trypsin for optimal sequence coverage of α-synuclein acidic C-terminus. Up to 7 α-synuclein peptides were quantified, including the C-terminal peptide (132-140), resulting in a sequence coverage of 54% in CSF. The lower limits of quantification (LLOQ) ranged from 0.1 ng mL-1 to 1 ng mL-1 depending on the peptide. Regarding CSF tau, 4 peptides common to all isoforms were monitored, and LLOQ ranged from 0.5 ng mL-1 to 0.75 ng mL-1. The multiplex method was successfully applied to CSF samples from AD and DLB patients, two clinically overlapping neurodegenerative diseases. CSF α-synuclein levels were significantly lower in DLB patients compared to AD and controls. Moreover, tau and α-synuclein concentrations showed opposite trends in AD and DLB patients, suggesting the benefit of combining the two biomarkers for differentiation of DLB from AD and controls.

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.

Targeted versus untargeted omics - the CAFSA story.

BACKGROUND: In 2009, untargeted metabolomics led to the delineation of a new clinico-biological entity called cerebellar ataxia with elevated cerebrospinal free sialic acid, or CAFSA. In order to elucidate CAFSA, we applied sequentially targeted and untargeted omic approaches. METHODS AND RESULTS: First, we studied five of the six CAFSA patients initially described. Besides increased CSF free sialic acid concentrations, three patients presented with markedly decreased 5-methyltetrahydrofolate (5-MTHF) CSF concentrations. Exome sequencing identified a homozygous POLG mutation in two affected sisters, but failed to identify a causative gene in the three sporadic patients with high sialic acid but low 5-MTHF. Using targeted mass spectrometry, we confirmed that free sialic acid was increased in the CSF of a third known POLG-mutated patient. We then pursued pathophysiological analyses of CAFSA using mass spectrometry-based metabolomics on CSF from two sporadic CAFSA patients as well as 95 patients with an unexplained encephalopathy and 39 controls. This led to the identification of a common metabotype between the two initial CAFSA patients and three additional patients, including one patient with Kearns-Sayre syndrome. Metabolites of the CSF metabotype were positioned in a reconstruction of the human metabolic network, which highlighted the proximity of the metabotype with acetyl-CoA and carnitine, two key metabolites regulating mitochondrial energy homeostasis. CONCLUSION: Our genetic and metabolomics analyses suggest that CAFSA is a heterogeneous entity related to mitochondrial DNA alterations either through POLG mutations or a mechanism similar to what is observed in Kearns-Sayre syndrome.

Oxidative-stress detoxification and signalling in cyanobacteria: the crucial glutathione synthesis pathway supports the production of ergothioneine and ophthalmate.

Using genetics and metabolomics we investigated the synthesis (gshA and gshB genes) and catabolism (ggt) of the conserved antioxidant glutathione in the model cyanobacterium Synechocystis PCC6803. These three genes are crucial to Synechocystis, in agreement with the proposed invention of glutathione by ancient cyanobacteria to protect themselves against the toxicity of oxygen they produced through photosynthesis. Consistent with their indispensability, gshA and gshB also operate in the production of another antioxidant, ergothioneine, as well as of the glutathione analogues ophthalmate and norophthalmate. Furthermore, we show that glutathione, ophthalmate and norophthalmate are accumulated in cells stressed by glucose, and that the two glutathione-dependent glyoxalase enzymes operate in the protection against glucose and its catabolite methylglyoxal. These findings are interesting because ophthalmate and norophthalmate were observed only in mammals so far, where ophthalmate is regarded as a biomarker of glutathione depletion. Instead, our data suggest that ophthalmate and norophthalmate are stress-induced markers of cysteine depletion triggered by its accelerated incorporation into glutathione, to face its increased demand for detoxification purposes. Hence, Synechocystis is an attractive model for the analysis of the role of glutathione, ergothioneine, ophthalmate and norophthalmate, in signalling and detoxification of oxidants and metabolic by-products.

Rapid Detection of Abrin Toxin and Its Isoforms in Complex Matrices by Immuno-Extraction and Quantitative High Resolution Targeted Mass Spectrometry.

Abrin expressed by the tropical plant Abrus precatorius is highly dangerous with an estimated human lethal dose of 0.1-1 µg/kg body weight. Due to the potential misuse as a biothreat agent, abrin is in the focus of surveillance. Fast and reliable methods are therefore of great importance for early identification. Here, we have developed an innovative and rapid multiepitope immuno-mass spectrometry workflow which is capable of unambiguously differentiating abrin and its isoforms in complex matrices. Toxin-containing samples were incubated with magnetic beads coated with multiple abrin-specific antibodies, thereby concentrating and extracting all the isoforms. Using an ultrasonic bath for digestion enhancement, on-bead trypsin digestion was optimized to obtain efficient and reproducible peptide recovery in only 30 min. Improvements made to the workflow reduced total analysis time to less than 3 h. A large panel of common and isoform-specific peptides was monitored by multiplex LC-MS/MS through the parallel reaction monitoring mode on a quadrupole-Orbitrap high resolution mass spectrometer. Additionally, absolute quantification was accomplished by isotope dilution with labeled AQUA peptides. The newly established method was demonstrated as being sensitive and reproducible with quantification limits in the low ng/mL range in various food and clinical matrices for the isoforms of abrin and also the closely related, less toxic Abrus precatorius agglutinin. This method allows for the first time the rapid detection, differentiation, and simultaneous quantification of abrin and its isoforms by mass spectrometry.