Analytical error reduction using single point calibration for accurate and precise metabolomic phenotyping

Integration of proteomic and metabolomic analysis reveal distinct metabolic alterations of prostate cancer-associated fibroblasts compared to normal fibroblasts from patient's stroma samples

The prostate gland is a complex and heterogeneous organ composed of epithelium and stroma. Whilst many studies into prostate cancer focus on epithelium, the stroma is known to play a key role in disease with the emergence of a cancer-associated fibroblasts (CAF) phenotype associated upon disease progression. In this work, we studied the metabolic rewiring of stromal fibroblasts following differentiation to a cancer-associated, myofibroblast-like, phenotype. We determined that CAFs were metabolically more active compared to normal fibroblasts. This corresponded with a heightened lipogenic metabolism, as both reservoir species and building block compounds. Interestingly, lipid metabolism affects mitochondria functioning yet the mechanisms of lipid-mediated functions are unclear. Data showing oxidised fatty acids and glutathione system are elevated in CAFs, compared to normal fibroblasts, strengthens the hypothesis that increased metabolic activity is related to mitochondrial activity. This manuscript describes mechanisms responsible for the altered metabolic flux and shows that prostate cancer-derived extracellular vesicles can increase basal respiration in normal fibroblasts, mirroring that of the disease-like phenotype. This indicates that extracellular vesicles derived from prostate cancer cells may drive an altered oxygen-dependent metabolism associated to mitochondria in CAFs.

Higher Plasma Levels of Endocannabinoids and Analogues Correlate With a Worse Cardiometabolic Profile in Young Adults

CONTEXT

The endocannabinoid system (ECS) is a signaling system composed of endocannabinoids (eCBs), their receptors, and the enzymes involved in their synthesis and metabolism. Alterations in the ECS are linked to the development of cardiometabolic diseases.

OBJECTIVE

Here, we investigated the relationship between plasma levels of eCBs and their analogues with body composition and cardiometabolic risk factors.

METHODS

The study included 133 young adults (age 22.1 ± 2.2 years, 67% women). Fasting plasma levels of eCBs and their analogues were measured using liquid chromatography-tandem mass spectrometry. Body composition, brown adipose tissue (BAT) volume, glucose uptake, and traditional cardiometabolic risk factors were measured.

RESULTS

Plasma levels of eCBs and several eCB analogues were positively correlated with adiposity and traditional cardiometabolic risk factors (eg, serum insulin and triacylglyceride levels, all r ≥ 0.17 and P ≤ .045). Plasma levels of 2-arachidonoyl glycerol and N-pentadecenoylethanolamine were negatively correlated with BAT volume and glucose uptake (all r ≤ -0.17 and P ≤ .047). We observed that the plasma levels of eCBs and their analogues were higher in metabolically unhealthy overweight-obese participants than in metabolically healthy overweight-obese participants.

CONCLUSION

Our findings show that the plasma levels of eCBs and their analogues are related to higher levels of adiposity and worse cardiometabolic profile.

From sound check to encore: A journey through high-resolution mass spectrometry-based food analyses and metabolomics

This manuscript presents a comprehensive review of high-resolution mass spectrometry in the field of food analysis and metabolomics. We have followed the historical evolution of metabolomics, its associated techniques and technologies, and its increasing role in food science and research. The review provides a critical comparison and synthesis of tentative identification guidelines proposed for over 15 years, offering a condensed resource for researchers in the field. We have also examined a wide range of recent metabolomics studies, showcasing various methodologies and highlighting key findings as a testimony of the versatility of the field and the possibilities it offers. In doing so, we have also carefully provided a compilation of the software tools that may be employed in this type of studies. The manuscript also explores the prospects of high-resolution mass spectrometry and metabolomics in food science. By covering the history, guidelines, applications, and tools of metabolomics, this review attempts to become a comprehensive guide for researchers in a rapidly evolving field.

Cold-induced changes in plasma signaling lipids are associated with a healthier cardiometabolic profile independently of brown adipose tissue

Cold exposure activates brown adipose tissue (BAT) and potentially improves cardiometabolic health through the secretion of signaling lipids by BAT. Here, we show that 2 h of cold exposure in young adults increases the levels of omega-6 and omega-3 oxylipins, the endocannabinoids (eCBs) anandamide and docosahexaenoylethanolamine, and lysophospholipids containing polyunsaturated fatty acids. Contrarily, it decreases the levels of the eCBs 1-LG and 2-LG and 1-OG and 2-OG, lysophosphatidic acids, and lysophosphatidylethanolamines. Participants overweight or obese show smaller increases in omega-6 and omega-3 oxylipins levels compared to normal weight. We observe that only a small proportion (∼4% on average) of the cold-induced changes in the plasma signaling lipids are slightly correlated with BAT volume. However, cold-induced changes in omega-6 and omega-3 oxylipins are negatively correlated with adiposity, glucose homeostasis, lipid profile, and liver parameters. Lastly, a 24-week exercise-based randomized controlled trial does not modify plasma signaling lipid response to cold exposure.

Insights into serum metabolic biomarkers for early detection of incident diabetic kidney disease in Chinese patients with type 2 diabetes by random forest

Diabetic kidney disease (DKD) is a leading cause of end-stage renal disease (ESRD) worldwide. Early detection is critical for the risk stratification and early intervention of progressive DKD. Serum creatinine (sCr) and urine output are used to assess kidney function, but these markers are limited by their delayed changes following kidney pathology, and lacking of both sensitivity and accuracy. Hence, it is essential to illustrate potential diagnostic indicators to enhance the precise prediction of early DKD. A total of 194 Chinese individuals include 30 healthy participants (Stage 0) and 164 incidents with type 2 diabetes (T2D) spanning from DKD's Stage 1a to 4 were recruited and their serums were subjected for untargeted metabolomic analysis. Random forest (RF), a machine learning approach, together with univariate linear regression (ULR) and multivariate linear regression (MvLR) analysis were applied to characterize the features of untargeted metabolites of DKD patients and to identify candidate DKD biomarkers. Our results indicate that 2-(α-D-mannopyranosyl)-L-tryptophan (ADT), succinyladenosine (SAdo), pseudouridine and N,N,N-trimethyl-L-alanyl-L-proline betaine (L-L-TMAP) were associated with the development of DKD, in particular, the latter three that were significantly elevated in Stage 2-4 T2D incidents. Each of the four metabolites in combination with sCr achieves better performance than sCr alone with area under the receiver operating characteristic curve (AUC) of 0.81-0.91 in predicting DKD stages. An average of 3.9 years follow-up study of another cohort including 106 Stage 2-3 patients suggested that "urinary albumin-to-creatinine ratio (UACR) + ADT + SAdo" can be utilized for better prognosis evaluation of early DKD (average AUC = 0.9502) than UACR without sexual difference.

Lipidomics and biodistribution of extracellular vesicles-secreted by hepatocytes from Zucker lean and fatty rats

Extracellular vesicles (EVs) have been involved in metabolic syndrome, although their specific role in the development of the pathology is still unknown. To further study the role of EVs, we have analysed by Raman tweezers microspectroscopy and mass spectrometry-based lipidomics the small EVs population secreted by fatty (ZF) and lean (ZL) hepatocytes obtained from Zucker rats. We have also explored in vivo and ex vivo biodistribution of these EVs through fluorine-18-radiolabelling using a positron emission tomography imaging. Based on the proportion of proteins to lipids and the types of lipids, our results indicate that within the range of small EVs, primary hepatocytes secrete different subpopulations of particles. These differences were observed in the enrichment of triglyceride species in EVs secreted by ZF hepatocytes. Biodistribution experiments showed accumulation in the brain, heart, lungs, kidney and specially in bladder after intravenous administration. In summary, we show that EVs released by a fatty hepatocytes carry a different lipid signature compared to their lean counterpart. Biodistribution experiment has shown no difference in the distribution of EVs secreted by ZF and ZL hepatocytes but has given us a first view of possible target organs for these particles. Our results might open a door to both pathology studies and therapeutic interventions.

Non-targeted analysis of lipidic extracts by high-resolution mass spectrometry to characterise the chemical exposome: Comparison of four clean-up strategies applied to egg

Biota samples are used to monitor chemical stressors and their impact on the ecosystem and to describe dietary chemical exposure. These complex matrices require an extraction step followed by clean-up to avoid damaging sensitive analytical instruments based on chromatography coupled to mass spectrometry. While interest for non-targeted analysis (NTA) is increasing, there is no versatile or generic sample preparation for a wide range of contaminants suitable for a diversity of biotic matrices. Among the contaminants' variety, persistent contaminants are mostly hydrophobic (mid- to non-polar) and bio-magnify through the lipidic fraction. During their extraction, lipids are generally co-extracted, which may cause matrix effect during the analysis such as hindering the acquired signal. The aim of this study was to evaluate the efficacy of four clean-up methods to selectively remove lipids from extracts prior to NTA. We evaluated (i) gel permeation chromatography (GPC), (ii) Captiva EMR-lipid cartridge (EMR), (iii) sulphuric acid degradation (H2SO4) and (iv) polydimethyl siloxane (PDMS) for their efficiency to remove lipids from hen egg extracts. Gas and liquid chromatography coupled with high-resolution mass spectrometry fitted with either electron ionisation or electrospray ionisation sources operating in positive and negative modes were used to determine the performances of the clean-up methods. A set of 102 chemicals with a wide range of physico-chemical properties that covers the chemical space of mid- to non-polar contaminants, was used to assess and compare recoveries and matrix effects. Matrix effects, that could hinder the mass spectrometer signal, were lower for extracts cleaned-up with H2SO4 than for the ones cleaned-up with PDMS, EMR and GPC. The recoveries were satisfactory for both GPC and EMR while those determined for PDMS and H2SO4 were low due to poor partitioning and degradation/dissociation of the compounds, respectively. The choice of the clean-up methods, among those assessed, should be a compromise that takes into account the matrix under consideration, the levels and the physico-chemical properties of the contaminants.

Monophasic Variant of Salmonella Typhimurium Infection Affects the Serum Metabolome in Swine

Salmonella is the most relevant foodborne zoonotic agent found in swine, and its presence in French herds is significant. Its carriage is asymptomatic, which makes it difficult to detect during rearing, thus increasing the risk of its presence on pork meat. Studies have shown that enteric infection in animals could be associated with changes in the serum metabolome composition, through the immune response or changes in the digestive microbiota composition. We hypothesized that these changes in the serum metabolome composition could be used as markers for the detection of asymptomatic animals infected by Salmonella. Using untargeted analysis by liquid chromatography coupled with mass spectrometry, we showed that significant differences in the composition of the serum metabolome could be detected between infected or noninfected animals both 1 and 21 days after experimental infection. This serum metabolome composition significantly changed during the 21 days postinfection in the infected animal groups, suggesting an evolution of the impact of infection with time. Despite this evolution, differences in the serum metabolome composition persisted between infected and noninfected animals 21 days after the initial infection. We also showed a possible difference between high-shedding and low-shedding animals 21 days postinfection. Finally, some of the variations in the metabolome were found to be significantly associated with variations of specific members of the fecal microbiota. Thus, excreting and asymptomatic animals, but also high-shedding animals, could be identified on the basis of their serum metabolome composition.

Metabolomic signature and molecular profile of normal and degenerated human intervertebral disc cells

BACKGROUND CONTEXT

Intervertebral disc degeneration (IVDD) is an incurable, specific treatment-orphan disease with an increasing burden worldwide. Although great efforts have been made to develop new regenerative therapies, their clinical success is limited.

PURPOSE

Characterize the metabolomic and gene expression changes underpinning human disc degeneration. This study also aimed to disclose new molecular targets for developing and optimizing novel biological approaches for IVDD.

STUDY DESIGN

Intervertebral disc cells were obtained from IVDD patients undergoing circumferential arthrodesis surgery or from healthy subjects. Mimicking the harmful microenvironment of degenerated discs, cells isolated from the nucleus pulposus (NP) and annulus fibrosus (AF) were exposed to the proinflammatory cytokine IL-1β and the adipokine leptin. The metabolomic signature and molecular profile of human disc cells were unraveled for the first time.

METHODS

The metabolomic and lipidomic profiles of IVDD and healthy disc cells were analyzed by high-performance liquid chromatography-mass spectrometry (UHPLC-MS). Gene expression was investigated by SYBR green-based quantitative real-time RT-PCR. Altered metabolites and gene expression were documented.

RESULTS

Lipidomic analysis revealed decreased levels of triacylglycerols (TG), diacylglycerol (DG), fatty acids (FA), phosphatidylcholine (PC), lysophosphatidylinositols (LPI) and sphingomyelin (SM), and increased levels of bile acids (BA) and ceramides, likely promoting disc cell metabolism changing from glycolysis to fatty acid oxidation and following cell death. The gene expression profile of disc cells suggests LCN2 and LEAP2/GHRL as promising molecular therapeutic targets for disc degeneration and demonstrates the expression of genes related to inflammation (NOS2, COX2, IL-6, IL-8, IL-1β, and TNF-α) or encoding adipokines (PGRN, NAMPT, NUCB2, SERPINE2, and RARRES2), matrix metalloproteinases (MMP9 and MMP13), and vascular adhesion molecules (VCAM1).

CONCLUSIONS

Altogether, the presented results disclose the NP and AF cell biology changes from healthy to degenerated discs, allowing the identification of promising molecular therapeutic targets for intervertebral disc degeneration.

CLINICAL SIGNIFICANCE

Our results are relevant to improving current biological-based strategies aiming to repair IVD by restoring cellular lipid metabolites as well as adipokines homeostasis. Ultimately, our results will be valuable for successful, long-lasting relief of painful IVDD.

Pipecolate and Taurine are Rat Urinary Biomarkers for Lysine and Threonine Deficiencies

BACKGROUND

The consumption of poor-quality protein increases the risk of essential amino acid (EAA) deficiency, particularly for lysine and threonine. Thus, it is necessary to be able to detect easily EAA deficiency.

OBJECTIVES

The purpose of this study was to develop metabolomic approaches to identify specific biomarkers for an EAA deficiency, such as lysine and threonine.

METHODS

Three experiments were performed on growing rats. In experiment 1, rats were fed for 3 weeks with lysine (L30), or threonine (T53)-deficient gluten diets, or nondeficient gluten diet (LT100) in comparison with the control diet (milk protein, PLT). In experiments 2a and 2b, rats were fed at different concentrations of lysine (L) or threonine (T) deficiency: L/T15, L/T25, L/T40, L/T60, L/T75, P20, L/T100 and L/T170. Twenty-four-hour urine and blood samples from portal vein and vena cava were analyzed using LC-MS. Data from experiment 1 were analyzed by untargeted metabolomic and Independent Component - Discriminant Analysis (ICDA) and data from experiments 2a and 2b by targeted metabolomic and a quantitative Partial Least- Squares (PLS) regression model. Each metabolite identified as significant by PLS or ICDA was then tested by 1-way ANOVA to evaluate the diet effect. A two-phase linear regression analysis was used to determine lysine and threonine requirements.

RESULTS

ICDA and PLS found molecules that discriminated between the different diets. A common metabolite, the pipecolate, was identified in experiments 1 and 2a, confirming that it could be specific to lysine deficiency. Another metabolite, taurine, was found in experiments 1 and 2b, so probably specific to threonine deficiency. Pipecolate or taurine breakpoints obtained give a value closed to the values obtained by growth indicators.

CONCLUSIONS

Our results showed that the EAA deficiencies influenced the metabolome. Specific urinary biomarkers identified could be easily applied to detect EAA deficiency and to determine which AA is deficient.

Untargeted Multiomics Approach Coupling Lipidomics and Metabolomics Profiling Reveals New Insights in Diabetic Retinopathy

Diabetic retinopathy (DR) is a microvascular complication of diabetes mellitus (DM) which is the main cause of vision loss in the working-age population. Currently known risk factors such as age, disease duration, and hemoglobin A1c lack sufficient efficiency to distinguish patients with early stages of DR. A total of 194 plasma samples were collected from patients with type 2 DM and DR (moderate to proliferative (PDR) or control (no or mild DR) matched for age, gender, diabetes duration, HbA1c, and hypertension. Untargeted lipidomic and metabolomic approaches were performed. Partial-least square methods were used to analyze the datasets. Levels of 69 metabolites and 85 lipid species were found to be significantly different in the plasma of DR patients versus controls. Metabolite set enrichment analysis indicated that pathways such as metabolism of branched-chain amino acids (methylglutaryl carnitine p = 0.004), the kynurenine pathway (tryptophan p < 0.001), and microbiota metabolism (p-Cresol sulfate p = 0.004) were among the most enriched deregulated pathways in the DR group. Moreover, Glucose-6-phosphate (p = 0.001) and N-methyl-glutamate (p < 0.001) were upregulated in DR. Subgroup analyses identified a specific signature associated with PDR, macular oedema, and DR associated with chronic kidney disease. Phosphatidylcholines (PCs) were dysregulated, with an increase of alkyl-PCs (PC O-42:5 p < 0.001) in DR, while non-ether PCs (PC 14:0-16:1, p < 0.001; PC 18:2-14:0, p < 0.001) were decreased in the DR group. Through an unbiased multiomics approach, we identified metabolites and lipid species that interestingly discriminate patients with or without DR. These features could be a research basis to identify new potential plasma biomarkers to promote 3P medicine.

Metabolomics-Based Investigation on the Metabolic Changes in Crassostrea gigas Experimentally Exposed to Galvanic Anodes

Cathodic protection is widely used to protect metal structures from corrosion in marine environments using sacrificial galvanic anodes. These anodes, either in Zinc, or preferentially nowadays in Al-Zn-In alloys, are expected to corrode instead of the metal structures. This leads to the release of dissolved species, Zn²⁺, Al³⁺, and In³⁺, and solid phases such as Al(OH)₃. Few studies have been conducted on their effects on marine organisms, and they concluded that further investigations are needed. We therefore evaluated the effects of Zn and Al-Zn-In anodes on oysters stabulated in tanks, under controlled conditions defined through a comparison with those prevailing in a given commercial seaport used as reference. We analyzed the entire metabolome of gills with a non-targeted metabolomic approach HRMS. A modelling study of the chemical species, corresponding to the degradation products of the anodes, likely to be present near the exposed oysters, was also included. We identified 16 and two metabolites modulated by Zn- and Al-Zn-In-anodes, respectively, that were involved in energy metabolism, osmoregulation, oxidative stress, lipid, nucleotide nucleoside and amino acid metabolisms, defense and signaling pathways. The combination of chemical modelling and metabolomic approach, used here for the first time, enlightened the influence of Zn present in the Al-Zn-In anodes.

Quantitative Analytical and Computational Workflow for Large-Scale Targeted Plasma Metabolomics

Quantifying metabolites from various biological samples is necessary for the clinical and biomedical translation of metabolomics research. One of the ongoing challenges in biomedical metabolomics studies is the large-scale quantification of targeted metabolites, mainly due to the complexity of biological sample matrices. Furthermore, in LC-MS analysis, the response of compounds is influenced by their physicochemical properties, chromatographic conditions, eluent composition, sample preparation, type of MS ionization source, and analyzer used. To facilitate large-scale metabolite quantification, we evaluated the relative response factor (RRF) approach combined with an integrated analytical and computational workflow. This approach considers a compound's individual response in LC-MS analysis relative to that of a non-endogenous reference compound to correct matrix effects. We created a quantitative LC-MS library using the Skyline/Panorama web platform for data processing and public sharing of data. In this study, we developed and validated a metabolomics method for over 280 standard metabolites and quantified over 90 metabolites. The RRF quantification was validated and compared with conventional external calibration approaches as well as literature reports. The Skyline software environment was adapted for processing such metabolomics data, and the results are shared as a "quantitative chromatogram library" with the Panorama web application. This new workflow was found to be suitable for large-scale quantification of metabolites in human plasma samples. In conclusion, we report a novel quantitative chromatogram library with a targeted data analysis workflow for biomedical metabolomic applications.

Mass spectrometry-based metabolomic analysis as a tool for quality control of natural complex products

Metabolomics is an area of intriguing and growing interest. Since the late 1990s, when the first Omic applications appeared to study metabolite's pool ("metabolome"), to understand new aspects of the global regulation of cellular metabolism in biology, there have been many evolutions. Currently, there are many applications in different fields such as clinical, medical, agricultural, and food. In our opinion, it is clear that developments in metabolomics analysis have also been driven by advances in mass spectrometry (MS) technology. As natural complex products (NCPs) are increasingly used around the world as medicines, food supplements, and substance-based medical devices, their analysis using metabolomic approaches will help to bring more and more rigor to scientific studies and industrial production monitoring. This review is intended to emphasize the importance of metabolomics as a powerful tool for studying NCPs, by which significant advantages can be obtained in terms of elucidation of their composition, biological effects, and quality control. The different approaches of metabolomic analysis, the main and basic techniques of multivariate statistical analysis are also briefly illustrated, to allow an overview of the workflow associated with the metabolomic studies of NCPs. Therefore, various articles and reviews are illustrated and commented as examples of the application of MS-based metabolomics to NCPs.

Antibacterial Activities and Life Cycle Stages of Asparagopsis armata: Implications of the Metabolome and Microbiome

The red alga Asparagopsis armata is a species with a haplodiplophasic life cycle alternating between morphologically distinct stages. The species is known for its various biological activities linked to the production of halogenated compounds, which are described as having several roles for the algae such as the control of epiphytic bacterial communities. Several studies have reported differences in targeted halogenated compounds (using gas chromatography-mass spectrometry analysis (GC-MS)) and antibacterial activities between the tetrasporophyte and the gametophyte stages. To enlarge this picture, we analysed the metabolome (using liquid chromatography-mass spectrometry (LC-MS)), the antibacterial activity and the bacterial communities associated with several stages of the life cycle of A. armata: gametophytes, tetrasporophytes and female gametophytes with developed cystocarps. Our results revealed that the relative abundance of several halogenated molecules including dibromoacetic acid and some more halogenated molecules fluctuated depending on the different stages of the algae. The antibacterial activity of the tetrasporophyte extract was significantly higher than that of the extracts of the other two stages. Several highly halogenated compounds, which discriminate algal stages, were identified as candidate molecules responsible for the observed variation in antibacterial activity. The tetrasporophyte also harboured a significantly higher specific bacterial diversity, which is associated with a different bacterial community composition than the other two stages. This study provides elements that could help in understanding the processes that take place throughout the life cycle of A. armata with different potential energy investments between the development of reproductive elements, the production of halogenated molecules and the dynamics of bacterial communities.

Plasma metabolomic response to high-carbohydrate meals of differing glycaemic load in overweight women

BACKGROUND

Metabolomic dysregulation following a meal in overweight individuals with the Metabolic Syndrome (MetS) involves multiple pathways of nutrient storage and oxidation.

OBJECTIVE

The aim of the current study was to perform an acute cross-over intervention to examine the interactive actions of meal glycaemic load (GL) on the dynamic responses of the plasma metabolome in overweight females.

METHODS

Postmenopausal women [63 ± 1.23y; Healthy (n = 20) and MetS (n = 20)] ingested two differing high-carbohydrate test meals (73 g carbohydrate; 51% energy) composed of either low glycemic index (LGI) or high (HGI) foods in a randomised sequence. Plasma metabolome was analysed using liquid chromatography-mass spectrometry (LC-MS).

RESULTS

In the overweight women with MetS, there were suppressed postprandial responses for several amino acids (AAs), including phenylalanine, leucine, valine, and tryptophan, p < 0.05), irrespective of the meal type. Meal GL exerted a limited impact on the overall metabolomic response, although the postprandial levels of alanine were higher with the low GL meal and uric acid was greater following the high GL meal (p < 0.05).

CONCLUSIONS

MetS participants exhibited reduced differences in the concentrations of a small set of AAs and a limited group of metabolites implicated in energy metabolism following the meals. However, the manipulation of meal GL had minimal impact on the postprandial metabolome. This study suggests that the GL of a meal is not a major determinant of postprandial response, with a greater impact exerted by the metabolic health of the individual. Trial registration Australia New Zealand Clinical Trials Registry: ACTRN12615001108505 (21/10/2015).

Matrix Effects in GC–MS Profiling of Common Metabolites after Trimethylsilyl Derivatization

Metabolite profiling using gas chromatography coupled to mass spectrometry (GC–MS) is one of the most frequently applied and standardized methods in research projects using metabolomics to analyze complex samples. However, more than 20 years after the introduction of non-targeted approaches using GC–MS, there are still unsolved challenges to accurate quantification in such investigations. One particularly difficult aspect in this respect is the occurrence of sample-dependent matrix effects. In this project, we used model compound mixtures of different compositions to simplify the study of the complex interactions between common constituents of biological samples in more detail and subjected those to a frequently applied derivatization protocol for GC–MS analysis, namely trimethylsilylation. We found matrix effects as signal suppression and enhancement of carbohydrates and organic acids not to exceed a factor of ~2, while amino acids can be more affected. Our results suggest that the main reason for our observations may be an incomplete transfer of carbohydrate and organic acid derivatives during the injection process and compound interaction at the start of the separation process. The observed effects were reduced at higher target compound concentrations and by using a more suitable injection-liner geometry.

Normalization Approach by a Reference Material to Improve LC-MS-Based Metabolomic Data Comparability of Multibatch Samples

Large cohorts of samples from multiple batches are usually required for global metabolomic studies to characterize the metabolic state of human disease. As such, it is critical to eliminate systematic variation and truly reveal the biologically associated alterations. In this study, we proposed a reference material-based approach (Ref-M) for data correction by liquid chromatography-mass spectrometry and represented by an analysis of multibatch human serum samples. The reference material was generated by mixing serum from healthy donors and distributed to each extraction batch of subject samples. Pooled quality control samples and isotopic internal standards were then applied in each acquisition batch for data quality control. Finally, each metabolite in subject samples was normalized by its counterpart in the reference serum. We demonstrated that Ref-M significantly enhanced the numbers of efficient features and effectively eliminated the batch variation of 522 serum samples of healthy individuals, benign pulmonary nodules, and lung cancer patients. Twenty differential metabolites were identified to distinguish lung cancer from healthy controls in the training set. The discriminant model was validated in an independent data set with an area under the receiver operating characteristics (ROC) curve (AUC) of 0.853. Another 40 serum samples further tested with Ref-M were achieved an AUC of 0.843 by the established model. Our results showed that the reference material-based approach presents the potential to improve the data comparability and precision for biomarker discovery in large-scale metabolomic studies.

ISG15 Is a Novel Regulator of Lipid Metabolism during Vaccinia Virus Infection

Interferon-stimulated gene 15 (ISG15) is a 15-kDa ubiquitin-like modifier that binds to target proteins in a process termed ISGylation. ISG15, first described as an antiviral molecule against many viruses, participates in numerous cellular processes, from immune modulation to the regulation of genome stability. Interestingly, the role of ISG15 as a regulator of cell metabolism has recently gained strength. We previously described ISG15 as a regulator of mitochondrial functions in bone marrow-derived macrophages (BMDMs) in the context of Vaccinia virus (VACV) infection. Here, we demonstrate that ISG15 regulates lipid metabolism in BMDMs and that ISG15 is necessary to modulate the impact of VACV infection on lipid metabolism. We show that Isg15-/- BMDMs demonstrate alterations in the levels of several key proteins of lipid metabolism that result in differences in the lipid profile compared with Isg15+/+ (wild-type [WT]) BMDMs. Specifically, Isg15-/- BMDMs present reduced levels of neutral lipids, reflected by decreased lipid droplet number. These alterations are linked to increased levels of lipases and are independent of enhanced fatty acid oxidation (FAO). Moreover, we demonstrate that VACV causes a dysregulation in the proteomes of BMDMs and alterations in the lipid content of these cells, which appear exacerbated in Isg15-/- BMDMs. Such metabolic changes are likely caused by increased expression of the metabolic regulators peroxisome proliferator-activated receptor-γ (PPARγ) and PPARγ coactivator-1α (PGC-1α). In summary, our results highlight that ISG15 controls BMDM lipid metabolism during viral infections, suggesting that ISG15 is an important host factor to restrain VACV impact on cell metabolism. IMPORTANCE The functions of ISG15 are continuously expanding, and growing evidence supports its role as a relevant modulator of cell metabolism. In this work, we highlight how the absence of ISG15 impacts macrophage lipid metabolism in the context of viral infections and how poxviruses modulate metabolism to ensure successful replication. Our results open the door to new advances in the comprehension of macrophage immunometabolism and the interaction between VACV and the host.

Cerebrospinal Fluid and Plasma Amine Profiles in Interictal Migraine

OBJECTIVE

Impaired amine metabolism has been associated with the etiology of migraine, that is, why patients continue to get migraine attacks. However, evidence from cerebrospinal fluid (CSF) is lacking. Here, we evaluated individual amine levels, global amine profiles, and amine pathways in CSF and plasma of interictal migraine patients and healthy controls.

METHODS

CSF and plasma were sampled between 8:30 am and 1:00 pm, randomly and interchangeably over the time span to avoid any diurnal and seasonal influences, from healthy volunteers and interictal migraine patients, matched for age, sex, and sampling time. The study was approved by the local medical ethics committee. Individual amines (n = 31), global amine profiles, and specific amine pathways were analyzed using a validated ultraperformance liquid chromatography mass spectrometry platform.

RESULTS

We analyzed n = 99 participants with migraine with aura, n = 98 with migraine without aura, and n = 96 healthy volunteers. Univariate analysis with Bonferroni correction indicated that CSF L-arginine was reduced in migraine with aura (10.4%, p < 0.001) and without aura (5.0%, p = 0.03). False discovery rate-corrected CSF L-phenylalanine was also lower in migraine with aura (6.9%, p = 0.011) and without aura (8.1%, p = 0.001), p = 0.088 after Bonferroni correction. Multivariate analysis revealed that CSF global amine profiles were similar for both types of migraine (p = 0.64), but distinct from controls (p = 0.009). Global profile analyses were similar in plasma. The strongest associated pathways with migraine were related to L-arginine metabolism.

INTERPRETATION

L-Arginine was decreased in the CSF (but not in plasma) of interictal patients with migraine with or without aura, and associated pathways were altered. This suggests that dysfunction of nitric oxide signaling is involved in susceptibility to getting migraine attacks. ANN NEUROL 2023.

Plasma Levels of Omega-3 and Omega-6 Derived Oxylipins Are Associated with Fecal Microbiota Composition in Young Adults

Pre-clinical studies suggest that circulating oxylipins, i.e., the oxidation products of polyunsaturated fatty acids (PUFAs), modulate gut microbiota composition in mice, but there is no information available in humans. Therefore, this study aimed to investigate the relationship between omega-3 and omega-6 derived oxylipins plasma levels and fecal microbiota composition in a cohort of young adults. 80 young adults (74% women; 21.9 ± 2.2 years old) were included in this cross-sectional study. Plasma levels of oxylipins were measured using liquid chromatography-tandem mass spectrometry. Fecal microbiota composition was analyzed by V3-V4 16S rRNA gene sequencing. We observed that plasma levels of omega-3 derived oxylipins were positively associated with the relative abundance of Clostridium cluster IV genus (Firmicutes phylum; rho ≥ 0.415, p ≤ 0.009) and negatively associated with the relative abundance of Sutterella genus (Proteobacteria phylum; rho ≥ -0.270, p ≤ 0.041), respectively. Moreover, plasma levels of omega-6 derived oxylipins were negatively associated with the relative abundance of Acidaminococcus and Phascolarctobacterium genera (Firmicutes phylum; all rho ≥ -0.263, p ≤ 0.024), as well as Sutterella, Succinivibrio, and Gemmiger genera (Proteobacteria phylum; all rho ≥ -0.263, p ≤ 0.024). Lastly, the ratio between omega-6 and omega-3 oxylipins plasma levels was negatively associated with the relative abundance of Clostridium cluster IV genus (Firmicutes phylum; rho = -0.334, p = 0.004) and Butyricimonas genus (Bacteroidetes phylum; rho = -0.292, p = 0.014). In conclusion, our results show that the plasma levels of omega-3 and omega-6 derived oxylipins are associated with the relative abundance of specific fecal bacteria genera.

Proteomic Signatures of the Serological Response to Influenza Vaccination in a Large Human Cohort Study

The serological response to the influenza virus vaccine is highly heterogeneous for reasons that are not entirely clear. While the impact of demographic factors such as age, body mass index (BMI), sex, prior vaccination and titer levels are known to impact seroconversion, they only explain a fraction of the response. To identify signatures of the vaccine response, we analyzed 273 protein levels from 138 serum samples of influenza vaccine recipients (2019-2020 season). We found that levels of proteins functioning in cholesterol transport were positively associated with seroconversion, likely linking to the known impact of BMI. When adjusting seroconversion for the demographic factors, we identified additional, unexpected signatures: proteins regulating actin cytoskeleton dynamics were significantly elevated in participants with high adjusted seroconversion. Viral strain specific analysis showed that this trend was largely driven by the H3N2 strain. Further, we identified complex associations between adjusted seroconversion and other factors: levels of proteins of the complement system associated positively with adjusted seroconversion in younger participants, while they were associated negatively in the older population. We observed the opposite trends for proteins of high density lipoprotein remodeling, transcription, and hemostasis. In sum, careful integrative modeling can extract new signatures of seroconversion from highly variable data that suggest links between the humoral response as well as immune cell communication and migration.

Linoleic acid-derived oxylipins and isoprostanes plasma levels are influenced by 1,25-Dihydroxyvitamin D levels in middle-aged sedentary adults: The FIT-AGEING study

INTRODUCTION

Vitamin D - concretely its active form 1,25-dihydroxyvitamin D (1,25(OH)₂D) - maintains several physiological processes. Oxylipins are oxidized lipids derived from ω-6 and ω-3 polyunsaturated fatty acids involved in inflammation. Little is known about the association of 1,25(OH)₂D with inflammatory parameters in middle-aged populations - who could be at risk of vitamin D deficiency -. The aim of this study was to investigate the relationship between 1,25(OH)₂D plasma levels with circulating white blood cells, platelets counts and oxylipins levels.

MATERIALS AND METHODS

A total of 74 (53 % women) middle-aged (40-65 years old) adults were recruited for this cross-sectional study. 1,25(OH)₂D plasma levels were measured using an immunochemiluminometric assay. White blood cells and platelets were analyzed by hemocytometry. ω-6 and ω-3 oxylipins plasma levels were measured using liquid chromatography - tandem mass spectrometry. Simple and multiple linear regression models, and Pearson correlation analyses, were performed to study the association of 1,25(OH)₂D levels with WBC and platelets counts, and oxylipins, respectively.

RESULTS

1,25(OH)₂D plasma levels were positively related with linoleic acid-derived oxylipins and isoprostanes plasma levels, whereas an inverse relationship with dihomo-γ-linolenic acid/linoleic acid and arachidonic acid/linoleic acid ratios was unveiled. No significant associations were observed for circulating ω-3 oxylipins, white blood cells levels or platelets count.

CONCLUSIONS

Linoleic acid-derived oxylipins and isoprostanes plasma levels may be influenced by 1,25(OH)₂D plasma levels. Further investigations are needed to elucidate the impact of other vitamin D forms upon circulating oxylipins levels.

The Plasma Oxylipin Signature Provides a Deep Phenotyping of Metabolic Syndrome Complementary to the Clinical Criteria

Metabolic syndrome (MetS) is a complex condition encompassing a constellation of cardiometabolic abnormalities. Oxylipins are a superfamily of lipid mediators regulating many cardiometabolic functions. Plasma oxylipin signature could provide a new clinical tool to enhance the phenotyping of MetS pathophysiology. A high-throughput validated mass spectrometry method, allowing for the quantitative profiling of over 130 oxylipins, was applied to identify and validate the oxylipin signature of MetS in two independent nested case/control studies involving 476 participants. We identified an oxylipin signature of MetS (coined OxyScore), including 23 oxylipins and having high performances in classification and replicability (cross-validated AUC_ROC of 89%, 95% CI: 85–93% and 78%, 95% CI: 72–85% in the Discovery and Replication studies, respectively). Correlation analysis and comparison with a classification model incorporating the MetS criteria showed that the oxylipin signature brings consistent and complementary information to the clinical criteria. Being linked with the regulation of various biological processes, the candidate oxylipins provide an integrative phenotyping of MetS regarding the activation and/or negative feedback regulation of crucial molecular pathways. This may help identify patients at higher risk of cardiometabolic diseases. The oxylipin signature of patients with metabolic syndrome enhances MetS phenotyping and may ultimately help to better stratify the risk of cardiometabolic diseases.

Impact of in Situ Simulated Climate Change on Communities and Non-Indigenous Species: Two Climates, Two Responses

Climate change constitutes a major challenge for marine urban ecosystems and ocean warming will likely strongly affect local communities. Non-Indigenous Species (NIS) have been shown to often have higher heat resistance than natives, but studies investigating how forthcoming global warming might affect them in marine urban environments remain scarce, especially in Situ studies. Here we used an in Situ warming experiment in a NW Mediterranean (warm temperate) and a NE Atlantic (cold temperate) marina to see how global warming might affect recruited communities in the near future. In both marinas, warming resulted in significantly different community structure, lower biomass, and more empty space compared to control. However, while in the warm temperate marina, NIS showed an increased surface cover, it was reduced in the cold temperate one. Metabolomic analyses on Bugula neritina in the Atlantic marina revealed potential heat stress experienced by this introduced bryozoan and a potential link between heat stress and the expression of a halogenated alkaloid, Caelestine A. The present results might indicate that the effects of global warming on the prevalence of NIS may differ between geographical provinces, which could be investigated by larger scale studies.

Expanding the Coverage of Metabolic Landscape in Cultivated Rice with Integrated Computational Approaches

Genome-scale metabolomics analysis is increasingly used for pathway and function discovery in the post-genomics era. The great potential offered by developed mass spectrometry (MS)-based technologies has been hindered, since only a small portion of detected metabolites were identifiable so far. To address the critical issue of low identification coverage in metabolomics, we adopted a deep metabolomics analysis strategy by integrating advanced algorithms and expanded reference databases. The experimental reference spectra and in silico reference spectra were adopted to facilitate the structural annotation. To further characterize the structure of metabolites, two approaches were incorporated into our strategy, i.e., structural motif search combined with neutral loss scanning and metabolite association network. Untargeted metabolomics analysis was performed on 150 rice cultivars using ultra-performance liquid chromatography coupled with quadrupole-Orbitrap MS. Consequently, a total of 1939 out of 4491 metabolite features in the MS/MS spectral tag (MS2T) library were annotated, representing an extension of annotation coverage by an order of magnitude in rice. The differential accumulation patterns of flavonoids between indica and japonica cultivars were revealed, especially O-sulfated flavonoids. A series of closely-related flavonolignans were characterized, adding further evidence for the crucial role of tricin-oligolignols in lignification. Our study provides an important protocol for exploring phytochemical diversity in other plant species.

Unraveling membrane properties at the organelle-level with LipidDyn

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Lipidomics of organelles could be used to design models for molecular simulations.

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The bottleneck is the analysis and rationalization of the data from simulations.

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LipidDyn is an automated pipeline to streamline the analyses of lipid bilayers.

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LipidDyn allows to collect analysis in a non-time-consuming and reproducible manner.

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We applied LipidDyn to different case studies to illustrate its potential.

Cellular membranes are formed from different lipids in various amounts and proportions depending on the subcellular localization. The lipid composition of membranes is sensitive to changes in the cellular environment, and its alterations are linked to several diseases. Lipids not only form lipid-lipid interactions but also interact with other biomolecules, including proteins.

Molecular dynamics (MD) simulations are a powerful tool to study the properties of cellular membranes and membrane-protein interactions on different timescales and resolutions. Over the last few years, software and hardware for biomolecular simulations have been optimized to routinely run long simulations of large and complex biological systems. On the other hand, high-throughput techniques based on lipidomics provide accurate estimates of the composition of cellular membranes at the level of subcellular compartments. Lipidomic data can be analyzed to design biologically relevant models of membranes for MD simulations. Similar applications easily result in a massive amount of simulation data where the bottleneck becomes the analysis of the data. In this context, we developed LipidDyn, a Python-based pipeline to streamline the analyses of MD simulations of membranes of different compositions. Once the simulations are collected, LipidDyn provides average properties and time series for several membrane properties such as area per lipid, thickness, order parameters, diffusion motions, lipid density, and lipid enrichment/depletion. The calculations exploit parallelization, and the pipeline includes graphical outputs in a publication-ready form. We applied LipidDyn to different case studies to illustrate its potential, including membranes from cellular compartments and transmembrane protein domains. LipidDyn is available free of charge under the GNU General Public License from https://github.com/ELELAB/LipidDyn.

Dissecting the relationship between plasma and tissue metabolome in a cohort of women with obesity: Analysis of subcutaneous and visceral adipose, muscle, and liver

Untargeted metabolomics of blood samples has become widely applied to study metabolic alterations underpinning disease and to identify biomarkers. However, understanding the relevance of a blood metabolite marker can be challenging if it is unknown whether it reflects the concentration in relevant tissues. To explore this field, metabolomic and lipidomic profiles of plasma, four sites of adipose tissues (ATs) from peripheral or central depot, two sites of muscle tissue, and liver tissue from a group of nondiabetic women with obesity who were scheduled to undergo bariatric surgery (n = 21) or other upper GI surgery (n = 5), were measured by liquid chromatography coupled with mass spectrometry. Relationships between plasma and tissue profiles were examined using Pearson correlation analysis subject to Benjamini-Hochberg correction. Plasma metabolites and lipids showed the highest number of significantly positive correlations with their corresponding concentrations in liver tissue, including lipid species of ceramide, mono- and di-hexosylceramide, sphingomyelin, phosphatidylcholine (PC), phosphatidylethanolamine (PE), lysophosphatidylethanolamine, dimethyl phosphatidylethanolamine, ether-linked PC, ether-linked PE, free fatty acid, cholesteryl ester, diacylglycerol and triacylglycerol, and polar metabolites linked to several metabolic functions and gut microbial metabolism. Plasma also showed significantly positive correlations with muscle for several phospholipid species and polar metabolites linked to metabolic functions and gut microbial metabolism, and with AT for several triacylglycerol species. In conclusion, plasma metabolomic and lipidomic profiles were reflective more of the liver profile than any of the muscle or AT sites examined in the present study. Our findings highlighted the importance of taking into consideration the metabolomic relationship of various tissues with plasma when postulating plasma metabolites marker to underlying mechanisms occurring in a specific tissue.

Plasma Levels of Endocannabinoids and Their Analogues Are Related to Specific Fecal Bacterial Genera in Young Adults: Role in Gut Barrier Integrity

OBJECTIVE

To investigate the association of plasma levels of endocannabinoids with fecal microbiota.

METHODS

Plasma levels of endocannabinoids, anandamide (AEA) and 2-arachidonoylglycerol (2-AG), as well as their eleven analogues, and arachidonic acid (AA), were measured using liquid chromatography-tandem mass spectrometry in 92 young adults. DNA extracted from stool samples was analyzed using 16S rRNA gene sequencing. Lipopolysaccharide levels were measured in plasma samples.

RESULTS

Plasma levels of endocannabinoids and their analogues were not related to beta or alpha diversity indexes. Plasma levels of AEA and related N-acylethanolamines correlated positively with the relative abundance of Faecalibacterium genus (all rho ≥ 0.26, p ≤ 0.012) and Akkermansia genus (all rho ≥ 0.22, p ≤ 0.036), and negatively with the relative abundance of Bilophila genus (all rho ≤ -0.23, p ≤ 0.031). Moreover, plasma levels of 2-AG and other acylglycerols correlated positively with the relative abundance of Parasutterella (all rho ≥ 0.24, p ≤ 0.020) and Odoribacter genera (all rho ≥ 0.27, p ≤ 0.011), and negatively with the relative abundance of Prevotella genus (all rho ≤ -0.24, p ≤ 0.023). In participants with high lipopolysaccharide values, the plasma levels of AEA and related N-acylethanolamines, as well as AA and 2-AG, were negatively correlated with plasma levels of lipopolysaccharide (all rho ≤ -0.24, p ≤ 0.020).

CONCLUSION

Plasma levels of endocannabinoids and their analogues are correlated to specific fecal bacterial genera involved in maintaining gut barrier integrity in young adults. This suggests that plasma levels of endocannabinoids and their analogues may play a role in the gut barrier integrity in young adults.

Norm ISWSVR: A Data Integration and Normalization Approach for Large-Scale Metabolomics

Large-scale and long-period metabolomics study is more susceptible to various sources of systematic errors, resulting in nonreproducibility and poor data quality. A reliable and robust batch correction method removes unwanted systematic variations and improves the statistical power of metabolomics data, which undeniably becomes an important issue for the quality control of metabolomics. This study proposed a novel data normalization and integration method, Norm ISWSVR. It is a two-step approach via combining the best-performance internal standard correction with support vector regression normalization, comprehensively removing the systematic and random errors and matrix effects. This method was investigated in three untargeted lipidomics or metabolomics datasets, and the performance was further evaluated systematically in comparison with that of 11 other normalization methods. As a result, Norm ISWSVR decreased the data's median cross-validated relative standard deviation (cvRSD), increased the correlation between QCs, improved the classification accuracy of biomarkers, and was well-compatible with quantitative data. More importantly, Norm ISWSVR also allows a low frequency of QCs, which could significantly decrease the burden of a large-scale experiment. Correspondingly, Norm ISWSVR favorably improves the data quality of large-scale metabolomics data.

Amplified Drought and Seasonal Cycle Modulate Quercus pubescens Leaf Metabolome

The intensification of summer drought expected with climate change can induce metabolism modifications in plants to face such constraints. In this experiment, we used both a targeted approach focused on flavonoids, as well as an untargeted approach, to study a broader fraction of the leaf metabolome of Quercus pubescens exposed to amplified drought. A forest site equipped with a rainfall exclusion device allowed reduction of natural rainfall by ~30% over the tree canopy. Leaves of natural drought (ND) and amplified drought (AD) plots were collected over three seasonal cycles (spring, summer, and autumn) in 2013 (the second year of rain exclusion), 2014, and 2015. As expected, Q. pubescens metabolome followed a seasonal course. In the summer of 2015, the leaf metabolome presented a shifted and early autumnal pattern because of harsher conditions during this year. Despite low metabolic modification at the global scale, our results demonstrated that 75% of Quercus metabolites were upregulated in springs when trees were exposed to AD, whereas 60 to 73% of metabolites (93% in summer 2015), such as kaempferols and quercetins, were downregulated in summers/autumns. Juglanin, a kaempferol pentoside, as well as rhododendrin derivatives, were upregulated throughout the year, suggesting an antioxidant ability of these metabolites. Those changes in terms of phenology and leaf chemistry could, in the end, affect the ecosystem functioning.

Effect of Different Exercise Training Modalities on Fasting Levels of Oxylipins and Endocannabinoids in Middle-Aged Sedentary Adults: A Randomized Controlled Trial

This study aimed to investigate the effects of different exercise training programs on fasting plasma levels of oxylipins, endocannabinoids (eCBs), and eCBs-like molecules in middle-aged sedentary adults. A 12-week randomized controlled trial was conducted using a parallel group design. Sixty-five middle-aged adults (40-65 years old) were randomly assigned to: (a) no exercise (control group), (b) concurrent training based on international physical activity recommendations (PAR group), (c) high-intensity interval training (HIIT group), and (d) HIIT together with whole-body electromyostimulation (HIIT + EMS group). Plasma levels of oxylipins, eCBs, and eCBs-like molecules were determined in plasma samples before and after the intervention using targeted lipidomics. Body composition was assessed through dual-energy X-ray absorptiometry, and dietary intake through a food frequency questionnaire and three nonconsecutive 24-hr recalls. The physical activity recommendations, HIIT, and HIIT-EMS groups showed decreased plasma levels of omega-6 and omega-3-derived oxylipins, and eCBs and eCBs-like molecules after 12 weeks (all Δ ≤ -0.12; all p < .05). Importantly, after Bonferroni post hoc corrections, the differences in plasma levels of omega-6 and omega-3 oxylipins were not statistically significant compared with the control group (all p > .05). However, after post hoc corrections, plasma levels of anandamide and oleoylethanolamide were increased in the physical activity recommendations group compared with the control group (anandamide: Δ = 0.05 vs. -0.09; oleoylethanolamide: Δ = -0.12 vs. 0.013, all p ≤ .049). In conclusion, this study reports that a 12-week exercise training intervention, independent of the modality applied, does not modify fasting plasma levels of omega-6 and omega-3 oxylipins, eCBs, and eCBs-like molecules in middle-aged sedentary adults.

Non-targeted metabolomics of saliva to explore potential biomarkers for gastric ulceration in pigs fed hemp

Gastric ulceration is a common disease in pig production worldwide and is associated with economic losses as well as animal health and welfare issues. The aim of this study was to explore potential salivary biomarkers for gastric ulceration in pigs. In addition, the aim was to study the effect of hemp on the incidence of gastric ulcers. Approximately 440 growing-finishing pigs in the period from 30 to 110 kg BW were allocated to four different diets: meal feed (Meal); pelleted feed (Pellets); pelleted feed added 4% hempseed cake (Hemp Cake); pelleted feed added 4% hempseed hulls (Hemp Hulls). The day before slaughter, saliva samples from each pig were collected. After slaughter, the stomachs were emptied to assess the consistency of the stomach content and examined for gastric ulceration using an index scale (0-10). Noticeable changes of the gastric mucosa (total index score ≥ 6) were observed in 291 pigs. The odds of having index scores 0-5 relative to index scores 6-8 and 9-10, respectively, were higher (P < 0.001) for pigs fed Meal compared to pigs fed Pellets. The odds of suffering from severe gastric ulcers tended (P = 0.08) to be lower in pigs fed Hemp Hulls compared to pigs fed Pellets. A non-targeted liquid chromatography mass spectrometry based metabolomics analysis was performed on saliva samples to determine any separation between pigs with healthy stomachs and those with gastric ulcers and to examine a possible correlation between gastric ulcer index and potential biomarkers. Partial least-squares discriminant analysis showed a separation between pigs with ulcers and those with healthy stomachs/hyperkeratosis (HK). Metabolites contributing to the separation between groups were identified. Levels of oxylipins deriving from linoleic acid were lower (P < 0.001) in pigs with ulcers compared to healthy/HK pigs. This may indicate a shift in the metabolic pathways towards more pro-inflammatory arachidonic acid-derived eicosanoids, which might reflect an increased inflammatory response. Thus, reduced levels of oxylipins derived from linoleic acid seemed to be associated with active gastric ulcers, and thereby they might function as biomarkers for gastric ulceration in pigs. In addition, supplementation of hempseed hulls had a beneficial effect on severe gastric ulcers, as hempseed hulls changed the consistency of the gastric content by conferring more solidness. However, it was not possible to observe any reliable separation between pigs fed pellets supplemented with hemp products and pigs fed non-supplemented pellets according to the identified salivary metabolites.

A Real-Life Reproducibility Assessment for NMR Metabolomics

Nuclear magnetic resonance (NMR) metabolomics is currently popular enough to attract both specialized and non-specialized NMR groups involving both analytical trained personnel and newcomers, including undergraduate students. Recent interlaboratory studies performed by established NMR metabolomics groups demonstrated high reproducibility of the state-of-the-art NMR equipment and SOPs. There is, however, no assessment of NMR reproducibility when mixing both analytical experts and newcomers. An interlaboratory assessment of NMR quantitation reproducibility was performed using two NMR instruments belonging to different laboratories and involving several operators with different backgrounds and metabolomics expertise for the purpose of assessing the limiting factors for data reproducibility in a multipurpose NMR environment. The variability induced by the operator, automatic pipettes, NMR tubes and NMR instruments was evaluated in order to assess the limiting factors for quantitation reproducibility. The results estimated the expected reproducibility data in a real-life multipurpose NMR laboratory to a maximum 4% variability, demonstrating that the current NMR equipment and SOPs may compensate some of the operator-induced variability.

Untargeted metabolomics as a tool to monitor biocontrol product residues' fate on field-treated Prunus persica

Evidence of chemical plant protection products' (PPPs) long-term impact has been found in all environmental compartments. Therefore, other types of PPPs are developed to complement chemical PPPs like PPPs from natural sources, namely biocontrol products (BPs). Little is known about those new BPs, and it is important to assess their potential long-term environmental impact. Recently, the Environmental Metabolic Footprinting (EMF) approach was developed. It permits studying sample's entire meta-metabolome (endometabolome and xenometabolome) through a kinetics tracking of metabolomes of treated and untreated samples. Those metabolomes are compared time-by-time to estimate the "resilience time" of the samples after treatment. The current study aims to investigate BP residues' dissipation on peach fruits (Prunus persica). For that, an untargeted Liquid Chromatography-Mass Spectrometry metabolomics approach based on the EMF was optimised to separate the xenometabolome of the PPP from the endometabolome of the fruits. This "new version" of the EMF approach is able to target the BP treatment residues' (xenometabolome) dissipation exclusively. Thus, it is able to determine the time needed to have no more residues in the studied matrix: the "dissipation interval". Field experiment was conducted on peach tree orchard against brown rot treated with (i) a plant extract BP (Akivi); (ii) a reference mineral extract BP (Armicarb®); and (iii) a Chemical reference treatment campaign. Formulated Akivi and its by-products' dissipation was monitored, a degradation kinetics appeared but the sampling did not last long enough to allow the determination of the "dissipation interval". Armicarb® and the Chemical reference's residues and by-products showed a persistence pattern along the sampling kinetics. These results indicate that the EMF approach, formerly developed on soil and sediment, is applicable for fruit matrices and can be used to investigate the fate of complex BP treatment on the matrix through the xenometabolome tracking on treated fruits.

Deep models of integrated multiscale molecular data decipher the endothelial cell response to ionizing radiation

The vascular endothelium is a hot spot in the response to radiation therapy for both tumors and normal tissues. To improve patient outcomes, interpretable systemic hypotheses are needed to help radiobiologists and radiation oncologists propose endothelial targets that could protect normal tissues from the adverse effects of radiation therapy and/or enhance its antitumor potential. To this end, we captured the kinetics of multi-omics layers-i.e. miRNome, targeted transcriptome, proteome, and metabolome-in irradiated primary human endothelial cells cultured in vitro. We then designed a strategy of deep learning as in convolutional graph networks that facilitates unsupervised high-level feature extraction of important omics data to learn how ionizing radiation-induced endothelial dysfunction may evolve over time. Last, we present experimental data showing that some of the features identified using our approach are involved in the alteration of angiogenesis by ionizing radiation.

The impact of ethnicity and intra-pancreatic fat on the postprandial metabolome response to whey protein in overweight Asian Chinese and European Caucasian women with prediabetes

The "Thin on the Outside Fat on the Inside" TOFI_Asia study found Asian Chinese to be more susceptible to Type 2 Diabetes (T2D) compared to European Caucasians matched for gender and body mass index (BMI). This was influenced by degree of visceral adipose deposition and ectopic fat accumulation in key organs, including liver and pancreas, leading to altered fasting plasma glucose, insulin resistance, and differences in plasma lipid and metabolite profiles. It remains unclear how intra-pancreatic fat deposition (IPFD) impacts TOFI phenotype-related T2D risk factors associated with Asian Chinese. Cow's milk whey protein isolate (WPI) is an insulin secretagogue which can suppress hyperglycemia in prediabetes. In this dietary intervention, we used untargeted metabolomics to characterize the postprandial WPI response in 24 overweight women with prediabetes. Participants were classified by ethnicity (Asian Chinese, n=12; European Caucasian, n=12) and IPFD (low IPFD < 4.66%, n=10; high IPFD ≥ 4.66%, n=10). Using a cross-over design participants were randomized to consume three WPI beverages on separate occasions; 0 g (water control), 12.5 g (low protein, LP) and 50 g (high protein, HP), consumed when fasted. An exclusion pipeline for isolating metabolites with temporal (T_0-240mins) WPI responses was implemented, and a support vector machine-recursive feature elimination (SVM-RFE) algorithm was used to model relevant metabolites by ethnicity and IPFD classes. Metabolic network analysis identified glycine as a central hub in both ethnicity and IPFD WPI response networks. A depletion of glycine relative to WPI concentration was detected in Chinese and high IPFD participants independent of BMI. Urea cycle metabolites were highly represented among the ethnicity WPI metabolome model, implicating a dysregulation in ammonia and nitrogen metabolism among Chinese participants. Uric acid and purine synthesis pathways were enriched within the high IPFD cohort's WPI metabolome response, implicating adipogenesis and insulin resistance pathways. In conclusion, the discrimination of ethnicity from WPI metabolome profiles was a stronger prediction model than IPFD in overweight women with prediabetes. Each models' discriminatory metabolites enriched different metabolic pathways that help to further characterize prediabetes in Asian Chinese women and women with increased IPFD, independently.

Untargeted Metabolomics Reveals a Complex Impact on Different Metabolic Pathways in Scallop Mimachlamys varia (Linnaeus, 1758) after Short-Term Exposure to Copper at Environmental Dose

Ports are a good example of how coastal environments, gathering a set of diverse ecosystems, are subjected to pollution factors coming from human activities both on land and at sea. Among them, trace element as copper represents a major factor. Abundant in port ecosystem, copper is transported by runoff water and results from diverse port features (corrosion of structures, fuel, anti-fouling products, etc.). The variegated scallop Mimachlamys varia is common in the Atlantic port areas and is likely to be directly influenced by copper pollution, due to its sessile and filtering lifestyle. Thus, the aim of the present study is to investigate the disruption of the variegated scallop metabolism, under a short exposure (48 h) to a copper concentration frequently encountered in the waters of the largest marina in Europe (82 μg/L). For this, we chose a non-targeted metabolomic approach using ultra-high performance liquid chromatography coupled to high resolution mass spectrometry (UHPLC-HRMS), offering a high level of sensitivity and allowing the study without a priori of the entire metabolome. We described 28 metabolites clearly modulated by copper. They reflected the action of copper on several biological functions such as osmoregulation, oxidative stress, reproduction and energy metabolism.

Spot urine collection: A valid alternative to total urine collection for metabolomic studies in dairy cattle

Urine is a highly suitable biological matrix for metabolomics studies. Total collection for 24-h periods is the gold standard as it ensures the presence of all metabolites excreted throughout the day. However, in animal studies, it presents limitations related to animal welfare and also due to alterations of the metabolome originating from the use of acid for preventing microbial growth or microbial contamination. In this study, we investigated whether spot urine collection is a practical alternative to total collection for metabolomic studies in lactating cows. For this purpose, we collected urine samples from 4 lactating Holstein cows fed 4 diets in a 4 × 4 Latin square design. Urine was collected for 24 h using a collecting device (i.e., total collection) or collected once per day 4 h after the morning feeding (i.e., spot urine collection). Dietary treatments differed by the amount of nitrogen content (high vs. low) and by the nature of the energy (starch vs. fiber). Urine metabolome was analyzed by 2 untargeted complementary methods, nuclear magnetic resonance and hydrophilic-interaction liquid chromatography (HILIC) coupled to a time-of-flight mass spectrometer, and by 1 targeted method, HILIC-tandem mass spectrometry. Although sampling technique had an effect on the abundance of metabolites detected, spot urine samples were equally capable of showing differences in urine metabolome than samples from total collection. When considering nitrogen levels in the diet, the robustness and precision for discriminating high- and low-nitrogen diets was equally achieved with both sampling techniques. A total of 22 discriminant metabolites associated with the N level of diets were identified from untargeted HILIC coupled to a time-of-flight mass spectrometer (n = 9) and nuclear magnetic resonance (n = 11), and 2 from targeted HILIC-tandem mass spectrometry. Alternatively, starch or fiber in the diet induced less changes in the metabolome that were not clearly discriminated independently of the sampling technique. We concluded that spot urine collection can successfully reveal differences in the urine metabolome elicited by dietary N levels and be used as a substitute of total urinary 24-h collection for metabolomic studies.

Towards a comprehensive characterisation of the human internal chemical exposome: Challenges and perspectives

The holistic characterisation of the human internal chemical exposome using high-resolution mass spectrometry (HRMS) would be a step forward to investigate the environmental ætiology of chronic diseases with an unprecedented precision. HRMS-based methods are currently operational to reproducibly profile thousands of endogenous metabolites as well as externally-derived chemicals and their biotransformation products in a large number of biological samples from human cohorts. These approaches provide a solid ground for the discovery of unrecognised biomarkers of exposure and metabolic effects associated with many chronic diseases. Nevertheless, some limitations remain and have to be overcome so that chemical exposomics can provide unbiased detection of chemical exposures affecting disease susceptibility in epidemiological studies. Some of these limitations include (i) the lack of versatility of analytical techniques to capture the wide diversity of chemicals; (ii) the lack of analytical sensitivity that prevents the detection of exogenous (and endogenous) chemicals occurring at (ultra) trace levels from restricted sample amounts, and (iii) the lack of automation of the annotation/identification process. In this article, we discuss a number of technological and methodological limitations hindering applications of HRMS-based methods and propose initial steps to push towards a more comprehensive characterisation of the internal chemical exposome. We also discuss other challenges including the need for harmonisation and the difficulty inherent in assessing the dynamic nature of the internal chemical exposome, as well as the need for establishing a strong international collaboration, high level networking, and sustainable research infrastructure. A great amount of research, technological development and innovative bio-informatics tools are still needed to profile and characterise the "invisible" (not profiled), "hidden" (not detected) and "dark" (not annotated) components of the internal chemical exposome and concerted efforts across numerous research fields are paramount.

Bifidobacterium species associated with breastfeeding produce aromatic lactic acids in the infant gut

Breastfeeding profoundly shapes the infant gut microbiota, which is critical for early life immune development, and the gut microbiota can impact host physiology in various ways, such as through the production of metabolites. However, few breastmilk-dependent microbial metabolites mediating host-microbiota interactions are currently known. Here, we demonstrate that breastmilk-promoted Bifidobacterium species convert aromatic amino acids (tryptophan, phenylalanine and tyrosine) into their respective aromatic lactic acids (indolelactic acid, phenyllactic acid and 4-hydroxyphenyllactic acid) via a previously unrecognized aromatic lactate dehydrogenase (ALDH). The ability of Bifidobacterium species to convert aromatic amino acids to their lactic acid derivatives was confirmed using monocolonized mice. Longitudinal profiling of the faecal microbiota composition and metabolome of Danish infants (n = 25), from birth until 6 months of age, showed that faecal concentrations of aromatic lactic acids are correlated positively with the abundance of human milk oligosaccharide-degrading Bifidobacterium species containing the ALDH, including Bifidobacterium longum, B. breve and B. bifidum. We further demonstrate that faecal concentrations of Bifidobacterium-derived indolelactic acid are associated with the capacity of these samples to activate in vitro the aryl hydrocarbon receptor (AhR), a receptor important for controlling intestinal homoeostasis and immune responses. Finally, we show that indolelactic acid modulates ex vivo immune responses of human CD4+ T cells and monocytes in a dose-dependent manner by acting as an agonist of both the AhR and hydroxycarboxylic acid receptor 3 (HCA3). Our findings reveal that breastmilk-promoted Bifidobacterium species produce aromatic lactic acids in the gut of infants and suggest that these microbial metabolites may impact immune function in early life.

Discovery of a Metabolic Signature Predisposing High Risk Patients with Mild Cognitive Impairment to Converting to Alzheimer's Disease

Assessing dementia conversion in patients with mild cognitive impairment (MCI) remains challenging owing to pathological heterogeneity. While many MCI patients ultimately proceed to Alzheimer’s disease (AD), a subset of patients remain stable for various times. Our aim was to characterize the plasma metabolites of nineteen MCI patients proceeding to AD (P-MCI) and twenty-nine stable MCI (S-MCI) patients by untargeted metabolomics profiling. Alterations in the plasma metabolites between the P-MCI and S-MCI groups, as well as between the P-MCI and AD groups, were compared over the observation period. With the help of machine learning-based stratification, a 20-metabolite signature panel was identified that was associated with the presence and progression of AD. Furthermore, when the metabolic signature panel was used for classification of the three patient groups, this gave an accuracy of 73.5% using the panel. Moreover, when specifically classifying the P-MCI and S-MCI subjects, a fivefold cross-validation accuracy of 80.3% was obtained using the random forest model. Importantly, indole-3-propionic acid, a bacteria-generated metabolite from tryptophan, was identified as a predictor of AD progression, suggesting a role for gut microbiota in AD pathophysiology. Our study establishes a metabolite panel to assist in the stratification of MCI patients and to predict conversion to AD.

Metabolomic Signatures Discriminate Horses with Clinical Signs of Atypical Myopathy from Healthy Co-grazing Horses

Atypical myopathy (AM) is a severe rhabdomyolysis syndrome that occurs in grazing horses. Despite the presence of toxins in their blood, all horses from the same pasture are not prone to display clinical signs of AM. The objective of this study was to compare the blood metabolomic profiles of horses with AM clinical signs with those of healthy co-grazing (Co-G) horses. To do so, plasma samples from 5 AM horses and 11 Co-G horses were investigated using untargeted metabolomics. Metabolomic data were evaluated using unsupervised, supervised, and pathway analyses. Unsupervised principal component analysis performed with all detected features separated AM and healthy Co-G horses. Supervised analyses had identified 1276 features showing differential expression between both groups. Among them, 46 metabolites, belonging predominantly to the fatty acid, fatty ester, and amino acid chemical classes, were identified by standard comparison. Fatty acids, unsaturated fatty acids, organic dicarboxylic acids, and fatty esters were detected with higher intensities in AM horses in link with the toxins' pathological mechanism. The main relevant pathways were lipid metabolism; valine, leucine, and isoleucine metabolism; and glycine metabolism. This study revealed characteristic metabolite changes in the plasma of clinically affected horses, which might ultimately help scientists and field veterinarians to detect and manage AM. The raw data of metabolomics are available in the MetaboLights database with the access number MTBLS2579.

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.

Statistical analysis in metabolic phenotyping

Metabolic phenotyping is an important tool in translational biomedical research. The advanced analytical technologies commonly used for phenotyping, including mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy, generate complex data requiring tailored statistical analysis methods. Detailed protocols have been published for data acquisition by liquid NMR, solid-state NMR, ultra-performance liquid chromatography (LC-)MS and gas chromatography (GC-)MS on biofluids or tissues and their preprocessing. Here we propose an efficient protocol (guidelines and software) for statistical analysis of metabolic data generated by these methods. Code for all steps is provided, and no prior coding skill is necessary. We offer efficient solutions for the different steps required within the complete phenotyping data analytics workflow: scaling, normalization, outlier detection, multivariate analysis to explore and model study-related effects, selection of candidate biomarkers, validation, multiple testing correction and performance evaluation of statistical models. We also provide a statistical power calculation algorithm and safeguards to ensure robust and meaningful experimental designs that deliver reliable results. We exemplify the protocol with a two-group classification study and data from an epidemiological cohort; however, the protocol can be easily modified to cover a wider range of experimental designs or incorporate different modeling approaches. This protocol describes a minimal set of analyses needed to rigorously investigate typical datasets encountered in metabolic phenotyping.

Local intestinal microbiota response and systemic effects of feeding black soldier fly larvae to replace soybean meal in growing pigs

Black soldier fly (Hermetia illucens; BSF) larvae as dietary protein source have the ability to deliver nutrients and could possess functional properties that positively support animal productivity and health. More knowledge, however, is needed to assess the impact of feeding a BSF based diet on gut and animal health. Sixteen post-weaned male pigs were randomly assigned to two groups and fed for three weeks with iso-caloric and iso-proteinaceous experimental diets prepared with either soybean meal (SBM) as reference protein source or with BSF as single source of dietary protein. At the end of the trial, the pigs were sacrificed to collect relevant digesta, gut tissue and blood samples to study changes induced by the dietary treatments using ~ omics based analyses. Inclusion of BSF in the diet supports the development of the intestinal microbiome that could positively influence intestinal health. By amine metabolite analysis, we identified two metabolites i.e. sarcosine and methionine sulfoxide, in plasma that serve as markers for the ingestion of insect based ingredients. BSF seems to possess functional properties indicated by the appearance of alpha-aminobutyric acid and taurine in blood plasma of pigs that are known to induce health beneficial effects.

Nandrolone and estradiol biomarkers identification in bovine urine applying a liquid chromatography high-resolution mass spectrometry metabolomics approach

With the aim of specifically investigating patterns associated with three steroid treatments (17β-nandrolone, 17β-estradiol, and 17β-nandrolone + 17β-estradiol) in bovine, an reversed phase liquid chromatography (RPLC)-electrospray ionization (ESI)(+/-)-high-resolution mass spectrometry (HRMS) study was conducted to characterize the urinary profiles of involved animals. Although specific fingerprints with strong differences could be highlighted between urinary metabolite profiles within urine samples collected on control and treated animals, it appeared further that significant discriminations could also be observed between steroid treatments, evidencing thus specific patterns and candidate biomarkers associated to each treatment. An MS-2 structural elucidation step enabled level-1 identification of two biomarkers mainly involved in energy pathways, in relation to skeletal muscle functioning. These results make it possible to envisage a global strategy for the detection of anabolic practices involving steroids, while at the same time providing clues as to the compounds used, which would facilitate the confirmation stage to follow.

Effect of a short-term salinity stress on the growth, biovolume, toxins, osmolytes and metabolite profiles on three strains of the Dinophysis acuminata-complex (Dinophysis cf. sacculus)

Dinophysis is the main dinoflagellate genus responsible for diarrheic shellfish poisoning (DSP) in human consumers of filter feeding bivalves contaminated with lipophilic diarrheic toxins. Species of this genus have a worldwide distribution driven by environmental conditions (temperature, irradiance, salinity, nutrients etc.), and these factors are sensitive to climate change. The D. acuminata-complex may contain several species, including D. sacculus. The latter has been found in estuaries and semi-enclosed areas, water bodies subjected to quick salinity variations and its natural repartition suggests some tolerance to salinity changes. However, the response of strains of D. acuminata-complex (D. cf. sacculus) subjected to salinity stress and the underlying mechanisms have never been studied in the laboratory. Here, a 24 h hypoosmotic (25) and hyperosmotic (42) stress was performed in vitro in a metabolomic study carried out with three cultivated strains of D. cf. sacculus isolated from the French Atlantic and Mediterranean coasts. Growth rate, biovolume and osmolyte (proline, glycine betaine and dimethylsulfoniopropionate (DMSP)) and toxin contents were measured. Osmolyte contents were higher at the highest salinity, but only a significant increase in glycine betaine was observed between the control (35) and the hyperosmotic treatment. Metabolomics revealed significant and strain-dependent differences in metabolite profiles for different salinities. These results, as well as the absence of effects on growth rate, biovolume, okadaic acid (OA) and pectenotoxin (PTXs) cellular contents, suggest that the D. cf. sacculus strains studied are highly tolerant to salinity variations.

Multiplatform metabolomics for an integrative exploration of metabolic syndrome in older men

BACKGROUND

Metabolic syndrome (MetS), a cluster of factors associated with risks of developing cardiovascular diseases, is a public health concern because of its growing prevalence. Considering the combination of concomitant components, their development and severity, MetS phenotypes are largely heterogeneous, inducing disparity in diagnosis.

METHODS

A case/control study was designed within the NuAge longitudinal cohort on aging. From a 3-year follow-up of 123 stable individuals, we present a deep phenotyping approach based on a multiplatform metabolomics and lipidomics untargeted strategy to better characterize metabolic perturbations in MetS and define a comprehensive MetS signature stable over time in older men.

FINDINGS

We characterize significant changes associated with MetS, involving modulations of 476 metabolites and lipids, and representing 16% of the detected serum metabolome/lipidome. These results revealed a systemic alteration of metabolism, involving various metabolic pathways (urea cycle, amino-acid, sphingo- and glycerophospholipid, and sugar metabolisms…) not only intrinsically interrelated, but also reflecting environmental factors (nutrition, microbiota, physical activity…).

INTERPRETATION

These findings allowed identifying a comprehensive MetS signature, reduced to 26 metabolites for future translation into clinical applications for better diagnosing MetS.

FUNDING

The NuAge Study was supported by a research grant from the Canadian Institutes of Health Research (CIHR; MOP-62842). The actual NuAge Database and Biobank, containing data and biologic samples of 1,753 NuAge participants (from the initial 1,793 participants), are supported by the Fonds de recherche du Québec (FRQ; 2020-VICO-279753), the Quebec Network for Research on Aging, a thematic network funded by the Fonds de Recherche du Québec - Santé (FRQS) and by the Merck-Frost Chair funded by La Fondation de l'Université de Sherbrooke. All metabolomics and lipidomics analyses were funded and performed within the metaboHUB French infrastructure (ANR-INBS-0010). All authors had full access to the full data in the study and accept responsibility to submit for publication.