Visceral Adipose Tissue Phospholipid Signature of Insulin Sensitivity and Obesity.

Alterations in visceral adipose tissue (VAT) are closely linked to cardiometabolic abnormalities. The aim of this work is to define a metabolic signature in VAT of insulin resistance (IR) dependent on, and independent of, obesity. An untargeted UPLC-Q-Exactive metabolomic approach was carried out on the VAT of obese insulin-sensitive (IS) and insulin-resistant subjects (N = 11 and N = 25, respectively) and nonobese IS and IR subjects (N = 25 and N = 10, respectively). The VAT metabolome in obesity was defined among other things by changes in the metabolism of lipids, nucleotides, carbohydrates, and amino acids, whereas when combined with high IR, it affected the metabolism of 18 carbon fatty acyl-containing phospholipid species. A multimetabolite model created by glycerophosphatidylinositol (18:0); glycerophosphatidylethanolamine (18:2); glycerophosphatidylserine (18:0); and glycerophosphatidylcholine (18:0/18:1), (18:2/18:2), and (18:2/18:3) exhibited a highly predictive performance to identify the metabotype of "insulin-sensitive obesity" among obese individuals [area under the curve (AUC) 96.7% (91.9-100)] and within the entire study population [AUC 87.6% (79.0-96.2)]. We demonstrated that IR has a unique and shared metabolic signature dependent on, and independent of, obesity. For it to be used in clinical practice, these findings need to be validated in a more accessible sample, such as blood.

Habitual Nut Exposure, Assessed by Dietary and Multiple Urinary Metabolomic Markers, and Cognitive Decline in Older Adults: The InCHIANTI Study.

SCOPE: The association between self-reported dietary intake and urinary metabolomic markers of habitual nut exposure with cognitive decline over a 3-year follow-up in an older Italian population is prospectively evaluated. METHODS AND RESULTS: A total of 119 older participants are selected, based on self-referred nut intake: the non-nut consumer (n = 72) and the regular consumer (≥2.9 g d-1 , n = 47). Nut exposure is measured at baseline either with the use of a validated food frequency questionnaire or with an HPLC-Q-ToF-MS metabolomic approach. Three years after, 28 from the nonconsumers and 10 from the consumers experienced cognitive decline. Dietary nut exposure is characterized by urinary metabolites of polyphenols and fatty acids pathways. Nut consumption estimated either by the dietary marker or by the urinary marker model is in both cases associated with less cognitive decline (OR: 0.78, 95% CI: 0.61,0.99; p = 0.043 and OR: 0.995, 95% CI: 0.991,0.999; p = 0.016, respectively) with AUCs 73.2 (95% CI: 62.9, 83.6) and 73.1 (62.5, 83.7), respectively. CONCLUSIONS: A high intake of nuts may protect older adults from cognitive decline. Metabolomics provides accurate and complementary information of the nut exposure and reinforces the results obtained using dietary information.

Characterization of Metabolomic Profile Associated with Metabolic Improvement after Bariatric Surgery in Subjects with Morbid Obesity.

The exact impact of bariatric surgery in metabolically "healthy" (MH) or "unhealthy" (MU) phenotypes for the study of the metabolic improvement is still unknown. We applied an untargeted LC-ESI-TripleTOF-MS-driven metabolomics approach in serum samples from 39 patients with morbid obesity (MH and MU) 1, 3, and 6 months after bariatric surgery. Multiple factor analysis, along with correlation and enrichment analyses, was carried out to distinguish those metabolites associated with metabolic improvement. Hydroxypropionic acids, medium-/long-chain hydroxy fatty acids, and bile acid glucuronides were the most discriminative biomarkers of response between MH and MU phenotypes. Hydroxypropionic (hydroxyphenyllactic-related) acids, amino acids, and glycerolipids were the most significant clusters of metabolites altered after bariatric surgery in MU ( p < 0.001). After surgery, MU and MH changed toward a common metabolic state 3 months after surgery. We observed a negative correlation with changes in waist circumference and cholesterol levels with metabolites of lipid metabolism. Glycemic variables were correlated with hexoses, which, in turn, correlated with gluconic acid and amino acid metabolism. Finally, we noted that hydroxyphenyllactic acid was associated with amino acid and lipid metabolism. Microbial metabolism of amino acid and BA glucuronidation pathways may be the key points of metabolic rearrangement after surgery.

Metabotypes of response to bariatric surgery independent of the magnitude of weight loss.

OBJECTIVE: Bariatric surgery is considered the most efficient treatment for morbid obesity and its related diseases. However, its role as a metabolic modifier is not well understood. We aimed to determine biosignatures of response to bariatric surgery and elucidate short-term metabolic adaptations. METHODS: We used a LC- and FIA-ESI-MS/MS approach to quantify acylcarnitines, (lyso)phosphatidylcholines, sphingomyelins, amino acids, biogenic amines and hexoses in serum samples of subjects with morbid obesity (n = 39) before and 1, 3 and 6 months after bariatric surgery. K-means cluster analysis allowed to distinguish metabotypes of response to bariatric surgery. RESULTS: For the first time, global metabolic changes following bariatric surgery independent of the baseline health status of the subjects have been revealed. We identify two metabolic phenotypes (metabotypes) at the interval 6 months-baseline after surgery, which presented differences in the levels of compounds of urea metabolism, gluconeogenic precursors and (lyso)phospholipid particles. Clinically, metabotypes were different in terms of the degree of improvement in insulin resistance, cholesterol, low-density lipoproteins and uric acid independent of the magnitude of weight loss. CONCLUSIONS: This study opens new perspectives and new hypotheses on the metabolic benefits of bariatric surgery and understanding of the biology of obesity and its associated diseases.

Untargeted Profiling of Concordant/Discordant Phenotypes of High Insulin Resistance and Obesity To Predict the Risk of Developing Diabetes.

This study explores the metabolic profiles of concordant/discordant phenotypes of high insulin resistance (IR) and obesity. Through untargeted metabolomics (LC-ESI-QTOF-MS), we analyzed the fasting serum of subjects with high IR and/or obesity ( n = 64). An partial least-squares discriminant analysis with orthogonal signal correction followed by univariate statistics and enrichment analysis allowed exploration of these metabolic profiles. A multivariate regression method (LASSO) was used for variable selection and a predictive biomarker model to identify subjects with high IR regardless of obesity was built. Adrenic acid and a dyglyceride (DG) were shared by high IR and obesity. Uric and margaric acids, 14 DGs, ketocholesterol, and hydroxycorticosterone were unique to high IR, while arachidonic, hydroxyeicosatetraenoic (HETE), palmitoleic, triHETE, and glycocholic acids, HETE lactone, leukotriene B4, and two glutamyl-peptides to obesity. DGs and adrenic acid differed in concordant/discordant phenotypes, thereby revealing protective mechanisms against high IR also in obesity. A biomarker model formed by DGs, uric and adrenic acids presented a high predictive power to identify subjects with high IR [AUC 80.1% (68.9-91.4)]. These findings could become relevant for diabetes risk detection and unveil new potential targets in therapeutic treatments of IR, diabetes, and obesity. An independent validated cohort is needed to confirm these results.

Evaluation and comparison of bioinformatic tools for the enrichment analysis of metabolomics data.

BACKGROUND: Bioinformatic tools for the enrichment of 'omics' datasets facilitate interpretation and understanding of data. To date few are suitable for metabolomics datasets. The main objective of this work is to give a critical overview, for the first time, of the performance of these tools. To that aim, datasets from metabolomic repositories were selected and enriched data were created. Both types of data were analysed with these tools and outputs were thoroughly examined. RESULTS: An exploratory multivariate analysis of the most used tools for the enrichment of metabolite sets, based on a non-metric multidimensional scaling (NMDS) of Jaccard's distances, was performed and mirrored their diversity. Codes (identifiers) of the metabolites of the datasets were searched in different metabolite databases (HMDB, KEGG, PubChem, ChEBI, BioCyc/HumanCyc, LipidMAPS, ChemSpider, METLIN and Recon2). The databases that presented more identifiers of the metabolites of the dataset were PubChem, followed by METLIN and ChEBI. However, these databases had duplicated entries and might present false positives. The performance of over-representation analysis (ORA) tools, including BioCyc/HumanCyc, ConsensusPathDB, IMPaLA, MBRole, MetaboAnalyst, Metabox, MetExplore, MPEA, PathVisio and Reactome and the mapping tool KEGGREST, was examined. Results were mostly consistent among tools and between real and enriched data despite the variability of the tools. Nevertheless, a few controversial results such as differences in the total number of metabolites were also found. Disease-based enrichment analyses were also assessed, but they were not found to be accurate probably due to the fact that metabolite disease sets are not up-to-date and the difficulty of predicting diseases from a list of metabolites. CONCLUSIONS: We have extensively reviewed the state-of-the-art of the available range of tools for metabolomic datasets, the completeness of metabolite databases, the performance of ORA methods and disease-based analyses. Despite the variability of the tools, they provided consistent results independent of their analytic approach. However, more work on the completeness of metabolite and pathway databases is required, which strongly affects the accuracy of enrichment analyses. Improvements will be translated into more accurate and global insights of the metabolome.

Strawberry consumption improves aging-associated impairments, mitochondrial biogenesis and functionality through the AMP-activated protein kinase signaling cascade.

Dietary polyphenols have been recently proposed as activators of the AMP-activated protein kinase (AMPK) signaling pathway and this fact might explain the relationship between the consumption of polyphenol-rich foods and the slowdown of the progression of aging. In the present work, the effects of strawberry consumption were evaluated on biomarkers of oxidative damage and on aging-associated reductions in mitochondrial function and biogenesis for 8weeks in old rats. Strawberry supplementation increased antioxidant enzyme activities, mitochondrial biomass and functionality, and decreased intracellular ROS levels and biomarkers of protein, lipid and DNA damage (P<0.05). Furthermore, a significant (P<0.05) increase in the expression of the AMPK cascade genes, involved in mitochondrial biogenesis and antioxidant defences, was also detected after strawberry intake. These in vivo results were then verified in vitro on HepG2 cells, confirming the involvement of AMPK in the beneficial effects exerted by strawberry against aging progression.

Biomarkers of Morbid Obesity and Prediabetes by Metabolomic Profiling of Human Discordant Phenotypes.

Metabolomic studies aimed to dissect the connection between the development of type 2 diabetes and obesity are still scarce. In the present study, fasting serum from sixty-four adult individuals classified into four sex-matched groups by their BMI [non-obese versus morbid obese] and the increased risk of developing diabetes [prediabetic insulin resistant state versus non-prediabetic non-insulin resistant] was analyzed by LC- and FIA-ESI-MS/MS-driven metabolomic approaches. Altered levels of [lyso]glycerophospholipids was the most specific metabolic trait associated to morbid obesity, particularly lysophosphatidylcholines acylated with margaric, oleic and linoleic acids [lysoPC C17:0: R=-0.56, p=0.0003; lysoPC C18:1: R=-0.61, p=0.0001; lysoPC C18:2 R=-0.64, p<0.0001]. Several amino acids were biomarkers of risk of diabetes onset associated to obesity. For instance, glutamate significantly associated with fasting insulin [R=0.5, p=0.0019] and HOMA-IR [R=0.46, p=0.0072], while glycine showed negative associations [fasting insulin: R=-0.51, p=0.0017; HOMA-IR: R=-0.49, p=0.0033], and the branched chain amino acid valine associated to prediabetes and insulin resistance in a BMI-independent manner [fasting insulin: R=0.37, p=0.0479; HOMA-IR: R=0.37, p=0.0468]. Minority sphingolipids including specific [dihydro]ceramides and sphingomyelins also associated with the prediabetic insulin resistant state, hence deserving attention as potential targets for early diagnosis or therapeutic intervention.

Metabolomics-guided insights on bariatric surgery versus behavioral interventions for weight loss.

OBJECTIVE: To review the metabolomic studies carried out so far to identify metabolic markers associated with surgical and dietary treatments for weight loss in subjects with obesity. METHODS: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. RESULTS: Thirty-two studies successfully met the eligibility criteria. The metabolic adaptations shared by surgical and dietary interventions mirrored a state of starvation ketoacidosis (increase of circulating ketone bodies), an increase of acylcarnitines and fatty acid ß-oxidation, a decrease of specific amino acids including branched-chain amino acids (BCAA) and (lyso)glycerophospholipids previously associated with obesity, and adipose tissue expansion. The metabolic footprint of bariatric procedures was specifically characterized by an increase of bile acid circulating pools and a decrease of ceramide levels, a greater perioperative decline in BCAA, and the rise of circulating serine and glycine, mirroring glycemic control and inflammation improvement. In one study, 3-hydroxybutyrate was particularly identified as an early metabolic marker of long-term prognosis after surgery and proposed to increase current prognostic modalities and contribute to personalized treatment. CONCLUSIONS: Metabolomics helped in deciphering the metabolic response to weight loss treatments. Moving from association to causation is the next challenge to move to a further level of clinical application.

Dietary Epicatechin Is Available to Breastfed Infants through Human Breast Milk in the Form of Host and Microbial Metabolites.

Polyphenols play an important role in human health. To address their accessibility to a breastfed infant, we planned to evaluate whether breast milk (BM) (colostrum, transitional, and mature) epicatechin metabolites could be related to the dietary habits of mothers. The polyphenol consumption of breastfeeding mothers was estimated using a food frequency questionnaire and 24 h recalls. Solid-phase extraction-ultra performance liquid chromatography-tandem mass spectrometry (SPE-UPLC-MS/MS) was applied for direct epicatechin metabolite analysis. Their bioavailability in BM as a result of dietary ingestion was confirmed in a preliminary experiment with a single dose of dark chocolate. Several host and microbial phase II metabolites of epicatechin were detected in BM among free-living lactating mothers. Interestingly, a modest correlation between dihydroxyvalerolactone sulfate and the intake of cocoa products was observed. Although a very low percentage of dietary polyphenols is excreted in BM, they are definitely in the diet of breastfed infants. Therefore, evaluation of their role in infant health could be further promoted.

Bioavailability of tomato polyphenols is enhanced by processing and fat addition: Evidence from a randomized feeding trial.

SCOPE: Tomato contains a variety of phenolics associated with health-promoting properties. However, the effects of processing and the addition of oil during tomato sauce preparation on microbial metabolism of phenolics in the small intestine are still unclear. METHODS AND RESULTS: An open, controlled, randomized, and crossover feeding trial with 40 healthy volunteers was carried out to analyze the metabolites in plasma and urine after the consumption of tomato and tomato sauces, with tomato sauce enriched with refined olive oil (ROOE) and without refined olive oil (oil-free: OF). Ten phenolics in plasma and 93 metabolites in urine were quantified. Processing tomatoes into sauce enhanced the bioavailability of flavanones, flavanols, and some hydroxycinnamic acids, as reflected by the increase in the area under the plasma concentration versus time curve. An increase in their plasma half-life was also observed, particularly after ingestion of ROOE, possibly favored by enterohepatic circulation. A wide variety of gut microbial metabolites was also detected, namely flavanones, hydroxycinnamic acids, flavonols, hydroxyphenylpropanoic acids, hydroxyphenylacetic acids, and hydroxybenzoic acids. CONCLUSIONS: Flavanones and flavonols in ROOE presented higher bioavailability, suggesting that the processing undergone by the raw tomato improved their absorption.

Metabolomic insights into the intricate gut microbial-host interaction in the development of obesity and type 2 diabetes.

Gut microbiota has recently been proposed as a crucial environmental factor in the development of metabolic diseases such as obesity and type 2 diabetes, mainly due to its contribution in the modulation of several processes including host energy metabolism, gut epithelial permeability, gut peptide hormone secretion, and host inflammatory state. Since the symbiotic interaction between the gut microbiota and the host is essentially reflected in specific metabolic signatures, much expectation is placed on the application of metabolomic approaches to unveil the key mechanisms linking the gut microbiota composition and activity with disease development. The present review aims to summarize the gut microbial-host co-metabolites identified so far by targeted and untargeted metabolomic studies in humans, in association with impaired glucose homeostasis and/or obesity. An alteration of the co-metabolism of bile acids, branched fatty acids, choline, vitamins (i.e., niacin), purines, and phenolic compounds has been associated so far with the obese or diabese phenotype, in respect to healthy controls. Furthermore, anti-diabetic treatments such as metformin and sulfonylurea have been observed to modulate the gut microbiota or at least their metabolic profiles, thereby potentially affecting insulin resistance through indirect mechanisms still unknown. Despite the scarcity of the metabolomic studies currently available on the microbial-host crosstalk, the data-driven results largely confirmed findings independently obtained from in vitro and animal model studies, putting forward the mechanisms underlying the implication of a dysfunctional gut microbiota in the development of metabolic disorders.

Sensitive and Rapid UHPLC-MS/MS for the Analysis of Tomato Phenolics in Human Biological Samples.

An UHPLC-MS/MS method for the quantification of tomato phenolic metabolites in human fluids was optimized and validated, and then applied in a pilot dietary intervention study with healthy volunteers. A 5-fold gain in speed (3.5 min of total run); 7-fold increase in MS sensitivity and 2-fold greater efficiency (50% peak width reduction) were observed when comparing the proposed method with the reference-quality HPLC-MS/MS system, whose assay performance has been previously documented. The UHPLC-MS/MS method led to an overall improvement in the limits of detection (LOD) and quantification (LOQ) for all the phenolic compounds studied. The recoveries ranged between 68% and 100% in urine and 61% and 100% in plasma. The accuracy; intra- and interday precision; and stability met with the acceptance criteria of the AOAC International norms. Due to the improvements in the analytical method; the total phenolic metabolites detected in plasma and urine in the pilot intervention study were 3 times higher than those detected by HPLC-MS/MS. Comparing with traditional methods; which require longer time of analysis; the methodology described is suitable for the analysis of phenolic compounds in a large number of plasma and urine samples in a reduced time frame.

Plasma metabolomic biomarkers of mixed nuts exposure inversely correlate with severity of metabolic syndrome.

SCOPE: To identify the most discriminant dietary biomarkers of nuts exposure in subjects with metabolic syndrome (MetS), and investigate the potential association between exposure and the severity of the MetS diagnostic traits. METHODS AND RESULTS: We applied the untargeted LC-ESI-qToF-MS-driven metabolomic workflow to explore the changes occurring in the plasma metabolome of MetS subjects following 12-wk intake of mixed nuts (30 g/d; nuts versus control groups). Urolithin A glucuronide was the most discriminative biomarker of nuts exposure, showing the highest predictive capacity (area under the ROC curve = 89.6% [80.8-98.4]) despite the interindividual variation expected for a host-microbial cometabolite. Furthermore, the detection of urolithin A glucuronide in plasma showed significant inverse correlation with basal abdominal adiposity (waist circumference: r = -0.550, p < 0.01; waist-hip ratio: r = -0.409, p < 0.05) and impaired glycemic control (fasting insulin: r = -0.414, p < 0.05; HOMA-IR: r = -0.417, p < 0.05). Significant changes in medium-chain dicarboxylic acids, recognized as alternative energy substrates that are particularly relevant in the case of glycemic control impairment, were also associated with nut consumption. CONCLUSION: Higher levels of utolithin A glucuronide are reported in subjects with less severe MetS traits, especially in females. We believe that this inverse correlation may be related with profile of gut microbial dysbiosis, recently associated to subjects with MetS.

Phenolic and microbial-targeted metabolomics to discovering and evaluating wine intake biomarkers in human urine and plasma.

The discovery of biomarkers of intake in nutritional epidemiological studies is essential in establishing an association between dietary intake (considering their bioavailability) and diet-related risk factors for diseases. The aim is to study urine and plasma phenolic and microbial profile by targeted metabolomics approach in a wine intervention clinical trial for discovering and evaluating food intake biomarkers. High-risk male volunteers (n = 36) were included in a randomized, crossover intervention clinical trial. After a washout period, subjects received red wine or gin, or dealcoholized red wine over four weeks. Fasting plasma and 24-h urine were collected at baseline and after each intervention period. A targeted metabolomic analysis of 70 host and microbial phenolic metabolites was performed using ultra performance liquid chromatography-tandem mass spectrometer (UPLC-MS/MS). Metabolites were subjected to stepwise logistic regression to establish prediction models and received operation curves were performed to evaluate biomarkers. Prediction models based mainly on gallic acid metabolites, obtained sensitivity, specificity and area under the curve (AUC) for the training and validation sets of between 91 and 98% for urine and between 74 and 91% for plasma. Resveratrol, ethylgallate and gallic acid metabolite groups in urine samples also resulted in being good predictors of wine intake (AUC>87%). However, lower values for metabolites were obtained in plasma samples. The highest correlations between fasting plasma and urine were obtained for the prediction model score (r = 0.6, P<0.001), followed by gallic acid metabolites (r = 0.5-0.6, P<0.001). This study provides new insights into the discovery of food biomarkers in different biological samples.

New and vintage solutions to enhance the plasma metabolome coverage by LC-ESI-MS untargeted metabolomics: the not-so-simple process of method performance evaluation.

Although LC-MS untargeted metabolomics continues to expand into exiting research domains, methodological issues have not been solved yet by the definition of unbiased, standardized and globally accepted analytical protocols. In the present study, the response of the plasma metabolome coverage to specific methodological choices of the sample preparation (two SPE technologies, three sample-to-solvent dilution ratios) and the LC-ESI-MS data acquisition steps of the metabolomics workflow (four RP columns, four elution solvent combinations, two solvent quality grades, postcolumn modification of the mobile phase) was investigated in a pragmatic and decision tree-like performance evaluation strategy. Quality control samples, reference plasma and human plasma from a real nutrimetabolomic study were used for intermethod comparisons. Uni- and multivariate data analysis approaches were independently applied. The highest method performance was obtained by combining the plasma hybrid extraction with the highest solvent proportion during sample preparation, the use of a RP column compatible with 100% aqueous polar phase (Atlantis T3), and the ESI enhancement by using UHPLC-MS purity grade methanol as both organic phase and postcolumn modifier. Results led to the following considerations: submit plasma samples to hybrid extraction for removal of interfering components to minimize the major sample-dependent matrix effects; avoid solvent evaporation following sample extraction if loss in detection and peak shape distortion of early eluting metabolites are not noticed; opt for a RP column for superior retention of highly polar species when analysis fractionation is not feasible; use ultrahigh quality grade solvents and "vintage" analytical tricks such as postcolumn organic enrichment of the mobile phase to enhance ESI efficiency. The final proposed protocol offers an example of how novel and old-fashioned analytical solutions may fruitfully cohabit in untargeted metabolomics protocols.

The tomato sauce making process affects the bioaccessibility and bioavailability of tomato phenolics: a pharmacokinetic study.

Tomato sauce is the most commonly consumed processed tomato product worldwide, but very little is known about how the manufacturing process may affect the phenolic composition and bioavailability after consumption. In a prospective randomised, cross-over intervention study, we analysed the plasma and urinary levels of tomato phenolic compounds and their metabolites after acute consumption of raw tomatoes and tomato sauce, enriched or not with refined olive oil during production. Respectively, eleven and four phenolic metabolites were found in urine and plasma samples. The plasma concentration and urinary excretion of naringenin glucuronide were both significantly higher after the consumption of tomato sauce than raw tomatoes. The results suggest that the mechanical and thermal treatments during tomato sauce manufacture may help to deliver these potentially bioactive phenolics from the food matrix more effectively than the addition of an oil component, thus increasing their bioavailability.

High levels of Bifidobacteria are associated with increased levels of anthocyanin microbial metabolites: a randomized clinical trial.

The health benefits associated with the consumption of polyphenol-rich foods have been studied in depth, however, the full mechanism of action remains unknown. One of the proposed mechanisms is through microbiota interaction. In the present study, we aimed to explore the relationship between changes in fecal microbiota and changes in urinary phenolic metabolites after wine interventions. Nine participants followed a randomized, crossover, controlled interventional trial. After the washout period, they received red wine, dealcoholized red wine or gin for 20 days each. Polyphenol metabolites (n > 60) in urine were identified and quantified by UPLC-MS/MS and the microbial content of fecal samples was quantified by real-time quantitative PCR. Interventions with both red wine and dealcoholized red wine increased the fecal concentration of Bifidobacterium, Enterococcus and Eggerthella lenta, compared to gin intervention and baseline. When participants were categorized in tertiles of changes in fecal bacteria, those in the highest tertile of Bifidobacteria had higher urinary concentration changes in syringic acid, p-coumaric acid, 4-hydroxybenzoic acid and homovanillic acid (all anthocyanin metabolites) than those in tertile 1 (P < 0.05, all). In addition, changes of Bifidobacteria correlated positively with changes of these metabolites (r = 0.5-0.7, P < 0.05, all). Finally, the 68.5% changes in Bifidobacteria can be predicted by syringic acid and 4-hydroxybenzoic acid changes. This study confirms the important role of polyphenols as bacterial substrates and their modulatory capacity as an important field in the research of new products with prebiotic and probiotic characteristics for the food industry.

Urinary metabolomic fingerprinting after consumption of a probiotic strain in women with mastitis.

Infectious mastitis is a common condition among lactating women, with staphylococci and streptococci being the main aetiological agents. In this context, some lactobacilli strains isolated from breast milk appear to be particularly effective for treating mastitis and, therefore, constitute an attractive alternative to antibiotherapy. A (1)H NMR-based metabolomic approach was applied to detect metabolomic differences after consuming a probiotic strain (Lactobacillus salivarius PS2) in women with mastitis. 24h urine of women with lactational mastitis was collected at baseline and after 21 days of probiotic (PB) administration. Multivariate analysis (OSC-PLS-DA and hierarchical clustering) showed metabolome differences after PB treatment. The discriminant metabolites detected at baseline were lactose, and ibuprofen and acetaminophen (two pharmacological drugs commonly used for mastitis pain), while, after PB intake, creatine and the gut microbial co-metabolites hippurate and TMAO were detected. In addition, a voluntary desertion of the pharmacological drugs ibuprofen and acetaminophen was observed after probiotic administration. The application of NMR-based metabolomics enabled the identification of the overall effects of probiotic consumption among women suffering from mastitis and highlighted the potential of this approach in evaluating the outcomes of probiotics consumption. To our knowledge, this is the first time that this approach has been applied in women with mastitis during lactation.

Novel multimetabolite prediction of walnut consumption by a urinary biomarker model in a free-living population: the PREDIMED study.

The beneficial impact of walnuts on human health has been attributed to their unique chemical composition. In order to characterize the dietary walnut fingerprinting, spot urine samples from two sets of 195 (training) and 186 (validation) individuals were analyzed by an HPLC-q-ToF-MS untargeted metabolomics approach, selecting the most discriminating metabolites by multivariate data analysis (VIP ≥ 1.5). Stepwise logistic regression analysis was used to design a multimetabolite prediction biomarker model. The global performance of the model and each included metabolite in it was evaluated by receiver operating characteristic curves, using the area under the curve (AUC) values. Dietary exposure to walnuts was characterized by 18 metabolites, including markers of fatty acid metabolism, ellagitannin-derived microbial compounds, and intermediate metabolites of the tryptophan/serotonin pathway. The predictive model of walnut exposure included at least one compound of each class. The AUC (95% CI) for the combined biomarker model was 93.4% (90.1-96.8%) in the training set and 90.2% (85.9-94.6%) in the validation set. The AUCs for individual metabolites were ≤85%. As far as we know, this is the first study proposing a combination of biomarkers of walnut exposure in a population under free-living conditions, as considered in epidemiological studies examining associations between diet and health outcomes.