Scoary2: rapid association of phenotypic multi-omics data with microbial pan-genomes.

Unraveling bacterial gene function drives progress in various areas, such as food production, pharmacology, and ecology. While omics technologies capture high-dimensional phenotypic data, linking them to genomic data is challenging, leaving 40-60% of bacterial genes undescribed. To address this bottleneck, we introduce Scoary2, an ultra-fast microbial genome-wide association studies (mGWAS) software. With its data exploration app and improved performance, Scoary2 is the first tool to enable the study of large phenotypic datasets using mGWAS. As proof of concept, we explore the metabolome of yogurts, each produced with a different Propionibacterium reichii strain and discover two genes affecting carnitine metabolism.

Age-Dependent Serum Volatilomics of Milk and Yogurt Intake: A Randomized Crossover Study in Healthy Young and Older Men.

Nutritional biomarkers of dairy intake can be affected by both food transformation and the metabolic status of the consumer. To assess these effects, this study investigated the serum volatilome of 14 young (YA) and 14 older (OA) adult men undergoing a 3 week restriction of dairy and fermented foods followed by a randomized crossover acute intake of milk and yogurt. 3,5-Dimethyl-octan-2-one was identified as a potential marker of dairy product intake as its response after both milk and yogurt intake was significantly increased during the postprandial phase but significantly decreased in fasting serum samples of the OA group after the restriction phase. The postprandial response of two metabolites was significantly different for the two dairy products while 19 metabolites were modulated by age. Remarkably, the response of all age-dependent metabolites was higher in the OA than in the YA group after milk or yogurt intake, whereas at the end of the restriction phase, their fasting concentrations were lower in the OA than in the YA group. Among these, p-cresol, a specific marker of colonic protein fermentation, had a significant response in the OA but not the YA group, which may suggest impaired intestinal processing of dietary proteins in the OA group.

Identifying Plasma and Urinary Biomarkers of Fermented Food Intake and Their Associations with Cardiometabolic Health in a Dutch Observational Cohort.

Identification of food intake biomarkers (FIBs) for fermented foods could help improve their dietary assessment and clarify their associations with cardiometabolic health. We aimed to identify novel FIBs for fermented foods in the plasma and urine metabolomes of 246 free-living Dutch adults using nontargeted LC-MS and GC-MS. Furthermore, associations between identified metabolites and several cardiometabolic risk factors were explored. In total, 37 metabolites were identified corresponding to the intakes of coffee, wine, and beer (none were identified for cocoa, bread, cheese, or yoghurt intake). While some of these metabolites appeared to originate from raw food (e.g., niacin and trigonelline for coffee), others overlapped different fermented foods (e.g., 4-hydroxybenzeneacetic acid for both wine and beer). In addition, several fermentation-dependent metabolites were identified (erythritol and citramalate). Associations between these identified metabolites with cardiometabolic parameters were weak and inconclusive. Further evaluation is warranted to confirm their relationships with cardiometabolic disease risk.

Analysis of volatile short-chain fatty acids in the gas phase using secondary electrospray ionization coupled to mass spectrometry.

Quantification of metabolites present within exhaled breath is a major challenge for on-line breath analysis. It is also important for gauging the analytical performance, accuracy, reproducibility, reliability, and stability of the measuring technology. Short-chain fatty acids (SCFAs) are of high interest for nutrition and health. Their quantification enables a deep mechanistic understanding of a wide range of biological processes and metabolic pathways, while their high volatility makes them an attractive target for breath analysis. This article reports, for the first time, the development and testing of a modular, dynamic vapor generator for the qualitative and quantitative analysis of volatile SCFAs in the gaseous phase using a secondary electrospray ionization (SESI) source coupled to a high-resolution mass spectrometer. Representative compounds tested included acetic acid, propionic acid, butyric acid, pentanoic acid and hexanoic acid. Gas-phase experiments were performed both in dry and humid (95% relative humidity) conditions from ppt to low ppb concentrations. The results obtained exhibited excellent linearity within the examined concentration range, low limits of detection and quantification down to the lower ppt area. Mixture effects were also investigated and are presented.

Associations between dairy fat intake, milk-derived free fatty acids, and cardiometabolic risk in Dutch adults.

PURPOSE: Milk-derived free fatty acids (FFAs) may act as both biomarkers of intake and metabolic effect. In this study we explored associations between different types of dairy consumption, a selection of milk-derived free fatty acids, and cardiometabolic disease (CMD) risk factors. METHODS: Sixty-seven FFAs were quantified in the plasma of 131 free-living Dutch adults (median 60 years) using gas chromatography-flame ionization detector. Intakes of different dairy foods and groups were assessed using a food frequency questionnaire. Twelve different CMD risk factors were analyzed. Multiple linear regressions were used to evaluate the associations under study. RESULTS: Based on the fully adjusted models, 5 long-chain unsaturated FFAs (C18:1 t13 + c6 + c7 + u, C18:2 c9t11 + u, C20:1 c11, C20:3 c8c11c14, and C20:4 c5c8c11c14), 2 medium-chain saturated FFAs (C15, C15 iso), and a trans FFA (C16:1 t9) were positively associated with at least one variable of dairy intake, as well as plasma total and LDL cholesterol, blood pressure, and SCORE (p ≤ 0.05). A long-chain PUFA associated with high-fat fermented dairy intake (C18:2 t9t12), was negatively associated with serum triglyceride levels, and a long-chain saturated FFA associated with cheese intake (C18:1 u1) was negatively associated with plasma LDL cholesterol and serum triglyceride levels. No clear associations were observed between dairy intake and CMD risk factors. CONCLUSION: Milk-derived FFAs could act as sensitive biomarkers for dairy intake and metabolism, allowing the association between dairy and CMD risk to be more precisely evaluated.

Serum and Urine Metabolites in Healthy Men after Consumption of Acidified Milk and Yogurt.

The identification of molecular biomarkers that can be used to quantitatively link dietary intake to phenotypic traits in humans is a key theme in modern nutritional research. Although dairy products (with and without fermentation) represent a major food group, the identification of markers of their intake lags behind that of other food groups. Here, we report the results from an analysis of the metabolites in postprandial serum and urine samples from a randomized crossover study with 14 healthy men who ingested acidified milk, yogurt, and a non-dairy meal. Our study confirms the potential of lactose and its metabolites as markers of lactose-containing dairy foods and the dependence of their combined profiles on the fermentation status of the consumed products. Furthermore, indole-3-lactic acid and 3-phenyllactic acid are two products of fermentation whose postprandial behaviour strongly discriminates yogurt from milk intake. Our study also provides evidence of the ability of milk fermentation to increase the acute delivery of free amino acids to humans. Notably, 3,5-dimethyloctan-2-one also proves to be a specific marker for milk and yogurt consumption, as well as for cheese consumption (previously published data). These molecules deserve future characterisation in human interventional and observational studies.

Fermented foods and cardiometabolic health: Definitions, current evidence, and future perspectives.

Unhealthy diets contribute to the increasing burden of non-communicable diseases. Annually, over 11 million deaths worldwide are attributed to dietary risk factors, with the vast majority of deaths resulting from cardiometabolic diseases (CMDs) including cardiovascular disease (∼10 million) and type II diabetes (∼339,000). As such, defining diets and dietary patterns that mitigate CMD risk is of great public health importance. Recently, the consumption of fermented foods has emerged as an important dietary strategy for improving cardiometabolic health. Fermented foods have been present in the human diet for over 10,000 years, but knowledge on whether their consumption benefits human health, and the molecular and microbiological mechanisms underpinning their purported health benefits, is relatively nascent. This review provides an overview of the definitions of fermented foods, types and qualities of fermented foods consumed in Europe and globally, possible mechanisms between the consumption of fermented foods and cardiometabolic health, as well as the current state of the epidemiological evidence on fermented food intake and cardiometabolic health. Finally, we outline future perspectives and opportunities for improving the role of fermented foods in human diets.

Molecular effects of the consumption of margarine and butter varying in trans fat composition: a parallel human intervention study.

BACKGROUND: Whereas the dietary intake of industrial trans fatty acids (iTFA) has been specifically associated with inflammation, cardiovascular disease, and type 2 diabetes, understanding the impact of dietary fats on human health remains challenging owing to their complex composition and individual effects of their lipid components on metabolism. The aim of this study is to profile the composition of blood, measured by the fatty acid (FAs) profile and untargeted metabolome of serum and the transcriptome of blood cells, in order to identify molecular signatures that discriminate dietary fat intakes. METHODS: In a parallel study, the molecular effects of consuming dairy fat containing ruminant TFA (rTFA) or margarine containing iTFA were investigated. Healthy volunteers (n = 42; 45-69 y) were randomly assigned to diets containing margarine without TFA as major source of fat (wTFA control group with 0.4 g TFA per 100 g margarine), margarine with iTFA (iTFA group with 4.1 g TFA per 100 g margarine), or butter with rTFA (rTFA group with 6.3 g TFA per 100 g butter) for 4 weeks. The amounts of test products were individually selected so that fat intake contributed to 30-33% of energy requirements and TFA in the rTFA and iTFA groups contributed to up to 2% of energy intake. Changes in fasting blood values of lipid profiles (GC with flame-ionization detection), metabolome profiles (LC-MS, GC-MS), and gene expression (microarray) were measured. RESULTS: Eighteen FAs, as well as 242 additional features measured by LC-MS (185) and GC-MS (54) showed significantly different responses to the diets (PFDR-adjusted < 0.05), mainly distinguishing butter from the margarine diets while gene expression was not differentially affected. The most abundant TFA in the butter, i.e. TFA containing (E)-octadec-11-enoic acid (C18:1 t11; trans vaccenic acid), and margarines, i.e. TFA containing (E)-octadec-9-enoic acid (C18:1 t9; elaidic acid) were reflected in the significantly different serum levels of TFAs measured after the dietary interventions. CONCLUSIONS: The untargeted serum metabolome differentiates margarine from butter intake although the identification of the discriminating features remains a bottleneck. The targeted serum FA profile provides detailed information on specific molecules differentiating not only butter from margarine intake but also diets with different content of iTFAs in margarine. TRIAL REGISTRATION: ClinicalTrials.gov NCT00933322.

Breath response following a nutritional challenge monitored by secondary electrospray ionization high-resolution mass spectrometry.

On-line breath analysis using secondary electrospray ionization coupled to high-resolution mass spectrometry (SESI-HRMS) is a sensitive method for biomarker discovery. The strengths of this technology have already been demonstrated in the clinical environment. For the first time, this study demonstrates the application of SESI-HRMS in the field of nutritional science using a standardized nutritional intervention, consisting of a high-energy shake (950 kcal, 8% protein, 35% sugar and 57% fat). Eleven subjects underwent the intervention on three separate days and their exhaled breath was monitored up to six hours postprandially. In addition, sampling was performed during equivalent fasting conditions for selected subjects. To estimate the impact of inter- and intra-individual variability, analysis of variance simultaneous component analysis was conducted, revealing that the inter-individual variability accounted for 30% of the data variation. To distinguish the effect of the intervention from fasting conditions, partial least squares discriminant analysis was performed. Candidate compound annotation was performed with pathway analysis and collision-induced dissociation (CID) experiments. Pathway analysis highlighted, among others, features associated with the metabolism of linoleate, butanoate and amino sugars. Tentative compounds annotated through CID measurements include fatty acids, amino acids, and amino acid derivatives, some of them likely derived from nutrients by the gut microbiome (e.g. propanoate, indoles), as well as organic acids from the Krebs cycle. Time-series clustering showed an overlap of observed kinetic trends with those reported previously in blood plasma.

Postprandial Responses on Serum Metabolome to Milk and Yogurt Intake in Young and Older Men.

The identification and validation of biomarkers of food intake (BFIs) is a promising approach to develop more objective and complementary tools to the traditional dietary assessment methods. Concerning dairy, their evaluation in terms of intake is not simple, given the variety of existing foods, making it difficult to establish the association between specific dairy products consumption and the effects on human health, which is also dependent on the study population. Here, we aimed at identifying BFI of both milk (M) and yogurt (Y) in 14 healthy young (20-35 years) and 14 older (65-80 years). After a 3-week run-in period of dairy exclusion from the diet, the subjects acutely consumed 600 ml of M or Y. Metabolomics analyses were conducted on serum samples during the following 6 h (LC-MS and GC-MS). Several metabolites showing increased iAUC after milk or yogurt intake were considered as potential BFI, including lactose (M > Y, 2-fold), galactitol (M > Y, 1.5-fold), galactonate (M > Y, 1.2-fold), sphingosine-1-phosphate (M > Y from 2.1-fold), as well as an annotated disaccharide (Y > M, 3.6-fold). Delayed serum kinetics were also observed after Y compared to M intake lysine (+22 min), phenylalanine (+45 min), tyrosine (+30min), threonine (+38 min) 3-phenyllactic acid (+30 min), lactose (+30 min), galactitol (+45min) and galactonate (+30 min). The statistical significance of certain discriminant metabolites, such as sphingosine-1-phosphate and several free fatty acids, was not maintained in the older group. This could be related to the physiological modifications induced by aging, like dysregulated lipid metabolism, including delayed appearance of dodecanoic acid (+60 min) or altered postprandial appearance of myristic acid (+70% Cmax), 3-dehydroxycarnitine (-26% Cmin), decanoylcarnitine (-51% Cmin) and dodecanoylcarnitine (-40% Cmin). In conclusion, candidate BFI of milk or yogurt could be identified based on the modified postprandial response resulting from the fermentation of milk to yogurt. Moreover, population specificities (e.g., aging) should also be considered in future studies to obtain more accurate and specific BFI.

Evaluating the Robustness of Biomarkers of Dairy Food Intake in a Free-Living Population Using Single- and Multi-Marker Approaches.

Studies examining associations between self-reported dairy intake and health are inconclusive, but biomarkers hold promise for elucidating such relationships by offering objective measures of dietary intake. Previous human intervention studies identified several biomarkers for dairy foods in blood and urine using non-targeted metabolomics. We evaluated the robustness of these biomarkers in a free-living cohort in the Netherlands using both single- and multi-marker approaches. Plasma and urine from 246 participants (54 ± 13 years) who completed a food frequency questionnaire were analyzed using liquid and gas chromatography-mass spectrometry. The targeted metabolite panel included 37 previously-identified candidate biomarkers of milk, cheese, and/or yoghurt consumption. Associations between biomarkers and energy-adjusted dairy food intakes were assessed by a 'single-marker' generalized linear model, and stepwise regression was used to select the best 'multi-marker' panel. Multi-marker models that also accounted for common covariates better captured the subtle differences for milk (urinary galactose, galactitol; sex, body mass index, age) and cheese (plasma pentadecanoic acid, isoleucine, glutamic acid) over single-marker models. No significant associations were observed for yogurt. Further examination of other facets of validity of these biomarkers may improve estimates of dairy food intake in conjunction with self-reported methods, and help reach a clearer consensus on their health impacts.

Serum Metabolites Responding in a Dose-Dependent Manner to the Intake of a High-Fat Meal in Normal Weight Healthy Men Are Associated with Obesity.

Although the composition of the human blood metabolome is influenced both by the health status of the organism and its dietary behavior, the interaction between these two factors has been poorly characterized. This study makes use of a previously published randomized controlled crossover acute intervention to investigate whether the blood metabolome of 15 healthy normal weight (NW) and 17 obese (OB) men having ingested three doses (500, 1000, 1500 kcal) of a high-fat (HF) meal can be used to identify metabolites differentiating these two groups. Among the 1024 features showing a postprandial response, measured between 0 h and 6 h, in the NW group, 135 were dose-dependent. Among these 135 features, 52 had fasting values that were significantly different between NW and OB men, and, strikingly, they were all significantly higher in OB men. A subset of the 52 features was identified as amino acids (e.g., branched-chain amino acids) and amino acid derivatives. As the fasting concentration of most of these metabolites has already been associated with metabolic dysfunction, we propose that challenging normal weight healthy subjects with increasing caloric doses of test meals might allow for the identification of new fasting markers associated with obesity.

Microbiota and Metabolite Modifications after Dietary Exclusion of Dairy Products and Reduced Consumption of Fermented Food in Young and Older Men.

The gut microbiota adapts to age-related changes in host physiology but is also affected by environmental stimuli, like diet. As a source of both pre- and probiotics, dairy and fermented foods modulate the gut microbiota composition, which makes them interesting food groups to use for the investigation of interactions between diet and ageing. Here we present the effects of excluding dairy products and limiting fermented food consumption for 19 days on gut microbiota composition and circulating metabolites of 28 healthy, young (YA) and older (OA) adult men. The intervention affected gut microbial composition in both groups, with significant increases in Akkermansia muciniphila and decreases in bacteria of the Clostridiales order. Lower fasting levels of glucose and insulin, as well as dairy-associated metabolites like lactose and pentadecanoic acid, were observed after the intervention, with no effect of age. The intervention also decreased HDL and LDL cholesterol levels. Dairy fat intake was positively associated with the HDL cholesterol changes but not with the LDL/HDL ratio. In conclusion, restricting the intake of dairy and fermented foods in men modified their gut microbiota and blood metabolites, while the impact of the dietary restrictions on these outcomes was more marked than the effect of age.

Development of Personalized Nutrition: Applications in Lactose Intolerance Diagnosis and Management.

Recent discoveries in the "omics" field and the growing focus on preventive health have opened new avenues for personalized nutrition (PN), which is becoming an important theme in the strategic plans of organizations that are active in healthcare, food, and nutrition research. PN holds great potential for individual health optimization, disease management, public health interventions, and product innovation. However, there are still multiple challenges to overcome before PN can be truly embraced by the public and healthcare stakeholders. The diagnosis and management of lactose intolerance (LI), a common condition with a strong inter-individual component, is explored as an interesting example for the potential role of these technologies and the challenges of PN. From the development of genetic and metabolomic LI diagnostic tests that can be carried out in the home, to advances in the understanding of LI pathology and individualized treatment optimization, PN in LI care has shown substantial progress. However, there are still many research gaps to address, including the understanding of epigenetic regulation of lactase expression and how lactose is metabolized by the gut microbiota, in order to achieve better LI detection and effective therapeutic interventions to reverse the potential health consequences of LI.

A systematic review to identify biomarkers of intake for fermented food products.

BACKGROUND: Fermented foods are ubiquitous in human diets and often lauded for their sensory, nutritious, and health-promoting qualities. However, precise associations between the intake of fermented foods and health have not been well-established. This is in part due to the limitations of current dietary assessment tools that rely on subjective reporting, making them prone to memory-related errors and reporting bias. The identification of food intake biomarkers (FIBs) bypasses this challenge by providing an objective measure of intake. Despite numerous studies reporting on FIBs for various types of fermented foods and drinks, unique biomarkers associated with the fermentation process ("fermentation-dependent" biomarkers) have not been well documented. We therefore conducted a comprehensive, systematic review of the literature to identify biomarkers of fermented foods commonly consumed in diets across the world. RESULTS: After title, abstract, and full-text screening, extraction of data from 301 articles resulted in an extensive list of compounds that were detected in human biofluids following the consumption of various fermented foods, with the majority of articles focusing on coffee (69), wine (69 articles), cocoa (62), beer (34), and bread (29). The identified compounds from all included papers were consolidated and sorted into FIBs proposed for a specific food, for a food group, or for the fermentation process. Alongside food-specific markers (e.g., trigonelline for coffee), and food-group markers (e.g., pentadecanoic acid for dairy intake), several fermentation-dependent markers were revealed. These comprised compounds related to the fermentation process of a particular food, such as mannitol (wine), 2-ethylmalate (beer), methionine (sourdough bread, cheese), theabrownins (tea), and gallic acid (tea, wine), while others were indicative of more general fermentation processes (e.g., ethanol from alcoholic fermentation, 3-phenyllactic acid from lactic fermentation). CONCLUSIONS: Fermented foods comprise a heterogeneous group of foods. While many of the candidate FIBs identified were found to be non-specific, greater specificity may be observed when considering a combination of compounds identified for individual fermented foods, food groups, and from fermentation processes. Future studies that focus on how fermentation impacts the composition and nutritional quality of food substrates could help to identify novel biomarkers of fermented food intake.

Discriminating Dietary Responses by Combining Transcriptomics and Metabolomics Data in Nutrition Intervention Studies.

SCOPE: Combining different "omics" data types in a single, integrated analysis may better characterize the effects of diet on human health. METHODS AND RESULTS: The performance of two data integration tools, similarity network fusion tool (SNFtool) and Data Integration Analysis for Biomarker discovery using Latent variable approaches for "Omics" (DIABLO; MixOmics), in discriminating responses to diet and metabolic phenotypes is investigated by combining transcriptomics and metabolomics datasets from three human intervention studies: a postprandial crossover study testing dairy foods (n = 7; study 1), a postprandial challenge study comparing obese and non-obese subjects (n = 13; study 2); and an 8-week parallel intervention study that assessed three diets with variable lipid content on fasting parameters (n = 39; study 3). In study 1, combining datasets using SNF or DIABLO significantly improve sample classification. For studies 2 and 3, the value of SNF integration depends on the dietary groups being compared, while DIABLO discriminates samples well but does not perform better than transcriptomic data alone. CONCLUSION: The integration of associated "omics" datasets can help clarify the subtle signals observed in nutritional interventions. The performance of each integration tool is differently influenced by study design, size of the datasets, and sample size.

Prevalence of fermented foods in the Dutch adult diet and validation of a food frequency questionnaire for estimating their intake in the NQplus cohort.

BACKGROUND: Humans have a long history of consuming fermented foods. However, their prevalence in human diets remains largely undetermined, and there is a lack of validated dietary assessment tools assessing the intake of different fermented products. This study aimed to identify fermented foods consumed in The Netherlands and determine the relative validity of a food frequency questionnaire (FFQ) compared to multiple 24-h recalls for estimating their intake. METHODS: The validation population consisted of 809 participants (53.1 ± 11.9 years) from a Dutch observational cohort (NQplus) who completed a FFQ and multiple 24-h recalls. Fermented foods from the FFQ and recalls were identified and aggregated into conventional food groups. Percent difference in mean intakes, quintile cross-classification, Spearman's correlations, and Bland-Altman analyses were used to evaluate the agreement between the two dietary assessment methods. RESULTS: Approximately 16-18% of foods consumed by this population were fermented, and a further 9-14% were dishes containing a fermented ingredient. Fermented foods with the highest consumption included coffee (~ 453 g/day;~ 0.5% of daily energy intake), yoghurts (~ 88 g/day;~ 2.2%), beer (~ 84 g/day;~ 1.7%), wholegrain bread (~ 81 g/day;~ 9.4%), wine (~ 65 g/day;~ 2.7%), and cheese (~ 32 g/day;~ 5.0%). Mean percent difference between the FFQ and recalls was small for fermented beverages (coffee), breads (brown, white, wholegrain, rye), and fermented dairy (cheeses) (0.3-2.8%), but large for buttermilk and quark (≥53%). All fermented food groups had > 50% of participants classified into the same or adjacent quintile of intake (58%-buttermilk to 89%-fermented beverages). Strong Spearman's correlations (crude/energy-adjusted rs ≥ 0.50) were obtained for fermented beverages (coffee, beer, wine), cereals/grains (wholegrain bread), and dairy (yoghurts). For 'other bread', quark, and buttermilk, correlations were low (rs < 0.20). Bland-Altman analyses revealed good agreement for fermented beverages (coffee, beer), breads (brown, wholegrain, rye, other), pastries, chocolate, and fermented dairy (cheeses) (mean difference: 0.1-9.3). CONCLUSIONS: Fermented food groups with acceptable or good validity across all measures included commonly consumed foods in The Netherlands: fermented beverages (coffee), wholegrain and rye bread, and fermented dairy (cheeses). However, for less frequently consumed foods, such as quark and buttermilk, the levels of agreement were poor and estimates of intake should be interpreted with caution. This report provides the basis for developing a FFQ specific for fermented foods.

Nutrivolatilomics of Urinary and Plasma Samples to Identify Candidate Biomarkers after Cheese, Milk, and Soy-Based Drink Intake in Healthy Humans.

The characterization of volatile compounds in biological fluids offers a distinct approach to study the metabolic imprint of foods on the human metabolome, particularly to identify novel biomarkers of food intake (BFIs) that are not captured by classic metabolomics. Using a combination of dynamic headspace vacuum transfer In Trap extraction and gas chromatography coupled with mass spectrometry, we measured volatile compounds (the "volatilome") in plasma and urine samples from a randomized controlled crossover intervention study in which 11 healthy subjects ingested milk, cheese, or a soy-based drink. More than 2000 volatile compounds were detected in plasma, while 1260 compounds were detected in urine samples. A postprandial response in plasma was confirmed for 697 features. Univariate and multivariate analyses identified four molecules in plasma and 31 molecules in urine samples differentiating the ingestion of the foods, of which three metabolites in plasma and nine in urine were specific to the dairy products. Among these molecules, heptan-2-one, 3,5-dimethyloctan-2-one, and undecan-2-one in plasma and 3-ethylphenol, heptan-2-one, 1-methoxy-2-propyl acetate, and 9-decenoic acid were highly discriminative for dairy or cheese intake. In urine, 22 volatile compounds were highly discriminative for soy-based drink intake. The majority of these molecules have not been reported in humans. Our findings highlight the potential of plasma and urinary volatilomics for detection of novel dietary biomarkers.

In Silico Comparison Shows that the Pan-Genome of a Dairy-Related Bacterial Culture Collection Covers Most Reactions Annotated to Human Microbiomes.

The diversity of the human microbiome is positively associated with human health. However, this diversity is endangered by Westernized dietary patterns that are characterized by a decreased nutrient variety. Diversity might potentially be improved by promoting dietary patterns rich in microbial strains. Various collections of bacterial cultures resulting from a century of dairy research are readily available worldwide, and could be exploited to contribute towards this end. We have conducted a functional in silico analysis of the metagenome of 24 strains, each representing one of the species in a bacterial culture collection composed of 626 sequenced strains, and compared the pathways potentially covered by this metagenome to the intestinal metagenome of four healthy, although overweight, humans. Remarkably, the pan-genome of the 24 strains covers 89% of the human gut microbiome's annotated enzymatic reactions. Furthermore, the dairy microbial collection covers biological pathways, such as methylglyoxal degradation, sulfate reduction, g-aminobutyric (GABA) acid degradation and salicylate degradation, which are differently covered among the four subjects and are involved in a range of cardiometabolic, intestinal, and neurological disorders. We conclude that microbial culture collections derived from dairy research have the genomic potential to complement and restore functional redundancy in human microbiomes.

Identification of Milk and Cheese Intake Biomarkers in Healthy Adults Reveals High Interindividual Variability of Lewis System-Related Oligosaccharides.

BACKGROUND: The use of biomarkers of food intake (BFIs) in blood and urine has shown great promise for assessing dietary intake and complementing traditional dietary assessment tools whose use is prone to misreporting. OBJECTIVE: Untargeted LC-MS metabolomics was applied to identify candidate BFIs for assessing the intake of milk and cheese and to explore the metabolic response to the ingestion of these foods. METHODS: A randomized controlled crossover study was conducted in healthy adults [5 women, 6 men; age: 23.6 ± 5.0 y; BMI (kg/m2): 22.1 ± 1.7].  After a single isocaloric intake of milk (600 mL), cheese (100 g), or soy-based drink (600 mL), serum and urine samples were collected postprandially up to 6 h and after fasting after 24 h. Untargeted metabolomics was conducted using LC-MS. Discriminant metabolites were selected in serum by multivariate statistical analysis, and their mass distribution and postprandial kinetics were compared. RESULTS: Serum metabolites discriminant for cheese intake had a significantly lower mass distribution than metabolites characterizing milk intake (P = 4.1 × 10-4). Candidate BFIs for milk or cheese included saccharides, a hydroxy acid, amino acids, amino acid derivatives, and dipeptides. Two serum oligosaccharides, blood group H disaccharide (BGH) and Lewis A trisaccharide (LeA), specifically reflected milk intake but with high interindividual variability. The 2 oligosaccharides showed related but opposing trends: subjects showing an increase in either oligosaccharide did not show any increase in the other oligosaccharide. This result was confirmed in urine. CONCLUSIONS: New candidate BFIs for milk or cheese could be identified in healthy adults, most of which were related to protein metabolism. The increase in serum of LeA and BGH after cow-milk intake in adults calls for further investigations considering the beneficial health effects on newborns of such oligosaccharides in maternal milk. The trial is registered at clinicaltrials.gov as NCT02705560.