Metabolic and functional interplay between gut microbiota and fat-soluble vitamins

Gut microbiota is a complex ecosystem seen as an extension of human genome. It represents a major metabolic interface of interaction with food components and xenobiotics in the gastrointestinal (GI) environment. In this context, the advent of modern bacterial genome sequencing technology has enabled the identification of dietary nutrients as key determinants of gut microbial ecosystem able to modulate the host-microbiome symbiotic relationship and its effects on human health. This article provides a literature review on functional and molecular interactions between a specific group of lipids and essential nutrients, e.g., fat-soluble vitamins (FSVs), and the gut microbiota. A two-way relationship appears to emerge from the available literature with important effects on human metabolism, nutrition, GI physiology and immune function. First, FSV directly or indirectly modify the microbial composition involving for example immune system-mediated and/or metabolic mechanisms of bacterial growth or inhibition. Second, the gut microbiota influences at different levels the synthesis, metabolism and transport of FSV including their bioactive metabolites that are either introduced with the diet or released in the gut via entero-hepatic circulation. A better understanding of these interactions, and of their impact on intestinal and metabolic homeostasis, will be pivotal to design new and more efficient strategies of disease prevention and therapy, and personalized nutrition

Metabolomic Applications to Decipher Gut Microbial Metabolic Influence in Health and Disease

Dietary preferences and nutrients composition have been shown to influence human and gut microbial metabolism, which ultimately has specific effects on health and diseases’ risk. Increasingly, results from molecular biology and microbiology demonstrate the key role of the gut microbiota metabolic interface to the overall mammalian host’s health status. There is therefore raising interest in nutrition research to characterize the molecular foundations of the gut microbial–mammalian cross talk at both physiological and biochemical pathway levels. Tackling these challenges can be achieved through systems biology approaches, such as metabolomics, to underpin the highly complex metabolic exchanges between diverse biological compartments, including organs, systemic biofluids, and microbial symbionts. By the development of specific biomarkers for prediction of health and disease, metabolomics is increasingly used in clinical applications as regard to disease etiology, diagnostic stratification, and potentially mechanism of action of therapeutical and nutraceutical solutions. Surprisingly, an increasing number of metabolomics investigations in pre-clinical and clinical studies based on proton nuclear magnetic resonance (1H NMR) spectroscopy and mass spectrometry provided compelling evidence that system wide and organ-specific biochemical processes are under the influence of gut microbial metabolism. This review aims at describing recent applications of metabolomics in clinical fields where main objective is to discern the biochemical mechanisms under the influence of the gut microbiota, with insight into gastrointestinal health and diseases diagnostics and improvement of homeostasis metabolic regulation

Nutritional Metabonomics: An Approach to Promote Personalized Health and Wellness

Nutritional research has emerged in the last century from the study of nutrients as a means of nourishment to the general population to the quest for wellness improvement through specific food components. Advances in nutrigenomics technologies have allowed nutrition scientists to be for the first time at the forefront of nutritional research. Such advances have given them the ability to discern new vital scientific discoveries specifically for the development of new tailored dietary patterns. In this, nutritional metabonomics has rapidly evolved into a very powerful bioanalytical tool able to assess multi-parametric metabolic responses of living organisms to specific dietary interventions. Nutritional metabonomics therefore provides a systematic approach through the comprehensive analysis of metabolites aiming today at the quest for homeostatic balance which is dependent not only on the host but also on the crucial metabolic interactions with microbial symbionts

Intraspecific chemical variability of the leaf essential oil of Juniperus phoenicea subsp. turbinata from Corsica

The composition of 50 samples of essential oil of individual plants of Juniperus phoenicea subsp. turbinata from Corsica was investigated by GC, GC-MS and 13C NMR. [alpha]-Pinene, [beta]-phellandrene, [alpha]-terpinyl acetate, [Delta]-3-carene, myrcene and [alpha]-phellandrene were found to be the main constituents. The results were submitted to cluster analysis and discriminant analysis which allowed two groups of essential oils to be distinguished with respect to the content of [alpha]-pinene, [beta]-phellandrene and [alpha]-terpinyl acetate.http://www.sciencedirect.com/science/article/B6T4R-41TMSRJ-8/1/9a99aea13c1425fdcac449056f51c71

Serum Ascorbic Acid and Thiamine Concentrations in Sepsis: Secondary Analysis of the Swiss Pediatric Sepsis Study.

OBJECTIVES To determine circulating levels of ascorbic acid (VitC) and thiamine (VitB1) in neonates and children with blood culture-proven sepsis. DESIGN Nested single-center study of neonates and children prospectively included in the Swiss Pediatric Sepsis Study. SETTING One tertiary care academic hospital. PATIENTS Sixty-one neonates and children 0-16 years old. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS VitC and VitB1 were quantified in serum of patients (median age, 10.5 mo; interquartile range [IQR], 0.5-62.1 mo) with blood culture-proven sepsis. Median time between sepsis onset and sampling for measurement of vitamins was 3 days (IQR, 2-4 d). Median serum levels of VitC and VitB1 were 32.4 μmol/L (18.9-53.3 μmol/L) and 22.5 nmol/L (12.6-82 nmol/L); 36% of the patients (22/61) had low VitC and 10% (6/61) had VitC deficiency; and 72% (44/61) had low VitB1 and 13% (8/61) had VitB1 deficiency. Children with low VitC were older (p = 0.007) and had higher C-reactive protein (p = 0.004) compared with children with VitC within the normal range. Children with low VitB1 levels were older (p = 0.0009) and were less frequently receiving enteral or parenteral vitamin supplementation (p = 0.0000003) compared with children with normal VitB1 levels. CONCLUSIONS In this cohort of newborns and children with sepsis, low and deficient VitC and VitB1 levels were frequently observed. Age, systemic inflammation, and vitamin supplementation were associated with vitamin levels during sepsis

Reproducibility and relative validity of a food-frequency questionnaire for French-speaking Swiss adults

Due to the distinct cultural and language differences that exist in Switzerland, there is little information on the dietary intake among the general Swiss population. Adequately assessing dietary intake is thus paramount if nutritional epidemiological studies are to be conducted. To assess the reproducibility and validity of a food-frequency questionnaire (FFQ) developed for French-speaking Swiss adults. A total of 23 men and 17 women (43.1±2.0 years) filled out one FFQ and completed one 24-hour dietary recall at baseline and 1 month afterward. Crude Pearson's correlation coefficients between the first and the second FFQ ranged from 0.58 to 0.90, intraclass correlation coefficient (ICC) ranged between 0.53 and 0.92. Lin's concordance coefficients ranged between 0.55 and 0.87. Over 80% of participants were classified in the same or adjacent tertile using each FFQ. Macronutrient intakes estimated by both FFQs were significantly higher than those estimated from the 24-hour recall for protein and water, while no significant differences were found for energy, carbohydrate, fats (five groups), and alcohol. De-attenuated Pearson's correlation coefficients between the 24-hour recall and the first FFQ ranged between 0.31 and 0.49, while for the second FFQ the values ranged between 0.38 and 0.59. Over 40 and 95% of participants fell into the same or the adjacent energy and nutrient tertiles, respectively, using the FFQs and the 24-hour recall. This FFQ shows good reproducibility and can be used determining macronutrient intake in a French-speaking Swiss population in an epidemiological setting

Monitoring Healthy Metabolic Trajectories with Nutritional Metabonomics

Metabonomics is a well established analytical approach for the analysis of physiological regulatory processes via the metabolic profiling of biofluids and tissues in living organisms. Its potential is fully exploited in the field of “nutrimetabonomics” that aims at assessing the metabolic effects of active ingredients and foods in individuals. Yet, one of the greatest challenges in nutrition research is to decipher the critical interactions between mammalian organisms and environmental factors, including the gut microbiota. “Nutrimetabonomics” is today foreseen as a powerful approach for future nutritional programs tailored at health maintenance and disease prevention

Differential effect of maternal diet supplementation with α-Linolenic adcid or n-3 long-chain polyunsaturated fatty acids on glial cell phosphatidylethanolamine and phosphatidylserine fatty acid profile in neonate rat brains

<p>Abstract</p> <p>Background</p> <p>Dietary long-chain polyunsaturated fatty acids (LC-PUFA) are of crucial importance for the development of neural tissues. The aim of this study was to evaluate the impact of a dietary supplementation in n-3 fatty acids in female rats during gestation and lactation on fatty acid pattern in brain glial cells phosphatidylethanolamine (PE) and phosphatidylserine (PS) in the neonates.</p> <p>Methods</p> <p>Sprague-Dawley rats were fed during the whole gestation and lactation period with a diet containing either docosahexaenoic acid (DHA, 0.55%) and eicosapentaenoic acid (EPA, 0.75% of total fatty acids) or α-linolenic acid (ALA, 2.90%). At two weeks of age, gastric content and brain glial cell PE and PS of rat neonates were analyzed for their fatty acid and dimethylacetal (DMA) profile. Data were analyzed by bivariate and multivariate statistics.</p> <p>Results</p> <p>In the neonates from the group fed with n-3 LC-PUFA, the DHA level in gastric content (+65%, P < 0.0001) and brain glial cell PE (+18%, P = 0.0001) and PS (+15%, P = 0.0009) were significantly increased compared to the ALA group. The filtered correlation analysis (P < 0.05) underlined that levels of dihomo-γ-linolenic acid (DGLA), DHA and n-3 docosapentaenoic acid (DPA) were negatively correlated with arachidonic acid (ARA) and n-6 DPA in PE of brain glial cells. No significant correlation between n-3 and n-6 LC-PUFA were found in the PS dataset. DMA level in PE was negatively correlated with n-6 DPA. DMA were found to occur in brain glial cell PS fraction; in this class DMA level was correlated negatively with DHA and positively with ARA.</p> <p>Conclusion</p> <p>The present study confirms that early supplementation of maternal diet with n-3 fatty acids supplied as LC-PUFA is more efficient in increasing n-3 in brain glial cell PE and PS in the neonate than ALA. Negative correlation between n-6 DPA, a conventional marker of DHA deficiency, and DMA in PE suggests n-6 DPA that potentially be considered as a marker of tissue ethanolamine plasmalogen status. The combination of multivariate and bivariate statistics allowed to underline that the accretion pattern of n-3 LC-PUFA in PE and PS differ.</p

Comparison of nutritional composition between plant-based drinks and cow’s milk

The high decline in liquid milk consumption in Western countries has been compensated by the increased consumption of processed dairyproducts and the rapidly increasing number of new plant-based beverages constantly introduced in the market, advertised as milk substitutes and placed on shelves near milk products. To provide better understanding about the nutritional value of these drinks compared with cow’s milk, 27 plant-based drinks of 8 different species and two milk samples were purchased from two big retailers in Switzerland, and their composition regarding protein, carbohydrate, fat, vitamin, and mineral contents and residue load [glyphosate, aminomethylphosphonic acid (AMPA), and arsenic] was analyzed quantitatively and qualitatively. Energy and nutrient intakes were calculated and compared with the dietary reference values for Germany, Austria and Switzerland (D-A-CH). In addition, the digestible indispensable amino acid score (DIAAS) was calculated to estimate the quality of the proteins. Milk contained more energy; fat; carbohydrate; vitamins C, B2, B12, and A; biotin; pantothenic acid; calcium; phosphorus; and iodine than most plant-based drinks. Soy drinks provided slightly more proteinand markedly more vitamins B1 and B6, folic acid, and vitamins E and D2 (with supplemented vitamin D2) and K1, magnesium, manganese, iron, and copper than milk and the other plant-based drinks. However, with the exception of cow’s milk and soy drinks, which had > 3% protein, most milk alternatives contained � 1% protein; therefore, they cannot be considered good protein sources. In regard to protein quality, milk was outstanding compared with all plant-based drinks and exhibited higher calculated DIAASs. Our results show that the analyzed plant-based drinks are not real alternatives to milk in terms of nutrient composition, even if the actual fortification is taken into account. Improved fortification is still an issue and can be optimized using the most bioavailable and soluble derivatives. Complete replacement of milk with plant-based drinks without adjusting the overall diet can lead to deficiencies of certain important nutrients in the long term

Application of Multivariate Analysis, Support Vector Machines and Artificial Neural Network to the Processing of Nuclear Magnetic Resonance data of olive oil and fish oil samples for classification of geographic origin and discrimination between wild and farm fish.

Motivations Traceability and control of origin of food products are very important for the Consumers and for the European enforcement laboratories. For instance, The high added value of olive oil makes its control an important goal for EU producers and consumers. There is thus a need in developing analytical methods to ensure compliance with labeling, i.e.the control of geographical origin giving also support to the denominated protected origin (DPO) policy, and the determination of the genuineness of the product by the detection of eventual adulterations. Futhermore , EU regulations requires that origin, wild or farmed as well as geographic origin, of fish sold on the retail market be available to the consumers. Modern analytical techniques such as Nuclear Magnetic Resonance (NMR) provide very informative data on the composition in fatty acids and in other constituents of vegetable oils and fish oils. The combination of 1H NMR fingerprinting with multivariate analysis provides an original approach to study the profile of these oils in relation with geographical origin of olive oil or for discrimination between wild or farm origin for fish like salmons. Methods Concerning the experiment on fish oil, we used Support vector machines (SVMs) as a novel learning machine in the authentication of the origin of salmon. SVMs have the advantage of relying on a well-developed theory and have already proved to be successful in a number of practical applications. The method requires a very simple sample preparation of the fish oils extracted from the white muscle of salmon samples. Multivariate (chemometric) techniques are able to filter out the most relevant information from a spectrum, e.g. for a classification. In the experiment on olive oil samples, the principal component analysis (PCA) was carried out on the ~12,000 variables (chemical shifts) and four data sets were defined prior to PCA. Linear discriminant analysis (LDA) of the first 50 PC\u2019s was applied for classification of olive oil samples according to the geographic origin and year of production. The data analysis has been carried out with and without outliers, as well. Variable selection for LDA was achieved using: (i) the best five variables and (ii) an interactive forward stepwise manner. Results The use of SVMs for the discrimination between wild and farm salmon provides a new and effective method that eliminates the possibility of fraud through misrepresentation of the country of origin of salmon. The SVM has been able to distinguish correctly between the wild and farmed salmon; however ca. 5% of the country of origins were misclassified. Using LDA on the external validation sets the correct classification of olive oil varied between 47 and 75% (random selection), and between 35 and 92% (Kennard\u2013Stone selection (KS)) depending on geographic origin (country) and production years. A similar success rate could be achieved using partial least squares discriminant analysis (PLS DA). The success rate can be considerably improved by using probabilistic neural networks (PNN). Correct classification by PNN varied between 58 and 100% on the external validation sets. Other chemometric techniques, such as multiple linear regression, or generalized pair-wise correlation, did not give better results. Acknowledgements The authors are grateful to the Europeanproject COFAWS (European Commission DG RTD FP5 project GRD2\u20132000\u201331813) and to all the collaborators from the partners of this project (Eurofins Scientific (Nantes- France), North Atlantic Fisheries College (Scalloway, Shetland Islands - United Kingdom), SINTEF Fisheries and Aquaculture (Trondheim-Norway), Joint Research Centre (Ispra-Italy)) who contributed to the collection and preparation of fish samples, and for the authorization to exploit their NMR data in this work