J.P.M. van Duynhoven

Time-Domain NMR Applied to Food Products

Abstract Time-domain NMR is being used throughout all areas of food science and technology. A wide range of one- and two-dimensional relaxometric and diffusometric applications have been implemented on cost-effective, robust and easy-to-use benchtop NMR equipment. Time-domain NMR applications do not only cover research and development but also quality and process control in the food supply chain. Here the opportunity to further downsize and tailor equipment has allowed for “mobile” sensor applications as well as online quality inspection. The structural and compositional information produced by time-domain NMR experiments requires adequate data-analysis techniques. Here one can distinguish model-driven approaches for hypothesis testing, as well as explorative multi-variate approaches for hypothesis generation. Developments in hardware and software will further enhance measurement speed and reveal more detailed structural features in complex food systems.

Impact of Short-Term Intake of Red Wine and Grape Polyphenol Extract on the Human Metabolome

Red wine and grape polyphenols are considered to promote cardiovascular health and are involved in multiple biological functions. Their overall impact on the human metabolome is not known. Therefore, exogenous and endogenous metabolic effects were determined in fasting plasma and 24 h urine from healthy male adults consuming a mix of red wine and grape juice extracts (WGM) for 4 days in a placebo-controlled, crossover study. Syringic acid, 3-hydroxyhippuric acid, pyrogallol, 3-hydroxyphenylacetic acid, and 3-hydroxyphenylpropionic acid were confirmed as the strongest urinary markers of WGM intake. Overall, WGM had a mild impact on the endogenous metabolism. Most noticeable were changes in several amino acids deriving from tyrosine and tryptophan. Reductions in the microbial metabolites p-cresol sulfate and 3-indoxylsulfuric acid and increases in indole-3-lactic acid and nicotinic acid were observed in urine. In plasma, tyrosine was reduced. The results suggest that short-term intake of WGM altered microbial protein fermentation and/or amino acid metabolism.

Gender-dependent associations of metabolite profiles and body fat distribution in a healthy population with central obesity: towards metabolomics diagnostics

Obesity is a risk factor for cardiovascular diseases and type 2 diabetes especially when the fat is accumulated to central depots. Novel biomarkers are crucial to develop diagnostics for obesity and related metabolic disorders. We evaluated the associations between metabolite profiles (136 lipid components, 12 lipoprotein subclasses, 17 low-molecular-weight metabolites, 12 clinical markers) and 28 phenotype parameters (including different body fat distribution parameters such as android (A), gynoid (G), abdominal visceral (VAT), subcutaneous (SAT) fat) in 215 plasma/serum samples from healthy overweight men (n=32) and women (n=83) with central obesity. (Partial) correlation analysis and partial least squares (PLS) regression analysis showed that only specific metabolites were associated to A:G ratio, VAT, and SAT, respectively. These association patterns were gender dependent. For example, insulin, cholesterol, VLDL, and certain triacylglycerols (TG 54:1-3) correlated to VAT in women, while in men VAT was associated with TG 50:1-5, TG 55:1, phosphatidylcholine (PC 32:0), and VLDL ((X)L). Moreover, multiple regression analysis revealed that waist circumference and total fat were sufficient to predict VAT and SAT in women. In contrast, only VAT but not SAT could be predicted in men and only when plasma metabolites were included, with PC 32:0 being most strongly associated with VAT. These findings collectively highlight the potential of metabolomics in obesity and that gender differences need to be taken into account for novel biomarker and diagnostic discovery for obesity and metabolic disorders.

Comprehensive metabolomics to evaluate the impact of industrial processing on the phytochemical composition of vegetable purees

The effects of conventional industrial processing steps on global phytochemical composition of broccoli, tomato and carrot purees were investigated by using a range of complementary targeted and untargeted metabolomics approaches including LC-PDA for vitamins, (1)H NMR for polar metabolites, accurate mass LC-QTOF MS for semi-polar metabolites, LC-MRM for oxylipins, and headspace GC-MS for volatile compounds. An initial exploratory experiment indicated that the order of blending and thermal treatments had the highest impact on the phytochemicals in the purees. This blending-heating order effect was investigated in more depth by performing alternate blending-heating sequences in triplicate on the same batches of broccoli, tomato and carrot. For each vegetable and particularly in broccoli, a large proportion of the metabolites detected in the purees was significantly influenced by the blending-heating order, amongst which were potential health-related phytochemicals and flavour compounds like vitamins C and E, carotenoids, flavonoids, glucosinolates and oxylipins. Our metabolomics data indicates that during processing the activity of a series of endogenous plant enzymes, such as lipoxygenases, peroxidases and glycosidases, including myrosinase in broccoli, is key to the final metabolite composition and related quality of the purees.

A systematic approach to obtain validated Partial Least Square models for predicting lipoprotein subclasses from serum NMR spectra

A systematic approach is described for building validated PLS models that predict cholesterol and triglyceride concentrations in lipoprotein subclasses in fasting serum from a normolipidemic, healthy population. The PLS models were built on diffusion-edited (1)H NMR spectra and calibrated on HPLC-derived lipoprotein subclasses. The PLS models were validated using an independent test set. In addition to total VLDL, LDL, and HDL lipoproteins, statistically significant PLS models were obtained for 13 subclasses, including 5 VLDLs (particle size 64-31.3 nm), 4 LDLs (particle size 28.6-20.7 nm) and 4 HDLs (particle size 13.5-9.8 nm). The best models were obtained for triglycerides in VLDL (0.82 < Q(2) <0.92) and HDL (0.69 < Q(2) <0.79) subclasses and for cholesterol in HDL subclasses (0.68 < Q(2) <0.96). Larger variations in the model performance were observed for triglycerides in LDL subclasses and cholesterol in VLDL and LDL subclasses. The potential of the NMR-PLS model was assessed by comparing the LPD of 52 subjects before and after a 4-week treatment with dietary supplements that were hypothesized to change blood lipids. The supplements induced significant (p < 0.001) changes on multiple subclasses, all of which clearly exceeded the prediction errors.

Quantification of Complex Mixtures by NMR

Abstract NMR has firmly established itself as an analytical tool that can quantify analyte concentrations in complex mixtures in a rapid, cost-effective, accurate and precise manner. Here, the technological advances with respect to instrumentation, sample preparation, data acquisition and data processing over the past decade will be discussed. It will be shown that besides mainstream 1D 1H NMR also homo- and heteronuclear 2D experiments are gaining practical use. An overview will be given of the widespread applications of qNMR in diverse applications areas, ranging from foods, biomedicine to natural and pharmaceutical product analysis. Yet, qNMR is still limited to the quantification of a limited number of target compounds. Considering the current rate of developments in NMR acquisition and data processing, it is envisaged that in the near future a much wider range of analytes can be simultaneously assessed in a routine manner at even lower operational cost.

The effect of plant sterols and different low doses of omega-3 fatty acids from fish oil on lipoprotein subclasses

SCOPE Consumption of a low-fat spread enriched with plant sterols (PS) and different low doses (<2 g/day) of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) from fish oil reduces serum triglycerides (TGs) and low-density lipoprotein-cholesterol (LDL-Chol) and thus beneficially affects two blood lipid risk factors. Yet, their combined effects on TG and Chol in various lipoprotein subclasses have been investigated to a limited extent. METHODS AND RESULTS In a randomized, double-blind, placebo-controlled, parallel study, we determined TG and Chol in 13 LP subclasses in fasting serum of 282 hypercholesterolemic subjects, who consumed either a placebo spread or one of the four spreads containing PS (2.5 g/day) and EPA+DHA (0.0, 0.9, 1.3, and 1.8 g/day) for 4 weeks. After PS treatment, total LDL-Chol was reduced, which was not further changed by EPA+DHA. No shift in the LDL-Chol particle distribution was observed. The addition of EPA+DHA to PS dose-dependently reduced VLDL-Chol and VLDL-TG mainly in larger particles. Furthermore, the two highest doses of EPA+DHA increased Chol and TG in the larger HDL particles, while these concentrations were decreased in the smallest HDL particles. CONCLUSION The consumption of a low-fat spread enriched with both PS and EPA+DHA induced shifts in the lipoprotein distribution that may provide additional cardiovascular benefits over PS consumption alone.

Analyzing metabolomics-based challenge tests

Challenge tests are used to assess the resilience of human beings to perturbations by analyzing responses to detect functional abnormalities. Well known examples are allergy tests and glucose tolerance tests. Increasingly, metabolomics analysis of blood or serum samples is used to analyze the biological response of the individual to these challenges. The information content of such metabolomics challenge test data involves both the disturbance and restoration of homeostasis on a metabolic level and is thus inherently different from the analysis of steady state data. It opens doors to study the variation of resilience between individuals beyond the classical biomarkers; preferably in terms of underlying biological processes. We review challenge tests in which metabolomics was used to analyze the biological response. Specifically, we describe strategies to perform statistical analyses on the responses and we will show some examples of these strategies applied to a postprandial challenge that was used to study a diet with anti-inflammatory properties. Finally we discuss open issues and give recommendation for further research.

The Large Scale Identification and Quantification of Conjugates of Intact and Gut Microbial Bioconversion Products of Polyphenols

A human diet containing a significant amount of flavonoids, such as present in tea, red wine, apple, and cocoa has been associated with reduced disease risks. After consumption, a part of these flavonoids can be directly absorbed by the small intestine, but the greatest part passages towards the large intestine where microbes break the flavonoids down into phenolic metabolites. After absorption into the blood, both intact and metabolized flavonoids are subsequently methylated, sulphated, and glucuronidated or a combination thereof. The exact chemical structural elucidation and quantification of these conjugates present in the human body are key to identify potential bioactive components. However, this is still a tedious task due to their relative low abundance in a complex background of other high-abundant metabolites and the many possible isomeric forms. Therefore, we aimed to systematically identify these conjugates by using a combination of pre-concentration and separation by solid phase extraction (SPE) followed by LC-FTMSn and 1D 1H NMR. The combination of LC-FTMSn and HPLC-TOF-MS-SPE-NMR resulted in the efficient identification and quantification of low abundant polyphenol metabolites down to micromolar concentrations and thus opens up new perspectives for in depth studying of the bioavailability and the possible mode of action of flavonoids like flavan-3-ols and their gut-microbial break-down products circulating in the human body.

Quantitative NMR assessment of polysaccharides in complex food matrices

Polysaccharides are a critical component of many food stuffs owing to their stable rheological properties. Food polysaccharides show great structural diversity. These characteristics, together with strong matrix interactions, complicate the quantitative assessment of polysaccharides in complex product formulations. Most current analytical approaches rely on qualitative identification of polysaccharides and quantification based on monosaccharide analysis. NMR for example has typically been applied for qualitative purposes but recently progress has been made in semi-quantification. However employing this technique for the absolute quantitative assessment polysaccharides is less straightforward. This is primarily due to broadened and overlapping lineshapes, which compromise NMR signal integration. In this chapter the authors describe the hybrid NMR approach that they have developed in response to this problem for quantifying polysaccharides in food products. They demonstrate that through combining information on identified polysaccharides and monosaccharide composition it is possible to achieve absolute quantification of polysaccharides in full product formulations in the w/w% range with 10% precision.