Assessing Adherence to Healthy Dietary Habits Through the Urinary Food Metabolome: Results From a European Two-Center Study.

Background: Diet is one of the most important modifiable lifestyle factors in human health and in chronic disease prevention. Thus, accurate dietary assessment is essential for reliably evaluating adherence to healthy habits. Objectives: The aim of this study was to identify urinary metabolites that could serve as robust biomarkers of diet quality, as assessed through the Alternative Healthy Eating Index (AHEI-2010). Design: We set up two-center samples of 160 healthy volunteers, aged between 25 and 50, living as a couple or family, with repeated urine sampling and dietary assessment at baseline, and 6 and 12 months over a year. Urine samples were subjected to large-scale metabolomics analysis for comprehensive quantitative characterization of the food-related metabolome. Then, lasso regularized regression analysis and limma univariate analysis were applied to identify those metabolites associated with the AHEI-2010, and to investigate the reproducibility of these associations over time. Results: Several polyphenol microbial metabolites were found to be positively associated with the AHEI-2010 score; urinary enterolactone glucuronide showed a reproducible association at the three study time points [false discovery rate (FDR): 0.016, 0.014, 0.016]. Furthermore, other associations were found between the AHEI-2010 and various metabolites related to the intake of coffee, red meat and fish, whereas other polyphenol phase II metabolites were associated with higher AHEI-2010 scores at one of the three time points investigated (FDR < 0.05 or ß ≠ 0). Conclusion: We have demonstrated that urinary metabolites, and particularly microbiota-derived metabolites, could serve as reliable indicators of adherence to healthy dietary habits. Clinical Trail Registration: www.ClinicalTrials.gov, Identifier: NCT03169088.

Challenges Associated With the Design and Deployment of Food Intake Urine Biomarker Technology for Assessment of Habitual Diet in Free-Living Individuals and Populations-A Perspective.

Improvement of diet at the population level is a cornerstone of national and international strategies for reducing chronic disease burden. A critical challenge in generating robust data on habitual dietary intake is accurate exposure assessment. Self-reporting instruments (e.g., food frequency questionnaires, dietary recall) are subject to reporting bias and serving size perceptions, while weighed dietary assessments are unfeasible in large-scale studies. However, secondary metabolites derived from individual foods/food groups and present in urine provide an opportunity to develop potential biomarkers of food intake (BFIs). Habitual dietary intake assessment in population surveys using biomarkers presents several challenges, including the need to develop affordable biofluid collection methods, acceptable to participants that allow collection of informative samples. Monitoring diet comprehensively using biomarkers requires analytical methods to quantify the structurally diverse mixture of target biomarkers, at a range of concentrations within urine. The present article provides a perspective on the challenges associated with the development of urine biomarker technology for monitoring diet exposure in free-living individuals with a view to its future deployment in "real world" situations. An observational study (n = 95), as part of a national survey on eating habits, provided an opportunity to explore biomarker measurement in a free-living population. In a second food intervention study (n = 15), individuals consumed a wide range of foods as a series of menus designed specifically to achieve exposure reflecting a diversity of foods commonly consumed in the UK, emulating normal eating patterns. First Morning Void urines were shown to be suitable samples for biomarker measurement. Triple quadrupole mass spectrometry, coupled with liquid chromatography, was used to assess simultaneously the behavior of a panel of 54 potential BFIs. This panel of chemically diverse biomarkers, reporting intake of a wide range of commonly-consumed foods, can be extended successfully as new biomarker leads are discovered. Towards validation, we demonstrate excellent discrimination of eating patterns and quantitative relationships between biomarker concentrations in urine and the intake of several foods. In conclusion, we believe that the integration of information from BFI technology and dietary self-reporting tools will expedite research on the complex interactions between dietary choices and health.

Design and Characterisation of a Randomized Food Intervention That Mimics Exposure to a Typical UK Diet to Provide Urine Samples for Identification and Validation of Metabolite Biomarkers of Food Intake.

Poor dietary choices are major risk factors for obesity and non-communicable diseases, which places an increasing burden on healthcare systems worldwide. To monitor the effectiveness of healthy eating guidelines and strategies, there is a need for objective measures of dietary intake in community settings. Metabolites derived from specific foods present in urine samples can provide objective biomarkers of food intake (BFIs). Whilst the majority of biomarker discovery/validation studies have investigated potential biomarkers for single foods only, this study considered the whole diet by using menus that delivered a wide range of foods in meals that emulated conventional UK eating patterns. Fifty-one healthy participants (range 19-77 years; 57% female) followed a uniquely designed, randomized controlled dietary intervention, and provided spot urine samples suitable for discovery of BFIs within a real-world context. Free-living participants prepared and consumed all foods and drinks in their own homes and were asked to follow the protocols for meal consumption and home urine sample collection. This study also assessed the robustness, and impact on data quality, of a minimally invasive urine collection protocol. Overall the study design was well-accepted by participants and concluded successfully without any drop outs. Compliance for urine collection, adherence to menu plans, and observance of recommended meal timings, was shown to be very high. Metabolome analysis using mass spectrometry coupled with data mining demonstrated that the study protocol was well-suited for BFI discovery and validation. Novel, putative biomarkers for an extended range of foods were identified including legumes, curry, strongly-heated products, and artificially sweetened, low calorie beverages. In conclusion, aspects of this study design would help to overcome several current challenges in the development of BFI technology. One specific attribute was the examination of BFI generalizability across related food groups and across different preparations and cooking methods of foods. Furthermore, the collection of urine samples at multiple time points helped to determine which spot sample was optimal for identification and validation of BFIs in free-living individuals. A further valuable design feature centered on the comprehensiveness of the menu design which allowed the testing of biomarker specificity within a biobank of urine samples.

Calystegines are Potential Urine Biomarkers for Dietary Exposure to Potato Products.

SCOPE: Metabolites derived from specific foods present in urine samples can provide objective biomarkers of food intake (BFIs). This study investigated the possibility that calystegines (a class of iminosugars) may provide BIFs for potato (Solanum tuberosum L.) product exposure. METHODS AND RESULTS: Calystegine content is examined in published data covering a wide range of potato cultivars. Rapid methods are developed for the quantification of calystegines in cooked potato products and human urine using triple quadrupole mass spectrometry. The potential of calystegines as BFIs for potato consumption is assessed in a controlled food intervention study in the United Kingdom and validated in an epidemiological study in Portugal. Calystegine concentrations are reproducibly above the quantification limit in first morning void urines the day after potato consumption, showing a good dose-response relationship, particularly for calystegine A3 . The design of the controlled intervention mimicks exposure to a typical UK diet and showed that neither differences in preparation/cooking method or influence of other foods in the diet has significant impact on biomarker performance. Calystegine biomarkers also perform well in the independent validation study. CONCLUSION: It is concluded that calystegines have many of the characteristics needed to be considered as specific BFIs for potato product intake.

A Standardized Strategy for Simultaneous Quantification of Urine Metabolites to Validate Development of a Biomarker Panel Allowing Comprehensive Assessment of Dietary Exposure.

SCOPE: Metabolites derived from individual foods found in human biofluids after consumption could provide objective measures of dietary intake. For comprehensive dietary assessment, quantification methods would need to manage the structurally diverse mixture of target metabolites present at wide concentration ranges. METHODS AND RESULTS: A strategy for selection of candidate dietary exposure biomarkers is developed. An analytical method for 62 food biomarkers is validated by extensive analysis of chromatographic and ionization behavior characteristics using triple quadrupole mass spectrometry. Urine samples from two food intervention studies are used: a controlled, inpatient study (n = 19) and a free-living study where individuals (n = 15) are provided with food as a series of menu plans. As proof-of-principle, it is demonstrated that the biomarker panel could discriminate between menu plans by detecting distinctive changes in the concentration in urine of targeted metabolites. Quantitative relationships between four biomarker concentrations in urine and dietary intake are shown. CONCLUSION: Design concepts for an analytical strategy are demonstrated, allowing simultaneous quantification of a comprehensive panel of chemically-diverse biomarkers of a wide range of commonly-consumed foods. It is proposed that integration of self-reported dietary recording tools with biomarker approaches will provide more robust assessment of dietary exposure.

Validation of a new software eAT24 used to assess dietary intake in the adult Portuguese population.

OBJECTIVE: The aim of the current study was to evaluate the accuracy of the new software eAT24 used to assess dietary intake in the National Food, Nutrition and Physical Activity Survey (IAN-AF) against urinary biomarkers: N (nitrogen), K (potassium) and Na (sodium). DESIGN: We conducted a cross-sectional study. Two non-consecutive 24-h dietary recalls (24-HDR) were applied, and a 24-h urine sample was collected. We examined differences between estimates from dietary and urine measures, Pearson correlation coefficients were calculated and the Bland-Altman plots were drawn. Multiple linear regression was used to evaluate the factors associated with the difference between estimates. SETTING: Sub-sample from the Portuguese IAN-AF sampling frame. PARTICIPANTS: Ninety-five adults (men and women) aged 18-84 years. RESULTS: The estimated intake calculated using the dietary recall data was lower than that estimated from urinary excretion for the three biomarkers studied (protein 94·3 v. 100·4 g/d, K 3212 v. 3416 mg/d and Na 3489 v. 4003 mg/d). Considering 2 d of recall, the deattenuated correlation coefficients were 0·33, 0·64 and 0·26 for protein, K and Na, respectively. For protein, differences between dietary and urinary estimates varied according to BMI (ß = -1·96, P = 0·017). The energy intake and 24-h urine volume were significantly associated with the difference between estimates for protein (ß = 0·03, P < 0·001 and ß = -0·02, P = 0·002, respectively), K (ß = 0·71, P < 0·001 and ß = -0·42, P = 0·040, respectively) and Na (ß = 1·55, P < 0·001 and ß = -0·81, P = 0·011, respectively). CONCLUSIONS: The new software eAT24 performed well in estimating protein and K intakes, but lesser so in estimating Na intake, using two non-consecutive 24-HDR.

Developing community-based urine sampling methods to deploy biomarker technology for the assessment of dietary exposure.

OBJECTIVE: Obtaining objective, dietary exposure information from individuals is challenging because of the complexity of food consumption patterns and the limitations of self-reporting tools (e.g., FFQ and diet diaries). This hinders research efforts to associate intakes of specific foods or eating patterns with population health outcomes. DESIGN: Dietary exposure can be assessed by the measurement of food-derived chemicals in urine samples. We aimed to develop methodologies for urine collection that minimised impact on the day-to-day activities of participants but also yielded samples that were data-rich in terms of targeted biomarker measurements. SETTING: Urine collection methodologies were developed within home settings. PARTICIPANTS: Different cohorts of free-living volunteers. RESULTS: Home collection of urine samples using vacuum transfer technology was deemed highly acceptable by volunteers. Statistical analysis of both metabolome and selected dietary exposure biomarkers in spot urine collected and stored using this method showed that they were compositionally similar to urine collected using a standard method with immediate sample freezing. Even without chemical preservatives, samples can be stored under different temperature regimes without any significant impact on the overall urine composition or concentration of forty-six exemplar dietary exposure biomarkers. Importantly, the samples could be posted directly to analytical facilities, without the need for refrigerated transport and involvement of clinical professionals. CONCLUSIONS: This urine sampling methodology appears to be suitable for routine use and may provide a scalable, cost-effective means to collect urine samples and to assess diet in epidemiological studies.

Developing a Food Exposure and Urine Sampling Strategy for Dietary Exposure Biomarker Validation in Free-Living Individuals.

SCOPE: Dietary choices modulate the risk of chronic diseases and improving diet is a central component of public health strategies. Food-derived metabolites present in urine could provide objective biomarkers of dietary exposure. To assist biomarker validation, this work aims to develop a food intervention strategy mimicking a typical annual diet over a short period of time and assesses urine sampling protocols potentially suitable for future deployment of biomarker technology in free-living populations. METHODS AND RESULTS: Six different menu plans comprehensively represent a typical UK annual diet that is split into two dietary experimental periods. Free-living adult participants (n = 15 and n = 36, respectively) are provided with all their food, as a series of menu plans, over a period of three consecutive days. Multiple spot urine samples are collected and stored at home. CONCLUSION: A successful food exposure strategy is established following a conventional UK eating pattern, which is suitable for biomarker validation in free-living individuals. The urine sampling procedure is acceptable for volunteers and delivered samples suitable for biomarker quantification. The study design provides scope for validation of existing biomarker candidates and potentially for discovery of new biomarker leads, and should help inform the future deployment of biomarker technology for habitual dietary exposure measurement.

Spot and Cumulative Urine Samples Are Suitable Replacements for 24-Hour Urine Collections for Objective Measures of Dietary Exposure in Adults Using Metabolite Biomarkers.

BACKGROUND: Measurement of multiple food intake exposure biomarkers in urine may offer an objective method for monitoring diet. The potential of spot and cumulative urine samples that have reduced burden on participants as replacements for 24-h urine collections has not been evaluated. OBJECTIVE: The aim of this study was to determine the utility of spot and cumulative urine samples for classifying the metabolic profiles of people according to dietary intake when compared with 24-h urine collections in a controlled dietary intervention study. METHODS: Nineteen healthy individuals (10 male, 9 female, aged 21-65 y, BMI 20-35 kg/m2) each consumed 4 distinctly different diets, each for 1 wk. Spot urine samples were collected ∼2 h post meals on 3 intervention days/wk. Cumulative urine samples were collected daily over 3 separate temporal periods. A 24-h urine collection was created by combining the 3 cumulative urine samples. Urine samples were analyzed with metabolite fingerprinting by both high-resolution flow infusion electrospray mass spectrometry (FIE-HRMS) and proton nuclear magnetic resonance spectroscopy (1H-NMR). Concentrations of dietary intake biomarkers were measured with liquid chromatography triple quadrupole mass spectrometry and by integration of 1H-NMR data. RESULTS: Cross-validation modeling with 1H-NMR and FIE-HRMS data demonstrated the power of spot and cumulative urine samples in predicting dietary patterns in 24-h urine collections. Particularly, there was no significant loss of information when post-dinner (PD) spot or overnight cumulative samples were substituted for 24-h urine collections (classification accuracies of 0.891 and 0.938, respectively). Quantitative analysis of urine samples also demonstrated the relation between PD spot samples and 24-h urines for dietary exposure biomarkers. CONCLUSIONS: We conclude that PD spot urine samples are suitable replacements for 24-h urine collections. Alternatively, cumulative samples collected overnight predict similarly to 24-h urine samples and have a lower collection burden for participants.

Ultra high performance liquid chromatography-high resolution mass spectrometry plasma lipidomics can distinguish between canine breeds despite uncontrolled environmental variability and non-standardized diets.

INTRODUCTION AND OBJECTIVES: The purpose of this study was to use high accurate mass metabolomic profiling to investigate differences within a phenotypically diverse canine population, with breed-related morphological, physiological and behavioural differences. Previously, using a broad metabolite fingerprinting approach, lipids appear to dominate inter- and intra- breed discrimination. The purpose here was to use Ultra High Performance Liquid Chromatography-High Resolution Mass Spectrometry (UHPLC-HRMS) to identify in more detail, inter-breed signatures in plasma lipidomic profiles of home-based, client-owned dogs maintained on different diets and fed according to their owners' feeding regimens. METHODS: Nine dog breeds were recruited in this study (Beagle, Chihuahua, Cocker Spaniel, Dachshund, Golden Retriever, Greyhound, German Shepherd, Labrador Retriever and Maltese: 7-12 dogs per breed). Metabolite profiling on a MTBE lipid extract of fasted plasma was performed using UHPLC-HRMS. RESULTS: Multivariate modelling and classification indicated that the main source of lipidome variance was between the three breeds Chihuahua, Dachshund and Greyhound and the other six breeds, however some intra-breed variance was evident in Labrador Retrievers. Metabolites associated with dietary intake impacted on breed-associated variance and following filtering of these signals out of the data-set unique inter-breed lipidome differences for Chihuahua, Golden Retriever and Greyhound were identified. CONCLUSION: By using a phenotypically diverse home-based canine population, we were able to show that high accurate mass lipidomics can enable identification of metabolites in the first pass plasma profile, capturing distinct metabolomic variability associated with genetic differences, despite environmental and dietary variability.

Characterisation of the main drivers of intra- and inter- breed variability in the plasma metabolome of dogs.

INTRODUCTION: Dog breeds are a consequence of artificial selection for specific attributes. These closed genetic populations have metabolic and physiological characteristics that may be revealed by metabolomic analysis. OBJECTIVES: To identify and characterise the drivers of metabolic differences in the fasted plasma metabolome and then determine metabolites differentiating breeds. METHODS: Fasted plasma samples were collected from dogs maintained under two environmental conditions (controlled and client-owned at home). The former (n = 33) consisted of three breeds (Labrador Retriever, Cocker Spaniel and Miniature Schnauzer) fed a single diet batch, the latter (n = 96), client-owned dogs consisted of 9 breeds (Beagle, Chihuahua, Cocker Spaniel, Dachshund, Golden Retriever, Greyhound, German Shepherd, Labrador Retriever and Maltese) consuming various diets under differing feeding regimens. Triplicate samples were taken from Beagle (n = 10) and Labrador Retriever (n = 9) over 3 months. Non-targeted metabolite fingerprinting was performed using flow infusion electrospray-ionization mass spectrometry which was coupled with multivariate data analysis. Metadata factors including age, gender, sexual status, weight, diet and breed were investigated. RESULTS: Breed differences were identified in the plasma metabolome of dogs housed in a controlled environment. Triplicate samples from two breeds identified intra-individual variability, yet breed separation was still observed. The main drivers of variance in dogs maintained in the home environment were associated with breed and gender. Furthermore, metabolite signals were identified that discriminated between Labrador Retriever and Cocker Spaniels in both environments. CONCLUSION: Metabolite fingerprinting of plasma samples can be used to investigate breed differences in client-owned dogs, despite added variance of diet, sexual status and environment.

Changes in the human plasma and urinary metabolome associated with acute dietary exposure to sucrose and the identification of potential biomarkers of sucrose intake.

SCOPE: The intake of sucrose is of public health concern but limited information is available on the metabolic effects of short-term exposure. Our aim was to use metabolomics to investigate the metabolic impact of acute sucrose exposure. METHODS AND RESULTS: We performed a randomized, parallel, single-dose feeding study on healthy females (n = 90, aged 29.9 ± 4.7 years, BMI 23.3 ± 2.5 kg/m(2) ) consuming either 0, 50, or 100 g sucrose in 500 mL water. Blood and urine samples were taken before and 24 h post sucrose intake. Urine and plasma samples underwent detailed metabolite profiling analysis using established protocols. Flow-injection electrospray MS fingerprinting analysis showed that 3 h after intake was the most informative time point in urine and plasma and out of 120 explanatory signals, highlighted 16 major metabolite signals in urine and 25 metabolite signals in plasma that were discriminatory and correlated with sucrose intake over time. The main confirmed metabolites positively correlated with intake were sucrose, fructose, and erythronic acid, while those negatively correlating with intake included fatty acids and derivatives, acyl-carnitines, and ketone bodies. GC-TOF-MS profiling analysis confirmed the fingerprinting data. CONCLUSION: Acute exposure to sucrose identified a number of metabolites correlated with sucrose intake and several compounds attributed to metabolic fasting.

Dietary exposure biomarker-lead discovery based on metabolomics analysis of urine samples.

Although robust associations between dietary intake and population health are evident from conventional observational epidemiology, the outcomes of large-scale intervention studies testing the causality of those links have often proved inconclusive or have failed to demonstrate causality. This apparent conflict may be due to the well-recognised difficulty in measuring habitual food intake which may lead to confounding in observational epidemiology. Urine biomarkers indicative of exposure to specific foods offer information supplementary to the reliance on dietary intake self-assessment tools, such as FFQ, which are subject to individual bias. Biomarker discovery strategies using non-targeted metabolomics have been used recently to analyse urine from either short-term food intervention studies or from cohort studies in which participants consumed a freely-chosen diet. In the latter, the analysis of diet diary or FFQ information allowed classification of individuals in terms of the frequency of consumption of specific diet constituents. We review these approaches for biomarker discovery and illustrate both with particular reference to two studies carried out by the authors using approaches combining metabolite fingerprinting by MS with supervised multivariate data analysis. In both approaches, urine signals responsible for distinguishing between specific foods were identified and could be related to the chemical composition of the original foods. When using dietary data, both food distinctiveness and consumption frequency influenced whether differential dietary exposure could be discriminated adequately. We conclude that metabolomics methods for fingerprinting or profiling of overnight void urine, in particular, provide a robust strategy for dietary exposure biomarker-lead discovery.

Hydroxylated phenylacetamides derived from bioactive benzoxazinoids are bioavailable in humans after habitual consumption of whole grain sourdough rye bread.

SCOPE: Understanding relationships between dietary whole grain and health is hindered by incomplete knowledge of potentially bioactive metabolites derived from these foods. We aimed to discover compounds in urine correlated with changes in amounts of whole grain rye consumption. METHODS AND RESULTS: After a wash-out period, volunteers consumed 48-g whole grain rye foods per day for 4 wk and then doubled their intake for a further 4 wk. Samples of 24-h urines were analyzed by flow infusion electrospray MS followed by supervised multivariate data analysis. Urine samples from participants who reported high intakes of rye flakes, rye pasta, or total whole grain rye products could not be discriminated adequately from their wash-out samples. However, discrimination was seen in urine samples from participants who reported high whole grain sourdough rye bread consumption. Accurate mass analysis of explanatory signals followed by fragmentation identified conjugates of the benzoxazinoid lactam 2-hydroxy-1,4-benzoxazin-3-one and hydroxylated phenyl acetamide derivatives. Statistical validation showed sensitivities of 84-96% and specificities of 70-81% (p values < 0·05) for elevated concentrations of these signals after preferential whole grain sourdough rye bread consumption. CONCLUSION: Several potentially bioactive alkaloids have been identified in humans consuming fermented whole grain sourdough rye bread.

Data-driven strategy for the discovery of potential urinary biomarkers of habitual dietary exposure.

BACKGROUND: An understanding of causal relations between diet and health is hindered by the lack of robust biological markers of food exposure. OBJECTIVE: We aimed to develop a data-driven procedure to discover urine biomarkers indicative of habitual exposure to different foods. DESIGN: The habitual diet of 68 participants was assessed by using 4 food-frequency questionnaires over 3 mo, and participants were assigned to different consumption-frequency classes for 58 dietary components. Flow infusion electrospray-ionization mass spectrometry followed by supervised multivariate data analysis was used to determine whether the chemical composition of urine was related to specific differences in the consumption levels of each food. RESULTS: Foods were eaten habitually in 1 of 5 basic patterns differing in range and distribution of consumption frequency. Overnight, 24-h, and fasting urine samples proved useful for biomarker lead discovery with habitual citrus exposure used as a paradigm. Exposure level discrimination robustness improved linearly as urine samples from low-frequency citrus consumers were compared with urine samples from participants reporting increasingly higher intakes. For all foods, distinctiveness and consumption-frequency range influenced the likelihood that differential dietary exposure could be detected. Model output statistics indicated foods for which biomarker lead discovery was feasible. Metabolites proposed previously as acute intake biomarkers of citrus (proline betaine), oily fish (methylhistidine), coffee (dihydrocaffeic acid derivatives), and tomato (phenolic metabolites) were also biomarkers of habitual exposure. A significance threshold in modeling output statistics was determined to guide the discovery of potential biomarkers for other foods. CONCLUSION: This data-driven strategy can identify urinary metabolites associated with habitual exposure to specific foods. This trial has the UK registration number 4349 and was registered at isrtcn.org as CCT-NAPN-A13175.

Differential effect of three base modifications on DNA thermostability revealed by high resolution melting.

High resolution melting (HRM) can detect and quantify the presence of 5-methylcytosine (5mC) in DNA samples, but the ability of HRM to diagnose other DNA modifications remains unexplored. The DNA bases N6-methyladenine and 5-hydroxymethylcytosine occur across almost all phyla. While their function remains controversial, their presence perturbs DNA structure. Such modifications could affect gene regulation, chromatin condensation and DNA packaging. Here, we reveal that DNA containing N6-methyladenine or 5-hydroxymethylcytosine exhibits reduced thermal stability compared to cytosine-methylated DNA. These thermostability changes are sufficiently divergent to allow detection and quantification by HRM analysis. Thus, we report that HRM distinguishes between sequence-identical DNA differing only in the modification type of one base. This approach is also able to distinguish between two DNA fragments carrying both N6-methyladenine and 5-methylcytosine but differing only in the distance separating the modified bases. This finding provides scope for the development of new methods to characterize DNA chemically and to allow for low cost screening of mutant populations of genes involved in base modification. More fundamentally, contrast between the thermostabilizing effects of 5mC on dsDNA compared with the destabilizing effects of N6-methyladenine (m6A) and 5-hydroxymethylcytosine (5hmC) raises the intriguing possibility of an antagonistic relationship between modification types with functional significance.

Separating the inseparable: the metabolomic analysis of plant-pathogen interactions.

Plant-microbe interactions-whether pathogenic or symbiotic-exert major influences on plant physiology and productivity. Analysis of such interactions represents a particular challenge to metabolomic approaches due to the intimate association between the interacting partners coupled with a general commonality of metabolites. We here describe an approach based on co-cultivation of Arabidopsis cell cultures and bacterial plant pathogens to assess the metabolomes of both interacting partners, which we refer to as dual metabolomics.

Development and validation of a standardized protocol to monitor human dietary exposure by metabolite fingerprinting of urine samples.

Conventional tools for measuring dietary exposure have well recognized limitations. Measurement of food-derived metabolites in biofluids provides an alternative approach and our aim was to develop an experimental protocol which ensures that extraneous variability does not obscure metabolic signals from ingested foods. Healthy adults consumed a standardized meal in the evening before each test day and collected pooled overnight urine. On each test day of three different studies, urine was collected in the fasted state and at different time points after consumption of a standardized breakfast. Metabolite fingerprinting of samples using Flow Infusion Electrospray-Ionization Mass Spectrometry followed by multivariate data analysis showed strong discrimination between overnight, fasting and postprandial samples, in each study separately and when data from the three studies were pooled. Such differences were robust and highly reproducible within individuals on separate occasions. Urine volume was an efficient data normalization factor for metabolite fingerprinting data. Postprandial urines had a stable chemical composition over a period of 2-4 h after eating a standardized breakfast, suggesting that there is a flexible time window for urine collection. Fasting urine samples provided a stable baseline for universal comparisons with postprandial samples. A dietary exposure biomarker discovery protocol was validated by demonstrating that top-ranked signals discriminating between fasting and 2-4 h postprandial urine samples could be linked to metabolites abundant in some components of the standardized breakfast. We conclude that the protocol developed will have value in the search for biomarker leads of dietary exposure. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0289-0) contains supplementary material, which is available to authorized users.

Use of mass spectrometry fingerprinting to identify urinary metabolites after consumption of specific foods.

BACKGROUND: The lack of robust biological markers of dietary exposure hinders the quantitative understanding of causal relations between diet and health. OBJECTIVE: We aimed to develop an efficient procedure to discover metabolites in urine that may have future potential as biomarkers of acute exposure to foods of high public health importance. DESIGN: Twenty-four participants were provided with a test breakfast in which the cereal component of a standardized breakfast was replaced by 1 of 4 foods of high public health importance; 1.5-, 3-, and 4.5-h postprandial urine samples were collected. Flow infusion electrospray-ionization mass spectrometry followed by supervised multivariate data analysis was used to discover signals resulting from consumption of each test food. RESULTS: Fasted-state urine samples provided a universal comparator for food biomarker lead discovery in postprandial urine. The filtering of data features associated with consumption of the common components of the standardized breakfast improved discrimination models and readily identified metabolites that showed consumption of specific test foods. A combination of trimethylamine-N-oxide and 1-methylhistidine was associated with salmon consumption. Novel ascorbate derivatives were discovered in urine after consumption of either broccoli or raspberries. Sulphonated caffeic acid and sulphonated methyl-epicatechin concentrations increased dramatically after consumption of raspberries. CONCLUSIONS: This biomarker lead discovery strategy can identify urinary metabolites associated with acute exposure to individual foods. Future studies are required to validate the specificity and utility of potential biomarkers in an epidemiologic context.

Proline betaine and its biotransformation products in fasting urine samples are potential biomarkers of habitual citrus fruit consumption.

The lack of robust measures of dietary exposure hinders a quantitative understanding of causal relationships between diet and health. Non-targeted metabolite fingerprinting was used to explore the relationships between citrus exposure in free-living human subjects, estimated by a FFQ, and the chemical content of urine. Volunteers (study 1, n 12; study 2, n 11) were classified into high-, medium- and low-frequency citrus consumption groups. Overnight and spot fasting urine samples were obtained after exposure to a standardised citrus-free evening meal. The urine samples were analysed by flow injection electrospray-ionisation MS followed by supervised multivariate data classification analysis to discover discriminatory features associated with the level of citrus exposure. Good separation of high and low citrus consumption classes was achieved. Deeper exploration of high-ranked explanatory mass signals revealed several correlated signals derived from proline betaine. Targeted analysis of the relative levels of proline betaine in both fasting and overnight urine samples demonstrated good correlation with FFQ exposure data. Acute exposure of volunteers to orange juice resulted in the appearance of proline betaine and several biotransformed products in postprandial urine samples. Biomarker validation showed sensitivities of 80·8-92·2 % and specificities of 74·2-94·1 % (false discovery rate-adjusted P values < 0·05) for elevated proline betaine in participants who reported high citrus consumption. Proline betaine biotransformation products displayed weaker quantitative relationships with habitual citrus exposure. Targeted screening for the presence of biotransformation products of hesperidin and narirutin, known to be abundant in oranges, revealed that they were relatively poor indicators of citrus exposure.