Amanda J. Lloyd

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.

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.

The application of MANOVA to analyse Arabidopsis thaliana metabolomic data from factorially designed experiments

Metabolomic technologies produce complex multivariate datasets and researchers are faced with the daunting task of extracting information from these data. Principal component analysis (PCA) has been widely applied in the field of metabolomics to reduce data dimensionality and for visualising trends within the complex data. Although PCA is very useful, it cannot handle multi-factorial experimental designs and, often, clear trends of biological interest are not observed when plotting various PC combinations. Even if patterns are observed, PCA provides no measure of their significance. Multivariate analysis of variance (MANOVA) applied to these PCs enables the statistical evaluation of main treatments and, more importantly, their interactions within the experimental design. The power and scope of MANOVA is demonstrated through two different factorially designed metabolomic investigations using Arabidopsis ethylene signalling mutants and their wild-type. One investigation has multiple experimental factors including challenge with the economically important pathogen Botrytis cinerea and also replicate experiments, while the second has different sample preparation methods and one level of replication ‘nested’ within the design. In both investigations there are specific factors of biological interest and there are also factors incorporated within the experimental design, which affect the data. The versatility of MANOVA is displayed by using data from two different metabolomic techniques; profiling using direct injection mass spectroscopy (DIMS) and fingerprinting using fourier transform infra-red (FT-IR) spectroscopy. MANOVA found significant main effects and interactions in both experiments, allowing a more complete and comprehensive interpretation of the variation within each investigation, than with PCA alone. Canonical variate analysis (CVA) was applied to investigate these effects and their biological significance. In conclusion, the application of MANOVA followed by CVA provided extra information than PCA alone and proved to be a valuable statistical addition in the overwhelming task of analysing metabolomic data.

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.

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.

Biphasic ethylene production during the hypersensitive response in Arabidopsis: A window into defence priming mechanisms?

The hypersensitive response (HR) is a cell death phenomenon associated with localised resistance to pathogens. Biphasic patterns in the generation of H2O2, salicylic acid and ethylene have been observed in tobacco during the early stages of the HR. These biphasic models reflect an initial elicitation by pathogen-associated molecular patterns followed by a second phase, induced by pathogen-encoded avirulence gene products. The first phase has been proposed to potentiate the second, to increase the efficacy of plant resistance to disease. This potentiation is comparable to the “priming” of plant defences which is seen when plants display systemic resistance to disease. The events regulating the generation of the biphasic wave, or priming, remains obscure, however recently we demonstrated a key role for nitric oxide in this process in a HR occurring in tobacco. Here we use laser photoacoustic detection to demonstrate that biphasic ethylene production also occurs during a HR occurring in Arabidopsis. We suggest that ethylene emanation during the HR represents a ready means of visualising biphasic events during the HR and that exploiting the genomic resources offered by this model species will facilitate the development of a mechanistic understanding of potentiating / priming processes.

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.

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 objectivesThe 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.MethodsNine 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.ResultsMultivariate 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.ConclusionBy 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.

Use of biomarkers to assess fruit and vegetable intake

A high intake of fruit and vegetables (FV) has been associated with reduced risk of a number of chronic diseases, including CVD. The aim of this review is to describe the potential use of biomarkers to assess FV intake. Traditional methods of assessing FV intake have limitations, and this is likely to impact on observed associations with disease outcomes and markers of disease risk. Nutritional biomarkers may offer a more objective and reliable method of assessing dietary FV intake. Some single blood biomarkers, such as plasma vitamin C and serum carotenoids, are well established as indicators of FV intake. Combining potential biomarkers of intake may more accurately predict overall FV intake within intervention studies than the use of any single biomarker. Another promising approach is metabolomic analysis of biological fluids using untargeted approaches to identify potential new biomarkers of FV intake. Using biomarkers to measure FV intake may improve the accuracy of dietary assessment.

Dietary compliance in a human intervention study investigating the impact of specific foods on urinary metabolites

N. D. Willis, S. E. Dodds, A. J. Lloyd, L. Xie, E. S. Chambers, I. Garcia-Perez, G. Frost, M. Beckmann, J. Draper and J. C. Mathers Human Nutrition Research Centre, Institute for Ageing and Health, Newcastle University, Campus for Ageing and Vitality, Newcastle-upon-Tyne, NE4 5PL, UK, Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, SY23 3DA, UK and Nutrition and Dietetic Research Group, Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Hammersmith Hospital Campus, Imperial College London, London, W12 0NN, UK