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Thiamine (vitamin B1) is an essential micronutrient required as a cofactor in many metabolic processes. Clinical symptoms of thiamine deficiency are poorly defined, hence biomarkers of thiamine status are important. The erythrocyte transketolase activity coefficient (ETKac) is a sensitive measure of thiamine status, but its interpretation may be confounded where the availability of the transketolase enzyme is limited. Basal ETK activity per gram of hemoglobin provides a complementary biomarker of thiamine status; however, its measurement and calculation are poorly described. Here, we describe in detail the assessment of basal ETK activity, including the calculation of path length in microplates and the molar absorption coefficient of NADH specific to the assay, and the measurement of hemoglobin in sample hemolysates. To illustrate the application of the methods, we present ETKac and basal ETK activity from women in The Gambia and UK. In conclusion, we present a clear protocol for the measurement of basal ETK activity that will permit the harmonization of methods to improve replication between laboratories., This work was funded by the NIHR Cambridge Biomedical Research Centre (IS-BRC-1215-20014). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care.

Breastfeeding is regarded as the ideal way to nourish infants. However, feeding with formula milk is also common in much of the West. Despite this, the function of the molecular components of breast- and formula milks are not fully understood, less still the relationship between the composition of the milk and the infant’s metabolism and how this influences the infant’s development. The Biotechnology and Biological Sciences Research Council (BBSRC)-funded project ‘The validation of biomarkers of metabolic efficacy in infant nutrition’ aims to identify lipid biomarkers that can be used to study the effect of diet on growth and development of infants. In this work, we have been able to validate these markers. Here, we present an approach to biomarker discovery that has new depth and will inform research questions about how metabolism is governed, and which species can be used to identify situations where metabolism is becoming defective.

Rationale We describe a novel method for preparing milk samples and profiling their triglyceride (TG) fractions. This method was used to explore how the TG profile of milk modulates as lactation progresses and how the TG profile differs between breasts. Methods Fresh milk was spotted onto Whatman filter paper and air-dried. Liquid Extraction Surface Analysis coupled to Fourier Transform Mass Spectrometry (LESA-MS) was adapted for molecular profiling. Collision-Induced Dissociation (CID) was used to profile fatty acid residues. Results LESA-MS produced the relative abundances of all isobaric TGs described and showed that mammary glands within one individual can produce a different profile of TGs. CID was used to uncover the configuration of isobaric triglycerides, indicating the relative amounts of the fatty acids contributing to that triglyceride's mass. This also indicated the presence of very long chain fatty acids (C26:0 and C26:1) that have not been reported before in human breast milk. Conclusions We conclude that spotting on paper and the use of LESA-MS and CID on milk spots is not only a means for analysing milk in unprecedented detail for this preparation time, but is also amenable to conditions in which collecting and storing fresh milk samples for detailed profiling is prohibitively difficult.

Rationale Lipoproteins belong to the most commonly measured clinical biochemical parameters. Lipidomics is an orthogonal approach and aims to profile the individual lipid molecules that jointly form the lipoprotein particles. However, in the first step of the extraction of lipid molecules from serum, an organic solvent is used leading to dissociation of the lipoproteins. Thus far it has been impossible to combine lipidomics and lipoprotein analysis in one analytical system. Methods Human plasma was diluted in phosphate‐buffered saline (PBS) and injected onto a Superose 6 PC 3.2 column with PBS as a mobile phase to separate lipoproteins. The eluent was led to a Syrris FLLEX module, which also received CHCl3/MeOH (3:1). The two phases were mixed and subsequently separated using a Teflon membrane in an especially designed pressurized flow chamber. The organic phase was led to a standard electrospray source of an Orbitrap mass spectrometer. Results Size‐exclusion chromatography (SEC) has been commonly applied to separate lipoproteins and is considered a practical alternative to ultracentrifugation. Through the on‐line liquid‐liquid extraction method it becomes possible to obtained detailed mass spectra of lipids across different lipoprotein fractions. The extracted ion chromatograms of specific lipid signals showed their distribution against the size of lipoprotein particles. Conclusions The application of on‐line liquid‐liquid extraction allows for the continuous electrospray‐based mass spectral analysis of SEC eluent, providing the detailed lipid composition of lipoprotein particles separated by size. This approach provides new possibilities for the study of the biochemistry of lipoproteins. © 2015 The Authors. Rapid Communications in Mass Spectrometry Published by John Wiley & Sons Ltd.

The identification of quantitative trait loci (QTL) for plant metabolites requires the quantitation of these metabolites across a large range of progeny. We developed a rapid metabolic profiling method using both untargeted and targeted direct infusion tandem mass spectrometry (DIMSMS) with a linear ion trap mass spectrometer yielding sufficient precision and accuracy for the quantification of a large number of metabolites in a high-throughput environment. The untargeted DIMSMS method uses top-down data-dependent fragmentation yielding MS(2) and MS(3) spectra. We have developed software tools to assess the structural homogeneity of the MS(2) and MS(3) spectra hence their utility for phenotyping and genetical metabolomics. In addition we used a targeted DIMS(MS) method for rapid quantitation of specific compounds. This method was compared with targeted LC/MS/MS methods for these compounds. The DIMSMS methods showed sufficient precision and accuracy for QTL discovery. We phenotyped 200 individual Lolium perenne genotypes from a mapping population harvested in two consecutive years. Computational and statistical analyses identified 246 nominal m/z bins with sufficient precision and homogeneity for QTL discovery. Comparison of the data for specific metabolites obtained by DIMSMS with the results from targeted LC/MS/MS analysis showed that quantitation by this metabolic profiling method is reasonably accurate. Of the top 100 MS(1) bins, 22 ions gave one or more reproducible QTL across the 2 years.

Most analytical methods in metabolomics are based on one of two strategies. The first strategy is aimed at specifically analysing a limited number of known metabolites or compound classes. Alternatively, an unbiased approach can be used for profiling as many features as possible in a given metabolome without prior knowledge of the identity of these features. Using high-resolution mass spectrometry with instruments capable of measuring m/z ratios with sufficiently low mass measurement uncertainties and simultaneous high scan speeds, it is possible to combine these two strategies, allowing unbiased profiling of biological samples and targeted analysis of specific compounds at the same time without compromises. Such high mass accuracy and mass resolving power reduces the number of candidate metabolites occupying the same retention time and m/z ratio space to a minimum. In this study, we demonstrate how targeted analysis of phospholipids as well as unbiased profiling is achievable using a benchtop orbitrap instrument after high-speed reversed-phase chromatography. The ability to apply both strategies in one experiment is an important step forward in comprehensive analysis of the metabolome. Copyright © 2009 John Wiley & Sons, Ltd.

Metabolomics describes the measurement of the full complement of the products of metabolism in a single biological sample and correlating these metabolomic profiles with known physiological or pathological states. The metabolome offers the possibility of finding unique fingerprints responsible for different phenotypes. Analytical techniques such as nuclear magnetic resonance or mass spectrometry measure thousands of compounds within the metabolome simultaneously and appropriate data mining and database tools allow the finding of significant correlations between the measured metabolomes. The first direct outcome of nutritional metabolomics will be the discovery of biomarkers, which can reveal changes in health and disease but also indicate short term and long-term dietary intake. The concerted actions of nutrigenomics and metabolomics will play a crucial role in understanding how specific interactions of single nucleotide polymorphisms (SNP) influence a person's response to a diet. Finally, systems biology approaches to human nutrition combine transcriptomics, proteomics and metabolomics with the aim of understanding how diets interact within the human being.

Insights into associations between diet and Cardiovascular Disease (CVD) are constantly evolving due to methodological developments and identification of novel pathophysiological pathways. Nutritional epidemiology research often aims to examine the association between single nutrients/foods and CVD. More recently, dietary patterns (DPs) which incorporate cumulative and interactive effects of foods/nutrients, are studied in association with cardio metabolic disease risk. Hypothesis-driven approaches to DP analysis are based on adherence to predefined diets (e.g. Mediterranean diet score) therefore, they may not reflect overall diet. While exploratory DP approaches (e.g. principal components analysis) can represent real-world dietary behaviours, they may not fully explain the disease-relevant variation in dietary intake. Reduced rank regression (RRR) takes advantage of both prior knowledge and data-driven aspects by incorporating hypothesised intermediates on the diet-disease pathway when identifying DPs. T...