Integrated Analytical and Statistical Two-Dimensional Spectroscopy Strategy for Metabolite Identification: Application to Dietary Biomarkers

Abstract

A major purpose of exploratory metabolic profiling is for the identification of molecular species that are statistically associated with specific biological or medical outcomes; unfortunately, the structure elucidation process of unknowns is often a major bottleneck in this process. We present here new holistic strategies that combine different statistical spectroscopic and analytical techniques to improve and simplify the process of metabolite identification. We exemplify these strategies using study data collected as part of a dietary intervention to improve health and which elicits a relatively subtle suite of changes from complex molecular profiles. We identify three new dietary biomarkers related to the consumption of peas (N-methyl nicotinic acid), apples (rhamnitol), and onions (N-acetyl-S-(1Z)-propenyl-cysteine-sulfoxide) that can be used to enhance dietary assessment and assess adherence to diet. As part of the strategy, we introduce a new probabilistic statistical spectroscopy tool, RED-STORM (Resolution EnhanceD SubseT Optimization by Reference Matching), that uses 2D J-resolved 1H NMR spectra for enhanced information recovery using the Bayesian paradigm to extract a subset of spectra with similar spectral signatures to a reference. RED-STORM provided new information for subsequent experiments (e.g., 2D-NMR spectroscopy, solid-phase extraction, liquid chromatography prefaced mass spectrometry) used to ultimately identify an unknown compound. In summary, we illustrate the benefit of acquiring J-resolved experiments alongside conventional 1D 1H NMR as part of routine metabolic profiling in large data sets and show that application of complementary statistical and analytical techniques for the identification of unknown metabolites can be used to save valuable time and resources.

Circulating Pro- and Anti-Inflammatory Metabolites and Its Potential Role in Rheumatoid Arthritis Pathogenesis

“…cetoleic acid [25][26][27][28][29][30][31] Vegetables Vegetarian and lactovegetarian diet) Urine p-Hydroxyphenylacetate Hippurate; phenylacetylglutamine; lysine; hippurate; N-acetyl glycoprotein; succinate [19,32,33] Broccoli Urine Ascorbate; tetronic acids; l-xylonate/l-lyxonate; naringenin glucuronide [28] Onion Urine N-acetyl-S-(1Z)-propenyl-cysteine-sulfoxide 4-Ethyl-5-amino-pyrocatechol [34] Lettuce, spinach, green peppers Serum 3-Carboxy-4-methyl-5 -propyl-2-furanpropanoic [30] Cabbage, brussels sprouts, pointed cabbage Urine N-acetyl-S-(N-3-methylthiopropyl)cysteine; N-acetyl-S-(N-allylthiocarbamoyl)cysteine; iberin N-acetyl-cysteine; erucin N-acetyl-cysteine; N-acetyl-(N -benzylthiocarbamoyl)-cysteine; sulforaphane N-acetyl-cysteine; sulforaphane N-cysteine,3-Hydroxy-hippuric acid sulfate;…”

“…3-hydroxy-hippuric acid; iberin N-acetyl-cysteine [29] Fruit Apples and pears Urine Phloretin [35,36]; rhamnitol [34] Citrus Urine Proline betaine; limonene 8,9-diol glucuronide; nootkatone 13,14-diol glucuronide; hesperetin 3 -O-glucuronide; hydroxyproline betaine; N-methyltyramine sulfate; naringenin 7-O-glucuronide; stachydrine; scyllo-and chiro-inositol [28,30,[35][36][37][38][39][40] Orange juice Urine N-methyl proline; methyl glucopyranoside (α+β); stachydrine; betonicine; N-acetyl putrescine; dihydroferulic acid [41] The identification of food biomarkers is an ongoing process; a consensus has not been reached as to which metabolites would be the most adequate biomarkers for different types of foods. Moreover, some metabolites are markers of categories of food, not being able to discriminate between the exact types of foods being analyzed (1-methylhistidine and 3-methylhistidine are found in meat and are not useful in discriminating between types of meat).…”

Metabolomic‐Based Approach to Identify Biomarkers of Apple Intake

“…Previous literature has also identified biomarkers such as phloretin and rhamnitol as candidate biomarkers of apple intake. [ 31–34 ] Due to different study designs, analytical procedures, and apple variety it is not surprising to obtain different biomarkers. Previous work has demonstrated that rhamnitol levels in apples vary due to geographic location and highlights the need for validation of candidate biomarkers.…”

“…[ 31–33 ] The polyphenol epicatechin, its conjugates and metabolites, have also been associated with apple intake [ 31,33 ] but this polyphenol is commonly found in multiple foods. Many other compounds have been identified as potential markers of apple consumption, mainly in studies looking at consumption of multiple fruits, including rhamnitol [ 34 ] and metabolic products of quercetin. [ 32 ] While some interesting biomarkers for apple intake have emerged in the literature, it is clear that more work is needed in order to discover robust biomarkers of apple intake, and steps taken to validate these biomarkers.…”

Application of novel solid phase extraction-NMR protocols for metabolic profiling of human urine

“…Within metabolic proling, 1 H Nuclear Magnetic Resonance (NMR) spectroscopy has become an extremely valuable tool for the characterisation of complex mixtures; 2 statistical spectroscopy tools have also been applied to extract information from complex spectral sets. 3 Posma et al 4 have demonstrated the use of statistical 2D NMR, utilising the RED-STORM probabilistic statistical spectroscopy tool on data acquired from diet-controlled human urine samples, in order to further expand the understanding of dietary biomarkers.…”