Metabolomics

Psoriatic arthritis (PsA), an inflammatory arthritis that develops in individuals with psoriasis, is associated with reduced quality of life. Identifying biomarkers associated with development of PsA as well as with PsA disease activity may help management of psoriatic disease. To use metabolomic fingerprinting to determine potential candidate markers of disease conversion (psoriasis to PsA) and/or PsA activity. A novel sample preparation protocol based on solid-phase microextraction (SPME) was used to prepare serum samples obtained from: (1) individuals with psoriasis, some of whom develop psoriatic arthritis (n = 20); (2) individuals with varying PsA activity (mild, moderate, severe; n = 10 each) and (3) healthy controls (n = 10). Metabolomic fingerprinting of the obtained extracts was performed using reversed-phase liquid chromatography coupled to high resolution mass spectrometry. Psoriasis patients who developed PsA had similar metabolomic profiles to patients with mild PsA and were also indistinguishable from patients with psoriasis who did not develop PsA. Elevated levels of selected long-chain fatty acids (e.g., 3-hydroxytetradecanedioic acid) that are associated with dysregulation of fatty acid metabolism, were observed in patients with severe PsA. In addition, 1,11-undecanedicarboxylic acid—an unusual fatty acid associated with peroxisomal disorders—was also identified as a classifier in PsA patients vs. healthy individuals. Furthermore, a number of different eicosanoids with either pro- or anti-inflammatory properties were detected solely in serum samples of patients with moderate and severe PsA. A global metabolomics approach was employed to analyze the serum metabolome of patients with psoriasis, PsA, and healthy controls in order to examine potential differences in the biochemical profiles at a metabolite level. A closer examination of circulating metabolites may potentially provide markers of PsA activity.

Natural extracts used in flavour and fragrances are exposed to authentication issues. Companies working in this industrial market acquire the raw materials locally but also abroad, sourcing exotic plants with specific olfactive features or lower costs of production. The geographical origin, the botanical variety, environmental conditions, extraction processes and storage conditions represent some parameters affecting the natural extract quality. All these factors are likely to affect the sensorial properties and especially the organoleptic characteristics of the extract. In addition, fraudulent practices known as adulterations have also an impact on the quality. Sensitive and precise analytical techniques are required to identify adulterations among other sources of variability. In this context, the highly valuable rose absolute was selected as a model study for its importance in perfumery. The existence of two botanical species and several production countries are additional reasons that make this extract an interesting case study. Because the usual GC–MS metabolomic approach is not able to cover the broad range of non-volatile compounds, complementary approaches are required. An UHPLC-ToFMS fingerprinting approach was therefore developed to allow the identification of non-volatile markers of the two closely related species of the genus Rosa. Thus, 12-oxophytodienoic acid was identified as a biomarker (level 2 according to MSI guideline) enabling the distinction between R. centifolia and R. damascena. Our results finally underline the efficiency of the UHPLC-ToFMS metabolomic approach for the qualification of odorant extracts.

Whey protein improves fasting lipids and insulin response in overweight and obese individuals. Whey hydrolysate was recently shown to be more active than whole protein but the differences in metabolite profiles after intake remain unknown. This study discriminates plasma profiles after intake of four different whey protein fractions and establishes new hypotheses for the observed effects. Obese, non-diabetic subjects were included in the randomized, blinded, cross-over meal study. Subjects ingested a high-fat meal containing whey isolate (WI), whey concentrate hydrolysate (WH), α-lactalbumin or caseinoglycomacropeptide as the protein source. Plasma samples were collected at five time points and metabolites analysed using LC–Q-TOF–MS. Plasma concentrations of ten amino acids (AAs) were different between the meals. The plasma levels of AAs and AA derivatives were generally directly related to the AA composition of the meals. Highly elevated plasma levels of a number of cyclic dipeptides and other AA metabolites were found following intake of the WH meal and these metabolites are primary candidates to explain the superior insulinotropic effect of WH. The manufacturing process of WH caused oxidization of methionine to methionine sulfoxide which in turn caused in vivo generation of N-phenylacetyl-methionine and N-phenylacetyl-methionine sulfoxide. These two compounds have not previously been described in biological systems.

The precise pharmacological action of inchinkoto (ICKT, Yin-Chen-Hao-Tang in Chinese), a hepatoprotective herbal medicine, on total metabolic pathways has not been well investigated. The aim of this study was to explore the serum metabolites reflecting the pharmacological activity of ICKT, and mechanism of action of ICKT using serum metabolome analysis. 54 patients with obstructive jaundice due to malignancies were included in this study. ICKT was administered for 3 days. Serum and bile samples were collected before and 1 h after ICKT administration on days 1 and 4. Serum metabolome analysis including ICKT components were performed. The levels of total/direct bilirubin, C-reactive protein, γ-glutamyl transpeptidase, and albumin in the serum were significantly improved after ICKT administration. In the serum metabolome analysis, inosine was the only elevated metabolite on days 1 and 4. Most of the metabolites which were significantly changed after ICKT administration were lipid mediators, and all decreased on day 1. Notably, the levels of many lipid mediators were increased on day 4. The difference in serum aspartic acid 1 h after ICKT administration was significantly correlated with a decrease in the levels of total bilirubin in the serum on day 4. Using metabolome analysis, we demonstrated several metabolic changes that may be associated with the pharmacological mechanisms of ICKT. The biological implications of these metabolites should be further investigated in basic research studies.

The safety assessment of foods and feeds from genetically modified (GM) crops includes the comparison of key characteristics, such as crop composition, agronomic phenotype and observations from animal feeding studies compared to conventional counterpart varieties that have a history of safe consumption, often including a near isogenic variety. The comparative compositional analysis of GM crops has been based on targeted, validated, quantitative analytical methods for the key food and feed nutrients and antinutrients for each crop, as identified by Organization of Economic Co-operation and Development (OCED). As technologies for untargeted metabolomic methods have evolved, proposals have emerged for their use to complement or replace targeted compositional analytical methods in regulatory risk assessments of GM crops to increase the number of analyzed metabolites. The technical opportunities, challenges and strategies of including untargeted metabolomics analysis in the comparative safety assessment of GM crops are reviewed. The results from metabolomics studies of GM and conventional crops published over the last eight years provide context to enable the discussion of whether metabolomics can materially improve the risk assessment of food and feed from GM crops beyond that possible by the Codex-defined practices used worldwide for more than 25 years. Published studies to date show that environmental and genetic factors affect plant metabolomics profiles. In contrast, the plant biotechnology process used to make GM crops has little, if any consequence, unless the inserted GM trait is intended to alter food or feed composition. The nutritional value and safety of food and feed from GM crops is well informed by the quantitative, validated compositional methods for list of key analytes defined by crop-specific OECD consensus documents. Untargeted metabolic profiling has yet to provide data that better informs the safety assessment of GM crops than the already rigorous Codex-defined quantitative comparative assessment. Furthermore, technical challenges limit the implementation of untargeted metabolomics for regulatory purposes: no single extraction method or analytical technique captures the complete plant metabolome; a large percentage of metabolites features are unknown, requiring additional research to understand if differences for such unknowns affect food/feed safety; and standardized methods are needed to provide reproducible data over time and laboratories.

The rapid growth in the worldwide use of plastics has resulted in a vast accumulation of microplastics in the air, soil and water. The impact of these microplastics on pregnancy and fetal development remains largely unknown. In pregnant mice, we recently demonstrated that exposure to micro- and nanoplastics throughout gestation resulted in significant fetal growth restriction. One possible explanation for reduced fetal growth is abnormal placental metabolism. To evaluate the effect of maternal exposure to microplastics on placental metabolism. In the present study, CD-1 pregnant mice were exposed to 5 μm polystyrene microplastics in filtered drinking water at one of four concentrations (0 ng/L (controls), 102 ng/L, 104 ng/L, 106 ng/L) throughout gestation (n = 7–11/group). At embryonic day 17.5, placental tissue samples were collected (n = 28–44/group). Metabolite profiles were determined using 1 H high-resolution magic angle spinning magnetic resonance spectroscopy. The relative concentration of lysine (p = 0.003) and glucose (p < 0.0001) in the placenta were found to decrease with increasing microplastic concentrations, with a significant reduction at the highest exposure concentration. Multivariate analysis identified shifts in the metabolic profile with MP exposure and pathway analysis identified perturbations in the biotin metabolism, lysine degradation, and glycolysis/gluconeogenesis pathways. Maternal exposure to microplastics resulted in significant alterations in placental metabolism. This study highlights the potential impact of microplastic exposure on pregnancy outcomes and that efforts should be made to minimize exposure to plastics, particularly during pregnancy.

Biomarkers for the development of type 2 diabetes (T2D) are useful for prediction and intervention of the disease at earlier stages. In this study, we performed a longitudinal study of changes in metabolites using an animal model of T2D, the spontaneously diabetic Torii (SDT) rat. Fasting plasma samples of SDT and control Sprague-Dawley (SD) rats were collected from 6 to 24 weeks of age, and subjected to gas chromatography–mass spectrometry-based metabolome analysis. Fifty-nine hydrophilic metabolites were detected in plasma samples, including amino acids, carbohydrates, sugars and organic acids. At 12 weeks of age, just before the onset of diabetes in SDT rats, the amounts of nine of these metabolites (asparagine, glutamine, glycerol, kynurenine, mannose, n-alpha-acetyllysine, taurine, threonine, and tryptophan) in SDT rats were significantly different from those in SD rats. In particular, metabolites in the tryptophan metabolism pathway (tryptophan and kynurenine) were decreased in SDT rats at 12 weeks of age and later. The lower tryptophan and kynurenine levels in the prediabetic state and later were further confirmed by a replication study on SDT rats and by a longitudinal study on another animal model of T2D, the Otsuka Long-Evans Tokushima Fatty rat. Our data indicate that tryptophan and its metabolites are potential biomarkers for prediabetes and that tryptophan metabolism may be a potential target of intervention for treatment of the disease.

Việc xác định chất chuyển hóa trong các mẫu sinh học bằng phổ cộng hưởng từ hạt nhân (NMR) là một nhiệm vụ khó khăn do độ phức tạp của các ma trận sinh học. Bài báo này giới thiệu một sơ đồ tính toán tự động mới cho việc xác định các chất chuyển hóa trong phổ 1D 1H NMR dựa trên Cơ sở Dữ liệu Chất chuyển hóa Con người. Sơ đồ phương pháp bao gồm các bước áp dụng tuần tự của tiền xử lý, giảm dữ liệu, sàng lọc chất chuyển hóa và lựa chọn sự kết hợp. Sơ đồ được đề xuất đã được thử nghiệm trên phổ 1D 1H NMR của: (a) một hỗn hợp axit amin, (b) một mẫu huyết thanh được pha trộn với hỗn hợp axit amin, (c) 20 mẫu huyết thanh, (d) 20 mẫu dịch ối của người, (e) 160 mẫu huyết thanh từ cơ sở dữ liệu công khai. Sơ đồ phương pháp đã được so sánh với các công cụ phần mềm được sử dụng rộng rãi, cho thấy hiệu suất tốt về việc xác định chính xác các chất chuyển hóa. Sơ đồ mạnh mẽ này đạt được khả năng xác định tự động các đỉnh cộng hưởng trong phổ 1H-NMR với độ chính xác cao và ít can thiệp của con người với nhiều ứng dụng trong phân tích chuyển hóa.