| 1. |
- Hålldin, Elin, et al.
(författare)
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Factors Explaining Interpersonal Variation in Plasma Enterolactone Concentrations in Humans
- 2019
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Ingår i: Molecular Nutrition and Food Research. - : Wiley. - 1613-4125 .- 1613-4133. ; 63:16
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Forskningsöversikt (refereegranskat)abstract
- Lignans are diphenolic plant compounds with potential health modulating properties that are absorbed to the circulation and metabolized to the enterolignans enterodiol (END) and enterolactone (ENL) by gut microbiota. Epidemiological studies have inconsistently shown that a high lignan intake and circulating ENL are associated with reduced risk of breast-, prostate-, and colorectal cancer as well as cardiovascular disease and total and cause-specific mortality. Inconsistencies can be due to interpersonal variation of ENL formation or responses. The aim of this review is to identify and evaluate the impact of factors influencing variability in plasma concentrations of the main enterolignan, ENL. The main determinants of plasma ENL concentrations are intake of lignan and lignan-rich foods, composition and activity of intestinal microflora, antimicrobial use, nutrient intake, BMI, smoking, sex, and age. Composition and activity of the intestinal microbiota appear to be the most critical factor governing interpersonal variability in plasma ENL concentration followed by the use of antibiotics. Future studies with combined data from gut microbiota and metabolomics with food intake and life style data can be used to estimate the relative contribution of the different factors to ENL concentration in quantitative terms.
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| 2. |
- Koistinen, Ville Mikael, et al.
(författare)
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Interlaboratory coverage test on plant food bioactive compounds and their metabolites by mass spectrometry-based untargeted metabolomics
- 2018
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Ingår i: Metabolites. - : MDPI AG. - 2218-1989 .- 2218-1989. ; 8:3
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Tidskriftsartikel (refereegranskat)abstract
- Bioactive compounds present in plant-based foods, and their metabolites derived from gut microbiota and endogenous metabolism, represent thousands of chemical structures of potential interest for human nutrition and health. State-of-the-art analytical methodologies, including untargeted metabolomics based on high-resolution mass spectrometry, are required for the profiling of these compounds in complex matrices, including plant food materials and biofluids. The aim of this project was to compare the analytical coverage of untargeted metabolomics methods independently developed and employed in various European platforms. In total, 56 chemical standards representing the most common classes of bioactive compounds spread over a wide chemical space were selected and analyzed by the participating platforms (n = 13) using their preferred untargeted method. The results were used to define analytical criteria for a successful analysis of plant food bioactives. Furthermore, they will serve as a basis for an optimized consensus method.
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| 3. |
- Low, Dorrain Yanwen, et al.
(författare)
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Data sharing in PredRet for accurate prediction of retention time: Application to plant food bioactive compounds
- 2021
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Ingår i: Food Chemistry. - : Elsevier BV. - 0308-8146 .- 1873-7072. ; 357
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Tidskriftsartikel (refereegranskat)abstract
- Prediction of retention times (RTs) is increasingly considered in untargeted metabolomics to complement MS/MS matching for annotation of unidentified peaks. We tested the performance of PredRet (http://predret.org/) to predict RTs for plant food bioactive metabolites in a data sharing initiative containing entry sets of 29–103 compounds (totalling 467 compounds, >30 families) across 24 chromatographic systems (CSs). Between 27 and 667 predictions were obtained with a median prediction error of 0.03–0.76 min and interval width of 0.33–8.78 min. An external validation test of eight CSs showed high prediction accuracy. RT prediction was dependent on shape and type of LC gradient, and number of commonly measured compounds. Our study highlights PredRet's accuracy and ability to transpose RT data acquired from one CS to another CS. We recommend extensive RT data sharing in PredRet by the community interested in plant food bioactive metabolites to achieve a powerful community-driven open-access tool for metabolomics annotation.
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