Lack of reliable peak detection impedes automated analysis of large-scale gas chromatography-mass spectrometry (GC-MS) metabolomics datasets. Performance and outcome of individual peak-picking ...algorithms can differ widely depending on both algorithmic approach and parameters, as well as data acquisition method. Therefore, comparing and contrasting between algorithms is difficult. Here we present a workflow for improved peak picking (WiPP), a parameter optimising, multi-algorithm peak detection for GC-MS metabolomics. WiPP evaluates the quality of detected peaks using a machine learning-based classification scheme based on seven peak classes. The quality information returned by the classifier for each individual peak is merged with results from different peak detection algorithms to create one final high-quality peak set for immediate down-stream analysis. Medium- and low-quality peaks are kept for further inspection. By applying WiPP to standard compound mixes and a complex biological dataset, we demonstrate that peak detection is improved through the novel way to assign peak quality, an automated parameter optimisation, and results in integration across different embedded peak picking algorithms. Furthermore, our approach can provide an impartial performance comparison of different peak picking algorithms. WiPP is freely available on GitHub (https://github.com/bihealth/WiPP) under MIT licence.
Cyclic fatty acid monomers (CFAM) are mainly formed during heat treatments, such as frying, of edible oils. These fatty acids are mixtures of disubstituted five- or six-carbon-membered ring ...structures. Some earlier studies have suggested that some of these molecules could be metabolized and detoxified, but so far, neither the detoxification mechanisms nor the metabolite identifications have been elucidated. The objective of the present study was to identify the metabolites resulting from the metabolism and detoxification of CFAM. A deuterium-labeled CFAM, 9-
2
H-10-(6-propyl-2-cyclohexenyl)-dodecenoic acid, was synthesized and fed to rats for 3 days, along with a standard chow diet while the control group was fed the same chow diet which did not contain any CFAM. Biological fluids (urine, blood) were collected for both groups of rats and analyzed using an untargeted metabolomic approach by ultra-performance liquid chromatography coupled with mass spectrometry. Two discriminant metabolites and 18 molecules derived from CFAM were identified or tentatively identified in plasma and urine samples, respectively. The structures of the metabolites suggest that CFAM having a six-carbon-membered ring could be detoxified by the classical drug metabolic pathway (phase I and phase II reactions), but our study also indicates that these are substrates for the β-oxidation pathway and eliminated as glucuronide, sulphate, and/or nitrate conjugates. Urine metabolomics investigations without diet effects have indicated a higher excretion of medium-chain acylcarnitines in the D-CFAM diet group, which may indicate an incomplete β-oxidation.
Foods of plant origin contain a large number of phytochemicals that may positively affect health. Phytochemicals are largely excreted in urine as metabolites that are formed in host tissues or by the ...microbiota and constitute a great proportion of the urinary metabolome. The latter can be characterized by a metabolomics approach. In this work, we compared the metabolism of lignins to that of the structurally related ferulic acid (FA) and sinapic acid (SA). Five groups of rats (n = 5) were fed for 2 d a purified diet alone control (C) or supplemented with lignin-enriched wheat bran (3% of the diet, wt:wt), poplar wood lignins (0.42%), FA (0.42%), or SA (0.42%). The metabolomes of urine samples collected after 1 and 2 d of supplementation were analyzed by high-resolution MS (liquid chromatography/quadrupole time-of-flight). Comparing metabolic fingerprints by gathering semiquantitative information on several hundreds of metabolites and using multivariate statistical analysis (partial least squares for discriminant analysis) showed the similarity between both lignin-supplemented and C groups and confirmed that lignins are largely inert and not absorbed in the body. One the other hand, metabolic fingerprints of the 2 phenolic acid-supplemented groups were clearly distinct from the C group. Differences between the groups were mainly from nonmetabolized FA and SA and metabolites excreted in urine. Thirteen of them were identified as sulfate esters and glucuronide and glycine conjugates of the same phenolic acids, and of dihydrosinapic, vanillic, and benzoic acids. This study shows that metabolomics allows the identification of new metabolites of phytochemicals and can be used to distinguish individuals fed different phytochemical-containing foods.
Metabolomics generates massive and complex data. Redundant different analytical species and the high degree of correlation in datasets is a constraint for the use of data mining/statistical methods ...and interpretation. In this context, we developed a new tool to detect analytical correlation into datasets without confounding them with biological correlations. Based on several parameters, such as a similarity measure, retention time, and mass information from known isotopes, adducts, or fragments, the algorithm principle is used to group features coming from the same analyte, and to propose one single representative per group. To illustrate the functionalities and added-value of this tool, it was applied to published datasets and compared to one of the most commonly used free packages proposing a grouping method for metabolomics data: 'CAMERA'. This tool was developed to be included in Galaxy and will be available in Workflow4Metabolomics (http://workflow4metabolomics.org). Source code is freely available for download under CeCILL 2.1 license at https://services.pfem.clermont.inra.fr/gitlab/grandpa /tool-acf and implement in Perl.
Some epidemiological studies show that heme iron consumption, in red meat, is associated to the development of several chronic diseases, including cancers and cardio-metabolic diseases. As heme iron ...intestinal absorption is finely regulated, we hypothesized that heme iron may act indirectly, through the peroxidation of dietary lipids, in food or in the intestinal lumen during digestion. This heme-iron-induced lipid peroxidation provokes the generation of toxic lipid oxidation products that could be absorbed, such as 4-hydroxynonenal (HNE). In a first experiment, heme iron given to rats by oral gavage together with the linoleic-acid-rich safflower oil induced the formation of HNE in the intestinal lumen. The HNE major urinary metabolite was elevated in the urine of the treated rats, indicating that this compound has been absorbed. In a second experiment, we showed that stable isotope-labeled HNE given orally to rats was able to reach non-intestinal tissues as a bioactive form and to make protein-adducts in heart, liver and skeletal muscle tissues. The presence of HNE-protein adducts in those tissues suggests a putative biological role of diet-originating HNE in extra-intestinal organs. This finding could have major consequences on the onset/development of chronic diseases associated with red meat over-consumption, and more largely to peroxidation-prone food consumption.
There is a growing interest in studying the nutritional effects of complex diets. For such studies, measurement of dietary compliance is a challenge because the currently available compliance markers ...cover only limited aspects of a diet. In the present study, an untargeted metabolomics approach was used to develop a compliance measure in urine to distinguish between two dietary patterns. A parallel intervention study was carried out in which 181 participants were randomized to follow either a New Nordic Diet (NND) or an Average Danish Diet (ADD) for 6 months. Dietary intakes were closely monitored over the whole study period, and 24 h urine samples as well as weighed dietary records were collected several times during the study. The urine samples were analyzed by UPLC-qTOF-MS, and a partial least-squares discriminant analysis with feature selection was applied to develop a compliance model based on data from 214 urine samples. The optimized model included 52 metabolites and had a misclassification rate of 19% in a validation set containing 139 samples. The metabolites identified in the model were markers of individual foods such as citrus, cocoa-containing products, and fish as well as more general dietary traits such as high fruit and vegetable intake or high intake of heat-treated foods. It was easier to classify the ADD diet than the NND diet probably due to seasonal variation in the food composition of NND and indications of lower compliance among the NND subjects. In conclusion, untargeted metabolomics is a promising approach to develop compliance measures that cover the most important discriminant metabolites of complex diets.
In this paper, we propose a hybrid and exploratory knowledge discovery approach for analyzing metabolomic complex data based on a combination of supervised classifiers, pattern mining and Formal ...Concept Analysis (FCA). The approach is based on three main operations, preprocessing, classification, and postprocessing. Classifiers are applied to datasets of the form individuals × features and produce sets of ranked features which are further analyzed. Pattern mining and FCA are used to provide a complementary analysis and support for visualization. A practical application of this framework is presented in the context of metabolomic data, where two interrelated problems are considered, discrimination and prediction of class membership. The dataset is characterized by a small set of individuals and a large set of features, in which predictive biomarkers of clinical outcomes should be identified. The problems of combining numerical and symbolic data mining methods, as well as discrimination and prediction, are detailed and discussed. Moreover, it appears that visualization based on FCA can be used both for guiding knowledge discovery and for interpretation by domain analysts.
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