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- aggregation classification "C3".
- aggregation creator person.
- aggregation creator person.
- aggregation date "2014".
- aggregation hasFormat 5786793.bibtex.
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- aggregation hasFormat 5786793.dc.
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- aggregation hasFormat 5786793.doc.
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- aggregation language "eng".
- aggregation subject "Biology and Life Sciences".
- aggregation title "Metabolic fingerprinting of the human gastrointestinal phenotype in health and disease".
- aggregation abstract "Introduction and Objectives: An increasing awareness exists that many intestinal diseases (e.g. colorectal cancer (CRC), inflammatory bowel diseases (IBD)) are intrinsically linked to alterations/perturbations in the mammalian-microbial symbiosis (known as dysbiosis). Intestinal dysfunctions can lead to alterations in the composition of the microbiota, which in turn has a significant impact on the gastrointestinal digestion, and as such on the human gastrointestinal metabolic phenotype. The goal of this study was to develop a generic sample clean-up and innovative analytical method that enables to monitor the metabolic changes of an individual or changes related to certain intestinal diseases (CRC and IBD). A first batch of human fecal samples was analyzed by means of high resolution mass spectrometry (HRMS) to enable metabolic fingerprinting i.e. provide an overview of all metabolites present in the investigated biological matrix and display the discriminating potential of this technique. Materials and Methods: Fecal samples were collected from healthy (n=10) and diseased individuals (IBD, n=10). To eliminate microbial activity, the samples were lyophilized and afterwards individually homogenized to powder. For the extraction of the fecal metabolites, a sequential strategy of experimental designs (fractional factorial design followed by a response surface model by Modde 5.0, Umetrics, Sweden) was used to optimize the generic extraction, which was performed on a pool of freeze-dried (FD) feces (n=6). The ensure the holistic nature of the analytical untargeted full scan detection method (UHPLC-Orbitrap HRMS), the method development started off with a targeted database (n=115) of small molecules related to gastro-intestinal digestion (amino acids, amines, bile acids, carbohydrates, carboxyclic acids, phenolics, polyols, short chain fatty acids, etc.), characterized with a wide range of physico-chemical properties. Results and Discussion: The full factorial design indicated that the mass of the FD feces (200 mg), pre-extraction with ultrapure water and extraction volume (1 mL) were significant influencing parameters. During the second optimization step, i.e. response surface model, the benefit of diluting the extracted samples (1/3) for reducing matrix suppression during analysis became clear. The optimization of the UHPLC-Orbitrap MS method resulted in the detection of 108 compounds of 115, which indicates the holistic nature of the method for polar to relatively polar molecules. Orthogonal partial least square analysis (untargeted) and heat map visualization (targeted) on the UHPLC-HRMS analyzed fecal samples (healthy and diseased individuals) displayed a clear clustering between the different groups (healthy vs. IBD) and a variation in metabolic phenotypes, respectively. Future studies, will adverse this method to discover potential biomarkers specific for IBD patients.".
- aggregation authorList BK332945.
- aggregation isDescribedBy 5786793.
- aggregation similarTo LU-5786793.