DATA MODELLING OF LC/MS-BASED METABOLOMIC PROFILING TO COMPARE BETWEEN HUMAN PLASMA AND URINE SAMPLES ASSOCIATED WITH BEETROOT JUICE
Data modelling- based untargeted metabolomic researches is one of the best approaches which can be used to compare among biological fluid samples to provide a comprehensive and reliable sight about the changes of metabolomic profiling. This study sought to compare between human urine and plasma to investigate metabolomic changes of a diet pre- and postintake beetroot juice that offer unique metabolomic fingerprint associated to the potential effects of beetroot juice. A current pilot study of metabolomic patterns used Liquid Chromatography coupled to Mass Spectrometer (LC-MS) to carry out an analysis for seventytwo plasma and urine samples, equally. Samples were collected from nine adult healthy subjects (4 samples per subject) at pre-, as baseline, and post-intake beetroot juice in three stages, after 2hrs, 4hrs, and 8hrs. On the basis of the validation of data modelling, robust separation was observed between urine samples pre and post-intake beetroot juice and was more fitting and significant than the separation between plasma samples. The results of pilot study indicate that metabolomics screening of urine samples may be the best tool and a potential approach to predict the metabolomic profiling than plasma samples to assess the metabolic effect of a diet pre- and post-intake beetroot juice. As a result of the effects of beetroot juice, the present results also uncover significantly changes in most important metabolites including amino acid, peptide, Co-factors and vitamins which may contribute to the consolidation of the using of plant metabolites and natural substances to synthesis the nanoparticles for the biomedical applications.
Keywords: Metabolomic Profiling, Beetroot Juice (BJ), Biological Fluid, LC-MS, Principal Components Analysis (PCA), Orthogonal Partial Least Squares- Discriminant Analysis (OPLSDA)