Abstract

A brief overview of the potentiality and use of the metabolic fingerprint of a system or biological process is here proposed. The information on the type, quantity and variation of the pool of metabolites and its relationship with a given biological process is commonly referred to as metabolomics. One powerful analytical approach to the detection and quantitation of metabolites is by Nuclear Magnetic Resonance Spectroscopy (NMR). Additionally, the recently introduced High Resolution Magic Angle Spinning (HR-MAS) NMR approach improved dramatically the potentiality of the method allowing direct sampling of ex vivo specimens, such as tissues and cells, without any pre-treatment or extraction steps. The NMR data can be processed towards the target or non-target analysis of the metabolites. The former passes through the identification of all the metabolites, the latter adopts a multivariate statistical approach such as Principal Components Analysis. In this article, the main methodological points of NMR analysis with multivariate statistics are briefly outlined and discussed. A final case-study on the discrimination of healthy and neoplastic tissues via HR-MAS NMR metabolomics is reported as a paradigmatic application.

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