A quantum mechanics-based approach for optimization of metabolite basis-sets. Application to quantitation of HRMAS-NMR signals
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文摘
High-resolution magic angle spinning (HRMAS) Nuclear magnetic resonance (NMR) 1H spectroscopy is playing an increasingly important role for diagnosis. This technique enables setting up metabolite profiles of ex vivo pathological and healthy tissue. Automatic quantitation of HRMAS signals provides reliable reference profiles useful to monitor diseases and pharmaceutical follow-up. However for several metabolites, the values of chemical shifts of proton groups may slightly differ according to the microenvironment in the tissue or cells, in particular to its pH. This hampers accurate estimation of the metabolite concentrations mainly when using quantitation algorithms based on a metabolite basis-set: the metabolite fingerprints are not correct anymore. In this work, we propose an accurate method based on quantum mechanical (QM) simulations. The proposed algorithm automatically corrects mismatches between the signal under analysis and the signals of the simulated basis-set by modifying the basis-set signals. In the optimization procedure, the basis-set signals are simulated again by varying the chemical shifts of metabolites in the QM procedure. Cross-correlation was used as cost function to measure how well the signals match each other. The proposed method, QM-QUEST, provides more robust fitting while limiting user involvement and respects the correct fingerprints of metabolites. Its efficiency is demonstrated by accurately quantitating signals from tissue samples of human brains with oligodendroglioma.