An algorithm for the automated quantitation of metabolites in in vitro NMR signals.
The quantitation of metabolite concentrations from in vitro NMR spectra is hampered by the sensitivity of peak positions to experimental conditions. The quantitation methods currently available are generally labor intensive and cannot readily be automated. Here, an algorithm is presented for the automatic time domain analysis of high-resolution NMR spectra. The TARQUIN algorithm uses a set of basis functions obtained by quantum mechanical simulation using predetermined parameters. Each basis function is optimized by subdividing it into a set of signals from magnetically equivalent spins and varying the simulated chemical shifts of each of these groups to match the signal undergoing analysis. A novel approach to the standard multidimensional minimization problem is introduced based on evaluating the fit resulting from different permutations of possible chemical shifts, obtained from one-dimensional searches. Results are presented from the analysis of (1)H proton magic angle spinning spectra of cell lines illustrating the robustness of the method in a typical application. Simulation was used to investigate the biggest peak shifts that can be tolerated.
Reynolds
Greg
G
Department of Electronic, Electrical, and Computer Engineering, University of Birmingham, UK. gmr001@bham.ac.uk
Wilson
Martin
M
Peet
Andrew
A
Arvanitis
Theodoros N
TN
D000465:Algorithms; D001704:Biopolymers / Q000032:analysis*; D001921:Brain / Q000378:metabolism*; D002460:Cell Line; D006801:Humans; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D009474:Neurons / Q000378:metabolism*; D011522:Protons
D001704:Biopolymers; D011522:Protons