Optimization of NMR analysis of biological fluids for quantitative accuracy
With the rising interest in the use of nuclear magnetic resonance (NMR) for the study of biological fluids such as urine and serum for metabonomic or diagnostic purposes, new challenges have arisen concerning the efficacy of NMR data acquisition and analysis. In particular the quantification of sample constituents such as metabolites is of great importance. This study compares five one-dimensional proton NMR pulse sequences using synthetic urine samples to determine appropriate acquisition parameters for reasonable sample throughput and accuracy. Each pulse sequence has its own advantages and limitations with respect to solvent suppression, stable baseline, exchangeable protons, and quantization of resonances near the residual water peak. Hardware issues such as low-pass filters, unique to each spectrometer, also impact quantitation accuracy. Metabolite concentrations were determined using integration referenced to an added internal standard, and using the Chenomx NMR Suite software package. Since nuclei in different metabolites and the internal standard all have different longitudinal relaxation rates (T 1) we included a mathematical correction factor for quantitation.
KeywordsNMR metabonomics quantitation accuracy metabolite
The authors would like to thank Dr. Ryan McKay for his helpful suggestions and assistance, Bruce Lix for many discussions and help in experiment design, Angela Thiessen for sample preparation and analysis, James Oikawa and Chenomx Inc. for sample preparation, Pascal Mercier for his helpful discussion and assistance with Chenomx software, and Jeff Devries for his technical assistance with spectrometer hardware. This research was supported by the Canadian Institutes of Health Research (CIHR), Genome Prairie, and Genome Canada. We would like to thank the Canadian National High Field NMR Centre (NANUC) for their assistance and use of the facilities. Operation of NANUC is funded by CIHR, the Natural Science and Engineering Research Council of Canada and the University of Alberta.
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