Computational protocol: Metabonomics evaluations of age-related changes in the urinary compositions of male Sprague Dawley rats and effects of data normalization methods on statistical and quantitative analysis

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Protocol publication

[…] NMR spectra were processed using ACD/Labs 1D NMR Manager (Toronto, Canada). The raw FIDs were zero filled to 131,072 points, multiplied by a 0.3 Hz exponential function and Fourier transformed. The transformed spectra were then phased using the "simple method" and baseline corrected using the "SpAveraging" method with a box half width of 61 points and a noise factor of 3. All spectra were autoreferenced to the TMSP peak at 0.0 ppm. The spectra were overlaid in the processing window and grouped. Dark regions containing the resonances for water, urea, and other NMR solvent peaks were removed prior to integration. The total NMR intensity without water, urea, TMSP and other solvent regions was recorded and the intensity of the TMSP was recorded separately. The intelligent bucketing module was employed for integration with the bucket width set to 0.04 ppm and the looseness set to 50% for bin size optimization. The table of integrals normalized to total spectra intensity was exported for statistical analysis. The table was also renormalized by three different factors to investigate the effects of normalization on the analysis. The renormalization factors included: weight, 1/weight, and concentration of creatinine.All statistical analyses of NMR data were done using Statistica version 6.0 (Statsoft, Tulsa, OK). Principle component analysis (PCA) based on covariance of the data was applied to the bucketed intensities. Metabolite identification within the individual spectra was accomplished using the Chenomx NMR Suite (Chenomx, Calgary, Canada), which has a database of >250 compounds. The concentrations obtained by Chenomx analysis were first normalized to the determined creatinine concentration and the data between two different studies compared. The concentrations were also normalized by the TMSP peak intensity divided by the total NMR intensity without water, urea, TMSP and solvent regions. This was done to reduce the effects of TMSP volatility and other experimental errors that result in variance in the TMSP peak since the Chenomx NMR Suite uses the TMSP peak area to quantify the concentrations of the metabolites detected in the spectra. […]

Pipeline specifications

Software tools Statistica, Chenomx NMR Suite
Applications Miscellaneous, NMR-based metabolomics
Organisms Rattus norvegicus
Diseases Multiple Sclerosis
Chemicals Oxygen, Citric Acid