Strategy for NMR metabolomic analysis of urine in mouse models of obesity--from sample collection to interpretation of acquired data.
The mouse model of monosodium glutamate induced obesity was used to examine and consequently optimize the strategy for analysis of urine samples by NMR spectroscopy. A set of nineteen easily detectable metabolites typical in obesity-related studies was selected. The impact of urine collection protocol, choice of (1)H NMR pulse sequence, and finally the impact of the normalization method on the detected concentration of selected metabolites were investigated. We demonstrated the crucial effect of food intake and diurnal rhythms resulting in the choice of a 24-hour fasting collection protocol as the most convenient for tracking obesity-induced increased sensitivity to fasting. It was shown that the Carr-Purcell-Meiboom-Gill (CPMG) experiment is a better alternative to one-dimensional nuclear Overhauser enhancement spectroscopy (1D-NOESY) for NMR analysis of mouse urine due to its ability to filter undesirable signals of proteins naturally present in rodent urine. Normalization to total spectral area provided comparable outcomes as did normalization to creatinine or probabilistic quotient normalization in the CPMG-based model. The optimized approach was found to be beneficial mainly for low abundant metabolites rarely monitored due to their overlap by strong protein signals.
Institute of Microbiology, Academy of Sciences of the Czech Republic, Vídeňská 1083, 142 20 Prague 4, Czech Republic; Department of Analytical Chemistry, Faculty of Science, Palacký University, 17. listopadu 1192/12, 771 46 Olomouc, Czech Republic.
Helena
H
Pelantová
Institute of Microbiology, Academy of Sciences of the Czech Republic, Vídeňská 1083, 142 20 Prague 4, Czech Republic; Faculty of Chemical Technology, University of Chemistry and Technology Prague, Technická 5, 166 28 Prague 6, Czech Republic.
Martina
M
Bugáňová
Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Technická 2, 166 27 Prague 6, Czech Republic.
Jiří
J
Anýž
Institute of Organic Chemistry and Biochemistry, Academy of Sciences of the Czech Republic, Flemingovo nám. 2, 166 10 Prague 6, Czech Republic.
Blanka
B
Železná
Institute of Organic Chemistry and Biochemistry, Academy of Sciences of the Czech Republic, Flemingovo nám. 2, 166 10 Prague 6, Czech Republic.
Lenka
L
Maletínská
Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Technická 2, 166 27 Prague 6, Czech Republic.
Daniel
D
Novák
3rd Medical Department, 1st Faculty of Medicine, Charles University and General Faculty Hospital in Prague, U nemocnice 1, 128 08 Prague 2, Czech Republic.
Martin
M
Haluzík
Institute of Microbiology, Academy of Sciences of the Czech Republic, Vídeňská 1083, 142 20 Prague 4, Czech Republic.
Marek
M
Kuzma
D000818:Animals; D000831:Animals, Newborn; D015415:Biomarkers / Q000652:urine*; D003627:Data Interpretation, Statistical; D004195:Disease Models, Animal; D008297:Male; D055442:Metabolome; D055432:Metabolomics / Q000379:methods*; D008815:Mice, Inbred Strains; D019906:Nuclear Magnetic Resonance, Biomolecular / Q000379:methods*; D009765:Obesity / Q000378:metabolism*; D025341:Principal Component Analysis; D013048:Specimen Handling
D015415:Biomarkers
Mouse; NMR metabolomics; Obesity; Urine