Tissue, urine and serum NMR metabolomics dataset from a 5/6 nephrectomy rat model of chronic kidney disease

Abstract

Serum, urine and tissue from a rat model of chronic kidney disease (CKD) were analysed using nuclear magnetic resonance (NMR) spectroscopy-based metabolomics methods, and compared with samples from sham operated rats. Both urine and serum were sampled at multiple timepoints, and the results have been reported elsewhere ( https://doi.org/10.1007/s11306-019-1569-3 [1] ). The data could be useful to researchers working with human CKD or rat models of the disease. In addition, several different types of NMR spectra were recorded, including 1D NOESY, CPMG, and 2D J-resolved spectra, and the data could be useful for method comparison and algorithm development, both in terms of NMR spectroscopy and multivariate analysis.

Personalized Metabolic Profile by Synergic Use of NMR and HRMS

“…The other is the completeness of the matrix because if there are too many missing values, the classification ability or the detection of correlations between metabolites becomes weaker [ 28 ]. In our experience and from analyzing the literature on NMR urine metabolomics, the maximum number of metabolites quantified in at least 80% of samples is around 50–60 [ 10 , 11 , 12 , 13 , 14 , 15 ]. This number is far from that achieved in LC-MS studies, which have reached more than a thousand [ 29 ].…”

“…For example, a study performed at two different fields (600 and 700 MHz) starting from a list of 151 metabolites that are potentially quantifiable in urine showed that only 50 presented data strongly correlated between the values obtained at the two magnetic fields [ 9 ]. This result represents a limit of quantifiable compounds in urine using NMR, and most studies in the literature have used a dataset of this size [ 10 , 11 , 12 , 13 , 14 , 15 ]. However, in one case, it was possible to reach 209 quantified metabolites [ 16 ], but only a fraction was detected in more than 80% of the samples.…”

Personalized metabolic profile by synergic use of NMR and HRMS

“…The other parameter is the completeness of the matrix, because if there are too many missing values, the classi cation or detection of correlations between metabolites will be weaker 25 . In our experience, and analyzing the literature on NMR urine metabolomics, the maximum number of metabolites that can be quanti ed using this technique in at least 80% of the samples is around 50-60 [12][13][14][15][16][17] . This number is far from that achieved in LC-MS studies, which in the case of BC, for example, can reach more than a thousand 26 .…”

“…In a study performed at two different elds (600 and 700 MHz), and using a list of 151 metabolites potentially quanti able in urine, it was found that only 33% (50 metabolites) presented data that correlated strongly between the values obtained in the two experimental conditions 11 . This result sets a limit to the number of compounds that can be accurately quanti ed in urine using NMR and all studies in the literature use a dataset comprising a number similar to this [12][13][14][15][16][17] .…”

“…O was from Cambridge Isotope Laboratories, Inc. (Andover, MA, USA); anthranilic acid-ring-13 C 6 ( 13 C 6 -AA) and 3-(trimethylsilyl)-2,2,3,3-d propionic acid (TSP) was from Sigma-Aldrich (Schnelldorf, Germany); 15 N, 13 C 2 -3-Hydroxy-DL-kynurenine ( 15 N-13 C 2 -OH-KYN) was from AMRI (Albany, NY, USA).…”