¹H NMR-based urine metabolomics for the evaluation of kidney injury in Wistar rats by 3-MCPD

Abstract

The cause of toxicity induced by 3-chloro-1,2-propanediol (3-MCPD) remains under investigation, and progress towards understanding this toxicity has been limited by the lack of sensitive and reliable biomarkers. Global metabolomics were analyzed to characterize the phenotypical biochemical perturbations and potential mechanisms of the 3-MCPD-induced toxicity. 3-MCPD was administered to Wistar rats (60 mg per kg bw, oral) for 7, 21, and 35 days and urine samples were collected at each time point. The urinary metabolomics was performed by H NMR, and the NMR spectrum signals of the detected metabolites were normalized and analyzed by orthogonal pattern recognition methods (PCA and OPLS-DA). This analysis revealed a time- and dose-dependency of the biochemical perturbations induced by 3-MCPD toxicity. Several metabolites responsible for glycine, serine and threonine metabolism, taurine and hypotaurine metabolism and nicotinate and nicotinamide metabolism revealed that 3-MCPD produced serious kidney toxicity, consistent with clinical biochemistry and histopathology. Significant changes in seven identified metabolites were validated as phenotypic biomarkers of 3-MCPD toxicity. Overall, our work demonstrates the powerful use of metabolomics for improved detection of toxicity and biomarker discovery and highlights the powerful predictive potential of such analyses for understanding food toxicity.

Kidney Tissue Targeted Metabolic Profiling of Unilateral Ureteral Obstruction Rats by NMR

“…The validity of the model is evaluated by the CV-ANOVA method at the level of p < 0.05 (Hao et al, 2016 ). The corresponding S-plots, where each point represents a single NMR spectral region segment, were used to identify which spectral variables contributed to the separation of the samples on the scores plot (Ji et al, 2016 ). Variable importance in the projection (VIP) values and coefficients were also applied to screen the important variables.…”

Absorption, Distribution, Metabolism and Excretion of 3-MCPD 1-Monopalmitate after Oral Administration in Rats

“…18 In 2016, the metabolomic study of free 3-MCPD in Wistar rats was evaluated; the results indicated that the metabolism of glycine, serine, and threonine and that of taurine and hypotaurine were two key pathways related to 3-MCPD. 19 Until now, no systematic research about the ADME situation of 3-MCPD esters in vivo was reported. Due to this fact, a systematic study on the absorption, distribution, metabolism, and excretion of 3-MCPD esters in vivo was performed.…”

“…ADME may alter the pharmacokinetics of food components and consequently influence their beneficial or toxicological activities at a selected organ or tissue. Only a few studies report the metabolism and metabonomics of 3-MCPD and its fatty acid esters in vivo and their metabonomic results in rat urine and the cultured cells. − In 2013, Li and colleagues reported that indoxyl sulfate, xanthurenic acid, phenylacetylglycine, nonanedioic acid, and taurine can be used as biomarkers and represent the consumption of 3-MCPD esters in a long-term toxicity study . In 2015, Andreoli and colleagues reported that 2,3-dihydroxypropyl mercapturic acid (DHPMA) was detected and identified as the metabolite of free 3-MCPD in human urine .…”

“…In 2015, Andreoli and colleagues reported that 2,3-dihydroxypropyl mercapturic acid (DHPMA) was detected and identified as the metabolite of free 3-MCPD in human urine . In 2016, the metabolomic study of free 3-MCPD in Wistar rats was evaluated; the results indicated that the metabolism of glycine, serine, and threonine and that of taurine and hypotaurine were two key pathways related to 3-MCPD . Until now, no systematic research about the ADME situation of 3-MCPD esters in vivo was reported.…”

A scoring metric for multivariate data for reproducibility analysis using chemometric methods

“…In chemometrics and information theory, there are several common metrics used for pattern recognition [10–16]. It is important to mention the Euclidean distance [17–20] and the Mahalanobis distance [21–26] as the most used, however, there are other metrics based on a probabilistic approach [27], for example, the Hellinger distance [28], the Kullback-Leibler divergence [29] and the Jensen-Shannon distance [30, 31].…”