Dietary restriction (DR) has many beneficial effects, but the detailed metabolic mechanism remains largely unresolved. As diet is essentially related to metabolism, we investigated the metabolite profiles of urines from control and DR animals using NMR and LC/MS metabolomic approaches. Multivariate analysis presented distinctive metabolic profiles and marker signals from glucuronide and glycine conjugation pathways in the DR group. Broad profiling of the urine phase II metabolites with neutral loss scanning showed that levels of glucuronide and glycine conjugation metabolites were generally higher in the DR group. The up-regulation of phase II detoxification in the DR group was confirmed by mRNA and protein expression levels of uridinediphospho-glucuronosyltransferase and glycine-N-acyltransferase in actual liver tissues. Histopathology and serum biochemistry showed that DR was correlated with the beneficial effects of low levels of serum alanine transaminase and glycogen granules in liver. In addition, the Nuclear factor (erythroid-derived 2)-like 2 signaling pathway was shown to be up-regulated, providing a mechanistic clue regarding the enhanced phase II detoxification in liver tissue. Taken together, our metabolomic and biochemical studies provide a possible metabolic perspective for understanding the complex mechanism underlying the beneficial effects of DR. It has been known for more than 70 years that dietary restriction (DR) 1 can extend the life span and delay the onset of age-related diseases, based on an early rodent study showing such effects (1). However, not until the 1980s was DR recognized as a good model for studying the mechanism of or inhibitory measures for aging (2). So far, extensive studies employing model organisms such as yeasts, nematodes, fruit flies, and rodents have shown that DR has beneficial effects in most of the species studied (for a review, see Ref.3). Most notably, a recent 20-year-long study showed that monkeys, the species closest to humans, also benefit from DR similarly (4). Although there has not been (or could not have been) a systematic study on the effects of DR on the human life span, several longitudinal studies strongly suggest that changes in dietary intake can affect the life span and/or disease-associated marker values greatly (5-7).This inverse correlation between dietary intake and longterm health strongly indicates that DR's effects should involve metabolism, and that DR elicits the reorganization of metabolic pathways. It also seems quite natural that something we eat should affect the body's metabolism. Despite this seemingly straightforward relationship between diet and metabolism, the mechanisms underlying the beneficial effects of DR are anything but simple. Intensive efforts, spanning decades, to understand the mechanisms of DR have identified several genes that might mediate the effects of DR, such as mTOR, IGF-1, AMPK, and SIRT1 (for a review, see Ref. 8). Still, most of them are involved in early nutrient-sensing steps, and specific metabolic pathway...

BackgroundSimvastatin, which is used to control elevated cholesterol levels, is one of the most widely prescribed drugs. However, a daily excessive dose can induce drug-toxicity, especially in muscle and liver. Current markers for toxicity reflect mostly the late stages of tissue damage; thus, more efficient methods of toxicity evaluation are desired.Methodology/Principal FindingsAs a new way to evaluate toxicity, we performed NMR-based metabonomics analysis of urine samples. Compared to conventional markers, such as AST, ALT, and CK, the urine metabolic profile provided clearer distinction between the pre- and post-treatment groups treated with toxic levels of simvastatin. Through multivariate statistical analysis, we identified marker metabolites associated with the toxicity. Importantly, we observed that the treatment group could be further categorized into two subgroups based on the NMR profiles: weak toxicity (WT) and high toxicity (HT). The distinction between these two groups was confirmed by the enzyme values and histopathological exams. Time-dependent studies showed that the toxicity at 10 days could be reliably predicted from the metabolic profiles at 6 days.Conclusions/SignificanceThis metabonomics approach may provide a non-invasive and effective way to evaluate the simvastatin-induced toxicity in a manner that can complement current measures. The approach is expected to find broader application in other drug-induced toxicity assessments.

Deer antler has been widely used as a dietary supplement for hundreds of years in Asian countries. The chemical composition of deer antlers strongly depends on the growth conditions of the deer, especially the feeds, but the effects of different feeds on deer antlers have not been studied. To expand our knowledge of the chemical constituents of deer antler and establish an efficient way of differentiating antlers obtained with different feeds, we applied an NMR-based metabolomics approach and OPLS-DA multivariate analysis. We show that the antlers from one species on two different feeds, made from grass or mulberry trees, can be reliably differentiated by our metabolomics approach. We identified chemical constituents of the deer antlers and the marker compounds that contribute to the difference between the feed groups. We also rigorously validated our differentiation approach by showing that it can correctly classify blind samples into their respective feed groups. Our approach is expected to help design feeds to produce antlers with more defined constituents, especially those with higher bioactivities.

Cisplatin is the founding member of the platin-group drugs that has platinum metal and ammonium group. Since its fi rst approval in 1978 by US Food and Drug Administration, it has been widely used for various types of cancer such as lung, ovarian, lymphomas, breast and bladder cancers (Smith and Talbot, 1992;von der Maase et al., 2000;Crino et al., 2001;Muggia, 2009). The mechanism of anticancer effect is cytotoxicity due to DNA cross-linking, oxidative damages and apoptosis (Gong et al., 1999;Pruefer et al., 2008). Due to these cytotoxic effect, cisplatin kills not only cancer cells but also normal cells, resulting in undesirable effects in various tissues including kidney, nerves, ear and gastroenteric ones (Loehrer and Einhorn, 1984). Among these, the nephrotoxicity is most common and can be a cause for the cessation of the drug therapy (Arany and Safi rstein, 2003;Yao et al., 2007). Typically, BloodCisplatin is widely used for various types of cancers. However, its side effects, most notably, renal toxicity often limit its clinical utility. Although previous metabolomic studies reported possible toxicity markers, they used small number of animals and statistical approaches that may not perform best in the presence of intra-group variation. Here, we identifi ed urinary biomarkers associated with renal toxicity induced by cisplatin using NMR-based metabolomics combined with Orthogonal Projections to Latent Structures-Discriminant Analysis (OPLS-DA). Male Sprague-Dawley rats (n=22) were treated with cisplatin (10 mg/kg single dose), and the urines obtained before and after treatment were analyzed by NMR. Multivariable analysis of NMR data presented clear separation between non-treated and treated groups. The OPLS-DA statistical results revealed that 1,3-dimethylurate, taurine, glucose, glycine and branched-chain amino acid (isoleucine, leucine and valine) were signifi cantly elevated in the treated group and that phenylacetylglycine and sarcosine levels were decreased in the treated group. To test the robustness of the approach, we built a prediction model for the toxicity and were able to predict all the unknown samples (n=14) correctly. We believe the proposed NMR-based metabolomics with OPLS-DA approach and the resulting urine markers can be used to augment the currently available blood markers. AbstractUrea Nitrogen (BUN), and blood creatinine are checked to monitor the expression of renal toxicity. In addition, hydration and diuretic measures are taken to minimize possible kidney damages. Still, BUN and creatinine are measured from blood and are late stage kidney functional markers (Hewitt et al.,

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