A metabonomic investigation of the biochemical effects of mercuric chloride in the rat using 1H NMR and HPLC-TOF/MS: time dependent changes in the urinary profile of endogenous metabolites as a result of nephrotoxicity

Network Pharmacology Combined with Metabolomics Approach to Investigate the Toxicity Mechanism of Paclobutrazol

Paclobutrazol (PBZ) is a commonly used plant growth regulator (PGR) with good antibacterial activity. It has widespread applications in agricultural production. However, there is limited research reported on the potential risks of human health resulting from PBZ residues. In this study, using Sprague-Dawley rats, we carried out a systematic study on the hepatotoxicity and nephrotoxicity of PBZ in different doses (0.2, 0.5, and 1.0 g/kg). The metabolic profiles and network pharmacology were combined to construct a PBZ-endogenous substances-gene-hepatorenal diseases network to elucidate the underlying mechanism of PBZ's hepatorenal toxicity. At first, metabolomics analysis was done to investigate the metabolites and the related metabolic pathways associated with PBZ. Secondly, the network pharmacology approach was used in further exploration of the toxic targets. Additionally, molecular docking was carried out to investigate the interactions between PBZ and potential targets. The results indicated that PBZ showed obvious toxicity towards the liver and kidney of rats. The metabolomics analysis showed that PBZ mainly affected 4 metabolic pathways, including tryptophan metabolism, arachidonic acid metabolism, linoleic acid metabolism, and purine metabolism. Network pharmacology and molecular docking revealed that CYP1A2, CYP2A6, CYP2E1, MAOA, PLA2G2A, PTGS1, and XDH were critical targets for PBZ hepatorenal toxicity. This preliminary study revealed PBZ's hepatorenal toxicity and provided a theoretical basis for the rational and safe use of PBZ. Furthermore, it provided possible intervention targets for further research on how to avoid or reduce the damage caused by pesticides to the human body.

Kynurenine pathway in kidney diseases

Kidney diseases have become one of the most common health care problems. Due to a growing number of advanced aged patients with concomitant disorders the prevalence of these diseases will increase over the coming decades. Despite available laboratory tests, accurate and rapid diagnosis of renal dysfunction has yet to be realized, and prognosis is uncertain. Moreover, data on diagnostic and prognostic markers in kidney diseases are lacking. The kynurenine (KYN) pathway is one of the routes of tryptophan (Trp) degradation, with biologically active substances presenting ambiguous properties. The KYN pathway is known to be highly dependent on immunological system activity. As the kidneys are one of the main organs involved in the formation, degradation and excretion of Trp end products, pathologies involving the kidneys result in KYN pathway activity disturbances. This review aims to summarize changes in the KYN pathway observed in the most common kidney disease, chronic kidney disease (CKD), with a special focus on diabetic kidney disease, acute kidney injury (AKI), glomerulonephritis and kidney graft function monitoring. Additionally, the importance of KYN pathway activity in kidney cancer pathogenesis is discussed, as are available pharmacological agents affecting KYN pathway activity in the kidney. Despite limited clinical data, the KYN pathway appears to be a promising target in the diagnosis and prognosis of kidney diseases. Modulation of KYN pathway activity by pharmacological agents should be considered in the treatment of kidney diseases.

Intestinal microbiome and metabolome analyses reveal metabolic disorders in the early stage of renal transplantation

Renal transplantation is the most effective treatment for end-stage renal disease, but the long-term prognosis of organs after transplantation is not ideal. In recent years, the importance of gut microbes and metabolites in the study of disease mechanisms has gradually received attention. However, the coordination between gut microbes and the metabolism of renal transplant patients needs further study. We integrated 16s sequencing and metabolomics data to describe the changes in the serum and fecal metabolites of renal transplant patients. Our data revealed that the gut microbial diversity decreased and the relative abundance of many bacteria, such as Enterococcus and Streptococcus, significantly changed after transplantation. In addition, a large number of amino acids and peptides in serum and feces significantly changed, suggesting an abnormal amino acid metabolism after transplantation. Spearman's correlation analysis revealed the changes in the co-metabolism pattern between gut microbes and the host metabolism after transplantation. Furthermore, Enterococcus was found to be correlated with renal functions and metabolites reflecting renal damage. This study provides potential gut microbes and metabolites impacting renal health, which helps in understanding the renal damage in patients with kidney transplantation.

Urinary Metabolomic Profile of Preterm Infants Receiving Human Milk with Either Bovine or Donkey Milk-Based Fortifiers

Fortification of human milk (HM) for preterm and very low-birth weight (VLBW) infants is a standard practice in most neonatal intensive care units. The optimal fortification strategy and the most suitable protein source for achieving better tolerance and growth rates for fortified infants are still being investigated. In a previous clinical trial, preterm and VLBW infants receiving supplementation of HM with experimental donkey milk-based fortifiers (D-HMF) showed decreased signs of feeding intolerance, including feeding interruptions, bilious gastric residuals and vomiting, with respect to infants receiving bovine milk-based fortifiers (B-HMF). In the present ancillary study, the urinary metabolome of infants fed B-HMF (n = 27) and D-HMF (n = 27) for 21 days was analyzed by ¹H NMR spectroscopy at the beginning (T0) and at the end (T1) of the observation period. Results showed that most temporal changes in the metabolic responses were common in the two groups, providing indications of postnatal adaptation. The significantly higher excretion of galactose in D-HMF and of carnitine, choline, lysine and leucine in B-HMF at T1 were likely due to different formulations. In conclusion, isocaloric and isoproteic HM fortification may result in different metabolic patterns, as a consequence of the different quality of the nutrients provided by the fortifiers.

Metabolomics in pharmacology - a delve into the novel field of pharmacometabolomics

Introduction: Pharmacometabolomics is an emerging science pursuing the application of precision medicine. Combining both genetic and environmental factors, the so-called pharmacometabolomic approach guides patient selection and stratification in clinical trials and optimizes personalized drug dosage, improving efficacy and safety.Areas covered: This review illustrates the progressive introduction of pharmacometabolomics as an innovative solution for enhancing the discovery of novel drugs and improving research and development (R&D) productivity of the pharmaceutical industry. An extended analysis on published pharmacometabolomics studies both in animal models and humans includes results obtained in several areas such as hepatology, gastroenterology, nephrology, neuropsychiatry, oncology, drug addiction, embryonic cells, neonatology, and microbiomics.Expert opinion: a tailored, individualized therapy based on the optimization of pharmacokinetics and pharmacodynamics, the improvement of drug efficacy, and the abolition of drug toxicity and adverse drug reactions is a key issue in precision medicine. Genetics alone has become insufficient for deciphring intra- and inter-individual variations in drug-response, since they originate both from genetic and environmental factors, including human microbiota composition. The association between pharmacogenomics and pharmacometabolomics may be considered the new strategy for an in-deep knowledge on changes and alterations in human and microbial metabolic pathways due to the action of a drug.

From 1H NMR-based non-targeted to LC-MS-based targeted metabolomics strategy for in-depth chemome comparisons among four Cistanche species

The great orthogonality between ¹H NMR spectroscopy and LC-MS implies that their deployments in series could offer an opportunity to gain the qualified molecular markers via comparative metabolomics, and an attempt was made here to propose an integrated strategy namely "from ¹H NMR-based non-targeted to LC-MS-based targeted metabolomics". In-depth chemome comparisons of Cistanche plants, such as C. deserticola, C. salsa, C. tubulosa, and C. sinensis, that possess dramatic economic and ecological benefits for the arid regions in the northwest China attributing to their dramatic medicinal and edible values, were employed to verify the applicability. ¹H NMR-based non-targeted matabolomics acted as the survey experiment to find those signals offering decisive contributions towards the species discrimination, and the signals were translated to a set of putative identities, eighteen ones in total, through matching with authentic compounds and referring to some accessible databases. Afterwards, an advanced LC-MS platform assembling reversed phase liquid chromatography, hydrophilic interaction liquid chromatography, and tailored multiple reaction monitoring, was introduced to simultaneously quantify those eighteen potential markers in a single analytical run, because those candidates exhibited great polarity span as well as wide content range. Significant species differences occurred amongst their chemome patterns. Echinacoside, acteoside, betaine, mannitol, 6-deoxycatalpol, sucrose, and 8-epi-loganic acid were disclosed as the markers enabling the discrimination of those four species. The findings offered an alternative tool to differentiate Cistanche plants. More importantly, the strategy namely "from ¹H NMR-based non-targeted to LC-MS-based targeted metabolomics" facilitates the pursuit of molecular markers among analogue plants, and thereby provides a promising choice for in-depth chemome comparison.

Simultaneous Determination of Five Specific and Sensitive Nephrotoxicity Biomarkers in Serum and Urine Samples of Four Drug-Induced Kidney Injury Models

In clinical diagnosis, serum creatinine (CR) was commonly used as the routine markers for the evaluation of kidney injury. To investigate the specific and sensitive nephrotoxicity biomarkers in different drug-induced kidney injury (DKI) models, receiver operating characteristic (ROC) analysis was applied in this study. The quantification data were acquired by the LC-MS determination. Histopathology results showed that different kinds of kidney injuries were observed in different DKI models (gentamycin, cisplatin, methotrexate and amphotericin B models), indicating the injuries might be caused by different mechanisms. Then, five typical biomarkers were simultaneously determined by a newly developed and validated LC-MS method. Uric acid, CR, hippuric acid, 3-indoxyl sulfate and phenaceturic acid were separated by an Apollo C₁₈ column and a methanol/water (5 mM ammonium acetate) gradient program. The prepared calibration curves showed good linearity with regression coefficients all above 0.9927. Of all the analytes, the precision were below 9.9% and the accuracy were from -10.3% to 9.2%. ROC results showed that different nephrotoxicity biomarkers were specific in different DKI models. The changes of different biomarkers might be induced by different nephrotoxic mechanisms in the DKI models. These specific and sensitive biomarkers in combination with serum CR are promising in the clinical diagnosis of DKI.

Plasma metabolic profiling analysis of toxicity induced by brodifacoum using metabonomics coupled with multivariate data analysis

Brodifacoum is one of the most widely used rodenticides for rodent control and eradication; however, human and animal poisoning due to primary and secondary exposure has been reported since its development. Although numerous studies have described brodifacoum induced toxicity, the precise mechanism still needs to be explored. Gas chromatography mass spectrometry (GC-MS) coupled with an ultra performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) was applied to characterize the metabolic profile of brodifacoum induced toxicity and discover potential biomarkers in rat plasma. The toxicity of brodifacoum was dose-dependent, and the high-dose group obviously manifested toxicity with subcutaneous hemorrhage. The blood brodifacoum concentration showed a positive relation to the ingestion dose in toxicological analysis. Significant changes of twenty-four metabolites were identified and considered as potential toxicity biomarkers, primarily involving glucose metabolism, lipid metabolism and amino acid metabolism associated with anticoagulant activity, nephrotoxicity and hepatic damage. MS-based metabonomics analysis in plasma samples is helpful to search for potential poisoning biomarkers and to understand the underlying mechanisms of brodifacoum induced toxicity.

A metabonomic study of adjuvant-induced arthritis in rats using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry

Rheumatoid arthritis (RA) is a chronic systemic inflammatory and autoimmune disease accompanied by the destruction and deformities of joints. Adjuvant-induced arthritis (AIA) is one of the excellent animal models of RA used to understand disease pathogenesis and screen potential drugs. In this paper, a urinary metabonomics method based on ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) has been established to investigate the disease progression of AIA and find potential biomarkers of secondary inflammation in AIA rats. 24 potential biomarkers were identified, including xanthurenic acid, kynurenic acid, 4-pyridoxic acid, and phenylalanine, which revealed that tryptophan metabolism, phenylalanine metabolism, gut microbiota metabolism and energy metabolism were disturbed in AIA rats. These potential biomarkers and their corresponding pathways are helpful to further understand the mechanisms of AIA and pathogenesis of RA. This study demonstrates that metabonomics based on UPLC-Q-TOF-MS is a powerful methodology to analyze the underlying disease pathogenesis.

Evaluation of the indicative roles of seven potential biomarkers on hepato-nephrotoxicity induced by Genkwa Flos

ETHNOPHARMACOLOGICAL RELEVANCE

Genkwa Flos, a classical traditional Chinese medicine, is used for the definite antitumor activity and tends to be taken overdose or long term in these years. While the excessive application can result in damage to liver and kidney. In this study, the indicative roles of seven potential biomarkers were evaluated to investigate hepato-nephrotoxicity in the early stages after oral administration of Genkwa Flos for 14 days.

MATERIALS AND METHODS

Histopathology, serum biochemistry and seven potential biomarkers in serum or urine from male Sprague-Dawley rats were monitored. Hepatic and renal tissues were histopathologically examined to identify specific changes occurring. Routine serum biochemical parameters were tested by using standard clinical laboratory methods. Seven biomarkers including cholic acid, taurine, 5-oxoproline, hippuric acid, uric acid, 3-indoxyl sulfate and kynurenic acid were detected by a developed LC-MS method.

RESULTS

The histopathological alterations and the increased levels of serum biochemistry were detected on the 8th day after Genkwa Flos treated. The seven analytes were also found significantly changed in Genkwa Flos treated group, especially cholic acid, taurine, 5-oxoproline and hippuric acid which were changed on the 2nd or 4th day.

CONCLUSIONS

Although serum biochemistry and histopathology suggested that Genkwa Flos was responsible for the hepato-nephrotoxicity that occurred following the ingestion of this medicinal herb, evaluation of these biomarkers might be more beneficial for the early detection of liver and kidney injuries. This study could be further used in hepatic and renal failures caused by other reasons in the following research works.

Metabolomics in nephrotoxicity

Nephrotoxicity or renal toxicity can be a result of hemodynamic changes, direct injury to cells and tissue, inflammatory tissue injury, and/or obstruction of renal excretion. Nephrotoxicity is frequently induced by a wide spectrum of therapeutic drugs and environ mental pollutants. Knowledge of the complex molecular and pathophysiologic mechanisms leading to nephrotoxicity remains limited, in part, by research that historically focused on single or relatively few risk markers. As such, current kidney injury biomarkers are inadequate in terms of sensitivity and specificity. In contrast, metabolomics enables screening of a vast array of metabolites simultaneously using NMR and MS to assess their role in nephrotoxicity development and progression. A more comprehensive understanding of these biochemical pathways would also provide valuable insight to disease mechanisms critical for drug development and treatment.

Therapeutic effect of Xue Niao An on glyoxylate-induced calcium oxalate crystal deposition based on urinary metabonomics approach

The anti-nephrolithiasis effect of Xue Niao An (XNA) capsules is explored by analyzing urine metabolic profiles in mouse models, with ultra-high performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS). An animal model of calcium oxalate crystal renal deposition was established in mice by intra-abdominal injection of glyoxylate. Then, treatment with XNA by intra-gastric administration was performed. At the end of the study, calcium deposition in kidney was measured by Von Kossa staining under light microscopy, and the Von Kossa staining changes showed that XNA significantly alleviated the calcium oxalate crystal deposition. Meanwhile, urine samples for fifteen metabolites, including amino acids and fatty acids, with significant differences were detected in the calcium oxalate group, while XNA treatment attenuated metabolic imbalances. Our study indicated that the metabonomic strategy provided comprehensive insight on the metabolic response to XNA treatment of rodent renal calcium oxalate deposition.

Determination of 12 potential nephrotoxicity biomarkers in rat serum and urine by liquid chromatography with mass spectrometry and its application to renal failure induced by Semen Strychni

In previous nephrotoxicity metabonomic studies, several potential biomarkers were found and evaluated. To investigate the relationship between the nephrotoxicity biomarkers and the therapeutic role of Radix Glycyrrhizae extract on Semen Strychni-induced renal failure, 12 typical biomarkers are selected and a simple LC-MS method has been developed and validated. Citric acid, guanidinosuccinic acid, taurine, guanidinoacetic acid, uric acid, creatinine, hippuric acid, xanthurenic acid, kynurenic acid, 3-indoxyl sulfate, indole-3-acetic acid, and phenaceturic acid were separated by a Phenomenex Luna C18 column and a methanol/water (5 mM ammonium acetate) gradient program with a runtime of 20 min. The prepared calibration curves showed good linearity with regression coefficients all above 0.9913. The absolute recoveries of analytes from serum and urine were all more than 70.4%. With the developed method, analytes were successfully determined in serum and urine samples within 52 days. Results showed that guanidinosuccinic acid, guanidinoacetic acid, 3-indoxyl sulfate, and indole-3-acetic acid (only in urine) were more sensitive than the conventional renal function markers in evaluating the therapeutic role of Radix Glycyrrhizae extract on Semen Strychni-induced renal failure. The method could be further used in predicting and monitoring renal failure cause by other reasons in the following researches.

Urinary metabonomics study on toxicity biomarker discovery in rats treated with Xanthii Fructus

ETHNOPHARMACOLOGICAL RELEVANCE

Xanthii Fructus (XF) is commonly called "Cang-Erzi" in traditional Chinese medicine (TCM) and widely used for the treatment of sinusitis, headache, rheumatism, and skin itching. However, the clinical utilization of XF is relatively restricted owing to its toxicity.

AIM OF THE STUDY

To discover the characteristic potential biomarkers in rats treated with XF by urinary metabonomics.

MATERIALS AND METHODS

Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) was applied in the study. The total ion chromatograms obtained from control and different dosage groups were distinguishable by a multivariate statistical analysis method.

RESULTS

The greatest difference in metabolic profile was observed between high dosage group and control group, and the metabolic characters in rats treated with XF were perturbed in a dose-dependent manner. The metabolic changes in response for XF treatment were observed in urinary samples, which were revealed by orthogonal projection to latent structures discriminate analysis (OPLS-DA), and 10 metabolites could be served as the potential toxicity biomarkers. In addition, the mechanism associated with the damages of lipid per-oxidation and the metabolic disturbances of fatty acid oxidation were investigated.

CONCLUSIONS

These results indicate that metabonomics analysis in urinary samples may be useful for predicting the toxicity induced by XF.

Use of the local false discovery rate for identification of metabolic biomarkers in rat urine following Genkwa Flos-induced hepatotoxicity

Metabolomics is concerned with characterizing the large number of metabolites present in a biological system using nuclear magnetic resonance (NMR) and HPLC/MS (high-performance liquid chromatography with mass spectrometry). Multivariate analysis is one of the most important tools for metabolic biomarker identification in metabolomic studies. However, analyzing the large-scale data sets acquired during metabolic fingerprinting is a major challenge. As a posterior probability that the features of interest are not affected, the local false discovery rate (LFDR) is a good interpretable measure. However, it is rarely used to when interrogating metabolic data to identify biomarkers. In this study, we employed the LFDR method to analyze HPLC/MS data acquired from a metabolomic study of metabolic changes in rat urine during hepatotoxicity induced by Genkwa flos (GF) treatment. The LFDR approach was successfully used to identify important rat urine metabolites altered by GF-stimulated hepatotoxicity. Compared with principle component analysis (PCA), LFDR is an interpretable measure and discovers more important metabolites in an HPLC/MS-based metabolomic study.

Global metabolic profiling of animal and human tissues via UPLC-MS

Obtaining comprehensive, untargeted metabolic profiles for complex solid samples, e.g., animal tissues, requires sample preparation and access to information-rich analytical methodologies such as mass spectrometry (MS). Here we describe a practical two-step process for tissue samples that is based on extraction into 'aqueous' and 'organic' phases for polar and nonpolar metabolites. Separation methods such as ultraperformance liquid chromatography (UPLC) in combination with MS are needed to obtain sufficient resolution to create diagnostic metabolic profiles and identify candidate biomarkers. We provide detailed protocols for sample preparation, chromatographic procedures, multivariate analysis and metabolite identification via tandem MS (MS/MS) techniques and high-resolution MS. By using these optimized approaches, analysis of a set of samples using a 96-well plate format would take ~48 h: 1 h for system setup, 8-10 h for sample preparation, 34 h for UPLC-MS analysis and 2-3 h for preliminary/exploratory data processing, representing a robust method for untargeted metabolic screening of tissue samples.

The role of metabolic biomarkers in drug toxicity studies

ABSTRACT Metabolic profiling is a technique that can potentially provide more sensitive and specific biomarkers of toxicity than the current clinical measures benefiting preclinical and clinical drug studies. Both nuclear magnetic resonance (NMR) and mass spectrometry (MS) platforms have been used for metabolic profiling studies of drug toxicity. Not only can both techniques provide novel biomarker(s) of toxicity but the combination of both techniques gives a broader range of metabolites evaluated. Changes in metabolic patterns can provide insight into mechanism(s) of toxicity and help to eliminate a potentially toxic new chemical entity earlier in the developmental process. Metabolic profiling offers numerous advantages in toxicological research and screening as sample collection and preparation are relatively simple. Further, sample throughput, reproducibility, and accuracy are high. The area of drug toxicity of therapeutic compounds has already been impacted by metabolic profiling studies and will continue to be impacted as new, more specific biomarker(s) are found. In order for a biomarker or pattern of biomarkers to be accepted, it must be shown that they originate from the target tissue of interest. Metabolic profiling studies are amenable to any biofluid or tissue sample making it possible to link the changes noted in urine for instance as originating from renal injury. Additionally, the ease of sample collection makes it possible to follow a single animal or subject over time in order to determine whether and when the toxicity resolves itself. This review focuses on the advantages of metabolic profiling for drug toxicity studies.

A metabonomic analysis of urine from rats treated with rhizoma alismatis using ultra-performance liquid chromatography/mass spectrometry

A metabonomic approach based on ultra-performance liquid chromatography coupled to mass spectrometry (UPLC/MS) was used to study the nephrotoxicity of rhizoma alismatis (RA) in rats. Potential biomarkers of RA toxicity were identified and the toxicological mechanism is discussed. Urine samples were collected from control and treated rats at various stages and analyzed by UPLC/MS in positive ionization mode. Histopathological analysis was used to evaluate renal function. The differences in the metabolic profiles of the control and treated rats were clearly distinguishable with principal components analysis (PCA) of the chromatographic data, and significant changes in 13 metabolite biomarkers were detected in the urine. This metabonomic method combined with PCA could discriminate the treated rats from the control rats on days 60, 120, and 180 after treatment, before serious organic renal damage was apparent on day 180 with histopathology. This research indicates that UPLC/MS-based metabonomic analysis of urine samples can be used to predict the chronic nephrotoxicity induced by rhizoma alismatis.

Differential biochemical response of rat kidney towards low and high doses of NiCl2 as revealed by NMR spectroscopy

Heavy metals are known for their associated nephrotoxicity and nickel is no exception. An integrated metabonomic approach, based on high-resolution (1) H NMR spectroscopy, was applied to determine the acute biochemical effects of NiCl(2) on the renal tissues of rats. Kidney homogenates from rats treated with NiCl(2) at two dose levels (4 and 20 mg kg(-1) b.w., i.p.) and those from controls were analysed using (1) H NMR spectroscopy and also assessed for antioxidant parameters at days 1, 3 and 5 post-dose. The major metabolite changes corresponding to nickel exposure were related to amino acids, osmolytes and energy metabolites. Differential responses were observed in (1) H NMR spectra with exposure to low and high doses of NiCl(2). For high doses, (1) H NMR spectral analysis revealed alterations in renal tissues, along with damage to the cortical and papillary region and depletion of renal osmolytes such as betaine, trimethyl amine oxide, myo-inositol and taurine, which persisted until day 5 post-dose. The metabolite profile of (1) H NMR spectra obtained from animals treated with lower dose of NiCl(2) initially increased as an immediate stress response and then showed signs of recovery with the passage of time. NMR spectral analysis was well corroborated with histopathological and oxidative stress results. Nickel-induced oxidative stress was observed in both groups of animals with increased levels of antioxidant parameters at initial time points, but continued to increase in the high-dose group. The present study shows a huge potential of metabonomics for mapping organ-based metabolic response during heavy metal toxicity.

Mass spectrometry-based holistic analytical approaches for metabolite profiling in systems biology studies

Metabonomics and metabolomics represent one of the three major platforms in systems biology. To perform metabolomics it is necessary to generate comprehensive "global" metabolite profiles from complex samples, for example, biological fluids or tissue extracts. Analytical technologies based on mass spectrometry (MS), and in particular on liquid chromatography-MS (LC-MS), have become a major tool providing a significant source of global metabolite profiling data. In the present review we describe and compare the utility of the different analytical strategies and technologies used for MS-based metabolomics with a particular focus on LC-MS. Both the advantages offered by the technology and also the challenges and limitations that need to be addressed for the successful application of LC-MS in metabolite analysis are described. Data treatment and approaches resulting in the detection and identification of biomarkers are considered. Special emphasis is given to validation issues, instrument stability, and QA/quality control (QC) procedures.

Metabolomics for early detection of drug-induced kidney injury: review of the current status

The identification of biomarkers of drug-induced kidney injury is an area of intensive focus in drug development. Traditional markers of renal function, including blood urea nitrogen and serum creatinine, are not region-specific and only increase significantly after substantial kidney injury. Therefore, more sensitive markers of kidney injury are needed. The ideal biomarkers will identify nephrotoxicity early in the drug-discovery process, resulting in decreased development costs and safer drugs. Metabolomics, the study of the small biochemicals present in a biological sample, has become a promising player in the nephrotoxicity arena. In this review, we describe the current status of the identification of metabolic biomarkers for drug-induced kidney toxicity screening. Many of these markers have been confirmed across multiple studies and can detect nephrotoxicity earlier than the traditional clinical chemistry and histopathology methods. Upon further validation, such markers will offer clear benefits for the pharmaceutical industry and regulatory agencies.

Database searching for structural identification of metabolites in complex biofluids for mass spectrometry-based metabonomics

MS and HPLC are commonly used for compound characterization and obtaining structural information; in the field of metabonomics, these two analytical techniques are often combined to characterize unknown endogenous or exogenous metabolites present in complex biological samples. Since the structures of a majority of these metabolites are not actually identified, the result of most metabonomic studies is a list of m/z values and retention times. However, without knowing actual structures, the biological significance of these 'features' cannot be determined. The process of identifying the structures of unknown compounds can be time intensive, costly and frequently requires the use of multiple orthogonal analytical techniques - this laborious procedure seems insurmountable for the long lists of unknowns that must be identified for each study. In addition, the limited sample volume and the extremely low concentration of most endogenous analytes frequently make purification and identification by other instrumentation nearly impossible. This review is intended to explore the problems and progress with current tools that are available for MS-based structure identification for both endogenous and exogenous metabolites.

Biomarker discovery in biological specimens (plasma, hair, liver and kidney) of diabetic mice based upon metabolite profiling using ultra-performance liquid chromatography with electrospray ionization time-of-flight mass spectrometry

BACKGROUND

The number of diabetic patients has recently been increasing worldwide. Diabetes is a multifactorial disorder based on environmental factors and genetic background. In many cases, diabetes is asymptomatic for a long period and the patient is not aware of the disease. Therefore, the potential biomarker(s), leading to the early detection and/or prevention of diabetes mellitus, are strongly required. However, the diagnosis of the prediabetic state in humans is a very difficult issue, because the lifestyle is variable in each person. Although the development of a diagnosis method in humans is the goal of our research, the extraction and structural identification of biomarker candidates in several biological specimens (i.e., plasma, hair, liver and kidney) of ddY strain mice, which undergo naturally occurring diabetes along with aging, were carried out based upon a metabolite profiling study.

METHODS

The low-molecular-mass compounds including metabolites in the biological specimens of diabetic mice (ddY-H) and normal mice (ddY-L) were globally separated by ultra-performance liquid chromatography (UPLC) using different reversed-phase columns (i.e., T3-C18 and HS-F5) and detected by electrospray ionization time-of-flight mass spectrometry (ESI-TOF-MS). The biomarker candidates related to diabetes mellitus were extracted from a multivariate statistical analysis, such as an orthogonal partial least-squares-discriminant analysis (OPLS-DA), followed by a database search, such as ChemSpider, KEGG and HMDB.

RESULTS

Many metabolites and unknown compounds in each biological specimen were detected as the biomarker candidates related to diabetic mellitus. Among them, the elucidation of the chemical structures of several possible metabolites, including more than two biological specimens, was carried out along with the comparison of the tandem MS/MS analyses using authentic compounds. One metabolite was clearly identified as N-acetyl-L-leucine based upon the MS/MS spectra and the retention time on the chromatograms.

CONCLUSIONS

N-acetyl-L-leucine is an endogenous compound included in all biological specimens (plasma, hair, liver and kidney). Therefore, this metabolite appears to be a potential biomarker candidate related to diabetes. Although the structures of other biomarker candidates have still not yet determined, the present approach based upon a metabolite profiling study using UPLC-ESI-TOF-MS could be helpful for understanding the abnormal state of various diseases.

Practical analytical approach for the identification of biomarker candidates in prediabetic state based upon metabonomic study by ultraperformance liquid chromatography coupled to electrospray ionization time-of-flight mass spectrometry

The number of diabetic patients has recently been increasing worldwide. Thus, the discovery of potential diabetic biomarker(s), leading to the early detection and/or prevention of diabetes mellitus, is strongly required. The diagnosis of the prediabetic state in humans is a very difficult issue because of the lifestyle differences in each person and ethical consideration. Upon the basis of these considerations, animal experiments using ddY strain mice (ddY-H), which undergo naturally occurring diabetes along with age, were carried out in this study. Biomarker discovery based upon a metabonome study is now quite common, the same as that in the proteome analysis. Reversed-phase liquid chromatography-mass spectrometry (LC-MS) has mainly been used for the extensive analysis of low-molecular mass compounds including metabolites. The metabolites in the plasma of diabetic mice (ddY-H) and normal mice (ddY-L) were exhaustively separated and detected by ultraperformance liquid chromatography along with electrospray ionization time-of-flight mass spectrometry (UPLC-ESI-TOF-MS) using T3-C18 and HS-F5 columns. The biomarker candidates related to diabetes mellitus were extracted from the metabolite profiling of ddY-H and ddY-L at 5, 9 13, and 20 weeks old using a multivariate statistical analysis such as orthogonal partial least-squares-discriminant analysis (OPLS-DA). Various metabolites and unknown compounds were detected as biomarker candidates related to diabetic mellitus. Furthermore, the concentration of several metabolites on Lysine biosynthesis and Lysine degradation pathways were remarkably changed between the 9-week old ddY-H and ddY-L mice. Because a couple of biomarker candidates related to the prediabetic state were identified using the present approach, the metabolite profiling study could be helpful for understanding the abnormal state of various diseases.

Advances in metabolic profiling of experimental nematode and trematode infections

Metabonomics, which is the combination of metabolic profiling of biological samples using spectroscopic methods, together with multivariate data analysis, is a powerful approach for biomarker recovery. Moreover, metabonomics holds promise to enhance our understanding of host-parasite interactions at the metabolic level, and therefore provides a framework for discovery of novel targets for diagnostics, drugs and vaccines. In this review, we summarise progress made to date with metabolic profiling strategies applied to different host-parasite models in the laboratory. First, we emphasise the application of two parasitic worm infections that are particularly relevant for Southeast Asia and the People's Republic of China, namely the trematode Schistosoma japonicum causing schistosomiasis, and the nematode Necator americanus causing hookworm disease. Next, we review metabolic profiling studies on the liver fluke Fasciola hepatica in the rat model, the intestinal fluke Echinostoma caproni harboured in mice and characterise the metabolic responses in the hamster to a S. japonicum-N. americanus co-infection. We extract parasite-specific biomarkers and distinguish them from a more general response to an infection at the biochemical level. For example, suppression of tricarboxylic acid cycle metabolites is only noted for a Schistosoma spp. infection, whereas alterations in metabolites derived from the gut microbiota are common for all the parasitic infections investigated thus far. Finally, we explore how the insight gained with experimental infections could be transferred to human populations and conclude with a section on research needs with regard to molecular diagnostics in parasitology.

Global metabolic profiling procedures for urine using UPLC-MS

The production of 'global' metabolite profiles involves measuring low molecular-weight metabolites (<1 kDa) in complex biofluids/tissues to study perturbations in response to physiological challenges, toxic insults or disease processes. Information-rich analytical platforms, such as mass spectrometry (MS), are needed. Here we describe the application of ultra-performance liquid chromatography-MS (UPLC-MS) to urinary metabolite profiling, including sample preparation, stability/storage and the selection of chromatographic conditions that balance metabolome coverage, chromatographic resolution and throughput. We discuss quality control and metabolite identification, as well as provide details of multivariate data analysis approaches for analyzing such MS data. Using this protocol, the analysis of a sample set in 96-well plate format, would take ca. 30 h, including 1 h for system setup, 1-2 h for sample preparation, 24 h for UPLC-MS analysis and 1-2 h for initial data processing. The use of UPLC-MS for metabolic profiling in this way is not faster than the conventional HPLC-based methods but, because of improved chromatographic performance, provides superior metabolome coverage.

Metabonomics study of urine and plasma in depression and excess fatigue rats by ultra fast liquid chromatography coupled with ion trap-time of flight mass spectrometry

A novel metabonomic method based on fast liquid chromatography coupled with ion trap-time of flight mass spectrometry (UFLC/MS-IT-TOF) was applied to study the metabolic changes of plasma and urine in depression and excess fatigue rats. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were applied for classifying the depression, excess fatigue and the control rats. Metabolites which were important for the classification in the three groups of rats were selected as potential biomarkers and identified by MS(n) information achieved from UFLC/MS-IT-TOF analysis. Spermine, propionylcarnitine, butyrylcarnitine, phenylalanine, lysophosphatidylcholine (LPC) C14:0 and LPC C18:2 were down-regulated, methyl-hippuric acid and chenodeoxycholic acid (CDCA) were up-regulated significantly in plasma of the excess fatigue rats. Spermine, leucine, propionylcarnitine, and butyrylcarnitine decreased, hippuric acid, methyl-hippuric acid, cholic acid, CDCA and LPC C16:0 increased markedly in plasma of the depression rats. Ethyl N2-acetyl-L-argininate and N-methyl-2-pyridone-5-carboxamide (2-PY) (or N-methyl-4-pyridone-3-carboxamide (4-PY)) were down-regulated, leucylproline and pantothenic acid were up-regulated remarkably both in urine of depression and excess fatigue rats. The concentration of kynurenic acid and N2-succinyl-L-ornithine was low in urine of depression rats compared with control rats. Based on the data, correlation networks for depression and excess fatigue rats revealed the abnormality of nicotinate and nicotinamide metabolism, arginine metabolism, cholesterol metabolism, tryptophan metabolism and kynurenine metabolism in depression rats, and in excess fatigue rat alterations of energy metabolism, nicotinate and nicotinamide metabolism and lecithin metabolism. Our results provide novel insights in the complex metabolic mechanisms occurring in depression and excess fatigue rats.

Analysis of time course 1H NMR metabolomics data by multivariate curve resolution

Modeling NMR-based metabolomics data often involves linear methods such as principal component analysis (PCA) and partial least squares (PLS). These methods have the objective of describing the main variance in the data and maximum covariance between the predictor variables and some response variable respectively. If the experiment is designed to investigate temporal biological fluctuations, however, the factors obtained become difficult to interpret in a biological context. Moreover, when these methods are applied to analyze data, an implicit assumption is made that the measurement errors exhibit an iid-normal distribution, often limiting the extent of the information recovered. A method for the linear decomposition of NMR-based metabolomics data by multivariate curve resolution (MCR), which has been used elsewhere for time course transcriptomics applications, is introduced and implemented via a weighted alternating least squares (ALS) approach. Measurement of error information is incorporated in the modeling process, allowing the least squares projections to be performed in a maximum likelihood fashion. As a result, noise heteroscedasticity resulting from pH-induced peak shifts can be modeled, eliminating the need for binning/bucketing. The utility of the method is demonstrated using two sets of temporal NMR metabolomics data, HgCl(2)-induced nephrotoxicity in rat, and fish (Japanese medaka, Oryzias latipes) embryogenesis. Profiles extracted for the nephrotoxicity data exhibit strong correlations with metabolites consistent with temporal fluctuations in glucosuria. The concentration of metabolites such as acetate, glucose, and alanine exhibit a steady increase, which peaks at Day 3 post dose and returns to basal levels at Day 8. Other metabolites including citrate and 2-oxoglutarate exhibit the opposite characteristics. Although the fish embryogenesis data are more complex, the profiles extracted by the algorithm display characteristics that depict temporal variation consistent with processes associated with embryogenesis.

Important roles of the hyphenated HPLC-DAD-MS-SPE-NMR technique in metabonomics

Metabolite identification is a key step for metabonomics study. A fully automated hyphenation of HPLC-diode-array detector (DAD) mass spectrometry (MS) solid phase extraction (SPE)-NMR spectroscopy (HPLC-DAD-MS-SPE-NMR) is one of the most efficient methods to determine the structure of a given unknown metabolite in a complex mixture (metabonome) and hence represents one of the most important analytical techniques for the further development of metabonomics. In this review, some recent applications of this technique in identifying novel and trace metabolites in plant extracts and drug metabolism have been discussed. Modification of this hyphenated technique, enabling multiple trappings of strong polar metabolites for biofluids, needs further development.

Toward an "omic" physiopathology of reactive chemicals: thirty years of mass spectrometric study of the protein adducts with endogenous and xenobiotic compounds

Cancer and degenerative diseases are major causes of morbidity and death, derived from the permanent modification of key biopolymers such as DNA and regulatory proteins by usually smaller, reactive molecules, present in the environment or generated from endogenous and xenobiotic components by the body's own biochemical mechanisms (molecular adducts). In particular, protein adducts with organic electrophiles have been studied for more than 30 [see, e.g., Calleman et al., 1978] years essentially for three purposes: (a) as passive monitors of the mean level of individual exposure to specific chemicals, either endogenously present in the human body or to which the subject is exposed through food or environmental contamination; (b) as quantitative indicators of the mean extent of the individual metabolic processing which converts a non-reactive chemical substance into its toxic products able to damage DNA (en route to cancer induction through genotoxic mechanisms) or key proteins (as in the case of several drugs, pesticides or otherwise biologically active substances); (c) to relate the extent of protein modification to that of biological function impairment (such as enzyme inhibition) finally causing the specific health damage. This review describes the role that contemporary mass spectrometry-based approaches employed in the qualitative and quantitative study of protein-electrophile adducts play in the discovery of the (bio)chemical mechanisms of toxic substances and highlights the future directions of research in this field. A particular emphasis is given to the measurement of often high levels of the protein adducts of several industrial and environmental pollutants in unexposed human populations, a phenomenon which highlights the possibility that a number of small organic molecules are generated in the human organism through minor metabolic processes, the imbalance of which may be the cause of "spontaneous" cases of cancer and of other degenerative diseases of still uncharacterized etiology. With all this in mind, it is foreseen that a holistic description of cellular functions will take advantage of new analytical methods based on time-integrated metabolomic measurements of a new biological compartment, the "adductome," aimed at better understanding integrated organism response to environmental and endogenous stressors.

Combining nuclear magnetic resonance spectroscopy and mass spectrometry in biomarker discovery

Metabolic profiling of biological specimens is emerging as a promising approach for discovering specific biomarkers in the diagnosis of a number of diseases. Amongst many analytical techniques, nuclear magnetic resonance spectroscopy and mass spectrometry are the most information-rich tools that enable high-throughput and global analysis of hundreds of metabolites in a single step. Although only one of the two techniques is utilized in a majority of metabolomics applications, there is a growing interest in combining the data from the two methods to effectively unravel the mammoth complexity of biological samples. In this article, current developments in nuclear magnetic resonance, mass spectrometry and multivariate statistical analysis methods are described. While some general applications that utilize the combination of the two analytical methods are presented briefly, the emphasis is laid on the recent applications of nuclear magnetic resonance and mass spectrometry methods in the studies of hepatopancreatobiliary and gastrointestinal malignancies.

Temporal metabolomic analysis of o-glucoside phenolic compounds and their aglycone forms in olive tree and derived materials

INTRODUCTION

Maturity is one of the most important factors associated with evaluation of the quality of fruit and vegetables. In olive oil, maturation plays a key role in the kinetics of biosynthetic pathways of the secondary metabolism. One of the most relevant pathways is that catalysed by beta-glucosidases, which are involved in olive oil debittering. Therefore, the knowledge of this influence can be of particular interest for olive oil industry.

OBJECTIVE

To monitor the profile of O-glucoside phenols and their aglycone forms in olive oil, alperujo (the semisolid residue resulting in the production of olive oil), stones, leaves and branches in order to interpret its evolution according to the sample and the period of the season (October, when olive drupes are green; December, when these drupes are green-purple; and February, when they are mostly black).

METHODOLOGY

Targeted phenols were extracted by previously optimised methods assisted by auxiliary energies (i.e. ultrasound, microwaves or superheated liquids) according to the characteristics of the sample. The analysis was carried out by liquid chromatography-tandem mass spectrometry with a triple quadrupole mass detector. Highly selective identification and sensitive determination of metabolites was performed in multiple-reaction monitoring mode. Statistical analysis to evaluate differences in the profile of the target compounds was based on principal compounds analysis.

RESULTS

The evolution of the analytes concentration is strongly related to the role of beta-glucosidases. An explanation for this evolution in olive oil, alperujo and stones is given by relation to the industrial process for olive oil production. For leaves and small branches, the concentration was practically constant over the season, which was foreseeable because of the perennial character of olive trees. Leaves and branches were found to be highly concentrated in O-glucoside derivatives, demonstrating their capacity for phenolic compounds storage.

CONCLUSIONS

Targeted metabolomic profiling has proved a useful tool to monitor O-glucoside phenolic compounds and their aglycone forms in olive materials. The profile of target compounds enables interpretion of their evolution according to the olive material and the period of the season.

NMR and the water-holding issue of pork

Consumers' awareness of food quality has never been more pronounced. Meat forms a substantial part of the food consumption, and accordingly techniques to control the quality of meat are needed. In addition, a better understanding of how basic biochemical and biophysical factors influence the final meat quality is also required for optimization of the quality. Water-holding capacity (WHC) is a major quality attribute of fresh meat. However, the exact mechanisms determining the WHC of meat are not fully understood. Especially, characteristics about proposed water populations in the meat and how they are interrelated with drip loss need to be studied further. Moreover, the distribution and mobility of water in muscle during its conversion to meat and how they are affected by intrinsic and extrinsic factors are poorly elucidated. Nuclear magnetic resonance (NMR) has during recent years gained increasing use within different areas of muscle physiology and meat science. NMR (1)H relaxation methodologies enable detection of the mobility of protons in heterogeneous materials and thereby provide possibilities for a characterization of the properties of water. The objective of this presentation is to give an overview of the use of NMR relaxation measurements to characterize the proposed water populations in meat and investigate how the distribution and mobility of the water changes postmortem. In addition, applications of NMR spectroscopy in metabolic studies will be considered.