Understanding mouse models of disease through metabolomics

OsLSC6 Regulates Leaf Sheath Color and Cold Tolerance in Rice Revealed by Metabolite Genome Wide Association Study

Plant metabolites including anthocyanins play an important role in the growth of plants, as well as in regulating biotic and abiotic stress responses to the environment. Here we report comprehensive profiling of 3315 metabolites and a further metabolic-based genome-wide association study (mGWAS) based on 292,485 SNPs obtained from 311 rice accessions, including 160 wild and 151 cultivars. We identified hundreds of common variants affecting a large number of secondary metabolites with large effects at high throughput. Finally, we identified a novel gene namely OsLSC6 (Oryza sativa leaf sheath color 6), which encoded a UDP 3-O-glucosyltransferase and involved in the anthocyanin biosynthesis of Cyanidin-3-Galc (sd1825) responsible for leaf sheath color, and resulted in significant different accumulation of sd1825 between wild (purple) and cultivars (green). The results of knockout transgenic experiments showed that OsLSC6 regulated the biosynthesis and accumulation of sd1825, controlled the purple leaf sheath. Our further research revealed that OsLSC6 also confers resistance to cold stress during the seedling stage in rice. And we identified that a SNP in OsLSC6 was responsible for the leaf sheath color and chilling tolerance, supporting the importance of OsLSC6 in plant adaption. Our study could not only demonstrate that OsLSC6 is a vital regulator during anthocyanin biosynthesis and abiotic stress responses, but also provide a powerful complementary tool based on metabolites-to-genes analysis by mGWAS for functional gene identification andpromising candidate in future rice breeding and improvement.

Animal Models: A Useful Tool to Unveil Metabolic Changes in Hepatocellular Carcinoma

Simple Summary

Hepatocellular carcinoma (HCC) represents an important health problem. At the moment, systemic therapies offered only modest clinical benefits. Thus, HCC represents a cancer extremely difficult to treat, and therapeutic breakthroughs are urgently needed. Metabolic reprogramming of neoplastic cells has been recognized as one of the core hallmarks of cancer. Experimental animal models represent an important tool that allows to investigate metabolic changes underlying HCC development and progression. In the present review, we characterize available rodent models of hepatocarcinogenesis. Moreover, we discuss the possibility that pharmacological targeting of Warburg metabolism may represent an additional tool to improve already available therapeutic approaches for HCC.

Abstract

Hepatocellular carcinoma (HCC) is one the most frequent and lethal human cancers. At present, no effective treatment for advanced HCC exist; therefore, the overall prognosis for HCC patients remains dismal. In recent years, a better knowledge of the signaling pathways involved in the regulation of HCC development and progression, has led to the identification of novel potential targets for therapeutic strategies. However, the obtained benefits from current therapeutic options are disappointing. Altered cancer metabolism has become a topic of renewed interest in the last decades, and it has been included among the core hallmarks of cancer. In the light of growing evidence for metabolic reprogramming in cancer, a wide number of experimental animal models have been exploited to study metabolic changes characterizing HCC development and progression and to further expand our knowledge of this tumor. In the present review, we discuss several rodent models of hepatocarcinogenesis, that contributed to elucidate the metabolic profile of HCC and the implications of these changes in modulating the aggressiveness of neoplastic cells. We also highlight the apparently contrasting results stemming from different animal models. Finally, we analyze whether these observations could be exploited to improve current therapeutic strategies for HCC.

Comparison of Metabolomic Profiles of Organs in Mice of Different Strains Based on SPME-LC-HRMS

Given that the extent to which genetics alters the metabolomic profile of tissues is still poorly understood, the current study aimed to characterize and investigate the metabolite profiles of brain, liver, kidney and skeletal muscle of two common mouse inbred strains (BALB/c, C57BL/6) and one outbred stock (CD1) for strain-specific differences. Male mice (n = 15) at the age of 12 weeks were used: BALB/c (n = 5), C57BL/6 (n = 5) and CD1 (n = 5). Solid phase microextraction (SPME) was applied for the extraction of analytes from the tissues. SPME fibers (approximately 0.2 mm in diameter) coated with a biocompatible sorbent (4 mm length of hydrophilic-lipophilic balanced particles) were inserted into each organ immediately after euthanasia. Samples were analyzed using liquid chromatography coupled to a Q-Exactive Focus Orbitrap mass spectrometer. Distinct interstrain differences in the metabolomic patterns of brain and liver tissue were revealed. The metabolome of kidney and muscle tissue in BALB/c mice differed greatly from C57BL/6 and CD1 strains. The main compounds differentiating all the targeted organs were alpha-amino acids, purine nucleotides and fatty acid esters. The results of the study indicate that the baseline metabolome of organs, as well as different metabolic pathways, vary widely among general-purpose models of laboratory mice commonly used in biomedical research.

Leaf metabolites profiling between red and green phenotypes of Suaeda salsa by widely targeted metabolomics

The Chenopodiaceae Suaeda salsa (L.) Pall. is a traditional Chinese medicine and food with green and red phenotypes in the Yellow River Delta. We identified 521 metabolites using widely targeted metabolomics, of which 165 were selected as significantly differential metabolites which could be related to the leaf traits of different phenotypes of S. salsa. Two anthocyanins (i.e. cyanidin O-acetylhexoside and delphinidin-3-O-(6'-O-α-rhamnopyranosy l-β-glucopyranoside)) were responsible for red colour in red leaves of S. salsa. Gallic acid, which existed only in red one, was the main reason for leaf succulence. D-arabitol and ribitol were two significantly upregulated carbohydrates in red phenotype. Four alkaloids (i.e. harmaline, aminophylline, pipecolate and trigonelline) were upregulated in red leaves. Hormonal changed involved a decrease in indoleacetic acid-valine (IAA-Val), N6-isopentenyladenosine-5'-monophosphate (iPRMP), isopentenyladenineriboside (iPR), trans-abscisic acid (S-ABA), salicylic acid O-hexoside, methyl jasmonate, N6-isopentenyladenine (iP), trans-zeatin riboside-O-glucoside iso2, trans-zeatin riboside-O-glucoside, and a tendency for dihydrozeatin 9-O-glucoside (DZ9G) down accumulation. In addition, the regulation of amino acids and lipids also contributed to the adaptation of red phenotype to harsh environment. Generally, our findings provide a comprehensive comparison of the metabolites between two phenotypes of S. salsa and an interpretation of phenotypic differences from the point of metabolomics.

GC/MS-based urine metabolomics analysis of renal allograft recipients with acute rejection

BACKGROUND

Acute renal allograft rejection is a common complication after renal transplantation that often leads to chronic rejection and ultimate graft loss. While renal allograft biopsy remains the gold standard for diagnosis of acute rejection, the possibility of biopsy-associated complications cannot be overlooked. The development of noninvasive methods for accurate detection of acute renal allograft rejection is thus of significant clinical importance.

METHODS

Gas chromatography-mass spectrometry (GC/MS) was employed for analysis of urine metabolites in 15 renal allograft recipients with acute rejection and 15 stable renal transplant recipients. Partial least squares (PLS) regression and leave-one-out analyses were performed to ascertain whether the metabolites identified could be exploited to distinguish acute rejection from stable groups as well as their sensitivity and specificity.

RESULTS

Overall, 14 metabolites were significantly altered in the acute rejection group (11 and 3 metabolites displayed higher and lower levels, respectively) relative to the stable transplant group. Data from PLS and leave-one-out analyses revealed that the differential metabolites identified not only distinguished acute rejection from stable transplant recipients but also showed high sensitivity and specificity for diagnosis of renal allograft recipients with acute rejection.

CONCLUSION

Urine metabolites identified with GC/MS can effectively distinguish acute rejection from stable transplant recipients, supporting the potential utility of metabolome analysis in non-invasive diagnosis of acute rejection.

Evaluating Potential Biomarkers of Health and Performance in Veal Calves

Veal calves undergo many challenges in the early stages of their life. Such challenges, including mixing procedures and transportation of calves to the veal farm, may have a negative influence on growth rate, feed intake, metabolism, immunity and disease susceptibility of calves. As a consequence, many hematological, physiological, metabolic and immunological parameters of stressed calves might be altered on arrival at the veal farm. Some of these response variables might be useful as biomarkers of performance of calves at the veal farm as they might provide information about an ongoing disease process, or may predict future diseases. Biomarkers might be helpful to group and manage calves in different risk categories after arrival. By adopting treatment decisions and protocols on a risk-group or individual basis, it would be possible to improve animal health and reduce both disease incidence and antibiotic use. Moreover, the use of biomarkers might be an economically feasible approach as some of them do not need invasive techniques and others can be measured in blood already taken during routine checks. Previous literature mainly assessed the physiological responses of calves to transportation. However, information on the link between on-farm arrival data and future health and performance of veal calves is limited. This review, therefore, examined a wide range of papers and aimed to identify potential biomarkers of future health and performance.

Biomarker Discovery in Animal Health and Disease: The Application of Post-Genomic Technologies

The causes of many important diseases in animals are complex and multifactorial, which present unique challenges. Biomarkers indicate the presence or extent of a biological process, which is directly linked to the clinical manifestations and outcome of a particular disease. Identifying biomarkers or biomarker profiles will be an important step towards disease characterization and management of disease in animals. The emergence of post-genomic technologies has led to the development of strategies aimed at identifying specific and sensitive biomarkers from the thousands of molecules present in a tissue or biological fluid. This review will summarize the current developments in biomarker discovery and will focus on the role of transcriptomics, proteomics and metabolomics in biomarker discovery for animal health and disease.

Bioactive Nutrients and Nutrigenomics in Age-Related Diseases

The increased life expectancy and the expansion of the elderly population are stimulating research into aging. Aging may be viewed as a multifactorial process that results from the interaction of genetic and environmental factors, which include lifestyle. Human molecular processes are influenced by physiological pathways as well as exogenous factors, which include the diet. Dietary components have substantive effects on metabolic health; for instance, bioactive molecules capable of selectively modulating specific metabolic pathways affect the development/progression of cardiovascular and neoplastic disease. As bioactive nutrients are increasingly identified, their clinical and molecular chemopreventive effects are being characterized and systematic analyses encompassing the "omics" technologies (transcriptomics, proteomics and metabolomics) are being conducted to explore their action. The evolving field of molecular pathological epidemiology has unique strength to investigate the effects of dietary and lifestyle exposure on clinical outcomes. The mounting body of knowledge regarding diet-related health status and disease risk is expected to lead in the near future to the development of improved diagnostic procedures and therapeutic strategies targeting processes relevant to nutrition. The state of the art of aging and nutrigenomics research and the molecular mechanisms underlying the beneficial effects of bioactive nutrients on the main aging-related disorders are reviewed herein.

The Progress of Metabolomics Study in Traditional Chinese Medicine Research

Traditional Chinese medicine (TCM) has played important roles in health protection and disease treatment for thousands of years in China and has gained the gradual acceptance of the international community. However, many intricate issues, which cannot be explained by traditional methods, still remain, thus, new ideas and technologies are needed. As an emerging system biology technology, the holistic view adopted by metabolomics is similar to that of TCM, which allows us to investigate TCM with complicated conditions and multiple factors in depth. In this paper, we tried to give a timely and comprehensive update about the methodology progression of metabolomics, as well as its applications, in different fields of TCM studies including quality control, processing, safety and efficacy evaluation. The herbs investigated by metabolomics were selected for detailed examination, including Anemarrhena asphodeloides Bunge, Atractylodes macrocephala Kidd, Pinellia ternate, etc.; furthermore, some valuable results have been obtained and summarized. In conclusion, although the study of metabolomics is at the early phase and requires further scrutiny and validation, it still provides bright prospects to dissect the synergistic action of multiple components from TCM. Overall, with the further development of analytical techniques, especially multi-analysis techniques, we expect that metabolomics will greatly promote TCM research and the establishment of international standards, which is beneficial to TCM modernization.

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.

Stability of energy metabolites-An often overlooked issue in metabolomics studies: A review

Recent advances in analytical chemistry have set the stage for metabolite profiling to help understand complex molecular processes in physiology. Despite ongoing efforts, there are concerns regarding metabolomics workflows, since it has been shown that internal (enzyme activity, blood contamination, and the dynamic nature of metabolite concentrations) as well as external factors (storage, handling, and analysis method) may affect the metabolome profile. Many metabolites are intrinsically instable, particularly some of those associated with central carbon metabolism. While enzymatic conversions have been studied in great detail, nonenzymatic, chemical conversions received comparatively little attention. This review aims to give an in-depth overview of nonenzymatic energy metabolite degradation/interconversion chemistry focusing on a selected range of metabolites. Special attention will be given to qualitative (degradation pathways) as well as quantitative aspects, that may affect the acquisition of accurate data in the context of metabolomics studies. Problems related to the use of isotopically labeled internal standards hindering the quantitative analysis of common metabolites will be presented with an experimental example. Finally, general conclusions and perspectives are given.

Identification of signatory secondary metabolites during mycoparasitism of Rhizoctonia solani by Stachybotrys elegans

Stachybotrys elegans is able to parasitize the fungal plant pathogen Rhizoctonia solani AG-3 following a complex and intimate interaction, which, among others, includes the production of cell wall-degrading enzymes, intracellular colonization, and expression of pathogenic process encoding genes. However, information on the metabolome level is non-existent during mycoparasitism. Here, we performed a direct-infusion mass spectrometry (DIMS) metabolomics analysis using an LTQ Orbitrap analyzer in order to detect changes in the profiles of induced secondary metabolites of both partners during this mycoparasitic interaction 4 and 5 days following its establishment. The diketopiperazine(s) (DKPs) cyclo(S-Pro-S-Leu)/cyclo(S-Pro-S-Ile), ethyl 2-phenylacetate, and 3-nitro-4-hydroxybenzoic acid were detected as the primary response of Rhizoctonia 4 days following dual-culturing with Stachybotrys, whereas only the latter metabolite was up-regulated 1 day later. On the other hand, trichothecenes and atranones were mycoparasite-derived metabolites identified during mycoparasitism 4 and 5 days following dual-culturing. All the above secondary metabolites are known to exhibit bioactivity, including fungitoxicity, and represent key elements that determine the outcome of the interaction being studied. Results could be further exploited in programs for the evaluation of the bioactivity of these metabolites per se or their chemical analogs, and/or genetic engineering programs to obtain more efficient mycoparasite strains with improved efficacy and toxicological profiles.

Metabolomics in paediatric oncology: a potential still to be exploited

Oncology is a branch of medicine in rapid evolution in the attempt to find innovative methods for early diagnosis and a better understanding of tumoral processes leading to the development of new therapies. Metabolomics is the emerging discipline among the "omics" sciences which makes it possible to further expand our knowledge concerning cancer biology. Different studies have revealed the potential role of metabolomics in gaining an understanding of pathophysiological processes in cancer, improving tumor staging, characterizing tumors and searching for biomarkers predictive of therapeutic responses. However, to date there are few works aimed at gaining deeper insights into infantile oncology through metabolomics.

Potential of metabolomics in preclinical and clinical drug development

Metabolomics is an upcoming technology system which involves detailed experimental analysis of metabolic profiles. Due to its diverse applications in preclinical and clinical research, it became an useful tool for the drug discovery and drug development process. This review covers the brief outline about the instrumentation and interpretation of metabolic profiles. The applications of metabolomics have a considerable scope in the pharmaceutical industry, almost at each step from drug discovery to clinical development. These include finding drug target, potential safety and efficacy biomarkers and mechanisms of drug action, the validation of preclinical experimental models against human disease profiles, and the discovery of clinical safety and efficacy biomarkers. As we all know, nowadays the drug discovery and development process is a very expensive, and risky business. Failures at any stage of drug discovery and development process cost millions of dollars to the companies. Some of these failures or the associated risks could be prevented or minimized if there were better ways of drug screening, drug toxicity profiling and monitoring adverse drug reactions. Metabolomics potentially offers an effective route to address all the issues associated with the drug discovery and development.

Metabolomics of ApcMin/+ mice genetically susceptible to intestinal cancer

Background

To determine how diets high in saturated fat could increase polyp formation in the mouse model of intestinal neoplasia, Apc^Min/+, we conducted large-scale metabolome analysis and association study of colon and small intestine polyp formation from plasma and liver samples of Apc^Min/+ vs. wild-type littermates, kept on low vs. high-fat diet. Label-free mass spectrometry was used to quantify untargeted plasma and acyl-CoA liver compounds, respectively. Differences in contrasts of interest were analyzed statistically by unsupervised and supervised modeling approaches, namely Principal Component Analysis and Linear Model of analysis of variance. Correlation between plasma metabolite concentrations and polyp numbers was analyzed with a zero-inflated Generalized Linear Model.

Results

Plasma metabolome in parallel to promotion of tumor development comprises a clearly distinct profile in Apc^Min/+ mice vs. wild type littermates, which is further altered by high-fat diet. Further, functional metabolomics pathway and network analyses in Apc^Min/+ mice on high-fat diet revealed associations between polyp formation and plasma metabolic compounds including those involved in amino-acids metabolism as well as nicotinamide and hippuric acid metabolic pathways. Finally, we also show changes in liver acyl-CoA profiles, which may result from a combination of Apc^Min/+-mediated tumor progression and high fat diet. The biological significance of these findings is discussed in the context of intestinal cancer progression.

Conclusions

These studies show that high-throughput metabolomics combined with appropriate statistical modeling and large scale functional approaches can be used to monitor and infer changes and interactions in the metabolome and genome of the host under controlled experimental conditions. Further these studies demonstrate the impact of diet on metabolic pathways and its relation to intestinal cancer progression. Based on our results, metabolic signatures and metabolic pathways of polyposis and intestinal carcinoma have been identified, which may serve as useful targets for the development of therapeutic interventions.

Metabolome-based genome-wide association study of maize kernel leads to novel biochemical insights

Plants produce a variety of metabolites that have a critical role in growth and development. Here we present a comprehensive study of maize metabolism, combining genetic, metabolite and expression profiling methodologies to dissect the genetic basis of metabolic diversity in maize kernels. We quantify 983 metabolite features in 702 maize genotypes planted at multiple locations. We identify 1,459 significant locus-trait associations (P≤1.8 × 10(-6)) across three environments through metabolite-based genome-wide association mapping. Most (58.5%) of the identified loci are supported by expression QTLs, and some (14.7%) are validated through linkage mapping. Re-sequencing and candidate gene association analysis identifies potential causal variants for five candidate genes involved in metabolic traits. Two of these genes were further validated by mutant and transgenic analysis. Metabolite features associated with kernel weight could be used as biomarkers to facilitate genetic improvement of maize.

NMR HRMAS spectroscopy of lung biopsy samples: Comparison study between human, pig, rat, and mouse metabolomics

PURPOSE

Using the metabolomics by NMR high-resolution magic angle spinning spectroscopy, we assessed the lung metabolome of various animal species in order to identify the animal model that could be substituted to human lung in studies on fresh lung biopsies.

METHODS

The experiments were conducted on intact lung biopsy samples of pig, rat, mouse, and human using a Bruker Advance III 500 spectrometer. Thirty-five to 39 metabolites were identified and 23 metabolites were quantified. Principal component analysis, partial least-squares discriminant analysis, and analysis of variance tests were performed in order to compare the metabolic profiles of each animal lung biopsies to those of the human lung.

RESULTS

The metabolic composition between human and pig lung was similar. However, human lung was distinguishable from mouse and rat regarding: Trimethylamine N-oxide and betaïne which were present in rodents but not in human lung, carnitine, and glycerophosphocholine which were present in mouse but not in human lung. Conversely, succinic acid was undetected in rat lung. Furthermore, fatty acids concentration was significantly higher in rodent lungs compared to human lung.

CONCLUSION

Using the metabolomics by NMR high-resolution magic angle spinning spectroscopy on lung biopsy, samples allowed to highlight that pig lung seems to be close to human lung as regarding its metabolite composition with more similarities than dissimilarities.

Current trends and challenges in sample preparation for global metabolomics using liquid chromatography-mass spectrometry

The choice of sample-preparation method is extremely important in metabolomic studies because it affects both the observed metabolite content and biological interpretation of the data. An ideal sample-preparation method for global metabolomics should (i) be as non-selective as possible to ensure adequate depth of metabolite coverage; (ii) be simple and fast to prevent metabolite loss and/or degradation during the preparation procedure and enable high-throughput; (iii) be reproducible; and (iv) incorporate a metabolism-quenching step to represent true metabolome composition at the time of sampling. Despite its importance, sample preparation is often an overlooked aspect of metabolomics, so the focus of this review is to explore the role, challenges, and trends in sample preparation specifically within the context of global metabolomics by liquid chromatography-mass spectrometry (LC-MS). This review will cover the most common methods including solvent precipitation and extraction, solid-phase extraction and ultrafiltration, and discuss how to improve analytical quality and metabolite coverage in metabolomic studies of biofluids, tissues, and mammalian cells. Recent developments in this field will also be critically examined, including in vivo methods, turbulent-flow chromatography, and dried blood spot sampling.

Gram-negative and Gram-positive bacterial infections give rise to a different metabolic response in a mouse model

Metabolomics has become an important tool to study host-pathogen interactions and to discover potential novel therapeutic targets. In an attempt to develop a better understanding of the process of pathogenesis and the associated host response we have used a quantitative ¹H NMR approach to study the metabolic response to different bacterial infections. Here we describe that metabolic changes found in serum of mice that were infected with Staphylococcus aureus, Streptococcus pneumoniae, Escherichia coli and Pseudomonas aeruginosa can distinguish between infections caused by Gram-positive and Gram-negative bacterial strains. By combining the results of the mouse study with those of bacterial footprinting culture experiments, bacterially secreted metabolites could be identified as potential bacterium-specific biomarkers for P. aeruginosa infections but not for the other strains. Multivariate statistical analysis revealed correlations between metabolic, cytokine and physiological responses. In TLR4 and TLR2 knockout mice, host-response pathway correlated metabolites could be identified and allowed us for the first time to distinguish between bacterial- and host-induced metabolic changes. Since Gram-positive and Gram-negative bacteria activate different receptor pathways in the host, our results suggest that it may become possible in the future to use a metabolomics approach to improve on current clinical microbiology diagnostic methods.

Stable isotope-resolved metabolomics and applications for drug development

Advances in analytical methodologies, principally nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS), during the last decade have made large-scale analysis of the human metabolome a reality. This is leading to the reawakening of the importance of metabolism in human diseases, particularly cancer. The metabolome is the functional readout of the genome, functional genome, and proteome; it is also an integral partner in molecular regulations for homeostasis. The interrogation of the metabolome, or metabolomics, is now being applied to numerous diseases, largely by metabolite profiling for biomarker discovery, but also in pharmacology and therapeutics. Recent advances in stable isotope tracer-based metabolomic approaches enable unambiguous tracking of individual atoms through compartmentalized metabolic networks directly in human subjects, which promises to decipher the complexity of the human metabolome at an unprecedented pace. This knowledge will revolutionize our understanding of complex human diseases, clinical diagnostics, as well as individualized therapeutics and drug response. In this review, we focus on the use of stable isotope tracers with metabolomics technologies for understanding metabolic network dynamics in both model systems and in clinical applications. Atom-resolved isotope tracing via the two major analytical platforms, NMR and MS, has the power to determine novel metabolic reprogramming in diseases, discover new drug targets, and facilitates ADME studies. We also illustrate new metabolic tracer-based imaging technologies, which enable direct visualization of metabolic processes in vivo. We further outline current practices and future requirements for biochemoinformatics development, which is an integral part of translating stable isotope-resolved metabolomics into clinical reality.

Differences in metabolomic profiles of male db/db and s/s, leptin receptor mutant mice

Leptin, a protein hormone secreted by adipose tissue, plays an important role in regulating energy metabolism and the immune response. Despite similar extremes of adiposity, mutant mouse models, db/db, carrying spontaneous deletion of the active form of the leptin receptor (LEPR-B) intracellular signaling domain, and the s/s, carrying a specific point mutation leading to a dysfunctional LEPR-B-STAT3 signaling pathway, have been shown to have robust differences in glucose homeostasis. This suggests specific effects of leptin, mediated by non-STAT3 LEPR-B pathways. Differences in the LEPR-B signaling pathways in these two LEPR-B mutant mice models are expected to lead to differences in metabolism. In the current study, the hypothesized differences in metabolism were investigated using the metabolomics approach. Proton nuclear magnetic resonance spectroscopy ((1)HNMR) was conducted on 24 h urine samples in deuterium oxide using a 500 MHz instrument at 25°C. Principle Component Analysis showed clear separation of urine NMR spectra between the groups (P < 0.05). The CHENOMX metabolite database was used to identify several metabolites that differed between the two mouse models. Significant differences (P < 0.05) in metabolites associated with the glycine, serine, and homocysteine metabolism were observed. The results demonstrate that the metabolomic profile of db/db and s/s mice are fundamentally different and provide insight into the unique metabolic effects of leptin exerted through non-STAT3 LEPR-B pathways.

An untargeted multi-technique metabolomics approach to studying intracellular metabolites of HepG2 cells exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin

Background

In vitro cell systems together with omics methods represent promising alternatives to conventional animal models for toxicity testing. Transcriptomic and proteomic approaches have been widely applied in vitro but relatively few studies have used metabolomics. Therefore, the goal of the present study was to develop an untargeted methodology for performing reproducible metabolomics on in vitro systems. The human liver cell line HepG2, and the well-known hepatotoxic and non-genotoxic carcinogen 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), were used as the in vitro model system and model toxicant, respectively.

Results

The study focused on the analysis of intracellular metabolites using NMR, LC-MS and GC-MS, with emphasis on the reproducibility and repeatability of the data. State of the art pre-processing and alignment tools and multivariate statistics were used to detect significantly altered levels of metabolites after exposing HepG2 cells to TCDD. Several metabolites identified using databases, literature and LC-nanomate-Orbitrap analysis were affected by the treatment. The observed changes in metabolite levels are discussed in relation to the reported effects of TCDD.

Conclusions

Untargeted profiling of the polar and apolar metabolites of in vitro cultured HepG2 cells is a valid approach to studying the effects of TCDD on the cell metabolome. The approach described in this research demonstrates that highly reproducible experiments and correct normalization of the datasets are essential for obtaining reliable results. The effects of TCDD on HepG2 cells reported herein are in agreement with previous studies and serve to validate the procedures used in the present work.

Analysis of metabolic and gene expression changes after hydrodynamic DNA injection into mouse liver

The hydrodynamic injection in mice tail vein of a plasmid (40 µg DNA) bearing the human α1-antitrypsin gene mediates: a) good liver gene transfer resulting in therapeutic plasma levels of human protein (1 mg/ml, approximately) from days 1-10 after injection; b) low liver injury as demonstrated by a poor and transient increase of aspartate aminotransferase (AST) and alanine transaminase (ALT) in mouse plasma; 3) limited expression and metabolic changes in host liver genes and metabolites as evaluated on days 2 and 10 after injection. Groups of three mice were uninjected (control) or hydrodynamically injected with saline or plasmid DNA and then sacrificed on days 2 and 10 after injection. The results of principal component analysis (PCA) show, both in expression microarray and metabolomic analysis, that changes between control and hydrodynamically injected groups are not dramatic and tend to normalize after 10 d. The differences are even smaller between DNA and saline hydrodynamically injected mice. Hydrodynamic injection induces a complex but limited gene expression and metabolic change which includes variations in molecules related to energy metabolism and stress response. The results contribute to support that hydrodynamic method is a safe procedure of liver gene transfer but the long-term effect of hydrodynamic gene transfer procedure, remains to be studied.

Metabolic profiling of vitamin C deficiency in Gulo-/- mice using proton NMR spectroscopy

Nutrient deficiencies are an ongoing problem in many populations and ascorbic acid is a key vitamin whose mild or acute absence leads to a number of conditions including the famously debilitating scurvy. As such, the biochemical effects of ascorbate deficiency merit ongoing scrutiny, and the Gulo knockout mouse provides a useful model for the metabolomic examination of vitamin C deficiency. Like humans, these animals are incapable of synthesizing ascorbic acid but with dietary supplements are otherwise healthy and grow normally. In this study, all vitamin C sources were removed after weaning from the diet of Gulo-/- mice (n = 7) and wild type controls (n = 7) for 12 weeks before collection of serum. A replicate study was performed with similar parameters but animals were harvested pre-symptomatically after 2-3 weeks. The serum concentration of 50 metabolites was determined by quantitative profiling of 1D proton NMR spectra. Multivariate statistical models were used to describe metabolic changes as compared to control animals; replicate study animals were used for external validation of the resulting models. The results of the study highlight the metabolites and pathways known to require ascorbate for proper flux.

Metabolomics and malaria biology

Metabolomics has ushered in a novel and multi-disciplinary realm in biological research. It has provided researchers with a platform to combine powerful biochemical, statistical, computational, and bioinformatics techniques to delve into the mysteries of biology and disease. The application of metabolomics to study malaria parasites represents a major advance in our approach towards gaining a more comprehensive perspective on parasite biology and disease etiology. This review attempts to highlight some of the important aspects of the field of metabolomics, and its ongoing and potential future applications to malaria research.

Xenobiotic metabolism: a view through the metabolometer

The combination of advanced ultraperformance liquid chromatography coupled with mass spectrometry, chemometrics, and genetically modified mice provide an attractive raft of technologies with which to examine the metabolism of xenobiotics. Here, a reexamination of the metabolism of the food mutagen PhIP (2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine), the suspect carcinogen areca alkaloids (arecoline, arecaidine, and arecoline 1-oxide), the hormone supplement melatonin, and the metabolism of the experimental cancer therapeutic agent aminoflavone is presented. In all cases, the metabolic maps of the xenobiotics were considerably enlarged, providing new insights into their toxicology. The inclusion of transgenic mice permitted unequivocal attribution of individual and often novel metabolic pathways to particular enzymes. Last, a future perspective for xenobiotic metabolomics is discussed and its impact on the metabolome is described. The studies reviewed here are not specific to the mouse and can be adapted to study xenobiotic metabolism in any animal species, including humans. The view through the metabolometer is unique and visualizes a metabolic space that contains both established and unknown metabolites of a xenobiotic, thereby enhancing knowledge of their modes of toxic action.

A mutation in the mitochondrial fission gene Dnm1l leads to cardiomyopathy

Mutations in a number of genes have been linked to inherited dilated cardiomyopathy (DCM). However, such mutations account for only a small proportion of the clinical cases emphasising the need for alternative discovery approaches to uncovering novel pathogenic mutations in hitherto unidentified pathways. Accordingly, as part of a large-scale N-ethyl-N-nitrosourea mutagenesis screen, we identified a mouse mutant, Python, which develops DCM. We demonstrate that the Python phenotype is attributable to a dominant fully penetrant mutation in the dynamin-1-like (Dnm1l) gene, which has been shown to be critical for mitochondrial fission. The C452F mutation is in a highly conserved region of the M domain of Dnm1l that alters protein interactions in a yeast two-hybrid system, suggesting that the mutation might alter intramolecular interactions within the Dnm1l monomer. Heterozygous Python fibroblasts exhibit abnormal mitochondria and peroxisomes. Homozygosity for the mutation results in the death of embryos midway though gestation. Heterozygous Python hearts show reduced levels of mitochondria enzyme complexes and suffer from cardiac ATP depletion. The resulting energy deficiency may contribute to cardiomyopathy. This is the first demonstration that a defect in a gene involved in mitochondrial remodelling can result in cardiomyopathy, showing that the function of this gene is needed for the maintenance of normal cellular function in a relatively tissue-specific manner. This disease model attests to the importance of mitochondrial remodelling in the heart; similar defects might underlie human heart muscle disease.

Untargeted metabolomics

Along with genes and proteins, metabolites play important roles in sustaining life. Their functions include "primary" functions in metabolism and energy storage, as well as "secondary" functions in cell-to-cell signaling, metal acquisition, and virulence. There remains much to be learned about the in vivo roles of metabolites. Approaches that accelerate measurement of metabolite levels directly from cells and tissues should increase our understanding of the diverse roles of metabolites and potentially lead to discovery of novel metabolites and metabolic pathways. Metabolomics is an important comparative tool to study global metabolite levels in samples under various conditions. In this unit, the steps needed to perform a mass spectrometry (MS)--based untargeted metabolomics experiment using bacterial supernatants are detailed. In contrast to a targeted metabolomics experiment, which measures ions from known metabolites, an untargeted metabolomics experiment registers all ions within a certain mass range, including ions belonging to structurally novel metabolites. The protocols in this unit describe the conditions necessary for analyzing hydrophobic metabolites and provide an example of how to structurally characterize a novel metabolite.

The Sod2 mutant mouse as a model for oxidative stress: a functional proteomics perspective

Oxidative stress has been implicated in the pathogenesis of numerous human diseases and disorders, but the mechanistic basis often remains enigmatic. The Sod2 mutant mouse, which is sensitized to mitochondrial stress, is an ideal mutant model for studying the role of oxidative stress in a diverse range of complications arising from mitochondrial dysfunction and diminished antioxidant defense. To fully appreciate the widespread molecular consequences under increased oxidative stress, a systems approach utilizing proteomics is able to provide a global overview of the complex biological changes, which a targeted single biomolecular approach cannot address fully. This review focuses on the applications of mass spectrometry and functional proteomics in the Sod2 mouse. The combinatorial approach provides novel insights into the interplay of chemistry and biology, free radicals and proteins, thereby augmenting our understanding of how redox perturbations influence protein dynamics. Ultimately, this knowledge can lead to the development of free radical-targeted therapies.

Introduction to omics

Exploiting the potential of omics for clinical diagnosis, prognosis, and therapeutic purposes has currently been receiving a lot of attention. In recent years, most of the effort has been put into demonstrating the possible clinical applications of the various omics fields. The cost-effectiveness analysis has been, so far, rather neglected. The cost of omics-derived applications is still very high, but future technological improvements are likely to overcome this problem. In this chapter, we will give a general background of the main omics fields and try to provide some examples of the most successful applications of omics that might be used in clinical diagnosis and in a therapeutic context.

Ultra-high performance liquid chromatography-mass spectrometry for the metabolomic analysis of urine in colorectal cancer

We report here the results of a pilot study in which ultra-high performance liquid chromatography/time-of- flight-mass spectrometry (UPLC/TOF-MS) and multivariate statistical analysis (supervised partial least squares discriminant analysis, PLS-DA) were applied for urinary metabolite profiling and data interpretation. The results of the PLS-DA indicated that the metabolic pattern as a whole was significantly different between the groups of preoperative colorectal cancer (CRC) patients, postoperative CRC patients, and healthy volunteers, respectively. The preoperative group of patients showed significantly increased levels of low-molecular weight compounds (LMC) MW 283 and MW 234 in comparison to the group of healthy volunteers group. After the operation, the levels of these two LMC significantly decreased. These preliminary results suggest that the UPLC-MS-based method coupled with pattern recognition will likely lead to procedures with the potential to be clinically applicable for the diagnosis of CRC and, consequently, to an improvement in patient prognosis.

Interdependence of signal processing and analysis of urine 1H NMR spectra for metabolic profiling

Metabolic profiling of urine presents challenges because of the extensive random variation of metabolite concentrations and the dilution resulting from changes in the overall urine volume. Thus statistical analysis methods play a particularly important role; however, appropriate choices of these methods are not straightforward. Here we investigate constant and variance-stabilization normalization of raw and peak picked spectra, for use with exploratory analysis (principal component analysis) and confirmatory analysis (ordinary and Empirical Bayes t-test) in (1)H NMR-based metabolic profiling of urine. We compare the performance of these methods using urine samples spiked with known metabolites according to a Latin square design. We find that analysis of peak picked and logarithm-transformed spectra is preferred, and that signal processing and statistical analysis steps are interdependent. While variance-stabilizing transformation is preferred in conjunction with principal component analysis, constant normalization is more appropriate for use with a t-test. Empirical Bayes t-test provides more reliable conclusions when the number of samples in each group is relatively small. Performance of these methods is illustrated using a clinical metabolomics experiment on patients with type 1 diabetes to evaluate the effect of insulin deprivation.

Application and analysis of structure-switching aptamers for small molecule quantification

Modern tools for the analysis of cellular function aim for the quantitative measurement of all members of a given class of biological molecules. Of the analyte classes, nucleic acid measurements are typically the most tractable, both on an individual analyte basis and in parallel. Thus, tools are being sought to enable measurement of other cellular molecules using nucleic acid biosensors. Of the variety of potential nucleic acid biosensor strategies, structure-switching aptamers (SSAs) present a unique opportunity to couple sensing and readout of the target molecule. However, little has been characterized about the parameters that determine the fidelity of the signal from SSA biosensors. In this study, a small molecule biosensor based on a SSA was engineered to detect the model small molecule, theophylline, in solution. Quantitative theophylline detection over nearly three orders-of-magnitude was achieved by scintillation counting and quantitative PCR. Further analysis showed that the biosensor fidelity is primarily controlled by the relative stability of the two conformations of the SSA.

Prospects for clinical cancer metabolomics using stable isotope tracers

Metabolomics provides a readout of the state of metabolism in cells or tissue and their responses to external perturbations. For this reason, the approach has great potential in clinical diagnostics. For more than two decades, we have been using stable isotope tracer approaches to probe cellular metabolism in greater detail. The ability to enrich common compounds with rare isotopes such as carbon ((13)C) and nitrogen ((15)N) is the only practical means by which metabolic pathways can be traced, which entails following the fate of individual atoms from the source molecule to products via metabolic transformation. Changes in regulation of pathways are therefore captured by this approach, which leads to deeper understanding of the fundamental biochemistry of cells. Using lessons learned from pathways tracing in cells and organs, we have been applying this methodology to human cancer patients in a clinical setting. Here we review the methodologies and approaches to stable isotope tracing in cells, animal models and in humans subjects.

Detection of apoptosis in tissue sections

TUNEL-based assays were used to demonstrate the presence of apoptotic cells in tissue sections derived from target tissues of animal models of different diseases. Emphasis was placed on tissue preparation and fixation, as these are crucial to successful histological staining. The protocol suggested here facilitates not only the reliable detection of TUNEL-positive cells but the immunodetection of different proteins in these cells and the surrounding tissues by DAB or fluorescence-based immunostaining.

Alzheimer's disease beyond the genomic era: nuclear magnetic resonance (NMR) spectroscopy-based metabolomics

Alzheimer's disease (AD) is a complex disease, with no definitive biomarkers available that allow clinical diagnosis; this represents a major problem for the advance of efficient drug discovery programs. A successful approach towards the understanding and treatment of AD should take into consideration this complex nature. In this sense, metabolic networks are subject to severe stoichiometric restrictions. Metabolomics amplifies changes both in the proteome and the genome, and represents a more accurate approximation to the phenotype of an organism in health and disease. In this article, we will examine the current rationale for metabolomics in AD, its basic methodology and the available data in animal models and human studies. The discussed topics will highlight the importance of being able to use the metabolomic information in order to understand disease mechanisms from a systems biology perspective as a non-invasive approach to diagnose and grade AD. This could allow the assessment of new therapies during clinical trials, the identification of patients at risk to develop adverse effects during treatment and the final implementation of new tools towards a more personalized medicine.

Stable isotope-assisted metabolomics in cancer research

Stable Isotopes are nontoxic, naturally occurring elemental surrogates that are fully compatible with live organisms, including humans in a clinical setting. The ability to enrich common compounds with rare isotopes such as carbon ((13)C) and nitrogen ((15)N) is the only practical means by which metabolic pathways can be traced, performed by following the fate of individual atoms from the source molecules to products via metabolic transformation. Changes in regulation of pathways are therefore captured by this approach, which leads to deeper understanding of fundamental biochemistry of cancer compared with non-cancerous cells, which can lead to new diagnostic tools.

Metabolic profiling using Fourier-transform ion-cyclotron-resonance mass spectrometry

With the aid of the extreme resolving power of Fourier-transform ion-cyclotron-resonance mass spectrometry (FT-ICR/MS), we have developed a metabolomics platform for high-throughput metabolic profiling and metabolite candidate identification integrating a data-processing system, the Dr.DMASS program ( http://kanaya.naist.jp/DrDMASS/ ), and a metabolite-species database, KNApSAcK ( http://kanaya.aist-nara.ac.jp/KNApSAcK/ ). We discuss the potential of this FT-ICR/MS-based metabolic profiling scheme as a general metabolomics tool by clarification of plant metabolic disorders and specific metabolite accumulation patterns caused by herbicidal enzyme inhibitors.

Proteomic profiling of animal models mimicking skeletal muscle disorders

Over the last few decades of biomedical research, animal models of neuromuscular diseases have been widely used for determining pathological mechanisms and for testing new therapeutic strategies. With the emergence of high-throughput proteomics technology, the identification of novel protein factors involved in disease processes has been decisively improved. This review outlines the usefulness of the proteomic profiling of animal disease models for the discovery of new reliable biomarkers, for the optimization of diagnostic procedures and the development of new treatment options for skeletal muscle disorders. Since inbred animal strains show genetically much less interindividual differences as compared to human patients, considerably lower experimental repeats are capable of producing meaningful proteomic data. Thus, animal model proteomics can be conveniently employed for both studying basic mechanisms of molecular pathogenesis and the effects of drugs, genetic modifications or cell-based therapies on disease progression. Based on the results from comparative animal proteomics, a more informed decision on the design of clinical proteomics studies could be reached. Since no one animal model represents a perfect pathobiochemical replica of all of the symptoms seen in complex human disorders, the proteomic screening of novel animal models can also be employed for swift and enhanced protein biochemical phenotyping.