Genomics, proteomics and metabonomics in toxicology: hopefully not 'fashionomics'

Application of Q-TOF-MS based metabonomics techniques to analyze the plasma metabolic profile changes on rats following death due to acute intoxication of phorate

Organophosphorus pesticides (OP_S) are widely used in the world, and many poisoning cases were caused by them. Phorate intoxication is especially common in China. However, there are currently few methods for discriminating phorate poisoning death from phorate exposure after death and interpretation of false-positive results due to the lack of effective biomarkers. In this study, we investigated the metabonomics of rat plasma at different dose levels of acute phorate intoxication using ultra-performance liquid chromatography quadrupole-time of flight mass spectrometry (UPLC-Q-TOF-MS) analysis. A total of 11 endogenous metabolites were significantly changed in the groups exposed to phorate at LD₅₀ level and three times of LD50 (3LD₅₀) level compared with the control group, which could be potential biomarkers of acute phorate intoxication. Plasma metabonomics analysis showed that diethylthiophosphate (DETP) could be a useful biomarker of acute phorate intoxication. The levels of uric acid, acylcarnitine, succinate, gluconic acid, and phosphatidylcholine (PC) (36:2) were increased, while pyruvate level was decreased in all groups exposed to phorate. The levels of ceramides (Cer) (d 18:0/16:0), palmitic acid, and lysophosphatidylcholine (lysoPC) (18:1) were only changed after 3LD₅₀ dosage. The results of this study indicate that the dose-dependent relationship exists between metabolomic profile change and toxicities associated with apoptosis, fatty acid metabolism disorder, energy metabolism disorder especially tricarboxylic acid (TCA) cycle, as well as liver, kidney, and nervous system functions after acute exposure of phorate. This study shows that metabonomics is a useful tool in identifying biomarkers for the forensic toxicology study of phorate poisoning.

Construction and Analysis of Human Diseases and Metabolites Network

The relationship between aberrant metabolism and the initiation and progression of diseases has gained considerable attention in recent years. To gain insights into the global relationship between diseases and metabolites, here we constructed a human diseases-metabolites network (HDMN). Through analyses based on network biology, the metabolites associated with the same disorder tend to participate in the same metabolic pathway or cascade. In addition, the shortest distance between disease-related metabolites was shorter than that of all metabolites in the Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic network. Both disease and metabolite nodes in the HDMN displayed slight clustering phenomenon, resulting in functional modules. Furthermore, a significant positive correlation was observed between the degree of metabolites and the proportion of disease-related metabolites in the KEGG metabolic network. We also found that the average degree of disease metabolites is larger than that of all metabolites. Depicting a comprehensive characteristic of HDMN could provide great insights into understanding the global relationship between disease and metabolites.

A History of the Molecular Initiating Event

The adverse outcome pathway (AOP) framework provides an alternative to traditional in vivo experiments for the risk assessment of chemicals. AOPs consist of a number of key events (KEs) linked by key event relationships across a range of biological organization backed by scientific evidence. The first KE in the pathway is the molecular initiating event (MIE)-the initial chemical trigger that starts an AOP. Over the past 3 years the AOP conceptual framework has gained a large amount of momentum in toxicology as an alternative to animal methods, and so the MIE has come into the spotlight. What is an MIE? How can MIEs be measured or predicted? What research is currently contributing to our understanding of MIEs? In this Perspective we outline answers to these key questions.

Nonclinical Safety and Toxicology

Nonclinical safety pharmacology and toxicology testing of drug candidates assess the potential adverse effects caused by the drug in relation to its intended use in humans. Hazards related to a drug have to be identified and the potential risks at the intended exposure have to be evaluated in comparison to the potential benefit of the drug. Preclinical safety is thus an integral part of drug discovery and drug development. It still causes significant attrition during drug development.Therefore, there is a need for smart selection of drug candidates in drug discovery including screening of important safety endpoints. In the recent years,there was significant progress in computational and in vitro technology allowing in silico assessment as well as high-throughput screening of some endpoints at very early stages of discovery. Despite all this progress, in vivo evaluation of drug candidates is still an important part to safety testing. The chapter provides an overview on the most important areas of nonclinical safety screening during drug discovery of small molecules.

Incidence and nature of testicular toxicity findings in pharmaceutical development

BACKGROUND

Testicular toxicity (TT) is a sporadic and challenging issue in pharmaceutical drug development. Efforts to develop TT screening assays or biomarkers have been overshadowed by consortium efforts to predict drug-induced toxicities such as hepatic injury, which are encountered more frequently.

METHODS

To gauge the current state of the field and to prioritize future TT activities, the International Life Sciences Institute-Health and Environmental Sciences Institute Developmental and Reproductive Toxicology (DART) Technical Committee sponsored a survey to better understand the incidence and nature of TT findings encountered during drug development.

RESULTS

Highlights from the 16 survey respondents include: (1) Although preclinical TT was encountered relatively infrequently, half of the participants observed repeated problems with TT during pharmaceutical development, (2) despite control measures such as use of sexually mature animals to diminish confounding effects of spurious lesions, interpretation of TT remains a challenge, (3) "traditional" evaluation tools such as hormonal monitoring and newer approaches such as -omics are utilized to investigate testicular changes, and (4) an understanding of the risk and relevance of TT findings is achieved through joint consideration of factors such as species specificity, potential mode of action, and safety margins.

CONCLUSIONS

TT remains a relatively uncommon but persistent challenge in pharmaceutical development. Although current preclinical TT approaches appear to be effective in limiting the occurrence of pharmaceutical candidate attrition in clinical trials, improved biomarker or screening platforms would allow companies to identify TT at an earlier stage, thus decreasing the time and resources expended on safety evaluation of pharmaceutical candidates.

A metabonomic and proteomic analysis of changes in IMCD3 cells chronically adapted to hypertonicity

BACKGROUND

The genomic response to adaptation of IMCD3 cells to hypertonicity results in both upregulation and downregulation of a variety of genes.

METHOD

The present study was undertaken to assess the metabonomic and proteomic response of IMCD3 cells that have been chronically adapted to hypertonicity (600 and 900 mosm/kg H(2)O) as compared to cells under isotonic conditions.

RESULTS

Adaptation of IMCD3 cells to hypertonic conditions resulted in a change of a wide range of organic osmolytes, including sorbitol (+8,291%), betaine (+1,099%), myo-inositol (+669%), taurine (+113%) and glycerophosphorylcholine (+61%). Evaluation of the polyol pathway for sorbitol production revealed a reduction in sorbitol dehydrogenase and an increase in aldose reductase mRNA in adapted cells. Proteome analysis revealed increased expression of six glycolytic proteins, including malic enzyme and pyruvate carboxylase, indicating the activation of the pyruvate shunt and changes in glucose metabolism. This study showed that the observed reduction in cell replication could possibly reflect a redirection of cellular energy from cell growth and replication to maintenance of intracellular ion levels in chronically adapted cells.

CONCLUSION

The combined metabonomic and proteomic analysis was shown to be a very helpful tool for the analysis of the effects caused by chronic adaptation to hypertonicity. It made it possible to better evaluate the importance of certain changes that occur in the process of adaptation.

Ocular effects of exposure to industrial chemicals: clinical management and proteomic approaches to damage assessment

Industrial chemicals in a variety of applications are often found in highly populated areas and their presence carries risks. The threat of serious consequences from inadvertent or intentional events involving hazardous chemicals is a possibility. Extremism and/or other illicit activities pose environmental threats from chemical exposures. We present here a review of the threat of ocular injury in small-and large-scale chemical releases and discuss mechanisms of damage and repair to the eyes. The emerging field of proteomics has been described in relation to its potential role in the assessment of ocular changes following chemical exposures and management of ocular trauma.

Metabonomics in pharmaceutical discovery and development

Metabonomics has emerged as a key technology in pharmaceutical discovery and development, evolving as the small molecule counterpart of transcriptomics and proteomics. In drug discovery laboratories, metabonomics aids in target identification, phenotyping, and the understanding of the biochemical basis of disease and toxicity. This review focuses on three areas where metabonomics is used in the industry: (1) analytical considerations, (2) chemometric and statistical concerns, and (3) biological aspects and applications.

Toxicogenomics applied to predictive and exploratory toxicology for the safety assessment of new chemical entities: a long road with deep potholes

Toxicology is the perturbation of metabolism by external factors such as xenobiotics, environmental factors or drugs. As such, toxicology covers a broad range of fields from studies of the whole organism responses to minute biochemical events. Mechanistic toxicogenomics is an attempt to harness genomic tools to understand the physiological basis for a toxic event based on an analysis of transcriptional, translational or metabolomic profiles. These studies are complicated by non-toxic adaptive responses in transcript, protein or metabolite expression levels that have to be distinguished from those that are proximally related to the toxic event. Substantial progress has been made on the identification of biomarkers and the establishment of screens derived from such toxicogenomics studies. The ultimate goal, of course, is predictive toxicogenomics, which is an attempt to infer the likelihood of occurrence of a toxic event with exposure to a new agent based upon comparative responses with large databases of gene, protein or metabolite expression data. Gene expression databases are currently limited by the fact that measurable toxic phenotypes generally precede or at best coincide with the earliest observable changes in transcriptional profiles. Unfortunately, predictive protein databases have been limited by technical difficulties. Metabonomics-based databases, which would probably have the highest predictive value, are limited in turn by the inability to perform high dose studies in humans. This chapter will conclude by reviewing those elements of toxicogenomics that apply specifically to the development of anti-infectives and the potential for accurately modelling the toxicity of future drugs.

Metabonomics Study of Intestinal Fistulas Based on Ultraperformance Liquid Chromatography Coupled with Q-TOF Mass Spectrometry (UPLC/Q-TOF MS)

Ultraperformance liquid chromatography coupled with Q-TOF mass spectrometry (UPLC/Q-TOF MS) is an effective and sensitive analytical tool. A UPLC/Q-TOF MS-based metabonomics technique was employed to investigate sera from 40 patients with intestinal fistula and 17 healthy volunteers in an effort to find potential biomarkers of the disease and reveal their pathophysiological changes. After the UPLC/Q-TOF analysis, the retention time and m/z data pair for each peak were detected. Partial least squares discriminant analysis (PLS-DA) and coefficient of correlation analysis were used for marker selection and identification. According to the data, nine potential biomarkers were identified: glycochenodeoxycholic acid, glycocholic [corrected] acid, taurochenodexycholic acid, taurodeoxycholic acid, and two kinds of lysophosphatidyl choline (C16:0 and C18:2) were found with increased concentrations in the patients, and phenylalanine, tryptophan, and carnitine were found with decreased concentrations in the patients. The results suggested that a subclinical hepatic injury and abnormal metabolism of two essential amino acids (phenylalanine and tryptophan), and a key compound of fatty acid synthesis and beta-oxidation (carnitine), occurred in the fistula patients. This work demonstrates the utility of metabonomics as a top-down systems biology tool for understanding clinical problems.

How omics technologies can contribute to the ‘3R’ principles by introducing new strategies in animal testing

In Europe, in light of ethical, political and commercial pressure, every effort should be made to replace animals with alternatives (e.g. in vitro models), to reduce the number of animals used in experiments to a minimum and to refine current testing strategies in a way that ensures animals undergo minimum pain and distress. Methods currently used in toxicology for mandatory safety tests rely heavily on the dosing of animals, followed by the detection and pathological evaluation of manifested toxic lesions. Through the integration of so-called 'omics' technologies, a global analysis of treatment-related changes on the molecular level becomes feasible and therefore might provide a means for predicting toxicity before classical toxicological endpoints. This Opinion article summarizes the key features of pushing the '3R' principles in animal testing, discusses the possible impact on safety testing in toxicology and describes the potential of using omics technologies for improved toxicity prediction to meet ethical, political and commercial expectations.

Metabonomic study of aristolochic acid-induced nephrotoxicity in rats

This paper describes a metabonomic study characterizing the nephrotoxicity induced by aristolochic acid (AA), a suspected kidney toxicant. For these studies, we examined the biochemical compositions of AA-treated rat urine using LC-MS and pattern recognition methods. The biochemical and histological patterns of rat groups treated with different AA sources showed distinct differences from those of the control group. Certain metabolic pathways, such as homocysteine formation and the folate cycle were significantly accelerated, while others, including arachidonic acid biosynthesis, were decreased. A subset-validation procedure using linear discriminant analysis (LDA) and selected predictive variables indicated that approximately 95% of the treated and nontreated rat urine samples were classified correctly into their respective treatment groups. The results suggested that this metabonomic approach is a promising methodology for the rapid in vivo screening of nephrotoxicity associated with ingesting multi-ingredient medicinal herb supplements, and provides a valid method for comprehending the chemical-induced perturbations in the metabolic network and the networked lesions.

Toxicogenomic analysis methods for predictive toxicology

Toxicogenomics, the application of genomic data to elucidate or predict an organism's response to a toxicant, can inform the drug development process in important ways. It is apparent that standardized approaches to many types of toxicogenomic questions are still being formulated. Specifically, a significant body of proof of principle studies has emerged that demonstrates a range of statistical methodologies applied to predictive toxicology. These studies rely on class prediction methods--mathematical models generated using the gene expression profiles of known toxins from representative toxicological classes--to predict the toxicological effect of a compound based on the similarities between its gene expression profile and the profiles of a given toxicological class. Class prediction methods hold promise for increasing the rate at which compounds can be evaluated for toxicity early in the drug discovery process, while at the same time reducing the length of toxicological studies and their associated costs. Class prediction methods are informed by class comparison and class discovery steps, which inform, respectively, the selection of genes whose response can be used to distinguish among the toxicological classes and the number of classes distinguishable using the response of these genes. Together these steps use a variety of complementary statistical techniques to achieve a successful class prediction model. This report attempts to review some of the themes that appear to be emerging in the application of these techniques to predictive toxicology methods over toxicogenomics' short history.

Toxicogenomics in Risk Assessment: Applications and Needs

Since its inception, there have been high expectations for the science of toxicogenomics to decrease the uncertainties associated with the risk assessment process by providing valuable insights into toxic mechanisms of action. However, the application of these data into risk assessment practices is still in the early stages of development, and proof of principle experiments have yet to emerge. The following discusses some potential applications as well as impediments that warrant a concerted investigation from all stakeholders in order to facilitate the acceptance and subsequent incorporation of toxicogenomics into regulatory decision making.

Gene expression profiling for pharmaceutical safety assessment

Toxicogenomics is the application of gene expression profiling technology to toxicology. This results in the generation of very large and complex gene expression data sets associated with the development of toxicities. It is widely assumed that this data can be deconvoluted to reveal novel insights into toxicological processes that are of value to the task of risk assessment. More specifically, it is hoped that toxicogenomics will aid in the prediction of the toxic potential and mechanisms of toxicity of novel chemical entities. On the basis of such promise, the pharmaceutical industry has invested heavily in this area, as the perceived rewards in terms of improved pipeline efficiency and safer drugs are immense. Consequently, a great deal of groundwork has been done over the past several years to establish working methods in toxicogenomics, both within industry and academia, demonstrating utility in proof-of-concept studies, generating the databases on which some approaches depend, and developing new data analysis tools. Despite such activity, there is little reported evidence to suggest that toxicogenomics is making a significant impact on the discovery and development of drugs. This may partly reflect the understandable reluctance of pharmaceutical industries to share information in a competitive environment. It may also partly reflect difficulties in bridging the gap between theory and practice, as is required to deliver real value to the industry. This review will assess the successes and shortcomings of toxicogenomics, and consider how it can be usefully applied to a drug discovery pipeline.

A lipidomic study of the effects of N-methyl-N'-nitro-N-nitrosoguanidine on sphingomyelin metabolism

Systems biology is a new and rapidly developing research area in which, by quantitatively describing the interaction among all the individual components of a cell, a systems-level understanding of a biological response can be achieved. Therefore, it requires high-throughput measurement technologies for biological molecules, such as genomic and proteomic approaches for DNA/RNA and protein, respectively. Recently, a new concept, lipidomics, which utilizes the mass spectrometry (MS) method for lipid analysis, has been proposed. Using this lipidomic approach, the effects of N-methyl-N'-nitro-N-nitrosoguanidine (MNNG) on sphingomyelin metabolism, a major class of sphingolipids, were evaluated. Sphingomyelin molecules were extracted from cells and analyzed by matrix-assisted laser desorption ionization-time of flight MS. It was found that MNNG induced profound changes in sphingomyelin metabolism, including the appearance of some new sphingomyelin species and the disappearance of some others, and the concentrations of several sphingomyelin species also changed. This was accompanied by the redistribution of acid sphingomyelinase (ASM), a key player in sphingomyelin metabolism. On the other hand, imipramine, an inhibitor of ASM, caused the accumulation of sphingomyelin. It also prevented some of the effects of MNNG, as well as the redistribution of ASM. Taken together, these data suggested that the lipidomic approach is highly effective for the systematic analysis of cellular lipids metabolism.