An integrated Qual/Quan strategy for ganglioside lipidomics using high-resolution mass spectrometry and Skyline software.

RATIONALE: Gangliosides (GS) are attractive targets in biomarker discovery because of their physiological significance in numerous human diseases including certain cancers and developmental and metabolic disorders. The robust strategy described here enables the profiling of numerous GS while obtaining quantitative data of exploratory biomarkers present in human plasma and whole blood. METHOD: The GS from human blood, human plasma, and several cell lines were extracted using a mixture of methanol and isopropanol/0.1% formic acid followed by direct analysis of the supernatant. The simultaneous Qualitative and Quantitative (Qual/Quan) approach involves micro flow (20 µL/min) high pressure liquid chromatography (HPLC)/high-resolution mass spectrometry (HRMS) and post-acquisition data processing with Skyline software for profiling numerous GS in biological matrices. The quantitative assay involves reverse-phase liquid chromatography/HRMS and calibration curves using commercially available GS. RESULTS: Protein precipitation resulted in ~60%-80% GS recovery from biological matrices. Direct injection of the extract allowed for quantification of targeted GS in human blood, plasma, and cancer cell lines. The lower limit of detection for the target analytes, GM1, GT1, GD1, spiked into 1% BSA/PBS, ranged from 1 to 10 ng/mL. Human lung cancer cell lines contained variable amounts (1-130 ng/mL) of soluble Fuc-GM1 analogs, potential biomarkers of lung cancer. CONCLUSIONS: A combination of simple extraction and micro-HPLC/HRMS allowed for quantification of GS in human serum and whole blood. Integration of HRMS with Skyline allowed for GS profiling in the same samples using post-acquisition HRMS data without the need for reanalysis. The strategy presented here is expected to play an important role in profiling exploratory GS biomarkers in discovery bioanalytical research.

Metabolomic and transcriptomic changes induced by overnight (16 h) fasting in male and female Sprague-Dawley rats.

The overnight (16-h) fast is one of the most common experimental manipulations performed in rodent studies. Despite its ubiquitous employment, a comprehensive evaluation of metabolomic and transcriptomic sequelae of fasting in conjunction with routine clinical pathology evaluation has not been undertaken. This study assessed the impact of a 16-h fast on urine and serum metabolic profiles, transcript profiles of liver, psoas muscle, and jejunum as well as on routine laboratory clinical pathology parameters. Fasting rats had an approximate 12% relative weight decrease compared to ad libitum fed animals, and urine volume was significantly increased. Fasting had no effect on hematology parameters, though several changes were evident in serum and urine clinical chemistry data. In general, metabolic changes in biofluids were modest in magnitude but broad in extent, with a majority of measured urinary metabolites and from 1/3 to 1/2 of monitored serum metabolites significantly affected. Increases in fatty acids and bile acids dominated the upregulated metabolites. Downregulated serum metabolites were dominated by diet-derived and/or gut-microflora derived metabolites. Major transcriptional changes included genes with roles in fatty acid, carbohydrate, cholesterol, and bile acid metabolism indicating decreased activity in glycolytic pathways and a shift toward increased utilization of fatty acids. Typically, several genes within these metabolic pathways, including key rate limiting genes, changed simultaneously, and those changes were frequently correlative to changes in clinical pathology parameters or metabolomic data. Importantly, up- or down-regulation of a variety of cytochrome P450s, transporters, and transferases was evident. Taken together, these data indicate profound consequences of fasting on systemic biochemistry and raise the potential for unanticipated interactions, particularly when metabolomic or transcriptomic data are primary end points.

Urinary metabolites of 2-bromoethanamine identified by stable isotope labelling: evidence for carbamoylation and glutathione conjugation.

2-Bromoethanamine (BEA) causes renal papillary necrosis (RPN) in rats after a single dose and has been widely used as a model compound for studying the lesion. Although the metabolism of BEA may be an important determinant of toxicity, the metabolic fate of the compound has not been fully elucidated. To date, the only identified BEA metabolites are aziridine, 2-oxazolidone and 5-hydroxy-2-oxazolidone. In this study, stable isotope labelling (SIL) of BEA analogs ((¹³C and ²H) were used to differentiate generated BEA metabolites from endogenous molecules which enabled the accurate liquid chromatography mass spectrometry detection of more than 180 novel metabolites. BEA metabolism was evaluated in rats after acute administration of a non-toxic dose (50 mg/kg) and a toxic dose (250 mg/kg) that caused frank RPN and polyuria. Newly identified metabolites include three carbamoylation products, two mercapturic acids and a group of amino acid conjugates. Overall, the results indicate that BEA metabolism is very complex, suggest the potential formation of reactive intermediates and establish that BEA is subject to conjugation with glutathione. The results also demonstrate the utility and sensitivity of the SIL approach for identification of metabolites from small, reactive compounds.

Normalization strategies for metabonomic analysis of urine samples.

Unlike plasma and most biological fluids which have solute concentrations that are tightly controlled, urine volume can vary widely based upon water consumption and other physiological factors. As a result, the concentrations of endogenous metabolites in urine vary widely and normalizing for these effects is necessary. Normalization approaches that utilized urine volume, osmolality, creatinine concentration, and components that are common to all samples ("total useful MS signal") were compared in order to determine which strategies could be successfully used to differentiate between dose groups based upon the complete endogenous metabolite profile. Variability observed in LC/MS results obtained from targeted and non-targeted metabonomic analyses was highly dependent on the strategy used for normalization. We therefore recommend the use of two different normalization techniques in order to facilitate detection of statistically significant changes in the endogenous metabolite profile when working with urine samples.

An automated liquid chromatography-mass spectrometry process to determine metabolic stability half-life and intrinsic clearance of drug candidates by substrate depletion.

An automated process is described for the detailed assessment of the in vitro metabolic stability properties of drug candidates in support of pharmaceutical property profiling. Compounds are incubated with liver microsomes using a robotic liquid handler. Aliquots are taken at various time points, and the resulting samples are quantitatively analyzed by liquid chromatography-mass spectrometry utilizing ion trap mass spectrometers to determine the amount of compound remaining. From these data metabolism rates can be calculated. A high degree of automation is achieved through custom software, which is employed for instrument setup, data processing, and results reporting. The assay setup is highly configurable, allowing for any combination of up to six user-selected time points, variable substrate concentration, and microsomes or other biologically active media. The data, based on relative substrate depletion, affords an estimate of metabolic stability through the calculation of half-life (t(1/2)) and intrinsic clearance, which are used to differentiate and rank order drug leads. In general, t(1/2) is the time necessary for the metabolism, following first-order kinetics, of 50% of the initial compound. Intrinsic clearance is the proportionality constant between rate of metabolism of a compound and its concentration at the enzyme site. Described here is the setup of the assay, and data from assay test compounds are presented.

An automated high throughput liquid chromatography-mass spectrometry process to assess the metabolic stability of drug candidates.

An automated high throughput process, termed the MetFast assay, is described to assess in vitro the general microsomal cytochrome P450 beta-nicotinamide adenine dinucleotide phosphate-mediated first-pass metabolic stability of potential drug candidates as a utility for pharmaceutical profiling. Utilizing robotic protocols with a multiprobe liquid handler, compounds are incubated with liver microsomes from different species. Samples are then analyzed by in-line liquid chromatography (LC)-mass spectrometry (MS) to determine the amount of compound remaining after a certain time, which allows calculation of metabolism rates. To quantitatively assess large numbers of structurally diverse compounds by LC-MS, a strategy based on an iterative two-step process was devised. Initially compounds are qualitatively analyzed by LC-ultraviolet (UV)/MS (step 1) to determine purity (UV detection) and structural integrity (MS detection). This step ensures that only correct and verified compounds with sufficient purity are being assayed to obtain reproducible high data quality. In addition, all necessary information is gathered to automatically generate specific quantitative methods for the subsequent bioanalytical analysis of metabolic stability samples by LC-UV/MS (step 2). In-house-developed, highly flexible and sophisticated data management software, termed SmartReport, is utilized for automated qualitative and quantitative LC-MS analysis set-up, data processing, and results reporting. The integration of key aspects, inherent "universal" collision-induced dissociation settings of ion trap mass spectrometers for tandem mass spectrometric scan functions utilized for compound-specific and sensitive quantitative MS methods, generic fast-LC conditions, generic MS instrument settings, and the functionality of SmartReport software resulted in an analytical process that routinely provides reproducible high-quality metabolic stability data on structurally diverse compounds. Described here is the setup of the MetFast assay, and metabolic stability data from assay validation compounds are given.

Expedient data mining for nontargeted high-resolution LC-MS profiles of biological samples.

BACKGROUND: The application of high-resolution LC-MS metabolomics for drug candidate toxicity screening reflects phenotypic changes of an organism caused by induced chemical interferences. Its success depends not only on the ability to translate the acquired analytical information into biological knowledge, but also on the timely delivery of the results to aid the decision making process in drug discovery and development. Recent improvements in analytical instrumentation have resulted in the ability to acquire extremely information-rich datasets. These new data collection abilities have shifted the bottleneck in the timeline of metabolomic studies to the data analysis step. RESULTS: This paper describes our approach to expedient data analysis of nontargeted high-resolution LC-MS profiles of biological samples. The workflow is illustrated with the example of metabolomics study of time-dependent fasting in male rats. The results from measurement of 220 endogenous metabolites in urine samples illustrate significant biochemical changes induced by fasting. CONCLUSION: The developed software enables the reporting of relative quantities of annotated components while maintaining practical turnaround times. Each component annotation in the report is validated using both calculated isotopic peaks patterns and experimentally determined retention time data on standards.

Automated and unbiased analysis of LC-MS metabolomic data.

BACKGROUND: LC-MS metabolomics provides a unique approach for evaluation of perturbations in biochemical pathways. LC-MS is a key technology for measuring endogenous metabolites and, while it has the impressive ability to acquire colossal volumes of data, the overall success of a study depends on the ability to translate the acquired analytical information into biological knowledge. Thus, a significant research effort has been dedicated to the development of informatics tools capable of automatically translating the complexity of acquired LC-MS datasets into meaningful biochemical sample descriptions. MATERIALS & METHODS: This article discusses our methodology for automated analysis of high-resolution accurate mass LC-MS data applied to a case study of evaluation of the effects of fasting in male rats. Blood serum samples from male rats were analyzed using an exactive mass spectrometer interfaced with an Accela UHPLC. RESULTS: An obtained list of annotated endogenous metabolites through matching of the detected components with corresponding profiles of synthetic standards served as a basis for statistical evaluation of observed physiological changes. CONCLUSION: The observed changes in certain endogenous metabolites prove that fasting could be a significant variable in toxicological studies since the fasting status of a particular animal may exacerbate or obscure drug-induced metabolic effects.