Isotopic ratio outlier analysis global metabolomics of Caenorhabditis elegans.

We demonstrate the global metabolic analysis of Caenorhabditis elegans stress responses using a mass-spectrometry-based technique called isotopic ratio outlier analysis (IROA). In an IROA protocol, control and experimental samples are isotopically labeled with 95 and 5% (13)C, and the two sample populations are mixed together for uniform extraction, sample preparation, and LC-MS analysis. This labeling strategy provides several advantages over conventional approaches: (1) compounds arising from biosynthesis are easily distinguished from artifacts, (2) errors from sample extraction and preparation are minimized because the control and experiment are combined into a single sample, (3) measurement of both the molecular weight and the exact number of carbon atoms in each molecule provides extremely accurate molecular formulas, and (4) relative concentrations of all metabolites are easily determined. A heat-shock perturbation was conducted on C. elegans to demonstrate this approach. We identified many compounds that significantly changed upon heat shock, including several from the purine metabolism pathway. The metabolomic response information by IROA may be interpreted in the context of a wealth of genetic and proteomic information available for C. elegans . Furthermore, the IROA protocol can be applied to any organism that can be isotopically labeled, making it a powerful new tool in a global metabolomics pipeline.

An integrated method for metabolite detection and identification using a linear ion trap/Orbitrap mass spectrometer and multiple data processing techniques: application to indinavir metabolite detection.

A new strategy using a hybrid linear ion trap/Orbitrap mass spectrometer and multiple post-acquisition data mining techniques was evaluated and applied to the detection and characterization of in vitro metabolites of indinavir. Accurate-mass, full-scan MS and MS/MS data sets were acquired with a generic data-dependent method and processed with extracted-ion chromatography (EIC), mass-defect filter (MDF), product-ion filter (PIF), and neutral-loss filter (NLF) techniques. The high-resolution EIC process was shown to be highly effective in the detection of common metabolites with predicted molecular weights. The MDF process, which searched for metabolites based on the similarity of mass defects of metabolites to those of indinavir and its core substructures, was able to find uncommon metabolites not detected by the EIC processing. The high-resolution PIF and NLF processes selectively detected metabolites that underwent fragmentation pathways similar to those of indinavir or its known metabolites. As a result, a total of 15 metabolites including two new indinavir metabolites were detected and characterized in a rat liver S9 incubation sample. Overall, these data mining techniques, which employed distinct metabolite search mechanisms, were complementary and effective in detecting both common and uncommon metabolites. In summary, the results demonstrated that this analytical strategy enables the high-throughput acquisition of accurate-mass LC/MS data sets, comprehensive search of a variety of metabolites through the post-acquisition processes, and effective structural characterization based on elemental compositions of metabolite molecules and their product ions.

Evaluation of cerebrospinal fluid concentration and plasma free concentration as a surrogate measurement for brain free concentration.

This study was designed to evaluate the use of cerebrospinal fluid (CSF) drug concentration and plasma unbound concentration (C(u,plasma)) to predict brain unbound concentration (C(u,brain)). The concentration-time profiles in CSF, plasma, and brain of seven model compounds were determined after subcutaneous administration in rats. The C(u,brain) was estimated from the product of total brain concentrations and unbound fractions, which were determined using brain tissue slice and brain homogenate methods. For theobromine, theophylline, caffeine, fluoxetine, and propranolol, which represent rapid brain penetration compounds with a simple diffusion mechanism, the ratios of the area under the curve of C(u,brain)/C(CSF) and C(u,brain)/C(u,plasma) were 0.27 to 1.5 and 0.29 to 2.1, respectively, using the brain slice method, and were 0.27 to 2.9 and 0.36 to 3.9, respectively, using the brain homogenate method. A P-glycoprotein substrate, CP-141938 (methoxy-3-[(2-phenyl-piperadinyl-3-amino)-methyl]-phenyl-N-methyl-methane-sulfonamide), had C(u,brain)/C(CSF) and C(u,brain)/C(u,plasma) ratios of 0.57 and 0.066, using the brain slice method, and 1.1 and 0.13, using the brain homogenate method, respectively. The slow brain-penetrating compound, N[3-(4'-fluorophenyl)-3-(4'-phenylphenoxy)propyl-]sarcosine, had C(u,brain)/C(CSF) and C(u,brain)/C(u,plasma) ratios of 0.94 and 0.12 using the brain slice method and 0.15 and 0.018 using the brain homogenate method, respectively. Therefore, for quick brain penetration with simple diffusion mechanism compounds, C(CSF) and C(u,plasma) represent C(u,brain) equally well; for efflux substrates or slow brain penetration compounds, C(CSF) appears to be equivalent to or more accurate than C(u,plasma) to represent C(u,brain). Thus, we hypothesize that C(CSF) is equivalent to or better than C(u,plasma) to predict C(u,brain). This hypothesis is supported by the literature data.

Use of a physiologically based pharmacokinetic model to study the time to reach brain equilibrium: an experimental analysis of the role of blood-brain barrier permeability, plasma protein binding, and brain tissue binding.

This study was designed 1) to examine the effects of blood-brain barrier (BBB) permeability [quantified as permeability-surface area product (PS)], unbound fraction in plasma (f(u,plasma)), and brain tissue (f(u,brain)) on the time to reach equilibrium between brain and plasma and 2) to investigate the drug discovery strategies to design and select compounds that can rapidly penetrate the BBB and distribute to the site of action. The pharmacokinetics of seven model compounds: caffeine, CP-141938 [methoxy-3-[(2-phenyl-piperadinyl-3-amino)-methyl]-phenyl-N-methyl-methane-sulfonamide], fluoxetine, NFPS [N[3-(4'-fluorophenyl)-3-(4'-phenylphenoxy)propyl]sarcosine], propranolol, theobromine, and theophylline in rat brain and plasma after subcutaneous administration were studied. The in vivo log PS and log f(u,brain) calculated using a physiologically based pharmacokinetic model correlates with in situ log PS (R(2) = 0.83) and in vitro log f(u,brain) (R(2) = 0.69), where the in situ PS and in vitro f(u,brain) was determined using in situ brain perfusion and equilibrium dialysis using brain homogenate, respectively. The time to achieve brain equilibrium can be quantitated with a proposed parameter, intrinsic brain equilibrium half-life [t(1/2eq,in) = V(b)ln2/(PS . f(u,brain))], where V(b) is the physiological volume of brain. The in vivo log t(1/2eq,in) does not correlate with in situ log PS (R(2) < 0.01) but correlates inversely with log(PS . f(u,brain)) (R(2) = 0.85). The present study demonstrates that rapid brain equilibration requires a combination of high BBB permeability and low brain tissue binding. A high BBB permeability alone cannot guarantee a rapid equilibration. The strategy to select compounds with rapid brain equilibration in drug discovery should identify compounds with high BBB permeability and low nonspecific binding in brain tissue.