Identifying xenobiotic metabolites with in silico prediction tools and LCMS suspect screening analysis.

Understanding the metabolic fate of a xenobiotic substance can help inform its potential health risks and allow for the identification of signature metabolites associated with exposure. The need to characterize metabolites of poorly studied or novel substances has shifted exposure studies towards non-targeted analysis (NTA), which often aims to profile many compounds within a sample using high-resolution liquid-chromatography mass-spectrometry (LCMS). Here we evaluate the suitability of suspect screening analysis (SSA) liquid-chromatography mass-spectrometry to inform xenobiotic chemical metabolism. Given a lack of knowledge of true metabolites for most chemicals, predictive tools were used to generate potential metabolites as suspect screening lists to guide the identification of selected xenobiotic substances and their associated metabolites. Thirty-three substances were selected to represent a diverse array of pharmaceutical, agrochemical, and industrial chemicals from Environmental Protection Agency's ToxCast chemical library. The compounds were incubated in a metabolically-active in vitro assay using primary hepatocytes and the resulting supernatant and lysate fractions were analyzed with high-resolution LCMS. Metabolites were simulated for each compound structure using software and then combined to serve as the suspect screening list. The exact masses of the predicted metabolites were then used to select LCMS features for fragmentation via tandem mass spectrometry (MS/MS). Of the starting chemicals, 12 were measured in at least one sample in either positive or negative ion mode and a subset of these were used to develop the analysis workflow. We implemented a screening level workflow for background subtraction and the incorporation of time-varying kinetics into the identification of likely metabolites. We used haloperidol as a case study to perform an in-depth analysis, which resulted in identifying five known metabolites and five molecular features that represent potential novel metabolites, two of which were assigned discrete structures based on in silico predictions. This workflow was applied to five additional test chemicals, and 15 molecular features were selected as either reported metabolites, predicted metabolites, or potential metabolites without a structural assignment. This study demonstrates that in some-but not all-cases, suspect screening analysis methods provide a means to rapidly identify and characterize metabolites of xenobiotic chemicals.

Glial fibrillary acidic protein exhibits altered turnover kinetics in a mouse model of Alexander disease.

Mutations in the astrocyte-specific intermediate filament glial fibrillary acidic protein (GFAP) lead to the rare and fatal disorder, Alexander disease (AxD). A prominent feature of the disease is aberrant accumulation of GFAP. It has been proposed that this accumulation occurs because of an increase in gene transcription coupled with impaired proteasomal degradation, yet this hypothesis remains untested. We therefore sought to directly investigate GFAP turnover in a mouse model of AxD that is heterozygous for a disease-causing point mutation (GfapR236H/+) (and thus expresses both wild-type and mutant protein). Stable isotope labeling by amino acids in cell culture, using primary cortical astrocytes, indicated that the in vitro half-lives of total GFAP in astrocytes from wild-type and mutant mice were similar at ∼3-4 days. Surprisingly, results obtained with stable isotope labeling of mammals revealed that, in vivo, the half-life of GFAP in mutant mice (15.4 ± 0.5 days) was much shorter than that in wild-type mice (27.5 ± 1.6 days). These unexpected in vivo data are most consistent with a model in which synthesis and degradation are both increased. Our work reveals that an AxD-causing mutation alters GFAP turnover kinetics in vivo and provides an essential foundation for future studies aimed at preventing or reducing the accumulation of GFAP. In particular, these data suggest that elimination of GFAP might be possible and occurs more quickly than previously surmised.

Upregulation of interferon-gamma-induced genes during prion infection.

Global gene expression analysis allows for the identification of transcripts that are differentially regulated during a disease state. Many groups, including our own, have identified hundreds of genes differentially regulated in response to prion infection. Eleven transcripts, upregulated in the brains of prion-infected animals, which were classified in the literature as stimulated by the cytokine interferon-gamma (IFN-γ), were identified. This is intriguing, as IFN-γ has recently been detected in the brains of prion-infected animals. Quantitation of several genes, categorized as IFN-γ inducible, by quantitative real-time polymerase chain reaction (qRT-PCR) confirms that these transcripts are upregulated. Future approaches for delineating the role of IFN-γ-induced transcripts and their function in prion infection are described.

Comparative prion disease gene expression profiling using the prion disease mimetic, cuprizone.

Identification of genes expressed in response to prion infection may elucidate biomarkers for disease, identify factors involved in agent replication, mechanisms of neuropathology and therapeutic targets. Although several groups have sought to identify gene expression changes specific to prion disease, expression profiles rife with cell population changes have consistently been identified. Cuprizone, a neurotoxicant, qualitatively mimics the cell population changes observed in prion disease, resulting in both spongiform change and astrocytosis. The use of cuprizone-treated animals as an experimental control during comparative expression profiling allows for the identification of transcripts whose expression increases during prion disease and remains unchanged during cuprizone-triggered neuropathology. In this study, expression profiles from the brains of mice preclinically and clinically infected with Rocky Mountain Laboratory (RML) mouse-adapted scrapie agent and age-matched controls were profiled using Affymetrix gene arrays. In total, 164 genes were differentially regulated during prion infection. Eighty-three of these transcripts have been previously undescribed as differentially regulated during prion disease. A 0.4% cuprizone diet was utilized as a control for comparative expression profiling. Cuprizone treatment induced spongiosis and astrocyte proliferation as indicated by glial fibrillary acidic protein (Gfap) transcriptional activation and immunohistochemistry. Gene expression profiles from brain tissue obtained from cuprizone-treated mice identified 307 differentially regulated transcript changes. After comparative analysis, 17 transcripts unaffected by cuprizone treatment but increasing in expression from preclinical to clinical prion infection were identified. Here we describe the novel use of the prion disease mimetic, cuprizone, to control for cell population changes in the brain during prion infection.