Faculty Bibliography

Metabolite identification is a crucial step in mass spectrometry (MS)-based metabolomics. However, it is still challenging to assess the confidence of assigned metabolites. We report a novel method for estimating the false discovery rate (FDR) of metabolite assignment with a target-decoy strategy, in which the decoys are generated through violating the octet rule of chemistry by adding small odd numbers of hydrogen atoms. The target-decoy strategy was integrated into JUMPm, an automated metabolite identification pipeline for large-scale MS analysis and was also evaluated with two other metabolomics tools, mzMatch and MZmine 2. The reliability of FDR calculation was examined by false data sets, which were simulated by altering MS1 or MS2 spectra. Finally, we used the JUMPm pipeline coupled to the target-decoy strategy to process unlabeled and stable-isotope-labeled metabolomic data sets. The results demonstrate that the target-decoy strategy is a simple and effective method for evaluating the confidence of high-throughput metabolite identification.

Retinoic acid (RA) is a vital morphogen for early patterning and organogenesis in the developing embryo. RA is a diffusible, lipophilic molecule that signals via nuclear RA receptor heterodimeric units that regulate gene expression by interacting with RA response elements in promoters of a significant number of genes. For precise RA signaling, a robust gradient of the morphogen is required. The developing embryo contains regions that produce RA, and specific intracellular concentrations of RA are created through local degradation mediated by Cyp26 enzymes. In order to elucidate the mechanisms by which RA executes precise developmental programs, the kinetics of RA metabolism must be clearly understood. Recent advances in techniques for endogenous RA detection and quantification have paved the way for mechanistic studies to shed light on downstream gene expression regulation coordinated by RA. It is increasingly coming to light that RA signaling operates not only as precise concentrations but also employs mechanisms of degradation and feedback inhibition to self-regulate its levels. A global gradient of RA throughout the embryo is often found concurrently with several local gradients, created by juxtaposed domains of RA synthesis and degradation. The existence of such local gradients has been found especially critical for the proper development of craniofacial structures that arise from the neural crest and the cranial placode populations. In this review we summarize the current understanding of how local gradients of RA are established in the embryo and their impact on craniofacial development.

Global metabolomics relies on highly reproducible and sensitive detection of a wide range of metabolites in biological samples. Here we report the optimization of metabolome analysis by nanoflow ultraperformance liquid chromatography coupled to high-resolution orbitrap mass spectrometry. Reliable peak features were extracted from the LC-MS runs based on mandatory detection in duplicates and additional noise filtering according to blank injections. The run-to-run variation in peak area showed a median of 14%, and the false discovery rate during a mock comparison was evaluated. To maximize the number of peak features identified, we systematically characterized the effect of sample loading amount, gradient length, and MS resolution. The number of features initially rose and later reached a plateau as a function of sample amount, fitting a hyperbolic curve. Longer gradients improved unique feature detection in part by time-resolving isobaric species. Increasing the MS resolution up to 120000 also aided in the differentiation of near isobaric metabolites, but higher MS resolution reduced the data acquisition rate and conferred no benefits, as predicted from a theoretical simulation of possible metabolites. Moreover, a biphasic LC gradient allowed even distribution of peak features across the elution, yielding markedly more peak features than the linear gradient. Using this robust nUPLC-HRMS platform, we were able to consistently analyze ~6500 metabolite features in a single 60 min gradient from 2 mg of yeast, equivalent to ~50 million cells. We applied this optimized method in a case study of drug (bortezomib) resistant and drug-sensitive multiple myeloma cells. Overall, 18% of metabolite features were matched to KEGG identifiers, enabling pathway enrichment analysis. Principal component analysis and heat map data correctly clustered isogenic phenotypes, highlighting the potential for hundreds of small molecule biomarkers of cancer drug resistance.

Deposition of insoluble protein aggregates is a hallmark of neurodegenerative diseases. The universal presence of beta-amyloid and tau in Alzheimer's disease (AD) has facilitated advancement of the amyloid cascade and tau hypotheses that have dominated AD pathogenesis research and therapeutic development. However, the underlying etiology of the disease remains to be fully elucidated. Here we report a comprehensive study of the human brain-insoluble proteome in AD by mass spectrometry. We identify 4,216 proteins, among which 36 proteins accumulate in the disease, including U1-70K and other U1 small nuclear ribonucleoprotein (U1 snRNP) spliceosome components. Similar accumulations in mild cognitive impairment cases indicate that spliceosome changes occur in early stages of AD. Multiple U1 snRNP subunits form cytoplasmic tangle-like structures in AD but not in other examined neurodegenerative disorders, including Parkinson disease and frontotemporal lobar degeneration. Comparison of RNA from AD and control brains reveals dysregulated RNA processing with accumulation of unspliced RNA species in AD, including myc box-dependent-interacting protein 1, clusterin, and presenilin-1. U1-70K knockdown or antisense oligonucleotide inhibition of U1 snRNP increases the protein level of amyloid precursor protein. Thus, our results demonstrate unique U1 snRNP pathology and implicate abnormal RNA splicing in AD pathogenesis.

BACKGROUND: The loss of synaptic function is a pivotal mechanism in the development of Alzheimer's Disease (AD). Structural changes and loss of plasticity in the postsynaptic density (PSD) may contribute to the pathogenesis. However, the underlying molecular events triggering synaptic dysfunction remain elusive. We report a quantitative proteomic analysis of the PSD from human postmortem brain tissues of possible and definite AD cases. METHODS: The analysis used both discovery and targeted mass spectrometry approaches and was repeated with biological replicates. During the discovery study, we compared several hundred proteins in the PSD-enriched fractions and found that 25 proteins were differentially regulated in AD. RESULTS: Interestingly, the majority of these protein changes were larger in definite AD cases than in possible AD cases. In the targeted analysis, we measured the level of 9 core PSD proteins and found that only IRSp53 was highly down-regulated in AD. The alteration of selected proteins (i.e. internexin and IRSp53) was further validated by immunoblotting against 7 control and 8 AD cases. CONCLUSIONS: These results expand our understanding of how AD impacts PSD composition, and hints at new hypotheses for AD pathogenesis.

Protein ubiquitination is an essential post-translational modification regulating neurodevelopment, synaptic plasticity, learning, and memory, and its dysregulation contributes to the pathogenesis of neurological diseases. Here we report a systematic analysis of ubiquitinated proteome (ubiquitome) in rat brain using a newly developed monoclonal antibody that recognizes the diglycine tag on lysine residues in trypsinized peptides (K-GG peptides). Initial antibody specificity analysis showed that the antibody can distinguish K-GG peptides from linear GG peptides or pseudo K-GG peptides derived from iodoacetamide. To evaluate the false discovery rate of K-GG peptide matches during database search, we introduced a null experiment using bacterial lysate that contains no such peptides. The brain ubiquitome was then analyzed by this antibody enrichment with or without strong cation exchange (SCX) prefractionation. During SCX chromatography, although the vast majority of K-GG peptides were detected in the fractions containing at least three positive charged peptides, specific K-GG peptides with two positive charges (e.g., protein N-terminal acetylated and C-terminal non-K/R peptides) were also identified in early fractions. The reliability of C-terminal K-GG peptides was also extensively investigated. Finally, we collected a data set of 1786 K-GG sites on 2064 peptides in 921 proteins and estimated their abundance by spectral counting. The study reveals a wide range of ubiquitination events on key components in presynaptic region (e.g., Bassoon, NSF, SNAP25, synapsin, synaptotagmin, and syntaxin) and postsynaptic density (e.g., PSD-95, GKAP, CaMKII, as well as receptors for NMDA, AMPA, GABA, serotonin, and acetylcholine). We also determined ubiquitination sites on amyloid precursor protein and alpha synuclein that are thought to be causative agents in Alzhermer's and Parkinson's disorders, respectively. As K-GG peptides can also be produced from Nedd8 or ISG15 modified proteins, we quantified these proteins in the brain and found that their levels are less than 2% of ubiquitin. Together, this study demonstrates that a large number of neuronal proteins are modified by ubiquitination and provides a feasible method for profiling the ubiquitome in the brain.

Coumadin (R/S-warfarin) is a highly efficacious and widely used anticoagulant; however, its highly variable metabolism remains an important contributor to uncertainties in therapeutic responses. Pharmacogenetic studies report conflicting findings on the clinical relevance of CYP2C19. A resolution to this controversy is impeded by a lack of de tailon the potential role of CYP2C19 in warfarin metabolism. Consequently, we assessed the efficiency of CYP2C19 metabolism of R- and S-warfarin and explored possible contributions in the liver using in vitro methods. Recombinant CYP2C19 metabolized R- and S-warfarin mainly to 6-, 7-, and 8-hydroxywarfarin, while 4'-hydroxywarfarin was a minormetabolite. Over all R-warfarin metabolism was slightly more efficient than that for S-warfarin. Metabolic pathways thatproduce R-6-, 7-, and 8-hydroxywarfarin in human liver microsomal reactions correlated strongly with CYP2C19 Smephenytoinhydroxylase activity. Similarly, CYP1A2 activity toward phenacetin correlated with formation of R-6 and 7-hydroxywarfarin such that R-8-hydroxywarfarin seems unique to CYP2C19 and possibly a biomarker. In following, CYP2C19 likely impacts R-warfarin metabolism and patient response to therapy. Intriguingly, CYP2C19 may contributeto S-warfarin metabolism in patients, especially when CYP2C9 activity is compromised due to drug interactions orgenetic polymorphisms.

INTRODUCTION: Coumadin (R/S-warfarin) is the most widely prescribed oral anticoagulant in the world; nevertheless, its clinical use is complicated by unpredictability in dose requirements to achieve and maintain optimal anticoagulation. Variations in warfarin metabolism among patients contribute to unpredictability in therapeutic responses. Studying the clinical relevance of warfarin metabolism poses a significant analytical challenge. Warfarin is given to patients as an equal mixture of R and S enantiomers. Both drugs undergo extensive metabolism through different pathways to generate > 20 structurally similar isomeric metabolites. AREAS COVERED: The article discusses how analytical methods have evolved to effectively resolve and quantify individual metabolites. The authors also discuss how the application of these methods has identified clinically relevant metabolic pathways for warfarin and fostered the investigation of clinical biomarkers for patient responses to therapy. The article additionally presents the power of these methods and how aspects of warfarin metabolism have led to the use of warfarin as a phenotyping probe for multiple drug metabolizing enzymes. EXPERT OPINION: Progress in these areas has been hampered by shortcomings in analytical methods and a narrow focus on one metabolic pathway. Recent advances in liquid chromatographic-mass spectral methods can rapidly analyze most warfarin metabolites. It is now possible to effectively assess alternate metabolic pathways and expand biomarker analyses for clinical and phenotyping applications.

Coumadin (R/S-warfarin) is a commonly prescribed anticoagulant for over approximately 20 million Americans. Although highly efficacious, positive clinical outcomes during warfarin therapy depend on maintaining a narrow therapeutic range for the drug. This goal is challenging due to large inter-individual variability in patient response, which has been attributed to diversity in drug metabolism. Warfarin is given as a racemic mixture and evidence suggest differences of R and S-warfarin in their therapeutic activities and metabolism. Previous investigation of warfarin metabolism has been hampered by the inability to quantify the individual enantiomers. To overcome this limitation a multi-mode LC-MS/MS method is reported. This strategy combines phenyl based reverse phase chromatography with chiral phase chromatography prior to quantitation by liquid chromatography tandem mass spectrometry. This approach was made possible through advances in UPLC technology producing narrow peaks suitable for transferring to a second column. The reported method separated individual R and S enantiomers of hydroxywarfarin and warfarin. All four possible isomers of 10-hydroxywarfarin were resolved to reveal unprecedented insights into the stereo-specific metabolism of warfarin. Characterization of the method demonstrated that it is robust and sensitive with inter-day coefficients of error between <7% and a detection limit of 2 nM in sample or 10 fmol on column for each analyte. Individual metabolites may be suitable surrogate biomarkers or predictive markers that predict warfarin dose, adverse interactions, or other important clinical outcomes during anticoagulant therapy. Consequently, the metabolite profiles obtained through this dual phase UPLC-MS/MS method are expected to increase our understanding of the role warfarin metabolism plays in patient response to therapy and yield new strategies to improve patient outcomes.

Effective coumadin (R/S-warfarin) therapy is complicated by inter-individual variability in metabolism. Recent studies have demonstrated that CYP3A isoforms likely contribute to patient responses and clinical outcomes. Despite a significant focus on CYP3A4, little is known about CYP3A5 and CYP3A7 metabolism of warfarin. Based on our studies, recombinant CYP3A4, CYP3A5 and CYP3A7 metabolized R- and S-warfarin to 10- and 4'-hydroxywarfarin with efficiencies that depended on the individual enzymes. For R-warfarin, CYP3A4, CYP3A7, and CYP3A5 demonstrated decreasing preference for 10-hydroxylation over 4'-hydroxylation. By contrast, there was no regioselectivity toward S-warfarin. While all enzymes preferentially metabolized R-warfarin, CYP3A4 was the most efficient at metabolizing all reactions. Individuals, namely African-Americans and children, with higher relative levels of CYP3A5 and/or CYP3A7, respectively, compared to CYP3A4 may metabolize warfarin less efficiently and thus may require lower doses and be at risk for adverse drug-drug interactions related to the contributions of the respective enzymes.