Capillary Electrophoresis-High Resolution Mass Spectrometry for Measuring In Vivo Arginine Isotope Incorporation in Alzheimer's Disease Mouse Models.

Immune-based metabolic reprogramming of arginine utilization in the brain contributes to the neuronal pathology associated with Alzheimer's disease (AD). To enable our long-term goals of differentiation of AD mouse model genotypes, ages, and sexes based on activity of this pathway, we describe here the novel dosing (using uniformly labeled (13C615N4) arginine) and analysis methods using capillary electrophoresis high-resolution accurate-mass mass spectrometry for isotope tracing of metabolic products of arginine. We developed a pseudoprimed infusion-dosing regimen, using repeated injections, to achieve a steady state of uniformly labeled arginine in 135-195 min post bolus dose. Incorporation of stable isotope labeled carbon and nitrogen from uniformly labeled arginine into a host of downstream metabolites was measured in vivo in mice using serially sampled dried blood spots from the tail. In addition to the dried blood spot time course samples, total isotope incorporation into arginine-related metabolites was measured in the whole brain and plasma after 285 min. Preliminary demonstration of the technique identified differences isotope incorporation in arginine metabolites between male and female mice in a mouse-model of sporadic Alzheimer's disease (APOE4/huNOS2). The technique described herein will permit arginine pathway activity differentiation between mouse genotypes, ages, sexes, or drug treatments in order to elucidate the contribution of this pathway to Alzheimer's disease.

Likelihood ratio statistics for gene set enrichment in Alzheimer's disease pathways.

INTRODUCTION: The study of Alzheimer's disease (AD) has revealed biological pathways with implications for disease neuropathology and pathophysiology. These pathway-level effects may also be mediated by individual characteristics or covariates such as age or sex. Evaluation of AD biological pathways in the context of interactions with these covariates is critical to the understanding of AD as well as the development of model systems used to study the disease. METHODS: Gene set enrichment methods are powerful tools used to interpret gene-level statistics at the level of biological pathways. We introduce a method for quantifying gene set enrichment using likelihood ratio-derived test statistics (gsLRT), which accounts for sample covariates like age and sex. We then use our method to test for age and sex interactions with protein expression levels in AD and to compare the pathway results between human and mouse species. RESULTS: Our method, based on nested logistic regressions is competitive with the existing standard for gene set testing in the context of linear models and complex experimental design. The gene sets we identify as having a significant association with AD-both with and without additional covariate interactions-are validated by previous studies. Differences between gsLRT results on mouse and human datasets are observed. DISCUSSION: Characterizing biological pathways involved in AD builds on the important work involving single gene drivers. Our gene set enrichment method finds pathways that are significantly related to AD while accounting for covariates that may be relevant to disease development. The method highlights commonalities and differences between human AD and mouse models, which may inform the development of higher fidelity models for the study of AD.

Skyline for Small Molecules: A Unifying Software Package for Quantitative Metabolomics.

Vendor-independent software tools for quantification of small molecules and metabolites are lacking, especially for targeted analysis workflows. Skyline is a freely available, open-source software tool for targeted quantitative mass spectrometry method development and data processing with a 10 year history supporting six major instrument vendors. Designed initially for proteomics analysis, we describe the expansion of Skyline to data for small molecule analysis, including selected reaction monitoring, high-resolution mass spectrometry, and calibrated quantification. This fundamental expansion of Skyline from a peptide-sequence-centric tool to a molecule-centric tool makes it agnostic to the source of the molecule while retaining Skyline features critical for workflows in both peptide and more general biomolecular research. The data visualization and interrogation features already available in Skyline, such as peak picking, chromatographic alignment, and transition selection, have been adapted to support small molecule data, including metabolomics. Herein, we explain the conceptual workflow for small molecule analysis using Skyline, demonstrate Skyline performance benchmarked against a comparable instrument vendor software tool, and present additional real-world applications. Further, we include step-by-step instructions on using Skyline for small molecule quantitative method development and data analysis on data acquired with a variety of mass spectrometers from multiple instrument vendors.

International Ring Trial of a High Resolution Targeted Metabolomics and Lipidomics Platform for Serum and Plasma Analysis.

A challenge facing metabolomics in the analysis of large human cohorts is the cross-laboratory comparability of quantitative metabolomics measurements. In this study, 14 laboratories analyzed various blood specimens using a common experimental protocol provided with the Biocrates AbsoluteIDQ p400HR kit, to quantify up to 408 metabolites. The specimens included human plasma and serum from male and female donors, mouse and rat plasma, as well as NIST SRM 1950 reference plasma. The metabolite classes covered range from polar (e.g., amino acids and biogenic amines) to nonpolar (e.g., diacyl- and triacyl-glycerols), and they span 11 common metabolite classes. The manuscript describes a strict system suitability testing (SST) criteria used to evaluate each laboratory's readiness to perform the assay, and provides the SST Skyline documents for public dissemination. The study found approximately 250 metabolites were routinely quantified in the sample types tested, using Orbitrap instruments. Interlaboratory variance for the NIST SRM-1950 has a median of 10% for amino acids, 24% for biogenic amines, 38% for acylcarnitines, 25% for glycerolipids, 23% for glycerophospholipids, 16% for cholesteryl esters, 15% for sphingolipids, and 9% for hexoses. Comparing to consensus values for NIST SRM-1950, nearly 80% of comparable analytes demonstrated bias of <50% from the reference value. The findings of this study result in recommendations of best practices for system suitability, quality control, and calibration. We demonstrate that with appropriate controls, high-resolution metabolomics can provide accurate results with good precision across laboratories, and the p400HR therefore is a reliable approach for generating consistent and comparable metabolomics data.

Discovery and targeted monitoring of polychlorinated biphenyl metabolites in blood plasma using LC-TIMS-TOF MS.

In the present work, the potential for rapid, targeted analysis of hydroxylated metabolites of polychlorinated biphenyls (OH-PCBs) in diluted human blood plasma using liquid chromatography coupled with trapped ion mobility spectrometry and TOF high resolution mass spectrometry (LC-TIMS-TOF MS) was evaluated. Experimental OH-PCB collisional cross section (CCSN2) and gas-phase candidate structures (<3% error) are reported for the first time and used, in addition to the LC retention time and accurate m/z, as OH-PCB identification features in order to increase the detection selectivity. The proposed LC-TIMS-TOF MS workflow combines a "dilute-and-shoot" sample preparation strategy, a robust liquid chromatography step, a high-resolving power mobility separation (R ~ 150-250) and high-resolution mass spectrometry (R ~ 30-40k) for the separation, identification and quantification of common OH-PCB isomers with limits of detection comparable to traditional workflows (e.g., LOD and LOQ of ~10 pg/mL and ~50 pg/mL, respectively). The higher selectivity and low detection limits provides multiple advantages compared to current methodologies that typically require long, labor-intensive preparation and/or derivatization steps prior to gas or liquid chromatography-mass spectrometry.

Analysis of isomeric opioids in urine using LC-TIMS-TOF MS.

In the present work, a fast separation, identification and quantification workflow based on liquid chromatography coupled to trapped ion mobility in tandem with mass spectrometry (LC-TIMS-MS) is described for the analysis of common isomeric drugs of abuse and their metabolites in human urine. In particular, the analytical performance of LC-TIMS-MS is shown for identification based on retention time, collision cross section and accurate mass for three sets of common isomeric opioids and their deuterated analogs in urine. The LC-TIMS-MS analysis provided limits of detection of 1.4-35.2 ng/mL with demonstrated linearity up to 500 ng/mL, enabling discovery and targeted monitoring (DTM) of opioids in urine, with high precision in retention times (RT) (< 0.3%), collision cross sections (CCS) (< 0.6%) and mass accuracy (< 1 ppm) across multiple measurements using external calibration. A good agreement was observed between theoretical and experimental CCS from candidate structures optimized at the DFT/B3LYP level. The need for complementary liquid and mobility separations prior to mass analysis is shown for the analysis of complex mixtures, with mobility resolving power of 80-130. The reproducibility and high speed of LC-TIMS-MS analysis provides a powerful platform for drug and metabolite screening in biological matrices with higher precision and confidence than traditional LC-multiple reaction monitoring (MRM) approaches.

Lipid specific molecular ion emission as a function of the primary ion characteristics in TOF-SIMS.

In the present work, the emission characteristics of lipids as a function of the primary ion cluster size and energy were studied using time-of-flight secondary ion mass spectrometry (TOF-SIMS). Characteristic fragmentation patterns for common lipids are described, and changes in secondary ion (SI) yields using various primary ion beams are reported. In particular, emission characteristics were studied for pairs of small polyatomic and nanoparticle primary ion beams (e.g., Bi3+ versus Ar1000+ and Au3+ versus Au400+4) based on the secondary ion yield of characteristic fragment and intact molecular ions as a function of the lipid class. Detailed descriptions of the fragmentation patterns are shown for positive and negative mode TOF-SIMS. Results demonstrate that the lipid structure largely dictates the spectral presence of molecular and/or fragment ions in each ionization mode due to the localization of the charge carrier (head group or fatty acid chain). Our results suggest that the larger the energy per atom for small polyatomic projectiles (Bi3+ and Au3+), the larger the SI yield; in the case of nanoparticle projectiles, the SI increase with primary ion energy (200-500 keV range) for Au400+4 and with the decrease of the energy per atom (10-40 eV/atom range) for Arn=500-2000+ clusters. The secondary ion yield of the molecular ion of lipids from a single standard or from a mixture of lipids does not significantly change with the primary ion identity in the positive ion mode TOF-SIMS and slightly decreases in the negative ion mode TOF-SIMS.

Isomer Separation of Polybrominated Diphenyl Ether Metabolites using nanoESI-TIMS-MS.

In this paper, high-resolution nano-electrospray ionization-trapped ion mobility spectrometry coupled to mass spectrometry (nESI-TIMS-MS) is used for the study of hydroxylated polybrominated diphenyl ether (OH-PBDE) metabolites. In particular, experimental ion-neutral collision cross sections (CCS) were measured for five structural OH-PBDE isomers using TIMS-MS. Candidate structures were proposed for each IMS band observed in good agreement with the experimental CCS measurements (5% error). The analytical power of TIMS-MS to baseline and partially separate structural isomers of OH-BDE in binary and ternary mixtures is shown for single charge species with a mobility resolving power of RIMS ~ 400. This work provides the proof of concept for the analysis of low concentration OH-PBDE in environmental samples based on accurate collision cross section and mass measurements without the need for derivatization and pre-fractionation protocols, thus significantly reducing the cost and analysis time.

DART-MS for rapid, preliminary screening of urine for DMAA.

Dimethylamylamine (DMAA) is a sympathomimetic amine found in weight-loss/workout supplements or used as an appetite suppressant. DMAA is a stimulant that is banned by the World Anti-Doping Agency (WADA). Adverse health effects as well as fatalities have been implicated with its use. Direct analysis in real time mass spectrometry (DART-MS) is an ambient ionization method that was employed to rapidly identify the presence of DMAA in various samples without any extraction or preparations whatsoever. DMAA was first identified in supplements, sampled directly in their solid forms. Furthermore, DMAA was detected directly in urine over 48 h as a means of indicating recent abuse of the substance. DART-MS analysis is instantaneous, and coupled with the high mass accuracy associated with the time-of-flight mass analyzer, results in unequivocal identification of the presence of DMAA. These features demonstrate DART-MS as an attractive potential alternative screening method for the presence of drugs and medications or for toxicological investigations.