Analysis of Ammonium Nitrate/Urea Nitrate with Crown Ethers and Sugars as Modifiers by Electrospray Ionization-Mass Spectrometry and Ion Mobility Spectrometry

Ammonium nitrate (AN) and urea nitrate (UN) are commonly used materials in improvised explosive devices (IEDs). Detection by mass spectrometry (MS) and/or ion mobility spectrometry (IMS) is traditionally difficult. The major challenges of detecting these species arise from their ionic nature and their low mass (for MS detection) and size (for IMS detection). Although AN and UN both produce characteristic higher mass (and size) cluster ions when ionized by electrospray ionization (ESI), detection of AN/UN using cluster ions poses difficulty at trace levels because their formation is concentration-dependent. The addition of modifiers to the ESI process is demonstrated here to overcome some of these challenges for the detection of AN and UN using MS and/or IMS

Precast Gelatin-Based Molds for Tissue Embedding Compatible with Mass Spectrometry Imaging

Preparation of tissue for matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) generally involves embedding the tissue followed by freezing and cryosectioning, usually between 5 and 25 μm thick, depending on the tissue type and the analyte(s) of interest. The brain is approximately 60% fat; it therefore lacks rigidity and poses structural preservation challenges during sample preparation. Histological sample preparation procedures are generally transferable to MALDI-MSI; however, there are various limitations. Optimal cutting temperature compound (OCT) is commonly used to embed and mount fixed tissue onto the chuck inside the cryostat during cryosectioning. However, OCT contains potential interferences that are detrimental to MALDI-MSI, while fixation is undesirable for the analysis of some analytes either due to extraction or chemical modification (i.e., polar metabolites). Therefore, a method for both fixed and fresh tissue compatible with MALDI-MSI and histology is desirable to increase the breadth of analyte(s), maintain the topographies of the brain, and provide rigidity to the fragile tissue while eliminating background interference. The method we introduce uses precast gelatin-based molds in which a whole mouse brain is embedded, flash frozen, and cryosectioned in preparation for mass spectrometry imaging (MSI)

Characterization of Phosphatidylcholine Oxidation Products by MALDI MS^<i>n</i>

Phospholipid oxidation has been implicated in the pathogenesis and progression of numerous age-related and neurodegenerative diseases. Despite these implications, this broad class of biomolecules remains poorly characterized. In this work, the fragmentation patterns of [M + H]⁺ and [M + Na]⁺ ions of intact phosphatidylcholine oxidation products (OxPCs) were characterized by matrix-assisted laser desorption/ionization tandem mass spectrometry (MALDI MS^<i>n</i>, <i>n</i> = 2, 3, and 4). MS² of both the [M + H]⁺ and [M + Na]⁺ ions of short-chain OxPCs yielded product ions related to the PC headgroup and the fatty acid substituents. MS³ of the [M + Na – N­(CH₃)₃]⁺ ions yielded fragmentation indicative of the OxPC modification; specifically, a product ion corresponding to the neutral loss of CO₂ (NL of 44) was observed for OxPCs containing a terminal carboxylic acid rather than an aldehyde. Furthermore, MS⁴ of the [M + Na – HPO₄(CH₂)₂N­(CH₃)₃]⁺ ions resulted in fragmentation pathways dependent on the <i>sn</i>-2 fatty acid chain length and type of functional group(s). Specifically, CHO-containing OxPCs with palmitic acid esterified to the <i>sn</i>-1 position of the glycerol backbone yielded a NL of 254, 2 u less than the nominal mass of palmitic acid, whereas the analogous terminal COOH-containing OxPCs demonstrated a NL of 256. Finally, the presence of a γ-ketone relative to the terminal carboxyl group resulted in C–C bond cleavages along the <i>sn</i>-2 substituent, providing diagnostic product ions for keto-containing OxPCs. This work illustrates the enhanced selectivity afforded by MS^<i>n</i> on the linear ion trap and develops a method for the identification of individual products of PC oxidation

l‑Carnitine Inhibits Lipopolysaccharide-Induced Nitric Oxide Production of SIM-A9 Microglia Cells

Microglia are the resident immune effector cells of the central nervous system. They account for approximately 10–15% of all cells found in the brain and spinal cord, acting as macrophages, sensing and engaging in phagocytosis to eliminate toxic proteins. Microglia are dynamic and can change their morphology in response to cues from their milieu. Parkinson’s disease is a neurodegenerative disease, associated with reactive gliosis, neuroinflammation, and oxidative stress. It is thought that Parkinson’s disease is caused by the accumulation of abnormally folded alpha-synuclein protein, accompanied by persistent neuroinflammation, oxidative stress, and subsequent neuronal injury/death. There is evidence in the literature for mitochondrial dysfunction in Parkinson’s disease as well as fatty acid beta-oxidation, involving l-carnitine. Here we investigate l-carnitine in the context of microglial activation, suggesting a potential new strategy of supplementation for PD patients. Preliminary results from our studies suggest that the treatment of activated microglia with the endogenous antioxidant l-carnitine can reverse the effects of detrimental neuroinflammation in vitro

Isotopic Ratio Outlier Analysis of the <i>S. cerevisiae</i> Metabolome Using Accurate Mass Gas Chromatography/Time-of-Flight Mass Spectrometry: A New Method for Discovery

Isotopic ratio outlier analysis (IROA) is a ¹³C metabolomics profiling method that eliminates sample to sample variance, discriminates against noise and artifacts, and improves identification of compounds, previously done with accurate mass liquid chromatography/mass spectrometry (LC/MS). This is the first report using IROA technology in combination with accurate mass gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS), here used to examine the <i>S. cerevisiae</i> metabolome. <i>S. cerevisiae</i> was grown in YNB media, containing randomized 95% ¹³C, or 5%¹³C glucose as the single carbon source, in order that the isotopomer pattern of all metabolites would mirror the labeled glucose. When these IROA experiments are combined, the abundance of the heavy isotopologues in the 5%¹³C extracts, or light isotopologues in the 95%¹³C extracts, follows the binomial distribution, showing mirrored peak pairs for the molecular ion. The mass difference between the ¹²C monoisotopic and the ¹³C monoisotopic equals the number of carbons in the molecules. The IROA-GC/MS protocol developed, using both chemical and electron ionization, extends the information acquired from the isotopic peak patterns for formulas generation. The process that can be formulated as an algorithm, in which the number of carbons, as well as the number of methoximations and silylations are used as search constraints. In electron impact (EI/IROA) spectra, the artifactual peaks are identified and easily removed, which has the potential to generate “clean” EI libraries. The combination of chemical ionization (CI) IROA and EI/IROA affords a metabolite identification procedure that enables the identification of coeluting metabolites, and allowed us to characterize 126 metabolites in the current study

LipidQC: Method Validation Tool for Visual Comparison to SRM 1950 Using NIST Interlaboratory Comparison Exercise Lipid Consensus Mean Estimate Values

As advances in analytical separation techniques, mass spectrometry instrumentation, and data processing platforms continue to spur growth in the lipidomics field, more structurally unique lipid species are detected and annotated. The lipidomics community is in need of benchmark reference values to assess the validity of various lipidomics workflows in providing accurate quantitative measurements across the diverse lipidome. LipidQC addresses the harmonization challenge in lipid quantitation by providing a semiautomated process, independent of analytical platform, for visual comparison of experimental results of National Institute of Standards and Technology Standard Reference Material (SRM) 1950, “Metabolites in Frozen Human Plasma”, against benchmark consensus mean concentrations derived from the NIST Lipidomics Interlaboratory Comparison Exercise

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% ¹³C, 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

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% ¹³C, 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

Expanding Per- and Polyfluoroalkyl Substances Coverage in Nontargeted Analysis Using Data-Independent Analysis and IonDecon

Per- and polyfluoroalkyl substances (PFAS) are widespread, persistent environmental contaminants that have been linked to various health issues. Comprehensive PFAS analysis often relies on ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC HRMS) and molecular fragmentation (MS/MS). However, the selection and fragmentation of ions for MS/MS analysis using data-dependent analysis results in only the topmost abundant ions being selected. To overcome these limitations, All Ions fragmentation (AIF) can be used alongside data-dependent analysis. In AIF, ions across the entire m/z range are simultaneously fragmented; hence, precursor–fragment relationships are lost, leading to a high false positive rate. We introduce IonDecon, which filters All Ions data to only those fragments correlating with precursor ions. This software can be used to deconvolute any All Ions files and generates an open source DDA formatted file, which can be used in any downstream nontargeted analysis workflow. In a neat solution, annotation of PFAS standards using IonDecon and All Ions had the exact same false positive rate as when using DDA; this suggests accurate annotation using All Ions and IonDecon. Furthermore, deconvoluted All Ions spectra retained the most abundant peaks also observed in DDA, while filtering out much of the artifact peaks. In complex samples, incorporating AIF and IonDecon into workflows can enhance the MS/MS coverage of PFAS (more than tripling the number of annotations in domestic sewage). Deconvolution in complex samples of All Ions data using IonDecon did retain some false fragments (fragments not observed when using ion selection, which were not isotopes or multimers), and therefore DDA and intelligent acquisition methods should still be acquired when possible alongside All Ions to decrease the false positive rate. Increased coverage of PFAS can inform on the development of regulations to address the entire PFAS problem, including both legacy and newly discovered PFAS