Lipid kinase PIK3C3 maintains healthy brown and white adipose tissues to prevent metabolic diseases.

Adequate mass and function of adipose tissues (ATs) play essential roles in preventing metabolic perturbations. The pathological reduction of ATs in lipodystrophy leads to an array of metabolic diseases. Understanding the underlying mechanisms may benefit the development of effective therapies. Several cellular processes, including autophagy and vesicle trafficking, function collectively to maintain AT homeostasis. Here, we investigated the impact of adipocyte-specific deletion of the lipid kinase phosphatidylinositol 3-kinase catalytic subunit type 3 (PIK3C3) on AT homeostasis and systemic metabolism in mice. We report that PIK3C3 functions in all ATs and that its absence disturbs adipocyte autophagy and hinders adipocyte differentiation, survival, and function with differential effects on brown and white ATs. These abnormalities cause loss of white ATs, whitening followed by loss of brown ATs, and impaired "browning" of white ATs. Consequently, mice exhibit compromised thermogenic capacity and develop dyslipidemia, hepatic steatosis, insulin resistance, and type 2 diabetes. While these effects of PIK3C3 largely contrast previous findings with the autophagy-related (ATG) protein ATG7 in adipocytes, mice with a combined deficiency in both factors reveal a dominant role of the PIK3C3-deficient phenotype. We have also found that dietary lipid excess exacerbates AT pathologies caused by PIK3C3 deficiency. Surprisingly, glucose tolerance is spared in adipocyte-specific PIK3C3-deficient mice, a phenotype that is more evident during dietary lipid excess. These findings reveal a crucial yet complex role for PIK3C3 in ATs, with potential therapeutic implications.

Glutamine metabolism improves left ventricular function but not macrophage-mediated inflammation following myocardial infarction.

Glutamine is a critical amino acid that serves as an energy source, building block, and signaling molecule for the heart tissue and the immune system. However, the role of glutamine metabolism in regulating cardiac remodeling following myocardial infarction (MI) is unknown. In this study, we show in adult male mice that glutamine metabolism is altered both in the remote (contractile) area and in infiltrating macrophages in the infarct area after permanent left anterior descending artery occlusion. We found that metabolites related to glutamine metabolism were differentially altered in macrophages at days 1, 3, and 7 after MI using untargeted metabolomics. Glutamine metabolism in live cells was increased after MI relative to no MI controls. Gene expression in the remote area of the heart indicated a loss of glutamine metabolism. Glutamine administration improved left ventricle (LV) function at days 1, 3, and 7 after MI, which was associated with improved contractile and metabolic gene expression. Conversely, administration of BPTES, a pharmacological inhibitor of glutaminase-1, worsened LV function after MI. Neither glutamine nor BPTES administration impacted gene expression or bioenergetics of macrophages isolated from the infarct area. Our results indicate that glutamine metabolism plays a critical role in maintaining LV contractile function following MI and that glutamine administration improves LV function. Glutamine metabolism may also play a role in regulating macrophage function, but macrophages are not responsive to exogenous pharmacological manipulation of glutamine metabolism.NEW & NOTEWORTHY Glutamine metabolism is altered in both infarct macrophages and the remote left ventricle (LV) following myocardial infarction (MI). Supplemental glutamine improves LV function following MI while inhibiting glutamine metabolism with BPTES worsens LV function. Supplemental glutamine or BPTES does not impact macrophage immunometabolic phenotypes after MI.

Taurine modulates host cell responses to Helicobacter pylori VacA toxin.

Colonization of the human stomach with Helicobacter pylori strains producing active forms of the secreted toxin VacA is associated with an increased risk of peptic ulcer disease and gastric cancer, compared with colonization with strains producing hypoactive forms of VacA. Previous studies have shown that active s1m1 forms of VacA cause cell vacuolation and mitochondrial dysfunction. In this study, we sought to define the cellular metabolic consequences of VacA intoxication. Untargeted metabolomic analyses revealed that several hundred metabolites were significantly altered in VacA-treated gastroduodenal cells (AGS and AZ-521) compared with control cells. Pathway analysis suggested that VacA caused alterations in taurine and hypotaurine metabolism. Treatment of cells with the purified active s1m1 form of VacA, but not hypoactive s2m1 or Δ6-27 VacA-mutant proteins (defective in membrane channel formation), caused reductions in intracellular taurine and hypotaurine concentrations. Supplementation of the tissue culture medium with taurine or hypotaurine protected AZ-521 cells against VacA-induced cell death. Untargeted global metabolomics of VacA-treated AZ-521 cells or AGS cells in the presence or absence of extracellular taurine showed that taurine was the main intracellular metabolite significantly altered by extracellular taurine supplementation. These results indicate that VacA causes alterations in cellular taurine metabolism and that repletion of taurine is sufficient to attenuate VacA-induced cell death. We discuss these results in the context of previous literature showing the important role of taurine in cell physiology and the pathophysiology or treatment of multiple pathologic conditions, including gastric ulcers, cardiovascular disease, malignancy, inflammatory diseases, and other aging-related disorders.

Direct Enantiomer Differentiation of Drugs and Drug-Like Compounds via Noncovalent Copper-Amino Acid Complexation and Ion Mobility-Mass Spectrometry.

Drug enantiomers can possess vastly different pharmacological properties, yet they are identical in their chemical composition and structural connectivity. Thus, resolving enantiomers poses a great challenge in the field of separation science. Enantiomer separations necessitate interaction of the analyte with a chiral environment─in mass spectrometry-based analysis, a common approach is through a three-point interaction with a chiral selector commonly introduced during sample preparation. In select cases, the structural difference imparted through noncovalent complexation results in enantiomer-specific structural differences, facilitating measurement using a structurally selective analytical technique such as ion mobility-mass spectrometry (IM-MS). In this work, we investigate the direct IM-MS differentiation of chiral drug compounds using mononuclear copper complexes incorporating an amino acid chiral selector. A panel of 20 chiral drugs and drug-like compounds were investigated for separation, and four l-amino acids (l-histidine, l-tryptophan, l-proline, and l-tyrosine) were evaluated as chiral selectors (CS) to provide the chiral environment necessary for differentiation. Enantiomer differentiation was achieved for four chiral molecule pairs (R/S-thalidomide, R/S-baclofen, R/S-metoprolol, and d/l-panthenol) with two-peak resolution (Rp-p) values ranging from 0.7 (>10% valley) to 1.5 (baseline separation). Calibration curves relating IM peak areas to enantiomeric concentrations enabled enantiomeric excess quantitation of racemic thalidomide and metoprolol with residuals of 5.7 and 2.5%, respectively. Theoretical models suggest that CuII and l-histidine complexation around the analyte chiral center is important for gas-phase stereoselectivity. This study demonstrates the potential of combining enantioselective noncovalent copper complexation with structurally selective IM-MS for differentiating chiral drugs and drug-like compounds.

Ion Mobility-Mass Spectrometry Strategies to Elucidate the Anhydrous Structure of Noncovalent Guest/Host Complexes.

Structural mass spectrometry (MS) techniques are fast and sensitive analytical methods to identify noncovalent guest/host complexation phenomena for desirable solution-phase properties. Current MS-based studies on guest/host complexes of drug and drug-like molecules are sparse, and there is limited guidance on how to interpret MS information in the context of host nanoencapsulation and inclusion. Here, we use structural MS strategies, combining energy-resolved MS (ERMS), ion mobility-MS (IM-MS), and computational modeling, to characterize 14 chemically distinct drug and drug-like compounds for their propensity to form guest/host complexes with the widely used excipient, beta-cyclodextrin (ßCD). The majority (11/14) yielded a 1:1 guest/host complex, and ion mobility collision cross section (CCS) analysis provided subtle evidence of gas-phase compaction of complexes in both polarities. The three distinct dissociation channels observed in ERMS (i.e., charged ßCD, charged guest, and partial guest loss) were used to direct charge-site assignments for computational modeling, and structural candidates were prioritized using helium-derived CCS measurements combined with root-mean-square distance analysis. The combined analytical information from ERMS, IM-MS, and computational modeling suggested that the majority of anhydrous complexes are inclusion complexes with ßCD. Taken together, this work demonstrates a roadmap for how multiple MS-based analytical measurements can be combined to interpret the structures that guest/host complexes adopt in the absence of water.

High-resolution ion mobility based on traveling wave structures for lossless ion manipulation resolves hidden lipid features.

High-resolution ion mobility (resolving power > 200) coupled with mass spectrometry (MS) is a powerful analytical tool for resolving isobars and isomers in complex samples. High-resolution ion mobility is capable of discerning additional structurally distinct features, which are not observed with conventional resolving power ion mobility (IM, resolving power ~ 50) techniques such as traveling wave IM and drift tube ion mobility (DTIM). DTIM in particular is considered to be the "gold standard" IM technique since collision cross section (CCS) values are directly obtained through a first-principles relationship, whereas traveling wave IM techniques require an additional calibration strategy to determine accurate CCS values. In this study, we aim to evaluate the separation capabilities of a traveling wave ion mobility structures for lossless ion manipulation platform integrated with mass spectrometry analysis (SLIM IM-MS) for both lipid isomer standards and complex lipid samples. A cross-platform investigation of seven subclass-specific lipid extracts examined by both DTIM-MS and SLIM IM-MS showed additional features were observed for all lipid extracts when examined under high resolving power IM conditions, with the number of CCS-aligned features that resolve into additional peaks from DTIM-MS to SLIM IM-MS analysis varying between 5 and 50%, depending on the specific lipid sub-class investigated. Lipid CCS values are obtained from SLIM IM (TW(SLIM)CCS) through a two-step calibration procedure to align these measurements to within 2% average bias to reference values obtained via DTIM (DTCCS). A total of 225 lipid features from seven lipid extracts are subsequently identified in the high resolving power IM analysis by a combination of accurate mass-to-charge, CCS, retention time, and linear mobility-mass correlations to curate a high-resolution IM lipid structural atlas. These results emphasize the high isomeric complexity present in lipidomic samples and underscore the need for multiple analytical stages of separation operated at high resolution.

Accelerating strain phenotyping with desorption electrospray ionization-imaging mass spectrometry and untargeted analysis of intact microbial colonies.

Reading and writing DNA were once the rate-limiting step in synthetic biology workflows. This has been replaced by the search for the optimal target sequences to produce systems with desired properties. Directed evolution and screening mutant libraries are proven technologies for isolating strains with enhanced performance whenever specialized assays are available for rapidly detecting a phenotype of interest. Armed with technologies such as CRISPR-Cas9, these experiments are capable of generating libraries of up to 1010 genetic variants. At a rate of 102 samples per day, standard analytical methods for assessing metabolic phenotypes represent a major bottleneck to modern synthetic biology workflows. To address this issue, we have developed a desorption electrospray ionization-imaging mass spectrometry screening assay that directly samples microorganisms. This technology increases the throughput of metabolic measurements by reducing sample preparation and analyzing organisms in a multiplexed fashion. To further accelerate synthetic biology workflows, we utilized untargeted acquisitions and unsupervised analytics to assess multiple targets for future engineering strategies within a single acquisition. We demonstrate the utility of the developed method using Escherichia coli strains engineered to overproduce free fatty acids. We determined discrete metabolic phenotypes associated with each strain, which include the primary fatty acid product, secondary products, and additional metabolites outside the engineered product pathway. Furthermore, we measured changes in amino acid levels and membrane lipid composition, which affect cell viability. In sum, we present an analytical method to accelerate synthetic biology workflows through rapid, untargeted, and multiplexed metabolomic analyses.

Noncovalent Host-Guest Complexes of Artemisinin with α-, ß-, and γ- Cyclodextrin Examined by Structural Mass Spectrometry Strategies.

Cyclodextrins (CDs) are a family of macrocyclic oligosaccharides with amphiphilic properties, which can improve the stability, solubility, and bioavailability of therapeutic compounds. There has been growing interest in the advancement of efficient and reliable analytical methods that assist with elucidating CD host-guest drug complexation. In this study, we investigate the noncovalent ion complexes formed between naturally occurring dextrins (αCD, ßCD, γCD, and maltohexaose) with the poorly water-soluble antimalarial drug, artemisinin, using a combination of ion mobility-mass spectrometry (IM-MS), tandem MS/MS, and theoretical modeling approaches. This study aims to determine if the drug can complex within the core dextrin cavity forming an inclusion complex or nonspecifically bind to the periphery of the dextrins. We explore the use of group I alkali earth metal additives to promote the formation of various noncovalent gas-phase ion complexes with different drug/dextrin stoichiometries (1:1, 1:2, 1:3, 1:4, and 2:1). Broad IM-MS collision cross section (CCS) mapping (n > 300) and power-law regression analysis were used to confirm the stoichiometric assignments. The 1:1 drug:αCD and drug:ßCD complexes exhibited strong preferences for Li+ and Na+ charge carriers, whereas drug:γCD complexes preferred forming adducts with the larger alkali metals, K+, Rb+, and Cs+. Although the ion-measured CCS increased with cation size for the unbound artemisinin and CDs, the 1:1 drug:dextrin complexes exhibit near-identical CCS values regardless of the cation, suggesting these are inclusion complexes. Tandem MS/MS survival yield curves of the [artemisinin:ßCD + X]+ ion (X = H, Li, Na, K) showed a decreased stability of the ion complex with increasing cation size. Empirical CCS measurements of the [artemisinin:ßCD + Li]+ ion correlated with predicted CCS values from the low-energy theoretical structures of the drug incorporated within the ßCD cavity, providing further evidence that gas-phase inclusion complexes are formed in these experiments. Taken together, this work demonstrates the utility of combining analytical information from IM-MS, MS/MS, and computational approaches in interpreting the presence of gas-phase inclusion phenomena.

Improving confidence in lipidomic annotations by incorporating empirical ion mobility regression analysis and chemical class prediction.

MOTIVATION: Mass spectrometry-based untargeted lipidomics aims to globally characterize the lipids and lipid-like molecules in biological systems. Ion mobility increases coverage and confidence by offering an additional dimension of separation and a highly reproducible metric for feature annotation, the collision cross-section (CCS). RESULTS: We present a data processing workflow to increase confidence in molecular class annotations based on CCS values. This approach uses class-specific regression models built from a standardized CCS repository (the Unified CCS Compendium) in a parallel scheme that combines a new annotation filtering approach with a machine learning class prediction strategy. In a proof-of-concept study using murine brain lipid extracts, 883 lipids were assigned higher confidence identifications using the filtering approach, which reduced the tentative candidate lists by over 50% on average. An additional 192 unannotated compounds were assigned a predicted chemical class. AVAILABILITY AND IMPLEMENTATION: All relevant source code is available at https://github.com/McLeanResearchGroup/CCS-filter. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Performance evaluation of in-source ion activation hardware for collision-induced unfolding of proteins and protein complexes on a drift tube ion mobility-mass spectrometer.

Native ion mobility-mass spectrometry (IM-MS) has emerged as an information-rich technique for gas phase protein structure characterization; however, IM resolution is currently insufficient for the detection of subtle structural differences in large biomolecules. This challenge has spurred the development of collision-induced unfolding (CIU) which utilizes incremental gas phase activation to unfold a protein in order to expand the number of measurable descriptors available for native protein ions. Although CIU is now routinely used in native mass spectrometry studies, the interlaboratory reproducibility of CIU has not been established. Here we evaluate the reproducibility of the CIU data produced across three laboratories (University of Michigan, Texas A&M University, and Vanderbilt University). CIU data were collected for a variety of protein ions ranging from 8.6-66 kDa. Within the same laboratory, the CIU fingerprints were found to be repeatable with root mean square deviation (RMSD) values of less than 5%. Collision cross section (CCS) values of the CIU intermediates were consistent across the laboratories, with most features exhibiting an interlaboratory reproducibility of better than 1%. In contrast, the activation potentials required to induce protein CIU transitions varied between the three laboratories. To address these differences, three source assemblies were constructed with an updated ion activation hardware design utilizing higher mechanical tolerance specifications. The production-grade assemblies were found to produce highly consistent CIU data for intact antibodies, exhibiting high precision ion CCS and CIU transition values, thus opening the door to establishing databases of CIU fingerprints to support future biomolecular classification efforts.

Insights and prospects for ion mobility-mass spectrometry in clinical chemistry.

INTRODUCTION: Ion mobility-mass spectrometry is an emerging technology in the clinical setting for high throughput and high confidence molecular characterization from complex biological samples. Ion mobility spectrometry can provide isomer separations on the basis of molecular structure, the ability of which is increasing through technological developments that afford enhanced resolving power. Integrating multiple separation dimensions, such as liquid chromatography-ion mobility-mass spectrometry (LC-IM-MS) provide dramatic enhancements in the mitigation of molecular interferences for high accuracy clinical measurements. AREAS COVERED: Multidimensional separations with LC-IM-MS provide better selectivity and sensitivity in molecular analysis. Mass spectrometry imaging of tissues to inform spatial molecular distribution is improved by complementary ion mobility analyses. Biomarker identification in surgical environments is enhanced by intraoperative biochemical analysis with mass spectrometry and holds promise for integration with ion mobility spectrometry. New prospects in high resolving power ion mobility are enhancing analysis capabilities, such as distinguishing isomeric compounds. EXPERT OPINION: Ion mobility-mass spectrometry holds many prospects for the field of isomer identification, molecular imaging, and intraoperative tumor margin delineation in clinical settings. These advantages are afforded while maintaining fast analysis times and subsequently high throughput. High resolving power ion mobility will enhance these advantages further, in particular for analyses requiring high confidence isobaric selectivity and detection.

Integrating ion mobility into comprehensive multidimensional metabolomics workflows: critical considerations.

BACKGROUND: Ion mobility (IM) separation capabilities are now widely available to researchers through several commercial vendors and are now being adopted into many metabolomics workflows. The added peak capacity that ion mobility offers with minimal compromise to other analytical figures-of-merit has provided real benefits to sensitivity and structural selectivity and have allowed more specific metabolite annotations to be assigned in untargeted workflows. One of the greatest promises of contemporary IM-enabled instrumentation is the capability of operating multiple analytical dimensions inline with minimal sample volumes, which has the potential to address many grand challenges currently faced in the omics fields. However, comprehensive operation of multidimensional mass spectrometry comes with its own inherent challenges that, beyond operational complexity, may not be immediately obvious to practitioners of these techniques. AIM OF REVIEW: In this review, we outline the strengths and considerations for incorporating IM analysis in metabolomics workflows and provide a critical but forward-looking perspective on the contemporary challenges and prospects associated with interpreting IM data into chemical knowledge. KEY SCIENTIFIC CONCEPTS OF REVIEW: We outline a strategy for unifying IM-derived collision cross section (CCS) measurements obtained from different IM techniques and discuss the emerging field of high resolution ion mobility (HRIM) that is poised to address many of the contemporary challenges associated with ion mobility metabolomics. Whereas the LC step limits the throughput of comprehensive LC-IM-MS, the higher peak capacity of HRIM can allow fast LC gradients or rapid sample cleanup via solid-phase extraction (SPE) to be utilized, significantly improving the sample throughput.

The acyl chains of phosphoinositide PIP3 alter the structure and function of nuclear receptor steroidogenic factor-1.

Nuclear receptors are transcription factors that bind lipids, an event that induces a structural conformation of the receptor that favors interaction with transcriptional coactivators. The nuclear receptor steroidogenic factor-1 (SF-1, NR5A1) binds the signaling phosphoinositides PI(4,5)P2 (PIP2) and PI(3,4,5)P3 (PIP3), and our previous crystal structures showed how the phosphoinositide headgroups regulate SF-1 function. However, what role the acyl chains play in regulating SF-1 structure remains unaddressed. Here, we used X-ray crystallography with in vitro binding and functional assays to examine how the acyl chains of PIP3 regulate human SF-1 ligand-binding domain structure and function. Altering acyl chain length and unsaturation regulates apparent binding of all tested phosphoinositides to SF-1. Mass spectrometry-based lipidomics data suggest C16 and C18 phospholipids preferentially associate with SF-1 expressed ectopically in bacteria. We then solved the 2.5 Å crystal structure of SF-1 bound to dioleoyl PIP3(18:1/18:1) to compare it with a matched structure of SF-1 bound to dipalmitoyl PIP3(16:0/16:0). The dioleoyl-bound structure was severely disordered in a specific SF-1 region associated with pathogenic human polymorphisms and within the coactivator-binding region critical for SF-1 function while inducing increased sensitivity to protease digestion in solution. Validating these structural observations, in vitro functional studies showed dioleoyl PIP3 induced 6-fold poorer affinity of a peroxisome proliferator-activated receptor gamma coactivator 1-alpha coactivator peptide for SF-1 compared with dipalmitoyl PIP3. Together, these data suggest the chemical nature of the phosphoinositide acyl chains controls the ordered state of specific, clinically important structural regions in SF-1, regulating SF-1 function in vitro.

Targeted and Untargeted Mass Spectrometry Reveals the Impact of High-Fat Diet on Peripheral Amino Acid Regulation in a Mouse Model of Alzheimer's Disease.

Recent research regarding amino acid metabolism has shown that there may be a link between obesity and Alzheimer's disease (AD). This work reports a metabolomics study using targeted and untargeted mass spectrometry-based metabolomic strategies to investigate this link. Targeted hydrophilic interaction liquid chromatography-triple quadrupole mass spectrometry and untargeted reversed-phase liquid chromatography-high resolution tandem mass spectrometry assays were developed to analyze the metabolic changes that occur in AD and obesity. APPSwe/PS1ΔE9 (APP/PSEN1) transgenic mice (to represent familial or early-onset AD) and wild-type littermate controls were fed either a high-fat diet (HFD, 60% kcal from lard) or a low-fat diet (LFD, 10% kcal from lard) from 2 months of age or a reversal diet (HFD, followed by LFD from 9.5 months). For targeted analyses, we applied the guidelines outlined in the Clinical and Laboratory Standards Institute (CLSI) LC-MS C62-A document and the U.S. Food and Drug Administration (FDA) bioanalytical method validation guidance for industry to evaluate the figures of merit of the assays. Our targeted and untargeted metabolomics results suggest that numerous peripheral pathways, specifically amino acid metabolism and fatty acid metabolism, were significantly affected by AD and diet. Multiple amino acids (including alanine, glutamic acid, leucine, isoleucine, and phenylalanine), carnitines, and members of the fatty acid oxidation pathway were significantly increased in APP/PSEN1 mice on HFD compared to those on LFD. More substantial effects and changes were observed in the APP/PSEN1 mice than in the WT mice, suggesting that they were more sensitive to an HFD. These dysregulated peripheral pathways include numerous amino acid pathways and fatty acid beta oxidation and suggest that obesity combined with AD further enhances cognitive impairment, possibly through aggravated mitochondrial dysfunction. Furthermore, partial reversibility of many altered pathways was observed, which highlights that diet change can mitigate the metabolic effects of AD. The same trends in individual amino acids were observed in both strategies, highlighting the biological validity of the results.

Multidimensional Separations of Intact Phase II Steroid Metabolites Utilizing LC-Ion Mobility-HRMS.

The detection and unambiguous identification of anabolic-androgenic steroid metabolites are essential in clinical, forensic, and antidoping analyses. Recently, sulfate phase II steroid metabolites have received increased attention in steroid metabolism and drug testing. In large part, this is because phase II steroid metabolites are excreted for an extended time, making them a potential long-term chemical marker of choice for tracking steroid misuse in sports. Comprehensive analytical methods, such as liquid chromatography-tandem mass spectrometry (LC-MS/MS), have been used to detect and identify glucuronide and sulfate steroids in human urine with high sensitivity and reliability. However, LC-MS/MS identification strategies can be hindered by the fact that phase II steroid metabolites generate nonselective ion fragments across the different metabolite markers, limiting the confidence in metabolite identifications that rely on exact mass measurement and MS/MS information. Additionally, liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is sometimes insufficient at fully resolving the analyte peaks from the sample matrix (commonly urine) chemical noise, further complicating accurate identification efforts. Therefore, we developed a liquid chromatography-ion mobility-high resolution mass spectrometry (LC-IM-HRMS) method to increase the peak capacity and utilize the IM-derived collision cross section (CCS) values as an additional molecular descriptor for increased selectivity and to improve identifications of intact steroid analyses at low concentrations.

Chemical Class Prediction of Unknown Biomolecules Using Ion Mobility-Mass Spectrometry and Machine Learning: Supervised Inference of Feature Taxonomy from Ensemble Randomization.

This work presents a machine learning algorithm referred to as the supervised inference of feature taxonomy from ensemble randomization (SIFTER), which supports the identification of features derived from untargeted ion mobility-mass spectrometry (IM-MS) experiments. SIFTER utilizes random forest machine learning on three analytical measurements derived from IM-MS (collision cross section, CCS), mass-to-charge (m/z), and mass defect (Δm) to classify unknown features into a taxonomy of chemical kingdom, super class, class, and subclass. Each of these classifications is assigned a calculated probability as well as alternate classifications with associated probabilities. After optimization, SIFTER was tested against a set of molecules not used in the training set. The average success rate in classifying all four taxonomy categories correctly was found to be >99%. Analysis of molecular features detected from a complex biological matrix and not used in the training set yielded a lower success rate where all four categories were correctly predicted for ∼80% of the compounds. This decline in performance is in part due to incompleteness of the training set across all potential taxonomic categories, but also resulting from a nearest-neighbor bias in the random forest algorithm. Ongoing efforts are focused on improving the class prediction accuracy of SIFTER through expansion of empirical data sets used for training as well as improvements to the core algorithm.

Resolution of Isomeric Mixtures in Ion Mobility Using a Combined Demultiplexing and Peak Deconvolution Technique.

A combined data acquisition and data processing strategy for improving the sensitivity and resolution of ion mobility measurements is described. This strategy is implemented on a commercially available drift tube ion mobility-mass spectrometry (IM-MS) instrument and utilizes both an existing ion multiplexing strategy to achieve up to an 8-fold gain in ion signal and a new postacquisition data reconstruction technique, termed "high resolution demultiplexing" (HRdm), to improve resolution in the ion mobility dimension. A series of isomeric mixtures were qualitatively investigated with HRdm, including biologically relevant lipids and carbohydrates, which were successfully resolved by HRdm, including two monosaccharide regioisomers which differed in drift time by only 0.8%. For a complex trisaccharide isomer mixture, HRdm was able to resolve 5 out of 6 components. An analysis of two-peak resolution (Rpp) and peak-to-peak separation (ΔP) indicated that HRdm performs with an effective resolving power (Rp) of between 180 to 250 for the highest deconvolution settings. Overall analysis times and drift time measurement precision were found to be unaffected between standard and HRdm processed data sets, which allowed statistically identical collision cross section values to be directly determined from all ion mobility spectra.

Targeted Strategy to Analyze Antiepileptic Drugs in Human Serum by LC-MS/MS and LC-Ion Mobility-MS.

Routine small-molecule analysis is challenging owing to the need for high selectivity and/or low limits of quantification. This work reports a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to quantify 14 antiepileptic drugs (AEDs) in human serum. For the optimized LC-MS/MS method described herein, we applied the guidelines outlined in the Clinical and Laboratory Standards Institute (CLSI) LC-MS C62-A document and the U.S. Food and Drug Administration (FDA) Bioanalytical Method Validation Guidance for Industry to evaluate the quality of the assay. In these studies, AED linearity, analyte recovery, matrix effects, precision, and accuracy were assessed. Using liquid chromatography-drift tube ion mobility-mass spectrometry (LC-DTIM-MS), a qualitative method was also used to increase confidence in AED identification using accurate mass and collision cross section (CCS) measurements. The LC-DTIM-MS method was also used to assess the ability of drift tube CCS measurements to aid in the separation and identification of AED structural isomers and other AEDs. These data show that another dimension of information, namely CCS measurements, provides an orthogonal dimension of structural information needed for AED analysis. Multiplexed AED measurements using LC-MS/MS and LC-DTIM-MS have the potential to enable better optimization of dosing owing to the high precision capabilities available in these types of analytical studies. Taken together, these data also show the ability to increase confidence in small-molecule identification and quantification using these analytical technologies.

Recommendations for reporting ion mobility Mass Spectrometry measurements.

Here we present a guide to ion mobility mass spectrometry experiments, which covers both linear and nonlinear methods: what is measured, how the measurements are done, and how to report the results, including the uncertainties of mobility and collision cross section values. The guide aims to clarify some possibly confusing concepts, and the reporting recommendations should help researchers, authors and reviewers to contribute comprehensive reports, so that the ion mobility data can be reused more confidently. Starting from the concept of the definition of the measurand, we emphasize that (i) mobility values (K0 ) depend intrinsically on ion structure, the nature of the bath gas, temperature, and E/N; (ii) ion mobility does not measure molecular surfaces directly, but collision cross section (CCS) values are derived from mobility values using a physical model; (iii) methods relying on calibration are empirical (and thus may provide method-dependent results) only if the gas nature, temperature or E/N cannot match those of the primary method. Our analysis highlights the urgency of a community effort toward establishing primary standards and reference materials for ion mobility, and provides recommendations to do so. © 2019 The Authors. Mass Spectrometry Reviews Published by Wiley Periodicals, Inc.

Mass spectrometry and ion mobility study of poly(ethylene glycol)-based polyurethane oligomers.

RATIONALE: Commercial-grade polymer synthesis is performed via melt polymerization, which leads to polydispersion. The work reported herein provides a synthetic strategy to produce mono-dispersive polyurethane oligomers and an analytical strategy to distinguish these oligomers, providing chemists with the tools necessary to synthesize and identify specific polymer structures that exhibit a desired property. METHODS: Three isomeric poly(ethylene glycol)-polyurethane (PEG-PUR) oligomers were synthesized and analyzed via flow-injection ion mobility mass spectrometry (IM-MS). Each polymer oligomer was injected and run independently via flow injection at 100 µL•min-1 and analyzed in positive ion mode on a drift tube quadrupole time-of-flight (QTOF) instrument. Mobility measurements were determined using a single-field approach. For tandem mass spectrometry (MS/MS) experiments, the sodium-adducted singly charged precursor ion was isolated in the quadrupole and subjected to a range of collision energies. RESULTS: In MS experiments, both +1 and +2 sodium-adducted species were observed for each oligomer at m/z 837.4 and 430.2, respectively. When isolated and fragmented via MS/MS, the +1 precursor yielded distinct product ions for each of the three isomeric oligomers. Fragmentation generally occurred at urethane linkages via 1,3- and 1,5-H shift mechanisms. IM was also used to distinguish the three isomers, with greater IM separation observed for the +2 versus the +1 species. CONCLUSIONS: Mono-disperse PEG-PUR oligomers were synthesized and analyzed. Although the polymeric oligomers analyzed in this study are quite small and structurally simple, this work serves as a model system for the synthesis and structural characterization of larger, more complex block copolymers.