Automated flow injection method for the high precision determination of drift tube ion mobility collision cross sections

Evaluation of a Reference-Free Collision Cross Section Calibration Strategy for Proteomics Using SLIM-Based High-Resolution Ion Mobility Spectrometry-Mass Spectrometry

Ion mobility spectrometry (IMS) is a gas-phase analytical technique that separates ions with different sizes and shapes and is compatible with mass spectrometry (MS) to provide an additional separation dimension. The rapid nature of the IMS separation combined with the high sensitivity of MS-based detection and the ability to derive structural information on analytes in the form of the property collision cross section (CCS) makes IMS particularly well-suited for characterizing complex samples in -omics applications. In such applications, the quality of CCS from IMS measurements is critical to confident annotation of the detected components in the complex -omics samples. However, most IMS instrumentation in mainstream use requires calibration to calculate CCS from measured arrival times, with the most notable exception being drift tube IMS measurements using multifield methods. The strategy for calibrating CCS values, particularly selection of appropriate calibrants, has important implications for CCS accuracy, reproducibility, and transferability between laboratories. The conventional approach to CCS calibration involves explicitly defining calibrants ahead of data acquisition and crucially relies upon availability of reference CCS values. In this work, we present a novel reference-free approach to CCS calibration which leverages trends among putatively identified features and computational CCS prediction to conduct calibrations post-data acquisition and without relying on explicitly defined calibrants. We demonstrated the utility of this reference-free CCS calibration strategy for proteomics application using high-resolution structures for lossless ion manipulations (SLIM)-based IMS-MS. We first validated the accuracy of CCS values using a set of synthetic peptides and then demonstrated using a complex peptide sample from cell lysate.

Toward Part-per-Million Precision in the Determination of an Ion's Collision Cross Section Using Multipass Cyclic Ion Mobility

In cyclic ion mobility (cIMS), ions are permitted to travel multiple passes around the drift cell, increasing the distance traveled and the relative separation between ions. This study tests the hypothesis that multiple passes around the cell can also result in improved precision when measuring an ion's mobility and the collision cross section (TWCCS) derived therefrom. Experiments were performed with a diverse set of compounds, including 16 polycyclic aromatic hydrocarbons using gas chromatographic atmospheric pressure chemical ionization and a set of drug molecules by direct infusion electrospray ionization. The average periodic drift time, viz., the average time required for the ion to travel around the cIMS cell once, shifts dramatically, approaching part-per-million (ppm) precision as the number of passes increases to ∼100. Extrapolation of the precision of the CCS values with respect to the number of passes led to the prediction that the precision will reach 1000 ppm after 50 passes, 100 ppm after 100 passes, and <10 ppm after 150 passes. Experiments wherein the number of passes exceeded 100 produced TWCCS values having within-run precisions ranging between 15 and 117 ppm. The improved precision with an increasing number of passes may be a consequence of mitigating space-charge effects by allowing the ions to occupy a larger region of the cIMS cell. A method is proposed to enable practical measurements of TWCCS with ppm precision and is demonstrated to characterize an unknown drug mixture.

Quality assessment of rose tea with different drying methods based on physicochemical properties, HS-SPME-GC-MS, and GC-IMS

The purpose of this study is to compare the physicochemical properties and volatile flavor compounds of rose tea obtained by the methods of normal temperature drying, hot-air drying (HAD), and vacuum freeze-drying (VFD) and to evaluate the quality of rose tea. The physicochemical results showed that the content of ascorbic acid (VC) and the pH value was the highest in rose tea obtained by HAD. The contents of anthocyanin, proanthocyanidins, and total phenols were highest in rose tea obtained by VFD. However, there was no significant difference in total flavonoids between drying methods. The volatile organic compounds (VOCs) in rose tea with different drying methods were analyzed by headspace solid-phase microextraction-gas chromatography-mass spectroscopy (HS-SPME-GC-MS) and HS GC-ion mobility spectroscopy (HS-GC-IMS), and the flavor fingerprint of rose tea was established by principal component analysis (PCA). The concentration of VOCs in rose tea varied greatly with different drying methods. The main flavor compounds of rose tea were alcohols, esters, aldehydes, and terpenoids. HS-GC-IMS was used for the identification of volatile flavor compounds of rose tea, thereby helping to assess the quality of rose tea. In addition, the rose tea samples with different drying methods were well distinguished by PCA. This study deepens the understanding of the physicochemical properties and volatile flavor compounds of rose tea with different drying methods and provides a reference for the identification of rose tea with different drying methods. PRACTICAL APPLICATION: This study deepens the understanding of the physicochemical properties and volatile flavor compounds of rose tea with different drying methods and provides a reference for the identification of rose tea with different drying methods. It also provides an effective theoretical basis for consumers to buy rose tea.

Synchronized Stepped Frequency Modulation for Multiplexed Ion Mobility Measurements

Implementation of frequency-encoded multiplexing for ion mobility spectrometry (e.g., Fourier transform ion mobility spectrometry (FT-IMS)) has facilitated the direct coupling of drift tube ion mobility instrumentation with ion-trap mass analyzers despite their duty cycle mismatch. Traditionally, FT-IMS experiments have been carried out to utilize continuous linear frequency sweeps that are independent of the scan rate of the ion-trap mass analyzer, thus creating a situation where multiple frequencies are swept over two sequential mass scans. This in turn creates a degree of ambiguity in which the ion current derived from a single modulation frequency cannot be assigned to a single data point in the frequency-modulated signal. In an effort to eliminate this ambiguity, this work describes a discrete stepwise function to modulate the ion gates of the IMS while synchronization between the generated frequencies and the scan rate of the linear ion trap is achieved. While the number of individual frequencies used in the stepped frequency sweeps is less than in continuous linear modulation experiments, there is no loss in performance and high levels of precision are maintained across differing combinations of terminal frequencies and scan lengths. Furthermore, the frequency-scan synchronization enables further data-processing techniques such as linear averaging of the frequency modulated signal to drastically improve signal-to-noise ratio for both high and low intensity analytes.

Resolving Power and Collision Cross Section Measurement Accuracy of a Prototype High-Resolution Ion Mobility Platform Incorporating Structures for Lossless Ion Manipulation

A production prototype structures for lossless ion manipulation ion mobility (SLIM IM) platform interfaced to a commercial high-resolution mass spectrometer (MS) is described. The SLIM IM implements the traveling wave ion mobility technique across a ∼13m path length for high-resolution IM (HRIM) separations. The resolving power (CCS/ΔCCS) of the SLIM IM stage was benchmarked across various parameters (traveling wave speeds, amplitudes, and waveforms), and results indicated that resolving powers in excess of 200 can be accessed for a broad range of masses. For several cases, resolving powers greater than 300 were achieved, notably under wave conditions where ions transition from a nonselective "surfing" motion to a mobility-selective ion drift, that corresponded to ion speeds approximately 30-70% of the traveling wave speed. The separation capabilities were evaluated on a series of isomeric and isobaric compounds that cannot be resolved by MS alone, including reversed-sequence peptides (SDGRG and GRGDS), triglyceride double-bond positional isomers (TG 3, 6, 9 and TG 6, 9, 12), trisaccharides (melezitose, raffinose, isomaltotriose, and maltotriose), and ganglioside lipids (GD1b and GD1a). The SLIM IM platform resolved the corresponding isomeric mixtures, which were unresolvable using the standard resolution of a drift-tube instrument (∼50). In general, the SLIM IM-MS platform is capable of resolving peaks separated by as little as ∼0.6% without the need to target a specific separation window or drift time. Low CCS measurement biases <0.5% were obtained under high resolving power conditions. Importantly, all the analytes surveyed are able to access high-resolution conditions (>200), demonstrating that this instrument is well-suited for broadband HRIM separations important in global untargeted applications.

Reevaluating the Role of Polarizability in Ion Mobility Spectrometry

With the expanding commercial availability of gas-phase separation systems that incorporate gas-phase mobility, there is a concurrent rise in efforts to cast the gas-phase mobility coefficient in terms of an ion-neutral collision cross-section (CCS). The motivating factors for this trend are varied, but many aim to complement experimental results with computationally generated CCS values from in silico structural approximations. Unfortunately, the current paradigm for relating experimental mobility results to computationally derived structures relies upon empirical approaches, including a myriad of variables that do not realistically bound the comparison. In this Critical Insight, we advocate for the development of a self-consistent experimental and computational framework that uses laboratory results to constrain the scope of the modeling effort. This paper aims to prompt discussion, challenge assumptions, and promote the development of more efficient, accurate computational techniques within the gas-phase ion measurement community. Specifically, we postulate whether experimental deviations from Langevin's polarization limit (K_pol) are suitable to estimate the relative contributions of hard-sphere collisions and long-range interactions within CCS values. Not surprisingly, different molecule classes exhibit different trends in the K/K_pol ratio when normalized for reduced mass, and the most common IMS calibrants (e.g., tune mix, polyalanine, tetraalkylammonium salts) follow different polarizability trends than many of the analytes probed in the literature. Succinctly, if gas-phase ion structure is largely invariant based upon the colliding neutral and newly developed experimental efforts can quantitatively capture ion polarizability, then modeling efforts describing a target analyte must be self-consistent as the collision neutral is changed in silico.

Assessing Collision Cross Section Calibration Strategies for Traveling Wave-Based Ion Mobility Separations in Structures for Lossless Ion Manipulations

The collision cross section (CCS) is an important property that aids in the structural characterization of molecules. Here, we investigated the CCS calibration accuracy with traveling wave ion mobility spectrometry (TWIMS) separations in structures for lossless ion manipulations (SLIM) using three sets of calibrants. A series of singly negatively charged phospholipids and bile acids were calibrated in nitrogen buffer gas using two different TW waveform profiles (square and sine) and amplitudes (20, 25, and 30 V_0-p). The calibration errors for the three calibrant sets (Agilent tuning mixture, polyalanine, and one assembled in-house) showed negligible differences using a sine-shaped TW waveform. Calibration errors were all within 1-2% of the drift tube ion mobility spectrometry (DTIMS) measurements, with lower errors for sine waveforms, presumably due to the lower average and maximum fields experienced by ions. Finally, ultrahigh-resolution multipass (long path length) SLIM TWIMS separations demonstrated improved CCS calibration for phospholipid and bile acid isomers.

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.

Collision Cross Section Conformational Analyses of Bile Acids via Ion Mobility-Mass Spectrometry

Bile acids serve as one of the most important classes of biological molecules in the gastrointestinal system. Due to their structural similarity, bile acids have historically been difficult to accurately annotate in complex biological matrices using mass spectrometry. They often have identical or nominally similar mass-to-charge ratios and similar fragmentation patterns that make identification by mass spectrometry arduous, normally involving chemical derivatization and separation via liquid chromatography. Here, we demonstrate the use of drift tube ion mobility (DTIM) to derive collision cross section (CCS) values in nitrogen drift gas (DTCCSN2) for use as an additional descriptor to facilitate expedited bile acid identification. We also explore trends in DTIM measurements and detail structural characteristics for differences in DTCCSN2 values between subclasses of bile acid molecules.

Breaking Down Structural Diversity for Comprehensive Prediction of Ion-Neutral Collision Cross Sections

Identification of unknowns is a bottleneck for large-scale untargeted analyses like metabolomics or drug metabolite identification. Ion mobility-mass spectrometry (IM-MS) provides rapid two-dimensional separation of ions based on their mobility through a neutral buffer gas. The mobility of an ion is related to its collision cross section (CCS) with the buffer gas, a physical property that is determined by the size and shape of the ion. This structural dependency makes CCS a promising characteristic for compound identification, but this utility is limited by the availability of high-quality reference CCS values. CCS prediction using machine learning (ML) has recently shown promise in the field, but accurate and broadly applicable models are still lacking. Here we present a novel ML approach that employs a comprehensive collection of CCS values covering a wide range of chemical space. Using this diverse database, we identified the structural characteristics, represented by molecular quantum numbers (MQNs), that contribute to variance in CCS and assessed the performance of a variety of ML algorithms in predicting CCS. We found that by breaking down the chemical structural diversity using unsupervised clustering based on the MQNs, specific and accurate prediction models for each cluster can be trained, which showed superior performance than a single model trained with all data. Using this approach, we have robustly trained and characterized a CCS prediction model with high accuracy on diverse chemical structures. An all-in-one web interface (https://CCSbase.net) was built for querying the CCS database and accessing the predictive model to support unknown compound identifications.

Fundamentals of Ion Mobility-Mass Spectrometry for the Analysis of Biomolecules

Ion mobility-mass spectrometry (IM-MS) combines complementary size- and mass-selective separations into a single analytical platform. This chapter provides context for both the instrumental arrangements and key application areas that are commonly encountered in bioanalytical settings. New advances in these high-throughput strategies are described with description of complementary informatics tools to effectively utilize these data-intensive measurements. Rapid separations such as these are especially important in systems, synthetic, and chemical biology in which many small molecules are transient and correspond to various biological classes for integrated omics measurements. This chapter highlights the fundamentals of IM-MS and its applications toward biomolecular separations and discusses methods currently being used in the fields of proteomics, lipidomics, and metabolomics.

Characterization of the Impact of Drug Metabolism on the Gas-Phase Structures of Drugs Using Ion Mobility-Mass Spectrometry

Conventional strategies for drug metabolite identification employ a combination of liquid chromatography-mass spectrometry (LC-MS), which offers higher throughput but provides limited structural information, and nuclear magnetic resonance spectroscopy, which can achieves the most definitive identification but lacks throughput. Ion mobility-mass spectrometry (IM-MS) is a rapid, two-dimensional analysis that separates ions on the basis of their gas-phase size and shape (reflected by collision cross section, CCS) and their mass-to-charge (m/z) ratios. The rapid nature of IM separation combined with the structural information provided by CCS make IM-MS a promising technique for obtaining more structural information on drug metabolites without sacrificing analytical throughput. Here, we present an in vitro biosynthesis coupled with IM-MS strategy for rapid generation and analysis of drug metabolites. Drug metabolites were generated in vitro using pooled subcellular fractions derived from human liver and analyzed using a rapid flow injection-IM-MS method. We measured CCS values for 19 parent drugs and their 37 metabolites generated in vitro (78 values in total), representing a wide variety of metabolic modifications. Post-IM fragmentation and computational modeling were used to support metabolite identifications and explore the structural characteristics driving behaviors observed in IM separation. Overall, we found the effects of metabolic modifications on the gas-phase structures of the metabolites to be highly dependent upon the structural characteristics of the parent compounds and the specific position of the modification. This in vitro biosynthesis coupled with rapid IM-MS analysis workflow represents a promising platform for rapid and high-confidence identification of drug metabolites, applicable at a large scale.

Ion Mobility Spectrometry in Food Analysis: Principles, Current Applications and Future Trends

In the last decade, ion mobility spectrometry (IMS) has reemerged as an analytical separation technique, especially due to the commercialization of ion mobility mass spectrometers. Its applicability has been extended beyond classical applications such as the determination of chemical warfare agents and nowadays it is widely used for the characterization of biomolecules (e.g., proteins, glycans, lipids, etc.) and, more recently, of small molecules (e.g., metabolites, xenobiotics, etc.). Following this trend, the interest in this technique is growing among researchers from different fields including food science. Several advantages are attributed to IMS when integrated in traditional liquid chromatography (LC) and gas chromatography (GC) mass spectrometry (MS) workflows: (1) it improves method selectivity by providing an additional separation dimension that allows the separation of isobaric and isomeric compounds; (2) it increases method sensitivity by isolating the compounds of interest from background noise; (3) and it provides complementary information to mass spectra and retention time, the so-called collision cross section (CCS), so compounds can be identified with more confidence, either in targeted or non-targeted approaches. In this context, the number of applications focused on food analysis has increased exponentially in the last few years. This review provides an overview of the current status of IMS technology and its applicability in different areas of food analysis (i.e., food composition, process control, authentication, adulteration and safety).

Ion mobility conformational lipid atlas for high confidence lipidomics

Lipids are highly structurally diverse molecules involved in a wide variety of biological processes. Here, we use high precision ion mobility-mass spectrometry to compile a structural database of 456 mass-resolved collision cross sections (CCS) of sphingolipid and glycerophospholipid species. Our CCS database comprises sphingomyelin, cerebroside, ceramide, phosphatidylethanolamine, phosphatidylcholine, phosphatidylserine, and phosphatidic acid classes. Primary differences observed are between lipid categories, with sphingolipids exhibiting 2–6% larger CCSs than glycerophospholipids of similar mass, likely a result of the sphingosine backbone’s restriction of the sn1 tail length, limiting gas-phase packing efficiency. Acyl tail length and degree of unsaturation are found to be the primary structural descriptors determining CCS magnitude, with degree of unsaturation being four times as influential per mass unit. The empirical CCS values and previously unmapped quantitative structural trends detailed in this work are expected to facilitate prediction of CCS in broadscale lipidomics research.

The biological functions of lipids critically depend on their highly diverse molecular structures. Here, the authors determine the mass-resolved collision cross sections of 456 sphingolipid and glycerophospholipid species, providing a reference for future structural lipidomics studies.

Collision cross section compendium to annotate and predict multi-omic compound identities

Ion mobility mass spectrometry (IM-MS) expands the analyte coverage of existing multi-omic workflows by providing an additional separation dimension as well as a parameter for characterization and identification of molecules - the collision cross section (CCS). This work presents a large, Unified CCS compendium of >3800 experimentally acquired CCS values obtained from traceable molecular standards and measured with drift tube ion mobility-mass spectrometers. An interactive visualization of this compendium along with data analytic tools have been made openly accessible. Represented in the compendium are 14 structurally-based chemical super classes, consisting of a total of 80 classes and 157 subclasses. Using this large data set, regression fitting and predictive statistics have been performed to describe mass-CCS correlations specific to each chemical ontology. These structural trends provide a rapid and effective filtering method in the traditional untargeted workflow for identification of unknown biochemical species. The utility of the approach is illustrated by an application to metabolites in human serum, quantified trends of which were used to assess the probability of an unknown compound belonging to a given class. CCS-based filtering narrowed the chemical search space by 60% while increasing the confidence in the remaining isomeric identifications from a single class, thus demonstrating the value of integrating predictive analyses into untargeted experiments to assist in identification workflows. The predictive abilities of this compendium will improve in specificity and expand to more chemical classes as additional data from the IM-MS community is contributed. Instructions for data submission to the compendium and criteria for inclusion are provided.

High-throughput, low-cost reaction screening using a modified 3D printer

We describe a reaction screening system, based on a 96-well array, and scaled to suit use on the individual scientist's bench. The system was built by modifying a desktop 3D printer and fitting it with a glass syringe and microtiter plate. The effects of experimental variables were characterized, and the performance of the system was optimized. Precise volumes of reaction mixtures (<3% CV) were dispensed into the 96-well array in ca. 40 minutes. The system was used to screen reagents and solvents for the N-alkylation, Katritzky transamination, and Suzuki cross-coupling reactions. Product distributions derived from electrospray mass spectra and represented as heat maps facilitated recognition of optimum conditions. Screening of 96 reaction mixtures was completed in the modest time of approximately 105 minutes (∼65 seconds per reaction mixture). The system is constructed from open-source software and inexpensive 3D printer hardware.

Untargeted Molecular Discovery in Primary Metabolism: Collision Cross Section as a Molecular Descriptor in Ion Mobility-Mass Spectrometry

In this work, we established a collision cross section (CCS) library of primary metabolites based on analytical standards in the Mass Spectrometry Metabolite Library of Standards (MSMLS) using a commercially available ion mobility-mass spectrometer (IM-MS). From the 554 unique compounds in the MSMLS plate library, we obtained a total of 1246 CCS measurements over a wide range of biochemical classes and adduct types. Resulting data analysis demonstrated that the curated CCS library provides broad molecular coverage of metabolic pathways and highlights intrinsic mass-mobility relationships for specific metabolite superclasses. The separation and characterization of isomeric metabolites were assessed, and all molecular species contained within the plate library, including isomers, were critically evaluated to determine the analytical separation efficiency in both the mass ( m/ z) and mobility (CCS/ΔCCS) dimension required for untargeted metabolomic analyses. To further demonstrate the analytical utility of CCS as an additional molecular descriptor, a well-characterized biological sample of human plasma serum (NIST SRM 1950) was examined by LC-IM-MS and used to provide a detailed isomeric analysis of carbohydrate constituents by ion mobility.

Software Tools and Approaches for Compound Identification of LC-MS/MS Data in Metabolomics

The annotation of small molecules remains a major challenge in untargeted mass spectrometry-based metabolomics. We here critically discuss structured elucidation approaches and software that are designed to help during the annotation of unknown compounds. Only by elucidating unknown metabolites first is it possible to biologically interpret complex systems, to map compounds to pathways and to create reliable predictive metabolic models for translational and clinical research. These strategies include the construction and quality of tandem mass spectral databases such as the coalition of MassBank repositories and investigations of MS/MS matching confidence. We present in silico fragmentation tools such as MS-FINDER, CFM-ID, MetFrag, ChemDistiller and CSI:FingerID that can annotate compounds from existing structure databases and that have been used in the CASMI (critical assessment of small molecule identification) contests. Furthermore, the use of retention time models from liquid chromatography and the utility of collision cross-section modelling from ion mobility experiments are covered. Workflows and published examples of successfully annotated unknown compounds are included.