Collision Cross Section Values Research Articles

Peptide collision cross sections of 22 post-translational modifications

Recent advances have rekindled the interest in ion mobility as an additional dimension of separation in mass spectrometry (MS)-based proteomics. Ion mobility separates ions according to their size and shape in the gas phase. Here, we set out to investigate the effect of 22 different post-translational modifications (PTMs) on the collision cross section (CCS) of peptides. In total, we analyzed ~4300 pairs of matching modified and unmodified peptide ion species by trapped ion mobility spectrometry (TIMS). Linear alignment based on spike-in reference peptides resulted in highly reproducible CCS values with a median coefficient of variation of 0.26%. On a global level, we observed a redistribution in the m/z vs. ion mobility space for modified peptides upon changes in their charge state. Pairwise comparison between modified and unmodified peptides of the same charge state revealed median shifts in CCS between −1.4% (arginine citrullination) and +4.5% (O-GlcNAcylation). In general, increasing modified peptide masses were correlated with higher CCS values, in particular within homologous PTM series. However, investigating the ion populations in more detail, we found that the change in CCS can vary substantially for a given PTM and is partially correlated with the gas phase structure of its unmodified counterpart. In conclusion, our study shows PTM- and sequence-specific effects on the cross section of peptides, which could be further leveraged for proteome-wide PTM analysis.Graphical

Coupling Isotopic Shifts with Collision Cross-Section Measurements for Carbohydrate Characterization in High-Resolution Ion Mobility Separations.

Herein, we introduce a two-dimensional strategy to better characterize carbohydrate isomers. In a single experiment, we can derive cyclic ion mobility-mass spectrometry (cIMS-MS)-based collision cross-section (CCS) values in conjunction with measuring isotopic shifts through the relative arrival times of light and heavy isotopologues. These isotopic shifts were introduced by permethylating carbohydrates with either light, CH3, or heavy, CD3, labels at every available hydroxyl group to generate a light/heavy pair of isotopologues for every individual species analyzed. We observed that our calculated CCS values, which were exclusively measured for the light isotopologues, were orthogonal to our measured isotopic shifts (i.e., relative arrival time values between heavy and light permethylated isotopologues). Our permethylation-induced isotopic shifts scaled well with increasing molecular weight, up to ∼m/z 1300, expanding the analysis of isotopic shifts to molecules 3-4 times as large as those previously studied. Our presented use of coupling CCS values with the measurement of isotopic shifts in a single cIMS-MS experiment is a proof-of-concept demonstration that our two-dimensional approach can improve the characterization of challenging isomeric carbohydrates. We envision that our presented 2D approach will have broad utility for varying molecular classes as well as being amenable to many forms of derivatization.

AllCCS2: Curation of Ion Mobility Collision Cross-Section Atlas for Small Molecules Using Comprehensive Molecular Representations.

The development of ion mobility-mass spectrometry (IM-MS) has revolutionized the analysis of small molecules, such as metabolomics, lipidomics, and exposome studies. The curation of comprehensive reference collision cross-section (CCS) databases plays a pivotal role in the successful application of IM-MS for small-molecule analysis. In this study, we presented AllCCS2, an enhanced version of AllCCS, designed for the universal prediction of the ion mobility CCS values of small molecules. AllCCS2 incorporated newly available experimental CCS data, including 10,384 records and 7713 unified values, as training data. By leveraging a neural network trained on diverse molecular representations encompassing mass spectrometry features, molecular descriptors, and graph features extracted using a graph convolutional network, AllCCS2 achieved exceptional prediction accuracy. AllCCS2 achieved median relative error (MedRE) values of 0.31, 0.72, and 1.64% in the training, validation, and testing sets, respectively, surpassing existing CCS prediction tools in terms of accuracy and coverage. Furthermore, AllCCS2 exhibited excellent compatibility with different instrument platforms (DTIMS, TWIMS, and TIMS). The prediction uncertainties in AllCCS2 from the training data and the prediction model were comprehensively investigated by using representative structure similarity and model prediction variation. Notably, small molecules with high structural similarities to the training set and lower model prediction variation exhibited improved accuracy and lower relative errors. In summary, AllCCS2 serves as a valuable resource to support applications of IM-MS technologies. The AllCCS2 database and tools are freely accessible at http://allccs.zhulab.cn/.

Two-dimensional liquid chromatography and ion mobility-mass spectrometry for the multicomponent characterization of different parts of the medicinal plant Gynostemma longipes.

Herba Gynostemma (Jiaogulan) is an herbaceous plant of the genus Gynostemma in the family Cucurbitaceae. Gynostemma longipes has lipid-lowering activity, thus, it is used as a medicinal material. However, its medicinal using parts have been recorded as whole plants or aerial parts in different provincial quality standards; therefore, it is necessary to conduct a comprehensive compositional analysis of the different parts of G. longipes (rhizomes, stems, and leaves) used in traditional medicine. In this study, offline two-dimensional liquid chromatography-ion mobility-quadrupole time-of-flight mass spectrometry (2D-LC/IM-QTOF-MS) was used to analyze the different parts of G. longipes obtained from Shaanxi province, China. By combining the retention times, mass fragments, collision cross-section values, reference standards, and information concerning literature compounds, 396 components were identified from the three parts of the plant, including 94 groups of isomers, and 217 components were identified or tentatively identified as new compounds. In the rhizomes, leaves, and stems, 240, 220, and 168 compounds, respectively, were identified. Differential analysis of the compounds in the rhizomes and aerial parts was also carried out, and 36 differential components were identified, of which 32 had higher contents in the rhizomes. Therefore, these findings indicate that the number of chemical components and the content of major differential components are higher in the rhizomes than the leaves and stems of G. longipes from the Maobaling Planting Base in Pingli county, Shaanxi province. Thus, the rhizomes of G. longipes are also an important part for medicinal use. These results will contribute to the establishment of quality control methods for G. longipes.

Collision cross section measurement and prediction methods in omics.

Omics studies such as metabolomics, lipidomics, and proteomics have become important for understanding the mechanisms in living organisms. However, the compounds detected are structurally different and contain isomers, with each structure or isomer leading to a different result in terms of the role they play in the cell or tissue in the organism. Therefore, it is important to detect, characterize, and elucidate the structures of these compounds. Liquid chromatography and mass spectrometry have been utilized for decades in the structure elucidation of key compounds. While prediction models of parameters (such as retention time and fragmentation pattern) have also been developed for these separation techniques, they have some limitations. Moreover, ion mobility has become one of the most promising techniques to give a fingerprint to these compounds by determining their collision cross section (CCS) values, which reflect their shape and size. Obtaining accurate CCS enables its use as a filter for potential analyte structures. These CCS values can be measured experimentally using calibrant-independent and calibrant-dependent approaches. Identification of compounds based on experimental CCS values in untargeted analysis typically requires CCS references from standards, which are currently limited and, if available, would require a large amount of time for experimental measurements. Therefore, researchers use theoretical tools to predict CCS values for untargeted and targeted analysis. In this review, an overview of the different methods for the experimental and theoretical estimation of CCS values is given where theoretical prediction tools include computational and machine modeling type approaches. Moreover, the limitations of the current experimental and theoretical approaches and their potential mitigation methods were discussed.

Ionmob: a Python package for prediction of peptide collisional cross-section values.

Including ion mobility separation (IMS) into mass spectrometry proteomics experiments is useful to improve coverage and throughput. Many IMS devices enable linking experimentally derived mobility of an ion to its collisional cross-section (CCS), a highly reproducible physicochemical property dependent on the ion's mass, charge and conformation in the gas phase. Thus, known peptide ion mobilities can be used to tailor acquisition methods or to refine database search results. The large space of potential peptide sequences, driven also by posttranslational modifications of amino acids, motivates an in silico predictor for peptide CCS. Recent studies explored the general performance of varying machine-learning techniques, however, the workflow engineering part was of secondary importance. For the sake of applicability, such a tool should be generic, data driven, and offer the possibility to be easily adapted to individual workflows for experimental design and data processing. We created ionmob, a Python-based framework for data preparation, training, and prediction of collisional cross-section values of peptides. It is easily customizable and includes a set of pretrained, ready-to-use models and preprocessing routines for training and inference. Using a set of ≈21 000 unique phosphorylated peptides and ≈17 000 MHC ligand sequences and charge state pairs, we expand upon the space of peptides that can be integrated into CCS prediction. Lastly, we investigate the applicability of in silico predicted CCS to increase confidence in identified peptides by applying methods of re-scoring and demonstrate that predicted CCS values complement existing predictors for that task. The Python package is available at github: https://github.com/theGreatHerrLebert/ionmob.

The IMSCal approach to determine collision cross section of multiply charged anions in traveling wave ion mobility spectrometry

The need for appropriate standards to calibrate ion arrival times in traveling wave ion mobility (TWIM) remains an issue for collision cross section (CCS) measurements, particularly in the case of multiply charged anions due to the scarcity of calibrants in the negative ion mode. In order to circumvent constraints raised for standards in the conventional power law calibration, the new approach recently implemented in the IMSCal software (Anal. Chem. 93 (2021) 3542–3550) has been evaluated here to derive CCS of multiply charged anions measured by TWIM. The mathematical model developed in IMSCal to describe ion motion in the TWIM cell was trained with different combinations of phosphoric acid clusters and deprotonated polyalanine standards and performance of so-obtained calibrations was evaluated for multiply deprotonated oligothymidine 10mers used as control analytes. Although optimal composition of the calibrant set could not be fully rationalized, one mandatory condition for best CCS accuracy is to include standards of different charge states to properly model the effects of radial distribution of ions in the TWIM cell. Further improvement of calibration robustness requires that one of these charge states equals that of the analytes to account for the effects of velocity relaxation also incorporated in the IMSCal model. Doing so, experimental CCS values could be readily obtained with relative error below ±5% for anions of charge state up to 6–.

Nanographite-assisted matrix solid phase dispersion microextraction of active and toxic compounds from complex food matrices using cyclodextrin aqueous solution as elution solvent.

In this study, a cyclodextrin aqueous solution was used as an environmentally friendly eluent to simultaneously extract active and toxic compounds from food matrices with the aid of nanographite-assisted matrix solid phase dispersion microextraction (NG-MSPDM). The NG-MSPDM procedure was optimized by single-factor experiments and response surface methodology to obtain optimum conditions. The proposed method achieved excellent linearity at 0.10-20μg/mL for all target analytes with a coefficient of correction (R2)≥0.9909, limits of detection < 52.01ng/mL, satisfactory reproducibility below 3.21%, and acceptable recoveries of 82.0-112%. To accurately determine the target components in the complex matrix, collision cross-section values of the analytes were obtained using ion mobility quadrupole time-of-flight mass spectrometry (IM-Q-TOF/MS). Results indicated that the NG-MSPDM method successfully achieved the simultaneous extraction of flavonoids and phenoxyacetic herbicides from Alpinia officinarum.

The analysis of the migration of per and poly fluoroalkyl substances (PFAS) from food contact materials using ultrahigh performance liquid chromatography coupled to ion-mobility quadrupole time-of-flight mass spectrometry (UPLC- IMS-QTOF)

Per-poly fluoroalkyl substances (PFASs) are a group of synthetic fluorine compounds used in food packaging materials to repel water and fats. This study assessed the chemical migration of PFAS from different food contact materials, including cardboard, recycled cardboard, biopolymer, paper and Teflon trays, from various markets. Migration assays were conducted using Tenax® as a food simulant, which was optimized by subjecting it to three consecutive extractions with 3 mL of ethanol within an hour. The resulting extractions were combined and concentrated to 0.5 mL using a nitrogen stream. The analysis was performed using ultrahigh performance liquid chromatography (UPLC) coupled with ion-mobility (IMS) quadrupole-time-of-flight (QTOF) mass spectrometry, which provided a powerful and novel tool for identifying a library of targets containing collision cross section values (CCS) and increasing confidence in subsequent identifications. Eleven PFAS compounds belonging to the family of perfluorocarboxylic acid, perfluorosulfonic acid and perfluorooctanesulfonamidoacetic acid substances (PFCAs, PFSAs and FOSAAs) were found in packaging samples obtained from China, with migrant concentrations ranging 3.2 and 22.3 μg/kg. In contrast, no detectable levels of PFAS were observed in packaging samples obtained in Spain. All trays tested were deemed to be suitable for use as food contact materials due to the fact that their migrant values were lower than 0.025 mg/kg for PFOA and its salts, and lower than a maximum concentration of 1 mg/kg for PFOA-related compounds.

Improved separation of fentanyl isomers using metal cation adducts and high-resolution ion mobility-mass spectrometry.

Fentanyl is a potent synthetic opioid that has attracted significant attention due to its illegal production and distribution, resulting in misuse, overdose, and fatalities. Because numerous fentanyl analogs, including structural isomers, with different potency have been discovered in the field, there is a critical need to continue developing analytical methodologies capable of accurate identification in forensic and clinical laboratories. This study aimed to develop a rapid method for detecting and separating fentanyl isomers based on ion mobility-mass spectrometry (IM-MS), where IM separates gas-phase ions based on differences in their size, shape, and charge. Several strategies for improved differentiation were implemented, including using unconventional cation adducts (e.g., alkali and transition metals) and data post-processing by high-resolution demultiplexing. A collection of collision cross section (CCS) values for the various metal ion adducts was gathered, which can be used to improve confidence of identification in future samples. Notable examples, such as [M + Cu]+ and [M + Ag]+ adducts, contributed to significant improvement of resolution between isomers. Furthermore, the addition of high-resolution post-processing provided resolving power of >150, which constitutes a significant increase in comparison with the normal 50-60 obtained with low-resolution drift tube instruments. Collectively, these improved separation strategies allowed for confident detection and subsequent quantitative analysis. The optimized IM-MS method resulted in quantification of fentanyl in human urine with limits of detection and quantification of 13 pg/mL and 40 pg/mL, respectively.

Complementary methods for structural assignment of isomeric candidate structures in non-target liquid chromatography ion mobility high-resolution mass spectrometric analysis

Non-target screening with LC/IMS/HRMS is increasingly employed for detecting and identifying the structure of potentially hazardous chemicals in the environment and food. Structural assignment relies on a combination of multidimensional instrumental methods and computational methods. The candidate structures are often isomeric, and unfortunately, assigning the correct structure among a number of isomeric candidate structures still is a key challenge both instrumentally and computationally. While practicing non-target screening, it is usually impossible to evaluate separately the limitations arising from (1) the inability of LC/IMS/HRMS to resolve the isomeric candidate structures and (2) the uncertainty of in silico methods in predicting the analytical information of isomeric candidate structures due to the lack of analytical standards for all candidate structures. Here we evaluate the feasibility of structural assignment of isomeric candidate structures based on in silico–predicted retention time and database collision cross-section (CCS) values as well as based on matching the empirical analytical properties of the detected feature with those of the analytical standards. For this, we investigated 14 candidate structures corresponding to five features detected with LC/HRMS in a spiked surface water sample. Considering the predicted retention times and database CCS values with the accompanying uncertainty, only one of the isomeric candidate structures could be deemed as unlikely; therefore, the annotation of the LC/IMS/HRMS features remained ambiguous. To further investigate if unequivocal annotation is possible via analytical standards, the reversed-phase LC retention times and low- and high-resolution ion mobility spectrometry separation, as well as high-resolution MS2 spectra of analytical standards were studied. Reversed-phase LC separated the highest number of candidate structures while low-resolution ion mobility and high-resolution MS2 spectra provided little means for pinpointing the correct structure among the isomeric candidate structures even if analytical standards were available for comparison. Furthermore, the question arises which prediction accuracy is required from the in silico methods to par the analytical separation. Based on the experimental data of the isomeric candidate structures studied here and previously published in the literature (516 retention time and 569 CCS values), we estimate that to reduce the candidate list by 95% of the structures, the confidence interval of the predicted retention times would need to decrease to below 0.05 min for a 15-min gradient while that of CCS values would need to decrease to 0.15%. Hereby, we set a clear goal to the in silico methods for retention time and CCS prediction.Graphical abstract

Ion mobility mass spectrometry enables the discrimination of positional isomers and the detection of conformers from cyclic oligosaccharides-metals supramolecular complexes

Cyclic oligosaccharides are well known to interact with various metals, able to form supramolecular complexes with distinct sizes and shapes. However, the presence of various isomers in a sample, including positional isomers and conformers, can significantly impact molecular recognition, encapsulation ability and chemical reactivity. Therefore, it is crucial to have tools for deep samples probing and correlation establishments. The emerging ion mobility mass spectrometry (IM-MS) has the advantages to be rapid and sensitive, but is still in its infancy for the investigation of supramolecular assemblies. In the herein study, it was demonstrated that IM-MS is suitable to discriminate several isomers of cyclodextrins (CD)-metals complexes, used as cyclic oligosaccharide models. In this sense, we investigated branched 6-O-α-glucosyl- or 6-O-α-maltosyl-β-cyclodextrins (G1-β-CD and G2-β-CD) and their purely cyclic isomers: CD8 (γ-CD) and CD9 (δ-CD). The corresponding collision cross section (CCS) values were deducted for the main positive singly and doubly charged species. Experimental CCS values were matched with models obtained from molecular modelling. The high mobility resolving power and resolution enabled discrimination of positional isomers, identification of various conformers and accurate relative content estimation. These results represent a milestone in the identification of carbohydrate conformers that cannot be easily reached by other approaches.

Highly accurate and large-scale collision cross sections prediction with graph neural networks

The collision cross section (CCS) values derived from ion mobility spectrometry can be used to improve the accuracy of compound identification. Here, we have developed the Structure included graph merging with adduct method for CCS prediction (SigmaCCS) based on graph neural networks using 3D conformers as inputs. A model was trained, evaluated, and tested with >5,000 experimental CCS values. It achieved a coefficient of determination of 0.9945 and a median relative error of 1.1751% on the test set. The model-agnostic interpretation method and the visualization of the learned representations were used to investigate the chemical rationality of SigmaCCS. An in-silico database with 282 million CCS values was generated for three different adduct types of 94 million compounds. Its source code is publicly available at https://github.com/zmzhang/SigmaCCS. Altogether, SigmaCCS is an accurate, rational, and off-the-shelf method to directly predict CCS values from molecular structures.

Are the Gas-Phase Structures of Molecular Elephants Enduring or Ephemeral? Results from Time-Dependent, Tandem Ion Mobility.

The structural stability of biomolecules in the gas phase remains an important topic in mass spectrometry applications for structural biology. Here, we evaluate the kinetic stability of native-like protein ions using time-dependent, tandem ion mobility (IM). In these tandem IM experiments, ions of interest are mobility-selected after a first dimension of IM and trapped for up to ∼14 s. Time-dependent, collision cross section distributions are then determined from separations in a second dimension of IM. In these experiments, monomeric protein ions exhibited structural changes specific to both protein and charge state, whereas large protein complexes did not undergo resolvable structural changes on the timescales of these experiments. We also performed energy-dependent experiments, i.e., collision-induced unfolding, as a comparison for time-dependent experiments to understand the extent of unfolding. Collision cross section values observed in energy-dependent experiments using high collision energies were significantly larger than those observed in time-dependent experiments, indicating that the structures observed in time-dependent experiments remain kinetically trapped and retain some memory of their solution-phase structure. Although structural evolution should be considered for highly charged, monomeric protein ions, these experiments demonstrate that higher-mass protein ions can have remarkable kinetic stability in the gas phase.

Identification and characterization of quaternary ammonium compounds in Flemish indoor dust by ion-mobility high-resolution mass spectrometry

Quaternary ammonium compounds (QACs) are a class of surfactants commonly used in disinfecting and cleaning products. Their use has substantially increased during the COVID-19 pandemic leading to increasing human exposure. QACs have been associated with hypersensitivity reactions and an increased risk of asthma. This study introduces the first identification, characterization and semi-quantification of QACs in European indoor dust using ion-mobility high-resolution mass spectrometry (IM-HRMS), including the acquisition of collision cross section values (DTCCSN2) for targeted and suspect QACs. A total of 46 indoor dust samples collected in Belgium were analyzed using target and suspect screening. Targeted QACs (n = 21) were detected with detection frequencies ranging between 4.2 and 100 %, while 15 QACs showed detection frequencies > 90 %. Semi-quantified concentrations of individual QACs showed a maximum of 32.23 µg/g with a median ∑QAC concentration of 13.05 µg/g and allowed the calculation of Estimated Daily Intakes for adults and toddlers. Most abundant QACs matched the patterns reported in indoor dust collected in the United States. Suspect screening allowed the identification of 17 additional QACs. A dialkyl dimethyl ammonium compound with mixed chain lengths (C16:C18) was characterized as a major QAC homologue with a maximum semi-quantified concentration of 24.90 µg/g. The high detection frequencies and structural variabilities observed call for more European studies on potential human exposure to these compounds. For all targeted QACs, drift tube IM-HRMS derived collision cross section values (DTCCSN2) are reported. Reference DTCCSN2 values allowed the characterization of CCS-m/z trendlines for each of the targeted QAC classes. Experimental CCS-m/z ratios of suspect QACs were compared with the CCS-m/z trendlines. The alignment between the two datasets served as an additional confirmation of the assigned suspect QACs. The use of the 4bit multiplexing acquisition mode with consecutive high-resolution demultiplexing confirmed the presence of isomers for two of the suspect QACs.

Food Fingerprinting: LC-ESI-IM-QTOF-Based Identification of Blumeatin as a New Marker Metabolite for the Detection of Origanum majorana Admixtures to O. onites/vulgare.

Oregano (Origanum vulgare and O. onites) is one of the most frequently counterfeited herbs in the world and is diluted with the leaves of a wide variety of plants. In addition to olive leaves, marjoram (O. majorana) is often used for this purpose in order to achieve a higher profit. However, apart from arbutin, no marker metabolites are known to reliably detect marjoram admixtures in oregano batches at low concentrations. In addition, arbutin is relatively widespread in the plant kingdom, which is why it is of great relevance to look for further marker metabolites in order to secure the analysis accordingly. Therefore, the aim of the present study was to use a metabolomics-based approach to identify additional marker metabolites with the aid of an ion mobility mass spectrometry instrument. The focus of the analysis was on the detection of non-polar metabolites, as this study was preceded by nuclear magnetic resonance spectroscopic investigations of the same samples based mainly on the detection of polar analytes. Using the MS-based approach, numerous marjoram specific features could be detected in admixtures of marjoram >10% in oregano. However, only one feature was detectable in admixtures of >5% marjoram. This feature was identified as blumeatin, which belongs to the class of flavonoid compounds. Initially, blumeatin was identified based on MS/MS spectra and collision cross section values using a database search. In addition, the identification of blumeatin was confirmed by a reference standard. Moreover, dried leaves of olive, myrtle, thyme, sage and peppermint, which are also known to be used to adulterate oregano, were measured. Blumeatin could not be detected in these plants, so this substance can be considered as an excellent marker compound for the detection of marjoram admixtures.

Noncovalent Host-Guest Complexes of Artemisinin with α-, β-, 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, βCD, 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:βCD 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:βCD + 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:βCD + Li]+ ion correlated with predicted CCS values from the low-energy theoretical structures of the drug incorporated within the βCD 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.

A Flexible, Modular Platform for Multidimensional Ion Mobility of Native-like Ions.

Native ion mobility (IM) mass spectrometry (MS) is used to probe the size, shape, and assembly of biomolecular complexes. IM-IM-MS can increase the amount of information available in structural studies by isolating subpopulations of structures for further analysis. Previously, IM-IM-MS has been implemented using the Structures for Lossless Ion Manipulations (SLIM) architecture to probe the structural stability of gas-phase protein ions. Here, a new multidimensional IM instrument constructed from SLIM devices is characterized using multiple operational modes. In this new design, modular devices are used to perform all ion manipulations, including initial accumulation, injection, separation, selection, and trapping. Using single-dimension IM, collision cross section (Ω) values are determined for a set of native-like ions. These Ω values are within 3% of those reported previously based on measurements using RF-confining drift cells. Tandem IM experiments are performed on a sample of ubiquitin ions that contains both compact and partially unfolded structures, demonstrating that this platform can isolate subpopulations of structures. Finally, additional modes of analysis, including multiplexed IM and inverse IM, are demonstrated using this platform. The ability of this platform to quickly switch between different modes of IM analysis makes it a highly flexible tool for studying protein structures and dynamics.

General Method to Obtain Collision Cross-Section Values in Multipass High-Resolution Cyclic Ion Mobility Separations.

In recent years, ion mobility spectrometry-mass spectrometry (IMS-MS) has advanced the field of omics-based research, especially with the development of high-resolution platforms; however, these separations have generally been qualitative in nature. The rotationally averaged ion neutral collision cross section (CCS) is one of the only quantitative metrics available for aiding in characterizing biomolecules in IMS-MS. However, determining the CCS of an ion for multipass IMS systems, such as in cyclic ion mobility-mass spectrometry (cIMS-MS) and structures for lossless ion manipulations, has been challenging due to the lack of methods available for calculating CCS when more than a single pass is required for separation as well as the laborious nature of requiring calibrants and unknown compounds to be subjected to identical number of passes, which may not be possible in certain instances because of peak splitting, high levels of diffusion, etc. Herein, we present a general method that uses average ion velocities for calculating CCS values in cIMS-MS-based separations. Initially, we developed calibration curves using common CCS calibrants [i.e., tetra-alkylammonium salts, polyalanine, and hexakis(fluoroalkoxy)phosphazines] at different traveling wave (TW) conditions and the calculated cIMS CCS values were within ∼1% error or less compared to previously established drift tube IMS CCS measurements. Since it has been established that glycans can split into their α/β anomers, we utilized this method for two glycan species, 2α-mannobiose and melibiose. Both glycans were analyzed at the same TW conditions as the calibrants, and we observed anomer splitting at pathlengths of 20 m for 2α-mannobiose and 40 m for melibiose and thus assigned two unique CCS values for each glycan, which is the first time this has ever been done. We have demonstrated that the use of average ion velocities is a robust approach for obtaining CCS values with good agreement to CCS measurements from the previous literature and anticipate that this methodology can be applied to any IMS-MS platform that utilizes multipass separations. Our future work aims to incorporate this methodology for the development of a high-resolution CCS database to aid in the characterization of human milk oligosaccharides.

Effects of charge on protein ion structure: Lessons from cation-to-anion, proton-transfer reactions.

Collision cross-section values, which can be determined using ion mobility experiments, are sensitive to the structures of protein ions and useful for applications to structural biology and biophysics. Protein ions with different charge states can exhibit very different collision cross-section values, but a comprehensive understanding of this relationship remains elusive. Here, we review cation-to-anion, proton-transfer reactions (CAPTR), a method for generating a series of charge-reduced protein cations by reacting quadrupole-selected cations with even-electron monoanions. The resulting CAPTR products are analyzed using a combination of ion mobility, mass spectrometry, and collisional activation. We compare CAPTR to other charge-manipulation strategies and review the results of various CAPTR-based experiments, exploring their contribution to a deeper understanding of the relationship between protein ion structure and charge state.