Collision Cross Section Measurements Research Articles

Exploring the Conformational Landscape of Poly(l-lysine) Dendrimers Using Ion Mobility Mass Spectrometry.

Ion mobility mass spectrometry (IM-MS) measures the mass, size, and shape of ions in the same experiment, and structural information is provided via collision cross-section (CCS) values. The majority of commercially available IM-MS instrumentation relies on the use of CCS calibrants, and here, we present data from a family of poly(l-lysine) dendrimers and explore their suitability for this purpose. In order to test these compounds, we employed three different IM-MS platforms (Agilent 6560 IM-QToF, Waters Synapt G2, and a home-built variable temperature drift tube IM-MS) and used them to investigate six different generations of dendrimers in two buffer gases (helium and nitrogen). Each molecule gives a highly discrete CCS distribution suggestive of single conformers for each m/z value. The DTCCSN2 values of this series of molecules (molecular weight: 330-16,214 Da) range from 182 to 2941 Å2, which spans the CCS range that would be found by many synthetic molecules including supramolecular compounds and many biopolymers. The CCS values for each charge state were highly reproducible in day-to-day analysis on each instrument, although we found small variations in the absolute CCS values between instruments. The rigidity of each dendrimer was probed using collisionally activated and high-temperature IM-MS experiments, where no evidence for a significant CCS change ensued. Taken together, this data indicates that these polymers are candidates for CCS calibration and could also help to reconcile differences found in CCS measurements on different instrument geometries.

Ion-molecule collision cross-section calculations using trajectory parallelization in distributed systems

Ion Mobility coupled with Mass Spectrometry (IM-MS) stands as a strong analytical method for structurally characterizing complex molecules. In IM-MS, the sample under investigation is ionized and propelled by an electric field into a drift tube, which collides against a buffer gas. The separation of the ion gas phase is then measured through the differences in their rotationally averaged Collision Cross-Section (CCS) values. The effectiveness of the measured Collision Cross-Section (CCS) for structural characterization critically depends on the validation against theoretical calculations. This validation process relies on intensive molecular mechanics simulations, which can be computationally demanding, especially for large systems such as molecular assemblies and viruses. Therefore, reliable and fast CCS calculations are needed to help interpret IM-MS experimental data. This work presents the MassCCS software, which considerably increases the CCS simulation performance by implementing a linked-cell-based algorithm, incorporating High-Performance Computing (HPC) techniques. We performed extensive tests regarding the system size, shape, and number of CPU cores. Experimental results reveal speedups up to 3 orders of magnitude faster than Collision Simulator for Ion Mobility Spectrometry (CoSIMS) and High-Performance Collision Cross Section (HPCCS), optimized solutions for CCS simulations, for a single node execution. In addition, we extended MassCCS at the inter-node level by employing OpenMP Cluster (OMPC). OMPC is an innovative programming model designed for the development of HPC applications. It streamlines the development process and simplifies software maintenance using only OpenMP directives. Notably, OMPC delivers a performance level comparable to a pure MPI implementation. This enhancement enabled expensive CCS calculations using nitrogen buffer gas for large systems such as human adenovirus with ∼11 million atoms in just ∼4 min, making MassCCS the most performant software nowadays, to the best of our knowledge. MassCCS is available as free software for Academic use at https://github.com/cces-cepid/massccs.

Separation and Characterization of Synthetic Cannabinoid Metabolite Isomers Using SLIM High-Resolution Ion Mobility-Tandem Mass Spectrometry (HRIM-MS/MS).

Synthetic cannabinoids, a subclass of new psychoactive substances (NPS), are laboratory-made substances that are chemically similar to those found naturally in the cannabis plant. Many of these substances are illicitly manufactured and have been associated with severe health problems, prompting a need to develop analytical methods capable of characterizing both known and previously undetected compounds. This work focuses on a novel Structures for Lossless Ion Manipulations (SLIM) IM-MS approach to the differentiation and structural characterization of synthetic cannabinoid metabolites, specifically MDA-19/BUTINACA, JWH-018, and JWH-250 isomer groups. These different compound classes are structurally very similar, differing only in the position of one or a few functional groups; this yielded similarity in measured collision cross section (CCS) values. However, the high resolution of SLIM IM provided adequate separation of many of these isomers, such as sodiated JWH-250 metabolites N-4-OH, N-5-OH, and 5-OH, which displayed CCS of 187.5, 182.5, and 202.3 Å2, respectively. In challenging cases where baseline separation was precluded due to nearly identical CCS, such as for JWH-018 isomers, simple derivatization by dansyl chloride selectively reacted with the 6-OH compound to provide differentiation of all isomers using a combination of CCS and m/z. Finally, the opportunity to use this method for structural elucidation of unknowns was demonstrated by using SLIM IM mobility-aligned MS/MS fragmentation. Different MDA-19/BUTINACA isomers were first mobility separated and could then be individually activated, yielding unique fragments for both targeted identification and structural determination. Overall, the described SLIM IM-MS/MS workflow provides significant potential as a rapid screening tool for the characterization of emerging NPS such as synthetic cannabinoids and their metabolites.

UV-A-Induced Photoisomerization and Photodimerization of Curcumin: An Ion Mobility Mass Spectrometry Study.

Curcumin, the bioactive compound present in spice plant turmeric, has been shown to exhibit selective phototoxic activities toward mammalian cancer cells, and it is being used extensively as a photosensitizer (PS) in photodynamic therapies (PDT). However, so far, the fate of curcumin toward photochemical transformations is not well understood. Here we report our findings of a number of novel photochemical reaction channels of curcumin in water-methanol mixture, like photoisomerization, photodimerization, and photooxidation (H2-loss). The reaction was performed by irradiating the curcumin solution with ultraviolet (UV) light of wavelength 350 nm, which is abundant in the earth's troposphere. Product identification and structure elucidation are done by employing an integrated method of drift tube ion mobility mass spectrometry (DTIMS) in combination with high-performance liquid chromatography (HPLC) and collision-induced dissociation (CID) of the mass-selected molecular ions. Two photoisomers of curcumin produced as a result of trans-cis configurational changes about C═C double bonds in the excited state have been identified, and it has been shown that they could serve as the precursors for formation of isomeric dimers via [2 + 2] cycloaddition and H2-loss products. Comparisons of the experimentally measured collision cross-section (CCS) values of the reactant and product ions obtained by the DTIMS method with those predicted by the electronic structure theory are found to be very effective for the discrimination of the produced photoisomers. The observed photochemical reaction channels are potentially significant toward uses of curcumin as a photosensitizer in photodynamic therapy.

Application of Ion Mobility Spectrometry and the Derived Collision Cross Section in the Analysis of Environmental Organic Micropollutants.

Ion mobility spectrometry (IMS) is a rapid gas-phase separation technique, which can distinguish ions on the basis of their size, shape, and charge. The IMS-derived collision cross section (CCS) can serve as additional identification evidence for the screening of environmental organic micropollutants (OMPs). In this work, we summarize the published experimental CCS values of environmental OMPs, introduce the current CCS prediction tools, summarize the use of IMS and CCS in the analysis of environmental OMPs, and finally discussed the benefits of IMS and CCS in environmental analysis. An up-to-date CCS compendium for environmental contaminants was produced by combining CCS databases and data sets of particular types of environmental OMPs, including pesticides, drugs, mycotoxins, steroids, plastic additives, per- and polyfluoroalkyl substances (PFAS), polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and polybrominated diphenyl ethers (PBDEs), as well as their well-known transformation products. A total of 9407 experimental CCS values from 4170 OMPs were retrieved from 23 publications, which contain both drift tube CCS in nitrogen (DTCCSN2) and traveling wave CCS in nitrogen (TWCCSN2). A selection of publicly accessible and in-house CCS prediction tools were also investigated; the chemical space covered by the training set and the quality of CCS measurements seem to be vital factors affecting the CCS prediction accuracy. Then, the applications of IMS and the derived CCS in the screening of various OMPs were summarized, and the benefits of IMS and CCS, including increased peak capacity, the elimination of interfering ions, the separation of isomers, and the reduction of false positives and false negatives, were discussed in detail. With the improvement of the resolving power of IMS and enhancements of experimental CCS databases, the practicability of IMS in the analysis of environmental OMPs will continue to improve.

Determining Collisional Cross Sections from Ion Decay with Individual Ion Mass Spectrometry.

Collision cross section (CCS) measurements determined by ion mobility spectrometry (IMS) provide useful information about gas-phase protein structure that is complementary to mass analysis. Methods for determining CCS without a dedicated IMS system have been developed for Fourier transform mass spectrometry (FT-MS) platforms by measuring the signal decay during detection. Individual ion mass spectrometry (I2MS) provides charge detection and measures ion lifetimes across the length of an FT-MS detection event. By tracking lifetimes for entire ion populations, we demonstrate simultaneous determination of charge, mass, and CCS for proteins and complexes ranging from ∼8 to ∼232 kDa.

Improved analysis of derivatized steroid hormone isomers using ion mobility-mass spectrometry (IM-MS).

Over the last decade, applications of ion mobility-mass spectrometry (IM-MS) have exploded due primarily to the widespread commercialization of robust instrumentation from several vendors. Unfortunately, the modest resolving power of many of these platforms (~40-60) has precluded routine separation of constitutional and stereochemical isomers. While instrumentation advances have pushed resolving power to >150 in some cases, chemical approaches offer an alternative for increasing resolution with existing IM-MS instrumentation. Herein we explore the utility of two reactions, derivatization by Girard's reagents and 1,1-carbonyldiimidazole (CDI), for improving IM separation of steroid hormone isomers. These reactions are fast (≤30min), simple (requiring only basic lab equipment/expertise), and low-cost. Notably, these reactions are structurally selective in that they target carbonyl and hydroxyl groups, respectively, which are found in all naturally occurring steroids. Many steroid hormone isomers differ only in the number, location, and/or stereochemistry of these functional groups, allowing these reactions to "amplify" subtle structural differences and improve IM resolution. Our results show that resolution was significantly improved amongst CDI-derivatized isomer groups of hydroxyprogesterone (two-peak resolution of Rpp = 1.10 between 21-OHP and 11B-OHP), deoxycortisone (Rpp = 1.47 between 11-DHC and 21-DOC), and desoximetasone (Rpp = 1.98 between desoximetasone and fluocortolone). Moreover, characteristic collision cross section (DTCCSN2) measurements can be used to increase confidence in the identification of these compounds in complex biological mixtures. To demonstrate the feasibility of analyzing the derivatized steroids in complex biological matrixes, the reactions were performed following steroid extraction from urine and yielded similar results. Additionally, we applied a software-based approach (high-resolution demultiplexing) that further improved theresolving power (>150). Overall, our results suggest that targeted derivatization reactions coupled with IM-MS can significantly improve the resolution of challenging isomer groups, allowing for more accurate and efficient analysis of complex mixtures.

Chemical Exposure Highlighted without Any A Priori Information in an Epidemiological Study by Metabolomic FT-ICR-MS Fingerprinting at High Throughput and High Resolution.

Epidemiological studies aim to assess associations between diseases and risk factors. Such investigations involve a large sample size and require powerful analytical methods to measure the effects of risk factors, resulting in a long analysis time. In this study, chemical exposure markers were detected as the main variables strongly affecting two components coming from a principal component analysis (PCA) exploration of the metabolomic data generated from urinary samples collected on a cohort of about 500 individuals using direct introduction coupled with a Fourier-transform ion cyclotron resonance instrument. The assignment of their chemical identity was first achieved based on their isotopic fine structures detected at very high resolution (Rp > 900,000). Their identification as dimethylbiguanide and sotalol was obtained at level 1, thanks to the available authentic chemical standards, tandem mass spectrometry (MS/MS) experiments, and collision cross section measurements. Epidemiological data confirmed that the subjects discriminated by PCA had declared to be prescribed these drugs for either type II diabetes or cardiac arrhythmia. Concentrations of these drugs in urine samples of interest were also estimated by rapid quantification using an external standard calibration method, direct introduction, and MS/MS experiments. Regression analyses showed a good correlation between the estimated drug concentrations and the scores of individuals distributed on these specific PCs. The detection of these chemical exposure markers proved the potential of the proposed high-throughput approach without any prior drug exposure knowledge as a powerful emerging tool for rapid and large-scale phenotyping of subjects enrolled in epidemiological studies to rapidly characterize the chemical exposome and adherence to medical prescriptions.

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.

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.

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–.

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.

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.

Expanding Orbitrap Collision Cross-Section Measurements to Native Protein Applications Through Kinetic Energy and Signal Decay Analysis.

The measurement of collision cross sections (CCS, σ) offers supplemental information about sizes and conformations of ions beyond mass analysis alone. We have previously shown that CCSs can be determined directly from the time-domain transient decay of ions in an Orbitrap mass analyzer as ions oscillate around the central electrode and collide with neutral gas, thus removing them from the ion packet. Herein, we develop the modified hard collision model, thus deviating from the prior FT-MS hard sphere model, to determine CCSs as a function of center-of-mass collision energy in the Orbitrap analyzer. With this model, we aim to increase the upper mass limit of CCS measurement for native-like proteins, characterized by low charge states and presumed to be in more compact conformations. We also combine CCS measurements with collision induced unfolding and tandem mass spectrometry experiments to monitor protein unfolding and disassembly of protein complexes and measure CCSs of ejected monomers from protein complexes.

Hydrogen-Deuterium-Exchange-Based Mass Distribution Shifts in High-Resolution Cyclic Ion Mobility Separations.

The mass distribution of ions influences separations in ion mobility spectrometry-mass spectrometry (IMS-MS). Herein, we introduce a method to induce mass distribution shifts for various analytes using hydrogen-deuterium exchange (HDX) immediately prior to ionization using a dual syringe approach. By replacing labile hydrogens on analytes with deuteriums, we were able to differentiate isomers using separations of isotopologues. For each analyte studied, every possible level of deuteration (from undeuterated to fully deuterated) was generated and then separated using cyclic ion mobility spectrometry-mass spectrometry (cIMS-MS). The information gained from such separations (relative arrival times; tRel. values) was found to be orthogonal to conventional IMS-MS separations. Additionally, the observed shifts were linearly additive with increasing deuteration, suggesting that this methodology could be extended to analytes with a larger number of labile hydrogens. For one isomer pair, as few as two deuteriums were able to produce a large enough mass distribution shift to differentiate isomers. In another experiment, we found that the mass distribution shift was large enough to overcome the reduced mass contribution, resulting in a "flipped" arrival time where the heavier deuterated isotopologue arrived before the lighter one. In this work, we present a proof-of-concept demonstration that mass-distribution-based shifts, tRel. values, could potentially act as an added dimension to characterize molecules in IMS-MS. We anticipate, along with future work in this area, that mass-distribution-based shifts could enable the identification of unknown molecules through a database-driven approach in an analogous fashion to collision cross section (CCS) measurements.

Guidelines and considerations for building multidimensional libraries for untargeted MS-based metabolomics.

Feature annotation is crucial in untargeted metabolomics but remains a major challenge. The large pool of metabolites collected under various instrumental conditions is underrepresented in publicly available databases. Retention time (RT) and collision cross section (CCS) measurements from liquid chromatography ion mobility high-resolution mass spectrometers can be employed in addition to MS/MS spectra to improve the confidence of metabolite annotation. Recent advancements in machine learning focus on improving the accuracy of predictions for CCS and RT values. Therefore, high-quality experimental data are crucial to be used either as training datasets or as a reference for high-confidence matching. This manuscript provides an easy-to-use workflow for the creation of an in-house metabolite library, offers an overview of alternative solutions, and discusses the challenges and advantages of using open-source software. A total of 100 metabolite standards from various classes were analyzed and subjected to the described workflow for library generation. The outcome was an open-access available NIST format metabolite library (.msp) with multidimensional information. The library was used to evaluate CCS prediction tools, MS/MS spectra heterogeneities (e.g., multiple adducts, in-source fragmentation, radical fragment ions using collision-induced dissociation), and the reporting of RT.

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

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. 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. 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.

Advancing Orbitrap Measurements of Collision Cross Sections to Multiple Species for Broad Applications.

Measurement of collision cross section (CCS), a parameter reflecting an ion's size and shape, alongside high-resolution mass analysis extends the depth of molecular analysis by providing structural information beyond molecular mass alone. Although these measurements are most commonly undertaken using a dedicated ion mobility cell coupled to a mass spectrometer, alternative methods have emerged to extract CCSs directly by analysis of the decay rates of either time-domain transient signals or the FWHM of frequency domain peaks in FT mass analyzers. This information is also accessible from FTMS mass spectra obtained in commonly used workflows directly without the explicit access to transient or complex Fourier spectra. Previously, these experiments required isolation of individual charge states of ions prior to CCS analysis, limiting throughput. Here we advance Orbitrap CCS measurements to more users and applications by determining CCSs from commonly available mass spectra files as well as estimating CCS for multiple charge states simultaneously and showcase these methods by the measurement of CCSs of fragment ions produced from collisional activation of proteins.

Collision Cross Section Prediction with Molecular Fingerprint Using Machine Learning.

High-resolution mass spectrometry is a promising technique in non-target screening (NTS) to monitor contaminants of emerging concern in complex samples. Current chemical identification strategies in NTS experiments typically depend on spectral libraries, chemical databases, and in silico fragmentation tools. However, small molecule identification remains challenging due to the lack of orthogonal sources of information (e.g., unique fragments). Collision cross section (CCS) values measured by ion mobility spectrometry (IMS) offer an additional identification dimension to increase the confidence level. Thanks to the advances in analytical instrumentation, an increasing application of IMS hybrid with high-resolution mass spectrometry (HRMS) in NTS has been reported in the recent decades. Several CCS prediction tools have been developed. However, limited CCS prediction methods were based on a large scale of chemical classes and cross-platform CCS measurements. We successfully developed two prediction models using a random forest machine learning algorithm. One of the approaches was based on chemicals’ super classes; the other model was direct CCS prediction using molecular fingerprint. Over 13,324 CCS values from six different laboratories and PubChem using a variety of ion-mobility separation techniques were used for training and testing the models. The test accuracy for all the prediction models was over 0.85, and the median of relative residual was around 2.2%. The models can be applied to different IMS platforms to eliminate false positives in small molecule identification.

Paper Spray Ionization Ion Mobility Mass Spectrometry of Sebum Classifies Biomarker Classes for the Diagnosis of Parkinson's Disease.

Parkinson’s disease (PD) is the second most common neurodegenerative disorder, and identification of robust biomarkers to complement clinical diagnosis will accelerate treatment options. Here, we demonstrate the use of direct infusion of sebum from skin swabs using paper spray ionization coupled with ion mobility mass spectrometry (PS-IM-MS) to determine the regulation of molecular classes of lipids in sebum that are diagnostic of PD. A PS-IM-MS method for sebum samples that takes 3 min per swab was developed and optimized. The method was applied to skin swabs collected from 150 people and elucidates ∼4200 features from each subject, which were independently analyzed. The data included high molecular weight lipids (>600 Da) that differ significantly in the sebum of people with PD. Putative metabolite annotations of several lipid classes, predominantly triglycerides and larger acyl glycerides, were obtained using accurate mass, tandem mass spectrometry, and collision cross section measurements.