An Interlaboratory Evaluation of Drift Tube Ion Mobility-Mass Spectrometry Collision Cross Section Measurements

Opening new paths for biological applications of ion mobility - mass spectrometry using Structures for Lossless Ion Manipulations

Ion mobility separations coupled to mass spectrometry (IM-MS) have received much attention for their ability to provide complementary structural information to solution-phase-based separations, as well as to aid in the identification of unknown compounds. While IM-MS is an increasingly powerful analytical technique, significant bottlenecks related to the resolution of measurements have kept it from becoming broadly applied for biological analyses. Presently, IM-MS-based measurements also remain limited in terms of their sensitivity as compared to state of the art MS-based approaches alone. Structures for Lossless Ion Manipulations (SLIM)-based IM separations provide a basis for overcoming these bottlenecks, addressing issues associated with resolution and sensitivity in the omics, and potentially opening the door to much broader application.

Ion Mobility Spectrometry and the Omics: Distinguishing Isomers, Molecular Classes and Contaminant Ions in Complex Samples

Ion mobility spectrometry (IMS) is a widely used analytical technique providing rapid gas phase separations. IMS alone is useful, but its coupling with mass spectrometry (IMS-MS) and various front-end separation techniques has greatly increased the molecular information achievable from different omic analyses. IMS-MS analyses are specifically gaining attention for improving metabolomic, lipidomic, glycomic, proteomic and exposomic analyses by increasing measurement sensitivity (e.g. S/N ratio), reducing the detection limit, and amplifying peak capacity. Numerous studies including national security-related analyses, disease screenings and environmental evaluations are illustrating that IMS-MS is able to extract information not possible with MS alone. Furthermore, IMS-MS has shown great utility in salvaging molecular information for low abundance molecules of interest when high concentration contaminant ions are present in the sample by reducing detector suppression. This review highlights how IMS-MS is currently being used in omic analyses to distinguish structurally similar molecules, isomers, molecular classes and contaminant ions.

Predicting Ion Mobility Collision Cross-Sections Using a Deep Neural Network: DeepCCS

Untargeted metabolomic measurements using mass spectrometry are a powerful tool for uncovering new small molecules with environmental and biological importance. The small molecule identification step, however, still remains an enormous challenge due to fragmentation difficulties or unspecific fragment ion information. Current methods to address this challenge are often dependent on databases or require the use of nuclear magnetic resonance (NMR), which have their own difficulties. The use of the gas-phase collision cross section (CCS) values obtained from ion mobility spectrometry (IMS) measurements were recently demonstrated to reduce the number of false positive metabolite identifications. While promising, the amount of empirical CCS information currently available is limited, thus predictive CCS methods need to be developed. In this article, we expand upon current experimental IMS capabilities by predicting the CCS values using a deep learning algorithm. We successfully developed and trained a prediction model for CCS values requiring only information about a compound's SMILES notation and ion type. The use of data from five different laboratories using different instruments allowed the algorithm to be trained and tested on more than 2400 molecules. The resulting CCS predictions were found to achieve a coefficient of determination of 0.97 and median relative error of 2.7% for a wide range of molecules. Furthermore, the method requires only a small amount of processing power to predict CCS values. Considering the performance, time, and resources necessary, as well as its applicability to a variety of molecules, this model was able to outperform all currently available CCS prediction algorithms.

Mobilising ion mobility mass spectrometry for metabolomics

Chromatography-based mass spectrometry approaches (xC-MS) are commonly used in untargeted metabolomics, providing retention time, m/z values and metabolite-specific fragments, all of which are used to identify and validate an unknown analyte. Ion mobility-mass spectrometry (IM-MS) is emerging as an enhancement to classic xC-MS strategies, by offering additional ion separation as well as collision cross section (CCS) determination. In order to apply such an approach to a metabolomics workflow, verified data from metabolite standards is necessary. In this work we present experimental DTCCSN2 values for a range of metabolites in positive and negative ionisation modes using drift tube-ion mobility-mass spectrometry (DT-IM-MS) with nitrogen as the buffer gas. The value of DTCCSN2 measurements for application in metabolite identification relies on a robust technique that acquires measurements of high reproducibility. We report that the CCS values found for 86% of metabolites measured in replicate have a relative standard deviation lower than 0.2%. Examples of metabolites with near identical mass are demonstrated to be separated by ion mobility with over 4% difference in DTCCSN2 values. We conclude that the integration of ion mobility into current LC-MS workflows can aid in small molecule identification for both targeted and untargeted metabolite screening.

ISiCLE: A Quantum Chemistry Pipeline for Establishing in Silico Collision Cross Section Libraries

High-throughput, comprehensive, and confident identifications of metabolites and other chemicals in biological and environmental samples will revolutionize our understanding of the role these chemically diverse molecules play in biological systems. Despite recent technological advances, metabolomics studies still result in the detection of a disproportionate number of features that cannot be confidently assigned to a chemical structure. This inadequacy is driven by the single most significant limitation in metabolomics, the reliance on reference libraries constructed by analysis of authentic reference materials with limited commercial availability. To this end, we have developed the in silico chemical library engine (ISiCLE), a high-performance computing-friendly cheminformatics workflow for generating libraries of chemical properties. In the instantiation described here, we predict probable three-dimensional molecular conformers (i.e., conformational isomers) using chemical identifiers as input, from which collision cross sections (CCS) are derived. The approach employs first-principles simulation, distinguished by the use of molecular dynamics, quantum chemistry, and ion mobility calculations, to generate structures and chemical property libraries, all without training data. Importantly, optimization of ISiCLE included a refactoring of the popular MOBCAL code for trajectory-based mobility calculations, improving its computational efficiency by over 2 orders of magnitude. Calculated CCS values were validated against 1983 experimentally measured CCS values and compared to previously reported CCS calculation approaches. Average calculated CCS error for the validation set is 3.2% using standard parameters, outperforming other density functional theory (DFT)-based methods and machine learning methods (e.g., MetCCS). An online database is introduced for sharing both calculated and experimental CCS values ( metabolomics.pnnl.gov ), initially including a CCS library with over 1 million entries. Finally, three successful applications of molecule characterization using calculated CCS are described, including providing evidence for the presence of an environmental degradation product, the separation of molecular isomers, and an initial characterization of complex blinded mixtures of exposure chemicals. This work represents a method to address the limitations of small molecule identification and offers an alternative to generating chemical identification libraries experimentally by analyzing authentic reference materials. All code is available at github.com/pnnl .

Potential of ion mobility-mass spectrometry for both targeted and non-targeted analysis of phase II steroid metabolites in urine

In recent years, the commercialization of hybrid ion mobility-mass spectrometers and their integration in traditional LC-MS workflows provide new opportunities to extend the current boundaries of targeted and non-targeted analyses. When coupled to LC-MS, ion mobility spectrometry (IMS) provides a novel characterization parameter, the so-called averaged collision cross section (CCS, Ω), as well as improves method selectivity and sensitivity by the separation of isobaric and isomeric molecules and the isolation of the analytes of interest from background noise. In this work, we have explored the potential and advantages of this technology for carrying out the determination of phase II steroid metabolites (i.e. androgen and estrogen conjugates, including glucuronide and sulfate compounds; n = 25) in urine samples. These molecules have been selected based on their relevance in the fields of chemical food safety and doping control, as well as in metabolomics studies. The influence of urine matrix on the CCS of steroid metabolites was evaluated in order to give more confidence to current CCS databases and support its use as complementary information to retention time (Rt) and mass spectra for compound identification. Samples were only diluted 10-fold with aqueous formic acid (0.1%, v/v) prior analysis. Only an almost insignificant effect of adult bovine urine matrix on the CCS of certain steroid metabolites was observed in comparison with calve urine matrix, which is a less complex sample. In addition, high accuracy was achieved for CCS measurements carried out over four months (ΔCCS < 1.3% for 99.8% of CCS measurements; n = 1806). Interestingly, it has been observed that signal-to-noise (S/N) ratio could be improved at least 2 or 7-fold when IMS is combined with LC-MS. In addition to the separation of isomeric steroid pairs (i.e. etiocholanolone glucuronide and epiandrosterone glucuronide, as well as 19-noretiocholanolone glucuronide and 19-norandrosterone glucuronide), steroid-based ions were also separated in the IMS dimension from co-eluting matrix compounds that presented similar mass-to-charge ratio (m/z). Finally, based on CCS measurements and as a proof of concept, 17α-boldenone glucuronide has been identified as one of the main metabolites resulted from boldione administration to calves.

Lipidomic consequences of phospholipid synthesis defects in Escherichia coli revealed by HILIC-ion mobility-mass spectrometry

Our understanding of phospholipid biosynthesis in Gram-positive and Gram-negative bacteria is derived from the prototypical Gram-negative organism Escherichia coli. The inner and outer membranes of E. coli are largely composed of phosphatidylethanolamine (PE), minor amounts of phosphatidylglycerol (PG) and cardiolipin (CL). We report here the utility of hydrophilic interaction liquid chromatography (HILIC) paired with ion mobility-mass spectrometry (IM-MS) for the comprehensive analysis of the E. coli lipidome. Using strains with chromosomal deletions in the PG and CL synthesis genes pgsA and clsABC, respectively, we show that defective phospholipid biosynthesis in E. coli results in fatty-acid specific changes in select lipid classes and the presence of the minor triacylated phospholipids, acylphosphatidyl glycerol (acylPG) and N-acylphosphatidylethanolamine (N-acylPE). Notably, acylPGs were accumulated in the clsABC-KO strain, but were absent in other mutant strains. The separation of 1-lyso and 2-lyso-phosphatidylethanolamines (lysoPEs) is demonstrated in both the HILIC and IM dimensions. Using our previously validated calibration method, collision cross section values of nearly 200 phospholipids found in E. coli were determined on a traveling wave IM-MS platform, including newly reported values for cardiolipins, positional isomers of lysoPEs, acylPGs and N-acylPEs.

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.

Conditions for Analysis of Native Protein Structures Using Uniform Field Drift Tube Ion Mobility Mass Spectrometry and Characterization of Stable Calibrants for TWIM-MS

Determination of collisional cross sections (CCS) by travelling wave ion mobility mass spectrometry (TWIM-MS) requires calibration against standards for which the CCS has been measured previously by drift tube ion mobility mass spectrometry (DTIM-MS). The different extents of collisional activation in TWIM-MS and DTIM-MS can give rise to discrepancies in the CCS of calibrants across the two platforms. Furthermore, the conditions required to ionize and transmit large, folded proteins and assemblies may variably affect the structure of the calibrants and analytes. Stable hetero-oligomeric phospholipase A₂ (PDx) and its subunits were characterized as calibrants for TWIM-MS. Conditions for acquisition of native-like TWIM (Synapt G1 HDMS) and DTIM (Agilent 6560 IM-Q-TOF) mass spectra were optimized to ensure the spectra exhibited similar charge state distributions. CCS measurements (DTIM-MS) for ubiquitin, cytochrome c, holo-myoglobin, serum albumin and glutamate dehydrogenase were in good agreement with other recent results determined using this and other DTIM-MS instruments. PDx and its β and γ subunits were stable across a wide range of cone and trap voltages in TWIM-MS and were stable in the presence of organic solvents. The CCS of PDx and its subunits were determined by DTIM-MS and were used as calibrants in determination of CCS of native-like cytochrome c, holo-myoglobin, carbonic anhydrase, serum albumin and haemoglobin in TWIM-MS. The CCS values were in good agreement with those measured by DTIM-MS where available. These experiments demonstrate conditions for analysis of native-like proteins using a commercially available DTIM-MS instrument, characterize robust calibrants for TWIM-MS, and present CCS values determined by DTIM-MS and TWIM-MS for native proteins to add to the current literature database. Graphical Abstract ᅟ.

New mass spectrometry technologies contributing towards comprehensive and high throughput omics analyses of single cells

Mass-spectrometry based omics technologies - namely proteomics, metabolomics and lipidomics - have enabled the molecular level systems biology investigation of organisms in unprecedented detail. There has been increasing interest for gaining a thorough, functional understanding of the biological consequences associated with cellular heterogeneity in a wide variety of research areas such as developmental biology, precision medicine, cancer research and microbiome science. Recent advances in mass spectrometry (MS) instrumentation and sample handling strategies are quickly making comprehensive omics analyses of single cells feasible, but key breakthroughs are still required to push through remaining bottlenecks. In this review, we discuss the challenges faced by single cell MS-based omics analyses and highlight recent technological advances that collectively can contribute to comprehensive and high throughput omics analyses in single cells. We provide a vision of the potential of integrating pioneering technologies such as Structures for Lossless Ion Manipulations (SLIM) for improved sensitivity and resolution, novel peptide identification tactics and standards free metabolomics approaches for future applications in single cell analysis.

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.

Separation of isomeric glycans by ion mobility spectrometry – the impact of fluorescent labelling

Bloodgroup oligosaccharides have been derivatized with labels common in HPLC and evaluated regarding their ion mobility behaviour.

Probing the structure of giant fullerenes by high resolution trapped ion mobility spectrometry

We present high-resolution trapped ion mobility spectrometry (TIMS) measurements for fullerene ions in molecular nitrogen.

Ion Mobility-Mass Spectrometry Reveals Details of Formation and Structure for GAA·TCC DNA and RNA Triplexes

DNA and RNA triplexes are thought to play key roles in a range of cellular processes such as gene regulation and epigenetic remodeling and have been implicated in human disease such as Friedreich's ataxia. In this work, ion mobility-mass spectrometry (IM-MS) is used with supporting UV-visible spectroscopy to investigate DNA triplex assembly, considering stability and specificity, for GAA·TTC oligonucleotide sequences of relevance to Friedreich's ataxia. We demonstrate that, contrary to other examples, parallel triplex structures are favored for these sequences and that stability is enhanced by increasing oligonucleotide length and decreasing pH. We also provide evidence for the self-association of these triplexes, consistent with a proposed model of higher order DNA structures formed in Friedreich's ataxia. By comparing triplex assembly using DNA- and RNA-based triplex-forming oligonucleotides, we demonstrate more favorable formation of RNA triplexes, suggesting a role for their formation in vivo. Finally, we interrogate the binding properties of netropsin, a known polyamide triplex destabilizer, with RNA-DNA hybrid triplexes, where preference for duplex binding is evident. We show that IM-MS is able to report on relevant solution-phase populations of triplex DNA structures, thereby further highlighting the utility of this technology in structural biology. Our data therefore provides new insights into the possible DNA and RNA assemblies that may form as a result of GAA triplet repeats. Graphical Abstract ᅟ.

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.

Online Parallel Accumulation-Serial Fragmentation (PASEF) with a Novel Trapped Ion Mobility Mass Spectrometer

In bottom-up proteomics, peptides are separated by liquid chromatography with elution peak widths in the range of seconds, whereas mass spectra are acquired in about 100 microseconds with time-of-flight (TOF) instruments. This allows adding ion mobility as a third dimension of separation. Among several formats, trapped ion mobility spectrometry (TIMS) is attractive because of its small size, low voltage requirements and high efficiency of ion utilization. We have recently demonstrated a scan mode termed parallel accumulation - serial fragmentation (PASEF), which multiplies the sequencing speed without any loss in sensitivity (Meier et al., PMID: 26538118). Here we introduce the timsTOF Pro instrument, which optimally implements online PASEF. It features an orthogonal ion path into the ion mobility device, limiting the amount of debris entering the instrument and making it very robust in daily operation. We investigate different precursor selection schemes for shotgun proteomics to optimally allocate in excess of 100 fragmentation events per second. More than 600,000 fragmentation spectra in standard 120 min LC runs are achievable, which can be used for near exhaustive precursor selection in complex mixtures or accumulating the signal of weak precursors. In 120 min single runs of HeLa digest, MaxQuant identified more than 6,000 proteins without matching to a library and with high quantitative reproducibility (R > 0.97). Online PASEF achieves a remarkable sensitivity with more than 2,500 proteins identified in 30 min runs of only 10 ng HeLa digest. We also show that highly reproducible collisional cross sections can be acquired on a large scale (R > 0.99). PASEF on the timsTOF Pro is a valuable addition to the technological toolbox in proteomics, with a number of unique operating modes that are only beginning to be explored.

Ion mobility mass spectrometry with molecular modelling to reveal bioactive isomer conformations and underlying relationship with isomerization

RATIONALE

In medicine and drug development, molecular modelling is an important tool. It is attractive to develop a platform connecting the theoretical structural modelling and the results from experimental measurement. In addition, the separation and structural analysis of bioactive constituent isomers are still challenging tasks.

METHODS

Drift tube ion mobility (IM) mass spectrometry (MS) provides the experimental collision cross section (CCS) which contains the structural information. The experimental CCS can be compared with the calculated CCS of the molecular modelling structures. This technique is especially useful for bioactive constituents in herbal medicine because active isomers with the same chemical formula are common in these samples. IM helps separate and identify these isomers and reveals details about their structures and conformations.

RESULTS

Two model bioactive constituents, caffeoylquinic acids (CQAs) and dicaffeoylquinic acids (di-CQAs), were selected to systematically investigate the influence of solution, ion source conditions and ion heating on the isomer CCS distributions. By comparing the calculated CCS with the experimental value, we identified the favorable conformations of CQAs. The most compact conformation of a CQA was less likely to isomerize than the more extended conformation. It was found that the isomerization tendency was in accord with the conformation favorability.

CONCLUSIONS

This study offers an effective approach to predict and demystify the conformation and isomerization of the active constituents in herbal medicines.

Italian cohort of patients affected by inflammatory bowel disease is characterised by variation in glycerophospholipid, free fatty acids and amino acid levels

BACKGROUND

Inflammatory bowel disease is a group of pathologies characterised by chronic inflammation of the intestine and an unclear aetiology. Its main manifestations are Crohn's disease and ulcerative colitis. Currently, biopsies are the most used diagnostic tests for these diseases and metabolomics could represent a less invasive approach to identify biomarkers of disease presence and progression.

OBJECTIVES

The lipid and the polar metabolite profile of plasma samples of patients affected by inflammatory bowel disease have been compared with healthy individuals with the aim to find their metabolomic differences. Also, a selected sub-set of samples was analysed following solid phase extraction to further characterise differences between pathological samples.

METHODS

A total of 200 plasma samples were analysed using drift tube ion mobility coupled with time of flight mass spectrometry and liquid chromatography for the lipid metabolite profile analysis, while liquid chromatography coupled with triple quadrupole mass spectrometry was used for the polar metabolite profile analysis.

RESULTS

Variations in the lipid profile between inflammatory bowel disease and healthy individuals were highlighted. Phosphatidylcholines, lyso-phosphatidylcholines and fatty acids were significantly changed among pathological samples suggesting changes in phospholipase A₂ and arachidonic acid metabolic pathways. Variations in the levels of cholesteryl esters and glycerophospholipids were also found. Furthermore, a decrease in amino acids levels suggests mucosal damage in inflammatory bowel disease.

CONCLUSIONS

Given good statistical results and predictive power of the model produced in our study, metabolomics can be considered as a valid tool to investigate inflammatory bowel disease.

Increasing Compound Identification Rates in Untargeted Lipidomics Research with Liquid Chromatography Drift Time-Ion Mobility Mass Spectrometry

Unknown metabolites represent a bottleneck in untargeted metabolomics research. Ion mobility-mass spectrometry (IM-MS) facilitates lipid identification because it yields collision cross section (CCS) information that is independent from mass or lipophilicity. To date, only a few CCS values are publicly available for complex lipids such as phosphatidylcholines, sphingomyelins, or triacylglycerides. This scarcity of data limits the use of CCS values as an identification parameter that is orthogonal to mass, MS/MS, or retention time. A combination of lipid descriptors was used to train five different machine learning algorithms for automatic lipid annotations, combining accurate mass ( m/ z), retention time (RT), CCS values, carbon number, and unsaturation level. Using a training data set of 429 true positive lipid annotations from four lipid classes, 92.7% correct annotations overall were achieved using internal cross-validation. The trained prediction model was applied to an unknown milk lipidomics data set and allowed for class 3 level annotations of most features detected in this application set according to Metabolomics Standards Initiative (MSI) reporting guidelines.

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

The field of ion mobility-based omics studies requires high-quality collision cross section (CCS) libraries to effectively utilize CCS as a molecular descriptor. Absolute CCS values with the highest precision are obtained on drift tube instruments by measuring the drift time of ions at multiple drift voltages, commonly referred to as a 'stepped field' experiment. However, generating large scale absolute CCS libraries from drift tube instruments is time consuming due to the current lack of high-throughput methods. This communication reports a fully automated stepped-field method to acquire absolute CCS on commercially available equipment. Using a drift tube ion mobility-mass spectrometer (DTIM-MS) coupled to a minimally modified liquid chromatography (LC) system, CCS values can be measured online with a carefully timed flow injection analysis (FIA) experiment. Results demonstrate that the FIA stepped-field method yields CCS values which are of high analytical precision (<0.4% relative standard deviation, RSD) and accuracy (≤0.4% difference) comparable to CCS values obtained using traditional direct-infusion stepped-field experiments. This high-throughput CCS method consumes very little sample volume (20 μL) and will expedite the generation of large-scale CCS libraries to support molecular identification within global untargeted studies.

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.

Conformational Landscapes of Ubiquitin, Cytochrome c, and Myoglobin: Uniform Field Ion Mobility Measurements in Helium and Nitrogen Drift Gas

In this study, a commercial uniform field drift tube ion mobility-mass spectrometer (IM-MS) was utilized to measure the gas-phase conformational populations of three well-studied proteins: ubiquitin (8566 Da), cytochrome c (12,359 Da), and myoglobin in both apo and holo forms (16,951 and 17,567 Da, respectively) in order to evaluate the use of this technology for broadscale structural proteomics applications. Proteins were electrosprayed from either acidic organic (pH ~3) or aqueous buffered (pH ~6.6) solution phase conditions, which generated a wide range of cation charge states corresponding to both extended (unfolded) and compact (folded) gas-phase conformational populations. Corresponding collision cross section (CCS) measurements were compiled for significant ion mobility peak features observed at each charge state in order to map the conformational landscapes of these proteins in both helium and nitrogen drift gases. It was observed that the conformational landscapes were similar in both drift gases, with differences being attributed primarily to ion heating during helium operation due to the necessity of operating the instrument with higher pressure differentials. Higher resolving powers were observed in nitrogen, which allowed for slightly better structural resolution of closely-spaced conformer populations. The instrumentation was found to be particularly adept at measuring low abundance conformers which are only present under gentle conditions which minimize ion heating. This work represents the single largest ion mobility CCS survey published to date for these three proteins with 266 CCS values and 117 ion mobility spectra, many of which have not been previously reported.

Utilizing ion mobility spectrometry and mass spectrometry for the analysis of polycyclic aromatic hydrocarbons, polychlorinated biphenyls, polybrominated diphenyl ethers and their metabolites

Polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) are persistent environmental pollutants originating from incomplete combustion of organic materials and synthetic sources. PAHs, PCBs, and PBDEs have all been shown to have a significant effect on human health with correlations to cancer and other diseases. Therefore, measuring the presence of these xenobiotics in the environment and human body is imperative for assessing their health risks. To date, their analyses require both gas chromatography and liquid chromatography separations in conjunction with mass spectrometry measurements for detection of both the parent molecules and their hydroxylated metabolites, making their studies extremely time consuming. In this work, we characterized PAHs, PCBs, PBDEs and their hydroxylated metabolites using ion mobility spectrometry coupled with mass spectrometry (IMS-MS) and in combination with different ionization methods including electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI) and atmospheric pressure photoionization (APPI). The collision cross section and m/z trend lines derived from the IMS-MS analyses displayed distinct trends for each molecule type. Additionally, the rapid isomeric and molecular separations possible with IMS-MS showed great promise for quickly distinguishing the parent and metabolized PAH, PCB, and PDBE molecules in complex environmental and biological samples.

Evaluating lipid mediator structural complexity using ion mobility spectrometry combined with mass spectrometry

AIM

Lipid mediators (LMs) are broadly defined as a class of bioactive lipophilic molecules that regulate cell-to-cell communication events with many having a strong correlation with various human diseases and conditions. LMs are usually analyzed with  LC-MS, but their numerous isomers greatly complicate the measurements with essentially identical fragmentation spectra and LC separations are not always sufficient for distinguishing the features. Results/methodology: In this work, we characterized LMs using ion mobility spectrometry (IMS) coupled with MS (IMS-MS). The collision cross-sections and m/z values from the IMS and MS analyses displayed distinct trend lines. Specifically, the structural trend lines for sodiated LMs originating from docosahexaenoic acid had the smallest collision cross-section values in relation to m/z, while those from linoleic acid had the largest. LC-IMS-MS analyses were also performed on LMs in flu infected mouse tissue samples. These multidimensional studies were able to assess known LMs while also detecting new species.

CONCLUSION

Adding IMS separations to conventional LC-MS analyses show great utility for enabling better identification and characterization of LMs in complex biological samples.

Ion mobility-derived collision cross section database: Application to mycotoxin analysis

The recent hyphenation of ion mobility spectrometry (IMS) with high resolution mass spectrometry (HRMS) has risen as a powerful technique for both targeted and non-targeted screening, reducing background noise and allowing separation of isomeric and isobaric compounds. Nevertheless, such an approach remains largely unexplored in food safety applications, such as mycotoxin analysis. To implement ion mobility in routinely MS-based mycotoxin workflows, searchable databases with collusion cross section (CCS) values and accurate mass-values are required. This paper provides for the first time a traveling-wave IMS (TWIMS)-derived CCS database for mycotoxins, including more than 100 CCS values. The measurements showed high reproducibility (RSD < 2%) across different instrumental conditions as well as several complex cereal matrices, showing a mean inter-matrix precision of RSD <0.9%. As a proof of concept, the database was applied to the analysis of several spiked as well as naturally incurred cereal-based samples. In addition, the effect of adducts on the drift time was studied in a series of mycotoxins in order to understand potential deviations from expected drift time behaviors. Overall, our study confirmed that CCS values represent a physicochemical property that can be used alongside the traditional molecular identifiers of precursor ion accurate mass, fragment ions, isotopic pattern, and retention time.

Determining Double Bond Position in Lipids Using Online Ozonolysis Coupled to Liquid Chromatography and Ion Mobility-Mass Spectrometry

The increasing focus on lipid metabolism has revealed a need for analytical techniques capable of structurally characterizing lipids with a high degree of specificity. Lipids can exist as any one of a large number of double bond positional isomers, which are indistinguishable by single-stage mass spectrometry alone. Ozonolysis reactions coupled to mass spectrometry have previously been demonstrated as a means for localizing double bonds in unsaturated lipids. Here we describe an online, solution-phase reactor using ozone produced via a low-pressure mercury lamp, which generates aldehyde products diagnostic of cleavage at a particular double bond position. This flow-cell device is utilized in conjunction with structurally selective ion mobility-mass spectrometry. The lamp-mediated reaction was found to be effective for multiple lipid species in both positive and negative ionization modes, and the conversion efficiency from precursor to product ions was tunable across a wide range (20-95%) by varying the flow rate through the ozonolysis device. Ion mobility separation of the ozonolysis products generated additional structural information and revealed the presence of saturated species in a complex mixture. The method presented here is simple, robust, and readily coupled to existing instrument platforms with minimal modifications necessary. For these reasons, application to standard lipidomic workflows is possible and aids in more comprehensive structural characterization of a myriad of lipid species.

Online Ozonolysis Combined with Ion Mobility-Mass Spectrometry Provides a New Platform for Lipid Isomer Analyses

One of the most significant challenges in contemporary lipidomics lies in the separation and identification of lipid isomers that differ only in site(s) of unsaturation or geometric configuration of the carbon-carbon double bonds. While analytical separation techniques including ion mobility spectrometry (IMS) and liquid chromatography (LC) can separate isomeric lipids under appropriate conditions, conventional tandem mass spectrometry cannot provide unequivocal identification. To address this challenge, we have implemented ozone-induced dissociation (OzID) in-line with LC, IMS, and high resolution mass spectrometry. Modification of an IMS-capable quadrupole time-of-flight mass spectrometer was undertaken to allow the introduction of ozone into the high-pressure trapping ion funnel region preceding the IMS cell. This enabled the novel LC-OzID-IMS-MS configuration where ozonolysis of ionized lipids occurred rapidly (10 ms) without prior mass-selection. LC-elution time alignment combined with accurate mass and arrival time extraction of ozonolysis products facilitated correlation of precursor and product ions without mass-selection (and associated reductions in duty cycle). Unsaturated lipids across 11 classes were examined using this workflow in both positive and negative ion modalities, and in all cases, the positions of carbon-carbon double bonds were unequivocally assigned based on predictable OzID transitions. Under these conditions, geometric isomers exhibited different IMS arrival time distributions and distinct OzID product ion ratios providing a means for discrimination of cis/trans double bonds in complex lipids. The combination of OzID with multidimensional separations shows significant promise for facile profiling of unsaturation patterns within complex lipidomes including human plasma.

Structural characterization of small molecular ions by ion mobility mass spectrometry in nitrogen drift gas: improving the accuracy of trajectory method calculations

An accurate theoretical collision cross section calculation method in nitrogen was developed for reliable structural ion mobility mass spectrometry.

Correlating Resolving Power, Resolution, and Collision Cross Section: Unifying Cross-Platform Assessment of Separation Efficiency in Ion Mobility Spectrometry

Here we examine the relationship among resolving power (Rp), resolution (Rpp), and collision cross section (CCS) for compounds analyzed in previous ion mobility (IM) experiments representing a wide variety of instrument platforms and IM techniques. Our previous work indicated these three variables effectively describe and predict separation efficiency for drift tube ion mobility spectrometry experiments. In this work, we seek to determine if our previous findings are a general reflection of IM behavior that can be applied to various instrument platforms and mobility techniques. Results suggest IM distributions are well characterized by a Gaussian model and separation efficiency can be predicted on the basis of the empirical difference in the gas-phase CCS and a CCS-based resolving power definition (CCS/ΔCCS). Notably traveling wave (TWIMS) was found to operate at resolutions substantially higher than a single-peak resolving power suggested. When a CCS-based Rp definition was utilized, TWIMS was found to operate at a resolving power between 40 and 50, confirming the previous observations by Giles and co-workers. After the separation axis (and corresponding resolving power) is converted to cross section space, it is possible to effectively predict separation behavior for all mobility techniques evaluated (i.e., uniform field, trapped ion mobility, traveling wave, cyclic, and overtone instruments) using the equations described in this work. Finally, we are able to establish for the first time that the current state-of-the-art ion mobility separations benchmark at a CCS-based resolving power of >300 that is sufficient to differentiate analyte ions with CCS differences as small as 0.5%.

Advancing the large-scale CCS database for metabolomics and lipidomics at the machine-learning era

Metabolomics and lipidomics aim to comprehensively measure the dynamic changes of all metabolites and lipids that are present in biological systems. The use of ion mobility-mass spectrometry (IM-MS) for metabolomics and lipidomics has facilitated the separation and the identification of metabolites and lipids in complex biological samples. The collision cross-section (CCS) value derived from IM-MS is a valuable physiochemical property for the unambiguous identification of metabolites and lipids. However, CCS values obtained from experimental measurement and computational modeling are limited available, which significantly restricts the application of IM-MS. In this review, we will discuss the recently developed machine-learning based prediction approach, which could efficiently generate precise CCS databases in a large scale. We will also highlight the applications of CCS databases to support metabolomics and lipidomics.

The potential of ion mobility-mass spectrometry for non-targeted metabolomics

Non-targeted analysis of metabolites in hypothesis-generating workflows has proven its potential to answer essential questions that arise when dealing with complex biological systems. Nevertheless, tracking changes in perturbed systems via accurate quantification and the identification process itself represent the most critical challenges in these workflows. Recent advances in ion mobility-mass spectrometry have enabled this technique to increase the confidence of metabolite annotation by introducing a complementary conditional molecular descriptor, that is collision cross section.

A structural examination and collision cross section database for over 500 metabolites and xenobiotics using drift tube ion mobility spectrometry

The confident identification of metabolites and xenobiotics in biological and environmental studies is an analytical challenge due to their immense dynamic range, vast chemical space and structural diversity. Ion mobility spectrometry (IMS) is widely used for small molecule analyses since it can separate isomeric species and be easily coupled with front end separations and mass spectrometry for multidimensional characterizations. However, to date IMS metabolomic and exposomic studies have been limited by an inadequate number of accurate collision cross section (CCS) values for small molecules, causing features to be detected but not confidently identified. In this work, we utilized drift tube IMS (DTIMS) to directly measure CCS values for over 500 small molecules including primary metabolites, secondary metabolites and xenobiotics. Since DTIMS measurements do not need calibrant ions or calibration like some other IMS techniques, they avoid calibration errors which can cause problems in distinguishing structurally similar molecules. All measurements were performed in triplicate in both positive and negative polarities with nitrogen gas and seven different electric fields, so that relative standard deviations (RSD) could be assessed for each molecule and structural differences studied. The primary metabolites analyzed to date have come from key metabolism pathways such as glycolysis, the pentose phosphate pathway and the tricarboxylic acid cycle, while the secondary metabolites consisted of classes such as terpenes and flavonoids, and the xenobiotics represented a range of molecules from antibiotics to polycyclic aromatic hydrocarbons. Different CCS trends were observed for several of the diverse small molecule classes and when urine features were matched to the database, the addition of the IMS dimension greatly reduced the possible number of candidate molecules. This CCS database and structural information are freely available for download at http://panomics.pnnl.gov/metabolites/ with new molecules being added frequently.