Large-scale collision cross-section profiling on a traveling wave ion mobility mass spectrometer

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.

Recent Advances in Mass Spectrometry-Based Structural Elucidation Techniques

Mass spectrometry (MS) has become the central technique that is extensively used for the analysis of molecular structures of unknown compounds in the gas phase. It manipulates the molecules by converting them into ions using various ionization sources. With high-resolution MS, accurate molecular weights (MW) of the intact molecular ions can be measured so that they can be assigned a molecular formula with high confidence. Furthermore, the application of tandem MS has enabled detailed structural characterization by breaking the intact molecular ions and protonated or deprotonated molecules into key fragment ions. This approach is not only used for the structural elucidation of small molecules (MW < 2000 Da), but also crucial biopolymers such as proteins and polypeptides; therefore, MS has been extensively used in multiomics studies for revealing the structures and functions of important biomolecules and their interactions with each other. The high sensitivity of MS has enabled the analysis of low-level analytes in complex matrices. It is also a versatile technique that can be coupled with separation techniques, including chromatography and ion mobility, and many other analytical instruments such as NMR. In this review, we aim to focus on the technical advances of MS-based structural elucidation methods over the past five years, and provide an overview of their applications in complex mixture analysis. We hope this review can be of interest for a wide range of audiences who may not have extensive experience in MS-based techniques.

Least absolute shrinkage and selection operator-based prediction of collision cross section values for ion mobility mass spectrometric analysis of lipids

A least absolute shrinkage and selection operator (LASSO)-based prediction method was developed for the prediction of lipids’ CCS values.

Predicting differential ion mobility behaviour in silico using machine learning

Although there has been a surge in popularity of differential mobility spectrometry (DMS) within analytical workflows, determining separation conditions within the DMS parameter space still requires manual optimization. A means of accurately predicting differential ion mobility would benefit practitioners by significantly reducing the time associated with method development. Here, we report a machine learning (ML) approach that predicts dispersion curves in an N2 environment, which are the compensation voltages (CVs) required for optimal ion transmission across a range of separation voltages (SVs) between 1500 to 4000 V. After training a random-forest based model using the DMS information of 409 cationic analytes, dispersion curves were reproduced with a mean absolute error (MAE) of ≤ 2.4 V, approaching typical experimental peak FWHMs of ±1.5 V. The predictive ML model was trained using only m/z and ion-neutral collision cross section (CCS) as inputs, both of which can be obtained from experimental databases before being extensively validated. By updating the model via inclusion of two CV datapoints at lower SVs (1500 V and 2000 V) accuracy was further improved to MAE ≤ 1.2 V. This improvement stems from the ability of the "guided" ML routine to accurately capture Type A and B behaviour, which was exhibited by only 2% and 17% of ions, respectively, within the dataset. Dispersion curve predictions of the database's most common Type C ions (81%) using the unguided and guided approaches exhibited average errors of 0.6 V and 0.1 V, respectively.

Sequence-Specific Model for Predicting Peptide Collision Cross Section Values in Proteomic Ion Mobility Spectrometry

The contribution of peptide amino acid sequence to collision cross section values (CCS) has been investigated using a dataset of ∼134 000 peptides of four different charge states (1+ to 4+). The migration data were acquired using a two-dimensional liquid chromatography (LC)/trapped ion mobility spectrometry/quadrupole/time-of-flight mass spectrometry (MS) analysis of HeLa cell digests created using seven different proteases and was converted to CCS values. Following the previously reported modeling approaches using intrinsic size parameters (ISP), we extended this methodology to encode the position of individual residues within a peptide sequence. A generalized prediction model was built by dividing the dataset into eight groups (four charges for both tryptic/nontryptic peptides). Position-dependent ISPs were independently optimized for the eight subsets of peptides, resulting in prediction accuracy of ∼0.981 for the entire population of peptides. We find that ion mobility is strongly affected by the peptide's ability to solvate the positively charged sites. Internal positioning of polar residues and proline leads to decreased CCS values as they improve charge solvation; conversely, this ability decreases with increasing peptide charge due to electrostatic repulsion. Furthermore, higher helical propensity and peptide hydrophobicity result in a preferential formation of extended structures with higher than predicted CCS values. Finally, acidic/basic residues exhibit position-dependent ISP behavior consistent with electrostatic interaction with the peptide macrodipole, which affects the peptide helicity. The MS raw data files have been deposited with the ProteomeXchange Consortium via the jPOST partner repository (http://jpostdb.org) with the dataset identifiers PXD021440/JPST000959, PXD022800/JPST001017, and PXD026087/ JPST001176.

Determining Collision Cross Sections from Differential Ion Mobility Spectrometry

The experimental determination of ion-neutral collision cross sections (CCSs) is generally confined to ion mobility spectrometry (IMS) technologies that operate under the so-called low-field limit or those that enable empirical calibration strategies (e.g., traveling wave IMS; TWIMS). Correlation of ion trajectories to CCS in other non-linear IMS techniques that employ dynamic electric fields, such as differential mobility spectrometry (DMS), has remained a challenge since its inception. Here, we describe how an ion's CCS can be measured from DMS experiments using a machine learning (ML)-based calibration. The differential mobility of 409 molecular cations (m/z: 86-683 Da and CCS 110-236 Å2) was measured in a N2 environment to train the ML framework. Several open-source ML routines were tested and trained using DMS-MS data in the form of the parent ion's m/z and the compensation voltage required for elution at specific separation voltages between 1500 and 4000 V. The best performing ML model, random forest regression, predicted CCSs with a mean absolute percent error of 2.6 ± 0.4% for analytes excluded from the training set (i.e., out-of-the-bag external validation). This accuracy approaches the inherent statistical error of ∼2.2% for the MobCal-MPI CCS calculations employed for training purposes and the <2% threshold for matching literature CCSs with those obtained on a TWIMS platform.

Ion Mobility-High-Resolution Mass Spectrometry (IM-HRMS) for the Analysis of Contaminants of Emerging Concern (CECs): Database Compilation and Application to Urine Samples

Ion mobility mass spectrometry (IM-MS)-derived collision cross section (CCS) values can serve as a valuable additional identification parameter within the analysis of compounds of emerging concern (CEC) in human matrices. This study introduces the first comprehensive database of ^DTCCS_N2 values of 148 CECs and their metabolites including bisphenols, alternative plasticizers (AP), organophosphate flame retardants (OP), perfluoroalkyl chemicals (PFAS), and others. A total of 311 ions were included in the database, whereby the ^DTCCS_N2 values for 113 compounds are reported for the first time. For 105 compounds, more than one ion is reported. Moreover, the ^DTCCS_N2 values of several isomeric CECs and their metabolites are reported to allow a distinction between isomers. Comprehensive quality assurance guidelines were implemented in the workflow of acquiring ^DTCCS_N2 values to ensure reproducible experimental conditions. The reliability and reproducibility of the complied database were investigated by analyzing pooled human urine spiked with 30 AP and OP metabolites at two concentration levels. For all investigated metabolites, the ^DTCCS_N2 values measured in urine showed a percent error of <1% in comparison to database values. ^DTCCS_N2 values of OP metabolites showed an average percent error of 0.12% (50 ng/mL in urine) and 0.15% (20 ng/mL in urine). For AP metabolites, these values were 0.10 and 0.09%, respectively. These results show that the provided database can be of great value for enhanced identification of CECs in environmental and human matrices, which can advance future suspect screening studies on CECs.

Deep learning the collisional cross sections of the peptide universe from a million experimental values

The size and shape of peptide ions in the gas phase are an under-explored dimension for mass spectrometry-based proteomics. To investigate the nature and utility of the peptide collisional cross section (CCS) space, we measure more than a million data points from whole-proteome digests of five organisms with trapped ion mobility spectrometry (TIMS) and parallel accumulation-serial fragmentation (PASEF). The scale and precision (CV < 1%) of our data is sufficient to train a deep recurrent neural network that accurately predicts CCS values solely based on the peptide sequence. Cross section predictions for the synthetic ProteomeTools peptides validate the model within a 1.4% median relative error (R > 0.99). Hydrophobicity, proportion of prolines and position of histidines are main determinants of the cross sections in addition to sequence-specific interactions. CCS values can now be predicted for any peptide and organism, forming a basis for advanced proteomics workflows that make full use of the additional information.

Proteomics has been advanced by algorithms that can predict different peptide features, but predicting peptide collisional cross sections (CCS) has remained challenging. Here, the authors measure over one million CCS values of tryptic peptides and develop a deep learning model for peptide CCS prediction.

Effect of Phosphorylation on the Collision Cross Sections of Peptide Ions in Ion Mobility Spectrometry

The insertion of ion mobility spectrometry (IMS) between LC and MS can improve peptide identification in both proteomics and phosphoproteomics by providing structural information that is complementary to LC and MS, because IMS separates ions on the basis of differences in their shapes and charge states. However, it is necessary to know how phosphate groups affect the peptide collision cross sections (CCS) in order to accurately predict phosphopeptide CCS values and to maximize the usefulness of IMS. In this work, we systematically characterized the CCS values of 4,433 pairs of mono-phosphopeptide and corresponding unphosphorylated peptide ions using trapped ion mobility spectrometry (TIMS). Nearly one-third of the mono-phosphopeptide ions evaluated here showed smaller CCS values than their unphosphorylated counterparts, even though phosphorylation results in a mass increase of 80 Da. Significant changes of CCS upon phosphorylation occurred mainly in structurally extended peptides with large numbers of basic groups, possibly reflecting intramolecular interactions between phosphate and basic groups.

Ion Mobility-Mass Spectrometry Imaging Workflow

Mass spectrometry imaging (MSI) is a powerful technique for the label-free spatially resolved analysis of biological tissues. Coupling ion mobility (IM) separation with MSI allows for separation of isobars in the mobility dimension and increases confidence of peak assignments. Recently, imaging experiments have been implemented on several commercially available and custom-designed ion mobility instruments, making IM-MSI experiments more broadly accessible to the MS community. However, the absence of open access data analysis software for IM-MSI systems presents a bottleneck. Herein, we present an imaging workflow to visualize IM-MSI data produced on the Agilent 6560 ion mobility quadrupole time-of-flight system. Specifically, we have developed a Python script, the ion mobility-mass spectrometry image creation script (IM-MSIC), which interfaces Agilent's Mass Hunter Mass Profiler software with the MacCoss lab's Skyline software and generates drift time and mass-to-charge-selected ion images. In the workflow, Mass Profiler is used for an untargeted feature detection. The IM-MSIC script mediates user input of data, extracts ion chronograms utilizing Skyline's command-line interface, and then proceeds toward ion image generation within a single user interface. Ion image postprocessing is subsequently performed using different tools implemented in accompanying scripts. Though the current work only showcases Agilent IM-MSI data, this workflow can be readily adapted for use with most major instrument vendors.

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

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

The use of UHPLC, IMS, and HRMS in multiresidue analytical methods: A critical review

Residue chemists who analyse pesticides in vegetables or veterinary drugs in animal-based food are currently facing a situation where there is a requirement to detect more and more compounds at lower and lower concentrations. Conventional tandem quadrupole instruments provide sufficient sensitivity, but speed and selectivity appear as future limitations. This will become an even larger issue when there is a need to not only detect active compounds but also their degradation products and metabolites. This will likely lead to a situation in which the conventional targeted approach must be expanded or augmented by a certain non-targeted strategy. High-resolution mass spectrometry provides such capabilities, but it frequently requires an additional degree of selectivity for the unequivocal confirmation of analytes present at trace levels in highly complex and variable food matrices. The hyphenation of ultrahigh performance liquid chromatography with ion mobility and high-resolution mass spectrometry provides analytical chemists with a new tool for performing such a demanding multiresidue analysis. The objective of this paper is to investigate the benefits of the added ion mobility dimension as well as to critically discuss the current limitations of this commercially available technology.

Data Independent Acquisition Mass Spectrometry Method for Improved Neuropeptidomic Coverage in Crustacean Neural Tissue Extracts

Neuropeptides are an important class of signaling molecules in the nervous and neuroendocrine system, but they are challenging to study due to their low concentration in vivo in the presence of numerous interfering artifacts. Often the limitation of mass spectrometry analyses of neuropeptides in complex tissue extracts is not due to neuropeptides being below the detection limit but due to ions not being selected for tandem mass spectrometry during the liquid chromatography elution time and therefore not being identified. In this study, a data independent acquisition (DIA) method was developed to improve the coverage of neuropeptides in neural tissue from the model organism C. borealis. The optimal mass-to-charge ratio range and isolation window were determined and subsequently used to detect more neuropeptides in extracts from the brain and pericardial organs than the conventional data dependent acquisition method. The DIA method led to the detection of almost twice as many neuropeptides in the brain and approximately 1.5-fold more neuropeptides in the pericardial organs. The technical and biological reproducibility were also explored and found to be improved over the original method, with 56% of neuropeptides detected in 3 out of 3 replicate injections and 62% in 3 out of 3 biological replicates. Furthermore, 68 putative novel neuropeptides were detected and identified with de novo sequencing. The quantitative accuracy of the method was also explored. The developed method is anticipated to be useful for gaining a deeper profiling of neuropeptides, especially those in low abundance, in a variety of sample types.

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.

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 Spectrometry-Mass Spectrometry Coupled with Gas-Phase Hydrogen/Deuterium Exchange for Metabolomics Analyses

Ion mobility spectrometry-mass spectrometry (IMS-MS) in combination with gas-phase hydrogen/deuterium exchange (HDX) and collision-induced dissociation (CID) is evaluated as an analytical method for small-molecule standard and mixture characterization. Experiments show that compound ions exhibit unique HDX reactivities that can be used to distinguish different species. Additionally, it is shown that gas-phase HDX kinetics can be exploited to provide even further distinguishing capabilities by using different partial pressures of reagent gas. The relative HDX reactivity of a wide variety of molecules is discussed in light of the various molecular structures. Additionally, hydrogen accessibility scoring (HAS) and HDX kinetics modeling of candidate (in silico) ion structures is utilized to estimate the relative ion conformer populations giving rise to specific HDX behavior. These data interpretation methods are discussed with a focus on developing predictive tools for HDX behavior. Finally, an example is provided in which ion mobility information is supplemented with HDX reactivity data to aid identification efforts of compounds in a metabolite extract. Graphical Abstract ᅟ.

Identification, Quantitation, and Imaging of the Crustacean Peptidome

Crustaceans serve as a useful, simplified model for studying peptides and neuromodulation, as they contain numerous neuropeptide homologs to mammals and enable electrophysiological studies at the single-cell and neural circuit levels. In particular, crustaceans contain well-defined neural networks, including the stomatogastric ganglion, esophageal ganglion, commissural ganglia, and several neuropeptide-rich organs, such as the brain, pericardial organs, and sinus glands. Due to the lack of a genomic database for crustacean peptides, an important step of crustacean peptidomics involves the discovery and identification of novel peptides and the construction of a database, more recently with the aid of mass spectrometry (MS). Herein, we present a general workflow and detailed methods for MS-based peptidomic analysis of crustacean tissue samples and circulating fluids. In conjunction with profiling, quantitation can also be performed with isotopic or isobaric labeling. Information regarding the localization patterns and changes of peptides can be studied via mass spectrometry imaging. Combining these sample preparation strategies and MS analytical techniques allows for a multifaceted approach to obtaining deep knowledge of crustacean peptidergic signaling pathways.

Ion Mobility Collision Cross Section Compendium

In this review, we focus on an important aspect of ion mobility (IM) research, namely the reporting of quantitative ion mobility measurements in the form of the gas-phase collision cross section (CCS), which has provided a common basis for comparison across different instrument platforms and offers a unique form of structural information, namely size and shape preferences of analytes in the absence of bulk solvent. This review surveys the over 24,000 CCS values reported from IM methods spanning the era between 1975 to 2015, which provides both a historical and analytical context for the contributions made thus far, as well as insight into the future directions that quantitative ion mobility measurements will have in the analytical sciences. The analysis was conducted in 2016, so CCS values reported in that year are purposely omitted. In another few years, a review of this scope will be intractable, as the number of CCS values which will be reported in the next three to five years is expected to exceed the total amount currently published in the literature.

Radio-Frequency (rf) Confinement in Ion Mobility Spectrometry: Apparent Mobilities and Effective Temperatures

Ion mobility is a powerful tool for separating and characterizing the structures of ions. Here, a radio-frequency (rf) confining drift cell is used to evaluate the drift times of ions over a broad range of drift field strengths (E/P, V cm^-1 Torr^-1). The presence of rf potentials radially confines ions and results in excellent ion transmission at low E/P (less than 1 V cm^-1 Torr^-1), thereby reducing the dependence of ion transmission on the applied drift voltage. Non-linear responses between drift time and reciprocal drift voltages are observed for extremely low E/P and high rf amplitudes. Under these conditions, pseudopotential wells generated by the rf potentials dampen the mobility of ions. The effective potential approximation is used to characterize this mobility dampening behavior, which can be mitigated by adjusting rf amplitudes and electrode dimensions. Using SIMION trajectories and statistical arguments, the effective temperatures of ions in an rf-confining drift cell are evaluated. Results for the doubly charged peptide GRGDS suggest that applied rf potentials can result in a subtle increase (2 K) in effective temperature compared to an electrostatic drift tube. Additionally, simulations of native-like ions of the protein complex avidin suggest that rf potentials have a negligible effect on the effective temperature of these ions. In general, the results of this study suggest that applied rf potentials enable the measurement of drift times at extremely low E/P and that these potentials have negligible effects on ion effective temperature. Graphical Abstract ᅟ.

Toward a Rational Design of Highly Folded Peptide Cation Conformations. 3D Gas-Phase Ion Structures and Ion Mobility Characterization

Heptapeptide ions containing combinations of polar Lys, Arg, and Asp residues with non-polar Leu, Pro, Ala, and Gly residues were designed to study polar effects on gas-phase ion conformations. Doubly and triply charged ions were studied by ion mobility mass spectrometry and electron structure theory using correlated ab initio and density functional theory methods and found to exhibit tightly folded 3D structures in the gas phase. Manipulation of the basic residue positions in LKGPADR, LRGPADK, KLGPADR, and RLGPADK resulted in only minor changes in the ion collision cross sections in helium. Replacement of the Pro residue with Leu resulted in only marginally larger collision cross sections for the doubly and triply charged ions. Disruption of zwitterionic interactions in doubly charged ions was performed by converting the C-terminal and Asp carboxyl groups to methyl esters. This resulted in very minor changes in the collision cross sections of doubly charged ions and even slightly diminished collision cross sections in most triply charged ions. The experimental collision cross sections were related to those calculated for structures of lowest free energy ion conformers that were obtained by extensive search of the conformational space and fully optimized by density functional theory calculations. The predominant factors that affected ion structures and collision cross sections were due to attractive hydrogen bonding interactions and internal solvation of the charged groups that overcompensated their Coulomb repulsion. Structure features typically assigned to the Pro residue and zwitterionic COO-charged group interactions were only secondary in affecting the structures and collision cross sections of these gas-phase peptide ions. Graphical Abstract ᅟ.

Multiple gas-phase conformations of proline-containing peptides: is it always cis/trans isomerization?

Ion mobility-mass spectrometry (IM-MS) is often employed to look at the secondary, tertiary, and quaternary structures of naked peptides and proteins in the gas-phase. Recently, it has offered a unique glimpse into proline-containing peptides and their cis/trans Xxx-Pro isomers. An experimental "signature" has been identified wherein a proline-containing peptide has its Pro residues substituted with another amino acid and the presence or absence of conformations in the IM-MS spectra is observed. Despite the high probability that one could attribute these conformations to cis/trans isomers, it is also possible that cis/trans isomers are not the cause of the additional conformations in proline-containing peptides. However, the experimental evidence of such a system has not been demonstrated or reported. Herein, we present the IM-MS analysis of Neuropeptide Y's wild-type (WT) signal sequence and Leu7Pro (L7P) mutant. Although comparison of arrival times and collision cross-sections of [M + 4H](4+) ions yields the cis/trans "signature", molecular dynamics indicates that a cis-Pro7 is not very stable and that trans-Pro7 conformations of the same cross-section arise with equal frequency. We believe that this work further underscores the importance of theoretical calculations in IM-MS structural assignments.

Does Thermal Breathing Affect Collision Cross Sections of Gas-Phase Peptide Ions? An Ab Initio Molecular Dynamics Study

Ab initio molecular dynamics (AIMD) with density functional theory (DFT) was applied to explore conformational motions and collision cross sections (Ω) of folded (2) and extended (7) conformers of doubly charged peptide ions, (Ala-Ala-Leu-Arg + 2H)(2+), in the gas phase at 300 and 473 K. The experimental Ω of (Ala-Ala-Leu-Arg +2H)(2+) was measured as 149 ± 1.2 Å(2) at 298 K. Thermally distributed mean values of Ω for 2 and 7 at 300 and 473 K were only 0.8-1.1% larger than for the equilibrium 0 K structures. Long (>10 ps) trajectory calculations indicated entropy-driven conformational change of 2 to 7 that occurred at random within a ∼ 4 ps time window. The experimental Ω was found to fit the calculated population averaged values for 2 and 7, indicating a rapid conformer interconversion. Overall, thermal breathing had only a minor effect on the peptide ion collision cross sections.

Advanced Multidimensional Separations in Mass Spectrometry: Navigating the Big Data Deluge

Hybrid analytical instrumentation constructed around mass spectrometry (MS) is becoming the preferred technique for addressing many grand challenges in science and medicine. From the omics sciences to drug discovery and synthetic biology, multidimensional separations based on MS provide the high peak capacity and high measurement throughput necessary to obtain large-scale measurements used to infer systems-level information. In this article, we describe multidimensional MS configurations as technologies that are big data drivers and review some new and emerging strategies for mining information from large-scale datasets. We discuss the information content that can be obtained from individual dimensions, as well as the unique information that can be derived by comparing different levels of data. Finally, we summarize some emerging data visualization strategies that seek to make highly dimensional datasets both accessible and comprehensible.

Collision cross section calibrants for negative ion mode traveling wave ion mobility-mass spectrometry

Unlike traditional drift-tube ion mobility-mass spectrometry, traveling-wave ion mobility-mass spectrometry typically requires calibration in order to generate collision cross section (CCS) values. Although this has received a significant amount of attention for positive-ion mode analysis, little attention has been paid for CCS calibration in negative ion mode. Here, we provide drift-tube CCS values for [M - H](-) ions of two calibrant series, polyalanine and polymalic acid, and evaluate both types of calibrants in terms of the accuracy and precision of the traveling-wave ion mobility CCS values that they produce.

Protein Structural Studies by Traveling Wave Ion Mobility Spectrometry: A Critical Look at Electrospray Sources and Calibration Issues

The question whether electrosprayed protein ions retain solution-like conformations continues to be a matter of debate. One way to address this issue involves comparisons of collision cross sections (Ω) measured by ion mobility spectrometry (IMS) with Ω values calculated for candidate structures. Many investigations in this area employ traveling wave IMS (TWIMS). It is often implied that nanoESI is more conducive for the retention of solution structure than regular ESI. Focusing on ubiquitin, cytochrome c, myoglobin, and hemoglobin, we demonstrate that Ω values and collisional unfolding profiles are virtually indistinguishable under both conditions. These findings suggest that gas-phase structures and ion internal energies are independent of the type of electrospray source. We also note that TWIMS calibration can be challenging because differences in the extent of collisional activation relative to drift tube reference data may lead to ambiguous peak assignments. It is demonstrated that this problem can be circumvented by employing collisionally heated calibrant ions. Overall, our data are consistent with the view that exposure of native proteins to electrospray conditions can generate kinetically trapped ions that retain solution-like structures on the millisecond time scale of TWIMS experiments. ᅟ

Novel isotopic N,N-dimethyl leucine (iDiLeu) reagents enable absolute quantification of peptides and proteins using a standard curve approach

Absolute quantification of protein targets using liquid chromatography-mass spectrometry (LC-MS) is a key component of candidate biomarker validation. One popular method combines multiple reaction monitoring (MRM) using a triple quadrupole instrument with stable isotope-labeled standards (SIS) for absolute quantification (AQUA). LC-MRM AQUA assays are sensitive and specific, but they are also expensive because of the cost of synthesizing stable isotope peptide standards. While the chemical modification approach using mass differential tags for relative and absolute quantification (mTRAQ) represents a more economical approach when quantifying large numbers of peptides, these reagents are costly and still suffer from lower throughput because only two concentration values per peptide can be obtained in a single LC-MS run. Here, we have developed and applied a set of five novel mass difference reagents, isotopic N,N-dimethyl leucine (iDiLeu). These labels contain an amine reactive group, triazine ester, are cost effective because of their synthetic simplicity, and have increased throughput compared with previous LC-MS quantification methods by allowing construction of a four-point standard curve in one run. iDiLeu-labeled peptides show remarkably similar retention time shifts, slightly lower energy thresholds for higher-energy collisional dissociation (HCD) fragmentation, and high quantification accuracy for trypsin-digested protein samples (median errors <15%). By spiking in an iDiLeu-labeled neuropeptide, allatostatin, into mouse urine matrix, two quantification methods are validated. The first uses one labeled peptide as an internal standard to normalize labeled peptide peak areas across runs (<19% error), whereas the second enables standard curve creation and analyte quantification in one run (<8% error).