A Priori Intrinsic PTM Size Parameters for Predicting the Ion Mobilities of Modified Peptides

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.

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

MOTIVATION

Including ion mobility separation (IMS) into mass spectrometry proteomics experiments is useful to improve coverage and throughput. Many IMS devices enable linking experimentally derived mobility of an ion to its collisional cross-section (CCS), a highly reproducible physicochemical property dependent on the ion's mass, charge and conformation in the gas phase. Thus, known peptide ion mobilities can be used to tailor acquisition methods or to refine database search results. The large space of potential peptide sequences, driven also by posttranslational modifications of amino acids, motivates an in silico predictor for peptide CCS. Recent studies explored the general performance of varying machine-learning techniques, however, the workflow engineering part was of secondary importance. For the sake of applicability, such a tool should be generic, data driven, and offer the possibility to be easily adapted to individual workflows for experimental design and data processing.

RESULTS

We created ionmob, a Python-based framework for data preparation, training, and prediction of collisional cross-section values of peptides. It is easily customizable and includes a set of pretrained, ready-to-use models and preprocessing routines for training and inference. Using a set of ≈21 000 unique phosphorylated peptides and ≈17 000 MHC ligand sequences and charge state pairs, we expand upon the space of peptides that can be integrated into CCS prediction. Lastly, we investigate the applicability of in silico predicted CCS to increase confidence in identified peptides by applying methods of re-scoring and demonstrate that predicted CCS values complement existing predictors for that task.

AVAILABILITY AND IMPLEMENTATION

The Python package is available at github: https://github.com/theGreatHerrLebert/ionmob.

Tandem Trapped Ion Mobility Spectrometry/Mass Spectrometry (tTIMS/MS) Reveals Sequence-Specific Determinants of Top-Down Protein Fragment Ion Cross Sections

Top-down proteomics provides a straightforward approach to the level of proteoforms but remains technologically challenging. Using ion mobility spectrometry/mass spectrometry (IMS/MS) to separate top-down fragment ions improves signal/noise and dynamic range. Such applications, however, do not yet leverage the primary information obtained from IMS/MS, which is the characterization of the fragment ion structure by the measured momentum transfer cross sections. Here, we perform top-down analysis of intact proteins and assemblies using our tandem trapped ion mobility spectrometer/mass spectrometer (tTIMS/MS) and compile over 1400 cross section values of fragment ions. Our analysis reveals that most fragment ions exhibit multiple, stable conformations similar to those of intact polypeptides and proteins. The data further indicate that the conformational heterogeneity is strongly influenced by the amino acid sequences of the fragment ions. Moreover, time-resolved tTIMS/MS experiments reveal that conformations of top-down fragment ions can be metastable on the timescale of ion mobility measurements. Taken together, our analysis indicates that top-down fragment ions undergo a folding process in the gas phase and that this folding process can lead to kinetic trapping of intermediate states in ion mobility measurements. Hence, because the folding free energy surface of a polypeptide ion is encoded by its amino acid sequence and charge state, our analysis suggests that cross sections can be exploited as sequence-specific determinants of top-down fragment ions.

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.

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.

Fast and Effective Ion Mobility-Mass Spectrometry Separation of d-Amino-Acid-Containing Peptides

Despite often minute concentrations in vivo, d-amino acid containing peptides (DAACPs) are crucial to many life processes. Standard proteomics protocols fail to detect them as d/l substitutions do not affect the peptide parent and fragment masses. The differences in fragment yields are often limited, obstructing the investigations of important but low abundance epimers in isomeric mixtures. Separation of d/l-peptides using ion mobility spectrometry (IMS) was impeded by small collision cross section differences (commonly ∼1%). Here, broad baseline separation of DAACPs with up to ∼30 residues employing trapped IMS with resolving power up to ∼340, followed by time-of-flight mass spectrometry is demonstrated. The d/l-pairs coeluting in one charge state were resolved in another, and epimers merged as protonated species were resolved upon metalation, effectively turning the charge state and cationization mode into extra separation dimensions. Linear quantification down to 0.25% proved the utility of high resolution IMS-MS for real samples with large interisomeric dynamic range. Very close relative mobilities found for DAACP pairs using traveling-wave IMS (TWIMS) with different ion sources and faster IMS separations showed the transferability of results across IMS platforms. Fragmentation of epimers can enhance their identification and further improve detection and quantification limits, and we demonstrate the advantages of online mobility separated collision-induced dissociation (CID) followed by high resolution mass spectrometry (TIMS-CID-MS) for epimer analysis.

Broad Separation of Isomeric Lipids by High-Resolution Differential Ion Mobility Spectrometry with Tandem Mass Spectrometry

Maturation of metabolomics has brought a deeper appreciation for the importance of isomeric identity of lipids to their biological role, mirroring that for proteoforms in proteomics. However, full characterization of the lipid isomerism has been thwarted by paucity of rapid and effective analytical tools. A novel approach is ion mobility spectrometry (IMS) and particularly differential or field asymmetric waveform IMS (FAIMS) at high electric fields, which is more orthogonal to mass spectrometry. Here we broadly explore the power of FAIMS to separate lipid isomers, and find a ~75% success rate across the four major types of glycero- and phospho- lipids (sn, chain length, double bond position, and cis/trans). The resolved isomers were identified using standards, and (for the first two types) tandem mass spectrometry. These results demonstrate the general merit of incorporating high-resolution FAIMS into lipidomic analyses. Graphical Abstract ᅟ.