Importance of collision cross section measurements by ion mobility mass spectrometry in structural biology

Full Native timsTOF PASEF-Enabled Quantitative Proteomics with the i2MassChroQ Software Package

Ion mobility mass spectrometry has become popular in proteomics lately, in particular because the Bruker timsTOF instruments have found significant adoption in proteomics facilities. The Bruker's implementation of the ion mobility dimension generates massive amounts of mass spectrometric data that require carefully designed software both to extract meaningful information and to perform processing tasks at reasonable speed. In a historical move, the Bruker company decided to harness the skills of the scientific software development community by releasing to the public the timsTOF data file format specification. As a proteomics facility that has been developing Free Open Source Software (FOSS) solutions since decades, we took advantage of this opportunity to implement the very first FOSS proteomics complete solution to natively read the timsTOF data, low-level process them, and explore them in an integrated quantitative proteomics software environment. We dubbed our software i2MassChroQ because it implements a (peptide)identification-(protein)inference-mass-chromatogram-quantification processing workflow. The software benchmarking results reported in this paper show that i2MassChroQ performed better than competing software on two critical characteristics: (1) feature extraction capability and (2) protein quantitative dynamic range. Altogether, i2MassChroQ yielded better quantified protein numbers, both in a technical replicate MS runs setting and in a differential protein abundance analysis setting.

Ultrafast, Selective, and Highly Sensitive Nonchromatographic Analysis of Fourteen Cannabinoids in Cannabis Extracts, Δ8-Tetrahydrocannabinol Synthetic Mixtures, and Edibles by Cyclic Ion Mobility Spectrometry-Mass Spectrometry

The diversity of cannabinoid isomers and complexity of Cannabis products pose significant challenges for analytical methodologies. In this study, we developed a method to analyze 14 different cannabinoid isomers in diverse samples within milliseconds by leveraging the unique adduct-forming behavior of silver ions in advanced cyclic ion mobility spectrometry-mass spectrometry. The developed method achieved the separation of isomers from four groups of cannabinoids: Δ3-tetrahydrocannabinol (THC) (1), Δ8-THC (2), Δ9-THC (3), cannabidiol (CBD) (4), Δ8-iso-THC (5), and Δ(4)8-iso-THC (6) (all MW = 314); 9α-hydroxyhexahydrocannabinol (7), 9β-hydroxyhexahydrocannabinol (8), and 8-hydroxy-iso-THC (9) (all MW = 332); tetrahydrocannabinolic acid (THCA) (10) and cannabidiolic acid (CBDA) (11) (both MW = 358); Δ8-tetrahydrocannabivarin (THCV) (12), Δ8-iso-THCV (13), and Δ9-THCV (14) (all MW = 286). Moreover, experimental and theoretical traveling wave collision cross section values in nitrogen (TWCCSN2) of cannabinoid-Ag(I) species were obtained for the first time with an average error between experimental and theoretical values of 2.6%. Furthermore, a workflow for the identification of cannabinoid isomers in Cannabis and Cannabis-derived samples was established based on three identification steps (m/z and isotope pattern of Ag(I) adducts, TWCCSN2, and MS/MS fragments). Afterward, calibration curves of three major cannabinoids were established with a linear range of 1-250 ng·ml-1 for Δ8-THC (2) (R2 = 0.9999), 0.1-25 ng·ml-1 for Δ9-THC (3) (R2 = 0.9987), and 0.04-10 ng·ml-1 for CBD (4) (R2 = 0.9986) as well as very low limits of detection (0.008-0.2 ng·ml-1). Finally, relative quantification of Δ8-THC (2), Δ9-THC (3), and CBD (4) in eight complex acid-treated CBD mixtures was achieved without chromatographic separation. The results showed good correspondence (R2 = 0.999) with those obtained by gas chromatography-flame ionization detection/mass spectrometry.

Predicting the Predicted: A Comparison of Machine Learning-Based Collision Cross-Section Prediction Models for Small Molecules

The application of machine learning (ML) to -omics research is growing at an exponential rate owing to the increasing availability of large amounts of data for model training. Specifically, in metabolomics, ML has enabled the prediction of tandem mass spectrometry and retention time data. More recently, due to the advent of ion mobility, new ML models have been introduced for collision cross-section (CCS) prediction, but those have been trained with different and relatively small data sets covering a few thousands of small molecules, which hampers their systematic comparison. Here, we compared four existing ML-based CCS prediction models and their capacity to predict CCS values using the recently introduced METLIN-CCS data set. We also compared them with simple linear models and with ML models that used fingerprints as regressors. We analyzed the role of structural diversity of the data on which the ML models are trained with and explored the practical application of these models for metabolite annotation using CCS values. Results showed a limited capability of the existing models to achieve the necessary accuracy to be adopted for routine metabolomics analysis. We showed that for a particular molecule, this accuracy could only be improved when models were trained with a large number of structurally similar counterparts. Therefore, we suggest that current annotation capabilities will only be significantly altered with models trained with heterogeneous data sets composed of large homogeneous hubs of structurally similar molecules to those being predicted.

Investigating direct current potentials that affect native protein conformation during trapped ion mobility spectrometry-mass spectrometry

Trapped ion mobility spectrometry-time-of-flight mass spectrometry (TIMS-TOFMS) has emerged as a tool to study protein conformational states. In TIMS, gas-phase ions are guided across the IM stages by applying direct current (DC) potentials (D1-6), which, however, might induce changes in protein structures through collisional activation. To define conditions for native protein analysis, we evaluated the influence of these DC potentials using the metalloenzyme bovine carbonic anhydrase (BCA) as primary test compound. The variation of DC potentials did not change BCA-ion charge and heme content but affected (relative) charge-state intensities and adduct retention. Constructed extracted-ion mobilograms and corresponding collisional cross-section (CCS) profiles gave useful insights in (alterations of) protein conformational state. For BCA, the D3 and D6 potential (which are applied between the deflection transfer and funnel 1 [F1] and the accumulation exit and the start of the ramp, respectively) had most profound effects, showing multimodal CCS distributions at higher potentials indicating gradual unfolding. The other DC potentials only marginally altered the CCS profiles of BCA. To allow for more general conclusions, five additional proteins of diverse molecular weight and conformational stability were analyzed, and for the main protein charge states, CCS profiles were constructed. Principal component analysis (PCA) of the obtained data showed that D1 and D3 exhibit the highest degree of correlation with the ratio of folded and unfolded protein (F/U) as extracted from the mobilograms obtained per set D potential. The correlation of D6 with F/U and protein charge were similar, and D2, D4, and D5 showed an inverse correlation with F/U but were correlated with protein charge. Although DC boundary values for induced conformational changes appeared protein dependent, a set of DC values could be determined, which assured native analysis of most proteins.

Recent advances in structural mass spectrometry methods in the context of biosimilarity assessment: from sequence heterogeneities to higher order structures

Biotherapeutics and their biosimilar versions have been flourishing in the biopharmaceutical market for several years. Structural and functional characterization is needed to achieve analytical biosimilarity through the assessment of critical quality attributes as required by regulatory authorities. The role of analytical strategies, particularly mass spectrometry-based methods, is pivotal to gathering valuable information for the in-depth characterization of biotherapeutics and biosimilarity assessment. Structural mass spectrometry methods (native MS, HDX-MS, top-down MS, etc.) provide information ranging from primary sequence assessment to higher order structure evaluation. This review focuses on recent developments and applications in structural mass spectrometry for biotherapeutic and biosimilar characterization.

A special issue of Essays in Biochemistry on structural mass spectrometry

Mass spectrometry (MS) is now established as an analytical tool to interrogate the structure and dynamics of proteins and their assemblies. An array of MS-based technologies has been developed, with each providing unique information pertaining to protein structure, and forming the heart of integrative structural biology studies. This special issue includes a collection of review articles that discuss both established and emerging structural MS methodologies, along with examples of how these technologies are being deployed to interrogate protein structure and function. Combined, this collection highlights the immense potential of the structural MS toolkit in the study of molecular mechanisms underpinning cellular homeostasis and disease.

Ion Mobility Mass Spectrometry (IM-MS) for Structural Biology: Insights Gained by Measuring Mass, Charge, and Collision Cross Section

The investigation of macromolecular biomolecules with ion mobility mass spectrometry (IM-MS) techniques has provided substantial insights into the field of structural biology over the past two decades. An IM-MS workflow applied to a given target analyte provides mass, charge, and conformation, and all three of these can be used to discern structural information. While mass and charge are determined in mass spectrometry (MS), it is the addition of ion mobility that enables the separation of isomeric and isobaric ions and the direct elucidation of conformation, which has reaped huge benefits for structural biology. In this review, where we focus on the analysis of proteins and their complexes, we outline the typical features of an IM-MS experiment from the preparation of samples, the creation of ions, and their separation in different mobility and mass spectrometers. We describe the interpretation of ion mobility data in terms of protein conformation and how the data can be compared with data from other sources with the use of computational tools. The benefit of coupling mobility analysis to activation via collisions with gas or surfaces or photons photoactivation is detailed with reference to recent examples. And finally, we focus on insights afforded by IM-MS experiments when applied to the study of conformationally dynamic and intrinsically disordered proteins.

Efficient protein conformation dynamics characterization enabled by mobility-mass spectrometry

Protein structure dynamics in solution and from solution to gas phase are important but challenging topics. Great efforts and advances have been made especially since the wide application of ion mobility mass spectrometry (IM-MS), by which protein collision cross section (CCS) in gas phase could be measured. Due to the lack of efficient experimental methods, protein structures in protein databank are typically referred as their structures in solution. Although conventional structural biology techniques provide high-resolution protein structures, complicated and stringent processes also limit their applicability under different solvent conditions, thus preventing the capture of protein dynamics in solution. Enabled by the combination of mobility capillary electrophoresis (MCE) and IM-MS, an efficient experimental protocol was developed to characterize protein conformation dynamics in solution and from solution to gas phase. As a first attempt, key factors that affecting protein conformations were distinguished and evaluated separately, including pH, temperature, softness of ionization process, presence and specific location of disulfide bonds. Although similar extent of unfolding could be observed for different proteins, in-depth analysis reveals that pH decrease from 7.0 to 3.0 dominates the unfolding of proteins without disulfide bonds in conventional ESI-MS experiments; while harshness of the ionization process dominates the unfolding of proteins with disulfide bonds. Second, disulfide bonds show capability of preserving protein conformations in acidic solution environments. However, by monitoring protein conformation dynamics and comparing results from different proteins, it is also found that their capability is position dependent. Surprisingly, disulfide bonds did not show the capability of preserving protein conformations during ionization processes.

The increasing role of structural proteomics in cyanobacteria

Cyanobacteria, also known as blue–green algae, are ubiquitous organisms on the planet. They contain tremendous protein machineries that are of interest to the biotechnology industry and beyond. Recently, the number of annotated cyanobacterial genomes has expanded, enabling structural studies on known gene-coded proteins to accelerate. This review focuses on the advances in mass spectrometry (MS) that have enabled structural proteomics studies to be performed on the proteins and protein complexes within cyanobacteria. The review also showcases examples whereby MS has revealed critical mechanistic information behind how these remarkable machines within cyanobacteria function.

Assessing the Dipole Moments and Directional Cross Sections of Proteins and Complexes by Differential Ion Mobility Spectrometry

Ion mobility spectrometry (IMS) has become a mainstream approach to fractionate complex mixtures, separate isomers, and assign the molecular geometries. All modalities were grouped into linear IMS (based on the absolute ion mobility, K) and field asymmetric waveform IMS (FAIMS) relying on the evolution of K at a high normalized electric field (E/N) that induces strong ion heating. In the recently demonstrated low-field differential (LOD) IMS, the field is too weak for significant heating but locks the macromolecular dipoles to produce novel separations controlled by the relevant directional collision cross sections (CCSs). Here, we show LODIMS for mass-selected species, exploring the dipole alignment across charge states for the monomers and dimers of an exemplary protein, the alcohol dehydrogenase. Distinct conformational families for aligned species are revealed with directional CCS estimated from the field-dependent trend lines. We set up a model to extract the fractions of pendular conformers as a function of field intensity and translate them into dipole moment distributions. These developments make a critical step toward establishing LODIMS as a new tool for top-down proteomics and integrative structural biology.

Characterizing Endogenous Protein Complexes with Biological Mass Spectrometry

Biological mass spectrometry (MS) encompasses a range of methods for characterizing proteins and other biomolecules. MS is uniquely powerful for the structural analysis of endogenous protein complexes, which are often heterogeneous, poorly abundant, and refractive to characterization by other methods. Here, we focus on how biological MS can contribute to the study of endogenous protein complexes, which we define as complexes expressed in the physiological host and purified intact, as opposed to reconstituted complexes assembled from heterologously expressed components. Biological MS can yield information on complex stoichiometry, heterogeneity, topology, stability, activity, modes of regulation, and even structural dynamics. We begin with a review of methods for isolating endogenous complexes. We then describe the various biological MS approaches, focusing on the type of information that each method yields. We end with future directions and challenges for these MS-based methods.

A Novel Approach to Characterize the Lipidome of Marine Archaeon Nitrosopumilus maritimus by Ion Mobility Mass Spectrometry

Archaea are differentiated from the other two domains of life by their biomolecular characteristics. One such characteristic is the unique structure and composition of their lipids. Characterization of the whole set of lipids in a biological system (the lipidome) remains technologically challenging. This is because the lipidome is innately complex, and not all lipid species are extractable, separable, or ionizable by a single analytical method. Furthermore, lipids are structurally and chemically diverse. Many lipids are isobaric or isomeric and often indistinguishable by the measurement of mass or even their fragmentation spectra. Here we developed a novel analytical protocol based on liquid chromatography ion mobility mass spectrometry to enhance the coverage of the lipidome and characterize the conformations of archaeal lipids by their collision cross-sections (CCSs). The measurements of ion mobility revealed the gas-phase ion chemistry of representative archaeal lipids and provided further insights into their attributions to the adaptability of archaea to environmental stresses. A comprehensive characterization of the lipidome of mesophilic marine thaumarchaeon, Nitrosopumilus maritimus (strain SCM1) revealed potentially an unreported phosphate- and sulfate-containing lipid candidate by negative ionization analysis. It was the first time that experimentally derived CCS values of archaeal lipids were reported. Discrimination of crenarchaeol and its proposed stereoisomer was, however, not achieved with the resolving power of the SYNAPT G2 ion mobility system, and a high-resolution ion mobility system may be required for future work. Structural and spectral libraries of archaeal lipids were constructed in non-vendor-specific formats and are being made available to the community to promote research of Archaea by lipidomics.

Weight average approaches for predicting dynamical properties of biomolecules

Recent advances in atomistic molecular dynamics (MD) simulations of biomolecules allow us to explore their conformational spaces widely, observing large-scale conformational fluctuations or transitions between distinct structures. To reproduce or refine experimental data using MD simulations, structure ensembles, which are characterized by multiple structures and their statistical weights on the rugged free-energy landscapes, are often used. Here, we summarize weight average approaches for various experimental measurements. Weight average approaches are now applied to hybrid quantum mechanics/molecular mechanics MD simulations to predict fast vibrational motions in a protein with a high accuracy for better understanding of molecular functions from atomic structures.

"Simultaneous targeted and non-targeted analysis of per- and polyfluoroalkyl substances in environmental samples by liquid chromatography-ion mobility-quadrupole time of flight-mass spectrometry and mass defect analysis"

Per- and polyfluoroalkyl substances (PFAS) represent a large group of synthetic organic compounds which exhibit unique properties and have been extensively used for consumer and industrial products, resulting in a widespread presence in the environment. Regulation requiring PFAS monitoring has been implemented worldwide due to their potential health and eco-toxicological effects. Targeted methods are commonly used to monitor between twenty to forty PFAS compounds, representing only a small fraction of the number of compounds that may be present. Consequently, there is an increasing interest in complementary non-targeted methods to screen and identify unknown PFAS compounds with the aim to improve knowledge and to generate more accurate models regarding their environmental mobility and persistence. This work details the development of a method that simultaneously provided targeted and non-targeted PFAS analysis. Ultra-high performance liquid chromatography (UHPLC) was coupled to ion mobility-quadrupole time of flight-mass spectrometry (IMS-QTOF-MS) and used to quantify known and screen unknown PFAS in environmental samples collected within the greater Sydney basin (Australia). The method was validated for the quantification of 14 sulfonate-based PFAS, and a non-targeted data analysis workflow was developed using a combination of mass defect analysis with common fragment and neutral loss filtering to identify fluorine-containing species. The optimised method was applied to the environmental samples and enabled the determination of 3-7 compounds from the targeted list and the detection of a further 56-107 untargeted PFAS. This simultaneous analysis reduces the complexity of multiple analyses, and allows for greater interrogation of the full PFAS load in environmental samples.

Effective collisional cross-section of small ions in the gas phase: Application to ion mobility spectrometry

RATIONALE

The observed drift times of monoatomic ions, including alkali metal ions and halide anions, are not fully consistent with their size. When the effect of mass is included through the Mason-Schamp equation, the deviation gets worse so that the trend of the experimental collisional cross-sections becomes completely opposite to what is expected. This is attributed to the stronger local electric field around smaller ions. The strong electric field in the vicinity of a small ion leads to strong ion-neutral interactions and creates a drag force against ion motion. The smaller the ions, the stronger the interaction, because of the higher charge density.

METHODS

In view of this, a modified equation is introduced to describe the relationship between the observed drift times or ion mobilities and the cross-sections of small ions. Here, for small ions with high charge density, the experimental collision cross-section is expressed as the effective collision cross-section, Ω_eff = σ_i (1 + α/r_i ³ ), that takes into account both intrinsic ion size, σ_i , and the ion-molecule interactions through a correction term of α/r_i ³ , which is proportional to the charge density.

RESULTS

A linear fit of the drift times of alkali metal ions and halide anions to the proposed equation showed relative deviations of <8.2%. The model successfully predicted the drift time of other small diatomic ions with reasonable error.

CONCLUSIONS

The proposed model can be used as a simple and efficient relationship in predicting the effective cross-section of small ions.

Broad-spectrum pharmacological activity of Australian propolis and metabolomic-driven identification of marker metabolites of propolis samples from three continents

Propolis is a by-product of honeybee farming known for its broad therapeutic benefits around the world and is extensively used in the health food and beverage industry. Despite Australia being one of the world's megadiverse countries with rich flora and fauna, Australian propolis samples have not been explored adequately with most in vitro and in vivo studies centred on their Brazilian and Chinese counterparts. In view of this, our study was designed to investigate the chemical composition and anti-proliferative, antibacterial, antifungal, anti-inflammatory and antioxidant properties of Australian propolis (AP-1) extract to draw a comparison with Brazilian (BP-1) and Chinese propolis (CP-1) extracts. The AP-1 extract displayed significantly greater anti-proliferative activity against the MCF7 and the MDA-MB-231 metastatic breast adenocarcinoma cell lines compared to BP-1 and CP-1 (p < 0.05). Similar trends were also observed in the antibacterial (Escherichia coli and Staphylococcus aureus), anti-inflammatory (lipopolysaccharide-induced RAW264.7 macrophages) and antioxidant assays (ABTS, DPPH and CUPRAC) with AP-1 exhibiting more potent activity than BP-1 and CP-1. The ultra-high performance liquid chromatography (UPLC) coupled with quadrupole high-resolution time of flight mass spectrometry (qTOF-MS) and chemometrics implementing unsupervised PCA and supervised OPLS-DA analyses of the propolis samples from Australia, China and Brazil revealed 67 key discriminatory metabolites belonging to seven main chemical classes including flavonoids, triterpenes, acid derivatives, stilbenes, steroid derivatives, diterpenes and miscellaneous compounds. Additionally, seven common phenolic compounds were quantified in the samples. Further mechanistic studies are necessary to elucidate the modes of action of Australian propolis for its prospective use in the food, nutraceutical and pharmaceutical industries.

Biochemical characterisation of class III biotin protein ligases from Botrytis cinerea and Zymoseptoria tritici

Biotin protein ligase (BPL) is an essential enzyme in all kingdoms of life, making it a potential target for novel anti-infective agents. Whilst bacteria and archaea have simple BPL structures (class I and II), the homologues from certain eukaryotes such as mammals, insects and yeast (class III) have evolved a more complex structure with a large extension on the N-terminus of the protein in addition to the conserved catalytic domain. The absence of atomic resolution structures of any class III BPL hinders structural and functional analysis of these enzymes. Here, two new class III BPLs from agriculturally important moulds Botrytis cinerea and Zymoseptoria tritici were characterised alongside the homologue from the prototypical yeast Saccharomyces cerevisiae. Circular dichroism and ion mobility-mass spectrometry analysis revealed conservation of the overall tertiary and secondary structures of all three BPLs, corresponding with the high sequence similarity. Subtle structural differences were implied by the different thermal stabilities of the enzymes and their varied Michaelis constants for their interactions with ligands biotin, MgATP, and biotin-accepting substrates from different species. The three BPLs displayed different preferences for fungal versus bacterial protein substrates, providing further evidence that class III BPLs have a 'substrate validation' activity for selecting only appropriate proteins for biotinylation. Selective, potent inhibition of these three BPLs was demonstrated despite sequence and structural homology. This highlights the potential for targeting BPL for novel, selective antifungal therapies against B. cinerea, Z. tritici and other fungal species.

Predicting the Shapes of Protein Complexes through Collision Cross Section Measurements and Database Searches

In structural biology, collision cross sections (CCSs) from ion mobility mass spectrometry (IM-MS) measurements are routinely compared to computationally or experimentally derived protein structures. Here, we investigate whether CCS data can inform about the shape of a protein in the absence of specific reference structures. Analysis of the proteins in the CCS database shows that protein complexes with low apparent densities are structurally more diverse than those with a high apparent density. Although assigning protein shapes purely on CCS data is not possible, we find that we can distinguish oblate- and prolate-shaped protein complexes by using the CCS, molecular weight, and oligomeric states to mine the Protein Data Bank (PDB) for potentially similar protein structures. Furthermore, comparing the CCS of a ferritin cage to the solution structures in the PDB reveals significant deviations caused by structural collapse in the gas phase. We then apply the strategy to an integral membrane protein by comparing the shapes of a prokaryotic and a eukaryotic sodium/proton antiporter homologue. We conclude that mining the PDB with IM-MS data is a time-effective way to derive low-resolution structural models.