To What Extent is FAIMS Beneficial in the Analysis of Proteins?

Improved detection of tryptic immunoglobulin variable region peptides by chromatographic and gas-phase fractionation techniques

The polyclonal repertoire of circulating antibodies potentially holds valuable information about an individual's humoral immune state. While bottom-up proteomics is well suited for serum proteomics, the vast number of antibodies and dynamic range of serum challenge this analysis. To acquire the serum proteome more comprehensively, we incorporated high-field asymmetric waveform ion-mobility spectrometry (FAIMS) or two-dimensional chromatography into standard trypsin-based bottom-up proteomics. Thereby, the number of variable region (VR)-related spectra increased 1.7-fold with FAIMS and 10-fold with chromatography fractionation. To match antibody VRs to spectra, we combined de novo searching and BLAST alignment. Validation of this approach showed that, as peptide length increased, the de novo accuracy decreased and BLAST performance increased. Through in silico calculations on antibody repository sequences, we determined the uniqueness of tryptic VR peptides and their suitability as antibody surrogate. Approximately one-third of these peptides were unique, and about one-third of all antibodies contained at least one unique peptide.

Plasma/Serum Proteomics based on Mass Spectrometry

Human blood is a window of physiology and disease. Examination of biomarkers in blood is a common clinical procedure, which can be informative in diagnosis and prognosis of diseases, and in evaluating treatment effectiveness. There is still a huge demand on new blood biomarkers and assays for precision medicine nowadays, therefore plasma/serum proteomics has attracted increasing attention in recent years. How to effectively proceed with the biomarker discovery and clinical diagnostic assay development is a question raised to researchers who are interested in this area. In this review, we comprehensively introduce the background and advancement of technologies for blood proteomics, with a focus on mass spectrometry (MS). Analyzing existing blood biomarkers and newly-built diagnostic assays based on MS can shed light on developing new biomarkers and analytical methods. We summarize various protein analytes in plasma/serum which include total proteome, protein post-translational modifications, and extracellular vesicles, focusing on their corresponding sample preparation methods for MS analysis. We propose screening multiple protein analytes in the same set of blood samples in order to increase success rate for biomarker discovery. We also review the trends of MS techniques for blood tests including sample preparation automation, and further provide our perspectives on their future directions.

High-Throughput Analyses of Therapeutic Antibodies Using High-Field Asymmetric Waveform Ion Mobility Spectrometry Combined with SampleStream and Intact Protein Mass Spectrometry

Intact protein mass spectrometry (MS) coupled with liquid chromatography was applied to characterize the pharmacokinetics and stability profiles of therapeutic proteins. However, limitations from chromatography, including throughput and carryover, result in challenges with handling large sample numbers. Here, we combined intact protein MS with multiple front-end separations, including affinity capture, SampleStream, and high-field asymmetric waveform ion mobility spectrometry (FAIMS), to perform high-throughput and specific mass measurements of a multivalent antibody with one antigen-binding fragment (Fab) fused to an immunoglobulin G1 (IgG1) antibody. Generic affinity capture ensures the retention of both intact species 1Fab-IgG1 and the tentative degradation product IgG1. Subsequently, the analytes were directly loaded into SampleStream, where each injection occurs within ∼30 s. By separating ions prior to MS detection, FAIMS further offered improvement in signal-overnoise by ∼30% for denatured protein MS via employing compensation voltages that were optimized for different antibody species. When enhanced FAIMS transmission of 1Fab-IgG1 was employed, a qualified assay was established for spiked-in serum samples between 0.1 and 25 μg/mL, resulting in ∼10% accuracy bias and precision coefficient of variation. Selective FAIMS transmission of IgG1 as the degradation surrogate product enabled more sensitive detection of clipped species for intact 1Fab-IgG1 at 5 μg/mL in serum, generating an assay to measure 1Fab-IgG1 truncation between 2.5 and 50% with accuracy and precision below 20% bias and coefficient of variation. Our results revealed that the SampleStream-FAIMS-MS platform affords high throughput, selectivity, and sensitivity for characterizing therapeutic antibodies from complex biomatrices qualitatively and quantitatively.

Benefits of FAIMS to Improve the Proteome Coverage of Deteriorated and/or Cross-Linked TMT 10-Plex FFPE Tissue and Plasma-Derived Exosomes Samples

The proteome characterization of complex, deteriorated, or cross-linked protein mixtures as paired clinical FFPE or exosome samples isolated from low plasma volumes (250 µL) might be a challenge. In this work, we aimed at investigating the benefits of FAIMS technology coupled to the Orbitrap Exploris 480 mass spectrometer for the TMT quantitative proteomics analyses of these complex samples in comparison to the analysis of protein extracts from cells, frozen tissue, and exosomes isolated from large volume plasma samples (3 mL). TMT experiments were performed using a two-hour gradient LC-MS/MS with or without FAIMS and two compensation voltages (CV = -45 and CV = -60). In the TMT experiments of cells, frozen tissue, or exosomes isolated from large plasma volumes (3 mL) with FAIMS, a limited increase in the number of identified and quantified proteins accompanied by a decrease in the number of peptides identified and quantified was observed. However, we demonstrated here a noticeable improvement (>100%) in the number of peptide and protein identifications and quantifications for the plasma exosomes isolated from low plasma volumes (250 µL) and FFPE tissue samples in TMT experiments with FAIMS in comparison to the LC-MS/MS analysis without FAIMS. Our results highlight the potential of mass spectrometry analyses with FAIMS to increase the depth into the proteome of complex samples derived from deteriorated, cross-linked samples and/or those where the material was scarce, such as FFPE and plasma-derived exosomes from low plasma volumes (250 µL), which might aid in the characterization of their proteome and proteoforms and in the identification of dysregulated proteins that could be used as biomarkers.

Mass spectrometry-based proteomics as an emerging tool in clinical laboratories

Mass spectrometry (MS)-based proteomics have been increasingly implemented in various disciplines of laboratory medicine to identify and quantify biomolecules in a variety of biological specimens. MS-based proteomics is continuously expanding and widely applied in biomarker discovery for early detection, prognosis and markers for treatment response prediction and monitoring. Furthermore, making these advanced tests more accessible and affordable will have the greatest healthcare benefit.This review article highlights the new paradigms MS-based clinical proteomics has created in microbiology laboratories, cancer research and diagnosis of metabolic disorders. The technique is preferred over conventional methods in disease detection and therapy monitoring for its combined advantages in multiplexing capacity, remarkable analytical specificity and sensitivity and low turnaround time.Despite the achievements in the development and adoption of a number of MS-based clinical proteomics practices, more are expected to undergo transition from bench to bedside in the near future. The review provides insights from early trials and recent progresses (mainly covering literature from the NCBI database) in the application of proteomics in clinical laboratories.

High-Field Asymmetric Waveform Ion Mobility Spectrometry Analysis of Carcinogenic Aromatic Amines in Tobacco Smoke with an Orbitrap Tribrid Mass Spectrometer

Smoking is a risk factor for bladder cancer (BC), although the specific chemicals responsible for BC remain uncertain. Considerable research has focused on aromatic amines (AAs), including o-toluidine (o-tol), o-anisidine (o-anis), 2-naphthylamine (2-NA), and 4-aminobiphenyl (4-ABP), which are linked to human BC based on elevated BC incidence in occupationally exposed factory workers. These AAs arise at nanogram levels per combusted cigarette. The unambiguous identification of AAs, particularly low-molecular-weight monocyclic AAs in tobacco smoke extracts, by liquid chromatography-mass spectrometry (LC-MS) is challenging due to their poor performance on reversed-phase columns and co-elution with isobaric interferences from the complex tobacco smoke matrix. We employed a tandem liquid-liquid and solid-phase extraction method to isolate AAs from the basic fraction of tobacco smoke condensate (TSC) and utilized high-field asymmetric waveform ion mobility spectrometry (FAIMS) coupled to high-resolution accurate mass (HRAM) Orbitrap LC-MS2 to assay AAs in TSC. The employment of FAIMS greatly reduced sample complexity by removing precursor co-isolation interfering species at the MS1 scan stage, resulting in dramatically improved signal-to-noise of the precursor ions and cleaner, high-quality MS2 spectra for unambiguous identification and quantification of AAs in TSC. We demonstrate the power of LC/FAIMS/MS2 by characterizing and quantifying two low-molecular-weight carcinogenic AAs, o-tol and o-anis, in TSC, using stable isotopically labeled internal standards. These results demonstrate the power of FAIMS in trace-level analyses of AA carcinogens in the complex tobacco smoke matrix.

Coupling High-Field Asymmetric Waveform Ion Mobility Spectrometry with Capillary Zone Electrophoresis-Tandem Mass Spectrometry for Top-Down Proteomics

Capillary zone electrophoresis-tandem mass spectrometry (CZE-MS/MS) has emerged as an essential technique for top-down proteomics (TDP), providing superior separation efficiency and high detection sensitivity for proteoform analysis. Here, we aimed to further enhance the performance of CZE-MS/MS for TDP via coupling online gas-phase proteoform fractionation using high-field asymmetric waveform ion mobility spectrometry (FAIMS). When the compensation voltage (CV) of FAIMS was changed from -50 to 30 V, the median mass of identified proteoforms increased from less than 10 kDa to about 30 kDa, suggesting that FAIMS can efficiently fractionate proteoforms by their size. CZE-FAIMS-MS/MS boosted the number of proteoform identifications from a yeast sample by nearly 3-fold relative to CZE-MS/MS alone. It particularly benefited the identification of relatively large proteoforms, improving the number of proteoforms in a mass range of 20-45 kDa by 6-fold compared to CZE-MS/MS alone. FAIMS fractionation gained nearly 20-fold better signal-to-noise ratios of randomly selected proteoforms than no FAIMS. We expect that CZE-FAIMS-MS/MS will be a useful tool for further advancing the sensitivity and coverage of TDP. This work shows the first example of coupling CE with ion mobility spectrometry (IMS) for TDP.

High-Field Asymmetric Waveform Ion Mobility Spectrometry: Practical Alternative for Cardiac Proteome Sample Processing

Heart tissue sample preparation for mass spectrometry (MS) analysis that includes prefractionation reduces the cellular protein dynamic range and increases the relative abundance of nonsarcomeric proteins. We previously described "IN-Sequence" (IN-Seq) where heart tissue lysate is sequentially partitioned into three subcellular fractions to increase the proteome coverage more than a single direct tissue analysis by mass spectrometry. Here, we report an adaptation of the high-field asymmetric ion mobility spectrometry (FAIMS) coupled to mass spectrometry, and the establishment of a simple one step sample preparation coupled with gas-phase fractionation. The FAIMS approach substantially reduces manual sample handling, significantly shortens the MS instrument processing time, and produces unique protein identification and quantification approximating the commonly used IN-Seq method in less time.

CaptiveSpray Differential Ion Mobility Spectrometry Device with Enhanced Ion Transmission and Improved Resolving Power

A performance enhanced CaptiveSpray differential ion mobility device was designed and constructed by incorporating a circular channel and a gas flow homogenizing channel (GFHC) between the CaptiveSpray ion source and planar differential ion mobility spectrometry (DMS). The GFHC was used to reduce gas flow heterogeneity prior to the entrance of the DMS device. The optimal flared entrance greatly reduces gas flow velocity at the inlet region owing to its relatively large gas inlet interface, which assists in reducing disparities between the minimum and maximum gas velocity along the x-axis. The circular electrode was machined with channels along the x- and y-axis for the passage of auxiliary gas and was applied with a potential to focus the incoming ions from the CaptiveSpray source into the DMS channel. Using reserpine as a reference standard, substantial signal enhancement was achieved with a concomitant reduction of the peak width in the ionogram.

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.

Don't let go: co-fractionation mass spectrometry for untargeted mapping of protein-metabolite interactomes

The chemical complexity of metabolomes goes hand in hand with their functional diversity. Small molecules have many essential roles, many of which are executed by binding and modulating the function of a protein partner. The complex and dynamic protein-metabolite interaction (PMI) network underlies most if not all biological processes, but remains under-characterized. Herein, we highlight how co-fractionation mass spectrometry (CF-MS), a well-established approach to map protein assemblies, can be used for proteome and metabolome identification of the PMIs. We will review recent CF-MS studies, discuss the main advantages and limitations, summarize the available CF-MS guidelines, and outline future challenges and opportunities.

Coupling High-Field Asymmetric Ion Mobility Spectrometry with Capillary Electrophoresis-Electrospray Ionization-Tandem Mass Spectrometry Improves Protein Identifications in Bottom-Up Proteomic Analysis of Low Nanogram Samples

In this work, we pioneered the assessment of coupling high-field asymmetric waveform ion mobility spectrometry (FAIMS) with ultrasensitive capillary electrophoresis hyphenated with tandem mass spectrometry (CE-MS/MS) to achieve deeper proteome coverage of low nanogram amounts of digested cell lysates. An internal stepping strategy using three or four compensation voltages per analytical run with varied cycle times was tested to determine optimal FAIMS settings and MS parameters for the CE-FAIMS-MS/MS method. The optimized method applied to bottom-up proteomic analysis of 1 ng of HeLa protein digest standard identified 1314 ± 30 proteins, 4829 ± 200 peptide groups, and 7577 ± 163 peptide spectrum matches (PSMs) corresponding to a 16, 25, and 22% increase, respectively, over CE-MS/MS alone, without FAIMS. Furthermore, the percentage of acquired MS/MS spectra that resulted in PSMs increased nearly 2-fold with CE-FAIMS-MS/MS. Label-free quantitation of proteins and peptides was also assessed to determine the precision of replicate analyses from FAIMS methods with increased cycle times. Our results also identified from 1 ng of HeLa protein digest without any prior enrichment 76 ± 9 phosphopeptides, 18% of which were multiphosphorylated. These results represent a 46% increase in phosphopeptide identifications over the control experiments without FAIMS yielding 2.5-fold more multiphosphorylated peptides.

A proteomic and RNA-seq transcriptomic dataset of capsaicin-aggravated mouse chronic colitis model

An inappropriate diet is a risk factor for inflammatory bowel disease (IBD). It is established that the consumption of spicy food containing capsaicin is strongly associated with the recurrence and worsening of IBD symptoms. Moreover, capsaicin can induce neutrophil accumulation in the lamina propria, contributing to disease deterioration. To uncover the potential signaling pathway involved in capsaicin-induced relapse and the effects of capsaicin on neutrophil activation, we performed proteomic analyses of intestinal tissues from chronic colitis mice following capsaicin administration and transcriptomic analyses of dHL-60 cells after capsaicin stimulation. Collectively, these multiomic analyses identified proteins and genes that may be involved in disease flares, thereby providing new insights for future research.

The hitchhiker's guide to dynamic ion-solvent clustering: applications in differential ion mobility spectrometry

This article highlights the fundamentals of ion-solvent clustering processes that are pertinent to understanding an ion's behaviour during differential mobility spectrometry (DMS) experiments. We contrast DMS with static-field ion mobility, where separation is affected by mobility differences under the high-field and low-field conditions of an asymmetric oscillating electric field. Although commonly used in mass spectrometric (MS) workflows to enhance signal-to-noise ratios and remove isobaric contaminants, the chemistry and physics that underpins the phenomenon of differential mobility has yet to be fully fleshed out. Moreover, we are just now making progress towards understanding how the DMS separation waveform creates a dynamic clustering environment when the carrier gas is seeded with the vapour of a volatile solvent molecule (e.g., methanol). Interestingly, one can correlate the dynamic clustering behaviour observed in DMS experiments with gas-phase and solution-phase molecular properties such as hydrophobicity, acidity, and solubility. However, to create a generalized, global model for property determination using DMS data one must employ machine learning. In this article, we provide a first-principles description of differential ion mobility in a dynamic clustering environment. We then discuss the correlation between dynamic clustering propensity and analyte physicochemical properties and demonstrate that analytes exhibiting similar ion-solvent interactions (e.g., charge-dipole) follow well-defined trends with respect to DMS clustering behaviour. Finally, we describe how supervised machine learning can be used to create predictive models of molecular properties using DMS data. We additionally highlight open questions in the field and provide our perspective on future directions that can be explored.

The addition of FAIMS increases targeted proteomics sensitivity from FFPE tumor biopsies

Mass spectrometry-based targeted proteomics allows objective protein quantitation of clinical biomarkers from a single section of formalin-fixed, paraffin-embedded (FFPE) tumor tissue biopsies. We combined high-field asymmetric waveform ion mobility spectrometry (FAIMS) and parallel reaction monitoring (PRM) to increase assay sensitivity. The modular nature of the FAIMS source allowed direct comparison of the performance of FAIMS-PRM to PRM. Limits of quantitation were determined by spiking synthetic peptides into a human spleen matrix. In addition, 20 clinical samples were analyzed using FAIMS-PRM and the quantitation of HER2 was compared with that obtained with the Ventana immunohistochemistry assay. FAIMS-PRM improved the overall signal-to-noise ratio over that from PRM and increased assay sensitivity in FFPE tissue analysis for four (HER2, EGFR, cMET, and KRAS) of five proteins of clinical interest. FAIMS-PRM enabled sensitive quantitation of basal HER2 expression in breast cancer samples classified as HER2 negative by immunohistochemistry. Furthermore, we determined the degree of FAIMS-dependent background reduction and showed that this correlated with an improved lower limit of quantitation with FAIMS. FAIMS-PRM is anticipated to benefit clinical trials in which multiple biomarker questions must be addressed and the availability of tumor biopsy samples is limited.

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.

Leveraging Parameter Dependencies in High-Field Asymmetric Waveform Ion-Mobility Spectrometry and Size Exclusion Chromatography for Proteome-wide Cross-Linking Mass Spectrometry

Ion-mobility spectrometry shows great promise to tackle analytically challenging research questions by adding another separation dimension to liquid chromatography-mass spectrometry. The understanding of how analyte properties influence ion mobility has increased through recent studies, but no clear rationale for the design of customized experimental settings has emerged. Here, we leverage machine learning to deepen our understanding of field asymmetric waveform ion-mobility spectrometry for the analysis of cross-linked peptides. Knowing that predominantly m/z and then the size and charge state of an analyte influence the separation, we found ideal compensation voltages correlating with the size exclusion chromatography fraction number. The effect of this relationship on the analytical depth can be substantial as exploiting it allowed us to almost double unique residue pair detections in a proteome-wide cross-linking experiment. Other applications involving liquid- and gas-phase separation may also benefit from considering such parameter dependencies.

Improved Identification of Proteoforms in Top-Down Proteomics Using FAIMS with Internal CV Stepping

In top-down (TD) proteomics, prefractionation prior to mass spectrometric (MS) analysis is a crucial step for both the high confidence identification of proteoforms and increased proteome coverage. In addition to liquid-phase separations, gas-phase fractionation strategies such as field asymmetric ion mobility spectrometry (FAIMS) have been shown to be highly beneficial in TD proteomics. However, so far, only external compensation voltage (CV) stepping has been demonstrated for TD proteomics, i.e., single CVs were applied for each run. Here, we investigated the use of internal CV stepping (multiple CVs per acquisition) for single-shot TD analysis, which has huge advantages in terms of measurement time and the amount of sample required. In addition, MS parameters were optimized for the individual CVs since different CVs target certain mass ranges. For example, small proteoforms identified mainly with more negative CVs can be identified with lower resolution and number of microscans than larger proteins identified primarily via less negative CVs. We investigated the optimal combination and number of CVs for different gradient lengths and validated the optimized settings with the low-molecular-weight proteome of CaCo-2 cells obtained using a range of different sample preparation techniques. Compared to measurements without FAIMS, both the number of identified protein groups (+60-94%) and proteoforms (+46-127%) and their confidence were significantly increased, while the measurement time remained identical. In total, we identified 684 protein groups and 2675 proteoforms from CaCo-2 cells in less than 24 h using the optimized multi-CV method.

Mapping Protein Structural Evolution upon Unfolding

In the past, many intensive attempts failed to capture or underestimated the copopulated intermediate conformers from the protein folding/unfolding reaction. We report a promising approach to kinetically trap, resolve, and quantify protein conformers that evolve during unfolding in solution. We conducted acid-induced unfolding of three model proteins (cytochrome c, myoglobin, and lysozyme), and the corresponding reaction aliquots upon decreasing the pH were electrosprayed for high field asymmetric waveform ion mobility spectrometry (FAIMS) measurements. The copopulated conformers were resolved, visualized, and quantified by a two-dimensional mapping of the FAIMS output. Contrary to expectations, all the above proteins appeared metamorphic (multiple-folded conformations) at the physiological pH, and cytochrome c exhibited an unusual "conformational shuttling" before forming the molten globule state. Thus, in contrast to many previous studies, a wide variety of thermodynamically stable intermediate conformers, including compact, molten globule, and partially unfolded forms, was trapped from solution, probing the unfolding mechanism in detail.

Predicting ion mobility as a function of the electric field for small ions in light gases

High resolution mobility devices such as Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) and Differential Mobility spectrometers (DMS) use strong electric fields to gas concentration ratios, E/N, to separate ions in the gas phase. While extremely successful, their empirical results show a non-linear, ion-dependent relation between mobility K and E/N that is difficult to characterize. The one-temperature theory Mason-Schamp equation, which is the most widely used ion mobility equation, unfortunately, cannot capture this behavior. When the two-temperature theory is used, it can be shown that the K-E/N behavior can be followed quite closely numerically by equating the effect of increasing the field to an increase in the ion temperature. This is attempted here for small ions in a Helium gas environment showing good agreement over the whole field range. To improve the numerical characterization, the Lennard-Jones (L-J) potentials may be optimized. This is attempted for Carbon, Hydrogen, Oxygen and Nitrogen at different degrees of theory up to the fourth approximation, which is assumed to be exact. The optimization of L-J improves the accuracy yielding errors of about 3% on average. The fact that a constant set of L-J potentials work for the whole range of E/N and for several molecules, also suggests that inelastic collisions can be circumvented in calculations for He. The peculiar K-E/N hump behaviors are studied, and whether mobility increases or decreases with E/N is shown to derive from a competition between relative kinetic energy and the interaction potentials.

Ion Mobility Spectrometry of Superheated Macromolecules at Electric Fields up to 500 Td

Since its inception in 1980s, differential or field asymmetric waveform ion mobility spectrometry (FAIMS) has been implemented at or near ambient gas pressure. We recently developed FAIMS at 15-30 Torr with mass spectrometry and utilized it to analyze amino acids, isomeric peptides, and protein conformers. The separations broadly mirrored those at atmospheric pressure, save for larger proteins that (as predicted) exhibited dipole alignment at ambient but not low pressure. Here we reduce the pressure down to 4.7 Torr, allowing normalized electric fields up to 543 Td-double the maximum in prior FAIMS or IMS studies of polyatomic ions. Despite the collisional heating to ∼1000 °C at the waveform peaks, the proteins of size from ubiquitin to albumin survived intact. The dissociation of macromolecules in FAIMS appears governed by the average ion temperature over the waveform cycle, unlike the isomerization controlled by the peak temperature. The global separation trends in this "superhot" regime extend those at moderately low pressures, with distinct conformers and no alignment as theorized. Although the scaling of the compensation voltage with the field fell below cubic at lower fields, the resolving power increased and the resolution of different proteins or charge states substantially improved.

Systematic Identification of Proteins Binding with Cisplatin in Blood by Affinity Chromatography and a Four-Dimensional Proteomic Method

Cisplatin is widely used for the treatment of various solid tumors. It is mainly administered by intravenous injection, and a substantial amount of the drug will bind to plasma proteins, a feature that is closely related to its pharmacokinetics, activity, toxicity, and side effects. However, due to the unique properties of platinum complexes and the complexity of the blood proteome, existing methods cannot systematically identify the binding proteome of cisplatin in blood. In this study, high-abundance protein separation and an ion mobility mass spectrometry-based 4D proteomic method were combined to systematically and comprehensively identify the binding proteins of cisplatin in blood. The characteristic isotope patterns of platinated peptides and a similarity algorithm were utilized to eliminate false-positive identification. Finally, 39 proteins were found to be platinated. Bioinformatics analysis showed that the identified proteins were mainly involved in the complement and coagulation cascade pathways. The binding ratio of some peptides with cisplatin was measured based on the area ratio of the free peptide using the parallel reaction monitoring method. This study provides a new method for systematically identifying binding proteins of metal drugs in blood, and the identified proteins might be helpful for understanding the toxicity of platinum anticancer drugs.

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.

Deeper Protein Identification Using Field Asymmetric Ion Mobility Spectrometry in Top-Down Proteomics

Field asymmetric ion mobility spectrometry (FAIMS), when used in proteomics studies, provides superior selectivity and enables more proteins to be identified by providing additional gas-phase separation. Here, we tested the performance of cylindrical FAIMS for the identification and characterization of proteoforms by top-down mass spectrometry of heterogeneous protein mixtures. Combining FAIMS with chromatographic separation resulted in a 62% increase in protein identifications, an 8% increase in proteoform identifications, and an improvement in proteoform identification compared to samples analyzed without FAIMS. In addition, utilization of FAIMS resulted in the identification of proteins encoded by lower-abundance mRNA transcripts. These improvements were attributable, in part, to improved signal-to-noise for proteoforms with similar retention times. Additionally, our results show that the optimal compensation voltage of any given proteoform was correlated with the molecular weight of the analyte. Collectively these results suggest that the addition of FAIMS can enhance top-down proteomics in both discovery and targeted applications.

The Charge-State and Structural Stability of Peptides Conferred by Microsolvating Environments in Differential Mobility Spectrometry

The presence of solvent vapor in a differential mobility spectrometry (DMS) cell creates a microsolvating environment that can mitigate complications associated with field-induced heating. In the case of peptides, the microsolvation of protonation sites results in a stabilization of charge density through localized solvent clustering, sheltering the ion from collisional activation. Seeding the DMS carrier gas (N₂) with a solvent vapor prevented nearly all field-induced fragmentation of the protonated peptides GGG, AAA, and the Lys-rich Polybia-MP1 (IDWKKLLDAAKQIL-NH₂). Modeling the microsolvation propensity of protonated n-propylamine [PrNH₃]⁺, a mimic of the Lys side chain and N-terminus, with common gas-phase modifiers (H₂O, MeOH, EtOH, iPrOH, acetone, and MeCN) confirms that all solvent molecules form stable clusters at the site of protonation. Moreover, modeling populations of microsolvated clusters indicates that species containing protonated amine moieties exist as microsolvated species with one to six solvent ligands at all effective ion temperatures (T_eff) accessible during a DMS experiment (ca. 375-600 K). Calculated T_eff of protonated GGG, AAA, and Polybia-MPI using a modified two-temperature theory approach were up to 86 K cooler in DMS environments seeded with solvent vapor compared to pure N₂ environments. Stabilizing effects were largely driven by an increase in the ion's apparent collision cross section and by evaporative cooling processes induced by the dynamic evaporation/condensation cycles incurred in the presence of an oscillating electric separation field. When the microsolvating partner was a protic solvent, abstraction of a proton from [MP1 + 3H]³⁺ to yield [MP1 + 2H]²⁺ was observed. This result was attributed to the proclivity of protic solvents to form hydrogen-bond networks with enhanced gas-phase basicity. Collectively, microsolvation provides analytes with a solvent "air bag," whereby charge reduction and microsolvation-induced stabilization were shown to shelter peptides from the fragmentation induced by field heating and may play a role in preserving native-like ion configurations.

Global Phosphoproteome Analysis Using High-Field Asymmetric Waveform Ion Mobility Spectrometry on a Hybrid Orbitrap Mass Spectrometer

Mass spectrometry is the premier tool for identifying and quantifying protein phosphorylation on a global scale. Analysis of phosphopeptides requires enrichment, and even after the samples remain highly complex and exhibit broad dynamic range of abundance. Achieving maximal depth of coverage for phosphoproteomics therefore typically necessitates offline liquid chromatography prefractionation, a time-consuming and laborious approach. Here, we incorporate a recently commercialized aerodynamic high-field asymmetric waveform ion mobility spectrometry (FAIMS) device into the phosphoproteomic workflow. We characterize the effects of phosphorylation on the FAIMS separation, describe optimized compensation voltage settings for unlabeled phosphopeptides, and demonstrate the advantages of FAIMS-enabled gas-phase fractionation. Standard FAIMS single-shot analyses identified around 15-20% additional phosphorylation sites than control experiments without FAIMS. In comparison to liquid chromatography prefractionation, FAIMS experiments yielded similar or superior results when analyzing up to four discrete gas-phase fractions. Although using FAIMS led to a modest reduction in the precision of quantitative measurements when using label-free approaches, the data collected with FAIMS yielded a 26% increase in total reproducible measurements. Overall, we conclude that the new FAIMS technology is a valuable addition to any phosphoproteomic workflow, with greater benefits emerging from longer analyses and higher amounts of material.

Improved Sensitivity of Ultralow Flow LC-MS-Based Proteomic Profiling of Limited Samples Using Monolithic Capillary Columns and FAIMS Technology

In this work, we pioneered a combination of ultralow flow (ULF) high-efficiency ultranarrow bore monolithic LC columns coupled to MS via a high-field asymmetric waveform ion mobility spectrometry (FAIMS) interface to evaluate the potential applicability for high sensitivity, robust, and reproducible proteomic profiling of low nanogram-level complex biological samples. As a result, ULF LC-FAIMS-MS brought unprecedented sensitivity levels and high reproducibility in bottom-up proteomic profiling. In addition, FAIMS improved the dynamic range, signal-to-noise ratios, and detection limits in ULF LC-MS-based measurements by significantly reducing chemical noise in comparison to the conventional nanoESI interface used with the same ULF LC-MS setup. Two, three, or four compensation voltages separated by at least 15 V were tested within a single LC-MS run using the FAIMS interface. The optimized ULF LC-ESI-FAIMS-MS/MS conditions resulted in identification of 2,348 ± 42 protein groups, 10,062 ± 285 peptide groups, and 15,734 ± 350 peptide-spectrum matches for 1 ng of a HeLa digest, using a 1 h gradient at the flow rate of 12 nL/min, which represents an increase by 38%, 91%, and 131% in respective identifications, as compared to the control experiment (without FAIMS). To evaluate the practical utility of the ULF LC-ESI-FAIMS-MS platform in proteomic profiling of limited samples, approximately 100, 1,000, and 10,000 U937 myeloid leukemia cells were processed, and a one-tenth of each sample was analyzed. Using the optimized conditions, we were able to reliably identify 251 ± 54, 1,135 ± 80, and 2,234 ± 25 protein groups from injected aliquots corresponding to ∼10, 100, and 1,000 processed cells.

Recent advances in mass spectrometry based clinical proteomics: applications to cancer research

Cancer biomarkers have transformed current practices in the oncology clinic. Continued discovery and validation are crucial for improving early diagnosis, risk stratification, and monitoring patient response to treatment. Profiling of the tumour genome and transcriptome are now established tools for the discovery of novel biomarkers, but alterations in proteome expression are more likely to reflect changes in tumour pathophysiology. In the past, clinical diagnostics have strongly relied on antibody-based detection strategies, but these methods carry certain limitations. Mass spectrometry (MS) is a powerful method that enables increasingly comprehensive insights into changes of the proteome to advance personalized medicine. In this review, recent improvements in MS-based clinical proteomics are highlighted with a focus on oncology. We will provide a detailed overview of clinically relevant samples types, as well as, consideration for sample preparation methods, protein quantitation strategies, MS configurations, and data analysis pipelines currently available to researchers. Critical consideration of each step is necessary to address the pressing clinical questions that advance cancer patient diagnosis and prognosis. While the majority of studies focus on the discovery of clinically-relevant biomarkers, there is a growing demand for rigorous biomarker validation. These studies focus on high-throughput targeted MS assays and multi-centre studies with standardized protocols. Additionally, improvements in MS sensitivity are opening the door to new classes of tumour-specific proteoforms including post-translational modifications and variants originating from genomic aberrations. Overlaying proteomic data to complement genomic and transcriptomic datasets forges the growing field of proteogenomics, which shows great potential to improve our understanding of cancer biology. Overall, these advancements not only solidify MS-based clinical proteomics' integral position in cancer research, but also accelerate the shift towards becoming a regular component of routine analysis and clinical practice.

Identification of Plasmodium falciparum proteoforms from liver stage models

BACKGROUND

Immunization with attenuated malaria sporozoites protects humans from experimental malaria challenge by mosquito bite. Protection in humans is strongly correlated with the production of T cells targeting a heterogeneous population of pre-erythrocyte antigen proteoforms, including liver stage antigens. Currently, few T cell epitopes derived from Plasmodium falciparum, the major aetiologic agent of malaria in humans are known.

METHODS

In this study both in vitro and in vivo malaria liver stage models were used to sequence host and pathogen proteoforms. Proteoforms from these diverse models were subjected to mild acid elution (of soluble forms), multi-dimensional fractionation, tandem mass spectrometry, and top-down bioinformatics analysis to identify proteoforms in their intact state.

RESULTS

These results identify a group of host and malaria liver stage proteoforms that meet a 5% false discovery rate threshold.

CONCLUSIONS

This work provides proof-of-concept for the validity of this mass spectrometry/bioinformatic approach for future studies seeking to reveal malaria liver stage antigens towards vaccine development.

Ion Mobility Spectrometry: Fundamental Concepts, Instrumentation, Applications, and the Road Ahead

Ion mobility spectrometry (IMS) is a rapid separation technique that has experienced exponential growth as a field of study. Interfacing IMS with mass spectrometry (IMS-MS) provides additional analytical power as complementary separations from each technique enable multidimensional characterization of detected analytes. IMS separations occur on a millisecond timescale, and therefore can be readily nested into traditional GC and LC/MS workflows. However, the continual development of novel IMS methods has generated some level of confusion regarding the advantages and disadvantages of each. In this critical insight, we aim to clarify some common misconceptions for new users in the community pertaining to the fundamental concepts of the various IMS instrumental platforms (i.e., DTIMS, TWIMS, TIMS, FAIMS, and DMA), while addressing the strengths and shortcomings associated with each. Common IMS-MS applications are also discussed in this review, such as separating isomeric species, performing signal filtering for MS, and incorporating collision cross-section (CCS) values into both targeted and untargeted omics-based workflows as additional ion descriptors for chemical annotation. Although many challenges must be addressed by the IMS community before mobility information is collected in a routine fashion, the future is bright with possibilities.

Direct measurement of light and heavy antibody chains using ion mobility and middle-down mass spectrometry

The analysis of monoclonal antibodies (mAbs) by a middle-down mass spectrometry (MS) approach is a growing field that attracts the attention of many researchers and biopharmaceutical companies. Usually, liquid fractionation techniques are used to separate mAbs polypeptides chains before MS analysis. Gas-phase fractionation techniques such as high-field asymmetric waveform ion mobility spectrometry (FAIMS) can replace liquid-based separations and reduce both analysis time and cost. Here, we present a rapid FAIMS tandem MS method capable of characterizing the polypeptide sequence of mAbs light and heavy chains in an unprecedented, easy, and fast fashion. This new method uses commercially available instruments and takes ~24 min, which is 40-60% faster than regular liquid chromatography-MS/MS analysis, to acquire fragmentation data using different dissociation methods.

Proteome Imaging: From Classic to Modern Mass Spectrometry-Based Molecular Histology

In order to overcome the limitations of classic imaging in Histology during the actually era of multiomics, the multi-color "molecular microscope" by its emerging "molecular pictures" offers quantitative and spatial information about thousands of molecular profiles without labeling of potential targets. Healthy and diseased human tissues, as well as those of diverse invertebrate and vertebrate animal models, including genetically engineered species and cultured cells, can be easily analyzed by histology-directed MALDI imaging mass spectrometry. The aims of this review are to discuss a range of proteomic information emerging from MALDI mass spectrometry imaging comparative to classic histology, histochemistry and immunohistochemistry, with applications in biology and medicine, concerning the detection and distribution of structural proteins and biological active molecules, such as antimicrobial peptides and proteins, allergens, neurotransmitters and hormones, enzymes, growth factors, toxins and others. The molecular imaging is very well suited for discovery and validation of candidate protein biomarkers in neuroproteomics, oncoproteomics, aging and age-related diseases, parasitoproteomics, forensic, and ecotoxicology. Additionally, in situ proteome imaging may help to elucidate the physiological and pathological mechanisms involved in developmental biology, reproductive research, amyloidogenesis, tumorigenesis, wound healing, neural network regeneration, matrix mineralization, apoptosis and oxidative stress, pain tolerance, cell cycle and transformation under oncogenic stress, tumor heterogeneity, behavior and aggressiveness, drugs bioaccumulation and biotransformation, organism's reaction against environmental penetrating xenobiotics, immune signaling, assessment of integrity and functionality of tissue barriers, behavioral biology, and molecular origins of diseases. MALDI MSI is certainly a valuable tool for personalized medicine and "Eco-Evo-Devo" integrative biology in the current context of global environmental challenges.

Performance Enhancements in Differential Ion Mobility Spectrometry-Mass Spectrometry (DMS-MS) by Using a Modified CaptiveSpray Source

Differential ion mobility spectrometry (DMS) spatially separates ions in the gas phase using the mobility differences of the ions under applied low and high electric fields. The use of DMS as an ion filter (or ion selector) prior to mass spectrometry analysis has been compromised by the limited ion transmission efficiency. This paper reports enhancement of the DMS-MS sensitivity and signal stability using a modified CaptiveSpray™ source. In terms of the ion sampling and transmission efficiency, the modified CaptiveSpray source swept ~ 89% of the ions generated by the tapered capillary through the DMS device (compared to ~ 10% with a conventional microspray source). The signal fluctuation improved from 11.7% (relative standard deviation, RSD) with microspray DMS-MS to 3.6% using CaptiveSpray-DMS-MS. Coupling of LC to DMS-MS via the modified CaptiveSpray source was simple and robust. Using DMS as a noise-filtering device, LC-DMS-MS performed better than conventional LC-MS for analyzing a BSA digest standard. Although LC-DMS-MS had a lower sequence coverage (55%), a higher Mascot score (283) was obtained compared to those of LC-MS (sequence coverage 65%; Mascot score 192) under the same elution conditions. The improvement in the confidence of the search result was attributed to the preferential elimination of noise ions. Graphical Abstract ᅟ.

Comprehensive Single-Shot Proteomics with FAIMS on a Hybrid Orbitrap Mass Spectrometer

Liquid chromatography (LC) prefractionation is often implemented to increase proteomic coverage; however, while effective, this approach is laborious, requires considerable sample amount, and can be cumbersome. We describe how interfacing a recently described high-field asymmetric waveform ion mobility spectrometry (FAIMS) device between a nanoelectrospray ionization (nanoESI) emitter and an Orbitrap hybrid mass spectrometer (MS) enables the collection of single-shot proteomic data with comparable depth to that of conventional two-dimensional LC approaches. This next generation FAIMS device incorporates improved ion sampling at the ESI-FAIMS interface, increased electric field strength, and a helium-free ion transport gas. With fast internal compensation voltage (CV) stepping (25 ms/transition), multiple unique gas-phase fractions may be analyzed simultaneously over the course of an MS analysis. We have comprehensively demonstrated how this device performs for bottom-up proteomics experiments as well as characterized the effects of peptide charge state, mass loading, analysis time, and additional variables. We also offer recommendations for the number of CVs and which CVs to use for different lengths of experiments. Internal CV stepping experiments increase protein identifications from a single-shot experiment to >8000, from over 100 000 peptide identifications in as little as 5 h. In single-shot 4 h label-free quantitation (LFQ) experiments of a human cell line, we quantified 7818 proteins with FAIMS using intra-analysis CV switching compared to 6809 without FAIMS. Single-shot FAIMS results also compare favorably with LC fractionation experiments. A 6 h single-shot FAIMS experiment generates 8007 protein identifications, while four fractions analyzed for 1.5 h each produce 7776 protein identifications.

Ambient ionisation mass spectrometry for in situ analysis of intact proteins

Ambient surface mass spectrometry is an emerging field which shows great promise for the analysis of biomolecules directly from their biological substrate. In this article, we describe ambient ionisation mass spectrometry techniques for the in situ analysis of intact proteins. As a broad approach, the analysis of intact proteins offers unique advantages for the determination of primary sequence variations and posttranslational modifications, as well as interrogation of tertiary and quaternary structure and protein-protein/ligand interactions. In situ analysis of intact proteins offers the potential to couple these advantages with information relating to their biological environment, for example, their spatial distributions within healthy and diseased tissues. Here, we describe the techniques most commonly applied to in situ protein analysis (liquid extraction surface analysis, continuous flow liquid microjunction surface sampling, nano desorption electrospray ionisation, and desorption electrospray ionisation), their advantages, and limitations and describe their applications to date. We also discuss the incorporation of ion mobility spectrometry techniques (high field asymmetric waveform ion mobility spectrometry and travelling wave ion mobility spectrometry) into ambient workflows. Finally, future directions for the field are discussed.

Characterization of Complete Histone Tail Proteoforms Using Differential Ion Mobility Spectrometry

Histone proteins are subject to dynamic post-translational modifications (PTMs) that cooperatively modulate the chromatin structure and function. Nearly all functional PTMs are found on the N-terminal histone domains (tails) of ∼50 residues protruding from the nucleosome core. Using high-definition differential ion mobility spectrometry (FAIMS) with electron transfer dissociation, we demonstrate rapid baseline gas-phase separation and identification of tails involving monomethylation, trimethylation, acetylation, or phosphorylation in biologically relevant positions. These are by far the largest variant peptides resolved by any method, some with PTM contributing just 0.25% to the mass. This opens the door to similar separations for intact proteins and in top-down proteomics.

High sensitivity field asymmetric ion mobility spectrometer

A high sensitivity field asymmetric ion mobility spectrometer (FAIMS) was designed, fabricated, and tested. The main components of the system are a 10.6 eV UV photoionization source, an ion filter driven by a high voltage/high frequency n-MOS inverter circuit, and a low noise ion detector. The ion filter electronics are capable to generate square waveforms with peak-to-peak voltages up to 1000 V at frequencies up to 1 MHz with adjustable duty cycles. The ion detector current amplifier has a gain up to 10¹² V/A with an effective equivalent input noise level down to about 1 fA/Hz^1/2 during operation with the ion filter at the maximum voltage and frequency. The FAIMS system was characterized by detecting different standard chemical compounds. Additionally, we investigated the use of a synchronous modulation/demodulation technique to improve the signal-to-noise ratio in FAIMS measurements. In particular, we implemented the modulation of the compensation voltage with the synchronous demodulation of the ion current. The analysis of the measurements at low concentration levels led to an extrapolated limit of detection for acetone of 10 ppt with an averaging time of 1 s.