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

Fast and deep phosphoproteome analysis with the Orbitrap Astral mass spectrometer

Owing to its roles in cellular signal transduction, protein phosphorylation plays critical roles in myriad cell processes. That said, detecting and quantifying protein phosphorylation has remained a challenge. We describe the use of a novel mass spectrometer (Orbitrap Astral) coupled with data-independent acquisition (DIA) to achieve rapid and deep analysis of human and mouse phosphoproteomes. With this method, we map approximately 30,000 unique human phosphorylation sites within a half-hour of data collection. The technology is benchmarked to other state-of-the-art MS platforms using both synthetic peptide standards and with EGF-stimulated HeLa cells. We apply this approach to generate a phosphoproteome multi-tissue atlas of the mouse. Altogether, we detect 81,120 unique phosphorylation sites within 12 hours of measurement. With this unique dataset, we examine the sequence, structural, and kinase specificity context of protein phosphorylation. Finally, we highlight the discovery potential of this resource with multiple examples of phosphorylation events relevant to mitochondrial and brain biology.

Fast and Deep Phosphoproteome Analysis with the Orbitrap Astral Mass Spectrometer

Owing to its roles in cellular signal transduction, protein phosphorylation plays critical roles in myriad cell processes. That said, detecting and quantifying protein phosphorylation has remained a challenge. We describe the use of a novel mass spectrometer (Orbitrap Astral) coupled with data-independent acquisition (DIA) to achieve rapid and deep analysis of human and mouse phosphoproteomes. With this method we map approximately 30,000 unique human phosphorylation sites within a half-hour of data collection. The technology was benchmarked to other state-of-the-art MS platforms using both synthetic peptide standards and with EGF-stimulated HeLa cells. We applied this approach to generate a phosphoproteome multi-tissue atlas of the mouse. Altogether, we detected 81,120 unique phosphorylation sites within 12 hours of measurement. With this unique dataset, we examine the sequence, structural, and kinase specificity context of protein phosphorylation. Finally, we highlight the discovery potential of this resource with multiple examples of novel phosphorylation events relevant to mitochondrial and brain biology.

A simplified protocol for deep quantitative proteomic analysis of gingival crevicular fluid for skeletal maturity indicators

Assessment of craniofacial skeletal maturity is of great importance in orthodontic diagnosis and treatment planning. Traditional radiographic methods suffer from clinician subjectivity and low reproducibility. Recent biochemical methods, such as the use of gingival crevicular fluid (GCF) protein biomarkers involved in bone metabolism, have provided new opportunities to assess skeletal maturity. However, mass spectrometry (MS)-based GCF proteomic analysis still faces significant challenges, including the interference of high abundance proteins, laborious sample prefractionation and relatively limited coverage of GCF proteome. To improve GCF sample processing and further discover novel biomarkers, we herein developed a single-pot, solid-phase-enhanced sample-preparation (SP3)-based high-field asymmetric waveform ion mobility spectrometry (FAIMS)-MS protocol for deep quantitative analysis of the GCF proteome for skeletal maturity indicators. SP3 combined with FAIMS could minimize sample loss and eliminate tedious and time-consuming offline fractionation, thereby simplifying GCF sample preparation and improving analytical coverage and reproducibility of the GCF proteome. A total of 5407 proteins were identified in GCF samples from prepubertal and circumpubertal groups, representing the largest dataset of human GCF proteome to date. Compared to the prepubertal group, 61 proteins were differentially expressed (31 up-regulated, 30 down-regulated) in the circumpubertal group. The six-protein marker panel, including ATP5D, CLTA, CLTB, DNM2, HSPA8 and NCK1, showed great potential to predict the circumpubertal stage (ROC-AUC 0.937), which provided new insights into skeletal maturity assessment.

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.

Quantitative Time-Course Analysis of Osmotic and Salt Stress in Arabidopsis thaliana Using Short Gradient Multi-CV FAIMSpro BoxCar DIA

A major limitation when undertaking quantitative proteomic time-course experimentation is the tradeoff between depth-of-analysis and speed-of-analysis. In high complexity and high dynamic range sample types, such as plant extracts, balance between resolution and time is especially apparent. To address this, we evaluate multiple compensation voltage (CV) high field asymmetric waveform ion mobility spectrometry (FAIMSpro) settings using the latest label-free single-shot Orbitrap-based DIA acquisition workflows for their ability to deeply quantify the Arabidopsis thaliana seedling proteome. Using a BoxCarDIA acquisition workflow with a -30 -50 -70 CV FAIMSpro setting, we were able to consistently quantify >5000 Arabidopsis seedling proteins over a 21-min gradient, facilitating the analysis of ∼42 samples per day. Utilizing this acquisition approach, we then quantified proteome-level changes occurring in Arabidopsis seedling shoots and roots over 24 h of salt and osmotic stress, to identify early and late stress response proteins and reveal stress response overlaps. Here, we successfully quantify >6400 shoot and >8500 root protein groups, respectively, quantifying nearly ∼9700 unique protein groups in total across the study. Collectively, we pioneer a short gradient, multi-CV FAIMSpro BoxCarDIA acquisition workflow that represents an exciting new analysis approach for undertaking quantitative proteomic time-course experimentation in plants.

A fully automated FAIMS-DIA mass spectrometry-based proteomic pipeline

Here, we present a standardized, "off-the-shelf" proteomics pipeline working in a single 96-well plate to achieve deep coverage of cellular proteomes with high throughput and scalability. This integrated pipeline streamlines a fully automated sample preparation platform, a data-independent acquisition (DIA) coupled with high-field asymmetric waveform ion mobility spectrometer (FAIMS) interface, and an optimized library-free DIA database search strategy. Our systematic evaluation of FAIMS-DIA showing single compensation voltage (CV) at -35 V not only yields the deepest proteome coverage but also best correlates with DIA without FAIMS. Our in-depth comparison of direct-DIA database search engines shows that Spectronaut outperforms others, providing the highest quantifiable proteins. Next, we apply three common DIA strategies in characterizing human induced pluripotent stem cell (iPSC)-derived neurons and show single-shot mass spectrometry (MS) using single-CV (-35 V)-FAIMS-DIA results in >9,000 quantifiable proteins with <10% missing values, as well as superior reproducibility and accuracy compared with other existing DIA methods.

A Combined Gas-Phase Separation Strategy for ADP-ribosylated Peptides

ADP-ribosylation (ADPr) is a post-translational modification that is best studied using mass spectrometry. Method developments that are permissive with low inputs or baseline levels of protein ribosylation represent the next frontier in the field. High-field asymmetric waveform ion mobility spectrometry (FAIMS) reduces peptide complexity in the gas phase, providing a means to achieve maximal ADPr peptide sequencing depth. We therefore investigated the extent to which FAIMS with or without traditional gas-phase fractionation-separation (GPS) can increase the number of ADPr peptides. We examined ADPr peptides enriched from mouse spleens. We gleaned additional insight by also reporting findings from the corresponding non-ADPr peptide contaminants and the peptide inputs for ADPr peptide enrichment. At increasingly higher negative compensation voltages, ADPr peptides were more stable, whereas the non-ADPr peptides were filtered out. A combination of 3 GPS survey scans, each with 8 compensation voltages, resulted in 790 high-confidence ADPr peptides, compared to 90 with GPS alone. A simplified acquisition strategy requiring only two injections corresponding to two MS1 scan ranges coupled to optimized compensation voltage settings provided 402 ADPr peptides corresponding to 234 ADPr proteins. We conclude that our combined GPS strategy is a valuable addition to any ADP-ribosylome workflow. The data are available via ProteomeXchange with identifier PXD040898.

Recent progress in quantitative phosphoproteomics

INTRODUCTION

Protein phosphorylation is a critical post-translational modification involved in the regulation of numerous cellular processes from signal transduction to modulation of enzyme activities. Knowledge of dynamic changes of phosphorylation levels during biological processes, under various treatments or between healthy and disease models is fundamental for understanding the role of each phosphorylation event. Thereby, LC-MS/MS based technologies in combination with quantitative proteomics strategies evolved as a powerful strategy to investigate the function of individual protein phosphorylation events.

AREAS COVERED

State-of-the-art labeling techniques including stable isotope and isobaric labeling provide precise and accurate quantification of phosphorylation events. Here, we review the strengths and limitations of recent quantification methods and provide examples based on current studies, how quantitative phosphoproteomics can be further optimized for enhanced analytic depth, dynamic range, site localization, and data integrity. Specifically, reducing the input material demands is key to a broader implementation of quantitative phosphoproteomics, not least for clinical samples.

EXPERT OPINION

Despite quantitative phosphoproteomics is one of the most thriving fields in the proteomics world, many challenges still have to be overcome to facilitate even deeper and more comprehensive analyses as required in the current research, especially at single cell levels and in clinical diagnostics.

Expanding the Epitranscriptomic RNA Sequencing and Modification Mapping Mass Spectrometry Toolbox with Field Asymmetric Waveform Ion Mobility and Electrochemical Elution Liquid Chromatography

Post-transcriptional modifications of RNA strongly influence the RNA structure and function. Recent advances in RNA sequencing and mass spectrometry (MS) methods have identified over 140 of these modifications on a wide variety of RNA species. Most next-generation sequencing approaches can only map one RNA modification at a time, and while MS can assign multiple modifications simultaneously in an unbiased manner, MS cannot accurately catalog and assign RNA modifications in complex biological samples due to limitations in the fragment length and coverage depth. Thus, a facile method to identify novel RNA modifications while simultaneously locating them in the context of their RNA sequences is still lacking. We combined two orthogonal modes of RNA ion separation before MS identification: high-field asymmetric ion mobility separation (FAIMS) and electrochemically modulated liquid chromatography (EMLC). FAIMS RNA MS increases both coverage and throughput, while EMLC LC-MS orthogonally separates RNA molecules of different lengths and charges. The combination of the two methods offers a broadly applicable platform to improve the length and depth of MS-based RNA sequencing while providing contextual access to the analysis of RNA modifications.

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.

Phospho-heavy-labeled-spiketide FAIMS stepped-CV DDA (pHASED) provides real-time phosphoproteomics data to aid in cancer drug selection

Global high-throughput phosphoproteomic profiling is increasingly being applied to cancer specimens to identify the oncogenic signaling cascades responsible for promoting disease initiation and disease progression; pathways that are often invisible to genomics analysis. Hence, phosphoproteomic profiling has enormous potential to inform and improve individualized anti-cancer treatment strategies. However, to achieve the adequate phosphoproteomic depth and coverage necessary to identify the activated, and hence, targetable kinases responsible for driving oncogenic signaling pathways, affinity phosphopeptide enrichment techniques are required and often coupled with offline high-pressure liquid chromatographic (HPLC) separation prior to nanoflow liquid chromatography-tandem mass spectrometry (nLC-MS/MS). These complex and time-consuming procedures, limit the utility of phosphoproteomics for the analysis of individual cancer patient specimens in real-time, and restrict phosphoproteomics to specialized laboratories often outside of the clinical setting. To address these limitations, here we have optimized a new protocol, phospho-heavy-labeled-spiketide FAIMS Stepped-CV DDA (pHASED), that employs online phosphoproteome deconvolution using high-field asymmetric waveform ion mobility spectrometry (FAIMS) and internal phosphopeptide standards to provide accurate label-free quantitation (LFQ) data in real-time. Compared with traditional single-shot LFQ phosphoproteomics workflows, pHASED provided increased phosphoproteomic depth and coverage (phosphopeptides = 4617 pHASED, 2789 LFQ), whilst eliminating the variability associated with offline prefractionation. pHASED was optimized using tyrosine kinase inhibitor (sorafenib) resistant isogenic FLT3-mutant acute myeloid leukemia (AML) cell line models. Bioinformatic analysis identified differential activation of the serine/threonine protein kinase ataxia-telangiectasia mutated (ATM) pathway, responsible for sensing and repairing DNA damage in sorafenib-resistant AML cell line models, thereby uncovering a potential therapeutic opportunity. Herein, we have optimized a rapid, reproducible, and flexible protocol for the characterization of complex cancer phosphoproteomes in real-time, a step towards the implementation of phosphoproteomics in the clinic to aid in the selection of anti-cancer therapies for patients.

A multi-purpose, regenerable, proteome-scale, human phosphoserine resource for phosphoproteomics

Mass-spectrometry-based phosphoproteomics has become indispensable for understanding cellular signaling in complex biological systems. Despite the central role of protein phosphorylation, the field still lacks inexpensive, regenerable, and diverse phosphopeptides with ground-truth phosphorylation positions. Here, we present Iterative Synthetically Phosphorylated Isomers (iSPI), a proteome-scale library of human-derived phosphoserine-containing phosphopeptides that is inexpensive, regenerable, and diverse, with precisely known positions of phosphorylation. We demonstrate possible uses of iSPI, including use as a phosphopeptide standard, a tool to evaluate and optimize phosphorylation-site localization algorithms, and a benchmark to compare performance across data analysis pipelines. We also present AScorePro, an updated version of the AScore algorithm specifically optimized for phosphorylation-site localization in higher energy fragmentation spectra, and the FLR viewer, a web tool for phosphorylation-site localization, to enable community use of the iSPI resource. iSPI and its associated data constitute a useful, multi-purpose resource for the phosphoproteomics community.

IQGAP1 and RNA Splicing in the Context of Head and Neck via Phosphoproteomics

IQGAP1 (IQ motif-containing GTPase-activating protein 1) scaffolds several signaling pathways in mammalian cells that are implicated in carcinogenesis, including the RAS and PI3K pathways that involve multiple protein kinases. IQGAP1 has been shown to promote head and neck squamous cell carcinoma (HNSCC); however, the underlying mechanism(s) remains unclear. Here, we report a mass spectrometry-based analysis identifying differences in phosphorylation of cellular proteins in vivo and in vitro in the presence or absence of IQGAP1. By comparing the esophageal phosphoproteome profiles between Iqgap1+/+ and Iqgap1-/- mice, we identified RNA splicing as one of the most altered cellular processes. Serine/arginine-rich splicing factor 6 (SRSF6) was the protein with the most downregulated levels of phosphorylation in Iqgap1-/- tissue. We confirmed that the absence of IQGAP1 reduced SRSF6 phosphorylation both in vivo and in vitro. We then expanded our analysis to human normal oral keratinocytes. Again, we found factors involved in RNA splicing to be highly altered in the phosphoproteome profile upon genetic disruption of IQGAP1. Both the Clinical Proteomic Tumor Analysis Consortium (CPTAC) and the Cancer Genome Atlas (TCGA) data sets indicate that phosphorylation of splicing-related proteins is important in HNSCC prognosis. The Biological General Repository for Interaction Datasets (BioGRID) repository also suggested multiple interactions between IQGAP1 and splicing-related proteins. Based on these collective observations, we propose that IQGAP1 regulates the phosphorylation of splicing proteins, which potentially affects their splicing activities and, therefore, contributes to HNSCC. Raw data are available from the MassIVE database with identifier MSV000087770.

Novel Online Three-Dimensional Separation Expands the Detectable Functional Landscape of Cellular Phosphoproteome

Protein phosphorylation is a prevalent post-translational modification that regulates essentially every aspect of cellular processes. Currently, liquid chromatography-tandem mass spectrometry (LC-MS/MS) with an extensive offline sample fractionation and a phosphopeptide enrichment method is a best practice for deep phosphoproteome profiling, but balancing throughput and profiling depth remains a practical challenge. We present an online three-dimensional separation method for ultradeep phosphoproteome profiling that combines an online two-dimensional liquid chromatography separation and an additional gas-phase separation. This method identified over 100,000 phosphopeptides (>60,000 phosphosites) in HeLa cells during 1.5 days of data acquisition, and the largest HeLa cell phosphoproteome significantly expanded the detectable functional landscape of cellular phosphoproteome.

Advances and Trends in Omics Technology Development

The human history has witnessed the rapid development of technologies such as high-throughput sequencing and mass spectrometry that led to the concept of “omics” and methodological advancement in systematically interrogating a cellular system. Yet, the ever-growing types of molecules and regulatory mechanisms being discovered have been persistently transforming our understandings on the cellular machinery. This renders cell omics seemingly, like the universe, expand with no limit and our goal toward the complete harness of the cellular system merely impossible. Therefore, it is imperative to review what has been done and is being done to predict what can be done toward the translation of omics information to disease control with minimal cell perturbation. With a focus on the “four big omics,” i.e., genomics, transcriptomics, proteomics, metabolomics, we delineate hierarchies of these omics together with their epiomics and interactomics, and review technologies developed for interrogation. We predict, among others, redoxomics as an emerging omics layer that views cell decision toward the physiological or pathological state as a fine-tuned redox balance.

Cracking chromatin with proteomics: From chromatome to histone modifications

Chromatin is the assembly of genomic DNA and proteins packaged in the nucleus of eukaryotic cells, which together are crucial in regulating a plethora of cellular processes. Histones may be the best known class of protein constituents in chromatin, which are decorated by a range of post-translational modifications to recruit accessory proteins and protein complexes to execute specific functions, ranging from DNA compaction, repair, transcription and duplication, all in a dynamic fashion and depending on the cellular state. The key role of chromatin in cellular fitness is emphasized by the deregulation of chromatin determinants predisposing to different diseases, including cancer. For this reason, deep investigation of chromatin composition is fundamental to better understand cellular physiology. Proteomic approaches have played a crucial role to understand critical aspects of this complex interplay, benefiting from the ability to identify and quantify proteins and their modifications in an unbiased manner. This review gives an overview of the proteomic approaches that have been developed by combining mass spectrometry-based with tailored biochemical and genetic methods to examine overall protein make-up of chromatin, to characterize chromatin domains, to determine protein interactions, and to decipher the broad spectrum of histone modifications that represent the quintessence of chromatin function. This article is protected by copyright. All rights reserved.

FAIMS Enhances the Detection of PTM Crosstalk Sites

Protein post-translational modifications (PTMs) enable cells to rapidly change in response to biological stimuli. With hundreds of different PTMs, understanding these control mechanisms is complex. To date, efforts have focused on investigating the effect of a single PTM on protein function. Yet, many proteins contain multiple PTMs. Moreover, one PTM can alter the prevalence of another, a phenomenon termed PTM crosstalk. Understanding PTM crosstalk is critical; however, its detection is challenging since PTMs occur substoichiometrically. Here, we develop an enrichment-free, label-free proteomics method that utilizes high-field asymmetric ion mobility spectrometry (FAIMS) to enhance the detection of PTM crosstalk. We show that by searching for multiple combinations of dynamic PTMs on peptide sequences, a 6-fold increase in candidate PTM crosstalk sites is identified compared with that of standard liquid chromatography-tandem mass spectrometry (LC-MS/MS) workflows. Additionally, by cycling through FAIMS compensation voltages within a single LC-FAIMS-MS/MS run, we show that our LC-FAIMS-MS/MS workflow can increase multi-PTM-containing peptide identifications without additional increases in run times. With 159 novel candidate crosstalk sites identified, we envisage LC-FAIMS-MS/MS to play an important role in expanding the repertoire of multi-PTM identifications. Moreover, it is only by detecting PTM crosstalk that we can "see" the full picture of how proteins are regulated.

Phosphoproteomics Sample Preparation Impacts Biological Interpretation of Phosphorylation Signaling Outcomes

The influence of phosphoproteomics sample preparation methods on the biological interpretation of signaling outcome is unclear. Here, we demonstrate a strong bias in phosphorylation signaling targets uncovered by comparing the phosphoproteomes generated by two commonly used methods-strong cation exchange chromatography-based phosphoproteomics (SCXPhos) and single-run high-throughput phosphoproteomics (HighPhos). Phosphoproteomes of embryonic stem cells exposed to ionizing radiation (IR) profiled by both methods achieved equivalent coverage (around 20,000 phosphosites), whereas a combined dataset significantly increased the depth (>30,000 phosphosites). While both methods reproducibly quantified a subset of shared IR-responsive phosphosites that represent DNA damage and cell-cycle-related signaling events, most IR-responsive phosphoproteins (>82%) and phosphosites (>96%) were method-specific. Both methods uncovered unique insights into phospho-signaling mediated by single (SCXPhos) versus double/multi-site (HighPhos) phosphorylation events; particularly, each method identified a distinct set of previously unreported IR-responsive kinome/phosphatome (95% disparate) directly impacting the uncovered biology.

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.

Evaluation and Optimization of High-Field Asymmetric Waveform Ion-Mobility Spectrometry for Multiplexed Quantitative Site-Specific N-Glycoproteomics

The heterogeneity and complexity of glycosylation hinder the depth of site-specific glycoproteomics analysis. High-field asymmetric-waveform ion-mobility spectrometry (FAIMS) has been shown to improve the scope of bottom-up proteomics. The benefits of FAIMS for quantitative N-glycoproteomics have not been investigated yet. In this work, we optimized FAIMS settings for N-glycopeptide identification, with or without the tandem mass tag (TMT) label. The optimized FAIMS approach significantly increased the identification of site-specific N-glycopeptides derived from the purified immunoglobulin M (IgM) protein or human lymphoma cells. We explored in detail the changes in FAIMS mobility caused by N-glycopeptides with different characteristics, including TMT labeling, charge state, glycan type, peptide sequence, glycan size, and precursor m/z. Importantly, FAIMS also improved multiplexed N-glycopeptide quantification, both with the standard MS2 acquisition method and with our recently developed Glyco-SPS-MS3 method. The combination of FAIMS and Glyco-SPS-MS3 methods provided the highest quantitative accuracy and precision. Our results demonstrate the advantages of FAIMS for improved mass spectrometry-based qualitative and quantitative N-glycoproteomics.

FAIMS-MS might contribute to phosphopeptides identification in plasma

FAIMS interface is gaining popularity because of the impressive 100-fold signal to noise enhancement in addition to the recent coupling to the Orbitrap technology, the most important analyzer developed in the last 20 years. The selection of group of ions and effective removal of single-charged ones at particular compensation voltages increases around 50% the proteome coverage at expenses of lower peptides coverage. However, specific setting for phosphoproteome analysis is yet poorly described. Here we have found the maximum transmission for several tryptic phosphopeptides isolated from a single complex mixture and we have set an experimental method based on five compensation voltages partially different to the ones described previously, demonstrating the relevance of voltages higher than 47 V, with an increase of around 20% of unique phosphopeptides. Using this experimental setup two complex phosphoproteomes isolates (SH-SY5Y cell line and plasma) were analyzed and found increments of 50% on phosphopeptides identification with the proposed method with respect to a previous one, for the cell line extract. Meanwhile for plasma 109 of the detected phosphopeptides are found for first time in this body fluid, presumably due to the release of intracellular proteins. With this FAIMS setup, 60% of the proteins identified are classified as very low abundant proteins.

Structural analysis of petroporphyrins from asphaltene by trapped ion mobility coupled with Fourier transform ion cyclotron resonance mass spectrometry

Molecular characterization of compounds present in highly complex mixtures such as petroleum is proving to be one of the main analytical challenges. Heavy fractions, such as asphaltenes, exhibit immense molecular and isomeric complexity. Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) with its unequalled resolving power, mass accuracy and dynamic range can address the isobaric complexity. Nevertheless, isomers remain largely inaccessible. Therefore, another dimension of separation is required. Recently, ion mobility mass spectrometry has revealed great potential for isomer description. In this study, the combination of trapped ion mobility and Fourier transform ion cyclotron resonance mass spectrometry (TIMS-FTICR) is used to obtain information on the structural features and isomeric diversity of vanadium petroporphyrins present in heavy petroleum fractions. The ion mobility spectra provided information on the isomeric diversity of the different classes of porphyrins. The determination of the collision cross section (CCS) from the peak apex allows us to hypothesize about the structural aspects of the petroleum molecules. In addition, the ion mobility signal full width at half maximum (FWHM) was used as a measure for isomeric diversity. Finally, theoretical CCS determinations were conducted first on core structures and then on alkylated petroporphyrins taking advantage of the linear correlation between the CCS and the alkylation level. This allowed the proposal of putative structures in agreement with the experimental results. The authors believe that the presented workflow will be useful for the structural prediction of real unknowns in highly complex mixtures.