High-field Asymmetric Waveform Ion Mobility Research Articles

Adaptive Multicore Dual-Path Fusion Multimodel Extraction of Heterogeneous Features for FAIMS Spectral Analysis.

With the increasing application scenarios and detection needs of high-field asymmetric waveform ion mobility spectrometry (FAIMS) analysis, deep learning-assisted spectral analysis has become an important method to improve the analytical effect and work efficiency. However, a single model has limitations in generalizing to different types of tasks, and a model trained from one batch of spectral data is difficult to achieve good results on another task with large differences. To address this problem, this study proposes an adaptive multicore dual-path fusion multimodel extraction of heterogeneous features for FAIMS spectral analysis model in conjunction with FAIMS small-sample data analysis scenarios. Multinetwork complementarity is achieved through multimodel feature extraction, adaptive feature fusion module adjusts feature size and dimension fusion to heterogeneous features, and multicore dual-path fusion can capture and integrate information at all scales and levels. The model's performance improves dramatically when performing complex mixture multiclassification tasks: accuracy, precision, recall, f1-score, and micro-AUC reach 98.11%, 98.66%, 98.33%, 98.30%, and 98.98%. The metrics for the generalization test using the untrained xylene isomer data were 96.42%, 96.66%, 96.96%, 96.65%, and 97.60%. The model not only exhibits excellent analytical results on preexisting data but also demonstrates good generalization ability on untrained data.

In-Source Collision-Induced Dissociation (CID) Improves Higher-Energy Collisional Dissociation (HCD)-Dependent Fragmentation of ADP-Ribosyl Peptides.

ADP-ribosylation is a posttranslational modification whose higher-energy collisional dissociation (HCD) products are dominated by complete or partial modification losses, complicating peptide sequencing and acceptor site localization efforts. We tested whether in-source collision-induced dissociation (CID) performed on a quadrupole-Orbitrap could convert ADPr to the smaller phosphoribose-H2O derivative to facilitate HCD-dependent peptide sequencing. ADP-ribosyl (ADPr) peptides derived from the human macrophage-like cell line THP-1 were analyzed on a quadrupole-Orbitrap. We monitored the dissociation of ADPr (+ 541.061 Da) to phosphoribosyl-H2O (+ 193.997 Da) peptides while varying the source and high-field asymmetric waveform ion mobility mass spectrometry (FAIMS) compensation voltages. Xcorr and ptmRS were used to evaluate peptide sequencing and acceptor site confidence, respectively. Phosphoribosyl-H2O acceptor sites were compared with those determined by electron-transfer higher-energy collision dissociation (EThcD), performed on a quadrupole-ion trap-Orbitrap. In-source CID of ADPr peptides to their phosphoribosyl-H2O derivatives increased with increasing source voltage (up to 50 V), as judged by monitoring the corresponding modification loss ([adenosine monophosphate/AMP]+) and the number of identified phosphoribosyl-H2O peptide identifications. The average Xcorr increased from 1.36 (ADPr) to 2.26 (phosphoribosyl-H2O), similar to that achieved with EThcD for ADPr peptides (2.29). The number of high-confidence acceptor sites (> 95%) also increased, from 31% (ADPr) to 70% (phosphoribosyl-H2O), which was comparable to EThcD (70%). In-source CID converts ADP-ribosyl to phosphoribosyl-H2O peptides that are more amenable to HCD-dependent peptide sequencing, providing an alternative method for acceptor site determination when ETD-based methods are not available.

Analysis of FAIMS for the Study of Affinity-Purified Protein Complexes Using the Orbitrap Ascend Tribrid Mass Spectrometer.

In this study, we analyzed the combination of affinity purification mass spectrometry (AP-MS) with high-field asymmetric waveform ion mobility spectrometry (FAIMS), integrated between nanoLC-MS and an Orbitrap Ascend Tribrid Mass Spectrometer. Our primary objective was to evaluate the application of the FAIMS interface for detecting affinity purified SAP25 protein complexes with enhanced sensitivity and robustness. As a result, we observed that nanoLC-FAIMS-MS (with FAIMS) significantly improved the sensitivity and detection limits at the protein level, peptide level and significantly reduced chemical contaminants compared to nanoLC-MS alone without FAIMS (No FAIMS). This FAIMS configuration resulted in 42% and 92% increases for the total proteins and unique proteins, respectively, and 44% and 88% increases for total peptides and unique peptides compared to the No FAIMS configuration. Our in-depth comparison of FAIMS and No FAIMS shows that FAIMS outperforms by significantly reducing the missing value by <15% in datasets and plays a significant role in filtering chemical contaminants. Our findings highlight the potential of FAIMS with Orbitrap Ascend Tribrid Mass Spectrometer to enhance the depth of AP-MS analysis. The data were deposited with the MASSIVE repository with the identifier MSV000096548.

Development of LC-FAIMS-MS and its application to lipidomics study of Acinetobacter baumannii infection

The recent advances in mass spectrometry (MS) technologies have enabled comprehensive lipid profiling in biological samples. However, the robustness and efficiency of MS-based lipidomics is compromised by the complexity of biological samples. High-field asymmetric waveform ion mobility spectrometry (FAIMS) is a technology that can continuously transmit one type of ion, independent of the mass-to-charge ratio. Here we present the development and application of LC-FAIMS-MS/MS-based platform for untargeted lipidomics. We used 3 optimally balanced compensation voltages, i.e., 29 V, 34 V and 39 V, to analyze all subclasses of glycerophospholipids. The reproducibility of the method was evaluated using reference standards. The reproducibility of retention times ranged from 0.9% to 1.5% RSD; whereas RSD values of 5%–10% were observed for peak areas. More importantly, the coupling of a FAIMS device can significantly improve the robustness and efficiency. We exploited this NPLC-FAIMS-HRMS to analyze the serum lipid profiles in mice infected intranasally with Acinetobacter baumannii. The temporal profiles of serum lipids after A. baumannii inoculation were obtained for 4 h, 8 h, and 24 h. We found that nearly all ether PC and ether PE lipids were significantly decreased 8 h after inoculation. The resultant volcano plot illustrated the distribution of 28 increased and 28 decreased lipid species in mouse sera 24 h after inoculation. We also found that a single ether PE composition can comprise multiple isomeric structures, and the relative abundance of each isomer could be quantified using the newly developed NPLC-FAIMS-PRM method. We have demonstrated that the proposed LC-FAIMS-MS is a valuable platform for lipidomics.

Effect of dynamic exclusion and the use of FAIMS, DIA and MALDI-mass spectrometry imaging with ion mobility on amyloid protein identification

Amyloidosis is a disease characterized by local and systemic extracellular deposition of amyloid protein fibrils where its excessive accumulation in tissues and resistance to degradation can lead to organ failure. Diagnosis is challenging because of approximately 36 different amyloid protein subtypes. Imaging methods like immunohistochemistry and the use of Congo red staining of amyloid proteins for laser capture microdissection combined with liquid chromatography tandem mass spectrometry (LMD/LC–MS/MS) are two diagnostic methods currently used depending on the expertise of the pathology laboratory. Here, we demonstrate a streamlined in situ amyloid peptide spatial mapping by Matrix Assisted Laser Desorption Ionization–Mass Spectrometry Imaging (MALDI-MSI) combined with Trapped Ion Mobility Spectrometry for potential transthyretin (ATTR) amyloidosis subtyping. While we utilized the standard LMD/LC–MS/MS workflow for amyloid subtyping of 31 specimens from different organs, we also evaluated the potential introduction in the MS workflow variations in data acquisition parameters like dynamic exclusion, or testing Data Dependent Acquisition combined with High-Field Asymmetric Waveform Ion Mobility Spectrometry (DDA FAIMS) versus Data Independent Acquisition (DIA) for enhanced amyloid protein identification at shorter acquisition times. We also demonstrate the use of Mascot’s Error Tolerant Search and PEAKS de novo sequencing for the sequence variant analysis of amyloidosis specimens.

Improvement of Tumor Neoantigen Detection by High-Field Asymmetric Waveform Ion Mobility Mass Spectrometry.

Cancer neoantigens have been shown to elicit cancer-specific T-cell responses and have garnered much attention for their roles in both spontaneous and therapeutically induced antitumor responses. Mass spectrometry (MS) profiling of tumor immunopeptidomes has been used, in part, to identify MHC-bound mutant neoantigen ligands. However, under standard conditions, MS-based detection of such rare but clinically relevant neoantigens is relatively insensitive, requiring 300 million cells or more. Here, to quantitatively define the minimum detectable amounts of therapeutically relevant MHC-I and MHC-II neoantigen peptides, we analyzed different dilutions of immunopeptidomes isolated from the well-characterized T3 mouse methylcholanthrene (MCA)-induced cell line by MS. Using either data-dependent acquisition or parallel reaction monitoring (PRM), we established the minimum amount of material required to detect the major T3 neoantigens in the presence or absence of high field asymmetric waveform ion mobility spectrometry (FAIMS). This analysis yielded a 14-fold enhancement of sensitivity in detecting the major T3 MHC-I neoantigen (mLama4) with FAIMS-PRM compared with PRM without FAIMS, allowing ex vivo detection of this neoantigen from an individual 100 mg T3 tumor. These findings were then extended to two other independent MCA-sarcoma lines (1956 and F244). This study demonstrates that FAIMS substantially increases the sensitivity of MS-based characterization of validated neoantigens from tumors.

Highly sensitive and selective sulfur hexafluoride detection based on DAPPI-FAIMS

This paper proposed a novel detection method of sulfur hexafluoride (SF6) by combining dopant-assisted atmospheric pressure photoionization (DAPPI) with high-field asymmetric waveform ion mobility spectroscopy (FAIMS). Acetone was employed as a dopant to achieve high sensitivity, and the negative ion mode of FAIMS was selected to achieve high selectivity. The impact of dopant concentrations on detection sensitivity and linearity was studied, and the influence of relative humidity on the detection of sulfur hexafluoride was studied. Ammonia, benzene, and hydrogen sulfide were selected as interferences to verify the selectivity. A linearity between the concentration and the signal was studied, and the detection limit for sulfur hexafluoride was determined. Experimental results demonstrated that the DAPPI source effectively enhanced the ionization efficiency of sulfur hexafluoride with a linear coefficient of 96.1 %. The sensitivity of sulfur hexafluoride is inversely proportional to relative humidity. Sulfur hexafluoride has a characteristic fingerprint spectrum different from air background and typical interfering, and can be distinguished from interfering substances in mixtures containing ammonia, benzene, and hydrogen sulfide. The concentration of sulfur hexafluoride has excellent linearity with signal intensity, the linear coefficient was 99.8 %, and the detection limit was 0.02 ppm.

Design and experiment of high-field asymmetric waveform ion mobility spectrometry chip based on an integrated temperature control printed circuit board structure.

During the detection of volatile organic compounds (VOC) using high-field asymmetric waveform ion mobility spectrometry (FAIMS), the ambient temperature significantly impacts the accuracy of planar FAIMS. To mitigate the influence of ambient temperature on detection accuracy and enhance resolution, a FAIMS system based on the inner impedance characteristics of a printed circuit board (PCB) was designed for temperature control. This study, conducted under standard atmospheric pressure, aimed to assess the signal stability of a planar FAIMS instrument with and without temperature control, and the effect of temperature change on the detection ability of acetone, ethanol, and their mixture was studied using PCB self-heating. Experimental results demonstrated that the base noise in FAIMS with temperature control was 0.2pA, whereas that in FAIMS without temperature control was 1.8pA. Notably, with increasing temperature, the detection ability of FAIMS changes accordingly. The optimal relative detection ability of acetone was observed when the electrode plate was heated to 45°C under an electric field of 15 kV/cm. This study provides a novel approach to improve the resolving power of FAIMS systems and their signal-to-noise ratio. The utilization of a PCB-based temperature control proved effective in stabilizing FAIMS signal characteristics and optimizing detection capabilities, particularly for VOCs such as acetone. These findings have significant implications for improving the accuracy and resolving power of FAIMS systems in VOC detection applications.

Ion Mobility–Based Enrichment-Free N-Terminomics Analysis Reveals Novel Legumain Substrates in Murine Spleen

Aberrant levels of the asparaginyl endopeptidase legumain have been linked to inflammation, neurodegeneration, and cancer, yet our understanding of this protease is incomplete. Systematic attempts to identify legumain substrates have been previously confined to in vitro studies, which fail to mirror physiological conditions and obscure biologically relevant cleavage events. Using high-field asymmetric waveform ion mobility spectrometry (FAIMS), we developed a streamlined approach for proteome and N-terminome analyses without the need for N-termini enrichment. Compared to unfractionated proteomic analysis, we demonstrate FAIMS fractionation improves N-termini identification by >2.5 fold, resulting in the identification of >2882 unique N-termini from limited sample amounts. In murine spleens, this approach identifies 6366 proteins and 2528 unique N-termini, with 235 cleavage events enriched in WT compared to legumain-deficient spleens. Among these, 119 neo-N-termini arose from asparaginyl endopeptidase activities, representing novel putative physiological legumain substrates. The direct cleavage of selected substrates by legumain was confirmed using in vitro assays, providing support for the existence of physiologically relevant extra-lysosomal legumain activity. Combined, these data shed critical light on the functions of legumain and demonstrate the utility of FAIMS as an accessible method to improve depth and quality of N-terminomics studies.

Targeted Mass Spectrometry Analyses of Somatic Mutations in Colorectal Cancer Specimens Using Differential Ion Mobility.

Identification of K-Ras and B-Raf mutations in colorectal cancer (CRC) is essential to predict patients' response to anti-EGFR therapy and formulate appropriate therapeutic strategies to improve prognosis and survival. Here, we combined parallel reaction monitoring (PRM) with high-field asymmetric waveform ion mobility (FAIMS) to enhance mass spectrometry sensitivity and improve the identification of low-abundance K-Ras and B-Raf mutations in biological samples without immunoaffinity enrichment. In targeted LC-MS/MS analyses, FAIMS reduced the occurrence of interfering ions and enhanced precursor ion purity, resulting in a 3-fold improvement in the detection limit for K-Ras and B-Raf mutated peptides. In addition, the ion mobility separation of isomeric peptides using FAIMS facilitated the unambiguous identification of K-Ras G12D and G13D peptides. The application of targeted LC-MS/MS analyses using FAIMS is demonstrated for the detection and quantitation of B-Raf V600E, K-Ras G12D, G13D, and G12V in CRC cell lines and primary specimens.

Application and integration of deep learning in FAIMS for identifying acetone concentration

In practical applications, analytical instruments are used for both qualitative and quantitative analysis. However, for high-field asymmetric-waveform ion mobility spectrometry (FAIMS), most studies to date have been focused on the qualitative analysis of substances, with limited research on quantitative analysis. Explored here is the feasibility of using deep learning in FAIMS for quantitative analysis, aided by redesigning the FAIMS upper computer. Integrating spectrum creation and deep learning analysis into the FAIMS upper computer boosts the processing and analysis of FAIMS data, laying a foundation for applying FAIMS practically. For analysis using image processing, multiple FAIMS spectral lines obtained under different conditions are converted into a three-dimensional thermodynamic map known as a FAIMS spectrum, and multiple FAIMS spectrum are preprocessed to obtain the data set of this experiment. The principles of partial-least-squares regression and the XGBoost and ResNeXt models are introduced in detail, and the data are analyzed using these models, while exploring the effects of different model parameters and determining their optimal values. The experimental results show that the pre-trained ResNeXt deep learning model performs the best on the test set, with a root mean square error of 0.86 mg/mL, indicating the potential of deep learning in realizing quantitative analysis of substances in FAIMS.

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.

Mass spectrometry quantifies target engagement for a KRASG12C inhibitor in FFPE tumor tissue

BackgroundQuantification of drug-target binding is critical for confirming that drugs reach their intended protein targets, understanding the mechanism of action, and interpreting dose-response relationships. For covalent inhibitors, target engagement can be inferred by free target levels before and after treatment. Targeted mass spectrometry assays offer precise protein quantification in complex biological samples and have been routinely applied in pre-clinical studies to quantify target engagement in frozen tumor tissues for oncology drug development. However, frozen tissues are often not available from clinical trials so it is critical that assays are applicable to formalin-fixed, paraffin-embedded (FFPE) tissues in order to extend mass spectrometry-based target engagement studies into clinical settings.MethodsWild-type RAS and RASG12C was quantified in FFPE tissues by a highly optimized targeted mass spectrometry assay that couples high-field asymmetric waveform ion mobility spectrometry (FAIMS) and parallel reaction monitoring (PRM) with internal standards. In a subset of samples, technical reproducibility was evaluated by analyzing consecutive tissue sections from the same tumor block and biological variation was accessed among adjacent tumor regions in the same tissue section.ResultsWild-type RAS protein was measured in 32 clinical non-small cell lung cancer tumors (622–2525 amol/µg) as measured by FAIMS-PRM mass spectrometry. Tumors with a known KRASG12C mutation (n = 17) expressed a wide range of RASG12C mutant protein (127–2012 amol/µg). The variation in wild-type RAS and RASG12C measurements ranged 0–18% CV across consecutive tissue sections and 5–20% CV among adjacent tissue regions. Quantitative target engagement was then demonstrated in FFPE tissues from 2 xenograft models (MIA PaCa-2 and NCI-H2122) treated with a RASG12C inhibitor (AZD4625).ConclusionsThis work illustrates the potential to expand mass spectrometry-based proteomics in preclinical and clinical oncology drug development through analysis of FFPE tumor biopsies.

Orbitrap Mass Spectrometry and High-Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) Enable the in-Depth Analysis of Human Serum Proteoforms.

Blood serum and plasma are arguably the most commonly analyzed clinical samples, with dozens of proteins serving as validated biomarkers for various human diseases. Top-down proteomics may provide additional insights into disease etiopathogenesis since this approach focuses on protein forms, or proteoforms, originally circulating in blood, potentially providing access to information about relevant post-translational modifications, truncations, single amino acid substitutions, and many other sources of protein variation. However, the vast majority of proteomic studies on serum and plasma are carried out using peptide-centric, bottom-up approaches that cannot recapitulate the original proteoform content of samples. Clinical laboratories have been slow to adopt top-down analysis, also due to higher sample handling requirements. In this study, we describe a straightforward protocol for intact proteoform sample preparation based on the depletion of albumin and immunoglobulins, followed by simplified protein fractionation via polyacrylamide gel electrophoresis. After molecular weight-based fractionation, we supplemented the traditional liquid chromatography-tandem mass spectrometry (LC-MS2) data acquisition with high-field asymmetric waveform ion mobility spectrometry (FAIMS) to further simplify serum proteoform mixtures. This LC-FAIMS-MS2 method led to the identification of over 1000 serum proteoforms < 30 kDa, outperforming traditional LC-MS2 data acquisition and more than doubling the number of proteoforms identified in previous studies.

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 -35V 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.

Dual ionization sources high-field asymmetric waveform ion mobility spectrometry with combined ultraviolet lamp source and corona discharge source

Dual ionization sources combining an ultraviolet (UV) lamp source and a corona discharge (CD) source were first used as ionization sources for high-field asymmetric waveform ion mobility spectrometry (FAIMS) to switch ionization modes without changing hardware. The CD source was manufactured using a tungsten needle and a copper ring and its usability was verified. The UV source and the CD source were combined into the FAIMS sensor and multiple ionization modes were attempted by controlling their on-off status. The optimal flow rate, quantitative and qualitative capabilities of the system were investigated, and the experiments on the impact of humidity and interferent on the system were conducted. The experimental results indicated that the flow rate of 3–4 L/min could ensure sufficient sensitivity and resolution of the system. The dual ionization sources configuration provided richer qualitative and quantitative information for FAIMS. This platform could operate in three ionization modes and had the potential to expand the analyzable compounds of UV-FAIMS. In summary, the research demonstrates that the dual ionization sources could be used as ionization sources for FAIMS, and the combined system provided convenience for chemical analysis.

False-Positive Glycopeptide Identification via In-FAIMS Fragmentation.

High-field asymmetric waveform ion mobility spectrometry (FAIMS) separates glycopeptides in the gas phase prior to mass spectrometry (MS) analysis, thus offering the potential to analyze glycopeptides without prior enrichment. Several studies have demonstrated the ability of FAIMS to enhance glycopeptide detection but have primarily focused on N-glycosylation. Here, we evaluated FAIMS for O-glycoprotein and mucin-domain glycoprotein analysis using samples of varying complexity. We demonstrated that FAIMS was useful in increasingly complex samples as it allowed for the identification of more glycosylated species. However, during our analyses, we observed a phenomenon called "in FAIMS fragmentation" (IFF) akin to in source fragmentation but occurring during FAIMS separation. FAIMS experiments showed a 2- to 5-fold increase in spectral matches from IFF compared with control experiments. These results were also replicated in previously published data, indicating that this is likely a systemic occurrence when using FAIMS. Our study highlights that although there are potential benefits to using FAIMS separation, caution must be exercised in data analysis because of prevalent IFF, which may limit its applicability in the broader field of O-glycoproteomics.

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.

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.

Simplified Liquid Chromatography–Mass Spectrometry Methods for Gestagen Analysis in Animal Fat and Liver

Gestagens, a class of veterinary drugs also called progestogens, are synthetic hormones used to increase feed efficiency and rate of gain in heifers. The Canadian Food Inspection Agency analyzes progestogens melengestrol acetate (MGA), megestrol acetate, and chlormadinone acetate using liquid chromatography–mass spectrometry (LC–MS). Our conventional gestagen method for kidney fat has many time-consuming steps, including solid-phase extraction. A sample preparation procedure having fewer clean-up steps was developed for routine diagnostic analysis of kidney fat and provided similar results faster, and at lower cost. A confirmatory liver method for gestagens, developed using salt-assisted extraction, employed minimal clean-up steps that resulted in high chemical background at the desired lower limit of quantification (LLOQ). Differential ion mobility spectrometry, specifically high-field asymmetric waveform ion mobility spectrometry (FAIMS), was used to filter chemical background in the gas phase. The effect of the ionization probe position on FAIMS parameters, including sensitivity, is described. With LC-FAIMS-MS, chemical background for each gestagen was virtually eliminated, resulting in a quantitative liver method having the desired 0.6 ng/g LLOQ and estimated limits of detection (LODs) up to 140 times lower than LC-MS. Incurred MGA samples, analyzed using kidney fat and liver methods from the same animal, show levels within the quantitative ranges of both methods.