Collision-Induced Unfolding, Tandem MS, Bottom-up Proteomics, and Interactomics for Identification of Protein Complexes in Native Surface Mass Spectrometry.

Endogenously occurring salts and nonvolatile matrix components in untreated biological surfaces can suppress protein ionization and promote adduct formation, challenging protein identification. Characterization of labile proteins within biological specimens is particularly demanding because additional purification or sample treatment steps can be time-intensive and can disrupt noncovalent interactions. It is demonstrated that the combined use of collision-induced unfolding, tandem mass spectrometry, and bottom-up proteomics improves protein characterization in native surface mass spectrometry (NSMS). This multiprong analysis is achieved by acquiring NSMS, MS/MS, ion mobility (IM), and bottom-up proteomics data from a single surface extracted sample. The validity of this multiprong approach was confirmed by the successful characterization of nine surface-deposited proteins, with molecular weights ranging from 8 to 147 kDa, in two separate mixtures. Bottom-up proteomics provided a list of proteins to match against observed proteins in NSMS and their detected subunits in tandem MS. The method was applied to characterize endogenous proteins from untreated chicken liver samples. The subcapsular liver sampling for NSMS analysis allowed for the detection of endogenous proteins with molecular weights of up to ∼220 kDa. Moreover, using IM-MS, collision cross sections and collision-induced unfolding pathways of enzymatic proteins and protein complexes of up to 145 kDa were obtained.

Native Mass Spectrometry and Collision-Induced Unfolding of Laser-Ablated Proteins.

Infrared laser ablation sample transfer (LAST) was used to collect samples from solid surfaces for mass spectrometry under native spray conditions. Native mass spectrometry was utilized to probe the charge states and collision-induced unfolding (CIU) characteristics of bovine serum albumin (BSA), bovine hemoglobin (BHb), and jack-bean concanavalin A (ConA) via direct injection electrospray, after liquid extraction surface sampling, and after LAST. Each protein was deposited from solution on solid surfaces and laser-ablated for off-line analysis or sampled for online analysis. It was found that the protein ion gas-phase charge-state distributions were comparable for direct infusion, liquid extraction, and laser ablation experiments. Moreover, calculated average collision cross section (CCS) values from direct injection, liquid extraction, and laser ablation experiments were consistent with previously reported literature values. Additionally, an equivalent number of mobility features and conformational turnovers were identified from unfolding pathways from all three methods for all charge states of each protein analyzed in this work. The presented work suggests that laser ablation yields intact proteins (BSA, BHb, and ConA), is compatible with native mass spectrometry, and could be suitable for spatially resolved interrogation of unfolding pathways of proteins.

Referenced Kendrick Mass Defect Annotation and Class-Based Filtering of Imaging MS Lipidomics Experiments.

Because of their diverse functionalities in cells, lipids are of primary importance when characterizing molecular profiles of physiological and disease states. Imaging mass spectrometry (IMS) provides the spatial distributions of lipid populations in tissues. Referenced Kendrick mass defect (RKMD) analysis is an effective mass spectrometry (MS) data analysis tool for classification and annotation of lipids. Herein, we extend the capabilities of RKMD analysis and demonstrate an integrated method for lipid annotation and chemical structure-based filtering for IMS datasets. Annotation of lipid features with lipid molecular class, radyl carbon chain length, and degree of unsaturation allows image reconstruction and visualization based on each structural characteristic. We show a proof-of-concept application of the method to a computationally generated IMS dataset and validate that the RKMD method is highly specific for lipid components in the presence of confounding background ions. Moreover, we demonstrate an application of the RKMD-based annotation and filtering to matrix-assisted laser desorption/ionization (MALDI) IMS lipidomic data from human kidney tissue analysis.

Infrared Laser Ablation Microsampling with a Reflective Objective.

A Schwarzschild reflective objective with a numerical aperture of 0.3 and working distance of 10 cm was used for laser ablation sampling of tissue for off-line mass spectrometry. The objective focused the laser to a diameter of 5 µm and produced 10 µm ablation spots on thin ink films and tissue sections. Rat brain tissue sections 50 µm thick were ablated in transmission geometry, and the ablated material was captured in a microcentrifuge tube containing solvent. Proteins from ablated tissue sections were quantified with a Bradford assay, which indicated that approximately 300 ng of protein was captured from a 1 mm2 area of ablated tissue. Areas of tissue ranging from 0.01 to 1 mm2 were ablated and captured for bottom-up proteomics. Proteins were extracted from the captured tissue and digested for liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis for peptide and protein identification.

Decontamination of metals from firefighter turnout gear.

Firefighters are exposed to many different contaminants during structural fires. Moreover, if their protective gear is not successfully decontaminated, firefighters are at risk of being repeatedly exposed to contaminants from previous fires. Thus, the successful removal of contaminants from firefighter turnout gear is necessary to prevent or reduce repeated exposure risks. Laundering methods can reduce the probability of re-exposure to contaminants, such as heavy metals, thus reducing repeated exposure risks. In this study, the efficiencies of heavy metal removal from the firefighter turnout gear outer textile by Decon7 cleaning solution and a standard reference detergent were compared. Nitric acid digests were used to extract metals from textile samples, which were cut from small sections of firefighter jackets, before and after their laundering with either cleaning solution. Inductively coupled plasma mass spectrometry (ICP-MS) was utilized to determine metal contents, including arsenic (As), antimony (Sb), cadmium (Cd), chromium (Cr), and lead (Pb) concentrations. Results from multiplicate samples indicated that, on average, Decon7 was significantly more efficient than a standard detergent in decreasing the concentrations of the five metals studied herein.

Deep-ultraviolet laser ablation sampling for proteomic analysis of tissue.

Deep-ultraviolet laser ablation with a pulsed 193 nm ArF excimer laser was used to remove localized regions from tissue sections from which proteins were extracted for spatially resolved proteomic analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS). The ability to capture intact proteins by ablation at 193 nm wavelength was verified by matrix-assisted laser desorption ionization (MALDI) of the protein standard bovine serum albumin (BSA), which showed that BSA was ablated and captured without fragmentation. A Bradford assay of the ablated and captured proteins indicated 90% efficiency for transfer of the intact protein at a laser fluence of 3 kJ/m2. Rat brain tissue sections mounted on quartz microscope slides and ablated in transmission mode yielded 2 µg protein per mm2 as quantified by the Bradford assay. Tissue areas ranging from 0.06 mm2 to 1 mm2 were ablated and the ejected material was collected for proteomic analysis. Extracted proteins were digested and the resulting peptides were analyzed by LC-MS/MS. The proteins extracted from the ablated areas were identified and the average number of identified proteins ranged from 85 in the 0.06 mm2 area to 2400 in the 1 mm2 area of a 50 µm thick tissue. In comparison to infrared laser ablation of equivalent sampled areas, both the protein mass and number of proteins identified using DUV laser ablation sampling were approximately four times larger.

Trihydroxycholanoyl-taurine in brains of rodents with hepatic encephalopathy.

Hepatic encephalopathy (HE), a neurological disease resulting from liver failure, is difficult to manage and its causes are unclear. Bile acids have been postulated to be involved in the provenance and progression of various diseases including HE. Hence, the characterization of bile acid profiles in the brains of subjects with and without liver failure can provide important clues for the potential treatment of HE. Nanoflow ultra-performance liquid chromatography electrospray ionization ion mobility mass spectrometry (UPLC-ESI-IM-MS) is a highly sensitive method for detection of specific molecules, such as bile acids in brain samples, at biologically relevant concentrations. We used UPLC-ESI-IM-MS to characterize bile acid profiles in brain samples from seven "healthy" control rodents and 22 "diseased" rodents with liver failure (i.e., induced HE). An isomer of trihydroxycholanoyl-taurine was detected in brain tissue samples from both rats and mice with induced HE; however, this isomer was not detected in the brains of healthy rats and mice. Our findings were confirmed by comparing IM arrival times (AT), exact mass measurements (m/z), and mass spectral fragmentation patterns of the experimentally observed suspected species to standards of trihydroxycholanoyl-taurine isomers. Moreover, In Silico Fractionation was employed to provide an additional analytical dimension to verify bile acid identifications.

Supercharging Prions via Amyloid-Selective Lysine Acetylation.

Repulsive electrostatic forces between prion-like proteins are a barrier against aggregation. In neuropharmacology, however, a prion's net charge (Z) is not a targeted parameter. Compounds that selectively boost prion Z remain unreported. Here, we synthesized compounds that amplified the negative charge of misfolded superoxide dismutase-1 (SOD1) by acetylating lysine-NH3+ in amyloid-SOD1, without acetylating native-SOD1. Compounds resembled a "ball and chain" mace: a rigid amyloid-binding "handle" (benzothiazole, stilbene, or styrylpyridine); an aryl ester "ball"; and a triethylene glycol chain connecting ball to handle. At stoichiometric excess, compounds acetylated up to 9 of 11 lysine per misfolded subunit (ΔZfibril =-8100 per 103 subunits). Acetylated amyloid-SOD1 seeded aggregation more slowly than unacetylated amyloid-SOD1 in vitro and organotypic spinal cord (these effects were partially due to compound binding). Compounds exhibited reactivity with other amyloid and non-amyloid proteins (e.g., fibrillar α-synuclein was peracetylated; serum albumin was partially acetylated; carbonic anhydrase was largely unacetylated).

Using isotopic envelopes and neural decision tree-based in silico fractionation for biomolecule classification.

Untargeted mass spectrometry (MS) workflows are more suitable than targeted workflows for high throughput characterization of complex biological samples. However, analysis workflows for untargeted methods are inadequate for characterization of complex samples that contain multiple classes of compounds as each chemical class might require a different type of data processing approach. To increase the feasibility of analyzing MS data for multi-class/component complex mixtures (i.e., mixtures containing more than one major class of biomolecules), we developed a neural network-based approach for classification of MS data. In our in silico fractionation (iSF) approach, we utilize a neural decision tree to sequentially classify biomolecules based on their MS-detected isotopic patterns. In the presented demonstration, the neural decision tree consisted of two supervised binary classifiers to positively classify polypeptides and lipids, respectively, and a third supervised network was trained to classify lipids into the eight main sub-categories of lipids. The two binary classifiers assigned polypeptide and lipid experimental components with 100% sensitivity and 100% specificity; however, the 8-target classifier assigned lipids into their respective subclasses with 95% sensitivity and 99% specificity. Here, we discuss important relationships between class-specific chemical properties and MS isotopic envelopes that enable analyte classification. Moreover, we evaluate the performance characteristics of the utilized networks.

MALDI imaging directed laser ablation tissue microsampling for data independent acquisition proteomics.

A multimodal workflow for mass spectrometry imaging was developed that combines MALDI imaging with protein identification and quantification by liquid chromatography tandem mass spectrometry (LC-MS/MS). Thin tissue sections were analyzed by MALDI imaging, and the regions of interest (ROI) were identified using a smoothing and edge detection procedure. A midinfrared laser at 3-µm wavelength was used to remove the ROI from the brain tissue section after MALDI mass spectrometry imaging (MALDI MSI). The captured material was processed using a single-pot solid-phase-enhanced sample preparation (SP3) method and analyzed by LC-MS/MS using ion mobility (IM) enhanced data independent acquisition (DIA) to identify and quantify proteins; more than 600 proteins were identified. Using a modified database that included isoform and the post-translational modifications chain, loss of the initial methionine, and acetylation, 14 MALDI MSI peaks were identified. Comparison of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of the identified proteins was achieved through an evolutionary relationships classification system.

Characterization of Electrospray Ionization (ESI) Parameters on In-ESI Hydrogen/Deuterium Exchange of Carbohydrate-Metal Ion Adducts.

The conformations of glycans are crucial for their biological functions. In-electrospray ionization (ESI) hydrogen/deuterium exchange-mass spectrometry (HDX-MS) is a promising technique for studying carbohydrate conformations since rapidly exchanging functional groups, e.g., hydroxyls, can be labeled on the timeframe of ESI. However, regular application of in-ESI HDX to characterize carbohydrates requires further analysis of the in-ESI HDX methodology. For instance, in this method, HDX occurs concurrently to the analyte transitioning from solution to gas-phase ions. Therefore, there is a possibility of sampling both gas-phase and solution-phase conformations of the analyte. Herein, we differentiate in-ESI HDX of metal-adducted carbohydrates from gas-phase HDX and illustrate that this method analyzes solvated species. We also systematically examine the effects of ESI parameters, including spray solvent composition, auxiliary gas flow rate, sheath gas flow rate, sample infusion rate, sample concentration, and spray voltage, and discuss their effects on in-ESI HDX. Further, we model the structural changes of a trisaccharide, melezitose, and its intramolecular and intermolecular hydrogen bonding in solvents with different compositions of methanol and water. These molecular dynamic simulations support our experimental results and illustrate how an individual ESI parameter can alter the conformations we sample by in-ESI HDX. In total, this work illustrates how the fundamental processes of ESI alter the magnitude of HDX for carbohydrates and suggest parameters that should be considered and/or optimized prior to performing experiments with this in-ESI HDX technique. Graphical Abstract ᅟ.

Identification of a panel of genes as a prognostic biomarker for glioblastoma.

BACKGROUND: Glioblastoma multiforme (GBM) is a fatal disease without effective therapy. Identification of new biomarkers for prognosis would enable more rational selections of strategies to cure patients with GBM and prevent disease relapse. METHODS: Seven datasets derived from GBM patients using microarray or next generation sequencing in R2 online database (http://r2.amc.nl) were extracted and then analyzed using JMP software. The survival distribution was calculated according to the Kaplan-Meier method and the significance was determined using log-rank statistics. The sensitivity of a panel of GBM cell lines in response to temozolomide (TMZ), salinomycin, celastrol, and triptolide treatments was evaluated using MTS and tumor-sphere formation assay. FINDINGS: We identified that CD44, ATP binding cassette subfamily C member 3 (ABCC3), and tumor necrosis factor receptor subfamily member 1A (TNFRSF1A) as highly expressed genes in GBMs are associated with patients' poor outcomes and therapy resistance. Furthermore, these three markers combined with MGMT, a conventional GBM marker, can classify GBM patients into five new subtypes with different overall survival time in response to treatment. The four-gene signature and the therapy response of GBMs to a panel of therapeutic compounds were confirmed in a panel of GBM cell lines. INTERPRETATION: The data indicate that the four-gene panel can be used as a therapy response index for GBM patients and potential therapeutic targets. These results provide important new insights into the early diagnosis and the prognosis for GBM patients and introduce potential targets for GBM therapeutics. FUND: Baylor Scott & White Health Startup Fund (E.W.); Collaborative Faculty Research Investment Program (CFRIP) of Baylor University, Baylor Scott & White Health, and Baylor College of Medicine (E.W., T.S., J.H.H.); NIH R01 NS067435 (J.H.H.); Scott & White Plummer Foundation Grant (J.H.H.); National Natural Science Foundation of China 816280007 (J.H.H. and Fu.W.).

Improving Accuracy and Confidence of Chemical Identification by Gas Chromatography/Vacuum Ultraviolet Spectroscopy-Mass Spectrometry: Parallel Gas Chromatography, Vacuum Ultraviolet, and Mass Spectrometry Library Searches.

Chemical identification often relies on matching measured chemical properties and/or spectral "fingerprints" of unknowns against their precompiled libraries. Chromatography, absorption spectroscopy, and mass spectrometry are all among analytical approaches that provide chemical measurement databases amenable to library searching. Occasionally, using conventional single-library or single-domain searches can lead to misidentification of unknowns. To improve chemical identification, we present a tandem gas chromatography/vacuum ultraviolet-mass spectrometry (GC/VUV-MS) chemical identification approach that utilizes databases from GC, VUV spectroscopy, and mass spectrometry analyses for a "multidomain" library search. Using standard chemical mixtures as well as aroma compounds as test cases, we demonstrate that multidatabase library searches utilizing GC, VUV, and MS data results in fully correct identification of chemical mixtures examined here that could only be identified with a 69.2% or an 88.5% success rate with MS or VUV library searches alone, respectively. Additionally, we introduce a library- and data domain-independent metric for evaluating the confidence of library search results. Using multidomain library searches improves both the chemical assignment accuracy and confidence.

Infrared laser ablation sampling coupled with data independent high resolution UPLC-IM-MS/MS for tissue analysis.

Infrared laser ablation microsampling was used with data-dependent acquisition (DDA) and ion mobility-enhanced data-independent acquisition (HDMSE) for mass spectrometry based bottom-up proteomics analysis of rat brain tissue. Results from HDMSE and DDA analyses of the 12 laser ablation sampled tissue sections showed that HDMSE consistently identified approximately seven times more peptides and four times more proteins than DDA. To evaluate the impact of ultra-performance liquid chromatography (UPLC) peak congestion on HDMSE and DDA analysis, whole tissue digests from rat brain were analyzed at six different UPLC separation times. Analogous to results from laser ablated samples, HDMSE analyses of whole tissue digests yielded about four times more proteins identified than DDA for all six UPLC separation times.

Broadband ion mobility deconvolution for rapid analysis of complex mixtures.

High resolving power ion mobility (IM) allows for accurate characterization of complex mixtures in high-throughput IM mass spectrometry (IM-MS) experiments. We previously demonstrated that pure component IM-MS data can be extracted from IM unresolved post-IM/collision-induced dissociation (CID) MS data using automated ion mobility deconvolution (AIMD) software [Matthew Brantley, Behrooz Zekavat, Brett Harper, Rachel Mason, and Touradj Solouki, J. Am. Soc. Mass Spectrom., 2014, 25, 1810-1819]. In our previous reports, we utilized a quadrupole ion filter for m/z-isolation of IM unresolved monoisotopic species prior to post-IM/CID MS. Here, we utilize a broadband IM-MS deconvolution strategy to remove the m/z-isolation requirement for successful deconvolution of IM unresolved peaks. Broadband data collection has throughput and multiplexing advantages; hence, elimination of the ion isolation step reduces experimental run times and thus expands the applicability of AIMD to high-throughput bottom-up proteomics. We demonstrate broadband IM-MS deconvolution of two separate and unrelated pairs of IM unresolved isomers (viz., a pair of isomeric hexapeptides and a pair of isomeric trisaccharides) in a simulated complex mixture. Moreover, we show that broadband IM-MS deconvolution improves high-throughput bottom-up characterization of a proteolytic digest of rat brain tissue. To our knowledge, this manuscript is the first to report successful deconvolution of pure component IM and MS data from an IM-assisted data-independent analysis (DIA) or HDMSE dataset.

The reaction between GSNO and H2S: On the generation of NO, HNO and N2O.

Several recent reports suggest that HNO may be produced endogenously by reaction of H2S and S-nitrosoglutathione (GSNO). This hypothesis was tested using deoxymyoglobin (MbFeII) to trap the expected HNO released from the target reaction, which should generate the stable HNO adduct, HNO-Mb, under anaerobic conditions. Under numerous experimental conditions, the sole globin product was NO-Mb, as characterized by absorbance, EPR, and NMR spectroscopies. Analogous reactions of GSNO with other biological reductants such as ascorbic acid, dithiothreitol, glutathione, and dithionite also yielded NO-Mb as the sole globin product; however, whereas analogous reduction of GSNO using NaBH4 generates HNO-Mb in high yield. Quantitative GC/MS analyses of reactions of GS15NO with H2S showed that the main reaction product was 15NO, with 15N2 produced at a comparable level to 15N2O. Overall yield of N2O is unchanged by the presence of MbFeII, discounting the intermediacy of either NO or HNO in its formation. Taken together, these results argue against the generation of free HNO as a major pathway in the reactions of GSNO with H2S, and instead imply some as yet uncharacterized intermediates generate the nitrogenic gases.

Vacuum Ultraviolet Spectroscopy and Mass Spectrometry: A Tandem Detection Approach for Improved Identification of Gas Chromatography-Eluting Compounds.

For wide class characterizations of volatile organic compounds (VOCs), conventional gas chromatography mass spectrometry (GC-MS)-based techniques are utilized. These GC-MS-based chemical identification approaches typically rely on library searches against ion fragmentation patterns of known compounds. Although MS library searches can often provide correct chemical identities, erroneous chemical assignments of structurally similar unknown compounds are also possible. Other detection systems, such as absorption spectrometers, have been used for VOC analysis and can provide complementary absorption data. Here, we demonstrate the analytical advantages of coupling vacuum ultraviolet (VUV) absorption spectroscopy and MS in tandem for the improved characterization of structurally similar VOCs. We also discuss technical considerations and limitations of coupling a VUV spectrometer to a quadrupole mass spectrometer. Moreover, we show that combining the isomer selectivity of VUV spectroscopy, as a nondestructive analyte detection approach, with the mass selectivity of MS in a VUV-MS detection system improves characterization of GC-eluting compounds. Utilizing GC/VUV-MS data, we demonstrate that orthogonal VUV and MS library searches improve identification of VOCs present in complex mixtures such as a mixed standard sample, a commercial perfume product, and an essential oil sample.

Automated peak width measurements for targeted analysis of ion mobility unresolved species.

Peak broadening in ion mobility (IM) is a relatively predictable process and abnormally broad peaks can be indicative of the presence of unresolved species. Here, we introduce a new ion mobility peak fitting (IM_FIT) software package for automated and systematic determination of traveling wave ion mobility (TWIM) unresolved species. To identify IM unresolved species, the IM_FIT software generates a trend line by plotting ions' mobility peak widths as a function of their arrival times. Utilizing user-defined thresholds, IM_FIT allows for automated and rapid detection of ions that deviate from the peak width trend line. To demonstrate the advantages of IM_FIT for automated detection of IM unresolved species, IM-mass spectrometry (IM-MS) data from a sample mixture containing polypropylene glycol and multiple peptides were analyzed. A total of 14 out of the 34 observed singly-charged IM peaks above 5% relative abundance (i.e., signal-to-noise ratios above ∼200) were tagged as potentially co-eluting ions by IM_FIT. Subsequently, the 14 IM peaks tagged as potentially unresolved (presumably, peaks corresponding to co-eluting compounds), were further analyzed by automated IM deconvolution (AIMD), liquid chromatography-IM-MS (LC-IM-MS), and/or ultra-high resolution mass spectrometry. Using the aforementioned techniques, more than 85% of the tagged IM peaks (12 out of 14) were confirmed to contain co-eluting ions. As an additional new finding, IM_FIT facilitated the discovery of an unexpected sequence-scrambled y-type fragment ion.

Determination of ion mobility collision cross sections for unresolved isomeric mixtures using tandem mass spectrometry and chemometric deconvolution.

Ion mobility (IM) is an important analytical technique for determining ion collision cross section (CCS) values in the gas-phase and gaining insight into molecular structures and conformations. However, limited instrument resolving powers for IM may restrict adequate characterization of conformationally similar ions, such as structural isomers, and reduce the accuracy of IM-based CCS calculations. Recently, we introduced an automated technique for extracting "pure" IM and collision-induced dissociation (CID) mass spectra of IM overlapping species using chemometric deconvolution of post-IM/CID mass spectrometry (MS) data [J. Am. Soc. Mass Spectrom., 2014, 25, 1810-1819]. Here we extend those capabilities to demonstrate how extracted IM profiles can be used to calculate accurate CCS values of peptide isomer ions which are not fully resolved by IM. We show that CCS values obtained from deconvoluted IM spectra match with CCS values measured from the individually analyzed corresponding peptides on uniform field IM instrumentation. We introduce an approach that utilizes experimentally determined IM arrival time (AT) "shift factors" to compensate for ion acceleration variations during post-IM/CID and significantly improve the accuracy of the calculated CCS values. Also, we discuss details of this IM deconvolution approach and compare empirical CCS values from traveling wave (TW)IM-MS and drift tube (DT)IM-MS with theoretically calculated CCS values using the projected superposition approximation (PSA). For example, experimentally measured deconvoluted TWIM-MS mean CCS values for doubly-protonated RYGGFM, RMFGYG, MFRYGG, and FRMYGG peptide isomers were 288.8 Å(2), 295.1 Å(2), 296.8 Å(2), and 300.1 Å(2); all four of these CCS values were within 1.5% of independently measured DTIM-MS values.

Evidence for electron-based ion generation in radio-frequency ionization.

Radio-frequency ionization (RFI) is a novel ionization method coupled to mass spectrometry (MS) for analysis of semi-volatile and volatile organic compounds (VOCs). Despite the demonstrated capabilities of RFI MS for VOC analysis in both positive- and negative-ion modes, mechanism of RFI is not completely understood. Improved understanding of the ion generation process in RFI should expand its utility in MS. Here, we studied the possibility of electron emission in RFI using both direct charged particle current measurements and indirect electron detection in a 9.4-T Fourier transform-ion cyclotron resonance (FT-ICR) mass spectrometer. We show that RF-generated electrons can be trapped in the ICR cell and, subsequently, reacted with neutral hexafluorobenzene (C6 F6 ) molecules to generate C6 F6 (●-) . Intensity of observed C6 F6 (●-) species correlated with the number of trapped electrons and decreased as a function of electron quenching period. We also measured the electron attachment rate constant of hexafluorobenzene using a post-RF electron trapping experiment. Measured electron attachment rate constant of hexafluorobenzene (1.19 (±0.53) × 10(-9) cm(3) molecule(-1) s(-1) ) for post-RF FT-ICR MS agreed with the previously reported value (1.60 (±0.30) × 10(-9) cm(3) molecule(-1) s(-1) ) from low-pressure ICR MS measurements. Experimental results from direct and indirect electron measurements suggest that RFI process involves RF-generated electrons under ultrahigh vacuum conditions.