Factorial experimental designs elucidate significant variables affecting data acquisition on a quadrupole Orbitrap mass spectrometer

Definitive Screening Designs to Optimize Library-Free DIA-MS Identification and Quantification of Neuropeptides

Method optimization is crucial for successful mass spectrometry (MS) analysis. However, extensive method assessments, altering various parameters individually, are rarely performed due to practical limitations regarding time and sample quantity. To maximize sample space for optimization while maintaining reasonable instrumentation requirements, a definitive screening design (DSD) is leveraged for systematic optimization of data-independent acquisition (DIA) parameters to maximize crustacean neuropeptide identifications. While DSDs require several injections, a library-free methodology enables surrogate sample usage for comprehensive optimization of MS parameters to assess biomolecules from limited samples. We identified several parameters contributing significant first- or second-order effects to method performance, and the DSD model predicted ideal values to implement. These increased reproducibility and detection capabilities enabled the identification of 461 peptides, compared to 375 and 262 peptides identified through data-dependent acquisition (DDA) and a published DIA method for crustacean neuropeptides, respectively. Herein, we demonstrate a DSD optimization workflow, using standard material, not reliant on spectral libraries for the analysis of any low abundance molecules from previous samples of limited availability. This extends the DIA method to low abundance isoforms dysregulated or only detectable in disease samples, thus improving characterization of previously inaccessible biomolecules, such as neuropeptides. Data are available via ProteomeXchange with identifier PXD038520.

Boost-DiLeu: Enhanced Isobaric N,N-Dimethyl Leucine Tagging Strategy for a Comprehensive Quantitative Glycoproteomic Analysis

Intact glycopeptide analysis has been of great interest because it can elucidate glycosylation site information and glycan structural composition at the same time. However, mass spectrometry (MS)-based glycoproteomic analysis is hindered by the low abundance and poor ionization efficiency of glycopeptides. Relatively large amounts of starting materials are needed for the enrichment, which makes the identification and quantification of intact glycopeptides from samples with limited quantity more challenging. To overcome these limitations, we developed an improved isobaric labeling strategy with an additional boosting channel to enhance N,N-dimethyl leucine (DiLeu) tagging-based quantitative glycoproteomic analysis, termed as Boost-DiLeu. With the integration of a one-tube sample processing workflow and high-pH fractionation, 3514 quantifiable N-glycopeptides were identified from 30 μg HeLa cell tryptic digests with reliable quantification performance. Furthermore, this strategy was applied to human cerebrospinal fluid (CSF) samples to differentiate N-glycosylation profiles between Alzheimer's disease (AD) patients and non-AD donors. The results revealed processes and pathways affected by dysregulated N-glycosylation in AD, including platelet degranulation, cell adhesion, and extracellular matrix, which highlighted the involvement of N-glycosylation aberrations in AD pathogenesis. Moreover, weighted gene coexpression network analysis (WGCNA) showed nine modules of glycopeptides, two of which were associated with the AD phenotype. Our results demonstrated the feasibility of using this strategy for in-depth glycoproteomic analysis of size-limited clinical samples. Taken together, we developed and optimized a strategy for the enhanced comprehensive quantitative intact glycopeptide analysis with DiLeu labeling, showing significant promise for identifying novel therapeutic targets or biomarkers in biological systems with a limited sample quantity.

Mass Spectrometric Profiling of Neuropeptides in Response to Copper Toxicity via Isobaric Tagging

Copper is a necessary nutrient but quickly becomes toxic at elevated levels. To properly handle environmental copper influxes and maintain metal homeostasis, organisms utilize various methods to chelate, excrete, and metabolize heavy metals. These mechanisms are believed to involve complex signaling pathways mediated by neuropeptides. This study incorporates custom N,N-dimethyl leucine isobaric tags to characterize the neuropeptidomic changes after different time points (1, 2, and 4 h) of copper exposure in a model organism, blue crab, Callinectes sapidus. Using a modified simplex optimization strategy, the number of identifiable and quantifiable neuropeptides was increased 3-fold to facilitate a deeper understanding of the signaling pathways involved in responding to heavy metal exposure. The time course exposure showed many interesting findings, including upregulation of inhibitory allatostatin peptides in the pericardial organs. Additionally, there was evidence of transport of a pigment dispersing hormone from the sinus glands to the brain. Overall, this study improves the multiplexing capabilities of neuropeptidomic studies to understand the temporal changes associated with copper toxicity.

Electron Transfer Dissociation Parameter Optimization Using Design of Experiments Increases Sequence Coverage of Monoclonal Antibodies

Middle-down analysis of monoclonal antibodies (mAbs) by tandem mass spectrometry (MS²) can provide detailed insight into their primary structure with minimal sample preparation. The middle-down approach uses an enzyme to cleave mAbs into Fc/2, LC, and Fd subunits that are then analyzed by reversed phase liquid chromatography tandem mass spectrometry (RPLC-MS²). As maximum sequence coverage is desired to obtain meaningful structural information at the subunit level, a host of dissociation methods have been developed, and sometimes combined, to bolster fragmentation and increase the number of identified fragments. Here, we present a design of experiments (DOE) approach to optimize MS² parameters, in particular those that may influence electron transfer dissociation (ETD) efficiency to increase the sequence coverage of antibody subunits. Applying this approach to the NIST monoclonal antibody standard (NISTmAb) using three RPLC-MS² runs resulted in high sequence coverages of 67%, 67%, and 52% for Fc/2, LC, and Fd subunits, respectively. In addition, we apply this DOE strategy to model the parameters required to maximize the number of fragments produced in "low", "medium", and "high" mass ranges, which ultimately resulted in even higher sequence coverages of NISTmAb subunits (75%, 78%, and 64% for Fc/2, LC, and Fd subunits, respectively). The DOE approach provides high sequence coverage percentages utilizing only one fragmentation method, ETD, and could be extended to other state-of-the-art techniques that combine multiple fragmentation mechanisms to increase coverage.

Accelerating Lipidomic Method Development through in Silico Simulation

Judicious selection of mass spectrometry (MS) acquisition parameters is essential for effectively profiling the broad diversity and dynamic range of biomolecules. Typically, acquisition parameters are individually optimized to maximally characterize analytes from each new sample matrix. This time-consuming process often ignores the synergistic relationship between MS method parameters, producing suboptimal results. Here we detail the creation of an algorithm which accurately simulates LC-MS/MS lipidomic data acquisition performance for a benchtop quadrupole-Orbitrap MS system. By coupling this simulation tool with a genetic algorithm for constrained parameter optimization, we demonstrate the efficient identification of LC-MS/MS method parameter sets individually suited for specific sample matrices. Finally, we utilize the in silico simulation to examine how continued developments in MS acquisition speed and sensitivity will further increase the power of MS lipidomics as a vital tool for impactful biochemical analysis.

Optimization of mass spectrometric parameters improve the identification performance of capillary zone electrophoresis for single-shot bottom-up proteomics analysis

The effects of MS1 injection time, MS2 injection time, dynamic exclusion time, intensity threshold, and isolation width were investigated on the numbers of peptide and protein identifications for single-shot bottom-up proteomics analysis using CZE-MS/MS analysis of a Xenopus laevis tryptic digest. An electrokinetically pumped nanospray interface was used to couple a linear-polyacrylamide coated capillary to a Q Exactive HF mass spectrometer. A sensitive method that used a 1.4 Th isolation width, 60,000 MS2 resolution, 110 ms MS2 injection time, and a top 7 fragmentation produced the largest number of identifications when the CZE loading amount was less than 100 ng. A programmable autogain control method (pAGC) that used a 1.4 Th isolation width, 15,000 MS2 resolution, 110 ms MS2 injection time, and top 10 fragmentation produced the largest number of identifications for CZE loading amounts greater than 100 ng; 7218 unique peptides and 1653 protein groups were identified from 200 ng by using the pAGC method. The effect of mass spectrometer conditions on the performance of UPLC-MS/MS was also investigated. A fast method that used a 1.4 Th isolation width, 30,000 MS2 resolution, 45 ms MS2 injection time, and top 12 fragmentation produced the largest number of identifications for 200 ng UPLC loading amount (6025 unique peptides and 1501 protein groups). This is the first report where the identification number for CZE surpasses that of the UPLC at the 200 ng loading level. However, more peptides (11476) and protein groups (2378) were identified by using UPLC-MS/MS when the sample loading amount was increased to 2 μg with the fast method. To exploit the fast scan speed of the Q-Exactive HF mass spectrometer, higher sample loading amounts are required for single-shot bottom-up proteomics analysis using CZE-MS/MS.

Optimization and Modeling of Quadrupole Orbitrap Parameters for Sensitive Analysis toward Single-Cell Proteomics

Single-cell proteomics represents a field of extremely sensitive proteomic analysis, owing to the minute amount of yet complex proteins in a single cell. Without amplification potential as of nucleic acids, single-cell mass spectrometry (MS) analysis demands special instrumentation running with optimized parameters to maximize the sensitivity and throughput for comprehensive proteomic discovery. To facilitate such analysis, we here investigated two factors critical to peptide sequencing and protein detection in shotgun proteomics, i.e. precursor ion isolation window (IW) and maximum precursor ion injection time (ITmax), on an ultrahigh-field quadrupole Orbitrap (Q-Exactive HF). Counterintuitive to the frequently used proteomic parameters for bulk samples (>100 ng), our experimental data and subsequent modeling suggested a universally optimal IW of 4.0 Th for sample quantity ranging from 100 ng to 1 ng, and a sample-quantity dependent ITmax of more than 250 ms for 1-ng samples. Compared with the benchmark condition of IW = 2.0 Th and ITmax = 50 ms, our optimization generated up to 300% increase to the detected protein groups for 1-ng samples. The additionally identified proteins allowed deeper penetration of proteome for better revealing crucial cellular functions such as signaling and cell adhesion. We hope this effort can prompt single-cell and trace proteomic analysis and enable a rational selection of MS parameters.

The PeptideAtlas of the Domestic Laying Hen

Proteomics-based biological research is greatly expanded by high-quality mass spectrometry studies, which are themselves enabled by access to quality mass spectrometry resources, such as high-quality curated proteome data repositories. We present a PeptideAtlas for the domestic chicken, containing an extensive and robust collection of chicken tissue and plasma samples with substantial value for the chicken proteomics community for protein validation and design of downstream targeted proteome quantitation. The chicken PeptideAtlas contains 6646 canonical proteins at a protein FDR of 1.3%, derived from ∼100 000 peptides at a peptide level FDR of 0.1%. The rich collection of readily accessible data is easily mined for the purposes of data validation and experimental planning, particularly in the realm of developing proteome quantitation workflows. Herein we demonstrate the use of the atlas to mine information on common chicken acute-phase proteins and biomarkers for cancer detection research, as well as their localization and polymorphisms. This wealth of information will support future proteome-based research using this highly important agricultural organism in pursuit of both chicken and human health outcomes.

Deep Coverage Proteomics Identifies More Low-Abundance Missing Proteins in Human Testis Tissue with Q-Exactive HF Mass Spectrometer

Since 2012, missing proteins (MPs) investigation has been one of the critical missions of Chromosome-Centric Human Proteome Project (C-HPP) through various biochemical strategies. On the basis of our previous testis MPs study, faster scanning and higher resolution mass-spectrometry-based proteomics might be conducive to MPs exploration, especially for low-abundance proteins. In this study, Q-Exactive HF (HF) was used to survey proteins from the same testis tissues separated by two separating methods (tricine- and glycine-SDS-PAGE), as previously described. A total of 8526 proteins were identified, of which more low-abundance proteins were uniquely detected in HF data but not in our previous LTQ Orbitrap Velos (Velos) reanalysis data. Further transcriptomics analysis showed that these uniquely identified proteins by HF also had lower expression at the mRNA level. Of the 81 total identified MPs, 74 and 39 proteins were listed as MPs in HF and Velos data sets, respectively. Among the above MPs, 47 proteins (43 neXtProt PE2 and 4 PE3) were ranked as confirmed MPs after verifying with the stringent spectra match and isobaric and single amino acid variants filtering. Functional investigation of these 47 MPs revealed that 11 MPs were testis-specific proteins and 7 MPs were involved in spermatogenesis process. Therefore, we concluded that higher scanning speed and resolution of HF might be factors for improving the low-abundance MP identification in future C-HPP studies. All mass-spectrometry data from this study have been deposited in the ProteomeXchange with identifier PXD004092.

Optimizing Mass Spectrometry Analyses: A Tailored Review on the Utility of Design of Experiments

Mass spectrometry (MS) has emerged as a tool that can analyze nearly all classes of molecules, with its scope rapidly expanding in the areas of post-translational modifications, MS instrumentation, and many others. Yet integration of novel analyte preparatory and purification methods with existing or novel mass spectrometers can introduce new challenges for MS sensitivity. The mechanisms that govern detection by MS are particularly complex and interdependent, including ionization efficiency, ion suppression, and transmission. Performance of both off-line and MS methods can be optimized separately or, when appropriate, simultaneously through statistical designs, broadly referred to as "design of experiments" (DOE). The following review provides a tutorial-like guide into the selection of DOE for MS experiments, the practices for modeling and optimization of response variables, and the available software tools that support DOE implementation in any laboratory. This review comes 3 years after the latest DOE review (Hibbert DB, 2012), which provided a comprehensive overview on the types of designs available and their statistical construction. Since that time, new classes of DOE, such as the definitive screening design, have emerged and new calls have been made for mass spectrometrists to adopt the practice. Rather than exhaustively cover all possible designs, we have highlighted the three most practical DOE classes available to mass spectrometrists. This review further differentiates itself by providing expert recommendations for experimental setup and defining DOE entirely in the context of three case-studies that highlight the utility of different designs to achieve different goals. A step-by-step tutorial is also provided.

Optimization of parameters affecting signal intensity in an LTQ-orbitrap in negative ion mode: A design of experiments approach

A multistage optimization of all the parameters affecting detection/response in an LTQ-orbitrap analyzer was performed, using a design of experiments methodology. The signal intensity, a critical issue for mass analysis, was investigated and the optimization process was completed in three successive steps, taking into account the three main regions of an orbitrap, the ion generation, the ion transmission and the ion detection regions. Oleuropein and hydroxytyrosol were selected as the model compounds. Overall, applying this methodology the sensitivity was increased more than 24%, the resolution more than 6.5%, whereas the elapsed scan time was reduced nearly to its half. A high-resolution LTQ Orbitrap Discovery mass spectrometer was used for the determination of the analytes of interest. Thus, oleuropein and hydroxytyrosol were infused via the instruments syringe pump and they were analyzed employing electrospray ionization (ESI) in the negative high-resolution full-scan ion mode. The parameters of the three main regions of the LTQ-orbitrap were independently optimized in terms of maximum sensitivity. In this context, factorial design, response surface model and Plackett-Burman experiments were performed and analysis of variance was carried out to evaluate the validity of the statistical model and to determine the most significant parameters for signal intensity. The optimum MS conditions for each analyte were summarized and the method optimum condition was achieved by maximizing the desirability function. Our observation showed good agreement between the predicted optimum response and the responses collected at the predicted optimum conditions.

Elucidation of Xylem-Specific Transcription Factors and Absolute Quantification of Enzymes Regulating Cellulose Biosynthesis in Populus trichocarpa

Cellulose, the main chemical polymer of wood, is the most abundant polysaccharide in nature.1 The ability to perturb the abundance and structure of cellulose microfibrils is of critical importance to the pulp and paper industry as well as for the textile, wood products, and liquid biofuels industries. Although much has been learned at the transcript level about the biosynthesis of cellulose, a quantitative understanding at the proteome level has yet to be established. The study described herein sought to identify the proteins directly involved in cellulose biosynthesis during wood formation in Populus trichocarpa along with known xylem-specific transcription factors involved in regulating these key proteins. Development of an effective discovery proteomic strategy through a combination of subcellular fractionation of stem differentiating xylem tissue (SDX) with recently optimized FASP digestion protocols, StageTip fractionation, as well as optimized instrument parameters for global proteomic analysis using the quadrupole-orbitrap mass spectrometer resulted in the deepest proteomic coverage of SDX protein from P. trichocarpa with 9,146 protein groups being identified (1% FDR). Of these, 20 cellulosic/hemicellulosic enzymes and 43 xylem-specific transcription factor groups were identified. Finally, selection of surrogate peptides led to an assay for absolute quantification of 14 cellulosic proteins in SDX of P. trichocarpa.

Global Proteomic Analysis of Functional Compartments in Immature Avian Follicles Using Laser Microdissection Coupled to LC-MS/MS

Laser microdissection (LMD) was utilized for the separation of the yolk, follicular wall (granulosa and theca), and surrounding stromal cells of small white follicles (SWF) obtained from reproductively active domestic fowl. Herein, we provide an in situ proteomics-based approach to studying follicular development through the use of LMD and mass spectrometry. This study resulted in a total of 2889 proteins identified from the three specific isolated compartments. White yolk from the smallest avian follicles resulted in the identification of 1984 proteins, while isolated follicular wall and ovarian stroma yielded 2470 and 2456 proteins, respectively. GO annotations highlighted the functional differences between the compartments. Among the three compartments examined, the relative abundance of vitellogenins, steroidogenic enzymes, anti-Mullerian hormone, transcription factors, and proteins involved in retinoic acid receptors/retinoic acid synthesis, transcription factors, and cell surface receptors such as EGFR and their associated signaling pathways reflected known cellular function of the ovary. This study has provided a global proteome for SWF, white yolk, and ovarian stroma of the avian ovary that can be used as a baseline for future studies and verifies that the coupling of LMD with proteomic analysis can be used to evaluate proteins from small, physiologically functional compartments of complex tissue.

Performance metrics for evaluating system suitability in liquid chromatography--Mass spectrometry peptide mass mapping of protein therapeutics and monoclonal antibodies

The use of liquid chromatography--mass spectrometry (LC-MS) for the characterization of proteins can provide a plethora of information related to their structure, including amino acid sequence determination and analysis of posttranslational modifications. The variety of LC-MS based applications has led to the use of LC-MS characterization of therapeutic proteins and monoclonal antibodies as an integral part of the regulatory approval process. However, the improper use of an LC-MS system, related to intrinsic instrument limitations, improper tuning parameters, or poorly optimized methods may result in the production of low quality data. Improper system performance may arise from subtle changes in operating conditions that limit the ability to detect low abundance species. To address this issue, we systematically evaluated LC-MS/MS operating parameters to identify a set of metrics that can be used in a workflow to determine if a system is suitable for its intended purpose. Development of this workflow utilized a bovine serum albumin (BSA) digest standard spiked with synthetic peptides present at 0.1% to 100% of the BSA digest peptide concentration to simulate the detection of low abundance species using a traditional bottom-up workflow and data-dependent MS(2) acquisition. BSA sequence coverage, a commonly used indicator for instrument performance did not effectively identify settings that led to limited dynamic range or poorer absolute mass accuracy on 2 separate LC-MS systems. Additional metrics focusing on the detection limit and sensitivity for peptide identification were determined to be necessary to establish system suitability for protein therapeutic characterization by LC-MS.

Definitive Screening Design Optimization of Mass Spectrometry Parameters for Sensitive Comparison of Filter and Solid Phase Extraction Purified, INLIGHT Plasma N-Glycans

High-throughput, quantitative processing of N-linked glycans would facilitate large-scale studies correlating the glycome with disease and open the field to basic and applied researchers. We sought to meet these goals by coupling filter-aided-N-glycan separation (FANGS) to the individuality normalization when labeling with glycan hydrazide tags (INLIGHT) for analysis of plasma. A quantitative comparison of this method was conducted against solid phase extraction (SPE), a ubiquitous and trusted method for glycan purification. We demonstrate that FANGS-INLIGHT purification was not significantly different from SPE in terms of glycan abundances, variability, functional classes, or molecular weight distributions. Furthermore, to increase the depth of glycome coverage, we executed a definitive screening design of experiments (DOE) to optimize the MS parameters for glycan analyses. We optimized MS parameters across five N-glycan responses using a standard glycan mixture, translated these to plasma and achieved up to a 3-fold increase in ion abundances.

Multiplexed peptide analysis using data-independent acquisition and Skyline

Here we describe the use of data-independent acquisition (DIA) on a Q-Exactive mass spectrometer for the detection and quantification of peptides in complex mixtures using the Skyline Targeted Proteomics Environment (freely available online at http://skyline.maccosslab.org). The systematic acquisition of mass spectrometry (MS) or tandem MS (MS/MS) spectra by DIA is in contrast to DDA, in which the acquired MS/MS spectra are only suitable for the identification of a stochastically sampled set of peptides. Similarly to selected reaction monitoring (SRM), peptides can be quantified from DIA data using targeted chromatogram extraction. Unlike SRM, data acquisition is not constrained to a predetermined set of target peptides. In this protocol, a spectral library is generated using data-dependent acquisition (DDA), and chromatograms are extracted from the DIA data for all peptides in the library. As in SRM, quantification using DIA data is based on the area under the curve of extracted MS/MS chromatograms. In addition, a quality control (QC) method suitable for DIA based on targeted MS/MS acquisition is detailed. Not including time spent acquiring data, and time for database searching, the procedure takes ∼1-2 h to complete. Typically, data acquisition requires roughly 1-4 h per sample, and a database search will take 0.5-2 h to complete.

Comprehensive lipidome analysis by shotgun lipidomics on a hybrid quadrupole-orbitrap-linear ion trap mass spectrometer

Here we report on the application of a novel shotgun lipidomics platform featuring an Orbitrap Fusion mass spectrometer equipped with an automated nanoelectrospray ion source. To assess the performance of the platform for in-depth lipidome analysis, we evaluated various instrument parameters, including its high resolution power unsurpassed by any other contemporary Orbitrap instrumentation, its dynamic quantification range and its efficacy for in-depth structural characterization of molecular lipid species by quadrupole-based higher-energy collisional dissociation (HCD), and ion trap-based resonant-excitation collision-induced dissociation (CID). This evaluation demonstrated that FTMS analysis with a resolution setting of 450,000 allows distinguishing isotopes from different lipid species and features a linear dynamic quantification range of at least four orders of magnitude. Evaluation of fragmentation analysis demonstrated that combined use of HCD and CID yields complementary fragment ions of molecular lipid species. To support global lipidome analysis, we designed a method, termed MS(ALL), featuring high resolution FTMS analysis for lipid quantification, and FTMS(2) analysis using both HCD and CID and ITMS(3) analysis utilizing dual CID for in-depth structural characterization of molecular glycerophospholipid species. The performance of the MS(ALL) method was benchmarked in a comparative analysis of mouse cerebellum and hippocampus. This analysis demonstrated extensive lipidome quantification covering 311 lipid species encompassing 20 lipid classes, and identification of 202 distinct molecular glycerophospholipid species when applying a novel high confidence filtering strategy. The work presented here validates the performance of the Orbitrap Fusion mass spectrometer for in-depth lipidome analysis.

The Q Exactive HF, a Benchtop mass spectrometer with a pre-filter, high-performance quadrupole and an ultra-high-field Orbitrap analyzer

The quadrupole Orbitrap mass spectrometer (Q Exactive) made a powerful proteomics instrument available in a benchtop format. It significantly boosted the number of proteins analyzable per hour and has now evolved into a proteomics analysis workhorse for many laboratories. Here we describe the Q Exactive Plus and Q Exactive HF mass spectrometers, which feature several innovations in comparison to the original Q Exactive instrument. A low-resolution pre-filter has been implemented within the injection flatapole, preventing unwanted ions from entering deep into the system, and thereby increasing its robustness. A new segmented quadrupole, with higher fidelity of isolation efficiency over a wide range of isolation windows, provides an almost 2-fold improvement of transmission at narrow isolation widths. Additionally, the Q Exactive HF has a compact Orbitrap analyzer, leading to higher field strength and almost doubling the resolution at the same transient times. With its very fast isolation and fragmentation capabilities, the instrument achieves overall cycle times of 1 s for a top 15 to 20 higher energy collisional dissociation method. We demonstrate the identification of 5000 proteins in standard 90-min gradients of tryptic digests of mammalian cell lysate, an increase of over 40% for detected peptides and over 20% for detected proteins. Additionally, we tested the instrument on peptide phosphorylation enriched samples, for which an improvement of up to 60% class I sites was observed.

Practical Considerations and Current Limitations in Quantitative Mass Spectrometry-based Proteomics

Quantitative mass spectrometry (MS)-based proteomics continues to evolve through advances in sample preparation, chemical and biochemical reagents, instrumentation, and software. The breadth of proteomes and biological applications combined with unique experimental goals makes optimizing MS-based proteomics workflows a daunting task. Several MS-based instrument platforms are commercially available with LC-MS/MS being the most common for quantitative proteomics studies. Although the direction of LC-MS/MS instrumentation development is toward more user-friendly interfaces, there remain fundamental aspects of the technology that can be optimized for improving data quality. The intent of this chapter is to provide an introductory framework for understanding some of the more significant LC-MS/MS experimental conditions that can influence quantitative MS-based proteomics measurements, including electrospray ionization (ESI) bias and ion transmission efficiency. Because each commercial LC-MS/MS system is unique with regard to ESI source, transmission optics, ion isolation and trapping, ion fragmentation, and mass analysis, the use of design of experiments (DoE) is discussed as a potential approach for efficiently optimizing multiple inter-related factors.

Accurate identification of deamidated peptides in global proteomics using a quadrupole orbitrap mass spectrometer

Deamidation of asparagine and glutamine residues is a common post-translational modification. Researchers often rely on mass spectrometric based proteomic techniques for the identification of these post-translational sites. Mass spectral analysis of deamidated peptides is complicated and often misassigned due to overlapping (13)C peak of the amidated form with the deamidated monoisotopic peak; these two peaks are only separated by 19.34 mDa. For proper assignment, it is inherently important to use a mass spectrometer with high mass measurement accuracy and high resolving power. Herein, mouse brain tissue lysate was prepared using filter-aided sample preparation (FASP) method and Stage Tip fractionation followed by analysis on a nanoLC coupled with a quadrupole orbitrap (Q-Exactive) mass spectrometer to accurately identify more than 5400 proteins. Mass spectral data was processed using MASCOT and ProteoIQ for accurate identification of peptides and proteins. MASCOT search values for precursor and MS/MS mass tolerances were investigated, and it was determined that data searched with greater than 5 ppm precursor mass tolerance resulted in the misassignment of deamidated peptides. Peptides that were identified with a mass measurement accuracy of ±5 ppm were correctly assigned.