Improving protein identification using complementary fragmentation techniques in fourier transform mass spectrometry

Identification of proteins by MS/MS is performed by matching experimental mass spectra against calculated spectra of all possible peptides in a protein data base. The search engine assigns each spectrum a score indicating how well the experimental data complies with the expected one; a higher score means increased confidence in the identification. One problem is the false-positive identifications, which arise from incomplete data as well as from the presence of misleading ions in experimental mass spectra due to gas-phase reactions, stray ions, contaminants, and electronic noise. We employed a novel technique of reduction of false positives that is based on a combined use of orthogonal fragmentation techniques electron capture dissociation (ECD) and collisionally activated dissociation (CAD). Since ECD and CAD exhibit many complementary properties, their combined use greatly increased the analysis specificity, which was further strengthened by the high mass accuracy (approximately 1 ppm) afforded by Fourier transform mass spectrometry. The utility of this approach is demonstrated on a whole cell lysate from Escherichia coli. Analysis was made using the data-dependent acquisition mode. Extraction of complementary sequence information was performed prior to data base search using in-house written software. Only masses involved in complementary pairs in the MS/MS spectrum from the same or orthogonal fragmentation techniques were submitted to the data base search. ECD/CAD identified twice as many proteins at a fixed statistically significant confidence level with on average a 64% higher Mascot score. The confidence in protein identification was hereby increased by more than 1 order of magnitude. The combined ECD/CAD searches were on average 20% faster than CAD-only searches. A specially developed test with scrambled MS/MS data revealed that the amount of false-positive identifications was dramatically reduced by the combined use of CAD and ECD.     

Andromeda: a peptide search engine integrated into the MaxQuant environment

A key step in mass spectrometry (MS)-based proteomics is the identification of peptides in sequence databases by their fragmentation spectra. Here we describe Andromeda, a novel peptide search engine using a probabilistic scoring model. On proteome data, Andromeda performs as well as Mascot, a widely used commercial search engine, as judged by sensitivity and specificity analysis based on target decoy searches. Furthermore, it can handle data with arbitrarily high fragment mass accuracy, is able to assign and score complex patterns of post-translational modifications, such as highly phosphorylated peptides, and accommodates extremely large databases. The algorithms of Andromeda are provided. Andromeda can function independently or as an integrated search engine of the widely used MaxQuant computational proteomics platform and both are freely available at www.maxquant.org. The combination enables analysis of large data sets in a simple analysis workflow on a desktop computer. For searching individual spectra Andromeda is also accessible via a web server. We demonstrate the flexibility of the system by implementing the capability to identify cofragmented peptides, significantly improving the total number of identified peptides.     

Incorporating sequence information into the scoring function: a hidden Markov model for improved peptide identification

MOTIVATION: The identification of peptides by tandem mass spectrometry (MS/MS) is a central method of proteomics research, but due to the complexity of MS/MS data and the large databases searched, the accuracy of peptide identification algorithms remains limited. To improve the accuracy of identification we applied a machine-learning approach using a hidden Markov model (HMM) to capture the complex and often subtle links between a peptide sequence and its MS/MS spectrum. Model: Our model, HMM_Score, represents ion types as HMM states and calculates the maximum joint probability for a peptide/spectrum pair using emission probabilities from three factors: the amino acids adjacent to each fragmentation site, the mass dependence of ion types and the intensity dependence of ion types. The Viterbi algorithm is used to calculate the most probable assignment between ion types in a spectrum and a peptide sequence, then a correction factor is added to account for the propensity of the model to favor longer peptides. An expectation value is calculated based on the model score to assess the significance of each peptide/spectrum match. RESULTS: We trained and tested HMM_Score on three data sets generated by two different mass spectrometer types. For a reference data set recently reported in the literature and validated using seven identification algorithms, HMM_Score produced 43% more positive identification results at a 1% false positive rate than the best of two other commonly used algorithms, Mascot and X!Tandem. HMM_Score is a highly accurate platform for peptide identification that works well for a variety of mass spectrometer and biological sample types. AVAILABILITY: The program is freely available on ProteomeCommons via an OpenSource license. See http://bioinfo.unc.edu/downloads/ for the download link.     

Application of different fragmentation techniques for the analysis of phosphopeptides using a hybrid linear ion trap-FTICR mass spectrometer

Electron capture dissociation (ECD) and infrared multiphoton dissociation (IRMPD) present complementary techniques for the fragmentation of peptides and proteins in Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) in addition to the commonly used collisionally activated dissociation (CAD). Both IRMPD and ECD have been shown to be applicable for an efficient sequencing of peptides and proteins, whereas ECD has proven especially valuable for mapping labile posttranslational modifications (PTMs), such as phosphorylations. In this work, we compare the different fragmentation techniques and MS detection in a linear ion trap and the ICR cell with respect to their abilities to efficiently identify and characterize phosphorylated peptides. For optimizing fragmentation parameters, sets of synthetic peptides with molecular weights ranging from approximately 1 to 4 kDa and different levels of phosphorylation were analyzed. The influence of spectrum averaging for obtaining high-quality spectra was investigated. Our results show that the fragmentation methods CAD and ECD allow for a facilitated analysis of phosphopeptides; however, their general applicability for analyzing phosphopeptides has to be evaluated in each specific case with respect to the given analytical task. The major advantage of complementary peptide cleavages by combining different fragmentation methods is the increased amount of information that is obtained during MS/MS analysis of modified peptides. On the basis of the obtained results, we are planning to design LC time-scale compatible, data-dependent MS/MS methods using the different fragmentation techniques in order to improve the identification and characterization of phosphopeptides.     

Optimization and use of peptide mass measurement accuracy in shotgun proteomics

Mass spectrometers that provide high mass accuracy such as FT-ICR instruments are increasingly used in proteomic studies. Although the importance of accurately determined molecular masses for the identification of biomolecules is generally accepted, its role in the analysis of shotgun proteomic data has not been thoroughly studied. To gain insight into this role, we used a hybrid linear quadrupole ion trap/FT-ICR (LTQ FT) mass spectrometer for LC-MS/MS analysis of a highly complex peptide mixture derived from a fraction of the yeast proteome. We applied three data-dependent MS/MS acquisition methods. The FT-ICR part of the hybrid mass spectrometer was either not exploited, used only for survey MS scans, or also used for acquiring selected ion monitoring scans to optimize mass accuracy. MS/MS data were assigned with the SEQUEST algorithm, and peptide identifications were validated by estimating the number of incorrect assignments using the composite target/decoy database search strategy. We developed a simple mass calibration strategy exploiting polydimethylcyclosiloxane background ions as calibrant ions. This strategy allowed us to substantially improve mass accuracy without reducing the number of MS/MS spectra acquired in an LC-MS/MS run. The benefits of high mass accuracy were greatest for assigning MS/MS spectra with low signal-to-noise ratios and for assigning phosphopeptides. Confident peptide identification rates from these data sets could be doubled by the use of mass accuracy information. It was also shown that improving mass accuracy at a cost to the MS/MS acquisition rate substantially lowered the sensitivity of LC-MS/MS analyses. The use of FT-ICR selected ion monitoring scans to maximize mass accuracy reduced the number of protein identifications by 40%.     

Synthesis of acid-cleavable light isotope-coded affinity tags (ICAT-L) for potential use in proteomic expression profiling analysis

A convenient synthesis of some homologous light isotope-coded affinity tags (ICAT-L) containing an acid-labile moiety between the affinity component biotin and an electrophilic polar linker is described. These light ICAT reagents give smooth mass spectral signals in tandem mass spectrometry (MS/MS) analyses of some commercially available cysteine-containing peptides. However, these ICAT molecules are designed for use in identification and relative quantification of whole or partially purified cellular and tissue proteomes. Since the biotin moiety can be readily cleaved off the reagent after mass tagging, undesired residual fragmentation patterns caused by biotin of derived peptides, as normally observed using biotin-containing ICAT reagents, are effectively eliminated. This strategy should enhance peptide sequence coverage significantly which, in turn, should result in improving the quality of data obtained during data-dependent peptide mass and tandem mass spectral analysis of whole proteomes.     

HMMatch: peptide identification by spectral matching of tandem mass spectra using hidden Markov models.

Peptide identification by tandem mass spectrometry is the dominant proteomics workflow for protein characterization in complex samples. The peptide fragmentation spectra generated by these workflows exhibit characteristic fragmentation patterns that can be used to identify the peptide. In other fields, where the compounds of interest do not have the convenient linear structure of peptides, fragmentation spectra are identified by comparing new spectra with libraries of identified spectra, an approach called spectral matching. In contrast to sequence-based tandem mass spectrometry search engines used for peptides, spectral matching can make use of the intensities of fragment peaks in library spectra to assess the quality of a match. We evaluate a hidden Markov model approach (HMMatch) to spectral matching, in which many examples of a peptide's fragmentation spectrum are summarized in a generative probabilistic model that captures the consensus and variation of each peak's intensity. We demonstrate that HMMatch has good specificity and superior sensitivity, compared to sequence database search engines such as X!Tandem. HMMatch achieves good results from relatively few training spectra, is fast to train, and can evaluate many spectra per second. A statistical significance model permits HMMatch scores to be compared with each other, and with other peptide identification tools, on a unified scale. HMMatch shows a similar degree of concordance with X!Tandem, Mascot, and NIST's MS Search, as they do with each other, suggesting that each tool can assign peptides to spectra that the others miss. Finally, we show that it is possible to extrapolate HMMatch models beyond a single peptide's training spectra to the spectra of related peptides, expanding the application of spectral matching techniques beyond the set of peptides previously observed.     

The problem with peptide presumption and low Mascot scoring

Mascot, a database-search algorithm, is used to deduce an amino acid sequence from a peptide tandem mass spectrum. The magnitude of the Ions score associated with each peptide mostly reflects the extent of b-y ion matching in a collision-induced dissociation spectrum. Recently, several studies have reported peptides identified with abnormally low Ions scores. While a majority of the spectra in these studies may be correctly assigned, low-scoring spectra could lack discernible b-y ion fragments needed to clearly delineate a peptide sequence. It appears that low-scoring identification may be predicated primarily on judgmental parent ion mass accuracy and that justification to include such low-scoring peptides may be based on inaccurate false discovery rate modeling. It is likely that additional scientific experimentation is needed or appropriate methodologies adopted before substandard fragment ion matching can be considered proof of peptide identification.     

Two-dimensional mass spectra generated from the analysis of 15N-labeled and unlabeled peptides for efficient protein identification and de novo peptide sequencing

Protein identification has been greatly facilitated by database searches against protein sequences derived from product ion spectra of peptides. This approach is primarily based on the use of fragment ion mass information contained in a MS/MS spectrum. Unambiguous protein identification from a spectrum with low sequence coverage or poor spectral quality can be a major challenge. We present a two-dimensional (2D) mass spectrometric method in which the numbers of nitrogen atoms in the molecular ion and the fragment ions are used to provide additional discriminating power for much improved protein identification and de novo peptide sequencing. The nitrogen number is determined by analyzing the mass difference of corresponding peak pairs in overlaid spectra of (15)N-labeled and unlabeled peptides. These peptides are produced by enzymatic or chemical cleavage of proteins from cells grown in (15)N-enriched and normal media, respectively. It is demonstrated that, using 2D information, i.e., m/z and its associated nitrogen number, this method can, not only confirm protein identification results generated by MS/MS database searching, but also identify peptides that are not possible to identify by database searching alone. Examples are presented of analyzing Escherichia coli K12 extracts that yielded relatively poor MS/MS spectra, presumably from the digests of low abundance proteins, which can still give positive protein identification using this method. Additionally, this 2D MS method can facilitate spectral interpretation for de novo peptide sequencing and identification of posttranslational or other chemical modifications. We envision that this method should be particularly useful for proteome expression profiling of organelles or cells that can be grown in (15)N-enriched media.     

Multi-spectra peptide sequencing and its applications to multistage mass spectrometry

Despite a recent surge of interest in database-independent peptide identifications, accurate de novo peptide sequencing remains an elusive goal. While the recently introduced spectral network approach resulted in accurate peptide sequencing in low-complexity samples, its success depends on the chance of presence of spectra from overlapping peptides. On the other hand, while multistage mass spectrometry (collecting multiple MS 3 spectra from each MS 2 spectrum) can be applied to all spectra in a complex sample, there are currently no software tools for de novo peptide sequencing by multistage mass spectrometry. We describe a rigorous probabilistic framework for analyzing spectra of overlapping peptides and show how to apply it for multistage mass spectrometry. Our software results in both accurate de novo peptide sequencing from multistage mass spectra (despite the inferior quality of MS 3 spectra) and improved interpretation of spectral networks. We further study the problem of de novo peptide sequencing with accurate parent mass (but inaccurate fragment masses), the protocol that may soon become the dominant mode of spectral acquisition. Most existing peptide sequencing algorithms (based on the spectrum graph approach) do not track the accurate parent mass and are thus not equipped for solving this problem. We describe a de novo peptide sequencing algorithm aimed at this experimental protocol and show that it improves the sequencing accuracy on both tandem and multistage mass spectrometry.     

Peptide identification using vectors of small fragment ions

Traditionally, peptide identification using fragmentation spectra relies on extracting the maximum amount of information from spectra. Using different combinations of small ion masses, we show that identifying a small number of fragment ions in a spectrum is sufficient for peptide identification. We consider y2-, y3-, b2-, and b3-ions and find the combination of b2-y2 to be sufficient for many peptides. Adding either the y3- or the b3-ion increases specificity and allows reliable peptide identification in the human proteome. Fragmentation spectra and peptides are represented as n-dimensional vectors, where n is given by the number of fragment ions considered, and the peptide mass. The identification score is given by the Euclidian distance between the spectra and the matching peptide in n-dimensional space. We show that this approach, using minimal information, allows for precise and fast peptide identification.     

Improving peptide relative quantification in MALDI‐TOF MS for biomarker assessment

Proteomic profiling by MALDI‐TOF MS presents various advantages (speed of analysis, ease of use, relatively low cost, sensitivity, tolerance against detergents and contaminants, and possibility of automation) and is being currently used in many applications (e.g. peptide/protein identification and quantification, biomarker discovery, and imaging MS). Earlier studies by many groups indicated that moderate reproducibility in relative peptide quantification is a major limitation of MALDI‐TOF MS. In the present work, we examined and demonstrate a clear effect, in cases apparently random, of sample dilution in complex samples (urine) on the relative quantification of peptides by MALDI‐TOF MS. Results indicate that in urine relative abundance of peptides cannot be assessed with confidence based on a single MALDI‐TOF MS spectrum. To account for this issue, we developed and propose a novel method of determining the relative abundance of peptides, taking into account that peptides have individual linear quantification ranges in relation to sample dilution. We developed an algorithm that calculates the range of dilutions at which each peptide responds in a linear manner and normalizes the received peptide intensity values accordingly. This concept was successfully applied to a set of urine samples from patients diagnosed with diabetes presenting normoalbuminuria (controls) and macroalbuminuria (cases).     

基于数据非依赖采集的蛋白质组质谱数据解析方法研究进展

数据非依赖采集（DIA）是蛋白质组学领域近年来快速发展的质谱采集技术，其通过无偏碎裂隔离窗口内的所有母离子采集二级谱图，理论上可实现蛋白质样品的深度覆盖，同时具有高通量、高重现性和高灵敏度的优点。现有的DIA数据采集方法可以分为全窗口碎裂方法、隔离窗口序列碎裂方法和四维DIA数据采集方法（4D-DIA）3大类。针对DIA数据的不同特点，主要数据解析方法包括谱库搜索方法、蛋白质序列库直接搜索方法、伪二级谱图鉴定方法和从头测序方法4大类。解析得到的肽段鉴定结果需要进行可信度评估，包括使用机器学习方法的重排序和对报告结果集合的假发现率估计两个步骤，实现对数据解析结果的质控。本文对DIA数据的采集方法、数据解析方法及软件和鉴定结果可信度评估方法进行了整理和综述，并展望了未来的发展方向。     

Identification of human liver diacetyl reductases by nano-liquid chromatography/Fourier transform ion cyclotron resonance mass spectrometry

Several forms of diacetyl-reducing enzyme were found to exist in the human liver cytosol. Three (DAR-2, DAR-5, and DAR-7) of them were purified as a single band on SDS-PAGE by a combination of a few kinds of column chromatographies. The in-gel tryptic digests of the purified enzymes were analyzed by nano-liquid chromatography (LC)/Fourier transform ion cyclotron resonance mass spectrometry (FT ICR MS), which provided peptide masses at a ppm-level accuracy. The enzymes, DAR-2, DAR-5, and DAR-7, were identified as alcohol dehydrogenase beta subunit (ADH2), carbonyl reductase (CBR1), and aldehyde reductase (AKR1A1), respectively, by peptide mass fingerprinting. In addition, an alternating-scan acquisition of nano-LC/FT ICR mass spectra, i.e., switching of normal acquisition conditions and in-source fragmentation conditions scan by scan, provided sets of parent and fragment ion masses of many of the tryptic peptides in a single LC/MS run. The peptide sequence-tag information at the ppm-level accuracy was used to further confirm the protein identities. It was demonstrated that nano-LC/FT ICR MS can be used for rigorous protein identification at a subpicomole level as an alternative technique to nano-LC/MS/MS.     

ICPLQuant – A software for non‐isobaric isotopic labeling proteomics

The main goal of many proteomics experiments is an accurate and rapid quantification and identification of regulated proteins in complex biological samples. The bottleneck in quantitative proteomics remains the availability of efficient software to evaluate and quantify the tremendous amount of mass spectral data acquired during a proteomics project. A new software suite, ICPLQuant, has been developed to accurately quantify isotope‐coded protein label (ICPL)‐labeled peptides on the MS level during LC‐MALDI and peptide mass fingerprint experiments. The tool is able to generate a list of differentially regulated peptide precursors for subsequent MS/MS experiments, minimizing time‐consuming acquisition and interpretation of MS/MS data. ICPLQuant is based on two independent units. Unit 1 performs ICPL multiplex detection and quantification and proposes peptides to be identified by MS/MS. Unit 2 combines MASCOT MS/MS protein identification with the quantitative data and produces a protein/peptide list with all the relevant information accessible for further data mining. The accuracy of quantification, selection of peptides for MS/MS‐identification and the automated output of a protein list of regulated proteins are demonstrated by the comparative analysis of four different mixtures of three proteins (Ovalbumin, Horseradish Peroxidase and Rabbit Albumin) spiked into the complex protein background of the DGPF Proteome Marker.     

ITMSQ: A software tool for N‐ and C‐terminal fragment ion pairs based isobaric tandem mass spectrometry quantification

Tandem MS (MS2) quantification using the series of N‐ and C‐terminal fragment ion pairs generated from isobaric‐labelled peptides was recently considered an accurate strategy in quantitative proteomics. However, the presence of multiplexed terminal fragment ion in MS2 spectra may reduce the efficiency of peptide identification, resulting in lower identification scores or even incorrect assignments. To address this issue, we developed a quantitative software tool, denoted isobaric tandem MS quantification (ITMSQ), to improve N‐ and C‐terminal fragment ion pairs based isobaric MS2 quantification. A spectrum splitting module was designed to separate the MS2 spectra from different samples, increasing the accuracy of both identification and quantification. ITMSQ offers a convenient interface through which parameters can be changed along with the labelling method, and the result files and all of the intermediate files can be exported. We performed an analysis of in vivo terminal amino acid labelling labelled HeLa samples and found that the numbers of quantified proteins and peptides increased by 13.64 and 27.52% after spectrum splitting, respectively. In conclusion, ITMSQ provides an accurate and reliable quantitative solutionfor N‐ and C‐terminal fragment ion pairs based isobaric MS2 quantitative methods.     

A paired ions scoring algorithm based on Morpheus for simultaneous identification and quantification of proteome samples prepared by isobaric peptide termini labeling strategies

The isobaric peptide termini labeling (IPTL) method is a promising strategy in quantitative proteomics for its high accuracy, while the increased complexity of MS2 spectra originated from the paired b, y ions has adverse effect on the identification and the coverage of quantification. Here, a paired ions scoring algorithm (PISA) based on Morpheus, a database searching algorithm specifically designed for high‐resolution MS2 spectra, was proposed to address this issue. PISA was first tested on two 1:1 mixed IPTL datasets, and increases in peptide to spectrum matchings, distinct peptides and protein groups compared to Morpheus itself and MASCOT were shown. Furthermore, the quantification is simultaneously performed and 100% quantification coverage is achieved by PISA since each of the identified peptide to spectrum matchings has several pairs of fragment ions which could be used for quantification. Then the PISA was applied to the relative quantification of human hepatocellular carcinoma cell lines with high and low metastatic potentials prepared by an IPTL strategy.     

ETISEQ – an algorithm for automated elution time ion sequencing of concurrently fragmented peptides for mass spectrometry-based proteomics

Background  

Concurrent peptide fragmentation (i.e. shotgun CID, parallel CID or MS^E) has emerged as an alternative to data-dependent acquisition in generating peptide fragmentation data in LC-MS/MS proteomics experiments. Concurrent peptide fragmentation data acquisition has been shown to be advantageous over data-dependent acquisition by providing greater detection dynamic range and providing more accurate quantitative information. Nevertheless, concurrent peptide fragmentation data acquisition remains to be widely adopted due to the lack of published algorithms designed specifically to process or interpret such data acquired on any mass spectrometer.     

Effectiveness of CID, HCD, and ETD with FT MS/MS for degradomic-peptidomic analysis: comparison of peptide identification methods

We report on the effectiveness of CID, HCD, and ETD for LC-FT MS/MS analysis of peptides using a tandem linear ion trap-Orbitrap mass spectrometer. A range of software tools and analysis parameters were employed to explore the use of CID, HCD, and ETD to identify peptides (isolated from human blood plasma) without the use of specific "enzyme rules". In the evaluation of an FDR-controlled SEQUEST scoring method, the use of accurate masses for fragments increased the number of identified peptides (by ~50%) compared to the use of conventional low accuracy fragment mass information, and CID provided the largest contribution to the identified peptide data sets compared to HCD and ETD. The FDR-controlled Mascot scoring method provided significantly fewer peptide identifications than SEQUEST (by 1.3-2.3 fold) and CID, HCD, and ETD provided similar contributions to identified peptides. Evaluation of de novo sequencing and the UStags method for more intense fragment ions revealed that HCD afforded more contiguous residues (e.g., ≥ 7 amino acids) than either CID or ETD. Both the FDR-controlled SEQUEST and Mascot scoring methods provided peptide data sets that were affected by the decoy database used and mass tolerances applied (e.g., identical peptides between data sets could be limited to ~70%), while the UStags method provided the most consistent peptide data sets (>90% overlap). The m/z ranges in which CID, HCD, and ETD contributed the largest number of peptide identifications were substantially overlapping. This work suggests that the three peptide ion fragmentation methods are complementary and that maximizing the number of peptide identifications benefits significantly from a careful match with the informatics tools and methods applied. These results also suggest that the decoy strategy may inaccurately estimate identification FDRs.     

Sequential Window Acquisition of all Theoretical Mass Spectra (SWATH) Analysis for Characterization and Quantification of Histone Post-translational Modifications

Histone post-translational modifications (PTMs) have a fundamental function in chromatin biology, as they model chromatin structure and recruit enzymes involved in gene regulation, DNA repair, and chromosome condensation. High throughput characterization of histone PTMs is mostly performed by using nano-liquid chromatography coupled to mass spectrometry. However, limitations in speed and stochastic sampling of data dependent acquisition methods in MS lead to incomplete discrimination of isobaric peptides and loss of low abundant species. In this work, we analyzed histone PTMs with a data-independent acquisition method, namely SWATH™ analysis. This approach allows for MS/MS-based quantification of all analytes without upfront assay development and no issues of biased and incomplete sampling. We purified histone proteins from human embryonic stem cells and mouse trophoblast stem cells before and after differentiation, and prepared them for MS analysis using the propionic anhydride protocol. Results on histone H3 peptides verified that sequential window acquisition of all theoretical mass spectra could accurately quantify peptides (<9% average coefficient of variation, CV) over four orders of magnitude, and we could discriminate isobaric and co-eluting peptides (e.g. H3K18ac and H3K23ac) using MS/MS-based quantification. This method provided high sensitivity and precision, supported by the fact that we could find significant differences for remarkably low abundance PTMs such as H3K9me2S10ph (relative abundance <0.02%). We performed relative quantification for few sample peptides using different fragment ions and observed high consistency (CV <15%) between the fragments. This indicated that different fragment ions can be used independently to achieve the same peptide relative quantification. Taken together, sequential window acquisition of all theoretical mass spectra proved to be an easy-to-use MS acquisition method to perform high quality MS/MS-based quantification of histone-modified peptides.Chromatin is a highly organized and dynamic entity in cell nuclei, mostly composed of DNA and histone proteins. Its structure directly influences gene expression, DNA repair, and cell duplication events such as mitosis and meiosis (1). Histones are assembled in octamers named nucleosomes, wrapped by DNA every ∼200 base pairs. Histones are heavily modified by dynamic post-translational modifications (PTMs)¹, which affect chromatin structure because of their chemical properties and their ability to recruit chromatin modifier enzymes and binding proteins (2). Moreover, histone PTMs can be inherited through cell division and thus are crucial components of epigenetic memory (3). The function of histone PTMs has been extensively studied in the last 15–20 years, and several links have been found between aberrations of histone PTM levels and development of diseases (4, 5). Such discoveries revealed the importance of histone PTMs in fine-tuning cell phenotype. Because of this, technology has been rapidly evolving to investigate histone PTM relative abundance with higher accuracy and throughput.Mass spectrometry (MS)-based strategies have continuously evolved toward higher throughput and flexibility, allowing not only identification and quantification of single histone PTMs, but also their combinatorial patterns and even characterization of the intact proteins (reviewed in (6, 7)). For histone analysis, a widely adopted workflow for nano-liquid chromatography–tandem mass spectrometry (nLC-MS/MS) includes derivatization of lysine residue side chains with propionic anhydride, proteolytic digestion with trypsin, and subsequent derivatization of peptide N termini (8, 9). Such protocol leads to generation of ArgC-like peptides (only cleaved after arginine residues) after digestion. Moreover, propionylation of N termini increases peptide hydrophobicity, thereby improving LC retention of shorter ones, and thus the MS signal. Because of the high mass accuracy, sensitivity, and the possibility to perform label-free quantification MS has become the technique of choice, outperforming antibody-based strategies, to study both known and novel global histone PTMs.Several acquisition methods have been developed for MS analysis to accomplish different needs of identification and quantification (10). The most widely adopted in shotgun or discovery proteomics is the data-dependent acquisition (DDA) mode. Such acquisition method does not require any previous knowledge about the analyte, as it automatically selects precursor ions detectable at the full scan level in a given order (commonly from the most intense) to perform MS/MS fragmentation (11). Label-free quantification is performed at the full MS scan level by integrating the area of the LC peak from an extracted ion chromatogram of the precursor mass corresponding to the given peptide. On the other hand, the selected reaction monitoring (SRM) mode is the most widely used acquisition method in targeted proteomics. Such method performs cyclic precursor ion selection, MS/MS fragmentation, and product ion selection of a list of masses input by the user. Even though the method preparation is intuitively more complex than DDA, SRM is highly popular because of the high selectivity and sensitivity, which leads to more accurate label-free quantification (12). However, both methods have inevitable drawbacks; a DDA approach cannot perform accurate quantification of isobaric and co-eluting peptides, for example, KacQLATKAAR and KQLATKacAAR (histone H3 aa 9–17), as the fragment ions should be monitored through the entire peptide peak elution to define the ratio between the two similar analytes. On the contrary, an SRM experiment prevents future data mining of unpredicted peptides, and thus such method cannot be used for any classical PTM discovery. Therefore, LC-MS/MS analysis of histone peptides is commonly performed by integrating shotgun and targeted acquisition within the same MS method (13). This method requires previous knowledge about retention time and mass of co-eluting isobaric species, and tedious manual peak integration or dedicated software to deconvolute such complex raw data. Although this mixed MS mode is a powerful approach, the targeted sequences in the method reduce the duty cycle and number of DDA MS/MS spectra that can be acquired, making it far from ideal.Data independent acquisition (DIA) modes are a third option that recently gained popularity in proteomics (14, 15). Sequential window acquisition of all theoretical mass spectra (SWATH™)-MS is a data independent workflow that uses a first quadrupole isolation window to step across a mass range, collecting high resolution full scan composite MS/MS at each step and generating an ion map of fragments from all detectable precursor masses (15, 16). From such data set, a virtual SRM, or pseudo-SRM, can be performed by extracting the product ion chromatogram of a given peptide (17) with bioinformatics tools such as Peakview®, Skyline (18), or OpenSWATH™ (19). In order to define which fragment masses should be used to quantify a given peptide, a spectral library of identified peptides can be manually programmed, downloaded (if available), or generated by previous DDA experiments. In terms of quantification power, SWATH™ combines the advantages of both DDA and SRM, as it allows for MS/MS-based label-free quantification, discrimination of isobaric peptides, and subsequent data mining of unpredicted species.Histone proteins are an excellent target sample to test SWATH™, as the peptides are heavily modified by PTMs and often have isobaric proteoforms present. We analyzed with both DDA and SWATH™ two model systems: (1) extracted histones from untreated (pluripotent) and retinoic acid (RA) treated (differentiated) human embryonic stem cells (hESCs, strain H9), and (2) extracted histones from undifferentiated and differentiated mouse trophoblast stem cells (mTSCs). The results from the DDA experiment were used to evaluate the reproducibility of peptide retention time and the variety of species identified. For the SWATH™ analysis we focused on histone H3, as it is the histone with the highest variety of modified peptides (6). Results highlighted that such acquisition method provides sensitive and precise MS/MS-based quantification of both isobaric and nonisobaric peptides. Our data demonstrate that quantification at the MS/MS level is highly reproducible, and identification of the peptide elution profile is assisted by the high mass accuracy and the large number of overlapping elution profiles of the fragment ions. Moreover, we show that by using different fragment ions for MS/MS quantification we achieved similar quantification results. Thus, we used all unique fragment ions for a given species to provide a robust quantification method, where by unique is intended fragment ions that belong to only one of the possible isobaric peptide proteoforms. Taken together, we prove that SWATH™-MS is a reliable and simple-to-use acquisition method to perform epigenetic histone PTM analysis.