- freely available
Int. J. Mol. Sci. 2013, 14(3), 5402-5431; doi:10.3390/ijms14035402
Published: 6 March 2013
Abstract: Chromatin is a highly structured nucleoprotein complex made of histone proteins and DNA that controls nearly all DNA-dependent processes. Chromatin plasticity is regulated by different associated proteins, post-translational modifications on histones (hPTMs) and DNA methylation, which act in a concerted manner to enforce a specific “chromatin landscape”, with a regulatory effect on gene expression. Mass Spectrometry (MS) has emerged as a powerful analytical strategy to detect histone PTMs, revealing interplays between neighbouring PTMs and enabling screens for their readers in a comprehensive and quantitative fashion. Here we provide an overview of the recent achievements of state-of-the-art mass spectrometry-based proteomics for the detailed qualitative and quantitative characterization of histone post-translational modifications, histone variants, and global interactomes at specific chromatin regions. This synopsis emphasizes how the advances in high resolution MS, from “Bottom Up” to “Top Down” analysis, together with the uptake of quantitative proteomics methods by chromatin biologists, have made MS a well-established method in the epigenetics field, enabling the acquisition of original information, highly complementary to that offered by more conventional, antibody-based, assays.
Chromatin is a highly ordered nucleoprotein complex that both mediates the DNA compaction into the eukaryotic nucleus and regulates gene expression. At the structural level, the basic unit of chromatin is the nucleosome, consisting of 147bp DNA wound around an octamer core containing one histone H3–H4 tetramer and two histone H2A-H2B dimers [1,2]. Functionally, chromatin is organized into two distinct regions: euchromatin is less condensed and generally permissive for transcription, whereas heterochromatin is highly condensed and transcriptionally silent. Heterochromatin is classified as being either constitutive or facultative. In constitutive heterochromatin, the DNA remains condensed throughout the cell cycle. In facultative heterochromatin however the DNA can lose its condensed form and become transcriptionally active in response to distinct signals [3–5].
Changes in the chromatin structure that do not involve the nucleotide sequence can translate into heritable adjustments of gene expression and thus be stored as an “epigenetic memory” of the cell [6–10]. Epigenetic inheritance can be explained through a step-wise model proposing that “epigenator, initiator and maintainer” factors operate sequentially and synergistically to enforce and maintain specific functional states of the genome . The “epigenator”, a signal emanating from the external environment, is translated by an “initiator” into a specific chromatin/DNA functional state, which is sustained by a number of different “maintainer” factors. These factors include the methylation of cytosine in CpG islands [12,13], covalent post-translational modifications of histones (hPTMs) and, in light of more recent studies, the activities of non-coding RNAs (ncRNA) [14,15].
Among the epigenetic maintainers listed, histone PTMs are largely recognized as key regulators of chromatin structure and function. hPTMs include acetylation, ubiquitination and sumoylation of Lysines; different methylation degrees of Arginines and Lysines; phosphorylation of Serines, Threonines and Tyrosines; ADP-ribosylation of Arginines, Glutamic and Aspartic acids; deimination (or citrullination) of Arginine; Proline isomerization [16–18], and in addition some less-characterized modifications.
The histone code hypothesis proposes that these modifications act either singly or in combination to control distinct downstream pathways or processes on chromatin, ultimately defining the functional status of the underlying DNA. The “letters” of this code are the modifications themselves, which are placed and removed by enzymes known as “writers” and “erasers”, respectively. hPTMs exert their function on chromatin through two distinct mechanisms. In the first, higher order chromatin structure is altered via changes in inter-nucleosomal or histone-DNA interactions, thus controlling the accessibility of DNA-binding proteins such as transcription factors (cis mechanisms). Alternatively, hPTMs can generate binding platforms for the recruitment of effector proteins containing specialized domains (trans mechanisms): the so-called “readers” of the code. The “readers” translate the information encoded by the modification patterns into specific biological outcomes [19–22]. In addition to hPTM patterns, chromatin is characterized by the local enrichment of a distinct set of histone variants; binding proteins, including various ATP-dependent chromatin remodelling complexes; and differential nucleosome density. Together, these components contribute to the establishment of specific “chromatin landscapes”, defining the functional state of the genome in that territory .
Antibodies specifically selected against hPTMs are traditionally used to study the language of histone modification through various assays. These include: immunofluorescence (IF) analyses of modifications at the single cell level, immunoblotting (WB) to profile PTMs in different samples and/or conditions, and chromatin immunoprecipitation (ChIP) that can be coupled to either PCR, DNA microarray (ChIP-on-chip) or deep sequencing (ChIP-Seq) for targeted or large-scale gene expression analysis. The last two methods allow the genome-wide mapping of modifications, with a resolution of a few nucleosomes [24–26]. Although advantageous for their sensitivity, antibody-based assays are hampered by limitations in their specificity and efficiency when used to reveal the combinatorial aspect of the code. In fact, modifications can occur on adjacent or closely spaced residues within the same histone, making an epitope-masking effect more likely. For instance, acetylation of K14 and phosphorylation of S10 co-occur on the H3 N-terminal region [27,28]. In this way, the modifications may escape detection by antibodies that are not specifically designed to recognize both modifications on the same epitope. To address this issue, a number of strategies have been developed to assess accurately the specificity of antibodies used in epigenetic research. Peach et al. combine immunoprecipitation (IP) of native HPLC-purified H3 with mass spectrometry to detect PTMs co-enriched by a certain antibody on the same polypeptide. Also, Fuchs et al. have developed a peptide-array assay, based on a comprehensive library of modified peptides [29,30].
Mass spectrometry (MS) has emerged as a promising complementary analytical strategy to identify known and novel PTMs on proteins, as well as for the relative quantitation and detection of synergies between them . The recent advent of high-resolution mass spectrometry has increased the relevance of MS-based hPTM analysis by enabling the discrimination of near-isobaric modifications, either singly or in combinations, on very long polypeptides and even on intact histones [32–40]. Finally, the use of different labeling strategies, both chemical and metabolic, has enabled the accurate quantitation of modifications, both in a relative and absolute manner .
The “epigenomics” and “chromatomics” disciplines share a common goal in studying chromatin structure, composition and features: to gain a comprehensive view, from genome to proteome, of the epigenetic phenomena underlying the establishment and inheritance of specific expression patterns [42,43]. In this review we provide an overview of the contributions made by MS-based proteomics towards achieving this ambitious aim.
2. Fundamentals of Mass Spectrometry Technology
Before considering the different MS strategies applied to in-depth investigations of histones and non-histonic chromatin proteins, we offer here a concise synopsis of the basic principles of mass spectrometry, referring to specialized reviews for more detailed descriptions [44,45].
Essentially, all mass spectrometers measure the mass-to-charge ratio (m/z) of freely moving gas-phase ions in electric and/or magnetic fields. One of the most important developments in instrumentation has been the introduction of “soft-ionization” technology, which permits proteins and peptides to be analyzed by MS. Proteins and peptides are polar, nonvolatile species that require an ionization method to transfer them into the gas phase, without extensive degradation. Two techniques paved the way for the modern bench-top MS proteomics: matrix-assisted laser desorption ionization (MALDI) [46,47] and electrospray ionization (ESI) . In a MALDI source, peptides are co-crystallized with a solid-phase matrix onto a metal plate. The matrix typically consists of a small organic molecule such as α-cyano-4-hydroxycinnamic acid or dihydrobenzoic acid (DHB). When laser pulses irradiate the resulting solid mixture, this absorbs the laser energy and transfers it to the acidified peptides. At the same time, the rapid heating causes desorption of both matrix and newly formed [M+H]+ protonated peptides into the gas phase. Currently, MALDI ionization can support different types of mass analyzers, but the most common combination for proteomics studies is the MALDI/time-of-flight (TOF) setup . In recent mass analyzers, ions generated in the source are accelerated to a fixed amount of kinetic energy and travel down a flight tube. The small ions have a higher velocity and are recorded by a detector before the larger ones. The m/z value displayed in a TOF spectrum is proportional to the time, for a given analyte, required to reach the detector. Unlike MALDI, the ESI source produces ions from the solution. Briefly, the ESI process consists of the formation of an electrically charged spray, driven by high voltage (2–6 kV), which triggers desolvation of peptide/protein-solvent droplets. This process is aided by high temperature and, in some cases, by sheath gas flow at the mass spectrometer inlet. There are different theoretical models to describe ESI ion formation, however the important features are: formation of multiply charged species, sensitivity to analyte concentration and flow rate.
Liquid chromatography (LC) instruments are usually coupled “on-line” with the ESI source to achieve continuous or high throughput analysis. For instance, reverse phase high-pressure liquid chromatography (RP-HPLC) has been widely adopted in proteomics to resolve very complex peptide mixtures prior to MS analysis (LC-MS), due to its high resolution, efficiency, reproducibility, and mobile phase compatibility with ESI. A further development of this technology is nano-ESI [50,51]. In this case, the flow rates are lowered to a nanoliter-per-minute regime to improve the sensitivity of the method. Nano-ESI is compatible with capillary RP-HPLC columns , allowing users to perform analyses with high sensitivity .
Two levels of information are provided by LC-MS analysis of peptides and proteins. First, molecular weight and the elemental composition of the analyte can be extracted when the analyzer achieves sufficient mass resolution. In the second, information about the primary sequence can be obtained if the peptide of interest (precursor ion) is subjected to tandem mass spectrometry (MS/MS) analysis. MS/MS is therefore a key technique for protein or peptide sequencing and PTM analysis. Collision-induced dissociation (CID)  has been the most widely used MS/MS technique in proteomics research. In this method, gas-phase peptide/protein cations are internally heated by multiple collisions with rare gas atoms. This leads to breakage of the C-N bond in the peptide backbone, resulting mainly in b- and y- fragment ions. However, CID fragmentation results in limited sequence information for large peptides (>15 amino acids) and intact proteins.
This limitation has been addressed by the development of novel methods for ion-electron reactions to carry out peptide fragmentation: electron capture dissociation (ECD) and electron transfer dissociation (ETD) enable sequencing of larger peptides, providing an option to investigate combinatorial features of hPTMs [55–58]. Both ECD and ETD are based on the transfer of electrons to the multi-protonated longer peptides (>2 kDa). In ECD, the electrons are generated from a heated filament composed of a rhenium-based alloy, whereas in ETD they are transferred by gas-phase radical ions. Despite the similarity between the two techniques, ECD can be used only in combination with fourier transform ion cyclotron resonance (FT-ICR) instruments, whereas ETD can be implemented in low-cost, high-capacity ion traps or new generation Orbitrap mass spectrometers and it has thus a wider applicability.
2.1. From “Bottom Up” to “Top Down”, via “Middle Down” MS Approaches in hPTM Research
The “Bottom Up” approach is highly popular in proteomics studies for investigations of protein PTMs . It is a “peptide-centric” strategy, based on the enzymatic digestion of proteins into peptides prior to MS analysis. The “Bottom Up” approach has been demonstrated successful in identifying known and novel modifications on histones, combining its sensitivity in detecting peptide m/z in full MS with its efficient MS/MS fragmentation via CID . The most common protease used in “Bottom Up” proteomics studies is trypsin, which cleaves at the C-terminal end of Arginine and Lysine residues . However, trypsin digestion is not ideal for the analysis of histones that are highly rich in these basic residues (especially at the N-terminal regions, where the modifications accumulate), because the peptides produced are too short to be efficiently retained and separated in RP-HPLC and thereafter be detected by the mass spectrometer . The endopeptidase Arg-C is a good alternative because of its specificity for the C-terminal region of Arginines, producing longer and easy-to-ionize peptides, also suitable for LC-MS [60,61]. In addition, peptides produced in this digestion retain a positive charge at C-terminal Arginine residues, leading to a well-defined y-ion series [62–64]. Alternatively, histones can be chemically derivatized using either propionic anhydride [(C3H5O)2O] or deuterated acetic anhydride (D6-acetic anhydride [(CD3CO)2O]), prior to trypsin digestion. These compounds trigger Lysine alkylation that prevents tryptic cleavages, resulting in Arg-C-like digestions. The advantage of this approach is that it leads to the described benefits of an Arg-C-like digestion while using trypsin as the protease, well-suited to in gel digestion . The in gel approach, commonly performed by SDS-PAGE, facilitates separation at the level of individual histone molecules .
Moreover, this derivatization labels unmodified and mono-methylated Lysines with a deuterated acetyl moiety (showing a delta mass of 45.0294 Da) but does not react with di-methyl, tri-methyl and acetyl Lysines, enabling the distinction between isobaric modification-bearing peptides. For example, peptide H3 (27–40) contains three Lysines, which can be differentially modified. In a case where two of these Lysines are mono-methylated, it is challenging to distinguish this species from an isobaric peptide containing a single di-methylation modification (Figure 1A). The derivatization approach however removes this isobaric feature (Figure 1B), since the addition of the deuterated acetyl moiety to unmodified and mono-methylated Lysines leads to a mass difference between the two-peptide isoforms. Furthermore, the peptides modified by distinct combinations of native and chemical modifications, display slightly different elution times, which contributes to the unambiguous assignment of modifications to specific residues.
A limitation of the “Bottom Up” approach emerges when analyzing histone variants or combinations of histone modifications. In fact, the short tryptic and Arg-C-like peptides do not permit detection of simultaneously occurring, long-distance PTMs. Offline chromatography, to separate histone variants or differently modified versions of the same histone molecule prior to “Bottom Up” analysis, is one solution to this problem. For instance, the three mammalian variants of histone H3 (H3.1, H3.2 and H3.3) share the majority of peptides produced upon enzymatic digestion; however the intact proteins can be separated prior to digestion and LC-MS using tap-tag purifications and/or RP-HPLC [67,68]. Alternatively, intact proteins or larger histone domains can be directly analyzed by mass spectrometry with the so-called “Top Down” and “Middle Down” strategies [69,70]. Histones are basic proteins and, in the acidic conditions used in MS, they are typically highly charged and thus capable of producing multiply charged fragment ions in MS/MS. Consequently, non-ergodic fragmentation methods  such as ETD and ECD on high-resolution instruments (Orbitrap, FT-ICR) are feasible for “Top Down” analysis [57,58]. “Top Down” enables the user to distinguish between co-occurring histone variants and differently modified isoforms, with information about the relative abundances and modification stoichiometries, thus providing a so-called “bird’s eye view” on the complete panel of histone isoforms present in a specific functional state . The approach however lacks the sensitivity of “Bottom Up” and, furthermore, the analysis of the spectra obtained is less straightforward. These two restraints have limited the uptake of this approach so far, even though recent advances in online separation of intact proteins by ultra high-pressure (UPLC) liquid chromatography have made the approach more feasible. Further improvements in implementations are therefore still required to make “Top Down” analysis of intact histones, with variants and modified forms, a more routine approach [73,74].
The “Middle Down” approach is an optimal compromise between “Top Down” and “Bottom Up” strategies, when the mass spectrometer is hyphenated to online liquid chromatography. In “Middle Down” approach, large histone peptides (>2 kDa) are analyzed upon the enzymatic digestion of histones with endoproteinases that have specificities to less frequently-occurring amino acids within histone sequences, such as Glu-C or Asp-N. In fact, since mammalian H3 contains the first Glutamic acid at position 50, Glu-C at pH 8 produces an N-terminal peptide (1–50) of 6 kDa that contains the majority of PTMs decorating this histone, as well as being suitable for MS analysis and sequencing by either ETD or ECD MS/MS fragmentation. Similarly, Asp-N is useful for “Middle Down” analysis of histone H4, because it cleaves at the N-terminal side of Aspartic acid at position 24. Again, the resulting peptide (1–24) includes all modifications annotated at the H4 tail . The “Middle Down” approach therefore allows a more precise detection of PTM combinations on particular histone regions, especially when combined with pre-fractionation of the enzymatic digestion products. For instance, a combination of weak-cation exchange with hydrophilic interaction liquid chromatography (WCX-HILIC) prior to high-resolution MS, efficiently resolve co-occurring and/or (near-) isobaric modified histone species , separating longer peptides first by their charge state and then by hydrophilicity. Based on this, Young et al. proposed a high-throughput approach using a gradient of decreasing organic solvent and decreasing pH on a commercial WCX-HILIC resin to separate and analyze by a “Middle Down” approach differentially modified histone domains  (See also Section 3).
An inconvenience of the “Top Down” and “Middle Down” approaches is the need for specialized software to summarize the complex combinatorial networks existing among hPTMs. The main problems concern the complexity of the MS/MS spectra generated, either from intact histones or from large peptides, and the increased incidence of internal peptide sequence fragments that further complicate the sequence annotation and consequently the PTM site-specific attribution in the MS/MS spectra [77–79] (Figure 2). Improvements in computational approaches should enable more detailed comprehension and visualization of the inter-reliant relationships between unique modified forms.
2.2. Bioinformatics Tools for hPTM Analysis
A number of bioinformatics tools have emerged to interpret the large amount of data generated by modern mass spectrometers. Of particular relevance to the analysis of the modifications that occur on histones are tools that enable identification of several different PTMs, often co-existing on the same peptide. Identification of PTM-bearing peptides in sequence databases, however, is more challenging than that of unmodified forms because the database search engine needs to take into account the diversity of modified forms that might exist. There are at present a number of computational methods available for the automated annotation of PTMs in peptides (Table 1). These methods analyze the MS and MS/MS data, taking into account the delta-mass values, and also neutral losses and other diagnostic ions for the PTM of interest .
The computational methods used to identify PTMs fall into two categories . In the first, the user selects a set of PTMs of interest prior to employ the bioinformatics tool for peptide and protein identification. This option is applied during the sequence database search, when PTMs are assigned to the relevant amino acids of a candidate peptide sequence. To limit the complexity required to search a very large set of possible modified forms, a restriction is usually imposed on the number of modifications that may be included in this search.
In the second approach, which is unbiased, PTMs are identified through a “blind” database search. In the initial step, a basic database search is performed, excluding the specification of PTMs of interest, but often specifying recurring/standard modifications such as oxidized Methionine, for example. The specification of this relatively common modification avoids false-positive PTM assignments later on. Once a set of peptides is identified in an MS/MS-based proteomics experiment the idea is that, since the PTM leads to a mass increment or deficit of the modified peptide relative to the form without the modification present, all unassigned MS/MS spectra can be searched to find those which might match a post-translationally modified form. The software therefore inspects unassigned spectra, using information based on a list of known modifications such as delta-mass values and lists of predicted and observed peptide masses.
Computational methods that search for post-translational modifications are however associated with higher rates of false-positive identifications. The combinatorial issues linked with assigning the masses of included modifications can dramatically increase the number of peptide and protein candidates in the output. In this regard though, technological improvements that enable higher mass accuracy when generating the MS and/or MS/MS spectra have helped to address this issue . High-resolution mass analyzers can resolve and identify peptides bearing modifications with very similar delta-mass values as well as multiply charged ions in MS/MS spectra. Recent data analysis software therefore considers product ions with multiple charges either before or during database searching.
Nevertheless some issues are still beyond the reach of current algorithms. The first is that some modifications may arise from in vitro artefacts rather than in vivo enzymatic activity. A well known example is the di-glycine (GG) tag which occurs on Lysine, and is used to determine ubiquitination sites: the elemental composition of this tag is identical to that of iodoacetamide (IAA), commonly used for the alkylation of Cysteines in standard shotgun MS proteomics workflows . Another issue is that most of the available methods are sub-optimal for the analysis of MS/MS spectra deriving from long peptide sequences and intact proteins, which may result from “Top Down” or “Middle Down” approaches. As described in the recent review by Sidoli et al., the complexity of these spectra requires more specialised search algorithms, which can efficiently determine monoisoptic peaks, recognize ion charge states and deconvolute multiply-charged ion signals into singly-charged ion mass values. Currently, only a few software packages are available for this purpose .
2.3. Quantitative MS-Based Approaches in Epigenetic Research
Various strategies have been developed in MS-based proteomics for accurate protein quantitation, from single proteins up to global proteome profiling. They can be grouped into four categories: chemical labeling, metabolic labeling, quantitation by the use of standard peptides and label-free. While the first three all rely on the use of differently isotope-encoded tags, the fourth implies the direct comparison among unlabeled proteomes. We refer to specialized reviews for an extensive description of these strategies for global protein analysis [96,97], while focusing on their application to the measurement of histone modification, variants and turnover.
Chemical derivatization as a means to modify cleavable residues has been widely applied in epigenetic studies for their technical advantages, previously described [62,63]. In addition, the alkylation of Lysines with the deuterated acetic anhydride can also be used to quantitatively estimate the acetylation status of histones. For instance, distinct acetylated forms of H4 in Drosophila melanogaster and their developmental changes have been profiled using D6-acetic anhydride prior digestion and MS-analysis . Reinberg and co-workers, using propionylation of histones, demonstrated that a significant portion of nuclesomes are asymetrically modified in embryonic stem cells, mouse embryonic fibroblasts (MEFs) and HeLa cells with respect to two prominent histone modifications: H3K27 di-/tri-methylation and H4K20 mono-methylation . Similarly, this strategy was used to observe the effect of G9a/Glp1 methyltransferase knockdown on global histone methylation .
In vivo metabolic labeling with isotope-encoded amino acids has emerged as the most powerful approach to accurately quantify changes of histones and their PTMs. In stable isotope labeling by amino acids in cell culture (SILAC), a growth medium is prepared where natural (“light”) amino acids are replaced by “heavy” SILAC amino acids. Cells grown in this medium incorporate the heavy amino acids. When light and heavy cell populations are mixed, they remain distinguishable by MS, and protein abundances are determined from the relative MS signal intensities . The possibility offered by this strategy to combine two cell populations from distinct media at a very early stage of the MS-proteomics workflow, significantly reduces the effects of experimental variation in sample preparation, thus leading to very accurate quantitation, which only takes into account changes caused by the different functional states. In the last years, SILAC has gained wide popularity in proteomics and, more recently, also in chromatin studies [36,103–105]. SILAC is preferentially used to profile protein levels; however it has also been successfully applied to identify and quantify hPTMs, and in particular to profile modification dynamics during the cell cycle: Bonenfant et al showed increasing phosphorylation on histone H3 and H4 and decreasing methylation of H3K27/K36 during mitosis ; Pesavento et al. proved that H4K20 methylation degree was tightly linked to cell cycle progression while Scharf et al. demonstrated that H4K20 mono-methylation promotes chromatin assembly, facilitating the subsequent deacetylation of H4 [107,108]. Using a SILAC MS-based experiment, Jung et al. showed that Polycomb repressive complex Suz-12 promotes the establishment of H3K27 di/tri-methylation in mouse embryonic stem cells, with a functional interplay between H3K27 tri-methylation and H3K27 acetylation, functioning as molecular switch in this system . A drawback of the SILAC approach is that it is limited to comparison of no more than three functional states in a single experiment . Recently, however, our group circumvented this limit adapting the SILAC approach to a “spike-in” strategy to determine breast cancer-specific histone PTM signatures. In this study, we focused on human breast cancer and comprehensively analyzed PTMs on histones H3 and H4 from a panel of heavy-labeled cancer cell lines (MCF7, MDA-MB231, MDA-MB453 and T-47D). Their modification patterns were compared to unlabeled normal epithelial breast cells (MCF10), used as a “spike-in” reference. The “spike-in” SILAC approach enabled quantitative tracking of the modification changes in cancer cells, as compared to their normal counterpart. With the accuracy of this strategy, it was possible to identify PTMs specifically associated to distinct type of breast cancer cell line with different properties (aggressiveness/prognosis). Among them some were already known as modifications linked to cancer, such as a decrease of H4K20 tri-methylation, whereas some emerged as novel markers of breast cancer, such as reduced levels of H3K9 tri-methylation .
A further limitation of SILAC is that it cannot be directly applied to clinical samples, as it relies on metabolic labeling of actively dividing cells. However, an interesting recent trend is the use of SILAC as an internal standard in the so-called “super-SILAC” approach , providing a solution to this restraint. In the super-SILAC approach, a combined heavy-labeled proteome mixture is derived from different cell lines cultured in heavy-isotope media. This “standard” mixture can then be spiked into clinical samples , generating a universal reference for quantitation, similar to that used in microarray analysis. It is possible to envisage the applicability of this strategy to quantify hPTM patterns from clinical samples by generating a super–SILAC mixture prior to biochemical methods to purify chromatin regions and/or bulk histones, thus generating a comprehensive set of heavy-labeled histone peptides, containing virtually all known hPTMs, as a universal reference.
The SILAC method has also been adapted for a range of other applications. In pulse experiments SILAC was used to measure the turnover of both hPTMs and histone variants: Zee et al. showed that H2A.Z has higher turnover rates than canonical H2A variants and, more generally, that acetylated histone peptides appear to turn-over much faster than methylated ones . A variation of SILAC, known as heavy methyl SILAC (hmSILAC), is used for high confidence identification of methylation at Lysines and Arginines. In heavy methyl SILAC labeling, 13CD3-Methionine is added to Methionine-depleted media; upon uptake in the cell, the “heavy” Methionine is converted into S-adenosyl Methionine (SAM), the sole donor of methyl groups in enzymatic methylation reaction. As such, histone and all non-histonic proteins that contain methylations are enzymatically heavy-methyl labeled. Such isotopically methylated peptides are then identified with high confidence in MS, based on the presence of the specific ‘light and heavy peak pair’ as marker of methylation, and subsequently quantified.
Ong et al. first used this strategy to identify unambiguously methylated sites in vivo on both histones and non-histonic proteins . Afterwards, hmSILAC was applied to study the dynamic turnover of H3K9 tri-methylation in pericentric chromatin . More recently, the same approach was applied to profile more globally the turnover of histone Lysine methylation, revealing that mono-, di-, and tri-methylated residues generally have progressively slower rates of formation. Furthermore, methylations associated with active genes were found to have faster rates than methylations associated with silent genes .
A combination of both standard- and heavy methyl- SILAC in pulse-chase experiments, carried out on synchronized cells, enabled Sweet et al. to track the progression of H3K79 methylations throughout the cell cycle . In addition, it was observed that H3K79 mono-methylations from newly-synthesized H3 molecules have the same turnover rates as those in pre-existing histones, with no differences among the three H3 variants .
Label-free or ion intensity-based quantitation strategies have been applied in a few studies to profile differently modified, but isobaric histone isoforms, which have a special feature to present identical molecular weight/mass (isobars) but different PTMs configurations, so they are undistinguishable in full MS and can be hardly separated by standard LC. Since in MS/MS such isobaric species are distinguishable based on the positional selectivity of ion fragmentation, a relative quantitation is possible in a label-free MS/MS-based manner, using the relative ratios of their fragment ions. “Top Down” intact histone analysis was successfully used to quantify different modified forms of H3.2 and H4, in a label-free approach [119,120] (See also Section 3).
Lastly, synthetic, isotopically labeled peptides can be used as internal standards for both relative and absolute quantitation of histones and their PTMs in “spike in” assays. Briefly, isotope-encoded peptides are synthesized with the same sequence of the modified histone peptide of interest, derived from the endoproteinase digestion used in the study. Relative quantitation is obtained when a known concentration of the standard peptide is “spiked into” each histone sample from the panel under investigation, and the intensity of the each native modified peptide is compared with that of the standard. With the same approach the absolute quantitation of modified peptides can be also achieved, when a calibration curve of the ion intensity versus the peptide standard, injected at distinct concentrations, is calculated. Typically, this approach is combined with single or multiple reaction monitoring MS (SRM/MRM), enabling very sensitive detection of even sub-stoichiometric modifications. This technique benefits from the triple quadropole (QQQ) instrumentation. Briefly, targeted peptides are selected in the first mass analyzer (Q1), fragmented by CID (in Q2) and one or several of the fragment ions uniquely derived from the targeted peptide are measured by the third analyzer (Q3). In this way, each peptide is characterized by a specific “transition” which links both the precursor and fragment ions, observed in both analyzers. The identity of each peptide can be inferred from the “transition” and the relative abundance can be estimated from the transition intensity relative to that of the standard . Darwanto and coworkers successfully employed SRM upon spike in of isotopically encoded histone peptides in U937 lymphoma cells expressing a mutated form of the hDot1a methyltransferase. They profiled changes in a set of hPTMs and observed that in these conditions the decrease of H3K79 methylation parallels a corresponding increase in H2B K120 ubiquitination .
3. Mass Spectrometry Analysis of Histone Variants and Their Modifications
In addition to post-translational modifications, histone variants contribute to the epigenetic regulation of gene expression . Histone variants typically accumulate at specific genomic regions and show unique modification patterns, affecting a variety of chromatin-related processes. Some interpretative models propose that they represent an “extra layer” of the histone code , providing additional mechanisms to modulate chromatin structure. However, at least for the majority of variants, the processes by which specific variants accumulate at certain regions and are transmitted throughout the cell cycle remain unclear. Except for H4, all core histones and linker histones H1 have a number of variant counterparts, often differing in a few amino acids, which hampers their analysis via conventional approaches, such as antibody-based assays.
Mammalian histone H3 has three major variants (H3.1, H3.2 and H3.3), in addition to a testis-specific variant (H3t) and a centromeric variant (CENP-A). The major variants are very similar in sequence composition. Histone H3.1 differs from H3.2 by a change in Cysteine 96 to Serine, while H3.3 differs from H3.1 by only 5 residues. However, they display differences in their expression, enrichment at specific chromatin domains, and in their post-translational modification signatures. Studies of the PTM patterns of H3 variants have been performed, profiting from all MS approaches described: “Bottom Up”, “Top Down” and “Middle Down”. “Bottom Up” analysis of mammalian, Arabidopsis thaliana, and Drosophila melanogaster H3 variants revealed that H3.3 is enriched in modifications associated with transcriptional activity [125–127]. “Top Down” analysis of H3 variants from rat brains showed comparable results using this complementary approach . Affinity purification of epitope-tagged H3.1 and H3.3 revealed a distinct set of modifications occurring on these two H3 variants before and after their assembly on chromatin, suggesting that pre-assembly modifications determine their final fate, as well as their PTM patterns on chromatin . A combinatorial view of modifications on H3.1 and H3.3 from asynchronous or colchicine-treated HeLa was achieved by “Top Down”: with this approach it was observed that only 5% of K4 was mono-methylated and about 50% of K9 was di-methylated in the H3.1 pool from asynchronous cells. In addition, more than 90% of the H3.1 pool was acetylated: K14 and K23 represent the major sites of acetylation. Upon colchicine treatment, however, the unmodified, mono- and di- phosphorylated S10 and S28 were detected in a 2:3:1 ratio, in addition to the K9 methylation and acetylations described. The absence of the K4 methylation in the colchicine-treated samples was probably due to the relatively small pool of molecules containing this modification . “Middle Down” analysis of H3 variants in a panel of rat tissues showed distinct patterns of H3.2 and H3.3 levels and modification status between various tissues . “Middle Down” was also successfully applied to the identification of more than 200 modifications in H3.2 and 70 modifications in H4 from human samples, including several not previously described [76,120].
Canonical human histone H2A is encoded by sixteen genes in a genomic cluster. Kelleher and co-workers identified and characterized twelve unique sequences by using intact mass and fragmentation spectra . The modifications on the canonical H2A are incompletely characterized: only phosphorylation of S1 and acetylation on the N-terminal K5 are reproducibly reported , as well as mono-ubiquitination at K119, involved in gene silencing and mediated by Polycomb proteins . The non-canonical H2A variants include H2A.X, H2A.Bbd, H2A.Z and macro-H2A. H2A.X phosphorylated at S139 is the so-called gamma-H2A.X, which localizes to sites of DNA double strand breaks (DSB) in response to DNA damage and thus represents a mark of the DNA damage response (DDR). Acetylation and ubiquitination of H2A.X were also shown to be involved in this process: acetylation of K5 is a prerequisite for the poly-ubiquitination and the subsequent release of H2A.X from the DNA damage sites . H2A.Z is present at promoters where it is believed to maintain active chromatin in regions adjacent to silent ones. However, potential roles in gene silencing have also been proposed . Acetylation of K4 and K7 of this variant were identified by a “Middle Down” approach in Jurkat cells . Macro-H2A, the largest H2A variant, is generally enriched at transcriptionally silent regions. MS characterization of macro-H2A identified K115 ubiquitination and S137 phosphorylation. The former is implicated in X-inactivation whereas the latter is enriched in mitosis [134,135]. In addition, K17 mono-methylation, K122 di-methylation and Y128 phosphorylation are identified .
A combination of CID and ECD MS fragmentation at protein and peptide levels led to the characterization of several H2B variants and associated PTMs [130,136]: acetylation on K5, K12, K15 and K20, and ubiquitination on K120. These PTMs were confirmed by peptide mass fingerprinting (PMF) MS analysis on bovine H2B, which revealed also K43 mono-methylation and K85 acetylation . “Bottom Up” approaches have also served to characterize modifications specific for the testis-specific variants of H2B (TH2B) . In addition, “Top Down” analysis using ECD fragmentation of the two major H2B variants of Tetrahymena thermophila led to the characterization of their primary sequences and modification patterns . Recently, mono-methylation and di-methylation at the N-terminal Proline of Drosophila melanogaster H2B have been identified using a combination of different strategies for sample preparation prior to MS analysis including D6-acetic anhydride derivatization followed by Trypsin digestion and Asp-N digestion. The abundance of this Proline methylation seems to depend on the developmental stage and is regulated by the enzyme dART8. The authors also observed predominant acetylation of H2B at K11 and K17 .
Histone H1 is commonly referred to as the linker histone. A single copy of this histone is proposed to bind near the entry/exit site of DNA on the nucleosome (the so called dyad), stabilizing the 30 nm fiber and thus regulating higher order chromatin structure and stability. Sequence divergence between histone H1 isoforms occurs mainly in the N- and C-terminal regions of the proteins, generating as many as eleven mammalian isoforms.
Mass spectrometry contributes to the identification of a number of PTMs specifically enriched on distinct linker histones, such as methylation, phosphorylation, acetylation, ubiquitination, formylation and ADP ribosylation [141–145]. RP-HPLC of the different H1 variants, followed by chemical derivatization of the protein with propionic anhydride and subsequent LC-MS/MS analysis revealed a K26 methylation and S27 phosphorylation on histone H1.4. Methylation on K26 appears to recruit heterochromatin protein 1 (HP1), whereas phosphorylation at S27 seems to inhibit HP1 binding, so that these two adjacent PTMs are believed to function as a molecular switch to modulate gene silencing [143,146]. Moreover, “Top Down” analysis of intact H1.2 and H1.4 purified at distinct cell cycle stages provided indications that S173 on H1.2 and S187 on H1.4 are phosphorylated only during interphase. Interphase phosphorylated H1.2 and H1.4 associate to active rDNA genes to facilitate their RNA Pol I-mediated transcription. Finally, phosphorylation of H1 reduces its association to chromatin and, consequently, the accessibility to factors that regulate transcription and replication .
4. Interaction Proteomics to Study Chromatin Architecture
A better knowledge of chromatin composition can contribute to a more comprehensive view of its higher-order structure and function. Until now, no purification method has emerged as a “gold standard” for chromatin purification and characterization, due to the difficulty in enriching chromatin samples from specific functional regions at a purity and quantity sufficient for subsequent analysis. In spite of these limitations and thanks to recent achievements in MS-based proteomics in terms of sensitivity and accuracy of quantitative information, a number of studies have demonstrated the high potential of this technology to characterize the chromatin proteome, with a focus on the histone code readers associated with specific functional regions (Figure 3).
An analysis of changes in protein levels in response to the overexpression of the oncoprotein MYC was the first attempt to characterize chromatin-binding proteins. This was achieved using differential detergent/salt extraction and chemical isotopic labeling by ICAT, in combination with multi-dimensional chromatography and mass spectrometry . Subsequently, when ad hoc biochemical protocols were established for the purification of distinct chromosomes, MS proved to be successful in characterizing their protein composition: mitotic chromosomes were purified at different stages of the cell cycle (mitosis, metaphase and interphase) and the associating non-histone proteins were identified by MS [149–154]. More recently, a multiclassifier combinatorial proteomics (MCCP) approach was developed, where SILAC quantitative proteomics is integrated with a bioinformatics analysis pipeline. A statistical approach is applied to confirm which known and uncharacterized proteins are chromosomal, to obtain a more comprehensive and unambiguous collection of proteins associated with mitotic chromosomes .
One elegant methodology to study the proteomic composition of telomeric regions was developed by the Kingston group using the PICh (Proteomics of Isolated Chromatin) approach. In this method, enrichment of cross-linked telomeric chromatin was achieved using DNA probes complementary to the telomeres, rich in repetitive sequences. The co-enriched proteins were characterized by MS and new telomere-associated proteins were observed . Yet, a drawback of PICh is the limited applicability to regions rich in repetitive DNA sequences.
All these methods provide a useful contribution to the knowledge of protein composition in large chromosomal regions or even intact chromosomes, but they are inadequate for gaining information on chromatin locus-specific composition.
Recently, a number of interactomics assays combining affinity-interaction mapping with SILAC-quantitative MS read-out have been developed for the comprehensive characterization of hPTM “readers”. Vermeulen et al. used pull-down assays with peptides that differ by a single post-translational modification to identify specific binders, either as individual interactors or as multiprotein complexes. With this approach, they discovered that TFIID binds H3K4 tri-methylation and recruits the entire transcription initiation complex, thereby providing a functional link between this modification and activation of transcription . The approach was extended further to screen all major tri-methylation marks on histones and, in combination with ChIP-Seq and BAC-GFP pull-downs, to define the comprehensive Lysine trimethyl-interactome . As an additional elaboration of the strategy, a SNAP (SILAC Nucleosome Affinity Purification) approach was established where recombinant nucleosomes bearing combinations of hPTMs and methylated DNA were used as baits to provide a “modification binding profile” for proteins regulated by the contribution of both DNA and histone methylations . Similarly, a SILAC-based affinity purification assay was carried out with recombinant, uniformly modified chromatin templates . In addition, the CLASPI (Cross-Linking Assisted and SILAC-based Protein Identification) approach has been described, which combines SILAC with chemical proteomics using photo-crosslinking-based histone peptide probes, to detect weak but specific interactions that may escape standard pull-down approaches . Finally, peptide arrays and MS have been employed to systematically uncover methyl-Lysine and chromatin-binding module interactors, as well as to identify novel H3K23 mono-methylation mark that mediates the recruitment of HP1 eta to heterochromatin . Tandem affinity purification (TAP) was also used to purify and identify chromatin-associated complex: such strategy has been successful employed recently to characterize PRC1 (Polycomb Repressive Complex 1) complexes .
These in vitro studies are very powerful tools for screening the soluble binders of hPTMs, but fall short in extracting information on the relative PTM stoichiometry, their combinations, and their synergies with histone variants and chromatin modifiers, under physiological conditions. Hence, the locus-specific determination of hPTM patterns and their interactions with protein complexes remains a very attractive, partially unachieved goal.
A SILAC-based quantitative proteomics approach was employed to generate a differential profile of proteins associated with both euchromatin and heterochromatin, exploiting the different accessibility of these regions to MNase, as a consequence of the differential nucleosome packaging. Upon limited MNase treatment, the two fractions of chromatin were separated by centrifugation, based on the differential density of the nucleosomal stretches; SILAC was used to discriminate the proteins associated with these two functional chromatin regions . Another approach developed for detection and characterization of proteins associated with specific chromatin domains is mChIP , where chromatin is isolated, sheared by sonication and then MS analysed. mChIP was successfully applied to study the interactomes of H2A (Hta2p) and its variant Htz1p in Saccharomyces cerevisiae. However, this study did not provide quantitative information on binding proteins, and thus had limited ability to discriminate specific binders from nonspecific chromatin-associated proteins. Recently, an approach to characterize the proteins and hPTMs associated with a specific genomic locus was described, combining Chromatin Affinity Purification and Mass Spectrometry (ChAP-MS). A single genomic LexA DNA binding site was utilized to purify and characterize the GAL1 locus, under transcriptionally active and repressive conditions . Building on these approaches, our group has recently developed a global, quantitative proteomic strategy, named ChroP (Chromatin Proteomics), to characterize functionally distinct chromatin regions . Native and Cross-linked chromatin immunoprecipitation, combined with SILAC-based quantitative proteomics, permit global investigations of synergies between histone PTMs, variants, and chromatin modifiers associated with silent and active chromatin regions, marked by H3K9 tri-methylation and H3K4 tri-methylation. We identified previously characterized protein associations and also revealed numerous novel interactions suggesting original pathways on chromatin. Among them, the histone variant H2A.X and the chromatin remodeling complex WICH were both found enriched in heterochromatin, suggesting that their specific recruitment by H3K9me3 may represent an additional level of modulation of the DNA damage response (DDR) in this chromatin compartment. The implementation of ChroP is relatively straightforward, given the minor modifications to the standard ChIP protocol for ChIP-Seq; hence, it is amenable to numerous applications in various functional studies by epigenetics groups, to dissect chromatin composition and dynamics in a system-wide fashion.
DNA methylation also plays a pivotal role in mediating the epigenetic inheritance of specific expressions pattern on the genome, and the study of the interacting proteins is critical for a deep understanding of the molecular basis of its function. This has been achieved using immobilized oligonucleotides in combination with quantitative proteomics, in a setup very similar to protein-based pull down assays: DOC-1 (Deleted in Oral Cancer-1) and RBP-J (recombination signal binding protein for immunoglobulin kappa J region) were found to bind methylated CpG regions with this strategy [168–170]. In line with studies that aim to link the genome features with their associated protein interactome, two recent studies found a novel protein interactor of a single nucleotide polymorphism at the IGF2 locus, which may provide an explanation for the phenotypic effects of this polymorphism [171,172].
Finally, given the increasing importance of RNA in the epigenetics field [173,174], the combination of RNA-pull-downs with quantitative proteomics enable investigations at both the RNA-protein interactome and protein-protein interactions mediated by the presence of non-coding RNAs [175,176]. Typically, protein UV cross-linking followed by immunoprecipitation (CLIP) or RNA-binding protein immunoprecipitation (RIP) in combination with microarray hybridization or sequencing provide transcriptome-wide identification of interacting RNAs . Alternatively, mass spectrometry can be employed to screen systematically for proteins specifically bound to a specific RNA recognition element (RRE) within a longer RNA fragments. This quantitative approach has been used to characterize proteins binding to the 3′-untranslated region (3′-UTR) of HDAC2  and of the viral gene DENV-2 . Recently, purification of cross-linked MS2-tagged ribonucleoproteins, using SILAC for unambiguous discrimination of genuine binders, has also been described . The extension of such protein-centric approaches to other RNA-centric methods will allow the genome-wide detection of novel RNA-binding proteins (RBP) for distinct RNAs species.
Mass spectrometry-based proteomics has emerged as a powerful analytical method for the analysis of histone proteins, their post-translational modifications and variants, as well as their associated “writers” and “readers”. The method is therefore able to provide information that is in line with, and highly complementary to, other commonly used techniques, such as ChIP-Seq. In this review we have provided an overview of various MS-based proteomics approaches that enable novel insights into chromatin biology. In recent years, the advances in the dynamic range and sensitivity of MS instruments have allowed for improved detection of sub-stoichiometric histone PTMs. Furthermore, the novel chromatin interactomics’ studies described in this review have led to the identification of regions specific modifications, variants and non-histonic associated proteins.
Detecting the combinatorial aspect of the histone code, however, remains a daunting task. The “Bottom Up” approach is efficient for amino acid sequencing and improved throughput for complex samples, however, it offers only a partial view of the complex cross-talks occurring among different hPTMs. In this respect, advances in “Middle Down” and “Top Down” approaches suggest that only a combination of the three MS approaches will provide the comprehensive solution to crack the histone code. At present however two major limitations limit the applicability of protein–centric approaches: first, the lack of straightforward “Middle Down” or “Top Down” analytical workflows, from sample preparation and protein separation, to MS detection and data processing, compatible with large-scale analyses; secondly, the bioinformatics tools available do not effectively handle the higher complexity of tandem mass spectra.
The global and quantitative profiling of hPTMs and the cognate interactomes by MS may have a strong impact in cancer epigenetics research. In fact, while for a long time much effort has been invested in identifying genetic mutations in cancer, in recent years the scientific community has progressively recognized that, in some cancers, epigenetic components may predominate over the genetic ones, with genetic and epigenetic determinants of cancer initiation and progression intricately entwined. In this light, the deep understanding of the epigenetic aberration in cancer is essential to recognize better why cancers arise (because the factors that could cause genetic damage might not be the same as those that could cause epigenetic damage) and why some cancers may respond better to certain types of therapies, as some types of therapies may be more efficient on epigenetically-damaged cancers. In this light, strategies based on the combination of high-resolution MS and quantitative proteomics for the analysis of chromatin, represent reliable, comprehensive and sensitive tools for the detection of changes in PTM abundances during the transition from a healthy condition to the tumor, offering an essential contribution to the understanding of epigenetic phenomena in cancer biology.
Tiziana Bonaldi’s research is supported by grants from the Giovanni Armenise-Harvard Foundation Career Development Program, the Association of International Cancer Research, the Italian Association for Cancer Research, Cariplo Foundation, and the Italian Ministry of Health. Monica Soldi’s work has been supported by FIRC fellowship.
Conflict of Interest
The authors declare no conflict of interest.
- Kornberg, R.D. Chromatin structure: A repeating unit of histones and DNA. Science 1974, 184, 868–871. [Google Scholar]
- Luger, K.; Mader, A.W.; Richmond, R.K.; Sargent, D.F.; Richmond, T.J. Crystal structure of the nucleosome core particle at 2.8 A resolution. Nature 1997, 389, 251–260. [Google Scholar]
- Dillon, N. Heterochromatin structure and function. Biol. Cell 2004, 96, 631–637. [Google Scholar]
- Beisel, C.; Paro, R. Silencing chromatin: comparing modes and mechanisms. Nat. Rev. Genet 2011, 12, 123–135. [Google Scholar]
- Grewal, S.I.; Jia, S. Heterochromatin revisited. Nat. Rev. Genet 2007, 8, 35–46. [Google Scholar]
- Probst, A.V.; Dunleavy, E.; Almouzni, G. Epigenetic inheritance during the cell cycle. Nat. Rev. Mol. Cell Biol 2009, 10, 192–206. [Google Scholar]
- Waddington, C.H. The epigenotype. 1942. Int. J. Epidemiol 2011, 41, 10–13. [Google Scholar]
- Berger, S.L. The complex language of chromatin regulation during transcription. Nature 2007, 447, 407–412. [Google Scholar]
- Nightingale, K.P.; O’Neill, L.P.; Turner, B.M. Histone modifications: signalling receptors and potential elements of a heritable epigenetic code. Curr. Opin. Genet. Dev 2006, 16, 125–136. [Google Scholar]
- Turner, B.M. Defining an epigenetic code. Nat. Cell Biol 2007, 9, 2–6. [Google Scholar]
- Berger, S.L.; Kouzarides, T.; Shiekhattar, R.; Shilatifard, A. An operational definition of epigenetics. Genes. Dev 2009, 23, 781–783. [Google Scholar]
- Klose, R.J.; Bird, A.P. Genomic DNA methylation: the mark and its mediators. Trends Biochem. Sci 2006, 31, 89–97. [Google Scholar]
- Bird, A. DNA methylation patterns and epigenetic memory. Genes. Dev 2002, 16, 6–21. [Google Scholar]
- Amaral, P.P.; Dinger, M.E.; Mercer, T.R.; Mattick, J.S. The eukaryotic genome as an RNA machine. Science 2008, 319, 1787–1789. [Google Scholar]
- Mattick, J.S.; Amaral, P.P.; Dinger, M.E.; Mercer, T.R.; Mehler, M.F. RNA regulation of epigenetic processes. Bioessays 2009, 31, 51–59. [Google Scholar]
- Kouzarides, T. Chromatin modifications and their function. Cell 2007, 128, 693–705. [Google Scholar]
- Bannister, A.J.; Kouzarides, T. Regulation of chromatin by histone modifications. Cell Res 2011, 21, 381–395. [Google Scholar]
- Campos, E.I.; Reinberg, D. Histones: Annotating chromatin. Annu. Rev. Genet 2009, 43, 559–599. [Google Scholar]
- Spotswood, H.T.; Turner, B.M. An increasingly complex code. J. Clin. Invest 2002, 110, 577–582. [Google Scholar]
- Jenuwein, T.; Allis, C.D. Translating the histone code. Science 2001, 293, 1074–1080. [Google Scholar]
- Taverna, S.D.; Li, H.; Ruthenburg, A.J.; Allis, C.D.; Patel, D.J. How chromatin-binding modules interpret histone modifications: lessons from professional pocket pickers. Nat. Struct. Mol. Biol 2007, 14, 1025–1040. [Google Scholar]
- Martin, C.; Zhang, Y. The diverse functions of histone lysine methylation. Nat. Rev. Mol. Cell Biol 2005, 6, 838–849. [Google Scholar]
- Margueron, R.; Reinberg, D. Chromatin structure and the inheritance of epigenetic information. Nat. Rev. Genet 2010, 11, 285–296. [Google Scholar]
- Park, P.J. Epigenetics meets next-generation sequencing. Epigenetics 2008, 3, 318–321. [Google Scholar]
- Barski, A.; Cuddapah, S.; Cui, K.; Roh, T.Y.; Schones, D.E.; Wang, Z.; Wei, G.; Chepelev, I.; Zhao, K. High-resolution profiling of histone methylations in the human genome. Cell 2007, 129, 823–837. [Google Scholar]
- Ku, C.S.; Naidoo, N.; Wu, M.; Soong, R. Studying the epigenome using next generation sequencing. J. Med. Genet 2011, 48, 721–730. [Google Scholar]
- Cheung, P.; Tanner, K.G.; Cheung, W.L.; Sassone-Corsi, P.; Denu, J.M.; Allis, C.D. Synergistic coupling of histone H3 phosphorylation and acetylation in response to epidermal growth factor stimulation. Mol. Cell 2000, 5, 905–915. [Google Scholar]
- Lo, W.S.; Trievel, R.C.; Rojas, J.R.; Duggan, L.; Hsu, J.Y.; Allis, C.D.; Marmorstein, R.; Berger, S.L. Phosphorylation of serine 10 in histone H3 is functionally linked in vitro and in vivo to Gcn5-mediated acetylation at lysine 14. Mol. Cell 2000, 5, 917–926. [Google Scholar]
- Peach, S.E.; Rudomin, E.L.; Udeshi, N.D.; Carr, S.A.; Jaffe, J.D. Quantitative Assessment of Chromatin Immunoprecipitation Grade Antibodies Directed against Histone Modifications Reveals Patterns of Co-occurring Marks on Histone Protein Molecules. Mol. Cell Proteomics 2012, 11, 128–137. [Google Scholar]
- Fuchs, S.M.; Krajewski, K.; Baker, R.W.; Miller, V.L.; Strahl, B.D. Influence of combinatorial histone modifications on antibody and effector protein recognition. Curr. Biol 2011, 21, 53–58. [Google Scholar]
- Aebersold, R.; Mann, M. Mass spectrometry-based proteomics. Nature 2003, 422, 198–207. [Google Scholar]
- Sidoli, S.; Cheng, L.; Jensen, O.N. Proteomics in chromatin biology and epigenetics: Elucidation of post-translational modifications of histone proteins by mass spectrometry. J. Proteomics 2012, 75, 3419–3433. [Google Scholar]
- Taverna, S.D.; Ueberheide, B.M.; Liu, Y.; Tackett, A.J.; Diaz, R.L.; Shabanowitz, J.; Chait, B.T.; Hunt, D.F.; Allis, C.D. Long-distance combinatorial linkage between methylation and acetylation on histone H3 N termini. Proc. Natl. Acad. Sci. USA 2007, 104, 2086–2091. [Google Scholar]
- Beck, H.C. Mass spectrometry in epigenetic research. Methods Mol. Biol 2010, 593, 263–282. [Google Scholar]
- Britton, L.M.; Gonzales-Cope, M.; Zee, B.M.; Garcia, B.A. Breaking the histone code with quantitative mass spectrometry. Expert Rev. Proteomics 2011, 8, 631–643. [Google Scholar]
- Eberl, H.C.; Mann, M.; Vermeulen, M. Quantitative proteomics for epigenetics. Chembiochem 2011, 12, 224–234. [Google Scholar]
- Garcia, B.A.; Shabanowitz, J.; Hunt, D.F. Characterization of histones and their post-translational modifications by mass spectrometry. Curr. Opin. Chem. Biol 2007, 11, 66–73. [Google Scholar]
- Villar-Garea, A.; Imhof, A. The analysis of histone modifications. Biochim. Biophys. Acta 2006, 1764, 1932–1939. [Google Scholar]
- Tipton, J.D.; Tran, J.C.; Catherman, A.D.; Ahlf, D.R.; Durbin, K.R.; Kelleher, N.L. Analysis of intact protein isoforms by mass spectrometry. J. Biol. Chem 2011, 286, 25451–25458. [Google Scholar]
- Plazas-Mayorca, M.D.; Zee, B.M.; Young, N.L.; Fingerman, I.M.; LeRoy, G.; Briggs, S.D.; Garcia, B.A. One-pot shotgun quantitative mass spectrometry characterization of histones. J. Proteome Res 2009, 8, 5367–5374. [Google Scholar]
- Zee, B.M.; Young, N.L.; Garcia, B.A. Quantitative proteomic approaches to studying histone modifications. Curr. Chem. Genomics 2011, 5, 106–114. [Google Scholar]
- Imhof, A.; Bonaldi, T. “Chromatomics” the analysis of the chromatome. Mol. Biosyst 2005, 1, 112–116. [Google Scholar]
- Bernstein, B.E.; Meissner, A.; Lander, E.S. The mammalian epigenome. Cell 2007, 128, 669–681. [Google Scholar]
- Yates, J.R.; Ruse, C.I.; Nakorchevsky, A. Proteomics by mass spectrometry: Approaches, advances, and applications. Annu. Rev. Biomed. Eng 2009, 11, 49–79. [Google Scholar]
- Walther, T.C.; Mann, M. Mass spectrometry-based proteomics in cell biology. J. Cell Biol 2010, 190, 491–500. [Google Scholar]
- Hillenkamp, F.; Karas, M. Mass spectrometry of peptides and proteins by matrix-assisted ultraviolet laser desorption/ionization. Methods Enzymol 1990, 193, 280–295. [Google Scholar]
- Hillenkamp, F.; Karas, M.; Beavis, R.C.; Chait, B.T. Matrix-assisted laser desorption/ionization mass spectrometry of biopolymers. Anal. Chem 1991, 63, 1193A–1203A. [Google Scholar]
- Fenn, J.B.; Mann, M.; Meng, C.K.; Wong, S.F.; Whitehouse, C.M. Electrospray ionization for mass spectrometry of large biomolecules. Science 1989, 246, 64–71. [Google Scholar]
- Lagarrigue, M.; Lavigne, R.; Guevel, B.; Com, E.; Chaurand, P.; Pineau, C. Matrix-assisted laser desorption/ionization imaging mass spectrometry: A promising technique for reproductive research. Biol. Reprod. 2012, 86. [Google Scholar] [CrossRef]
- Wilm, M.; Mann, M. Analytical properties of the nanoelectrospray ion source. Anal. Chem 1996, 68, 1–8. [Google Scholar]
- Wilm, M.; Shevchenko, A.; Houthaeve, T.; Breit, S.; Schweigerer, L.; Fotsis, T.; Mann, M. Femtomole sequencing of proteins from polyacrylamide gels by nano-electrospray mass spectrometry. Nature 1996, 379, 466–469. [Google Scholar]
- Shen, Y.; Zhao, R.; Berger, S.J.; Anderson, G.A.; Rodriguez, N.; Smith, R.D. High-efficiency nanoscale liquid chromatography coupled on-line with mass spectrometry using nanoelectrospray ionization for proteomics. Anal. Chem 2002, 74, 4235–4249. [Google Scholar]
- Shen, Y.; Moore, R.J.; Zhao, R.; Blonder, J.; Auberry, D.L.; Masselon, C.; Pasa-Tolic, L.; Hixson, K.K.; Auberry, K.J.; Smith, R.D. High-efficiency on-line solid-phase extraction coupling to 15–150-microm-i.d. column liquid chromatography for proteomic analysis. Anal. Chem 2003, 75, 3596–3605. [Google Scholar]
- Shukla, A.K.; Futrell, J.H. Tandem mass spectrometry: dissociation of ions by collisional activation. J. Mass Spectrom 2000, 35, 1069–1090. [Google Scholar]
- Kelleher, N.L.; Zubarev, R.A.; Bush, K.; Furie, B.; Furie, B.C.; McLafferty, F.W.; Walsh, C.T. Localization of labile posttranslational modifications by electron capture dissociation: the case of gamma-carboxyglutamic acid. Anal. Chem 1999, 71, 4250–4253. [Google Scholar]
- Mikesh, L.M.; Ueberheide, B.; Chi, A.; Coon, J.J.; Syka, J.E.; Shabanowitz, J.; Hunt, D.F. The utility of ETD mass spectrometry in proteomic analysis. Biochim. Biophys. Acta 2006, 1764, 1811–1822. [Google Scholar]
- Syka, J.E.; Coon, J.J.; Schroeder, M.J.; Shabanowitz, J.; Hunt, D.F. Peptide and protein sequence analysis by electron transfer dissociation mass spectrometry. Proc. Natl. Acad. Sci. USA 2004, 101, 9528–9533. [Google Scholar]
- Zubarev, R.A.; Horn, D.M.; Fridriksson, E.K.; Kelleher, N.L.; Kruger, N.A.; Lewis, M.A.; Carpenter, B.K.; McLafferty, F.W. Electron capture dissociation for structural characterization of multiply charged protein cations. Anal. Chem 2000, 72, 563–573. [Google Scholar]
- Olsen, J.V.; Ong, S.E.; Mann, M. Trypsin cleaves exclusively C-terminal to arginine and lysine residues. Mol. Cell Proteomics 2004, 3, 608–614. [Google Scholar]
- Bonaldi, T.; Imhof, A.; Regula, J.T. A combination of different mass spectroscopic techniques for the analysis of dynamic changes of histone modifications. Proteomics 2004, 4, 1382–1396. [Google Scholar]
- Jufvas, A.; Stralfors, P.; Vener, A.V. Histone variants and their post-translational modifications in primary human fat cells. PLoS One 2011, 6. [Google Scholar] [CrossRef]
- Smith, C.M.; Haimberger, Z.W.; Johnson, C.O.; Wolf, A.J.; Gafken, P.R.; Zhang, Z.; Parthun, M.R.; Gottschling, D.E. Heritable chromatin structure: Mapping “memory” in histones H3 and H4. Proc. Natl. Acad. Sci. USA 2002, 99, S16454–S16461. [Google Scholar]
- Garcia, B.A.; Mollah, S.; Ueberheide, B.M.; Busby, S.A.; Muratore, T.L.; Shabanowitz, J.; Hunt, D.F. Chemical derivatization of histones for facilitated analysis by mass spectrometry. Nat. Protoc 2007, 2, 933–938. [Google Scholar]
- Bonaldi, T.; Regula, J.T.; Imhof, A. The use of mass spectrometry for the analysis of histone modifications. Methods Enzymol 2004, 377, 111–130. [Google Scholar]
- Shevchenko, A.; Tomas, H.; Havlis, J.; Olsen, J.V.; Mann, M. In-gel digestion for mass spectrometric characterization of proteins and proteomes. Nat. Protoc 2006, 1, 2856–2860. [Google Scholar]
- Trelle, M.B.; Salcedo-Amaya, A.M.; Cohen, A.M.; Stunnenberg, H.G.; Jensen, O.N. Global histone analysis by mass spectrometry reveals a high content of acetylated lysine residues in the malaria parasite Plasmodium falciparum. J. Proteome Res 2009, 8, 3439–3450. [Google Scholar]
- Loyola, A.; Bonaldi, T.; Roche, D.; Imhof, A.; Almouzni, G. PTMs on H3 variants before chromatin assembly potentiate their final epigenetic state. Mol. Cell 2006, 24, 309–316. [Google Scholar]
- Trelle, M.B.; Jensen, O.N. Functional proteomics in histone research and epigenetics. Expert Rev. Proteomics 2007, 4, 491–503. [Google Scholar]
- Kelleher, N.L. Top-down proteomics. Anal. Chem 2004, 76, 197A–203A. [Google Scholar]
- Boyne, M.T., 2nd; Pesavento, J.J.; Mizzen, C.A.; Kelleher, N.L. Precise characterization of human histones in the H2A gene family by top down mass spectrometry. J. Proteome Res. 2006, 5, 248–253. [Google Scholar]
- Breuker, K.; Oh, H.; Lin, C.; Carpenter, B.K.; McLafferty, F.W. Nonergodic and conformational control of the electron capture dissociation of protein cations. Proc. Natl. Acad. Sci. USA 2004, 101, 14011–14016. [Google Scholar]
- Thomas, C.E.; Kelleher, N.L.; Mizzen, C.A. Mass spectrometric characterization of human histone H3: a bird’s eye view. J. Proteome Res 2006, 5, 240–247. [Google Scholar]
- Eliuk, S.M.; Maltby, D.; Panning, B.; Burlingame, A.L. High resolution electron transfer dissociation studies of unfractionated intact histones from murine embryonic stem cells using on-line capillary LC separation: determination of abundant histone isoforms and post-translational modifications. Mol. Cell Proteomics 2010, 9, 824–837. [Google Scholar]
- Tian, Z.; Zhao, R.; Tolic, N.; Moore, R.J.; Stenoien, D.L.; Robinson, E.W.; Smith, R.D.; Pasa-Tolic, L. Two-dimensional liquid chromatography system for online top-down mass spectrometry. Proteomics 2010, 10, 3610–3620. [Google Scholar]
- Garcia, B.A. What does the future hold for Top Down mass spectrometry? J. Am. Soc. Mass Spectrom 2010, 21, 193–202. [Google Scholar]
- Young, N.L.; DiMaggio, P.A.; Plazas-Mayorca, M.D.; Baliban, R.C.; Floudas, C.A.; Garcia, B.A. High throughput characterization of combinatorial histone codes. Mol. Cell Proteomics 2009, 8, 2266–2284. [Google Scholar]
- DiMaggio, P.A., Jr; Young, N.L.; Baliban, R.C.; Garcia, B.A.; Floudas, C.A. A mixed integer linear optimization framework for the identification and quantification of targeted post-translational modifications of highly modified proteins using multiplexed electron transfer dissociation tandem mass spectrometry. Mol. Cell Proteomics 2009, 8, 2527–2543. [Google Scholar]
- Frank, A.M.; Pesavento, J.J.; Mizzen, C.A.; Kelleher, N.L.; Pevzner, P.A. Interpreting top-down mass spectra using spectral alignment. Anal. Chem 2008, 80, 2499–2505. [Google Scholar]
- Guan, S.; Burlingame, A.L. Data processing algorithms for analysis of high-resolution MSMS spectra of peptides with complex patterns of posttranslational modifications. Mol. Cell Proteomics 2010, 9, 804–810. [Google Scholar]
- Matthiesen, R.; Trelle, M.B.; Hojrup, P.; Bunkenborg, J.; Jensen, O.N. VEMS 3.0: Algorithms and computational tools for tandem mass spectrometry based identification of post-translational modifications in proteins. J. Proteome Res 2005, 4, 2338–2347. [Google Scholar]
- Wilkins, M.R.; Gasteiger, E.; Gooley, A.A.; Herbert, B.R.; Molloy, M.P.; Binz, P.A.; Ou, K.; Sanchez, J.C.; Bairoch, A.; Williams, K.L.; et al. High-throughput mass spectrometric discovery of protein post-translational modifications. J. Mol. Biol 1999, 289, 645–657. [Google Scholar]
- Perkins, D.N.; Pappin, D.J.; Creasy, D.M.; Cottrell, J.S. Probability-based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis 1999, 20, 3551–3567. [Google Scholar]
- Cox, J.; Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol 2008, 26, 1367–1372. [Google Scholar]
- Savitski, M.M.; Nielsen, M.L.; Zubarev, R.A. ModifiComb, a new proteomic tool for mapping substoichiometric post-translational modifications, finding novel types of modifications, and fingerprinting complex protein mixtures. Mol. Cell. Proteomics 2006, 5, 935–948. [Google Scholar]
- Geer, L.Y.; Markey, S.P.; Kowalak, J.A.; Wagner, L.; Xu, M.; Maynard, D.M.; Yang, X.; Shi, W.; Bryant, S.H. Open mass spectrometry search algorithm. J. Proteome Res 2004, 3, 958–964. [Google Scholar]
- Colinge, J.; Masselot, A.; Cusin, I.; Mahe, E.; Niknejad, A.; Argoud-Puy, G.; Reffas, S.; Bederr, N.; Gleizes, A.; Rey, P.A.; et al. High-performance peptide identification by tandem mass spectrometry allows reliable automatic data processing in proteomics. Proteomics 2004, 4, 1977–1984. [Google Scholar]
- Baliban, R.C.; DiMaggio, P.A.; Plazas-Mayorca, M.D.; Young, N.L.; Garcia, B.A.; Floudas, C.A. A novel approach for untargeted post-translational modification identification using integer linear optimization and tandem mass spectrometry. Mol. Cell. Proteomics 2010, 9, 764–779. [Google Scholar]
- Zamdborg, L.; LeDuc, R.D.; Glowacz, K.J.; Kim, Y.B.; Viswanathan, V.; Spaulding, I.T.; Early, B.P.; Bluhm, E.J.; Babai, S.; Kelleher, N. ProSight PTM 2.0: Improved protein identification and characterization for top down mass spectrometry. Nucleic Acids Res 2007, 35, W701–W706. [Google Scholar]
- Chalkley, R.J.; Baker, P.R.; Huang, L.; Hansen, K.C.; Allen, N.P.; Rexach, M.; Burlingame, A.L. Comprehensive analysis of a multidimensional liquid chromatography mass spectrometry dataset acquired on a quadrupole selecting, quadrupole collision cell, time-of-flight mass spectrometer: II. New developments in Protein Prospector allow for reliable and comprehensive automatic analysis of large datasets. Mol. Cell. Proteomics 2005, 4, 1194–1204. [Google Scholar]
- Ahrne, E.; Ohta, Y.; Nikitin, F.; Scherl, A.; Lisacek, F.; Muller, M. An improved method for the construction of decoy peptide MS/MS spectra suitable for the accurate estimation of false discovery rates. Proteomics 2011, 11, 4085–4095. [Google Scholar]
- Eng, J.K.; McCormack, A.L.; Yates, J.R. An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J. Am. Soc. Mass Spectrom 1994, 5, 976–989. [Google Scholar]
- Liu, J.; Erassov, A.; Halina, P.; Canete, M.; Nguyen, D.V.; Chung, C.; Cagney, G.; Ignatchenko, A.; Fong, V.; Emili, A. Sequential interval motif search: Unrestricted database surveys of global MS/MS data sets for detection of putative post-translational modifications. Anal. Chem 2008, 80, 7846–7854. [Google Scholar]
- Craig, R.; Beavis, R.C. A method for reducing the time required to match protein sequences with tandem mass spectra. Rapid Commun. Mass Spectrom 2003, 17, 2310–2316. [Google Scholar]
- Marshall, A.G.; Hendrickson, C.L. High-resolution mass spectrometers. Annu. Rev. Anal. Chem 2008, 1, 579–599. [Google Scholar]
- Nielsen, M.L.; Vermeulen, M.; Bonaldi, T.; Cox, J.; Moroder, L.; Mann, M. Iodoacetamide-induced artifact mimics ubiquitination in mass spectrometry. Nat. Methods 2008, 5, 459–460. [Google Scholar]
- Bantscheff, M.; Schirle, M.; Sweetman, G.; Rick, J.; Kuster, B. Quantitative mass spectrometry in proteomics: A critical review. Anal. BioAnal. Chem 2007, 389, 1017–1031. [Google Scholar]
- Nikolov, M.; Schmidt, C.; Urlaub, H. Quantitative mass spectrometry-based proteomics: An overview. Methods Mol. Biol 2012, 893, 85–100. [Google Scholar]
- Voigt, P.; LeRoy, G.; Drury, W.J., 3rd; Zee, B.M.; Son, J.; Beck, D.B.; Young, N.L.; Garcia, B.A.; Reinberg, D. Asymmetrically modified nucleosomes. Cell 2012, 151, 181–193. [Google Scholar]
- Montes de Oca, R.; Shoemaker, C.J.; Gucek, M.; Cole, R.N.; Wilson, K.L. Barrier-to-autointegration factor proteome reveals chromatin-regulatory partners. PLoS One 2009, 4. [Google Scholar] [CrossRef]
- Yuan, X.; Gu, X.; Crabb, J.S.; Yue, X.; Shadrach, K.; Hollyfield, J.G.; Crabb, J.W. Quantitative proteomics: Comparison of the macular Bruch membrane/choroid complex from age-related macular degeneration and normal eyes. Mol. Cell Proteomics 2010, 9, 1031–1046. [Google Scholar]
- Salim, K.; Kehoe, L.; Minkoff, M.S.; Bilsland, J.G.; Munoz-Sanjuan, I.; Guest, P.C. Identification of differentiating neural progenitor cell markers using shotgun isobaric tagging mass spectrometry. Stem Cells Dev 2006, 15, 461–470. [Google Scholar]
- Ong, S.E.; Blagoev, B.; Kratchmarova, I.; Kristensen, D.B.; Steen, H.; Pandey, A.; Mann, M. Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol. Cell Proteomics 2002, 1, 376–386. [Google Scholar]
- Stunnenberg, H.G.; Vermeulen, M. Towards cracking the epigenetic code using a combination of high-throughput epigenomics and quantitative mass spectrometry-based proteomics. Bioessays 2011, 33, 547–551. [Google Scholar]
- Ong, S.E.; Mann, M. Stable isotope labeling by amino acids in cell culture for quantitative proteomics. Methods Mol. Biol 2007, 359, 37–52. [Google Scholar]
- Pimienta, G.; Chaerkady, R.; Pandey, A. SILAC for global phosphoproteomic analysis. Methods Mol. Biol 2009, 527, 107–116. [Google Scholar]
- Bonenfant, D.; Towbin, H.; Coulot, M.; Schindler, P.; Mueller, D.R.; van Oostrum, J. Analysis of dynamic changes in post-translational modifications of human histones during cell cycle by mass spectrometry. Mol. Cell Proteomics 2007, 6, 1917–1932. [Google Scholar]
- Pesavento, J.J.; Yang, H.; Kelleher, N.L.; Mizzen, C.A. Certain and progressive methylation of histone H4 at lysine 20 during the cell cycle. Mol. Cell Biol 2008, 28, 468–486. [Google Scholar]
- Scharf, A.N.; Meier, K.; Seitz, V.; Kremmer, E.; Brehm, A.; Imhof, A. Monomethylation of lysine 20 on histone H4 facilitates chromatin maturation. Mol. Cell Biol 2009, 29, 57–67. [Google Scholar]
- Jung, H.R.; Pasini, D.; Helin, K.; Jensen, O.N. Quantitative mass spectrometry of histones H3.2 and H3.3 in Suz12-deficient mouse embryonic stem cells reveals distinct, dynamic post-translational modifications at Lys-27 and Lys-36. Mol. Cell Proteomics 2010, 9, 838–850. [Google Scholar]
- Pan, C.; Olsen, J.V.; Daub, H.; Mann, M. Global effects of kinase inhibitors on signaling networks revealed by quantitative phosphoproteomics. Mol. Cell Proteomics 2009, 8, 2796–2808. [Google Scholar]
- Cuomo, A.; Moretti, S.; Minucci, S.; Bonaldi, T. SILAC-based proteomic analysis to dissect the “histone modification signature” of human breast cancer cells. Amino Acids 2011, 41, 387–399. [Google Scholar]
- Geiger, T.; Cox, J.; Ostasiewicz, P.; Wisniewski, J.R.; Mann, M. Super-SILAC mix for quantitative proteomics of human tumor tissue. Nat. Methods 2010, 7, 383–385. [Google Scholar]
- Geiger, T.; Wisniewski, J.R.; Cox, J.; Zanivan, S.; Kruger, M.; Ishihama, Y.; Mann, M. Use of stable isotope labeling by amino acids in cell culture as a spike-in standard in quantitative proteomics. Nat. Protoc 2011, 6, 147–157. [Google Scholar]
- Zee, B.M.; Levin, R.S.; Dimaggio, P.A.; Garcia, B.A. Global turnover of histone post-translational modifications and variants in human cells. Epigenetics Chromatin 2010, 3. [Google Scholar] [CrossRef]
- Ong, S.E.; Mittler, G.; Mann, M. Identifying and quantifying in vivo methylation sites by heavy methyl SILAC. Nat. Methods 2004, 1, 119–126. [Google Scholar]
- Fodor, B.D.; Kubicek, S.; Yonezawa, M.; O’Sullivan, R.J.; Sengupta, R.; Perez-Burgos, L.; Opravil, S.; Mechtler, K.; Schotta, G.; Jenuwein, T. Jmjd2b antagonizes H3K9 trimethylation at pericentric heterochromatin in mammalian cells. Genes. Dev 2006, 20, 1557–1562. [Google Scholar]
- Zee, B.M.; Levin, R.S.; Xu, B.; LeRoy, G.; Wingreen, N.S.; Garcia, B.A. In vivo residue-specific histone methylation dynamics. J. Biol. Chem 2010, 285, 3341–3350. [Google Scholar]
- Sweet, S.M.; Li, M.; Thomas, P.M.; Durbin, K.R.; Kelleher, N.L. Kinetics of re-establishing H3K79 methylation marks in global human chromatin. J. Biol. Chem 2010, 285, 32778–32786. [Google Scholar]
- Pesavento, J.J.; Mizzen, C.A.; Kelleher, N.L. Quantitative analysis of modified proteins and their positional isomers by tandem mass spectrometry: human histone H4. Anal. Chem 2006, 78, 4271–4280. [Google Scholar]
- Garcia, B.A.; Pesavento, J.J.; Mizzen, C.A.; Kelleher, N.L. Pervasive combinatorial modification of histone H3 in human cells. Nat. Methods 2007, 4, 487–489. [Google Scholar]
- Picotti, P.; Aebersold, R. Selected reaction monitoring-based proteomics: workflows, potential, pitfalls and future directions. Nat. Methods 2012, 9, 555–566. [Google Scholar]
- Darwanto, A.; Curtis, M.P.; Schrag, M.; Kirsch, W.; Liu, P.; Xu, G.; Neidigh, J.W.; Zhang, K. A modified “cross-talk” between histone H2B Lys-120 ubiquitination and H3 Lys-79 methylation. J. Biol. Chem 2010, 285, 21868–21876. [Google Scholar]
- Yuan, G.; Zhu, B. Histone variants and epigenetic inheritance. Biochim. Biophys. Acta 2012, 1819, 222–229. [Google Scholar]
- Hake, S.B.; Allis, C.D. Histone H3 variants and their potential role in indexing mammalian genomes: the “H3 barcode hypothesis”. Proc. Natl. Acad. Sci. USA 2006, 103, 6428–6435. [Google Scholar]
- Hake, S.B.; Garcia, B.A.; Duncan, E.M.; Kauer, M.; Dellaire, G.; Shabanowitz, J.; Bazett-Jones, D.P.; Allis, C.D.; Hunt, D.F. Expression patterns and post-translational modifications associated with mammalian histone H3 variants. J. Biol. Chem 2006, 281, 559–568. [Google Scholar]
- McKittrick, E.; Gafken, P.R.; Ahmad, K.; Henikoff, S. Histone H3.3 is enriched in covalent modifications associated with active chromatin. Proc. Natl. Acad. Sci. USA 2004, 101, 1525–1530. [Google Scholar]
- Johnson, L.; Mollah, S.; Garcia, B.A.; Muratore, T.L.; Shabanowitz, J.; Hunt, D.F.; Jacobsen, S.E. Mass spectrometry analysis of Arabidopsis histone H3 reveals distinct combinations of post-translational modifications. Nucleic Acids Res 2004, 32, 6511–6518. [Google Scholar]
- Garcia, B.A.; Siuti, N.; Thomas, C.E.; Mizzen, C.A.; Kelleher, N.L. Characterization of neurohistone variants and post-translational modifications by electron capture dissociation mass spectrometry. Int. J. Mass Spectrom 2007, 259, 184–196. [Google Scholar]
- Garcia, B.A.; Thomas, C.E.; Kelleher, N.L.; Mizzen, C.A. Tissue-specific expression and post-translational modification of histone H3 variants. J. Proteome Res 2008, 7, 4225–4236. [Google Scholar]
- Bonenfant, D.; Coulot, M.; Towbin, H.; Schindler, P.; van Oostrum, J. Characterization of histone H2A and H2B variants and their post-translational modifications by mass spectrometry. Mol. Cell Proteomics 2006, 5, 541–552. [Google Scholar]
- Wang, H.; Wang, L.; Erdjument-Bromage, H.; Vidal, M.; Tempst, P.; Jones, R.S.; Zhang, Y. Role of histone H2A ubiquitination in Polycomb silencing. Nature 2004, 431, 873–878. [Google Scholar]
- Ikura, T.; Tashiro, S.; Kakino, A.; Shima, H.; Jacob, N.; Amunugama, R.; Yoder, K.; Izumi, S.; Kuraoka, I.; Tanaka, K.; et al. DNA damage-dependent acetylation and ubiquitination of H2AX enhances chromatin dynamics. Mol. Cell Biol 2007, 27, 7028–7040. [Google Scholar]
- Rangasamy, D.; Greaves, I.; Tremethick, D.J. RNA interference demonstrates a novel role for H2A.Z in chromosome segregation. Nat. Struct. Mol. Biol 2004, 11, 650–655. [Google Scholar]
- Chu, F.; Nusinow, D.A.; Chalkley, R.J.; Plath, K.; Panning, B.; Burlingame, A.L. Mapping post-translational modifications of the histone variant MacroH2A1 using tandem mass spectrometry. Mol. Cell Proteomics 2006, 5, 194–203. [Google Scholar]
- Bernstein, E.; Muratore-Schroeder, T.L.; Diaz, R.L.; Chow, J.C.; Changolkar, L.N.; Shabanowitz, J.; Heard, E.; Pehrson, J.R.; Hunt, D.F.; Allis, C.D. A phosphorylated subpopulation of the histone variant macroH2A1 is excluded from the inactive X chromosome and enriched during mitosis. Proc. Natl. Acad. Sci. USA 2008, 105, 1533–1538. [Google Scholar]
- Siuti, N.; Roth, M.J.; Mizzen, C.A.; Kelleher, N.L.; Pesavento, J.J. Gene-specific characterization of human histone H2B by electron capture dissociation. J. Proteome Res 2006, 5, 233–239. [Google Scholar]
- Zhang, L.; Eugeni, E.E.; Parthun, M.R.; Freitas, M.A. Identification of novel histone post-translational modifications by peptide mass fingerprinting. Chromosoma 2003, 112, 77–86. [Google Scholar]
- Lu, S.; Xie, Y.M.; Li, X.; Luo, J.; Shi, X.Q.; Hong, X.; Pan, Y.H.; Ma, X. Mass spectrometry analysis of dynamic post-translational modifications of TH2B during spermatogenesis. Mol. Hum. Reprod 2009, 15, 373–378. [Google Scholar]
- Medzihradszky, K.F.; Zhang, X.; Chalkley, R.J.; Guan, S.; McFarland, M.A.; Chalmers, M.J.; Marshall, A.G.; Diaz, R.L.; Allis, C.D.; Burlingame, A.L. Characterization of Tetrahymena histone H2B variants and posttranslational populations by electron capture dissociation (ECD) Fourier transform ion cyclotron mass spectrometry (FT-ICR MS). Mol. Cell Proteomics 2004, 3, 872–886. [Google Scholar]
- Villar-Garea, A.; Forne, I.; Vetter, I.; Kremmer, E.; Thomae, A.; Imhof, A. Developmental regulation of N-terminal H2B methylation in Drosophila melanogaster. Nucleic Acids Res 2012, 40, 1536–1549. [Google Scholar]
- Talasz, H.; Sarg, B.; Lindner, H.H. Site-specifically phosphorylated forms of H1.5 and H1.2 localized at distinct regions of the nucleus are related to different processes during the cell cycle. Chromosoma 2009, 118, 693–709. [Google Scholar]
- Wisniewski, J.R.; Zougman, A.; Kruger, S.; Mann, M. Mass spectrometric mapping of linker histone H1 variants reveals multiple acetylations, methylations, and phosphorylation as well as differences between cell culture and tissue. Mol. Cell Proteomics 2007, 6, 72–87. [Google Scholar]
- Garcia, B.A.; Busby, S.A.; Barber, C.M.; Shabanowitz, J.; Allis, C.D.; Hunt, D.F. Characterization of phosphorylation sites on histone H1 isoforms by tandem mass spectrometry. J. Proteome Res 2004, 3, 1219–1227. [Google Scholar]
- Weiss, T.; Hergeth, S.; Zeissler, U.; Izzo, A.; Tropberger, P.; Zee, B.M.; Dundr, M.; Garcia, B.A.; Daujat, S.; Schneider, R. Histone H1 variant-specific lysine methylation by G9a/KMT1C and Glp1/KMT1D. Epigenetics Chromatin 2010, 3. [Google Scholar] [CrossRef]
- Villar-Garea, A.; Imhof, A. Fine mapping of posttranslational modifications of the linker histone H1 from Drosophila melanogaster. PLoS One 2008, 3. [Google Scholar] [CrossRef]
- Daujat, S.; Zeissler, U.; Waldmann, T.; Happel, N.; Schneider, R. HP1 binds specifically to Lys26-methylated histone H1.4, whereas simultaneous Ser27 phosphorylation blocks HP1 binding. J. Biol. Chem 2005, 280, 38090–38095. [Google Scholar]
- Zheng, Y.; John, S.; Pesavento, J.J.; Schultz-Norton, J.R.; Schiltz, R.L.; Baek, S.; Nardulli, A.M.; Hager, G.L.; Kelleher, N.L.; Mizzen, C.A. Histone H1 phosphorylation is associated with transcription by RNA polymerases I and II. J. Cell Biol 2010, 189, 407–415. [Google Scholar]
- Shiio, Y.; Eisenman, R.N.; Yi, E.C.; Donohoe, S.; Goodlett, D.R.; Aebersold, R. Quantitative proteomic analysis of chromatin-associated factors. J. Am. Soc. Mass Spectrom 2003, 14, 696–703. [Google Scholar]
- Porter, I.M.; McClelland, S.E.; Khoudoli, G.A.; Hunter, C.J.; Andersen, J.S.; McAinsh, A.D.; Blow, J.J.; Swedlow, J.R. Bod1, a novel kinetochore protein required for chromosome biorientation. J. Cell Biol 2007, 179, 187–197. [Google Scholar]
- Gassmann, R.; Henzing, A.J.; Earnshaw, W.C. Novel components of human mitotic chromosomes identified by proteomic analysis of the chromosome scaffold fraction. Chromosoma 2005, 113, 385–397. [Google Scholar]
- Uchiyama, S.; Kobayashi, S.; Takata, H.; Ishihara, T.; Hori, N.; Higashi, T.; Hayashihara, K.; Sone, T.; Higo, D.; Nirasawa, T.; et al. Proteome analysis of human metaphase chromosomes. J. Biol. Chem 2005, 280, 16994–17004. [Google Scholar]
- Takata, H.; Uchiyama, S.; Nakamura, N.; Nakashima, S.; Kobayashi, S.; Sone, T.; Kimura, S.; Lahmers, S.; Granzier, H.; Labeit, S.; et al. A comparative proteome analysis of human metaphase chromosomes isolated from two different cell lines reveals a set of conserved chromosome-associated proteins. Genes. Cells 2007, 12, 269–284. [Google Scholar]
- Morrison, C.; Henzing, A.J.; Jensen, O.N.; Osheroff, N.; Dodson, H.; Kandels-Lewis, S.E.; Adams, R.R.; Earnshaw, W.C. Proteomic analysis of human metaphase chromosomes reveals topoisomerase II alpha as an Aurora B substrate. Nucleic Acids Res 2002, 30, 5318–5327. [Google Scholar]
- Khoudoli, G.A.; Gillespie, P.J.; Stewart, G.; Andersen, J.S.; Swedlow, J.R.; Blow, J.J. Temporal profiling of the chromatin proteome reveals system-wide responses to replication inhibition. Curr. Biol 2008, 18, 838–843. [Google Scholar]
- Ohta, S.; Bukowski-Wills, J.C.; Sanchez-Pulido, L.; de Alves, F.L.; Wood, L.; Chen, Z.A.; Platani, M.; Fischer, L.; Hudson, D.F.; Ponting, C.P.; et al. The protein composition of mitotic chromosomes determined using multiclassifier combinatorial proteomics. Cell 2010, 142, 810–821. [Google Scholar]
- Dejardin, J.; Kingston, R.E. Purification of proteins associated with specific genomic Loci. Cell 2009, 136, 175–186. [Google Scholar]
- Vermeulen, M.; Mulder, K.W.; Denissov, S.; Pijnappel, W.W.; van Schaik, F.M.; Varier, R.A.; Baltissen, M.P.; Stunnenberg, H.G.; Mann, M.; Timmers, H.T. Selective anchoring of TFIID to nucleosomes by trimethylation of histone H3 lysine 4. Cell 2007, 131, 58–69. [Google Scholar]
- Vermeulen, M.; Eberl, H.C.; Matarese, F.; Marks, H.; Denissov, S.; Butter, F.; Lee, K.K.; Olsen, J.V.; Hyman, A.A.; Stunnenberg, H.G.; Mann, M. Quantitative interaction proteomics and genome-wide profiling of epigenetic histone marks and their readers. Cell 2010, 142, 967–980. [Google Scholar]
- Bartke, T.; Vermeulen, M.; Xhemalce, B.; Robson, S.C.; Mann, M.; Kouzarides, T. Nucleosome-interacting proteins regulated by DNA and histone methylation. Cell 2010, 143, 470–484. [Google Scholar]
- Nikolov, M.; Stutzer, A.; Mosch, K.; Krasauskas, A.; Soeroes, S.; Stark, H.; Urlaub, H.; Fischle, W. Chromatin affinity purification and quantitative mass spectrometry defining the interactome of histone modification patterns. Mol. Cell Proteomics 2011, 10. [Google Scholar] [CrossRef]
- Li, X.; Foley, E.A.; Molloy, K.R.; Li, Y.; Chait, B.T.; Kapoor, T.M. Quantitative chemical proteomics approach to identify post-translational modification-mediated protein-protein interactions. J. Am. Chem. Soc 2012, 134, 1982–1985. [Google Scholar]
- Liu, H.; Galka, M.; Iberg, A.; Wang, Z.; Li, L.; Voss, C.; Jiang, X.; Lajoie, G.; Huang, Z.; Bedford, M.T.; Li, S.S. Systematic identification of methyllysine-driven interactions for histone and nonhistone targets. J. Proteome Res 2010, 9, 5827–5836. [Google Scholar]
- Gao, Z.; Zhang, J.; Bonasio, R.; Strino, F.; Sawai, A.; Parisi, F.; Kluger, Y.; Reinberg, D. PCGF homologs, CBX proteins, and RYBP define functionally distinct PRC1 family complexes. Mol. Cell 2012, 45, 344–356. [Google Scholar]
- Torrente, M.P.; Zee, B.M.; Young, N.L.; Baliban, R.C.; LeRoy, G.; Floudas, C.A.; Hake, S.B.; Garcia, B.A. Proteomic interrogation of human chromatin. PLoS One 2011, 6, e24747. [Google Scholar]
- Lambert, J.P.; Mitchell, L.; Rudner, A.; Baetz, K.; Figeys, D. A novel proteomics approach for the discovery of chromatin-associated protein networks. Mol. Cell Proteomics 2009, 8, 870–882. [Google Scholar]
- Byrum, S.D.; Raman, A.; Taverna, S.D.; Tackett, A.J. ChAP-MS: A method for identification of proteins and histone posttranslational modifications at a single genomic locus. Cell Rep 2012, 2, 198–205. [Google Scholar]
- Soldi, M.; Bonaldi, T. The proteomic investigation of chromatin functional domains reveals novel synergisms among distinct heterochromatin components. Mol. Cell Proteomics 2013. in press. http://www.mcponline.org/content/early/2013/01/14/mcp.M112.024307.full.pdf. [Google Scholar]
- Mittler, G.; Butter, F.; Mann, M. A SILAC-based DNA protein interaction screen that identifies candidate binding proteins to functional DNA elements. Genome. Res 2009, 19, 284–293. [Google Scholar]
- Spruijt, C.G.; Bartels, S.J.; Brinkman, A.B.; Tjeertes, J.V.; Poser, I.; Stunnenberg, H.G.; Vermeulen, M. CDK2AP1/DOC-1 is a bona fide subunit of the Mi-2/NuRD complex. Mol. Biosyst 2010, 6, 1700–1706. [Google Scholar]
- Bartels, S.J.; Spruijt, C.G.; Brinkman, A.B.; Jansen, P.W.; Vermeulen, M.; Stunnenberg, H.G. A SILAC-based screen for Methyl-CpG binding proteins identifies RBP-J as a DNA methylation and sequence-specific binding protein. PLoS One 2011, 6. [Google Scholar] [CrossRef]
- Butter, F.; Kappei, D.; Buchholz, F.; Vermeulen, M.; Mann, M. A domesticated transposon mediates the effects of a single-nucleotide polymorphism responsible for enhanced muscle growth. EMBO Rep 2010, 11, 305–311. [Google Scholar]
- Markljung, E.; Jiang, L.; Jaffe, J.D.; Mikkelsen, T.S.; Wallerman, O.; Larhammar, M.; Zhang, X.; Wang, L.; Saenz-Vash, V.; Gnirke, A.; et al. ZBED6, a novel transcription factor derived from a domesticated DNA transposon regulates IGF2 expression and muscle growth. PLoS Biol. 2009, 7. [Google Scholar] [CrossRef]
- Tsai, M.C.; Manor, O.; Wan, Y.; Mosammaparast, N.; Wang, J.K.; Lan, F.; Shi, Y.; Segal, E.; Chang, H.Y. Long noncoding RNA as modular scaffold of histone modification complexes. Science 2010, 329, 689–693. [Google Scholar]
- Kanhere, A.; Viiri, K.; Araujo, C.C.; Rasaiyaah, J.; Bouwman, R.D.; Whyte, W.A.; Pereira, C.F.; Brookes, E.; Walker, K.; Bell, G.W.; et al. Short RNAs are transcribed from repressed polycomb target genes and interact with polycomb repressive complex-2. Mol. Cell 2010, 38, 675–688. [Google Scholar]
- Butter, F.; Scheibe, M.; Morl, M.; Mann, M. Unbiased RNA-protein interaction screen by quantitative proteomics. Proc. Natl. Acad. Sci. USA 2009, 106, 10626–10631. [Google Scholar]
- Scheibe, M.; Butter, F.; Hafner, M.; Tuschl, T.; Mann, M. Quantitative mass spectrometry and PAR-CLIP to identify RNA-protein interactions. Nucleic Acids Res 2012, 40, 9897–9902. [Google Scholar]
- Urlaub, H.; Kuhn-Holsken, E.; Luhrmann, R. Analyzing RNA-protein crosslinking sites in unlabeled ribonucleoprotein complexes by mass spectrometry. Methods Mol. Biol 2008, 488, 221–245. [Google Scholar]
- Ward, A.M.; Bidet, K.; Yinglin, A.; Ler, S.G.; Hogue, K.; Blackstock, W.; Gunaratne, J.; Garcia-Blanco, M.A. Quantitative mass spectrometry of DENV-2 RNA-interacting proteins reveals that the DEAD-box RNA helicase DDX6 binds the DB1 and DB2 3′ UTR structures. RNA Biol 2011, 8, 1173–1186. [Google Scholar]
- Tsai, B.P.; Wang, X.; Huang, L.; Waterman, M.L. Quantitative profiling of in vivo-assembled RNA-protein complexes using a novel integrated proteomic approach. Mol. Cell Proteomics 2011, 10. [Google Scholar] [CrossRef]
|Table 1. Software and search algorithms used to study hPTMs.|
|Software||Freely available||Unbiased PTM search||Reference|
© 2013 by the authors; licensee MDPI, Basel, Switzerland. This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).