Decoding chromatin states by proteomic profiling of nucleosome readers.

DNA and histone modifications combine into characteristic patterns that demarcate functional regions of the genome1,2. While many 'readers' of individual modifications have been described3-5, how chromatin states comprising composite modification signatures, histone variants and internucleosomal linker DNA are interpreted is a major open question. Here we use a multidimensional proteomics strategy to systematically examine the interaction of around 2,000 nuclear proteins with over 80 modified dinucleosomes representing promoter, enhancer and heterochromatin states. By deconvoluting complex nucleosome-binding profiles into networks of co-regulated proteins and distinct nucleosomal features driving protein recruitment or exclusion, we show comprehensively how chromatin states are decoded by chromatin readers. We find highly distinctive binding responses to different features, many factors that recognize multiple features, and that nucleosomal modifications and linker DNA operate largely independently in regulating protein binding to chromatin. Our online resource, the Modification Atlas of Regulation by Chromatin States (MARCS), provides in-depth analysis tools to engage with our results and advance the discovery of fundamental principles of genome regulation by chromatin states.

Multiple Levels of Control Determine How E4bp4/Nfil3 Regulates NK Cell Development.

The transcription factor E4bp4/Nfil3 has been shown to have a critical role in the development of all innate lymphoid cell types including NK cells. In this study, we show that posttranslational modifications of E4bp4 by either SUMOylation or phosphorylation have profound effects on both E4bp4 function and NK cell development. We examined the activity of E4bp4 mutants lacking posttranslational modifications and found that Notch1 was a novel E4bp4 target gene. We observed that abrogation of Notch signaling impeded NK cell production and the total lack of NK cell development from E4bp4-/- progenitors was completely rescued by short exposure to Notch peptide ligands. This work reveals both novel mechanisms in NK cell development by a transcriptional network including E4bp4 with Notch, and that E4bp4 is a central hub to process extrinsic stimuli.

Histone H3 lysine 56 methylation regulates DNA replication through its interaction with PCNA.

Histone modifications play important roles in regulating DNA-based biological processes. Of the modified sites, histone H3 lysine 56 (H3K56) is unique in that it lies within the globular core domain near the entry-exit sites of the nucleosomal DNA superhelix and its acetylation state in yeast is a marker for newly synthesized histones in transcription, DNA repair, and DNA replication. We now report the presence of H3K56 monomethylation (H3K56me1) in mammalian cells and find that the histone lysine methytransferase G9a/KMT1C is required for H3K56me1 both in vivo and in vitro. We also find that disruption of G9a or H3K56 impairs DNA replication. Furthermore, H3K56me1 associates with the replication processivity factor PCNA primarily in G1 phase of the cell cycle and, directly, in vitro. These results find H3K56me1 in mammals and indicate a role for H3K56me1 as a chromatin docking site for PCNA prior to its function in DNA replication.

Quantitative proteomic discovery of dynamic epigenome changes that control human cytomegalovirus (HCMV) infection.

This work represents the first comprehensive quantitative analysis of global histone post-translational modifications (PTMs) from a virus infection, namely human cytomegalovirus (HCMV) infection. We used a nanoLC-MS/MS platform to identify and quantify the dynamic histone H3 and H4 PTMs expressed during HCMV replication in primary fibroblasts. Specifically, we examined the changes in histone PTMs over a 96 h time course to sample the immediate early (IE), early (E), and late (L) stages of viral infection. Several changes in histone H3 and H4 PTMs were observed, including a marked increase in H3K79me2 and H3K27me3K36me2, and a decrease in H4K16ac, highlighting likely epigenetic strategies of transcriptional activation and silencing during HCMV lytic infection. Heavy methyl-SILAC (hm-SILAC) was used to further confirm the histone methylation flux (especially for H3K79) during HCMV infection. We evaluated DOT1L (the H3K79 methyltransferase) mRNA levels in mock and HCMV-infected cells over a 96 h time course, and observed a significant increase in this methyltransferase as early as 24 hpi showing that viral infection up-regulates DOT1L expression, which drives H3K79me2. We then used shRNA to create a DOT1L knockdown cell population, and found that HCMV infection of the knockdown cells resulted in a 10-fold growth defect when compared with infected control cells not subjected to knockdown. This work documents multiple histone PTMs that occur in response to HCMV infection of fibroblasts, and provides a framework for evaluation of the role of epigenetic modifications in the virus-host interaction.

Paired single residue-transposed Lys-N and Lys-C digestions for label-free identification of N-terminal and C-terminal MS/MS peptide product ions: ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry and tandem mass spectrometry for peptide de novo sequencing.

RATIONALE: Paired Lys-N and Lys-C proteases produce peptides of identical mass and similar retention time, but different tandem mass spectra. Data from these parallel experiments provide constraints that are applied before data analysis. With this approach, we can find matched spectra before analysis, distinguish ion type, and determine residue level confidence. METHODS: Aliquots are digested separately by Lys-N and Lys-C peptidases, and analyzed by reversed-phase nano-flow liquid chromatography, collision-induced dissociation, and 14.5 T Fourier transform ion cyclotron resonance mass spectrometry. Matched pairs of fragmentation spectra with equal precursor mass and similar retention times from each digestion are compared, leveraging single-residue transposed information with independent interferences to confidently identify fragment ion type, residues, and peptides. The paired spectra are solved together as a single de novo sequencing problem. RESULTS: Two pairs of spectra of a de novo sequenced 18-mer are presented. In one example, the 18-mer has coverage of all residues except the N- and C- terminal lysines and their adjacent residues. The confidence level is high due to six pairs of transposed ions. In the other example, the coverage is incomplete. Nonetheless, nine pairs of transposed ions facilitate identification of two trimer sequence tags with high confidence, one with medium confidence, and additional sequence information with residue-by-residue confidence, thus demonstrating the value of residue-by-residue confidence. CONCLUSIONS: Sequence identity and variability, such as post-translational modifications (PTMs), are essential to understanding biological function and disease. The present method facilitates discovery of new peptides with multiple levels of confidence, promises potential characterization of PTMs, and validates peptides from databases. Independent validation may be of interest for a number of applications.

Quantitative dynamics of the link between cellular metabolism and histone acetylation.

Acetylation on the tails of histones plays an important role in controlling transcription initiation. Although the steady-state abundances of histone acetyl groups have been reported, the rate at which histones are acetylated and deacetylated on a residue-specific basis has not been quantitatively established. We added [(13)C]glucose to human cells and monitored the dynamic incorporation of (13)C-labeled acetyl groups onto specific histone lysines with quantitative mass spectrometry. We determined the turnover of acetylation to be generally slower than phosphorylation, but fast relative to methylation, and that the rate varied depending on the histone, the residue modified, and also the neighboring modifications. Cells were also treated with a deacetylase inhibitor to determine the rate due to histone acetyltransferase activity alone and in the absence of deacetylase activity. Introduction of (13)C-labeled glucose also resulted in the incorporation of (13)C into alanine, which allowed us to partition histones into existing and newly synthesized protein categories. Newly synthesized histones were slower to accumulate histone modifications, especially modifications associated with silent chromatin. Finally, we applied our new approaches to find that quiescent fibroblasts exhibited lower levels of labeled acetyl accumulation compared with proliferating fibroblasts. This suggests that acetylation rates can be modulated in cells in different biological states and that these changes can be detected with the approach presented here. The methods we describe can be broadly applied to defining the turnover of histone acetylation in other cell states such as during cellular reprogramming and to quantify non-histone protein acetylation dynamics.

Tracking DOT1L methyltransferase activity by stable isotope labelling using a selective synthetic co-factor.

Epigenetic processes influence health and disease through mechanisms which alter gene expression. In contrast to genetic changes which affect DNA sequences, epigenetic marks include DNA base modifications or post-translational modification (PTM) of proteins. Histone methylation is a prominent and versatile example of an epigenetic marker: gene expression or silencing is dependent on the location and extent of the methylation. Protein methyltransferases exhibit functional redundancy and broad preferences for multiple histone residues, which presents a challenge for the study of their individual activities. We developed an isotopically labelled analogue of co-factor S-adenosyl-L-methionine (13CD3-BrSAM), with selectivity for the histone lysine methyltransferase DOT1L, permitting tracking of methylation activity by mass spectrometry (MS). This concept could be applied to other methyltransferases, linking PTM discovery to enzymatic mediators.

Novel phosphorylation sites in the S. cerevisiae Cdc13 protein reveal new targets for telomere length regulation.

The S. cerevisiae Cdc13 is a multifunctional protein with key roles in regulation of telomerase, telomere end protection, and conventional telomere replication, all of which are cell cycle-regulated processes. Given that phosphorylation is a key mechanism for regulating protein function, we identified sites of phosphorylation using nano liquid chromatography-tandem mass spectrometry (nanoLC-MS/MS). We also determined phosphorylation abundance on both wild type (WT) and a telomerase deficient form of Cdc13, encoded by the cdc13-2 allele, in both G1 phase cells, when telomerase is not active, and G2/M phase cells, when it is. We identified 21 sites of in vivo phosphorylation, of which only five had been reported previously. In contrast, phosphorylation of two in vitro targets of the ATM-like Tel1 kinase, S249 and S255, was not detected. This result helps resolve conflicting data on the importance of phosphorylation of these residues in telomerase recruitment. Multiple residues showed differences in their cell cycle pattern of modification. For example, phosphorylation of S314 was significantly higher in the G2/M compared to the G1 phase and in WT versus mutant Cdc13, and a S314D mutation negatively affected telomere length. Our findings provide new targets in a key telomerase regulatory protein for modulation of telomere dynamics.

A chemical probe selectively inhibits G9a and GLP methyltransferase activity in cells.

Protein lysine methyltransferases G9a and GLP modulate the transcriptional repression of a variety of genes via dimethylation of Lys9 on histone H3 (H3K9me2) as well as dimethylation of non-histone targets. Here we report the discovery of UNC0638, an inhibitor of G9a and GLP with excellent potency and selectivity over a wide range of epigenetic and non-epigenetic targets. UNC0638 treatment of a variety of cell lines resulted in lower global H3K9me2 levels, equivalent to levels observed for small hairpin RNA knockdown of G9a and GLP with the functional potency of UNC0638 being well separated from its toxicity. UNC0638 markedly reduced the clonogenicity of MCF7 cells, reduced the abundance of H3K9me2 marks at promoters of known G9a-regulated endogenous genes and disproportionately affected several genomic loci encoding microRNAs. In mouse embryonic stem cells, UNC0638 reactivated G9a-silenced genes and a retroviral reporter gene in a concentration-dependent manner without promoting differentiation.

PILOT_PROTEIN: identification of unmodified and modified proteins via high-resolution mass spectrometry and mixed-integer linear optimization.

A novel protein identification framework, PILOT_PROTEIN, has been developed to construct a comprehensive list of all unmodified proteins that are present in a living sample. It uses the peptide identification results from the PILOT_SEQUEL algorithm to initially determine all unmodified proteins within the sample. Using a rigorous biclustering approach that groups incorrect peptide sequences with other homologous sequences, the number of false positives reported is minimized. A sequence tag procedure is then incorporated along with the untargeted PTM identification algorithm, PILOT_PTM, to determine a list of all modification types and sites for each protein. The unmodified protein identification algorithm, PILOT_PROTEIN, is compared to the methods SEQUEST, InsPecT, X!Tandem, VEMS, and ProteinProspector using both prepared protein samples and a more complex chromatin digest. The algorithm demonstrates superior protein identification accuracy with a lower false positive rate. All materials are freely available to the scientific community at http://pumpd.princeton.edu.

Novel protein identification methods for biomarker discovery via a proteomic analysis of periodontally healthy and diseased gingival crevicular fluid samples.

AIM: To identify possible novel biomarkers in gingival crevicular fluid (GCF) samples from chronic periodontitis (CP) and periodontally healthy individuals using high-throughput proteomic analysis. MATERIALS AND METHODS: Gingival crevicular fluid samples were collected from 12 CP and 12 periodontally healthy subjects. Samples were trypically digested with trypsin, eluted using high-performance liquid chromatography, and fragmented using tandem mass spectrometry (MS/MS). MS/MS spectra were analysed using PILOT_PROTEIN to identify all unmodified proteins within the samples. RESULTS: Using the database derived from Homo sapiens taxonomy and all bacterial taxonomies, 432 human (120 new) and 30 bacterial proteins were identified. The human proteins, angiotensinogen, clusterin and thymidine phosphorylase were identified as biomarker candidates based on their high-scoring only in samples from periodontal health. Similarly, neutrophil defensin-1, carbonic anhydrase-1 and elongation factor-1 gamma were associated with CP. Candidate bacterial biomarkers include 33 kDa chaperonin, iron uptake protein A2 and phosphoenolpyruvate carboxylase (health-associated) and ribulose biphosphate carboxylase, a probable succinyl-CoA:3-ketoacid-coenzyme A transferase, or DNA-directed RNA polymerase subunit beta (CP-associated). Most of these human and bacterial proteins have not been previously evaluated as biomarkers of periodontal conditions and require further investigation. CONCLUSIONS: The proposed methods for large-scale comprehensive proteomic analysis may lead to the identification of novel biomarkers of periodontal health or disease.

A novel approach for untargeted post-translational modification identification using integer linear optimization and tandem mass spectrometry.

A novel algorithm, PILOT_PTM, has been developed for the untargeted identification of post-translational modifications (PTMs) on a template sequence. The algorithm consists of an analysis of an MS/MS spectrum via an integer linear optimization model to output a rank-ordered list of PTMs that best match the experimental data. Each MS/MS spectrum is analyzed by a preprocessing algorithm to reduce spectral noise and label potential complimentary, offset, isotope, and multiply charged peaks. Postprocessing of the rank-ordered list from the integer linear optimization model will resolve fragment mass errors and will reorder the list of PTMs based on the cross-correlation between the experimental and theoretical MS/MS spectrum. PILOT_PTM is instrument-independent, capable of handling multiple fragmentation technologies, and can address the universe of PTMs for every amino acid on the template sequence. The various features of PILOT_PTM are presented, and it is tested on several modified and unmodified data sets including chemically synthesized phosphopeptides, histone H3-(1-50) polypeptides, histone H3-(1-50) tryptic fragments, and peptides generated from proteins extracted from chromatin-enriched fractions. The data sets consist of spectra derived from fragmentation via collision-induced dissociation, electron transfer dissociation, and electron capture dissociation. The capability of PILOT_PTM is then benchmarked using five state-of-the-art methods, InsPecT, Virtual Expert Mass Spectrometrist (VEMS), Mod(i), Mascot, and X!Tandem. PILOT_PTM demonstrates superior accuracy on both the small and large scale proteome experiments. A protocol is finally developed for the analysis of a complete LC-MS/MS scan using template sequences generated from SEQUEST and is demonstrated on over 270,000 MS/MS spectra collected from a total chromatin digest.

The significance, development and progress of high-throughput combinatorial histone code analysis.

The physiological state of eukaryotic DNA is chromatin. Nucleosomes, which consist of DNA in complex with histones, are the fundamental unit of chromatin. The post-translational modifications (PTMs) of histones play a critical role in the control of gene transcription, epigenetics and other DNA-templated processes. It has been known for several years that these PTMs function in concert to allow for the storage and transduction of highly specific signals through combinations of modifications. This code, the combinatorial histone code, functions much like a bar code or combination lock providing the potential for massive information content. The capacity to directly measure these combinatorial histone codes has mostly been laborious and challenging, thus limiting efforts often to one or two samples. Recently, progress has been made in determining such information quickly, quantitatively and sensitively. Here we review both the historical and recent progress toward routine and rapid combinatorial histone code analysis.

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.

Here we present a novel methodology for the identification of the targeted post-translational modifications present in highly modified proteins using mixed integer linear optimization and electron transfer dissociation (ETD) tandem mass spectrometry. For a given ETD tandem mass spectrum, the rigorous set of modified forms that satisfy the mass of the precursor ion, within some tolerance error, are enumerated by solving a feasibility problem via mixed integer linear optimization. The enumeration of the entire superset of modified forms enables the method to normalize the relative contributions of the individual modification sites. Given the entire set of modified forms, a superposition problem is then formulated using mixed integer linear optimization to determine the relative fractions of the modified forms that are present in the multiplexed ETD tandem mass spectrum. Chromatographic information in the mass and time dimension is utilized to assess the likelihood of the assigned modification states, to average several tandem mass spectra for confident identification of lower level forms, and to infer modification states of partially assigned spectra. The utility of the proposed computational framework is demonstrated on an entire LC-MS/MS ETD experiment corresponding to a mixture of highly modified histone peptides. This new computational method will facilitate the unprecedented LC-MS/MS ETD analysis of many hypermodified proteins and offer novel biological insight into these previously understudied systems.

High throughput characterization of combinatorial histone codes.

We present a novel method utilizing "saltless" pH gradient weak cation exchange-hydrophilic interaction liquid chromatography directly coupled to electron transfer dissociation (ETD) mass spectrometry for the automated on-line high throughput characterization of hypermodified combinatorial histone codes. This technique, performed on a low resolution mass spectrometer, displays an improvement over existing methods with an approximately 100-fold reduction in sample requirements and analysis time. The scheme presented is capable of identifying all of the major combinatorial histone codes present in a sample in a 2-h analysis. The large N-terminal histone peptides are eluted by the pH and organic solvent weak cation exchange-hydrophilic interaction liquid chromatography gradient and directly introduced via nanoelectrospray ionization into a benchtop linear quadrupole ion trap mass spectrometer equipped with ETD. Each polypeptide is sequenced, and the modification sites are identified by ETD fragmentation. The isobaric trimethyl and acetyl modifications are resolved chromatographically and confidently distinguished by the synthesis of mass spectrometric and chromatographic information. We demonstrate the utility of the method by complete characterization of human histone H3.2 and histone H4 from butyrate-treated cells, but it is generally applicable to the analysis of highly modified peptides. We find this methodology very useful for chromatographic separation of isomeric species that cannot be separated well by any other chromatographic means, leading to less complicated tandem mass spectra. The improved separation and increased sensitivity generated novel information about much less abundant forms. In this method demonstration we report over 200 H3.2 forms and 70 H4 forms, including forms not yet detected in human cells, such as the remarkably highly modified histone H3.2 K4me3K9acK14acK18acK23acK27acK36me3. Such detail provided by our proteomics platform will be essential for determining how histone modifications occur and act in combination to propagate the histone code during transcriptional events and could greatly enable sequencing of the histone component of human epigenomes.

Selecting high quality protein structures from diverse conformational ensembles.

Protein structure prediction encompasses two major challenges: 1), the generation of a large ensemble of high resolution structures for a given amino-acid sequence; and 2), the identification of the structure closest to the native structure for a blind prediction. In this article, we address the second challenge, by proposing what is, to our knowledge, a novel iterative traveling-salesman problem-based clustering method to identify the structures of a protein, in a given ensemble, which are closest to the native structure. The method consists of an iterative procedure, which aims at eliminating clusters of structures at each iteration, which are unlikely to be of similar fold to the native, based on a statistical analysis of cluster density and average spherical radius. The method, denoted as ICON, has been tested on four data sets: 1), 1400 proteins with high resolution decoys; 2), medium-to-low resolution decoys from Decoys 'R' Us; 3), medium-to-low resolution decoys from the first-principles approach, ASTRO-FOLD; and 4), selected targets from CASP8. The extensive tests demonstrate that ICON can identify high-quality structures in each ensemble, regardless of the resolution of conformers. In a total of 1454 proteins, with an average of 1051 conformers per protein, the conformers selected by ICON are, on an average, in the top 3.5% of the conformers in the ensemble.

An Integrated Chemical Proteomics Approach for Quantitative Profiling of Intracellular ADP-Ribosylation.

ADP-ribosylation is integral to a diverse range of cellular processes such as DNA repair, chromatin regulation and RNA processing. However, proteome-wide investigation of its cellular functions has been limited due to numerous technical challenges including the complexity of the poly(ADP-ribose) (PAR) chains, low abundance of the modification and lack of sensitive enrichment methods. We herein show that an adenosine analogue with a terminal alkyne functionality at position 2 of the adenine (2-alkyne adenosine or 2YnAd) is suitable for selective enrichment, fluorescence detection and mass spectrometry proteomics analysis of the candidate ADP-ribosylome in mammalian cells. Although similar labelling profiles were observed via fluorescence imaging for 2YnAd and 6YnAd, a previously reported clickable NAD+ precursor, quantitative mass spectrometry analysis of the two probes in MDA-MB-231 breast cancer cells revealed a significant increase in protein coverage of the 2YnAd probe. To facilitate global enrichment of ADP-ribosylated proteins, we developed a dual metabolic labelling approach that involves simultaneous treatment of live cells with both 2YnAd and 6YnAd. By combining this dual metabolic labelling strategy with highly sensitive tandem mass tag (TMT) isobaric mass spectrometry and hierarchical Bayesian analysis, we have quantified the responses of thousands of endogenous proteins to clinical PARP inhibitors Olaparib and Rucaparib.

Biclustering via optimal re-ordering of data matrices in systems biology: rigorous methods and comparative studies.

BACKGROUND: The analysis of large-scale data sets via clustering techniques is utilized in a number of applications. Biclustering in particular has emerged as an important problem in the analysis of gene expression data since genes may only jointly respond over a subset of conditions. Biclustering algorithms also have important applications in sample classification where, for instance, tissue samples can be classified as cancerous or normal. Many of the methods for biclustering, and clustering algorithms in general, utilize simplified models or heuristic strategies for identifying the "best" grouping of elements according to some metric and cluster definition and thus result in suboptimal clusters. RESULTS: In this article, we present a rigorous approach to biclustering, OREO, which is based on the Optimal RE-Ordering of the rows and columns of a data matrix so as to globally minimize the dissimilarity metric. The physical permutations of the rows and columns of the data matrix can be modeled as either a network flow problem or a traveling salesman problem. Cluster boundaries in one dimension are used to partition and re-order the other dimensions of the corresponding submatrices to generate biclusters. The performance of OREO is tested on (a) metabolite concentration data, (b) an image reconstruction matrix, (c) synthetic data with implanted biclusters, and gene expression data for (d) colon cancer data, (e) breast cancer data, as well as (f) yeast segregant data to validate the ability of the proposed method and compare it to existing biclustering and clustering methods. CONCLUSION: We demonstrate that this rigorous global optimization method for biclustering produces clusters with more insightful groupings of similar entities, such as genes or metabolites sharing common functions, than other clustering and biclustering algorithms and can reconstruct underlying fundamental patterns in the data for several distinct sets of data matrices arising in important biological applications.

Descriptor-free molecular discovery in large libraries by adaptive substituent reordering.

Molecular discovery often involves identification of the best functional groups (substituents) on a scaffold. When multiple substitution sites are present, the number of possible substituent combinations can be very large. This article introduces a strategy for efficiently optimizing the substituent combinations by iterative rounds of compound sampling, substituent reordering to produce the most regular property landscape, and property estimation over the landscape. Application of this approach to a large pharmaceutical compound library demonstrates its ability to find active compounds with a threefold reduction in synthetic and assaying effort, even without knowing the molecular identity of any compound.