The cardiac transcription network modulated by Gata4, Mef2a, Nkx2.5, Srf, histone modifications, and microRNAs.

The transcriptome, as the pool of all transcribed elements in a given cell, is regulated by the interaction between different molecular levels, involving epigenetic, transcriptional, and post-transcriptional mechanisms. However, many previous studies investigated each of these levels individually, and little is known about their interdependency. We present a systems biology study integrating mRNA profiles with DNA-binding events of key cardiac transcription factors (Gata4, Mef2a, Nkx2.5, and Srf), activating histone modifications (H3ac, H4ac, H3K4me2, and H3K4me3), and microRNA profiles obtained in wild-type and RNAi-mediated knockdown. Finally, we confirmed conclusions primarily obtained in cardiomyocyte cell culture in a time-course of cardiac maturation in mouse around birth. We provide insights into the combinatorial regulation by cardiac transcription factors and show that they can partially compensate each other's function. Genes regulated by multiple transcription factors are less likely differentially expressed in RNAi knockdown of one respective factor. In addition to the analysis of the individual transcription factors, we found that histone 3 acetylation correlates with Srf- and Gata4-dependent gene expression and is complementarily reduced in cardiac Srf knockdown. Further, we found that altered microRNA expression in Srf knockdown potentially explains up to 45% of indirect mRNA targets. Considering all three levels of regulation, we present an Srf-centered transcription network providing on a single-gene level insights into the regulatory circuits establishing respective mRNA profiles. In summary, we show the combinatorial contribution of four DNA-binding transcription factors in regulating the cardiac transcriptome and provide evidence that histone modifications and microRNAs modulate their functional consequence. This opens a new perspective to understand heart development and the complexity cardiovascular disorders.

SAHA Capture Compound--a novel tool for the profiling of histone deacetylases and the identification of additional vorinostat binders.

Suberoylanilide hydroxamic acid (SAHA) is a potent histone deacetylase (HDAC) inhibitor. Inhibitors of HDACs are used in cancer therapy based on the role HDACs play in transcription by regulating chromatin compaction and non-histone proteins such as transcription factors. Profiling of HDAC expression is of interest in the functional proteomics analysis of cancer. Also, non-HDAC proteins may interact with HDAC inhibitor drugs and contribute to the drug mode of action. We here present a tool for the unbiased chemical proteomic profiling of proteins that specifically interact with SAHA. We designed and synthesized a trifunctional Capture Compound containing SAHA as selectivity and identified HDACs1, 2, 3 and 6, known and predicted HDAC interactors from human-derived HepG2 cell lysate, as well as a set of new potential non-HDAC targets of SAHA. One of these non-HDAC targets, isochorismatase domain-containing protein 2 (ISOC2) is putative hydrolase associated with the negative regulation of the tumor-suppressor p16(INK4a). We demonstrated the direct and dose-dependent interaction of SAHA to the purified recombinant ISOC2 protein. Using SAHA Capture Compound mass spectrometry, we thus identified potential new SAHA target proteins in an entirely unbiased chemical proteomics approach.

Improvement of capture compound mass spectrometry technology (CCMS) for the profiling of human kinases by combination with 2D LC-MS/MS.

An increasingly popular and promising field in functional proteomics is the isolation of proteome subsets based on small molecule-protein interactions. One platform approach in this field are Capture Compounds that contain a small molecule of interest to bind target proteins, a photo-activatable reactivity function to covalently trap bound proteins, and a sorting function to isolate captured protein conjugates from complex biological samples for direct protein identification by liquid chromatography/mass spectrometry (nLC-MS/MS). In this study we used staurosporine as a selectivity group for analysis in HepG2 cells derived from human liver. In the present study, we combined the functional isolation of kinases with different separation workflows of automated split-free nanoflow liquid chromatography prior to mass spectrometric analysis. Two different CCMS setups, CCMS technology combined with 1D LC-MS and 2D LC-MS, were compared regarding the total number of kinase identifications. By extending the chromatographic separation of the tryptic digested captured proteins from 1D LC linear gradients to 2D LC we were able to identify 97 kinases. This result is similar to the 1D LC setup we previously reported but this time 4 times less input material was needed. This makes CCMS of kinases an even more powerful tool for the proteomic profiling of this important protein family.

Comprehensive identification of staurosporine-binding kinases in the hepatocyte cell line HepG2 using Capture Compound Mass Spectrometry (CCMS).

The central role of kinases in cell signaling has set them in the focus of biomedical research. In functional proteomics analyses, large- scale profiling of kinases has become feasible through the use of affinity pulldown beads that carry immobilized kinase inhibitors. As an alternative approach to solid phase beads, Capture Compound Mass Spectrometry (CCMS) enables the functional isolation of protein-classes on the basis of small molecule-protein interactions in solution. Capture Compounds are trifunctional probes: a selectivity function interacts with the native target proteins in equilibrium, upon irradiation a photoactivatable reactivity function forms an irreversible covalent bond to the target proteins, and a sorting function allows the captured proteins to be isolated from a complex protein mixture. We report the design and application of a novel, fully water-soluble Capture Compound that carries the broadband kinase inhibitor staurosporine as selectivity function. We used this Capture Compound to profile the kinome of the human liver-derived cell line HepG2 and identified one hundred kinases. HepG2 cells are a widely used model system for hepatocarcinoma, hepatitis, and for investigation of drug toxicity effects. CCMS experiments in membrane fractions of human placenta are given as example for the applicability to human tissue.

Combinatorial effects of four histone modifications in transcription and differentiation.

Nucleosomes are involved in DNA compaction and transcriptional regulation. Yet it is unclear whether histone modification marks are primary or secondary to transcription and whether they interact to form a histone code. We investigated the relationship between transcription and four histone modifications (H4ac, H3ac, H3K4me2/3) using ChIP-chip and expression microarray readouts from two murine cell lines, one in two differentiation stages. We found that their association with transcript levels strongly depends on the combination of histone modifications. H3K4me2 coincides with elevated expression levels only in combination with acetylation, while H3ac positive association is diminished by co-occurring modifications. During differentiation, upregulated transcripts frequently gain H4ac, while most modification conversions are uncorrelated with expression changes. Our results suggest histone modifications form a code, as their combinatorial composition is associated with distinct readouts. Histones may primarily function as signaling marks for specific effectors rather than being a sufficient driving force for or a consequence of transcription.

Characterization of TBX20 in human hearts and its regulation by TFAP2.

The T-box family of transcription factors has been shown to have major impact on human development and disease. In animal studies Tbx20 is essential for the development of the atrioventricular channel, the outflow tract and valves, suggesting its potential causative role for the development of Tetralogy of Fallot (TOF) in humans. In the presented study, we analyzed TBX20 in cardiac biopsies derived from patients with TOF, ventricular septal defects (VSDs) and normal hearts. Mutation analysis did not reveal any disease causing sequence variation, however, TBX20 is significantly upregulated in tissue samples of patients with TOF, but not VSD. In depth analysis of TBX20 transcripts lead to the identification of two new exons 3' to the known TBX20 message resembling the mouse variant Tbx20a, as well as an extended 5'UTR. Functional analysis of the human TBX20 promoter revealed a 100 bp region that contains strong activating elements. Within this core promoter region we recognized functional binding sites for TFAP2 transcription factors and identified TFAP2 as repressors of the TBX20 gene in vitro and in vivo. Moreover, decreased TFAP2C levels in cardiac biopsies of TOF patients underline the biological significance of the pathway described. In summary, we provide first insights into the regulation of TBX20 and show its potential for human congenital heart diseases.

Ringo--an R/Bioconductor package for analyzing ChIP-chip readouts.

BACKGROUND: Chromatin immunoprecipitation combined with DNA microarrays (ChIP-chip) is a high-throughput assay for DNA-protein-binding or post-translational chromatin/histone modifications. However, the raw microarray intensity readings themselves are not immediately useful to researchers, but require a number of bioinformatic analysis steps. Identified enriched regions need to be bioinformatically annotated and compared to related datasets by statistical methods. RESULTS: We present a free, open-source R package Ringo that facilitates the analysis of ChIP-chip experiments by providing functionality for data import, quality assessment, normalization and visualization of the data, and the detection of ChIP-enriched genomic regions. CONCLUSION: Ringo integrates with other packages of the Bioconductor project, uses common data structures and is accompanied by ample documentation. It facilitates the construction of programmed analysis workflows, offers benefits in scalability, reproducibility and methodical scope of the analyses and opens up a broad selection of follow-up statistical and bioinformatic methods.

Metabolic profiles in heart failure due to non-ischemic cardiomyopathy at rest and under exercise.

AIMS: Identification of metabolic signatures in heart failure (HF) patients and evaluation of their diagnostic potential to discriminate HF patients from healthy controls during baseline and exercise conditions. METHODS: Plasma samples were collected from 22 male HF patients with non-ischemic idiopathic cardiomyopathy and left ventricular systolic dysfunction and 19 healthy controls before (t0), at peak (t1) and 1 h after (t2) symptom-limited cardiopulmonary exercise testing. Two hundred fifty-two metabolites were quantified by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography (LC)-MS/MS-based metabolite profiling. RESULTS: Plasma metabolite profiles clearly differed between HF patients and controls at t0 (P < 0.05). The metabolic signature of HF was characterized by decreased levels of complex lipids and fatty acids, notably phosphatidylcholines, cholesterol, and sphingolipids. Moreover, reduced glutamine and increased glutamate plasma levels, significantly increased purine degradation products, as well as signs of impaired glucose metabolism were observed. The metabolic differences increased strongly according to New York Heart Association functional class and the addition of three metabolites further improved prediction of exercise capacity (Q2 = 0.24 to 0.35). Despite a high number of metabolites changing significantly with exercise (30.2% at t1/t0), the number of significant alterations between HF and controls was almost unchanged at t1 and t2 (30.7 and 29.0% vs. 31.3% at t0) with a similar predictive group separation (Q2 = 0.50 for t0, 0.52 for t1, and 0.56 for t2, respectively). CONCLUSIONS: Our study identified a metabolic signature of non-ischemic HF with prominent changes in complex lipids including phosphatidylcholines, cholesterol, and sphingolipids. The metabolic changes were already evident at rest and largely preserved under exercise.

Proteome-wide identification of staurosporine-binding kinases using capture compound mass spectrometry.

The enormous diversity of kinases and their pivotal role in cell signaling have set kinases in the focus of biomedical research. Profiling the kinome of tissues of different origin is essential for biomarker discovery. In drug research, it is necessary to comprehend the specificity profile of a given kinase inhibitor. Capture Compound Mass Spectrometry (CCMS) (Koster et al., Assay Drug. Dev. Technol. 5:381-390, 2007) addresses the need for a tool to physically isolate and reliably profile the binders of kinase inhibitors directly in biological samples. Capture Compounds™ are trifunctional probes: a selectivity function consisting of the kinase inhibitor interacts reversibly with the native target proteins in equilibrium, a photoactivatable reactivity function forms an irreversible covalent bond to the target protein upon irradiation, and a sorting function allows the captured protein(s) to be isolated and identified by mass spectrometric analysis in an affinity-driven manner. Capture Compounds™ with any kinase inhibitor as selectivity function can be synthesized. We here used staurosporine as the selectivity function because it targets and, therefore, allows profiling a broad range of kinases (Romano and Giordano, Cell Cycle 7:3364-3668, 2008). Furthermore, we give an example of the application of the staurosporine Capture Compound to isolate kinases from human liver-derived HepG2 cells.

Dabigatran and dabigatran ethyl ester: potent inhibitors of ribosyldihydronicotinamide dehydrogenase (NQO2).

Recent studies have revealed that compounds believed to be highly selective frequently address multiple target proteins. We investigated the protein interaction profile of the widely prescribed thrombin inhibitor dabigatran (1), resulting in the identification and subsequent characterization of an additional target enzyme. Our findings are based on an unbiased functional proteomics approach called capture compound mass spectrometry (CCMS) and were confirmed by independent biological assays. 1 was shown to specifically bind ribosyldihydronicotinamide dehydrogenase (NQO2), a detoxification oxidoreductase. Molecular dockings predicted and biological experiments confirmed that dabigatran ethyl ester (2) inhibits NQO2 even more effectively than the parent 1 itself. Our data show that 1 and 2 are inhibitors of NQO2, thereby revealing a possible new aspect in the mode of action of 1. We present a workflow employing chemical proteomics, molecular modeling, and functional assays by which a compound's protein-interaction profile can be determined and used to tune the binding affinity.

Probing small molecule-protein interactions: A new perspective for functional proteomics.

The isolation of proteome subsets on the basis of the interactions of small molecules with proteins is an emerging paradigm in proteomics. Depending on the nature of the small molecule used as a bait, entire protein families can be monitored in biological samples, or new functions can be attributed to previously uncharacterized proteins. With pharmaceutical compounds as baits, drug targets and toxicity-relevant off-targets can be discovered in an unbiased proteomic screen. At the heart of this strategy are synthetic bi- or trifunctional small molecule probes. These probes carry the small molecules of interest as baits (selectivity function), as well as a sorting function for the isolation of small molecule-protein complexes or conjugates from complex protein mixtures. In some designs, a covalent linkage of the bound protein to the probe is established through a separate reactivity function or a combined selectivity/reactivity function. The covalent linkage allows for isolation or detection of probe-protein conjugates also under harsh or denaturing conditions. Ultimately, specifically isolated proteins are commonly identified by mass spectrometry. This review summarizes probe designs, workflows, and published applications of the three dominant approaches in the field, namely affinity pulldown, activity-based protein profiling, and Capture Compound Mass Spectrometry.

Dasatinib, imatinib and staurosporine capture compounds - Complementary tools for the profiling of kinases by Capture Compound Mass Spectrometry (CCMS).

Capture Compound Mass Spectrometry (CCMS) is a platform technology for the functional isolation of subproteomes. Here we report the synthesis of two new kinase Capture Compounds (CCs) based on the tyrosine-kinase specific inhibitors dasatinib and imatinib and compare their interaction profiles to that of our previously reported staurosporine-CCs. CCs are tri-functional molecules: they comprise a sorting function (e.g. the small molecule or drug of interest) which interacts with target proteins, a photo-activatable reactivity function to covalently trap the interacting proteins, and a sorting function to isolate the CC-protein conjugates from complex biological samples for protein identification by liquid chromatography/mass spectrometry (LC-MS/MS). We present data of CCMS experiments from human HepG2 cells and compare the profiles of the kinases isolated with dasatinib, imatinib and staurosporine CC, respectively. Dasatinib and imatinib have a more selective kinase binding profile than staurosporine. Moreover, the new CCs allow isolation and identification of additional kinases, complementing the staurosporine CC. The family of kinase CCs will be a valuable tool for the proteomic profiling of this important protein class. Besides sets of expected kinases we identified additional specific interactors; these off-targets may be of relevance in the view of the pharmacological profile of dasatinib and imatinib.

Capture compound mass spectrometry sheds light on the molecular mechanisms of liver toxicity of two Parkinson drugs.

Capture compound mass spectrometry (CCMS) is a novel technology that helps understand the molecular mechanism of the mode of action of small molecules. The Capture Compounds are trifunctional probes: A selectivity function (the drug) interacts with the proteins in a biological sample, a reactivity function (phenylazide) irreversibly forms a covalent bond, and a sorting function (biotin) allows the captured protein(s) to be isolated for mass spectrometric analysis. Tolcapone and entacapone are potent inhibitors of catechol-O-methyltransferase (COMT) for the treatment of Parkinson's disease. We aimed to understand the molecular basis of the difference of both drugs with respect to side effects. Using Capture Compounds with these drugs as selectivity functions, we were able to unambiguously and reproducibly isolate and identify their known target COMT. Tolcapone Capture Compounds captured five times more proteins than entacapone Capture Compounds. Moreover, tolcapone Capture Compounds isolated mitochondrial and peroxisomal proteins. The major tolcapone-protein interactions occurred with components of the respiratory chain and of the fatty acid beta-oxidation. Previously reported symptoms in tolcapone-treated rats suggested that tolcapone might act as decoupling reagent of the respiratory chain (Haasio et al., 2002b). Our results demonstrate that CCMS is an effective tool for the identification of a drug's potential off targets. It fills a gap in currently used in vitro screens for drug profiling that do not contain all the toxicologically relevant proteins. Thereby, CCMS has the potential to fill a technological need in drug safety assessment and helps reengineer or to reject drugs at an early preclinical stage.

GDP-capture compound--a novel tool for the profiling of GTPases in pro- and eukaryotes by capture compound mass spectrometry (CCMS).

The functional isolation of proteome subsets based on small molecule-protein interactions is an increasingly popular and promising field in functional proteomics. Entire protein families may be profiled on the basis of their common interaction with a metabolite or small molecule inhibitor. This is enabled by novel multifunctional small molecule probes. One platform approach in this field are Capture Compounds that contain a small molecule of interest to bind target proteins, a photo-activatable reactivity function to covalently trap bound proteins, and a sorting function to isolate Capture Compound-protein conjugates from complex biological samples for direct trypsinisation and protein identification by liquid chromatography/mass spectrometry (CCMS). We here present the synthesis and application of a novel GDP-Capture Compound for the functional enrichment of GTPases, a pivotal protein family that exerts key functions in signal transduction. We present data from CCMS experiments on two biological lysates from Escherichia coli and from human-derived Hek293 cells. The GDP-Capture Compound robustly captures a wide range of different GTPases from both systems and will be a valuable tool for the proteomic profiling of this important protein family.

Prediction of cardiac transcription networks based on molecular data and complex clinical phenotypes.

We present an integrative approach combining sophisticated techniques to construct cardiac gene regulatory networks based on correlated gene expression and optimized prediction of transcription factor binding sites. We analyze transcription levels of a comprehensive set of 42 genes in biopsies derived from hearts of a cohort of 190 patients as well as healthy individuals. To precisely describe the variety of heart malformations observed in the patients, we delineate a detailed phenotype ontology that allows description of observed clinical characteristics as well as the definition of informative meta-phenotypes. Based on the expression data obtained by real-time PCR we identify specific disease associated transcription profiles by applying linear models. Furthermore, genes that show highly correlated expression patterns are depicted. By predicting binding sites on promoter settings optimized using a cardiac specific chromatin immunoprecipitation data set, we reveal regulatory dependencies. Several of the found interactions have been previously described in literature, demonstrating that the approach is a versatile tool to predict regulatory networks.

Regulation of muscle development by DPF3, a novel histone acetylation and methylation reader of the BAF chromatin remodeling complex.

Chromatin remodeling and histone modifications facilitate access of transcription factors to DNA by promoting the unwinding and destabilization of histone-DNA interactions. We present DPF3, a new epigenetic key factor for heart and muscle development characterized by a double PHD finger. DPF3 is associated with the BAF chromatin remodeling complex and binds methylated and acetylated lysine residues of histone 3 and 4. Thus, DPF3 may represent the first plant homeodomains that bind acetylated lysines, a feature previously only shown for the bromodomain. During development Dpf3 is expressed in the heart and somites of mouse, chicken, and zebrafish. Morpholino knockdown of dpf3 in zebrafish leads to incomplete cardiac looping and severely reduced ventricular contractility, with disassembled muscular fibers caused by transcriptional deregulation of structural and regulatory proteins. Promoter analysis identified Dpf3 as a novel downstream target of Mef2a. Taken together, DPF3 adds a further layer of complexity to the BAF complex by representing a tissue-specific anchor between histone acetylations as well as methylations and chromatin remodeling. Furthermore, this shows that plant homeodomain proteins play a yet unexplored role in recruiting chromatin remodeling complexes to acetylated histones.