From protein microarray to biology: The discovery of epigenetic regulatory molecules

Chromatin, composed of repeating nucleosome units, is the genetic polymer of life. To aid in DNA compaction and organized storage, the double helix wraps around a core complex of histone proteins to form the nucleosome, and is therefore no longer freely accessible to cellular proteins for the processes of transcription, replication and DNA repair. Over the course of evolution, DNA-based applications have developed routes to access DNA bound up in chromatin, and further, have actually utilized the chromatin structure to create another level of complexity and information storage. The histone molecules that DNA surrounds have free-floating tails that extend out of the nucleosome. These tails are post-translationally modified to create docking sites for the proteins involved in transcription, replication and repair, thus providing one prominent way that specific genomic sequences are accessed and manipulated. Adding another degree of information storage, histone tail-modifications paint the genome in precise manners to influence a state of transcriptional activity or repression, to generate euchromatin, containing gene-dense regions, or heterochromatin, containing repeat sequences and low-density gene regions. The work presented here is the study of histone tail modifications, how they are written and how they are read, divided into two projects. Both begin with protein microarray experiments where we discover the protein domains that can bind modified histone tails, and how multiple tail modifications can influence this binding. Project one then looks deeper into the enzymes that lay down the tail modifications. Specifically, we studied histone-tail arginine methylation by PRMT6. We found that methylation of a specific histone residue by PRMT6, arginine 2 of H3, can antagonize the binding of protein domains to the H3 tail and therefore affect transcription of genes regulated by the H3-tail binding proteins. Project two focuses on a protein we identified to bind modified histone tails, PHF20, and was an endeavor to discover the biological role of this protein. Thus, in total, we are looking at a complete process: (1) histone tail modification by an enzyme (here, PRMT6), (2) how this and other modifications are bound by conserved protein domains, and (3) by using PHF20 as an example, the functional outcome of binding through investigating the biological role of a chromatin reader. ^

Identification of a conserved cluster in the RH domain of GRK critical for activation by GPCRs

One of the most critical aspects of G Protein Coupled Receptors (GPCRs) regulation is their rapid and acute desensitization following agonist stimulation. Phosphorylation of these receptors by GPCR kinases (GRK) is a major mechanism of desensitization. Considerable evidence from studies of rhodopsin kinase and GRK2 suggests there is an allosteric docking site for the receptor distinct from the GRK catalytic site. While the agonist-activated GPCR appears crucial for GRK activation, the molecular details of this interaction remain unclear. Recent studies suggested an important role for the N- and C-termini and domains in the small lobe of the kinase domain in allosteric activation; however, neither the mechanism of action of that site nor the RH domain contributions have been elucidated. To search for the allosteric site, we first indentified evolutionarily conserved sites within the RH and kinase domains presumably deterministic of protein function employing evolutionary trace (ET) methodology and crystal structures of GRK6. Focusing on a conserved cluster centered on helices 3, 9, and 10 in the RH domain, key residues of GRK5 and 6 were targeted for mutagenesis and functional assays. We found that a number of double mutations within helices 3, 9, and 10 and the N-terminus markedly reduced (50–90%) the constitutive phosphorylation of the β-2 Adrenergic Receptor (β2AR) in intact cells and phosphorylation of light-activated rhodopsin (Rho*) in vitro as compared to wild type (WT) GRK5 or 6. Based on these results, we designed peptide mimetics of GRK5 helix 9 both computationally and through chemical modifications with the goal of both confirming the importance of helix 9 and developing a useful inhibitor to disrupt the GPCR-GRK interaction. Several peptides were found to block Rho* phosphorylation by GRK5 including the native helix 9 sequence, Peptide Builder designed-peptide preserving only the key ET residues, and chemically locked helices. Most peptidomimetics showed inhibition of GRK5 activity greater than 80 % with an IC50 of ∼ 30 µM. Alanine scanning of helix 9 has further revealed both essential and non-essential residues for inhibition. Importantly, substitution of Arg 169 by an alanine in the native helix 9-based peptide gave an almost complete inhibition at 30 µM with an IC50 of ∼ 10 µM. In summary we report a previously unrecognized crucial role for the RH domain of GRK5 and 6, and the subsequent identification of a lead peptide inhibitor of protein-protein interaction with potential for specific blockade of GPCR desensitization. ^

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.

Advanced Protein Modeling Method: Benchmarking and Applications in Computer-Aided Drug Discovery

Development of homology modeling methods will remain an area of active research. These methods aim to develop and model increasingly accurate three-dimensional structures of yet uncrystallized therapeutically relevant proteins e.g. Class A G-Protein Coupled Receptors. Incorporating protein flexibility is one way to achieve this goal. Here, I will discuss the enhancement and validation of the ligand-steered modeling, originally developed by Dr. Claudio Cavasotto, via cross modeling of the newly crystallized GPCR structures. This method uses known ligands and known experimental information to optimize relevant protein binding sites by incorporating protein flexibility. The ligand-steered models were able to model, reasonably reproduce binding sites and the co-crystallized native ligand poses of the β2 adrenergic and Adenosine 2A receptors using a single template structure. They also performed better than the choice of template, and crude models in a small scale high-throughput docking experiments and compound selectivity studies. Next, the application of this method to develop high-quality homology models of Cannabinoid Receptor 2, an emerging non-psychotic pain management target, is discussed. These models were validated by their ability to rationalize structure activity relationship data of two, inverse agonist and agonist, series of compounds. The method was also applied to improve the virtual screening performance of the β2 adrenergic crystal structure by optimizing the binding site using β2 specific compounds. These results show the feasibility of optimizing only the pharmacologically relevant protein binding sites and applicability to structure-based drug design projects.

Analysis of VirB4, a membrane-associated ATPase subunit essential for T -complex transport in Agrobacterium tumefaciens

Agrobacterium tumefaciens is a plant pathogen with the unique ability to export oncogenic DNA-protein complexes (T-complexes) to susceptible plant cells and cause crown gall tumors. Delivery of the T-complexes across the bacterial membranes requires eleven VirB proteins and VirD4, which are postulated to form a transmembrane transporter. This thesis examines the subcellular localization and oligomeric structure of the 87-kDa VirB4 protein, which is one of three essential ATPases proposed to energize T-complex transport and/or assembly. Results of subcellular localization studies showed that VirB4 is tightly associated with the cytoplasmic membrane, suggesting that it is a membrane-spanning protein. The membrane topology of VirB4 was determined by using a nested deletion strategy to generate random fusions between virB4 and the periplasmically-active alkaline phosphatase, $\sp\prime phoA$. Analysis of PhoA and complementary $\beta$-galactosidase reporter fusions identified two putative periplasmically-exposed regions in VirB4. A periplasmic exposure of one of these regions was further confirmed by protease susceptibility assays using A. tumefaciens spheroplasts. To gain insight into the structure of the transporter, the topological configurations of other VirB proteins were also examined. Results from hydropathy analyses, subcellular localization, protease susceptibility, and PhoA reporter fusion studies support a model that all of the VirB proteins localize at one or both of the bacterial membranes. Immunoprecipitation and Co$\sp{2+}$ affinity chromatography studies demonstrated that native VirB4 (87-kDa) and a functional N-terminally tagged HIS-VirB4 derivative (89-kDa) interact and that the interaction is independent of other VirB proteins. A $\lambda$ cI repressor fusion assay supplied further evidence for VirB4 dimer formation. A VirB4 dimerization domain was localized to the N-terminal third of the protein, as judged by: (i) transdominance of an allele that codes for this region of VirB4; (ii) co-retention of a His-tagged N-terminal truncation derivative and native VirB4 on Co$\sp{2+}$ affinity columns; and (iii) dimer formation of the N-terminal third of VirB4 fused to the cI repressor protein. Taken together, these findings are consistent with a model that VirB4 is topologically configured as an integral cytoplasmic membrane protein with two periplasmic domains and that VirB4 assembles as homodimers via an N-terminal dimerization domain. Dimer formation is postulated to be essential for stabilization of VirB4 monomers during T-complex transporter assembly. ^

Regulations of SOX9 activity during chondrogenesis

Sox9 is a transcription factor required for chondrocyte differentiation and cartilage formation. In an effort to identify SOX9 interacting protein(s), we screened a chondrocyte cDNA library with a modified yeast two-hybrid method, Son of Sevenless (SOS) recruitment system (SRS). The catalytic subunit of cyclic AMP-dependent protein kinase A (PKA-Cα) and a new long form of c-Maf transcription factor (Lc-Maf) were found to interact specifically with SOX9. We showed here that two PKA phosphorylation consensus sites of SOX9 could be phosphorylated by PKA in vitro as well as in vivo. PKA phosphorylation of SOX9 increases its DNA binding and transcriptional activities on a Col2a1 chondrocyte-specific enhancer. Mutations of these two PKA phosphorylation sites markedly decreased the activation of SOX9 by PKA. ^ To test whether parathyroid hormone-related peptide (PTHrP) signaling results in SOX9 phosphorylation, we generated a phosphospecific antibody that specifically recognizes SOX9 that is phosphorylated at serine 181 (S 181) one of the two consensus PKA phosphorylation sites. Addition of PTHrP to COS7 cells cotransfected with SOX9 and PTH/PTHrP receptor strongly increased phosphorylation of SOX9 at S181; this phosphorylation was blocked by a PKA-specific inhibitor. In similar experiments we showed that PTHrP increased the activity of a SOX9-dependent Col2a1 enhancer. This increase in activity was abolished when a SOX9 mutant was used containing serine-to-alanine substitution in the two consensus PKA phosphorylation sites of SOX9. Using our phosphospecific SOX9 antibody we showed by immunohistochemistry of mouse embryos that Sox9 phosphorylated at S181 was localized almost exclusively in the pre-hypertrophic zone of the growth plate, an area corresponding to the major site of expression of PTH/PTHrP receptor. In contrast, no phosphorylation of Sox9 at S181 was detected in growth plates of PTH/PTHrP receptor null mutant mice. Sox9, regardless of phosphorylation state, was present in all chondrocytes of both genotypes except in hypertrophic chondrocytes. Thus, Sox9 is a target of PTHrP signaling and the PTHrP-dependent phosphorylation of SOX9 enhances its transcriptional activity. ^ In order to investigate the in vivo function of Sox9 phosphorylation by PKA, we are generating a mouse model of mutant Sox9 harboring point mutations in two PKA phosphorylation sites. Preliminary results indicated that heterozygous mice containing half amount of mutant Sox9 that can not be phosphorylated by PKA have normal skeletal phenotype and homozygous mice are being generated. ^ Lc-Maf encodes an extra ten amino acids at the carboxyl terminus of c-Maf and contains a completely different 3′ untranslated region. The interaction between SOX9 and Lc-Maf was further confirmed by co-immunoprecipitation and GST-pull down assays, which mapped the interacting domains of SOX9 to HMG DNA binding domain and that of Lc-Maf to basic leusine zipper motif. In situ hybridizations showed that RNA of Lc-Maf coexpressed with those of Sox9 and Col2a1 in areas of mesenchymal condensation during the early stages of mouse embryo development. A DNA binding site of Lc-Maf was identified at the 5′ part of a 48-bp Col2a1 enhancer element near the HMG binding site of SOX9. Lc-Maf and SOX9 synergistically activated a luciferase reporter plasmid containing a Col2al enhancer and increased the transcription of endogenous Col2a1 gene. In summary, Lc-Maf is the first identified SOX9-interating protein during chondrogenesis and may be an important activator of Col2a1 gene. ^

Signaling pathways in the transcriptional and post-translational regulation of the human glutathione S -transferase P1 gene

The human glutathione S-transferase P1 (GSTP1) protein is an endogenous inhibitor of c-jun N-terminal kinases (JNKs) and an important phase II detoxification enzyme. ^ Recent identification of a cAMP response element (CRE) in the 5 ′-region of the human GSTP1 gene and several putative phosphorylation sites for the Ser/Thr protein kinases, including, cAMP-dependent protein kinases (PKAs), protein kinases C (PKCs), and JNKs in the GSTP1 protein raised the possibility that signaling pathways may play an important role in the transcriptional and post-translational regulation of GSTP1 gene. This study examined (a) whether the signaling pathway mediated by CAMP, via the GSTP1 CRE, is involved in the transcriptional regulation of the GSTP1 gene, (b) whether signaling pathways mediated by the Ser/Thr protein kinases (PKAs, PKCs, and JNKs) induce post-translational modification, viz. phosphorylation of the GSTP1 protein, and (c) whether such phosphorylation of the GSTP1 protein alters its functions in metabolism and in JNK signaling. ^ The first major finding in this study is the establishment of the human GSTP1 gene as a novel CAMP responsive gene in which transcription is activated via an interaction between PKA activated CRE binding protein-1 (CREB-1) and the CRE in the 5′-regulatory region. ^ The second major finding in this study is the observation that the GSTP1 protein undergoes phosphorylation and functionally activated by second messenger-activated protein kinases, PKA and PKC, in tumor cells with activated signaling pathways. Following phosphorylation by PKA or PKC, the catalytic activity of the GSTP1 protein was significantly enhanced, as indicated by a decrease in its Km (2- to 3.6-fold) and an increase in Kcat/ Km (1.6- to 2.5-fold) for glutathione. Given the frequent over-expression of GSTP1 and the aberrant PKA/PKC signaling cascade observed in tumors, these findings suggest that phosphorylation of GSTP1 may contribute to the malignant progression and drug-resistant phenotype of these tumors. ^ The third major finding in this study is that the GSTP1 protein, an inhibitor of JNKs, undergoes significant phosphorylation in tumor cells with activated JNK signaling pathway and in those under oxidative stress. Following phosphorylation by JNK, the ability of GSTP1 to inhibit JNK downstream function, i.e. c-jun phosphorylation, was significantly enhanced, suggesting a feedback mechanism of regulation of JNK-mediated cellular signaling. (Abstract shortened by UMI.) ^