NETWORK TOPOLOGY IN HUMAN PROTEIN INTERACTION DATA PREDICTS FUNCTIONAL ASSOCIATION

High-throughput assays, such as yeast two-hybrid system, have generated a huge amount of protein-protein interaction (PPI) data in the past decade. This tremendously increases the need for developing reliable methods to systematically and automatically suggest protein functions and relationships between them. With the available PPI data, it is now possible to study the functions and relationships in the context of a large-scale network. To data, several network-based schemes have been provided to effectively annotate protein functions on a large scale. However, due to those inherent noises in high-throughput data generation, new methods and algorithms should be developed to increase the reliability of functional annotations. Previous work in a yeast PPI network (Samanta and Liang, 2003) has shown that the local connection topology, particularly for two proteins sharing an unusually large number of neighbors, can predict functional associations between proteins, and hence suggest their functions. One advantage of the work is that their algorithm is not sensitive to noises (false positives) in high-throughput PPI data. In this study, we improved their prediction scheme by developing a new algorithm and new methods which we applied on a human PPI network to make a genome-wide functional inference. We used the new algorithm to measure and reduce the influence of hub proteins on detecting functionally associated proteins. We used the annotations of the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) as independent and unbiased benchmarks to evaluate our algorithms and methods within the human PPI network. We showed that, compared with the previous work from Samanta and Liang, our algorithm and methods developed in this study improved the overall quality of functional inferences for human proteins. By applying the algorithms to the human PPI network, we obtained 4,233 significant functional associations among 1,754 proteins. Further comparisons of their KEGG and GO annotations allowed us to assign 466 KEGG pathway annotations to 274 proteins and 123 GO annotations to 114 proteins with estimated false discovery rates of <21% for KEGG and <30% for GO. We clustered 1,729 proteins by their functional associations and made pathway analysis to identify several subclusters that are highly enriched in certain signaling pathways. Particularly, we performed a detailed analysis on a subcluster enriched in the transforming growth factor β signaling pathway (P<10-50) which is important in cell proliferation and tumorigenesis. Analysis of another four subclusters also suggested potential new players in six signaling pathways worthy of further experimental investigations. Our study gives clear insight into the common neighbor-based prediction scheme and provides a reliable method for large-scale functional annotations in this post-genomic era.

Upregulation of Reactive Oxygen Species During the Retrovirus Life Cycle and Their Roles in a Mutant of Moloney Murine Leukemia Virus, ts1-Mediated Neurodegeneration

Viral invasion of the central nervous system (CNS) and development of neurological symptoms is a characteristic of many retroviruses. The mechanism by which retrovirus infection causes neurological dysfunction has yet to be fully elucidated. Given the complexity of the retrovirus-mediated neuropathogenesis, studies using small animal models are extremely valuable. Our laboratory has used a mutant moloney murine leukemia retrovirus, ts1-mediated neurodegneration. We hypothesize that astrocytes play an important role in ts1-induced neurodegeneration since they are retroviral reservoirs and supporting cells for neurons. It has been shown that ts1 is able to infect astrocytes in vivo and in vitro. Astrocytes, the dominant cell population in the CNS, extend their end feet to endothelial cells and neuronal synapse to provide neuronal support. Signs of oxidative stress in the ts1-infected CNS have been well-documented from previous studies. After viral infection, retroviral DNA is generated from its RNA genome and integrated into the host genome. In this study, we identified the life cycle of ts1 in the infected astrocytes. During the infection, we observed reactive oxygen species (ROS) upregulations: one at low levels during the early infection phase and another at high levels during the late infection phase. Initially we hypothesized that p53 might play an important role in ts1-mediated astrocytic cell death. Subsequently, we found that p53 is unlikely to be involved in the ts1-mediated astrocytic cell death. Instead, p53 phosphorylation was increased by the early ROS upregulation via ATM, the protein encoded by the ataxia-telangiectasia (A-T) mutated gene. The early upregulation of p53 delayed viral gene expression by suppressing expression of the catalytic subunit of NADPH oxidase (NOX). We further demonstrated that the ROS upregulation induced by NOX activation plays an important role in establishing retroviral genome into the host. Inhibition of NOX decreased viral replication and delayed the onset of pathological symptoms in ts1-infected mice. These observations lead us to conclude that suppression of NOX not only prevents the establishment of the retrovirus but also decreases oxidative stress in the CNS. This study provides us with new perspectives on the retrovirus-host cell interaction and sheds light on retrovirus-induced neurodegeneration as a result of the astrocyte-neuron interaction.

Human complement component C3 -binding proteins of Mycobacterium tuberculosis

Mycobacterium tuberculosis, the causative agent of tuberculosis, is a facultative intracellular pathogen that uses the host mononuclear phagocyte as a niche for survival and replication during infection. Complement component C3 has previously been shown to enhance the binding of M. tuberculosis to mononuclear phagocytes. Using a C3 ligand affinity blot protocol, we identified a 30 kDa C3-binding protein in M. tuberculosis as heparin-binding hemagglutinin (HbhA). HbhA was found to be a hydrophobic protein that localized to the cell membrane/cell wall fraction of M. tuberculosis, and this protein has previously been shown by others to be located on the surface of M. tuberculosis. The C3-binding activity of HbhA was localized to the C-terminus of the protein, which consists of lysine-alanine repeats. Full-length recombinant HbhA coated onto latex beads was shown to mediate the adherence of the beads to murine macrophage-like cells in both a C3-dependent and a C3-independent manner. An in-frame 576 by deletion in the hbhA gene was created in a virulent strain of M. tuberculosis using a PCR technique known as gene splicing by overlap extension (SOEing). Using the ΔhbhA mutant, HbhA was found not to be necessary for growth of M. tuberculosis in laboratory media or in macrophage-like cells, nor is HbhA required for adherence of M. tuberculosis to macrophage-like cells. HbhA is, however, required for infectivity of M. tuberculosis in mice. Mice infected with the ΔhbhA mutant show decreased growth in the lungs, liver, and spleen compared to mice infected with the wild-type strain. Using the ΔhbhA mutant strain, we were able to purify and identify a second 30-kDa C3-binding protein, HupB. These data demonstrate that HbhA is required for the in vivo but not the in vitro survival of M. tuberculosis and that HbhA is not necessary for the adherence of M. tuberculosis to the macrophage-like cells used in these studies. The expression of two proteins that bind human C3 may aid in the efficient binding of M. tuberculosis to complement receptors for uptake into mononuclear cells, or may influence other aspects of the host-parasite interaction. ^

Ligand-signaled upregulation of Enterococcus faecalis ace transcription, a mechanism for modulating host-E. faecalis interaction.

Enterococcus faecalis, the third most frequent cause of bacterial endocarditis, appears to be equipped with diverse surface-associated proteins showing structural-fold similarity to the immunoglobulin-fold family of staphylococcal adhesins. Among the putative E. faecalis surface proteins, the previously characterized adhesin Ace, which shows specific binding to collagen and laminin, was detectable in surface protein preparations only after growth at 46 degrees C, mirroring the finding that adherence was observed in 46 degrees C, but not 37 degrees C, grown E. faecalis cultures. To elucidate the influence of different growth and host parameters on ace expression, we investigated ace expression using E. faecalis OG1RF grown in routine laboratory media (brain heart infusion) and found that ace mRNA levels were low in all growth phases. However, quantitative reverse transcription-PCR showed 18-fold-higher ace mRNA amounts in cells grown in the presence of collagen type IV compared to the controls. Similarly, a marked increase was observed when cells were either grown in the presence of collagen type I or serum but not in the presence of fibrinogen or bovine serum albumin. The production of Ace after growth in the presence of collagen type IV was demonstrated by immunofluorescence microscopy, mirroring the increased ace mRNA levels. Furthermore, increased Ace expression correlated with increased collagen and laminin adhesion. Collagen-induced Ace expression was also seen in three of three other E. faecalis strains of diverse origins tested, and thus it appears to be a common phenomenon. The observation of host matrix signal-induced adherence of E. faecalis may have important implications on our understanding of this opportunistic pathogen.

Host-pathogen interactions of secreted and surface Staphylococcus aureus factors

Staphylococcus aureus is an opportunistic bacterial pathogen that can infect humans and other species. It utilizes an arsenal of virulence factors to cause disease, including secreted and cell wall anchored factors. Secreted toxins attack host cells, and pore-forming toxins destroy target cells by causing cell lysis. S. aureus uses cell-surface adhesins to attach to host molecules thereby facilitating host colonization. The Microbial Surface Components Recognizing Adhesive Matrix Molecules (MSCRAMMs) are a family of cell-wall anchored proteins that target molecules like fibronectin and fibrinogen. The Serine-aspartate repeat (Sdr) proteins are a subset of staphylococcal MSCRAMMs that share similar domain organization. Interestingly, the amino-terminus, is composed of three immunoglobulin-folded subdomains (N1, N2, and N3) that contain ligand-binding activity. Clumping factors A and B (ClfA and ClfB) and SdrG are Sdr proteins that bind to fibrinogen (Fg), a large, plasma glycoprotein that is activated during the clotting cascade to form fibrin. In addition to recognizing fibrinogen, ClfA and ClfB can bind to other host ligands. Analysis of S. aureus strains that cause osteomyelitis led to the discovery of the bone-sialoprotein-binding protein (Bbp), an Sdr protein. Because several MSCRAMMs target more than one molecule, I hypothesized that Bbp may recognize other host proteins. A ligand screen revealed that the recombinant construct BbpN2N3 specifically recognizes human Fg. Surface plasmon resonance was used to determine the affinity of BbpN2N3 for Fg, and a dissociation constant of 540 nM was determined. Binding experiments performed with recombinant Fg chains were used to map the binding of BbpN2N3 to the Fg Aalpha chain. Additionally, Bbp expressed on the surface of Lactococcus lactis and S. aureus Newman bald mediated attachment of these bacteria to Fg Aalpha. To further characterize the interaction between the two proteins, isothermal titration calorimetry and inhibition assays were conducted with synthetic Fg Aalpha peptides. To determine the physiological implications of Bbp binding to Fg, the effect of Bbp on fibrinogen clotting was studied. Results show that Bbp binding to Fg inhibits the formation of fibrin. The consequences of this interaction are currently under investigation. Together, these data demonstrate that human Fg is a novel ligand for Bbp. This study indicates that the MSCRAMM Bbp may aid in staphylococcal attachment by targeting both an extracellular matrix and a blood plasma protein. The implications of these novel findings are discussed.

ADHERENS JUNCTIONS AND THE ACTOMYOSIN NETWORK REGULATE ORGAN GROWTH BY MODULATING HIPPO PATHWAY ACTIVITY IN DROSOPHILA

Adherens junctions (AJs) and basolateral modules are important for the establishment and maintenance of apico-basal polarity. Loss of AJs and basolateral module members lead to tumor formation, as well as poor prognosis for metastasis. Recently, in mammalian studies it has been shown that loss of either AJ or basolateral module members deregulate Yorkie activity, the downstream transcriptional effector of the Hippo pathway. Importantly, it is unclear if AJ and basolateral components act through the same or parallel mechanisms to regulate Yorkie activity. Here, we dissect how loss of AJ and basolateral components affects Hippo signaling in Drosophila. Surprisingly, while scrib knock-down tissue displays increased reporter activity autonomously, α-cat knock-down tissue shows a cell autonomous decrease and a cell non-autonomous increase of Hippo reporter activity. We provided several lines of evidence to show the differential regulation in polarity protein localizations and oncogenic cooperative overgrowth by AJs and basolateral complexes. Finally, we show that Hippo pathway activity is induced in α-cat and scrib double knocked-down tissue. Taken together, our results provide evidence to show that basolateral modules and AJs act in parallel to modulate Hippo pathway activity. Non-muscle myosin II is an actomyosin component that interacts with the actin. Non-muscle myosin II also interacts with lgl, though the function of this interaction is not clear. Our lab demonstrated that modulating F-actin regulates Hippo pathway activity, and lgl also has been described as a Hippo pathway regulator. Therefore we suspect that myosin II is also involved in Hippo pathway regulation. We first characterized non-muscle Myosin II as a novel tumor suppressor gene by affecting Hippo pathway activity. Upstream regulators of Myosin II, members in the Rho signaling pathway, also displayed similar phenotypes as the Myosin II knock-down tissues. Apoptosis is also induced in myosin II knock-down tissues, however, blocking cell death does not affect myosin II knock-down induced Hippo activation. Our data suggested hyperactivating myosin II induced F-actin accumulation so therefore induces Hippo target activation. Unexpectedly, we also observed that reducing F-actin activity induced Hippo target activation in vivo. These controversial data indicated that actomyosin may regulate the Hippo pathway through multiple mechanisms.

Gene-gene interaction and gene-pathway analysis of genome-wide association for schizophrenia

Schizophrenia (SZ) is a complex disorder with high heritability and variable phenotypes that has limited success in finding causal genes associated with the disease development. Pathway-based analysis is an effective approach in investigating the molecular mechanism of susceptible genes associated with complex diseases. The etiology of complex diseases could be a network of genetic factors and within the genes, interaction may occur. In this work we argue that some genes might be of small effect that by itself are neither sufficient nor necessary to cause the disease however, their effect may induce slight changes to the gene expression or affect the protein function, therefore, analyzing the gene-gene interaction mechanism within the disease pathway would play crucial role in dissecting the genetic architecture of complex diseases, making the pathway-based analysis a complementary approach to GWAS technique. ^ In this study, we implemented three novel linkage disequilibrium based statistics, the linear combination, the quadratic, and the decorrelation test statistics, to investigate the interaction between linked and unlinked genes in two independent case-control GWAS datasets for SZ including participants of European (EA) and African (AA) ancestries. The EA population included 1,173 cases and 1,378 controls with 729,454 genotyped SNPs, while the AA population included 219 cases and 288 controls with 845,814 genotyped SNPs. We identified 17,186 interacting gene-sets at significant level in EA dataset, and 12,691 gene-sets in AA dataset using the gene-gene interaction method. We also identified 18,846 genes in EA dataset and 19,431 genes in AA dataset that were in the disease pathways. However, few genes were reported of significant association to SZ. ^ Our research determined the pathways characteristics for schizophrenia through the gene-gene interaction and gene-pathway based approaches. Our findings suggest insightful inferences of our methods in studying the molecular mechanisms of common complex diseases.^

THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.

INTERACTION OF BACILLUS ANTHRACIS EXOSPORIUM PROTEIN BCLA WITH COMPLEMENT FACTOR H AND SPORE PERSISTENCE IN THE LUNG

Anthrax outbreaks in the United States and Europe and its potential use as a bioweapon have made Bacillus anthracis an interest of study. Anthrax infections are caused by the entry of B. anthracis spores into the host via the respiratory system, the gastrointestinal tract, cuts or wounds in the skin, and injection. Among these four forms, inhalational anthrax has the highest lethality rate and persistence of spores in the lungs of animals following pulmonary exposure has been noted for decades. However, details or mechanisms of spore persistence were not known. In this study, we investigated spore persistence in a mouse model. The results suggest that B. anthracis spores have special properties that promote persistence in the lung, and that there may be multiple mechanisms contributing to spore persistence. Moreover, recent discoveries from our laboratory suggest that spores evolved a sophisticated mechanism to interact with the host complement system. The complement system is a crucial part of the host defense mechanism against foreign microorganisms. Knowledge of the specific interactions that occur between the complement system and B. anthracis was limited. Studies performed in our laboratory have suggested that spores of B. anthracis can target specific proteins, such as Factor H (fH) of the complement system. Spores of B. anthracis are enclosed by an exosporium, which consists of a basal layer surrounded by a nap of hair-like filaments. The major structural component of the filaments is called Bacillus collagen-like protein of anthracis (BclA), which comprises a central collagen-like region and a globular C-terminal domain. BclA is the first point of contact with the innate system of an infected host. In this study, we investigated the molecular details of BclA-fH interaction with respect to the specific binding mechanism and the functional significance of this interaction in a murine model of anthrax infection. We hypothesized that the recruitment of fH to the spore surface by BclA limits the extent of complement activation and promotes pathogen survival and persistence in the infected host. Findings from this study are significant to understanding how to treat post-exposure prophylaxis and improve our knowledge of spores with the host immune system.

Network-based analysis of genome-wide scans of natural selection

The genomic era brought by recent advances in the next-generation sequencing technology makes the genome-wide scans of natural selection a reality. Currently, almost all the statistical tests and analytical methods for identifying genes under selection was performed on the individual gene basis. Although these methods have the power of identifying gene subject to strong selection, they have limited power in discovering genes targeted by moderate or weak selection forces, which are crucial for understanding the molecular mechanisms of complex phenotypes and diseases. Recent availability and rapid completeness of many gene network and protein-protein interaction databases accompanying the genomic era open the avenues of exploring the possibility of enhancing the power of discovering genes under natural selection. The aim of the thesis is to explore and develop normal mixture model based methods for leveraging gene network information to enhance the power of natural selection target gene discovery. The results show that the developed statistical method, which combines the posterior log odds of the standard normal mixture model and the Guilt-By-Association score of the gene network in a naïve Bayes framework, has the power to discover moderate/weak selection gene which bridges the genes under strong selection and it helps our understanding the biology under complex diseases and related natural selection phenotypes.^