Thesis (Ph.D.)--Boston University. PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you. / Understanding the mechanisms and driving forces behind molecular evolution is the defining challenge ofcomputational biology. However, a comprehensive, quantitative theory ofmolecular evolution remains elusive. We evaluate a new graph-theoretic treatment ofthis problem. We start by defining a multi-dimensional protein domain universe graph (PDUG). The nodes in this graph are the atomic units of evolution - structures ofrecurring domains and sequences that fold into those structures. Each ofthe three dimensions in PDUG-structure, function and phylogeny represents a potential constraint from evolutionary pressure. We go on to characterize graph-theoretic properties such as phase transitions, power-law degree distributions, and correlations between the three dimensions. We compare the observed properties with those expected from random graphs. The comparison enables us to identify the likely contours of sets of co-evolved proteins. We further our understanding by assessing several computationally tractable models of evolution that recapitulate some fundamental characteristics of PDUG. We go on to define fitness characteristics derived from simple physical properties of structure and function that serve to clarify the uneven relationship between fold and sequence space topology. However, we also find that evolutionary history plays a crucial role since structural fitness is only the potential for sequence entropy, while variable time of evolutionary search determines the fulfillment of that potential. Armed with our new understanding of protein fitness we describe its progression over time. We establish that eukaryotic domains enjoy a faster exploration of sequence and function space than prokaryotic ones. We further note that biological phenomena such as thermophilic adaptation and duplication success may be explained in light of our newly found understanding ofprotein fitness. Finally, we employ the newly developed PDUG paradigm to quantify the structure-function relationship. We show through modeling of divergent evolution that functions coalesce non-randomly as sfructural clusters grow. We fmd that the widely held hierarchical description of structure space has theoretical underpinnings in the natural clustering of the PDUG. We finish by calculating the theoretical lower limit of uncertainty inherent in structure function correlation of protein domains. / 2031-01-02

For large regions of many proteins, and even entire proteins, no homology to known domains or proteins can be detected. These sequences are often referred to as orphans. Surprisingly, it has been reported that the large number of orphans is sustained in spite of a rapid increase of available genomic sequences. However, it is believed that de novo creation of coding sequences is rare in comparison to mechanisms such as domain shuffling and gene duplication; hence, most sequences should have homologs in other genomes. To investigate this, the sequences of 19 complete fungi genomes were compared. By using the phylogenetic relationship between these genomes, we could identify potentially de novo created orphans in Saccharomyces cerevisiae. We found that only a small fraction, &lt;2%, of the S. cerevisiae proteome is orphan, which confirms that de novo creation of coding sequences is indeed rare. Furthermore, we found it necessary to compare the most closely related species to distinguish between de novo created sequences and rapidly evolving sequences where homologs are present but cannot be detected. Next, the orphan proteins (OPs) and orphan domains (ODs) were characterized. First, it was observed that both OPs and ODs are short. In addition, at least some of the OPs have been shown to be functional in experimental assays, showing that they are not pseudogenes. Furthermore, in contrast to what has been reported before and what is seen for older orphans, S. cerevisiae specific ODs and proteins are not more disordered than other proteins. This might indicate that many of the older, and earlier classified, orphans indeed are fast-evolving sequences. Finally, &gt;90% of the detected ODs are located at the protein termini, which suggests that these orphans could have been created by mutations that have affected the start or stop codons. / <p>authorCount :2</p>

Scaffold proteins facilitate many aspects of intracellular signaling. These proteins can regulate two or more proteins in the same pathway, or coordinate signaling from multiple pathways. Scaffold proteins are therefore key control points for the flux of signaling and play essential roles in biological systems. There are four possible mechanisms by which scaffold proteins achieve activation and propagate signaling: 1) rigid protein binding between two or more proteins to co-localize binding partners, 2) ligand-induced activation such as may result from a conformational change, 3) disorder-to-order transition where the scaffold protein folds as a result of a protein-protein interaction, and 4) dynamic processes such as phosphorylation. The scaffold protein NF-κB essential modulator (NEMO) functions via ligand-induced activation and serves as the key control point for canonical NF-κB signaling. The work described in this thesis investigates the role of a previously uncharacterized domain within NEMO that is required for function, which we term the Intervening Domain (IVD). Bioinformatic analysis reveals a high level of sequence conservation across species within this domain. Conformational changes following ligand binding are observed for NEMO and these changes require conserved sequences in the IVD. Additionally, a functional IVD is shown to increase the binding affinity of NEMO for IKKβ, enhance the thermal stability of NEMO, and is required to propagate NF-κB signaling in cells. A fluorescence-based assay is also developed to characterize the formation of a complex composed of NEMO, a zinc ion, and IκBα. A separate fluorescence-based assay is developed to measure IKK activity and is used to determine that NEMO alone or in the presence of linear tetraubiquitin does not enhance the rate of IKKβ phosphorylation of an IκBα-derived peptide. Furthermore, a number of organic small molecules and macrocycles are screened against the NEMO-IKKβ interaction. One small molecule was validated as an inhibitor and its biophysical properties and inhibition kinetics are described in this thesis. These analyses represent the first characterization of a highly conserved domain required for the function of the key control point in NF-κB signaling. The IVD domain of NEMO could be targeted for development of an allosteric effector for therapeutic discovery.

Protein-protein interactions are of vital importance to the cell as they mediate the assembly of protein complexes that carry out diverse biological functions. Many proteins involved in cellular signaling are built by the combinatorial use of peptide recognition modules (PRMs), which are small protein domains that bind to their cognate ligands by recognizing short linear peptide motifs. Thousands of PRMs are found in nature, requiring improved methods to better elucidate their molecular determinants of binding and to allow accurate mapping of their interaction networks. In this thesis, I describe the development and application of phage-displayed peptide libraries to map the binding specificities of two common PRMs. First, I generated specificity profiles for 82 C. elegans and human PDZ domains that could be organized into a specificity map. The map revealed that PDZ domains have far greater substrate sequence specificity than previously believed, providing significant insights into the relationships between PDZ structure and specificity, and allowing specificity prediction for uncharacterized domains. My results were used to predict both endogenous and pathogenic PDZ interactions. This analysis revealed that viruses have evolved ligands that specifically mimic PDZ domains to subvert host cell immunity. Second, I analyzed the binding specificity for the SH3 domain family in S. cerevisae. I found that, like PDZ domains, SH3 domains have binding specificities that are more detailed than the conventional classification system. The phage-derived specificity profiles were combined with data from oriented peptide and yeast two-hybrid screening to generate a highly accurate SH3 domain interaction network. Given the prominent role of SH3 domains in endocytosis, the SH3 domain interaction data was used to predict the dynamic localization of several uncharacterized endocytosis proteins, which was subsequently confirmed by cell-based assays. The application of the techniques described here to other PRM families will significantly improve protein interaction maps for signaling pathways, which will illuminate our understanding of the cell circuitry, allow the use of PRMs as general affinity reagent and detection tools, and guide the development of small molecule inhibitors that mimic their peptide ligands for therapeutic intervention.

Protein-protein interactions are of vital importance to the cell as they mediate the assembly of protein complexes that carry out diverse biological functions. Many proteins involved in cellular signaling are built by the combinatorial use of peptide recognition modules (PRMs), which are small protein domains that bind to their cognate ligands by recognizing short linear peptide motifs. Thousands of PRMs are found in nature, requiring improved methods to better elucidate their molecular determinants of binding and to allow accurate mapping of their interaction networks. In this thesis, I describe the development and application of phage-displayed peptide libraries to map the binding specificities of two common PRMs. First, I generated specificity profiles for 82 C. elegans and human PDZ domains that could be organized into a specificity map. The map revealed that PDZ domains have far greater substrate sequence specificity than previously believed, providing significant insights into the relationships between PDZ structure and specificity, and allowing specificity prediction for uncharacterized domains. My results were used to predict both endogenous and pathogenic PDZ interactions. This analysis revealed that viruses have evolved ligands that specifically mimic PDZ domains to subvert host cell immunity. Second, I analyzed the binding specificity for the SH3 domain family in S. cerevisae. I found that, like PDZ domains, SH3 domains have binding specificities that are more detailed than the conventional classification system. The phage-derived specificity profiles were combined with data from oriented peptide and yeast two-hybrid screening to generate a highly accurate SH3 domain interaction network. Given the prominent role of SH3 domains in endocytosis, the SH3 domain interaction data was used to predict the dynamic localization of several uncharacterized endocytosis proteins, which was subsequently confirmed by cell-based assays. The application of the techniques described here to other PRM families will significantly improve protein interaction maps for signaling pathways, which will illuminate our understanding of the cell circuitry, allow the use of PRMs as general affinity reagent and detection tools, and guide the development of small molecule inhibitors that mimic their peptide ligands for therapeutic intervention.

High-throughput genome sequencing and sequence analysis technologies have created the need for automated annotation and analysis of large sets of genes. The Gene Ontology (GO) provides a common controlled vocabulary for describing gene function. However, the process for annotating proteins with GO terms is usually through a tedious manual curation process by trained professional annotators. With the wealth of genomic data that are now available, there is a need for accurate auto- mated annotation methods. The overall objective of my research is to improve our ability to automatically an- notate proteins with GO terms. The first method, Automatic Annotation of Protein Functional Class (AAPFC), employs protein functional domains as features and learns independent Support Vector Machine classifiers for each GO term. This approach relies only on protein functional domains as features, and demonstrates that statistical pattern recognition can outperform expert curated mapping of protein functional domain features to protein functions. The second method Predict of Gene Ontology (PoGO) describes a meta-classification method that integrates multiple heterogeneous data sources. This method leads to improved performance than the protein domain method can achieve alone. Apart from these two methods, several systems have been developed that employ pattern recognition to assign gene function using a variety of features, such as the sequence similarity, presence of protein functional domains and gene expression patterns. Most of these approaches have not considered the hierarchical relationships among the terms in the form of a directed acyclic graph (DAG). The DAG represents the functional relationships between the GO terms, thus it should be an important component of an automated annotation system. I describe a Bayesian network used as a multi-layered classifier that incorporates the relationships among GO terms found in the GO DAG. I also describe an inference algorithm for quickly assigning GO terms to unlabeled proteins. A comparative analysis of the method to other previously described annotation systems shows that the method provides improved annotation accuracy when the performance of individual GO terms are compared. More importantly, this method enables the classification of significantly more GO terms to more proteins than was previously possible.

Recently, there has been much interest in the resilience of complex networks to random failures and intentional attacks. The study of the network robustness is particularly important by several occasions. In one hand a higher degree of robustness to errors and attacks may be desired for maintaining the information flow in communication networks under attacks. On the other hand planning a very limited attack aimed at fragmenting a network by removal of minimum number of the most important nodes might have significant usage in drug design. Many real world networks were found to display scale free topology including WWW, the internet, social networks or regulatory gene and protein networks. In the recent studies it was shown that while these networks have a surprising error tolerance, their scale-free topology makes them fragile under intentional attack, leaving the scientists a challenge on how to improve the networks robustness against attacks. In this thesis, we studied the protein domain co-occurrence network of yeast which displays scale free topology generated with data from Biomart which links to Pfam database. Several networks obtained from protein domain co-occurrence network having exactly the same connectivity distribution were compared under attacks to investigate the assumption that the different networks with the same connectivity distribution do not need to have the same attack tolerances. In addition to this, we considered that the networks with the same connectivity distribution have higher attack tolerance as we organize the same resources in a better way. Then, we checked for the variations of attack tolerance of the networks with the same connectiviy distributions. Furthermore, we investigated whether there is an evolutionary mechanism for having networks with higher or lower attack tolerances for the same connectivity distribution. As a result of these investigations, the different networks with the same connectivity distribution do not have the same attack tolerances under attack. In addition to this, it was observed that the networks with the same connectivity distribution have higher attack tolerances as organizing the same resources in a better way which implies that there is an evolutionary mechanism for having networks with higher attack tolerance for the same connectivity distribution.

High quality reagents are preconditions for high performance protein analyses. But despite progress in some techniques, e.g. mass spectrometry, there is still a lack of affinity-based detection techniques with enhanced precision, specificity, and sensitivity. Building on the concept of multiple affinity recognition reactions and signal amplification, a proximity ligation assay (PLA) was developed as a molecular tool for analyzing proteins and their post-translational modification and interactions. PLA enhanced the analysis of protein expression levels and post-translational modifications in western blotting (Paper I), which had elevated sensitivity and specificity, and an ability to investigate protein phosphorylation. A general and straightforward method was established for the functionalization of affinity reagents through adding DNA strands to protein domains for protein analysis in medicine (Paper II). A method for protein domain-mediated conjugation was developed to simplify the use of recombinant affinity reagents, such as designed ankyrin repeat protein (DARPin), in DNA-mediated protein analyses. Alzheimer’s disease (AD) is characterized by progressive cognitive decline and memory impairment, and amyloid-beta plaques and neurofibrillary tangles (NFT) in the brain are clinical hallmarks of the disease. In order to understand the mechanisms underlying the formation of NFT, in situ PLA was used to explore the role of microtubule affinity related kinase 2 (MARK2) in phosphorylating tau protein during the pathological progress of AD (Paper III). The analyses of roles of MARK proteins 1-4 in phosphorylating tau protein in cells and in post-mortem human brains were performed in Paper IV. The focus of this thesis was the study of post-translational modifications and interactions of proteins in medicine. Procedures for high performance protein analysis in western blotting via proximity ligation were developed, and a functionalization method for recombinant affinity reagents in DNA-mediated protein analysis was established. These and other techniques were used to investigate the roles of tau-phosphorylating MARK family proteins in AD.

Signal transduction pathways allow organisms to sense and respond appropriately to a complex bouquet of environmental cues. The molecular determinants of specificity are constrained by the demands of signaling fidelity, yet flexible enough to allow pathway remodeling to meet novel environmental challenges. A detailed picture of how these forces shape bacterial two-component signaling systems has emerged over the last decade. However, the tension between constraint and flexibility in more complex architectures has not been well-studied. In this thesis, I combine comparative genomics and in vitro phosphotransfer experiments to investigate pathway remodeling using the Firmicutes sporulation initiation (Spo0) pathway as a model. The present-day Spo0 pathways in Bacilli and Clostridia share common ancestry, but possess different architectures. In Clostridia, a sensor kinase phosphorylates Spo0A, the master regulator of the sporulation, directly. In Bacilli, Spo0 is phosphorylated/activated indirectly via a four-protein phosphorelay. The presence in sister lineages of signaling pathways that activate the same response regulator and control analogous phenotypes, yet possess with different architectures, suggests a common ancestral pathway that evolved through interaction remodeling. The prevailing theory is that the ancestral pathway was a simpler, direct phosphorylation architecture; the more complex phosphorelay emerged within the Bacillar lineage. In contrast to this prevailing view, my analysis of 84 representative genomes supports a novel hypothesis for the evolution of Spo0 architectures, wherein the two protein, direct phosphorylation architecture is a derived state, which arose from an ancestral Spo0 phosphorelay. The combination of my bioinformatic analysis and the first experimental characterization of a Clostridial phosphorelay provide evidence for the presence of functional phosphorelays in both classes Bacilli and Clostridia. Further, a cross-species complementation assay between phosphorelays from each class suggests that interaction specificity has been conserved since the divergence of this phylum, 2.7 BYA. My results reveal a patchy phylogenetic distribution of both Spo0 pathway architectures, consistent with repeated remodeling events, in which a phosphorelay was replaced with a two protein, direct phosphorylation pathway. This remodeling likely occurred via acquisition of a sensor kinase with direct specificity for Spo0A. Further, my analysis suggests that the unusual architectures of the Spo0 pathway and its striking tendency to gain and lose interactions may be due to the juxtaposition of three key properties: the maintenance of interaction specificity through molecular recognition; the ecological role of endosporulation; and the degeneracy of interaction space that permits the ongoing recruitment of kinases to recognize novel environmental signals.

Amoebozoa is the eukaryotic supergroup sister to Obazoa, the lineage that contains the animals (including us humans) and Fungi. Amoebozoa is extraordinarily diverse, encompassing important model organisms and significant pathogens. Although amoebozoans are integral to global nutrient cycles and present in nearly all environments, they remain vastly understudied. Here we have isolated a naked eukaryotic amoeba with filose subpseudopodia, and a simple life cycle consisting of a trophic amoeba and a cyst stage. Using a wholistic approach including light, electron, fluorescence microscopy and SSU rDNA, we find that this amoeboid organism fails to match any previously described eukaryote genus. Our isolate amoebae are most similar to some variosean amoebae which also possess acutely pointed filose subpseudopodia. Maximum likelihood and Bayesian tree of the SSU-rDNA gene places our isolate in Variosea of Amoebozoa as a novel lineage with high statistical support closely related to the highly diverse protosteloid amoebae Protostelium. This novel variosean is herein named “Hodorica filosa” n. g. n. sp. We present a robust phylogeny of Amoebozoa based on a broad representative set of taxa in a phylogenomic framework (325 genes). By sampling 61 taxa using culture-based and single-cell transcriptomics, our analyses show two major clades of Amoebozoa, Discosea and Tevosa. Overall, the main macroevolutionary patterns in Amoebozoa appear to result from the parallel losses of homologous characters of a multiphase life cycle that included flagella, sex, and sporocarps rather than independent acquisition of convergent features Integrins are transmembrane receptors that activate signal transduction pathways upon extracellular matrix binding. The Integrin Mediated Adhesion Complex (IMAC), mediates various cell physiological processes and are key elements that are associated animal multicellularity. The IMAC was thought to be specific to animals. Over the last decade however, the IMAC complexes were discovered throughout Obazoa. We show the presence of an ancestral complex of integrin adhesion proteins that predate the evolution of the Amoebozoa. Co-option of an ancient protein complex was key to the emergence of animal multicellularity. The role of the IMAC in a unicellular context is unknown but must also play a critical role for at least some unicellular organisms.