The increased availability of data in biological databases provides many opportunities for understanding biological processes through these data. As recent attention has shifted from sequence analysis to higher-level analysis of genes across multiple genomes, there is a need to develop efficient algorithms for these large-scale applications that can help us understand the functions of genes. The overall objective of my research was to develop improved methods which can automatically assign groups of functionally related genes in large-scale data sets by applying new gene clustering algorithms. Proposed gene clustering algorithms that can help us understand gene function and genome evolution include new algorithms for protein family classification, a window-based strategy for gene clustering on chromosomes, and an exhaustive strategy that allows all clusters of small size to be enumerated. I investigate the problems of gene clustering in multiple genomes, and define gene clustering problems using mathematical methodology and solve the problems by developing efficient and effective algorithms. For protein family classification, I developed two supervised classification algorithms that can assign proteins to existing protein families in public databases and, by taking into account similarities between the unclassified proteins, allows for progressive construction of new families from proteins that cannot be assigned. This approach is useful for rapid assignment of protein sequences from genome sequencing projects to protein families. A comparative analysis of the method to other previously developed methods shows that the algorithm has a higher accuracy rate and lower mis-classification rate when compared to algorithms that are based on the use of multiple sequence alignments and hidden Markov models. The proposed algorithm performs well even on families with very few proteins and on families with low sequence similarity. Apart from the analysis of individual sequences, identifying genomic regions that descended from a common ancestor helps us study gene function and genome evolution. In distantly related genomes, clusters of homologous gene pairs serve as evidence used in function prediction, operon detection, etc. Thus, reliable identification of gene clusters is critical to functional annotation and analysis of genes. I developed an efficient gene clustering algorithm that can be applied on hundreds of genomes at the same time. This approach allows for large-scale study of evolutionary relationships of gene clusters and study of operon formation and destruction. By placing a stricter limit on the maximum cluster size, I developed another algorithm that uses a different formulation based on constraining the overall size of a cluster and statistical estimates that allow direct comparisons of clusters of different size. A comparative analysis of proposed algorithms shows that more biological insight can be obtained by analyzing gene clusters across hundreds of genomes, which can help us understand operon occurrences, gene orientations and gene rearrangements.

Stress activated protein kinase (SAPK) interacting protein 1 (Sin1) is a member of a recently characterized gene family, conserved from yeast to humans. The gene copy number is strictly conserved (one Sin1 gene per genome), and the protein may be expressed ubiquitously in mammalian tissues. The Sin1 family has been implicated in several different signal transduction pathways. Originally identified as a partial cDNA and candidate Ras inhibitor, recent functional studies have revealed interactions with an interferon (IFN) receptor subunit (IFNAR2), and the SAPK JNK. Interactions have also been described between the yeast orthologues and the phosphatidylinositol kinase TOR2. Collectively, these data suggest that Sin1 has an important cellular role, and this study has investigated possible functions for this protein. As human Sin1 proteins have no paralogues within the genome, secondary structure homology was used to identify major domains within the protein. Four major domains within human Sin1 were deduced: an N-terminal domain containing a functional nuclear localization signal, a functional nuclear export signal, and a coiledcoil region; the conserved region in the middle that is likely to be a ubiquitin-like β-grasp protein binding domain; a Ras binding domain; and a pleckstrin homology-like domain that targets Sin1 to the plasma membrane and lipid rafts in vivo. Full and partial length EGFP constructs were used to examine the localization of human Sin1, and several isoforms derived from alternative splicing. All isoforms localized to the nucleus and nucleolus. Beyond this, Sin1α and Sin1ϒ had cytoplasmic staining, while Sin1 and Sin1β were also found at the plasma membrane and lipid rafts. Both the N-terminal domain and the conserved region in the middle were found to contribute to nuclear localization. Comparative genomic analysis between human, mouse, rat, dog, and chicken Sin1 genes revealed a number of conserved intronic regions, and the putative functions of these were predicted. Additionally, a putative promoter module within a CpG island and encompassing the transcription start site was predicted in all species. The human CpG island was found to have promoter activity in HEK293 cells. Using bioinformatics, genes that may be co-regulated with Sin1 were identified. These genes contained the Sin1 promoter module, and were found to co-express in large scale gene expression studies. Most of these genes were directly involved in the cellular response to pathogen infection, suggesting a conserved role for Sin1 in this pathway. Key biochemical functions of the Sin1 proteins were also identified, including the ability of Sin1 proteins to form dimers, and the ability of over-expressed Sin1 to induce apoptosis (mediated through the conserved region in the middle). Additionally, endogenous Sin1 protein levels were found to change following serum deprivation and hypoosmotic stress. Together, these studies have provided significant insight into the cellular role of Sin1, suggesting a role in inducing apoptosis as part of the IFN response to viral infection. The biological significance of the Sin1 proteins is discussed in the context of their predicted functions and the evolution of the protein family.

Understanding how protein sequence, structure and function coevolve is at the core of functional genome annotation and protein engineering. The fundamental problem is to determine whether sequence variation contributes to functional differences or if it is a consequence of evolutionary divergence that is unrelated to functional specificity. To address this problem, we cannot merely analyze sequence variation between homologous proteins that have different functions. For comparison, we need to understand the factors that determine sequence variation in proteins that have the same function, such as a set of orthologous enzymes. Here, we address this problem by analyzing the evolution of functionally important residues in the o-succinylbenzoate synthase (OSBS) family. The OSBS family consists of several hundred enzymes that catalyze a step in menaquinone (Vit. K2) synthesis. Based on phylogeny, the OSBS family can be divided into eight major subfamilies. We assayed wild-type OSBS enzyme activities. The results show that the enzymes from γ-Proteobacteria subfamily 1 and Bacteroidetes have relatively low values, the enzyme from Cyanobacteria subfamily 1 is intermediate, and the values for the proteins from the Actinobacteria and Firmicutes subfamilies are relatively high. We are using computational and experimental methods to identify functionally important amino acids in each subfamily. Our data suggest that each subfamily has a different set of functionally important residues, even though the enzymes catalyze the same reaction. These differences may have accumulated because different mutations were required in each subfamily to compensate for deleterious mutations or to adapt to changing environments. We assessed the roles of these amino acids in enzyme structure and function. Our method achieved 70% successful rate to identify positions that play important roles in one family but not another. The residues P119 and A329 play important role in D. psychrophila but not in T.fusca OSBS. We also observed two class switch mutations in T.fusca, P11 and P22. The mutations at these two position have a similar kinetic parameters as wild-type D. psychrophila OSBS.

XB130 is a relatively unstudied novel signal adaptor protein. In the first phase of this study, an in silico search for proteins related to XB130 was conducted. Two other proteins (AFAP and AFAP1L1) were found to have a significant similarity to XB130 and were compared in detail. After an analysis of these three proteins, it was proposed that they are members of a novel protein family, termed the “AFAP family of signal adaptor proteins”. XB130 has previously been found to regulate cell cycle progression, death, and migration in lung epithelial cells. It was therefore hypothesized that XB130 is protective in acute lung injury (ALI) and important for facilitating repair after injury. XB130 was found to be differentially regulated in ALI depending on the initial insult. Engineering XB130 transgenic mice to further characterize the role of XB130 in lung injury/regeneration revealed that this protein could be essential for early embryo development.

XB130 is a relatively unstudied novel signal adaptor protein. In the first phase of this study, an in silico search for proteins related to XB130 was conducted. Two other proteins (AFAP and AFAP1L1) were found to have a significant similarity to XB130 and were compared in detail. After an analysis of these three proteins, it was proposed that they are members of a novel protein family, termed the “AFAP family of signal adaptor proteins”. XB130 has previously been found to regulate cell cycle progression, death, and migration in lung epithelial cells. It was therefore hypothesized that XB130 is protective in acute lung injury (ALI) and important for facilitating repair after injury. XB130 was found to be differentially regulated in ALI depending on the initial insult. Engineering XB130 transgenic mice to further characterize the role of XB130 in lung injury/regeneration revealed that this protein could be essential for early embryo development.

Abstract Analysis of the primary structure of DNA polymerase ε B subunit defined similarities to B subunits of eukaryotic DNA polymerases α, δ and ε as well as the small subunits of DNA polymerase DI of Euryarchaeota. Multiple sequence alignment of these proteins revealed the presence of 12 conserved motifs and defined a novel protein superfamily. The members of the B subunit family share a common domain architecture, suggesting a similar fold, and arguing for a conserved function among these proteins. The contribution of human DNA polymerase ε to nuclear DNA replication was studied using the antibody K18 that specifically inhibits the activity of this enzyme in vitro. This antibody significantly inhibited DNA synthesis both when microinjected into nuclei of exponentially growing human fibroblasts and in isolated HeLa cell nuclei, but did not inhibit SV40 DNA replication in vitro. These results suggest that the human DNA polymerase ε contributes substantially to the replicative synthesis of DNA and emphasises the differences between cellular replication and viral model systems. The human DNA polymerases ε and δ were found capable of gap-filling DNA synthesis during nucleotide excision repair in vitro. Both enzymes required PCNA and the clamp loader RFC, and in addition, polymerase δ required Fen-1 to prevent excessive displacement synthesis. Nucleotide excision repair of a defined DNA lesion was completely reconstituted utilising largely recombinant proteins, only ligase I and DNA polymerases δ and ε provided as highly purified human enzymes. This system was also utilised to study the role of the transcription factor II H during repair. Human non-homologous end joining of model substrates with different DNA end configurations was studied in HeLa cell extracts. This process depended partially on DNA synthesis as an aphidicolin-dependent DNA polymerase was required for the formation of a subset of end joining products. Experiments with neutralising antibodies reveal that DNA polymerase α but not DNA polymerases β or ε, may represent this DNA polymerase activity. Our results indicate that DNA synthesis contributes to the stability of DNA ends, and influences both the efficiency and outcome of the end joining event. Furthermore, our results suggest a minor role of PCNA in non-homologous end joining.

Mitochondrial ATP production is achieved using the electron transport chain (ETC), whereby the controlled oxidation of biomolecules is coupled to the activity of ATP synthase. ETC complexes organize into supramolecular structures called supercomplexes (ETC SCs). Protein factors regulating ETC SCs remain largely unknown despite their fundamental implications to mitochondrial respiratory function. Recent knock-out studies have delineated external ETC proteins HIGD1A and HIGD2A as assembly factors of ETC complexes III and IV, and their incorporation into SCs. In order to clarify the primary functions of HIGD1A and HIGD2A, as well as other previously uncharacterized HIG1 protein family members, stable overexpression (OE) models of each HIG1 protein were generated in HEK293t cells to preform comparative studies. We uncover a general dichotomy in the effects observed from HIGD2A vs. HIGD1A/1B/1C OE. Furthermore, we demonstrate that the previously unstudied protein family member HIGD1C is a negative regulator of complex IV SCs. A very limited number of protein factors specifically regulating the I1III2IV1 “respirasome” ETC SC have been identified. We propose a new framework where select complex I accessory subunits regulate respirasome assembly through protein-protein interactions between ETC complexes. Through specific point mutations to one such subunit, we generate a novel cell model with selective disassembly of the respirasome but otherwise functional individual ETC complexes. We demonstrate that respirasome disassembly limits respiration and modifies electron transfer pathways within the ETC. These findings to respirasome assembly and function may represent just a portion of higher order regulation that we are beginning to describe within eukaryotic metabolism.

A great challenge in bioinformatics is to accurately predict protein structure and function from its amino acid sequence, including annotation of protein domains, identification of protein disordered regions and detecting protein stability changes resulting from amino acid mutations. The combination of bioinformatics, genomics and proteomics becomes essential for the investigation of biological, cellular and molecular aspects of disease, and therefore can greatly contribute to the understanding of protein structures and facilitating drug discovery. In this thesis, a PREDICTOR, which consists of three machine learning methods applied to three different but related structure bioinformatics tasks, is presented: using profile Hidden Markov Models (HMMs) to identify remote sequence homologues, on the basis of protein domains; predicting order and disorder in proteins using Conditional Random Fields (CRFs); applying Support Vector Machines (SVMs) to detect protein stability changes due to single mutation. To facilitate structural instability and disease studies, these methods are implemented in three web servers: FISH, OnD-CRF and ProSMS, respectively. For FISH, most of the work presented in the thesis focuses on the design and construction of the web-server. The server is based on a collection of structure-anchored hidden Markov models (saHMM), which are used to identify structural similarity on the protein domain level. For the order and disorder prediction server, OnD-CRF, I implemented two schemes to alleviate the imbalance problem between ordered and disordered amino acids in the training dataset. One uses pruning of the protein sequence in order to obtain a balanced training dataset. The other tries to find the optimal p-value cut-off for discriminating between ordered and disordered amino acids.  Both these schemes enhance the sensitivity of detecting disordered amino acids in proteins. In addition, the output from the OnD-CRF web server can also be used to identify flexible regions, as well as predicting the effect of mutations on protein stability. For ProSMS, we propose, after careful evaluation with different methods, a clustered by homology and a non-clustered model for a three-state classification of protein stability changes due to single amino acid mutations. Results for the non-clustered model reveal that the sequence-only based prediction accuracy is comparable to the accuracy based on protein 3D structure information. In the case of the clustered model, however, the prediction accuracy is significantly improved when protein tertiary structure information, in form of local environmental conditions, is included. Comparing the prediction accuracies for the two models indicates that the prediction of mutation stability of proteins that are not homologous is still a challenging task. Benchmarking results show that, as stand-alone programs, these predictors can be comparable or superior to previously established predictors. Combined into a program package, these mutually complementary predictors will facilitate the understanding of structural instability and disease from protein sequence.

Thesis (Ph. D.)--University of Washington, 2005. / Vita. Includes bibliographical references (leaves 214-243).

Notre équipe étudie les mécanismes de résistance à l’apoptose induite par divers agents dans les cellules de lymphomes B infectées ou non par le virus d’Epstein-Barr (EBV). EBV est un virus oncogénique de la famille des gamma-herpès virus qui est associé notamment au lymphome de Burkitt (LB) et aux syndromes lymphoprolifératifs post-transplantation (PTLD). Des résultats précédents ont montré que l’utilisation de la nutline-3, une molécule capable de se fixer sur MDM2, active p53 dans ces cellules tumorales. Cependant cette activation de p53 provoque l’apoptose des cellules B EBV(-) alors que les cellules B EBV(+) en latence III (exprimant toutes les protéines virales dites « de latence ») sont beaucoup plus résistantes. Mon travail de thèse a consisté à étudier les mécanismes impliqués dans cette résistance afin de mettre en place des stratégies thérapeutiques pour la contourner. La première partie de ma thèse a été consacrée à l’étude du rôle de l’autophagie dans la résistance des cellules EBV(+) en latence III à l’apoptose. L’autophagie est un processus de dégradation des protéines qui joue un rôle physiologique complexe impliqué à la fois dans la survie et dans la mort cellulaire. Les travaux effectués ont montré que: 1) l’autophagie est induite en réponse au traitement par la nutline dans les cellules EBV(+) en latence III ; 2) ces cellules expriment fortement la Bécline-1 et présentent une activation constitutive de l’autophagie ; 3) l’autophagie participe à la résistance de ces cellules à l’apoptose. La seconde partie de ma thèse a été consacrée au développement de nouvelles molécules ciblant les protéines anti-apoptotiques de la famille de Bcl-2. En effet, outre Bcl-2 qui est surexprimé dans les cellules EBV(+), les cellules de LB et les PTLD surexpriment aussi Mcl-1, une autre protéine anti-apoptotique. Or il a été montré que cette protéine était fréquemment à l’origine de résistance à des inhibiteurs déjà développés (et en essais cliniques) contre Bcl-2. Le développement de molécules ciblant Mcl-1 s’avère donc utile pour les contrer. Pour cela une collaboration avec une équipe de chimiste (dirigée par Fanny Roussi à l’Institut de Chimie des Substances Naturelles à Gif-sur-Yvette) a été mise en place. Nous avons identifié et étudié les mécanismes d’action de plusieurs molécules inhibitrices potentielles de Mcl-1 et/ou Bcl-xL capables d’induire l’apoptose dans nos deux modèles de lymphomes. / Our team investigates the mechanisms of resistance to apoptosis induced in various B-cell lymphomas including some infected by the Epstein-Barr virus (EBV). EBV is an oncogenic member in the gamma-herpesvirus family. Among other pathologies, it is associated with Burkitt’s lymphoma (BL) and post-transplant lymphoproliferative disorders (PTLD). Previously, our laboratory has found that in these tumor cells, the binding of nutlin-3 to MDM2 results in the activation of p53. However, although p53 activation leads to apoptosis in EBV(-) cells, EBV(+) latency III cells which express all viral « latency » proteins are much more resistant. During this PhD project, I studied the mechanisms involved in this resistance and made attempts to define new therapeutic strategies that would bypass them. First, the role played by autophagy was investigated. This catabolic process which degrades proteins and organelles is physiologically complex as it is involved in both cell survival and cell death. Our work has demonstrated that: 1) autophagy was induced in nutlin-3 treated EBV(+) latency III cells; 2) Beclin-1 was strongly expressed in these cells whose autophagy was constitutively activated; 3) autophagy was involved in the resistance to apoptosis observed in these cells. Second, I turned my efforts to the identification of new molecules targeting anti-apoptotic members of the Bcl-2 family. Like Bcl-2, the antiapoptotic protein Mcl-1 is heavily expressed in LB and PTLD cell lines but in this case, independently of their EBV status and this is a frequent cause for the observed resistance to Bcl-2 inhibitors that are currently tested in clinical trials. Molecules targeting Mcl-1 could thus prove promising to circumvent this resistance. In a collaboration with a Chemistry team supervised by Fanny Roussi at the Institut de Chimie des Substances Naturelles in Gif-sur-Yvette, we have identified the mechanisms of action of potential inhibitors of Mcl-1 and/or Bcl-xL, another anti-apoptotic molecules which induce apoptosis in our two lymphoma models.