A significant number of proteins function as multimeric structures, most commonly as dimers. One of the primary mechanisms by which proteins evolve is through gene duplication and mutations of the resulting duplicated gene. The evolution of dimeric proteins after gene duplication is of interest because it can form three types of dimer: two homodimers and a heterodimer. Point mutations that occur in the interface of dimers would affect their binding strength and might change their path in the evolution. Here we designed an evolutionary model for protein dimerization after gene duplication. In this work, we have used dimers' PDB structures to construct the network of contacts between amino acids in the interface. Several pairwise energy contact matrices were examined to find reasonable interface binding energies. Using the population genetics theory, we defined a selection criteria based on dimer interface strength and let them evolve as the mutations happen. We observed that the dimer structures are bound to be in the mostly homodimer state or mostly heterodimer state, and there are few occasions that we have all three types of structures as strong dimers. We anticipate three fates for the dimer protein's evolution after gene duplication, neofunctionalization, subfunctionalization, and loss of the gene. A loss of function in homodimer structures might eventually lead to a subfunctionalization since the two interfaces are different. On the other hand, if a heterodimer loss happens, we would have two strong homodimer structures so both neofunctionalization and subfunctionalization might still happen. In the first case, one could gain a new function while the other homodimer performs the protein's old function. In the latter case, the two separate homodimers could each assume different parts of the full function of the original gene (which is the definition of subfunctionalization). / Thesis / Master of Science (MSc) / A large fraction of proteins are found to exist as dimers composed to two identical subunits. If the gene for the single subunit is duplicated, three types of dimers can emerge, two homodimer structures and a heterodimer structure. Gene duplication is a major driving force of evolution as it can allow the proteins to perform new tasks. Here we define a model to understand the evolution of dimeric proteins as they undergo mutations in their interface, changing their stickiness to each other. We find that evolution favours the dimers to either be homodimer or heterodimer, but not both at the same time. When there are two homodimers, one of them can acquire a new function (which is known as neofunctionalization). When there is a heterodimer, both genes are now required to do the orginal job of a single gene (which is known as subfunctionalization). These mechanism provide two possible reasons why the duplicate gene cannot subsequently be deleted from the genome.

Naturally evolving proteins must navigate a vast set of possible sequences to evolve new functions. This process depends on the genotype-phenotype map. Much effort has been directed at measuring protein genotype phenotype maps to uncover evolutionary trajectories that lead to new functions. Often, these maps are too large to comprehensively measure. Sparsely measured maps, however, are prone to missing key evolutionary trajectories. Many groups turn to computational models to infer missing phenotypes. These models treat mutations as independent perturbations to the genotype-phenotype map. A key question is how to handle non-independent effects known as epistasis. In this dissertation, we address two sources of epistasis: 1) global and 2) local epistasis. We find that incorporating global epistasis improves our predictive power, while local epistasis does not. We use our model to infer unknown phenotypes in the Plasmodium falciparum chloroquine transporter (PfCRT) genotype-phenotype map, a protein responsible for conferring drug resistance in malaria. From these predictions, we uncover key evolutionary trajectories that led high resistance. This dissertation includes previously published and unpublished co-authored material. / 2020-01-11

Two separate but related projects make up the work of this thesis. The growing amount of sequence data available in public databases provides an opportunity to compare species in new ways. It can be shown that there is a systematic change in amino acid composition in a dataset of sequences from 69 species possessing a range of optimal growth temperatures. By creating a phylogenetic tree of all available Archaea, pairs may be selected that contain a relatively closely related mesophile and (hyper)thermophile. In addition, pairs may be selected from Bacteria to include psychrophiles as well as other thermophiles. An evolutionary model is derived here that detects amino acid asymmetries in these species pairs beyond what might be expected to be caused by differences in GC content. This amino acid asymmetry can then be plausibly explained by temperature adaptation occurring in these species since they diverged from a common ancestor. In the second part, similarity searches using molecular sequences are drawn as networks, where open reading frames in one species may be linked to a corresponding sequence in another species if the similarity search score is above a given threshold. This process is similar to that used to identify orthologous sequences for use in evolutionary models. When drawn as a network of distinct clusters of similarity, patterns emerge that can be spurious or have some biological relevance. This work identifies the need to develop better methods of analyzing these network clusters. / Thesis / Master of Science (MSc)

All twenty amino acids did not appear simultaneously in nature. Instead some of them appeared early, while others were added into the genetic code later. The amino acids that were formed by Miller (1953) are suggested to have appeared early in evolutionary history, and the amino acids associated with codon capture developed late in the course of evolution. The chronological order of appearance of the amino acids proposed by Trifonov (2000) was G/A, V/D, P, S, E/L, T, R, N, K, Q, I, C, H, F, M, Y, W. According to Romero et al. (1997) amino acids G, D, E, P and S are disorder-promoting residues and C, F, W and Y are order-promoting residues this means that the early or the ancient amino acids were disorder promoting and the order promoting residues came late into the genetic code. These observations led to the hypothesis that the first proteins, which were comprised of the early amino acids only, were disordered, and, furthermore, that the appearance of the late amino acids and the appearance of the structural proteins were concurrent. Software developed by Brooks et al. (2004) to find the amino acid composition of the LUA (Last Universal Ancestor) was used to test this hypothesis. For this work, the Clusters of Orhtologous Groups of proteins (65 COGs) were split into enzymes and non-enzymes. It was found that intrinsic disorder was abundant in both the groups of proteins, with non enzymes being much more disorder than enzymes. Further analysis was done to check for the frequency of the modern amino acids C, F, W, and Y in the Protein data bank (PDB) and Swissprot.

Understanding how changes in functional requirements of the cell select for changes in protein sequence and structure is a fundamental challenge in molecular evolution. This dissertation delineates some of the underlying evolutionary forces using as a model system, the Haloalkanoate Dehalogenase Superfamily (HADSF). HADSF members have unique cap-core architecture with the Rossmann-fold core domain accessorized by variable cap domain insertions (delineated by length, topology, and point of insertion). To identify the boundaries of variable domain insertions in protein sequences, I have developed a comprehensive computational strategy (CapPredictor or CP) using a novel sequence alignment algorithm in conjunction with a structure-guided sequence profile. Analysis of more than 40,000 HADSF sequences led to the following observations: (i) cap-type classes exhibit similar distributions across different phyla, indicating existence of all cap-types in the last universal common ancestor, and (ii) comparative analysis of the predicted cap-type and functional diversity indicated that cap-type does not dictate the divergence of substrate recognition and chemical pathway, and hence biological function. By analyzing a unique dataset of core- and cap-domain-only protein structures, I investigated the consequences of the accessory cap domain on the sequence-structure relationship of the core domain. The relationship between sequence and structure divergence in the core fold was shown to be monotonic and independent of the corresponding cap type. However, core domains with the same cap type bore a greater similarity than the core domains with different cap types, suggesting coevolution of the cap and core domains. Remarkably, a few degrees of freedom are needed to describe the structural diversity in the Rossmann fold accounting for the majority of the observed structural variance. Finally, I examined the location and role of conserved residue positions and co-evolving residue pairs in the core domain in the context of the cap domain. Positions critical for function were conserved while non-conserved positions mapped to highly mobile regions. Notably, we found exponential dependence of co-variance on inter-residue distance. Collectively, these novel algorithms and analyses contribute to an improved understanding of enzyme evolution, especially in the context of the use of domain insertions to expand substrate specificity and chemical mechanism.

The study of protein evolution and adaptation resides at the junction between the disciplines of biological chemistry and evolutionary biology. We chose the B. thetaiotaomicron tetracycline resistant enzyme TetX2, as our model system to study the biophysical basis for adaptation to antibiotics; a phenomenon that continuously poses global health challenges. In the work presented here, experimental evolution and biophysical characterization were used to identify and link the physicochemical properties of TetX2 and its adaptive mutants to increased resistance to minocycline. Bacteroides thetaiotaomicron TetX2 was previously identified as a novel oxidoreductase with broad activity against tetracyclines. Experimental evolution of E. coli expressing a chromosomal copy of tet(X2) was used to identify an adaptive mutation (TetX2 T280A ) that confers higher resistance to minocycline and tigecycline. In addition to TetX2 T280A , a family of variants of TetX2 with single amino acid changes in TetX2 sequence that conferred equal or higher resistance towards MCN was identified by error-prone mutagenesis. Changes in fitness of E. coli carrying a single chromosomal copy of either wild-type or one of the mutant alleles were assessed by growth rate assays over a range of minocycline concentrations. Despite similar in vivo performances of TetX2 T280A and two other variants (TetX2 N371I and TetX2 N371T ), TetX2 T280A was the only successful mutant in the adaption experiment suggesting that mutational supply may play an important role in evolutionary dynamics of populations undergoing adaptation. The most surprising result is that the differences in growth rates among TetX2 variants arise from small changes in in vitro catalytic activity and in vivo protein expression. The steady-state kinetic studies with minocycline and NADPH suggest a binary mechanism for antibiotic inactivation by TetX2 which is supported by the structural characteristics of the enzyme. The atomic structures of the best adaptive mutant TetX2 T280A in complex with minocycline and tigecycline reveal the details of substrate recognition and show that the site of the mutation is ∼18 Å away from the active site suggesting an indirect mechanism for improved catalysis. Taken together, our data show that very small changes in the in vitro biochemical properties and expression levels can have surprisingly large fitness effects and are important during adaption. In addition, a promising preliminary mathematical model suggests that based on kinetic activity and in vivo expression levels the success of bacteria undergoing adaptation to antibiotics can be predicted.

Bacterial secondary metabolite biosynthetic pathways are frequently encoded in gene clusters. Genomic sequence information allows the identification of likely biosynthetic clusters based on sequence homology to known proteins. Biochemical characterization of suspected biosynthetic enzymes affords the discovery of pathways which may never be identified by traditional screening approaches. In the work presented here, I, in some cases in collaboration with others, characterize the three intragenomic GTP cyclohydrolase II (GCH II) homologs from Streptomyces coelicolor A3(2) and show that one catalyzes a related but distinct reaction from the other two. The basis for the altered activity is investigated and speaks to the chemical mechanism of not only the unusual enzyme but also to all GCH II enzymes. Further, I investigate two other enzymes found in the same gene cluster as the unusual GCH II. Using biochemical techniques, I show that the product of the unusual GCH II is used as a substrate by a creatinine amidohydrolase homolog. Using structural biology, I show that the third enzyme, a 6-pyruvoyltetrahydropterin synthase (PTPS), can not catalyze the PTPS reaction but is capable of binding a pterin substrate. Finally, I propose that the cluster from S. coelicolor containing the unusual GCH II encodes enzymes for a novel pathway to produce a pterin.

Insertions/deletions (indels) are potentially powerful evolutionary markers, but little is known about their evolution and few tools exist to effectively study them. To address this, I developed SeqFIRE, a tool for automated identification and extraction of indels from protein multiple sequence alignments. The program also extracts conserved alignment blocks, thus covering all major steps in preparing multiple sequence alignments for phylogenetic analysis. I then used SeqFIRE to build an indel database, using 299 single copy proteins from a broad taxonomic sampling of mainly multicellular eukaryotes. A total of 4,707 indels were extracted, of which 901 are simple (one genetic event) and 3,806 are complex (multiple events). The most abundant indels are single amino acid simple indels. Indel frequency decreases exponentially with length and shows a linear relationship with host protein size. Singleton indels reveal a strong bias towards insertions (2.31 x deletions on average). These analyses also identify 43 indels marking major clades in Plantae and Fungi (clade defining indels or CDIs), but none for Metazoa. In order to study the 3806 complex indels they were first classified by number of states. Analysis of the 2-state complex and simple indels combined (“bi-state indels”) confirms that insertions are over 2.5 times as frequent as deletions. Three-quarters of the complex indels had three-nine states (“slightly complex indels”). A tree-assisted search method was developed allowing me to identify 1,010 potential CDIs supporting all examined major branches of Plantae and Fungi. Forty-two proteins were also found to host complex indel CDIs for the deepest branches of Metazoa. After expanding the taxon set for these proteins, I identified a total of 49 non-bilaterian specific CDIs. Parsimony analysis of these indels places Ctenophora as sister taxon to all other Metazoa including Porifera. Six CDIs were also found placing Placozoa as sister to Bilateria. I conclude that slightly complex indels are a rich source of CDIs, and my tree-assisted search strategy could be automated and implemented in the program SeqFIRE to facilitate their discovery. This will have important implications for mining the phylogenomic content of the vast resource of protist genome data soon to become available.

Mitochondria evolved through endosymbiosis of an ancient prokaryote, and subsequently lost most genes to the host genome. In order for mitochondrial proteins to be correctly localized from the host cytosol to the mitochondrial compartments, a complex protein targeting and import machinery has evolved. Key receptor components in the protein translocase complex of the outer mitochondrial membrane, Tom20 and Tom22, recognize proteins to be imported and assist their insertion across the outer membrane. The solution structure of the Tom20 receptor domain from Arabidopsis thaliana was determined by nuclear magnetic resonance spectroscopy, and revealed that this protein has significant structural differences to its functional analogue found in animals and fungi.

Diss. (sammanfattning) Stockholm : Karol. inst., 2006. / Härtill 7 uppsatser.