Contributions to organic synthesis and reaction mechanisms

Development of new methods, leading to the first stereo-specific total synthesis of a steroid,viz equilenin, and of estrone and their derivatives and of several important synthones, useful for the preparation of physiologically active steroids, and the first conversion of an equilenane to estrane have been described. An account of the achievement of original syntheses of testosterone and its isomers and derivatives and degradation products, urinary steroids, terpenes and their important degradation products has been given. Mechanisms of Dieckmann cyclization, a novel dehydrogenation-addition reaction involving abietic acid and tetrachloro-o-benzoquinone, a rearrangement involving a substitution of cyclopentanone-2-carboxylic ester have been elucidated. An abnormaluv absorption exhibited by saturated 1,2-dicyano esters has been rationalized. Divergences in theord data of testosterone and 19-nortesto-sterone from their isomers have been explained by x-ray crystallographic studies of 8-isotestosterone, 8-iso-10-isotestosterone and 8-iso-10-iso-19-nortestosterone. A tentative explanation for the difference in their physiological activities has been suggested.

Location and scale mixtures of Gaussians with flexible tail behaviour: Properties, inference and application to multivariate clustering

The family of location and scale mixtures of Gaussians has the ability to generate a number of flexible distributional forms. The family nests as particular cases several important asymmetric distributions like the Generalized Hyperbolic distribution. The Generalized Hyperbolic distribution in turn nests many other well known distributions such as the Normal Inverse Gaussian. In a multivariate setting, an extension of the standard location and scale mixture concept is proposed into a so called multiple scaled framework which has the advantage of allowing different tail and skewness behaviours in each dimension with arbitrary correlation between dimensions. Estimation of the parameters is provided via an EM algorithm and extended to cover the case of mixtures of such multiple scaled distributions for application to clustering. Assessments on simulated and real data confirm the gain in degrees of freedom and flexibility in modelling data of varying tail behaviour and directional shape.

On probability-based inference under data missing by design

Whether a statistician wants to complement a probability model for observed data with a prior distribution and carry out fully probabilistic inference, or base the inference only on the likelihood function, may be a fundamental question in theory, but in practice it may well be of less importance if the likelihood contains much more information than the prior. Maximum likelihood inference can be justified as a Gaussian approximation at the posterior mode, using flat priors. However, in situations where parametric assumptions in standard statistical models would be too rigid, more flexible model formulation, combined with fully probabilistic inference, can be achieved using hierarchical Bayesian parametrization. This work includes five articles, all of which apply probability modeling under various problems involving incomplete observation. Three of the papers apply maximum likelihood estimation and two of them hierarchical Bayesian modeling. Because maximum likelihood may be presented as a special case of Bayesian inference, but not the other way round, in the introductory part of this work we present a framework for probability-based inference using only Bayesian concepts. We also re-derive some results presented in the original articles using the toolbox equipped herein, to show that they are also justifiable under this more general framework. Here the assumption of exchangeability and de Finetti's representation theorem are applied repeatedly for justifying the use of standard parametric probability models with conditionally independent likelihood contributions. It is argued that this same reasoning can be applied also under sampling from a finite population. The main emphasis here is in probability-based inference under incomplete observation due to study design. This is illustrated using a generic two-phase cohort sampling design as an example. The alternative approaches presented for analysis of such a design are full likelihood, which utilizes all observed information, and conditional likelihood, which is restricted to a completely observed set, conditioning on the rule that generated that set. Conditional likelihood inference is also applied for a joint analysis of prevalence and incidence data, a situation subject to both left censoring and left truncation. Other topics covered are model uncertainty and causal inference using posterior predictive distributions. We formulate a non-parametric monotonic regression model for one or more covariates and a Bayesian estimation procedure, and apply the model in the context of optimal sequential treatment regimes, demonstrating that inference based on posterior predictive distributions is feasible also in this case.

Bayesian Inference for Retrospective Population Genetics Models Using Markov Chain Monte Carlo Methods

Genetics, the science of heredity and variation in living organisms, has a central role in medicine, in breeding crops and livestock, and in studying fundamental topics of biological sciences such as evolution and cell functioning. Currently the field of genetics is under a rapid development because of the recent advances in technologies by which molecular data can be obtained from living organisms. In order that most information from such data can be extracted, the analyses need to be carried out using statistical models that are tailored to take account of the particular genetic processes. In this thesis we formulate and analyze Bayesian models for genetic marker data of contemporary individuals. The major focus is on the modeling of the unobserved recent ancestry of the sampled individuals (say, for tens of generations or so), which is carried out by using explicit probabilistic reconstructions of the pedigree structures accompanied by the gene flows at the marker loci. For such a recent history, the recombination process is the major genetic force that shapes the genomes of the individuals, and it is included in the model by assuming that the recombination fractions between the adjacent markers are known. The posterior distribution of the unobserved history of the individuals is studied conditionally on the observed marker data by using a Markov chain Monte Carlo algorithm (MCMC). The example analyses consider estimation of the population structure, relatedness structure (both at the level of whole genomes as well as at each marker separately), and haplotype configurations. For situations where the pedigree structure is partially known, an algorithm to create an initial state for the MCMC algorithm is given. Furthermore, the thesis includes an extension of the model for the recent genetic history to situations where also a quantitative phenotype has been measured from the contemporary individuals. In that case the goal is to identify positions on the genome that affect the observed phenotypic values. This task is carried out within the Bayesian framework, where the number and the relative effects of the quantitative trait loci are treated as random variables whose posterior distribution is studied conditionally on the observed genetic and phenotypic data. In addition, the thesis contains an extension of a widely-used haplotyping method, the PHASE algorithm, to settings where genetic material from several individuals has been pooled together, and the allele frequencies of each pool are determined in a single genotyping.

Mechanisms of the impact of a weed (grader grass, Themeda quadrivalvis) on reptile assemblage structure in a tropical savannah

Invasive grasses are among the worst threats to native biodiversity, but the mechanisms causing negative effects are poorly understood. To investigate the impact of an invasive grass on reptiles, we compared the reptile assemblages that used native kangaroo grass (Themeda triandra), and black spear grass (Heteropogon contortus), to those using habitats invaded by grader grass (Themeda quadrivalvis). There were significantly more reptile species, in greater abundances, in native kangaroo and black spear grass than in invasive grader grass. To understand the sources of negative responses of reptile assemblages to the weed, we compared habitat characteristics, temperatures within grass clumps, food availability and predator abundance among these three grass habitats. Environmental temperatures in grass, invertebrate food availability, and avian predator abundances did not differ among the habitats, and there were fewer reptiles that fed on other reptiles in the invaded than in the native grass sites. Thus, native grass sites did not provide better available thermal environments within the grass, food, or opportunities for predator avoidance. We suggest that habitat structure was the critical factor driving weed avoidance by reptiles in this system, and recommend that the maintenance of heterogeneous habitat structure, including clumping native grasses, with interspersed bare ground, and leaf litter are critical to reptile biodiversity.

Computational Techniques for Haplotype Inference and for Local Alignment Significance

This thesis which consists of an introduction and four peer-reviewed original publications studies the problems of haplotype inference (haplotyping) and local alignment significance. The problems studied here belong to the broad area of bioinformatics and computational biology. The presented solutions are computationally fast and accurate, which makes them practical in high-throughput sequence data analysis. Haplotype inference is a computational problem where the goal is to estimate haplotypes from a sample of genotypes as accurately as possible. This problem is important as the direct measurement of haplotypes is difficult, whereas the genotypes are easier to quantify. Haplotypes are the key-players when studying for example the genetic causes of diseases. In this thesis, three methods are presented for the haplotype inference problem referred to as HaploParser, HIT, and BACH. HaploParser is based on a combinatorial mosaic model and hierarchical parsing that together mimic recombinations and point-mutations in a biologically plausible way. In this mosaic model, the current population is assumed to be evolved from a small founder population. Thus, the haplotypes of the current population are recombinations of the (implicit) founder haplotypes with some point--mutations. HIT (Haplotype Inference Technique) uses a hidden Markov model for haplotypes and efficient algorithms are presented to learn this model from genotype data. The model structure of HIT is analogous to the mosaic model of HaploParser with founder haplotypes. Therefore, it can be seen as a probabilistic model of recombinations and point-mutations. BACH (Bayesian Context-based Haplotyping) utilizes a context tree weighting algorithm to efficiently sum over all variable-length Markov chains to evaluate the posterior probability of a haplotype configuration. Algorithms are presented that find haplotype configurations with high posterior probability. BACH is the most accurate method presented in this thesis and has comparable performance to the best available software for haplotype inference. Local alignment significance is a computational problem where one is interested in whether the local similarities in two sequences are due to the fact that the sequences are related or just by chance. Similarity of sequences is measured by their best local alignment score and from that, a p-value is computed. This p-value is the probability of picking two sequences from the null model that have as good or better best local alignment score. Local alignment significance is used routinely for example in homology searches. In this thesis, a general framework is sketched that allows one to compute a tight upper bound for the p-value of a local pairwise alignment score. Unlike the previous methods, the presented framework is not affeced by so-called edge-effects and can handle gaps (deletions and insertions) without troublesome sampling and curve fitting.

Mechanisms of the impact of a weed (grader grass, Themeda quadrivalvis) on reptile assemblage structure in a tropical savannah

Invasive grasses are among the worst threats to native biodiversity, but the mechanisms causing negative effects are poorly understood. To investigate the impact of an invasive grass on reptiles, we compared the reptile assemblages that used native kangaroo grass (Themeda triandra), and black spear grass (Heteropogon contortus), to those using habitats invaded by grader grass (Themeda quadrivalvis). There were significantly more reptile species, in greater abundances, in native kangaroo and black spear grass than in invasive grader grass. To understand the sources of negative responses of reptile assemblages to the weed, we compared habitat characteristics, temperatures within grass clumps, food availability and predator abundance among these three grass habitats. Environmental temperatures in grass, invertebrate food availability, and avian predator abundances did not differ among the habitats, and there were fewer reptiles that fed on other reptiles in the invaded than in the native grass sites. Thus, native grass sites did not provide better available thermal environments within the grass, food, or opportunities for predator avoidance. We suggest that habitat structure was the critical factor driving weed avoidance by reptiles in this system, and recommend that the maintenance of heterogeneous habitat structure, including clumping native grasses, with interspersed bare ground, and leaf litter are critical to reptile biodiversity.

An Optimal Mechanism for Sponsored Search Auctions on the Web and Comparison With Other Mechanisms

In this paper, we first describe a framework to model the sponsored search auction on the web as a mechanism design problem. Using this framework, we describe two well-known mechanisms for sponsored search auction-Generalized Second Price (GSP) and Vickrey-Clarke-Groves (VCG). We then derive a new mechanism for sponsored search auction which we call optimal (OPT) mechanism. The OPT mechanism maximizes the search engine's expected revenue, while achieving Bayesian incentive compatibility and individual rationality of the advertisers. We then undertake a detailed comparative study of the mechanisms GSP, VCG, and OPT. We compute and compare the expected revenue earned by the search engine under the three mechanisms when the advertisers are symmetric and some special conditions are satisfied. We also compare the three mechanisms in terms of incentive compatibility, individual rationality, and computational complexity. Note to Practitioners-The advertiser-supported web site is one of the successful business models in the emerging web landscape. When an Internet user enters a keyword (i.e., a search phrase) into a search engine, the user gets back a page with results, containing the links most relevant to the query and also sponsored links, (also called paid advertisement links). When a sponsored link is clicked, the user is directed to the corresponding advertiser's web page. The advertiser pays the search engine in some appropriate manner for sending the user to its web page. Against every search performed by any user on any keyword, the search engine faces the problem of matching a set of advertisers to the sponsored slots. In addition, the search engine also needs to decide on a price to be charged to each advertiser. Due to increasing demands for Internet advertising space, most search engines currently use auction mechanisms for this purpose. These are called sponsored search auctions. A significant percentage of the revenue of Internet giants such as Google, Yahoo!, MSN, etc., comes from sponsored search auctions. In this paper, we study two auction mechanisms, GSP and VCG, which are quite popular in the sponsored auction context, and pursue the objective of designing a mechanism that is superior to these two mechanisms. In particular, we propose a new mechanism which we call the OPT mechanism. This mechanism maximizes the search engine's expected revenue subject to achieving Bayesian incentive compatibility and individual rationality. Bayesian incentive compatibility guarantees that it is optimal for each advertiser to bid his/her true value provided that all other agents also bid their respective true values. Individual rationality ensures that the agents participate voluntarily in the auction since they are assured of gaining a non-negative payoff by doing so.

Endoplasmic reticulum stress and cell death mechanisms in the cell model of Huntington’s disease

This thesis clarifies important molecular pathways that are activated during the cell death observed in Huntington’s disease. Huntington’s disease is one of the most common inherited neurodegenerative diseases, which is primarily inherited in an autosomal dominant manner. HD is caused by an expansion of CAG repeats in the first exon of the IT15 gene. IT15 encodes the production of a Huntington’s disease protein huntingtin. Mutation of the IT15 gene results in a long stretch of polyQ residues close to the amino-terminal region of huntingtin. Huntington’s disease is a fatal autosomal neurodegenerative disorder. Despite the current knowledge of HD, the precise mechanism behind the selective neuronal death, and how the disease propagates, still remains an enigma. The studies mainly focused on the control of endoplasmic reticulum (ER) stress triggered by the mutant huntingtin proteins. The ER is a delicate organelle having essential roles in protein folding and calcium regulation. Even the slightest perturbations on ER homeostasis are effective enough to trigger ER stress and its adaptation pathways, called unfolded protein response (UPR). UPR is essential for cellular homeostasis and it adapts ER to the changing environment and decreases ER stress. If adaptation processes fail and stress is excessive and prolonged; irreversible cell death pathways are engaged. The results showed that inhibition of ER stress with chemical agents are able to decrease cell death and formation of toxic cell aggregates caused by mutant huntingtin proteins. The study concentrated also to the NF-κB (nuclear factor-kappaB) pathway, which is activated during ER stress. NF-κB pathway is capable to regulate the levels of important cellular antioxidants. Cellular antioxidants provide a first line of defence against excess reactive oxygen species. Excess accumulation of reactive oxygen species and subsequent activation of oxidative stress damages motley of vital cellular processes and induce cell degeneration. Data showed that mutant huntingtin proteins downregulate the expression levels of NF-κB and vital antioxidants, which was followed by increased oxidative stress and cell death. Treatment with antioxidants and inhibition of oxidative stress were able to counteract these adverse effects. In addition, thesis connects ER stress caused by mutant huntingtin to the cytoprotective autophagy. Autophagy sustains cellular balance by degrading potentially toxic cell proteins and components observed in Huntington’s disease. The results revealed that cytoprotective autophagy is active at the early points (24h) of ER stress after expression of mutant huntingtin proteins. GADD34 (growth arrest and DNA damage-inducible gene 34), which is previously connected to the regulation of translation during cell stress, was shown to control the stimulation of autophagy. However, GADD34 and autophagy were downregulated at later time points (48h) during mutant huntingtin proteins induced ER stress, and subsequently cell survival decreased. Overexpression GADD34 enhanced autophagy and decreased cell death, indicating that GADD34 plays a critical role in cell protection. The thesis reveales new interesting data about the neuronal cell death pathways seen in Huntington’s disease, and how cell degeneration is partly counteracted by various therapeutic agents. Expression of mutant huntingtin proteins is shown to alter signaling events that control ER stress, oxidative stress and autophagy. Despite that Huntington’s disease is mainly an untreatable disorder; these findings offer potential targets and neuroprotective strategies in designing novel therapies for Huntington’s disease.

Bending the Rules of Cell Protrusions : Molecular Mechanisms and Biological Roles of Inverse-BAR Proteins in Cell Morphogenesis

Plasma membrane adopts myriad of different shapes to carry out essential cellular processes such as nutrient uptake, immunological defence mechanisms and cell migration. Therefore, the details how different plasma membrane structures are made and remodelled are of the upmost importance. Bending of plasma membrane into different shapes requires substantial amount of force, which can be provided by the actin cytoskeleton, however, the molecules that regulate the interplay between the actin cytoskeleton and plasma membrane have remained elusive. Recent findings have placed new types of effectors at sites of plasma membrane remodelling, including BAR proteins, which can directly bind and deform plasma membrane into different shapes. In addition to their membrane-bending abilities, BAR proteins also harbor protein domains that intimately link them to the actin cytoskeleton. The ancient BAR domain fold has evolved into at least three structurally and functionally different sub-groups: the BAR, F-BAR and I-BAR domains. This thesis work describes the discovery and functional characterization of the Inverse-BAR domains (I-BARs). Using synthetic model membranes, we have shown that I-BAR domains bind and deform membranes into tubular structures through a binding-surface composed of positively charged amino acids. Importantly, the membrane-binding surface of I-BAR domains displays an inverse geometry to that of the BAR and F-BAR domains, and these structural differences explain why I-BAR domains induce cell protrusions whereas BAR and most F-BAR domains induce cell invaginations. In addition, our results indicate that the binding of I-BAR domains to membranes can alter the spatial organization of phosphoinositides within membranes. Intriguingly, we also found that some I-BAR domains can insert helical motifs into the membrane bilayer, which has important consequences for their membrane binding/bending functions. In mammals there are five I-BAR domain containing proteins. Cell biological studies on ABBA revealed that it is highly expressed in radial glial cells during the development of the central nervous system and plays an important role in the extension process of radial glia-like C6R cells by regulating lamellipodial dynamics through its I-BAR domain. To reveal the role of these proteins in the context of animals, we analyzed MIM knockout mice and found that MIM is required for proper renal functions in adult mice. MIM deficient mice displayed a severe urine concentration defect due to defective intercellular junctions of the kidney epithelia. Consistently, MIM localized to adherens junctions in cultured kidney epithelial cells, where it promoted actin assembly through its I-BAR andWH2 domains. In summary, this thesis describes the mechanism how I-BAR proteins deform membranes and provides information about the biological role of these proteins, which to our knowledge are the first proteins that have been shown to directly deform plasma membrane to make cell protrusions.

Mechanisms of KCC2 upregulation during development

Gamma-aminobutyric acid (GABA) acting through ionotropic GABAA receptors plays a crucial role in the activity of the central nervous system (CNS). It triggers Ca2+ rise providing trophic support in developing neurons and conducts fast inhibitory function in mature neuronal networks. There is a developmental change in the GABAA reversal potential towards more negative levels during the first two postnatal weeks in rodent hippocampus. This change provides the basis for mature GABAergic activity and is attributable to the developmental expression of the neuron-specific potassium chloride cotransporter 2 (KCC2). In this work we have studied the mechanisms responsible for the control of KCC2 developmental expression. As a model system we used hippocampal dissociated cultures plated from embryonic day (E) 17 mice embryos before the onset of KCC2 expression. We showed that KCC2 was significantly up-regulated during the first two weeks of culture development. Interestingly, the level of KCC2 upregulation was not altered by chronic pharmacological blockage of action potentials as well as GABAergic and glutamatergic synaptic transmission. By in silico analysis of the proximal KCC2 promoter region we identified 10 candidate transcription factor binding sites that are highly conserved in mammalian KCC2 genes. One of these transcription factors, namely early growth response factor 4 (Egr4), had similar developmental profile as KCC2 and considerably increased the activity of mouse KCC2 gene in neuronal cells. Next we investigated the involvement of neurotrophic factors in regulation of Egr4 and KCC2 expression. We found that in immature hippocampal cultures Egr4 and KCC2 levels were strongly up-regulated by brain derived neurotrophic factor (BDNF)and neurturin. The effect of neurotrophic factors was dependent on the activation of a mitogen activated protein kinase (MAPK) signal transduction pathway. Intact Egr4-binding site in proximal KCC2 promoter was required for BDNF-induced KCC2 transcription. In vitro data were confirmed by several in vivo experiments where we detected an upregulation of KCC2 protein levels after intrahippocampal administration of BDNF or neurturin. Importantly, a MAPK-dependent rise in Egr4 and KCC2 expression levels was also observed after a period of kainic acid-induced seizure activity in neonatal rats suggesting that neuronal activity might be involved in Egr4-mediated regulation of KCC2 expression. Finally we demonstrated that the mammalian KCC2 gene (alias Slc12a5) generated two neuron-specific isoforms by using alternative promoters and first exons. A novel isoform of KCC2, termed KCC2a, differed from the previously known KCC2b isoform by 40 unique N-terminal amino acid residues. KCC2a expression was restricted to CNS,remained relatively constant during postnatal development, and contributed 20 50% of total KCC2 mRNA expression in the neonatal mouse brainstem and spinal cord. In summary, our data provide insight into the complex regulation of KCC2 expression during early postnatal development. Although basal KCC2 expression seems to be intrinsically regulated, it can be further augmented by neurotrophic factors or by enhanced activity triggering MAPK phosphorylation and Egr4 induction. Additional KCC2a isoform, regulated by another promoter, provides basal KCC2 level in neonatal brainstem and spinal cord required for survival of KCC2b knockout mice.

Mechanisms for alphavirus nonstructural polyprotein processing

Replication and transcription of the RNA genome of alphaviruses relies on a set of virus-encoded nonstructural proteins. They are synthesized as a long polyprotein precursor, P1234, which is cleaved at three processing sites to yield nonstructural proteins nsP1, nsP2, nsP3 and nsP4. All the four proteins function as constitutive components of the membrane-associated viral replicase. Proteolytic processing of P1234 polyprotein is precisely orchestrated and coordinates the replicase assembly and maturation. The specificity of the replicase is also controlled by proteolytic cleavages. The early replicase is composed of P123 polyprotein intermediate and nsP4. It copies the positive sense RNA genome to complementary minus-strand. Production of new plus-strands requires complete processing of the replicase. The papain-like protease residing in nsP2 is responsible for all three cleavages in P1234. This study addressed the mechanisms of proteolytic processing of the replicase polyprotein in two alphaviruses Semliki Forest virus (SFV) and Sindbis virus (SIN) representing different branches of the genus. The survey highlighted the functional relation of the alphavirus nsP2 protease to the papain-like enzymes. A new structural motif the Cys-His catalytic dyad accompanied with an aromatic residue following the catalytic His was described for nsP2 and a subset of other thiol proteases. Such an architecture of the catalytic center was named the glycine specificity motif since it was implicated in recognition of a specific Gly residue in the substrate. In particular, the presence of the motif in nsP2 makes the appearance of this amino acid at the second position upstream of the scissile bond a necessary condition for the cleavage. On top of that, there were four distinct mechanisms identified, which provide affinity for the protease and specifically direct the enzyme to different sites in the P1234 polyprotein. Three factors RNA, the central domain of nsP3 and the N-terminus of nsP2 were demonstrated to be external modulators of the nsP2 protease. Here I suggest that the basal nsP2 protease specificity is inherited from the ancestral papain-like enzyme and employs the recognition of the upstream amino acid signature in the immediate vicinity of the scissile bond. This mechanism is responsible for the efficient processing of the SFV nsP3/nsP4 junction. I propose that the same mechanism is involved in the cleavage of the nsP1/nsP2 junction of both viruses as well. However, in this case it rather serves to position the substrate, whereas the efficiency of the processing is ensured by the capability of nsP2 to cut its own N-terminus in cis. Both types of cleavages are demonstrated here to be inhibited by RNA, which is interpreted as impairing the basal papain-like recognition of the substrate. In contrast, processing of the SIN nsP3/nsP4 junction was found to be activated by RNA and additionally potentiated by the presence of the central region of nsP3 in the protease. The processing of the nsP2/nsP3 junction in both viruses occurred via another mechanism, requiring the exactly processed N-terminus of nsP2 in the protease and insensitive to RNA addition. Therefore, the three processing events in the replicase polyprotein maturation are performed via three distinct mechanisms in each of two studied alphaviruses. Distinct sets of conditions required for each cleavage ensure sequential maturation of P1234 polyprotein: nsP4 is released first, then the nsP1/nsP2 site is cut in cis, and liberation of the nsP2 N-terminus activates the cleavage of the nsP2/nsP3 junction at last. The first processing event occurs differently in SFV and SIN, whereas the subsequent cleavages are found to be similar in the two viruses and therefore, their mechanisms are suggested to be conserved in the genus. The RNA modulation of the alphavirus nonstructural protease activity, discovered here, implies bidirectional functional interplay between the alphavirus RNA metabolism and protease regulation. The nsP2 protease emerges as a signal transmitting moiety, which senses the replication stage and responds with proteolytic cleavages. A detailed hypothetical model of the alphavirus replicase core was inferred from the data obtained in the study. Similar principles in replicase organization and protease functioning are expected to be employed by other RNA viruses.