Computational models for and from biology : simple gene assembly and reaction systems

The advancement of science and technology makes it clear that no single perspective is any longer sufficient to describe the true nature of any phenomenon. That is why the interdisciplinary research is gaining more attention overtime. An excellent example of this type of research is natural computing which stands on the borderline between biology and computer science. The contribution of research done in natural computing is twofold: on one hand, it sheds light into how nature works and how it processes information and, on the other hand, it provides some guidelines on how to design bio-inspired technologies. The first direction in this thesis focuses on a nature-inspired process called gene assembly in ciliates. The second one studies reaction systems, as a modeling framework with its rationale built upon the biochemical interactions happening within a cell. The process of gene assembly in ciliates has attracted a lot of attention as a research topic in the past 15 years. Two main modelling frameworks have been initially proposed in the end of 1990s to capture ciliates’ gene assembly process, namely the intermolecular model and the intramolecular model. They were followed by other model proposals such as templatebased assembly and DNA rearrangement pathways recombination models. In this thesis we are interested in a variation of the intramolecular model called simple gene assembly model, which focuses on the simplest possible folds in the assembly process. We propose a new framework called directed overlap-inclusion (DOI) graphs to overcome the limitations that previously introduced models faced in capturing all the combinatorial details of the simple gene assembly process. We investigate a number of combinatorial properties of these graphs, including a necessary property in terms of forbidden induced subgraphs. We also introduce DOI graph-based rewriting rules that capture all the operations of the simple gene assembly model and prove that they are equivalent to the string-based formalization of the model. Reaction systems (RS) is another nature-inspired modeling framework that is studied in this thesis. Reaction systems’ rationale is based upon two main regulation mechanisms, facilitation and inhibition, which control the interactions between biochemical reactions. Reaction systems is a complementary modeling framework to traditional quantitative frameworks, focusing on explicit cause-effect relationships between reactions. The explicit formulation of facilitation and inhibition mechanisms behind reactions, as well as the focus on interactions between reactions (rather than dynamics of concentrations) makes their applicability potentially wide and useful beyond biological case studies. In this thesis, we construct a reaction system model corresponding to the heat shock response mechanism based on a novel concept of dominance graph that captures the competition on resources in the ODE model. We also introduce for RS various concepts inspired by biology, e.g., mass conservation, steady state, periodicity, etc., to do model checking of the reaction systems based models. We prove that the complexity of the decision problems related to these properties varies from P to NP- and coNP-complete to PSPACE-complete. We further focus on the mass conservation relation in an RS and introduce the conservation dependency graph to capture the relation between the species and also propose an algorithm to list the conserved sets of a given reaction system.

Molecular Characteristics of Neuroblastoma with Special Reference to Novel Prognostic Factors and Diagnostic Applications

Molecular Characteristics of Neuroblastoma with Special Reference to Novel Prognostic Factors and Diagnostic Applications Department of Medical Biochemistry and Genetics Annales Universitatis Turkuensis, Medica-Odontologica, 2009, Turku, Finland Painosalama Oy, Turku, Finland 2009 Background: Neuroblastoma, which is the most common and extensively studied childhood solid cancer, shows a great clinical and biological heterogeneity. Most of the neuroblastoma patients older than one year have poor prognosis despite intensive therapies. The hallmark of neuroblastoma, biological heterogeneity, has hindered the discovery of prognostic tumour markers. At present, few molecular markers, such as MYCN oncogene status, have been adopted into clinical practice. Aims: The aim of the study was to improve the current prognostic methodology of neuroblastoma, especially by taking cognizance of the biological heterogeneity of neuroblastoma. Furthermore, unravelling novel molecular characteristics which associate with neuroblastoma tumour progression and cell differentiation was an additional objective. Results: A new strictly defined selection of neuroblastoma tumour spots of highest proliferation activity, hotspots, appeared to be representative and reliable in an analysis of MYCN amplification status using a chromogenic in situ hybridization technique (CISH). Based on the hotspot tumour tissue microarray immunohistochemistry and high-resolution oligo-array-based comparative genomic hybridization, which was integrated with gene expression and in silico analysis of existing transcriptomics, a polysialylated neural cell adhesion molecule (NCAM) and poorly characterized amplicon at 12q24.31 were discovered to associate with outcome. In addition, we found that a previously considered new neuroblastoma treatment target, the mutated c-kit receptor, was not mutated in neuroblastoma samples. Conclusions: Our studies indicate polysialylated NCAM and 12q24.31 amplicon to be new molecular markers with important value in prognostic evaluation of neuroblastoma. Moreover, the presented hotspot tumour tissue microarray method together with the CISH technique of the MYCN oncogene copy number is directly applicable to clinical use. Key words: neuroblastoma, polysialic acid, neural cell adhesion molecule, MYCN, c-kit, chromogenic in situ hybridization, hotspot

The Integrin Tail: A Tale of Cell Motility and Division

Integrin transmembrane receptor functions are regulated by adaptor molecules binding to their alpha and beta subunit intracellular domains, or tails, thus affecting integrin traffic and adhesion during e.g. cell motility. Interestingly, many cellular proteins function in both cell motility and cell division, thus raising the possibility that integrins might be involved in regulating the cell cycle. A thorough understanding of cell division is essential in cell biology and in human malignancies. It is well established that failures to complete cell cycle can give rise to genetically unstable cells with tumorigenic properties. Transformed cells promote the disruption of intercellular adhesions such as tight junctions, and this correlates with the onset of cell motility, invasion and unfavorable prognosis in cancer. In this study, we analyzed integrin regulation, mediated by adaptor binding to the  subunit tail, during cell motility and cell division. We revealed a novel molecular mechanism by which Rab21, through association with the integrin alpha subunits, drives integrin endosomal traffic during mitotic phases. In addition, we found indications for this finding in vivo, as RAB21 gene deletions were mapped in ovarian and prostate cancer samples. Importantly, the multinucleated phenotype of cultured ovarian cancer cells could be reverted by Rab21 overexpression. In this thesis work, we also show how the tight junction protein ZO-1 unexpectedly interacts with the 5 integrin cytoplasmic domain in the lamellipodia to promote cell motility and at the cleavage furrow to support separation of the daughter cells. The alpha5-ZO-1 complex formation was dependent on PKC which regulates ZO-1 phosphorylation and its subcellular localization. In addition, by an in situ detection method, we showed that a subset of metastatic human lung cancers expressed the alpha5beta-ZO-1 complex. Taken together, we were able to identify new molecular pathways that regulate integrin functions in an alpha tail-mediated fashion. These findings firmly suggest that genetic alterations in integrin traffic may lead to progression of tumorigenesis as a result of failed cell division. Also, the interplay of integrins and ZO-1 in forming spatially regulated adhesive structures broadens our view of crosstalk between pathways and distinct adhesive structures that can be involved in cancer cell biology.

Towards an Integrative Information Society: Studies on Individuality in Speech and Sign

The flow of information within modern information society has increased rapidly over the last decade. The major part of this information flow relies on the individual’s abilities to handle text or speech input. For the majority of us it presents no problems, but there are some individuals who would benefit from other means of conveying information, e.g. signed information flow. During the last decades the new results from various disciplines have all suggested towards the common background and processing for sign and speech and this was one of the key issues that I wanted to investigate further in this thesis. The basis of this thesis is firmly within speech research and that is why I wanted to design analogous test batteries for widely used speech perception tests for signers – to find out whether the results for signers would be the same as in speakers’ perception tests. One of the key findings within biology – and more precisely its effects on speech and communication research – is the mirror neuron system. That finding has enabled us to form new theories about evolution of communication, and it all seems to converge on the hypothesis that all communication has a common core within humans. In this thesis speech and sign are discussed as equal and analogical counterparts of communication and all research methods used in speech are modified for sign. Both speech and sign are thus investigated using similar test batteries. Furthermore, both production and perception of speech and sign are studied separately. An additional framework for studying production is given by gesture research using cry sounds. Results of cry sound research are then compared to results from children acquiring sign language. These results show that individuality manifests itself from very early on in human development. Articulation in adults, both in speech and sign, is studied from two perspectives: normal production and re-learning production when the apparatus has been changed. Normal production is studied both in speech and sign and the effects of changed articulation are studied with regards to speech. Both these studies are done by using carrier sentences. Furthermore, sign production is studied giving the informants possibility for spontaneous speech. The production data from the signing informants is also used as the basis for input in the sign synthesis stimuli used in sign perception test battery. Speech and sign perception were studied using the informants’ answers to questions using forced choice in identification and discrimination tasks. These answers were then compared across language modalities. Three different informant groups participated in the sign perception tests: native signers, sign language interpreters and Finnish adults with no knowledge of any signed language. This gave a chance to investigate which of the characteristics found in the results were due to the language per se and which were due to the changes in modality itself. As the analogous test batteries yielded similar results over different informant groups, some common threads of results could be observed. Starting from very early on in acquiring speech and sign the results were highly individual. However, the results were the same within one individual when the same test was repeated. This individuality of results represented along same patterns across different language modalities and - in some occasions - across language groups. As both modalities yield similar answers to analogous study questions, this has lead us to providing methods for basic input for sign language applications, i.e. signing avatars. This has also given us answers to questions on precision of the animation and intelligibility for the users – what are the parameters that govern intelligibility of synthesised speech or sign and how precise must the animation or synthetic speech be in order for it to be intelligible. The results also give additional support to the well-known fact that intelligibility in fact is not the same as naturalness. In some cases, as shown within the sign perception test battery design, naturalness decreases intelligibility. This also has to be taken into consideration when designing applications. All in all, results from each of the test batteries, be they for signers or speakers, yield strikingly similar patterns, which would indicate yet further support for the common core for all human communication. Thus, we can modify and deepen the phonetic framework models for human communication based on the knowledge obtained from the results of the test batteries within this thesis.

Chemical Biology Screen for Prostate Cancer Therapeutics

Prostate cancer initially responds to hormone-based therapeutics such as anti-androgen treatment or chemotherapeutics but eventually becomes resistant. Novel treatment options are therefore urgently needed. This thesis study applied a high-throughput screen of 4910 known drugs and drug-like small molecules to identify compounds that selectively inhibit growth of prostate cancer cells. In addition, the mechanisms underlying the cellular sensitivity to potent cancer selective compounds were addressed. Surprisingly, many of the compounds currently used in the clinics or studied in clinical trials were not cancer-selective. Only four drugs, aldehyde dehydrogenase inhibitor disulfiram (Antabus), antibiotic ionophore monensin, histone deacetylase inhibitor tricostatin A and fungicide thiram inhibited prostate cancer cell growth at nanomolar concentrations without major effects on non-malignant prostate epithelial cells. Disulfiram, monensin and a structurally similar compound to monensin, salinomycin, induced oxidative stress and inhibited aldehyde dehydrogenase activity. Moreover, monensin and salinomycin reduced androgen receptor signalling and steroidogenesis, enforced cell differentiation and reduced the overall levels of cancer stem cells. Taken together, novel and potentially prostate cancer-selective therapeutic agents were identified in this study, including the description of a multitude of intoxicating mechanisms such as those relating to oxidative stress. The results provide novel insights into prostate cancer biology and exemplify useful means of considering novel approaches to cancer treatment.

Pluripotency and genetic stability of human pluripotent stem cells

Pluripotent cells have the potential to differentiate into all somatic cell types. As the adult human body is unable to regenerate various tissues, pluripotent cells provide an attractive source for regenerative medicine. Human embryonic stem cells (hESCs) can be isolated from blastocyst stage embryos and cultured in the laboratory environment. However, their use in regenerative medicine is restricted due to problems with immunosuppression by the host and ethical legislation. Recently, a new source of pluripotent cells was established via the direct reprogramming of somatic cells. These human induced pluripotent stem cells (hiPSCs) enable the production of patient specific cell types. However, numerous challenges, such as efficient reprogramming, optimal culture, directed differentiation, genetic stability and tumor risk need to be solved before the launch of therapeutic applications. The main objective of this thesis was to understand the unique properties of human pluripotent stem cells. The specific aims were to identify novel factors involved in maintaining pluripotency, characterize the effects of low oxygen culture on hESCs, and determine the high resolution changes in hESCs and hiPSCs during culture and reprogramming. As a result, the previously uncharacterized protein L1TD1 was determined to be specific for pluripotent cells and essential for the maintenance of pluripotency. The low oxygen culture supported undifferentiated growth and affected expression of stem cell associated transcripts. High resolution screening of hESCs identified a number of culture induced copy number variations and loss of heterozygosity changes. Further, screening of hiPSCs revealed that reprogramming induces high resolution alterations. The results obtained in this thesis have important implications for stem cell and cancer biology and the therapeutic potential of pluripotent cells.

PV-1: Leukocyte trafficking molecule and vascular marker

The distinction between lymphatic vessels and blood vessels is a crucial factor in many studies in immunology, vascular biology and cancer biology. They both share several characteristics and perform related, though different functions. They are equally important for the performance of the human immune system with the continuous recirculation of leukocytes from the tissues via lymphatics to the blood vessels and back into the tissue presenting the link between both systems. This study was undertaken to elucidate the differences in the gene expression between primary blood- and lymphatic endothelial cells as well as the two immortalized cell lines HMEC-1 (human microvascular endothelial cell line 1) and TIME (telomerase immortalized microvascular endothelial cell line). Furthermore, we wanted to investigate the mystery surrounding the identity of the antigen recognized by the prototype blood vascular marker PAL-E. In the last step we wanted to study whether the PAL-E antigen would be involved in the process of leukocyte migration from the bloodstream into the surrounding tissue. Our results clearly show that the gene expression in primary blood endothelial cells (BEC), lymphatic endothelial cells (LEC) and the cell lines HMEC-1 and TIME is plastic. Comparison of a large set of BEC- and LEC datasets allowed us to assemble a catalog of new, stable BEC- or LEC specific markers, which we verified in independent experiments. Additionally, several lines of evidence demonstrated that PAL-E recognizes plasmalemma vesicle associated protein 1 (PV-1), which can form complexes with vimentin and neuropilin-1. Finally, numerous in vitro and in vivo experiments identify the first function of the protein PV-1 during leukocyte trafficking, where it acts as regulatory molecule.

Capillary electrophoresis for monitoring of carboxylic, phenolic and amino acids in bioprocesses

Bioprocess technology is a multidisciplinary industry that combines knowledge of biology and chemistry with process engineering. It is a growing industry because its applications have an important role in the food, pharmaceutical, diagnostics and chemical industries. In addition, the current pressure to decrease our dependence on fossil fuels motivates new, innovative research in the replacement of petrochemical products. Bioprocesses are processes that utilize cells and/or their components in the production of desired products. Bioprocesses are already used to produce fuels and chemicals, especially ethanol and building-block chemicals such as carboxylic acids. In order to enable more efficient, sustainable and economically feasible bioprocesses, the raw materials must be cheap and the bioprocesses must be operated at optimal conditions. It is essential to measure different parameters that provide information about the process conditions and the main critical process parameters including cell density, substrate concentrations and products. In addition to offline analysis methods, online monitoring tools are becoming increasingly important in the optimization of bioprocesses. Capillary electrophoresis (CE) is a versatile analysis technique with no limitations concerning polar solvents, analytes or samples. Its resolution and efficiency are high in optimized methods creating a great potential for rapid detection and quantification. This work demonstrates the potential and possibilities of CE as a versatile bioprocess monitoring tool. As a part of this study a commercial CE device was modified for use as an online analysis tool for automated monitoring. The work describes three offline CE analysis methods for the determination of carboxylic, phenolic and amino acids that are present in bioprocesses, and an online CE analysis method for the monitoring of carboxylic acid production during bioprocesses. The detection methods were indirect and direct UV, and laser-induced frescence. The results of this work can be used for the optimization of bioprocess conditions, for the development of more robust and tolerant microorganisms, and to study the dynamics of bioprocesses.

From genotype to phenotype : diversity and population structure of Flavobacterium psychrophilum

Flavobacterium psychrophilum is the etiological agent of bacterial cold-water disease (BCWD) causing high fish mortalities and significant economic losses to the freshwater salmonid aquaculture industry around the world. Today BCWD outbreaks are mainly treated with environmentally hazardous antimicrobial agents and alternative preventative measures are urgently needed in order to ensure the well-being of animals and the sustainability of aquaculture. The diversity of pathogenic bacteria challenges the development of universal control strategies and in many cases the pathogen population structure, i.e. the total genetic diversity of the species must be taken into account. This work integrates the tools of modern molecular biology and conventional phenotypic microbiology to gain knowledge about the diversity and population structure of F. psychrophilum. The present work includes genetic characterization of a large collection of isolates collected from diverse origins and years, from aquaculture in a whole region including different countries, and provides the first international validation of a universal multilocus sequence typing (MLST) approach for unambiguous genetic typing of F. psychrophilum. Population structure analyses showed that the global F. psychrophilum population is subdivided into pathogenic species-specific clones, of which one particular genetic lineage, clonal complex CC-ST2, has been responsible for the majority of BCWD outbreaks in rainbow trout (Oncorhynchus mykiss) in European aquaculture facilities over several decades. Genotypic and phenotypic population heterogeneity affecting antimicrobial resistance in F. psychrophilum within BCWD outbreaks was discovered. Specific genotypes were associated with severe infections in farmed rainbow trout and Atlantic salmon (Salmo salar), and in addition to high adherence, antimicrobial resistance was strongly associated with outbreak strains. The study brought additional support for the hypothesis of an epidemic F. psychrophilum population structure, where recombination is an important force for the generation and maintenance of genetic diversity, and a significant contribution towards mapping the genetic diversity of this important fish pathogen. Evidence indicating dissemination of virulent strains with commercial movement of fish and fish products was strengthened.

Differential evolution based classification with pool of distances and aggregation operators

The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.