Transcriptional and Epigenetic Regulation of Human CD4+ T Helper Lineage Specification

Activated T helper (Th) cells have ability to differentiate into functionally distinct Th1, Th2 and Th17 subsets through a series of overlapping networks that include signaling and transcriptional control and the epigenetic mechanisms to direct immune responses. However, inappropriate execution in the differentiation process and abnormal function of these Th cells can lead to the development of several immune mediated diseases. Therefore, the thesis aimed at identifying genes and gene regulatory mechanisms responsible for Th17 differentiation and to study epigenetic changes associated with early stage of Th1/Th2 cell differentiation. Genome wide transcriptional profiling during early stages of human Th17 cell differentiation demonstrated differential regulation of several novel and currently known genes associated with Th17 differentiation. Selected candidate genes were further validated at protein level and their specificity for Th17 as compared to other T helper subsets was analyzed. Moreover, combination of RNA interference-mediated downregulation of gene expression, genome-wide transcriptome profiling and chromatin immunoprecipitation followed by massive parallel sequencing (ChIP-seq), combined with computational data integration lead to the identification of direct and indirect target genes of STAT3, which is a pivotal upstream transcription factor for Th17 cell polarization. Results indicated that STAT3 directly regulates the expression of several genes that are known to play a role in activation, differentiation, proliferation, and survival of Th17 cells. These results provide a basis for constructing a network regulating gene expression during early human Th17 differentiation. Th1 and Th2 lineage specific enhancers were identified from genome-wide maps of histone modifications generated from the cells differentiating towards Th1 and Th2 lineages at 72h. Further analysis of lineage-specific enhancers revealed known and novel transcription factors that potentially control lineage-specific gene expression. Finally, we found an overlap of a subset of enhancers with SNPs associated with autoimmune diseases through GWASs suggesting a potential role for enhancer elements in the disease development. In conclusion, the results obtained have extended our knowledge of Th differentiation and provided new mechanistic insights into dysregulation of Th cell differentiation in human immune mediated diseases.

Application of RNAi to silence tartrate-resistant acid phosphatase: unexpected effects on the monocyte-macrophage lineage

Tartraatti-resistentin happaman fosfataasin hiljentäminen RNAi menetelmällä: odottamaton vaikutus monosyytti-makrofagi linjan soluissa RNA interferenssi (RNAi) eli RNA:n hiljentyminen löydettiin ensimmäisenä kasveissa, ja 2000-luvulla RNAi menetelmä on otettu käyttöön myös nisäkässoluissa. RNAi on mekanismi, jossa lyhyet kaksi juosteiset RNA molekyylit eli siRNA:t sitoutuvat proteiinikompleksiin ja sitoutuvat komplementaarisesti proteiinia koodaavaan lähetti RNA:han katalysoiden lähetti RNA:n hajoamisen. Tällöin RNA:n koodaamaa proteiinia ei solussa tuoteta. Tässä työssä on RNA interferenssi menetelmän avuksi kehitetty uusi siRNA molekyylien suunnittelualgoritmi siRNA_profile, joka etsii lähetti RNA:sta geenin hiljentämiseen sopivia kohdealueita. Optimaalisesti suunnitellulla siRNA molekyylillä voi olla mahdollista saavuttaa pitkäaikainen geenin hiljeneminen ja spesifinen kohdeproteiinin määrän aleneminen solussa. Erilaiset kemialliset modifikaatiot, mm. 2´-Fluoro-modifikaatio, siRNA molekyylin riboosirenkaassa lisäsivät siRNA molekyylin stabiilisuutta veren plasmassa sekä siRNA molekyylin tehokkuutta. Nämä ovat tärkeitä siRNA molekyylien ominaisuuksia kun RNAi menetelmää sovelletaan lääketieteellisiin tarkoituksiin. Tartraatti-resistentti hapan fosfataasi (TRACP) on entsyymi, joka esiintyy luunsyöjäsoluissa eli osteoklasteissa, antigeenejä esittelevissä dendiriittisissä soluissa sekä eri kudosten makrofageissa, jotka ovat syöjäsoluja. TRACP entsyymin biologista tehtävää ei ole saatu selville, mutta oletetaan että TRACP entsyymin kyvyllä tuottaa reaktiivisia happiradikaaleja on tehtävä sekä luuta hajoittavissa osteoklasteissa sekä antigeenia esittelevissä dendriittisissä soluissa. Makrofageilla, jotka yliekpressoivat TRACP entsyymiä, on myös solunsisäinen reaktiivisten happiradikaalien tuotanto sekä bakteerin tappokyky lisääntynyt. TRACP-geenin hiljentämiseen tarkoitetut spesifiset DNA ja siRNA molekyylit aiheuttivat monosyytti-makrofagilinjan soluviljelymallissa TRACP entsyymin tuoton lisääntymistä odotusten vastaisesti. DNA ja RNA molekyylien vaikutusta TRACP entsyymin tuoton lisääntymiseen tutkittiin myös Tolllike reseptori 9 (TLR9) poistogeenisestä hiirestä eristetyissä monosyyttimakrofaagisoluissa. TRACP entsyymin tuoton lisääntyminen todettiin sekvenssistä ja TLR9:stä riippumattomaksi vasteeksi solun ulkopuolisia DNA ja RNA molekyylejä vastaan. Havainto TRACP entsyymin tuoton lisääntymisestä viittaa siihen, että TRACP entsyymillä on tehtävä solun immuunipuolustusjärjestelmässä.

Herpes simplex virus type 1 (HSV-1) pathogenesis and HSV gene therapy of experimental autoimmune encephalomyelitis

The aim of this thesis was to develop new herpes simplex virus (HSV) vectors for gene therapy of experimental autoimmune encephalomyelitis (EAE), the principal model of multiple sclerosis (MS), and to study the pathogenesis of wild-type HSV-1 and HSV-1 vectors in vivo. By introducing potential immunomodulatory factors into mice with EAE we strived to develop therapies and possibly find molecules improving recovery from EAE. We aimed at altering the immune response by inducing favorable Th2-type cytokines, thus shifting the immune response from a Th1- or a Th17-response. Our HSV vector expressing interleukin (IL)-5 modulated the cytokine responses, decreased inflammation and alleviated EAE. The use of a novel method, bacterial artificial chromosome (BAC), for engineering recombinant HSV facilitated the construction of a new vector expressing leukemia inhibitory factor (LIF). LIF is a neurotropic cytokine with broad functions in the central nervous system (CNS). LIF promotes oligodendrocyte maturation and decreases demyelination and oligodendrocyte loss. The BAC-derived HSV-LIF vector alleviated the clinical symptoms, induced a higher number of oligodendrocytes and modulated T cell responses. By administering HSV via different infection routes, e.g. peripherally via the nose or eye, or intracranially to the brain, the effect of the immune response on HSV spread at different points of the natural infection route was studied. The intranasal infection was an effective delivery route of HSV to the trigeminal ganglion and CNS, whereas corneal infection displayed limited spread. The corneal and intranasal infections induced different peripheral immune responses, which might explain the observed differences in viral spread.

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.