Masteroppgaver for bioteknologi

Masteroppgaver for bioteknologi Institutt for biologi - Høsten 2012

Kartlegging av gener som påvirker Fitness Navn på hovedveileder: Navn på biveiledere etc. oppgaven (opptil 60 ord) Grundig beskrivelse (opptil 300 ord) Henrik Jensen Bernt-Erik Sæther og Ingelin Steinsland (Institutt for matematiske fag) Disse to oppgavene vil gi deg en unik mulighet for å lære stateof-the-art genomiske teknikker, og å bruke disse til å besvare spørsmål knytta til økologi og evolusjon i naturlige bestander. Fitness er en kombinasjon av overlevelse og reproduksjon, og måles ofte som bidraget til framtidige generasjoner. Målet med denne oppgava er å bruke data fra et langtidsstudie på gråspurv i tre naturlige populasjoner på Helgelandskysten for å: a) finne ut hvor på kromosomene gener som påvirker fitness ligger, og b) undersøke om noen av disse genene ligger på kjønnskromosomene. Dataene som vil bli brukt er genetisk informasjon på ca 10.000 SNPs fra ca 2.000 gråspurv med kjent slektskapsforhold. Denne informasjonen vil kombinieres med fenotypiske data på fitnessrelaterte trekk i QTL-analyser for å finne ut hvor i genomet slike gener befinner seg. Hovedsakelig vil det inngå analyser av store mengder genetiske data og statistisk modellering, men litt feltarbeid kan også være aktuelt. Lenke 1 Lenke 2 http://www.ntnu.no/ansatte/henrik.jensen http://www.math.ntnu.no/~ingelins/ Bioteknologi, Evolusjonsbiologi og systematikk/taksonomi, Økologi

Climate change, emerging pollutants and reproduction dysfunction in fish: Linking quantifiable measures of climate change with pollution and biological consequences oppgaven (max 300 ord): Augustine Arukwe Marianne Olufsen Emerging pollutants such as perfluorinated organic compounds (PFCs) are notorious environmental contaminants and have been detected globally in wildlife and humans. Particularly, PFCs have received a lot of societal attention because of their unique chemistry (as both water and oil repellent and reduction of surface tension), persistence, bioaccumulation and toxic effects. Because of this unique chemistry, PFCs represent a group of emerging compounds with not wellunderstood toxicological properties. The limited database indicates a need for further studies and most importantly integrating the climate change phenomenon. The increase in the average temperature on the Earth's near-surface air and oceans since the mid-twentieth century and it s projected continuation is generally termed Global warming. Current models predict a global warming of about 1.4-5.8 C between 1990 and 2100. These predictions are based on a wide range of assumption about the main forces driving future emissions that include population growth and technological advances. Increasing global temperature will cause sea levels to rise, and is expected to increase the intensity of extreme weather events and to change the amount and pattern of precipitation. Other effects of global warming include changes in agricultural yields, trade routes, glacier retreat, species extinctions and increases in the ranges of disease vectors and susceptibility of organisms to environmental contaminants. Increases in temperature and carbon dioxide (CO2) are the two most discussed and quantifiable measures of climate change. Increased CO2 concentrations produces lower ph and with overt physiological effects to aquatic animals. Oxygen depletion (or hypoxia) is a phenomenon that occurs in aquatic environments because the concentration of dissolved oxygen (DO; molecular oxygen dissolved in the water) is so low that it becomes detrimental to aquatic organisms, including reductions in biosynthetic processes. The depletion of O2 may result from a number of natural factors, but it is most often seen as a consequence of pollution and eutrophication in which plant nutrients enter a river, lake, or ocean, and phytoplankton blooms are encouraged. Thus, hypoxia is defined as a shortage of oxygen (O2) to <2 ml/l or <2.8 mg/l and is known to be a pressing global problem and a significant portion of world freshwater and marine ecosystem is already affected by hypoxia, including areas in central Norway and the Baltic sea. Furthermore, changes in temperature and hypoxic stress have been shown to affect contaminants distribution in the environment and in organisms through partitioning in different environmental matrixes. Until recently, comprehensive studies aimed at understanding the combined effects of climate change and contaminants on biological processes are lacking and their implications with regard to associations can only be understood through integrated, empirical and systematic research approaches. This project is a research council financed project that will use Atlantic cod in both in vitro and in vivo exprements. 4 master students are needed to focus on respective issues in this project related to lipid homeostasis, biotransformation, oxidative stress and endocrine disruption using biochemical, cellular and molecular methods. Oppgaven passer for: Environmental Toxicology, Cell and Molecular Biology, Biotechnology

Plant innate immunity: Characterizing damage associated molecular patterns (DAMPs) oppgaven (max 300 ord): Atle M. Bones Ralph Kissen Mechanisms used by plants and animals to resist infection show similarities in both structural and strategic aspects, but plants lack mobile defender cells or a somatic adaptive immune system. Instead, they have to rely on their two-layered innate immune system to defend themselves against potential pathogens. The first layer called PAMP-triggered immunity (PTI) is mediated by the perception of pathogen- or microbeassociated molecular patterns (PAMPs or MAMPs) through pattern recognition receptors (PRRs) at the plant cell surface. The second layer is called effector-triggered immunity (ETI) as it consists in the perception by the plant of so-called effectors that successful pathogens produce to overcome PTI. Another hardly characterized group of danger signals able to trigger an innate immune response are damage-associated molecular patterns (DAMPs) originating from the attacked plant itself. The proposed master project(s) will be part of a larger research project in which we will characterize DAMPs in the model plant Arabidopsis thaliana, and will investigate the molecular effects of a group of plant secondary metabolites acting as DAMPs. For this purpose, transgenic Arabidopsis plants will be generated in which we can induce the production of metabolites acting as endogenous danger molecules. The plant s primary immune responses will be monitored at the transcriptional level using microarray technology and at the protein level by a proteomics analysis. Bioinformatics analysis of these transcriptome and proteome changes after triggering the production of DAMPs will provide insights into the affected gene networks and metabolic pathways. The approaches in this master project cover therefore molecular biology (gene cloning, plant transformation, etc.), metabolite profiling, transcriptomics, proteomics, bioinformatics and in silico analysis. Cell and Molecular biology, Biotechnology

Molekylære mekanismer for Kosthold og revmatisk sykdom oppgaven (max 300 ord): Professor Berit Johansen Dr. Astrid Feuerherm, Dr Thuy Nguyen, MSc Randi Sommerfeldt Overvekt medfører forhøyet risiko for livsstilssykdommer, men også revmatiske sykdommer inkludert revmatoid artritt (RA) [1-3]. I tillegg til smerter og stivhet i muskler og ledd, er revmatisk sykdom assosiert med økt dødelighet og høyere forekomst av ulike systemiske komplikasjoner som hjertekarsykdom, osteoporose, infeksjoner og depresjon [4]. RA kjennetegnes av kronisk betennelse i leddhinnen i synoviale ledd. Fibroblastliknende synoviocytter endrer adferd og blir aggressive, invaderende celler som bryter ned underliggende brusk og bein [5, 6]. Hvordan kosthold påvirker denne adferden er ikke kjent. Fettvev kan produsere mer enn 50 cytokiner og andre bioaktive molekyler som deltar i utallige fysiologiske eller patologiske prosesser, inkludert inflammasjon [7, 8]. Insulin er et hormon som skilles ut av β-celler i bukspyttkjertelen i respons til forhøyet blodsukker etter et måltid for å regulere opptaket av glukose til vevet [9]. Noen cytokiner kan hemme insulinsignaliseringen, og kronisk forhøyede cytokinnivå kan dermed føre til insulinresistens [10]. Genregulatoriske effekter av insulin i synoviocytter er så langt ikke kjent. Adipokiner er en underklasse av cytokiner som særlig dannes av fettceller, adipocytter. Flere adipokiner er funnet i endrede nivå i pasienter med revmatisk sykdom, inkludert RA [11, 12]. Om synoviocytter selv produserer adipokiner og hvilke effekter disse har på leddbetennelsen er ikke klarlagt. Cellers adferd og egenskaper er bestemt av cellens genuttrykk. mirna er 19-23 bp lange ikke-kodende enkelttråd-rna som fungerer som negative regulatorer av genuttrykk, og det er beregnet at mirna regulerer opptil 60 % av våre proteinkodende gener [13]. Flere mirna eller mirna-relaterte faktorer er assosiert med RA der endrede nivå er funnet både i blod og leddvæske. Det er derfor interessant å kartlegge mirna-uttrykket i synoviocytter [13]. Aktuelle masteroppgaver: 1) Karakterisering av insulin-signalisering i synoviocytter 2) Karakterisering av adipokiner og adipokin-signalering i synoviocytter 3) Karakterisering av mikro-rna i synoviocytter MBIOT5, MBI-celle/molekylærbiologi

1. Magliano, M., Obesity and arthritis. Menopause Int, 2008. 14(4): p. 149-154. 2. WHO, Global status report on noncommunicable diseases 2010. Description of the global burden of NCDs, their risk factors and determinants., WHO, Editor. 2011. p. 1-176. 3. Kelly, T., et al., Global burden of obesity in 2005 and projections to 2030. International Journal of Obesity, 2008. 32(9): p. 1431-1437. 4. Gabriel, S. and K. Michaud, Epidemiological studies in incidence, prevalence, mortality, and comorbidity of the rheumatic diseases. Arthritis Research & Therapy, 2009. 11(3): p. 229. 5. Kumar, V. and S.L. Robbins, Robbins basic pathology. 2007, Philadelphia: Saunders Elsevier. 6. Bartok, B. and G.S. Firestein, Fibroblast-like synoviocytes: key effector cells in rheumatoid arthritis. Immunological Reviews, 2010. 233(1): p. 233-255. 7. Otero, M., Leptin, from fat to inflammation: old questions and new insights. FEBS Letters, 2005. 579: p. 295-301. 8. Ouchi, N., et al., Adipokines in inflammation and metabolic disease. Nat Rev Immunol. 11(2): p. 85-97. 9. Buse, J.B., et al., Human GLUT4/muscle-fat glucose-transporter gene. Characterization and genetic variation. Diabetes, 1992. 41(11): p. 1436-45. 10. Gregor, M.F. and G.S. Hotamisligil, Inflammatory mechanisms in obesity. Annu Rev Immunol, 2011. 29: p. 415-45. 11. Otero, M., Changes in plasma levels of fat-derived hormones adiponectin, leptin, resistin and visfatin in patients with rheumatoid arthritis. Annals of the Rheumatic Diseases, 2006. 65: p. 1198-1201. 12. Toussirot, E., The contribution of adipose tissue and adipokines to inflammation in joint diseases. Current Medicinal Chemistry, 2007. 14: p. 1095-1100. 13. Duroux-Richard, I., C. Jorgensen, and F. Apparailly, mirnas and rheumatoid arthritis - promising novel biomarkers. Swiss Med Wkly. 141: p. w13175.

Transcription co-factor database oppgaven (max 300 ord): Martin Kuiper Astrid Lagreid - IKM The scientific literature has an enormous amount of information about the function of particular proteins. To make this information easily available to scientists a process of data curation is used, in which biologists read relevant sections of scientific papers and then enter the relevant information into a database. At NTNU we are working on a database with comprehensive information that describes, or annotates the function of transcription factors that are found in humans, mouse and rat. This database will provide a significant help to researchers in the field of gene regulation. In addition, there are also many proteins that can function as transcriptional cofactors. The curation of these proteins can be performed as part of a Masters project. In order to be able to perform the work the student will learn the use of appropriate text mining and text retrieval tools, the use of text curation tools and an introduction to the field of knowledge management. The work itself will start with a list of several hundred potential transcription cofactors and their available annotation today. Based on this list the student will assemble additional information from literature and databases in order to provide further proof about functional annotations for these proteins. The work will most likely result in a scientific publication. Biotechnology / Information Technology

Using text mining tools to extract specific knowledge from PubMed oppgaven (max 300 ord): Martin Kuiper Heri Ramampiaro - IDI The result of a scientific exploration usually is a publication in a scientific journal. A tremendous amount of knowledge is available in the form of this literature, but the details remain largely hidden for computers. It is not possible today for a computer to comprehend natural language with all its intricacies and complex meaning. Thus, it remains a tremendous challenge to find and extract specific knowledge through automated means. For this purpose, many research groups are developing so-called text mining tools that can be deployed to automatically scan through the literature to find specific knowledge. A selection of these tools will be tried to optimise the detection of information about pairs of specific genes or gene products: more particularly the relationship that exists between a protein that is a transcription factor and the target gene that is regulated and expressed through that transcription factor. The results of this automated text mining will be entered into a database and used to asses experimental results. Today s high throughput experiments yield enormous amounts of data, and analysis of these data may provide a large amount of information. The information may lead to the formulation of many different, alternative hypotheses about for instance regulation events that may or may not happen in a particular experiment. It is impossible to experimentally verify all these individual hypotheses one by one, so we are developing an approach to integrate a wide diversity of information to see if this additional knowledge will help to highlight and prioritise particular hypotheses for experimental investigation. Text mining is a procedure that will be deployed to collect relevant information against which hypotheses will be tested. Biotechnology / Integrative Biology / Information Technology

Modelling stress response pathways in Arabidopsis Navn på hovedveileder: Navn på biveiledere etc. oppgaven (opptil 60 ord) Grundig beskrivelse (opptil 300 ord) Lenke 1 Lenke 2 Martin Kuiper Atle Bones Plants have an elaborate gene regulation system to deal with environmental stresses. In this project a comprehensive model of the Arabidopsis stress response pathways will be produced from public data sources, in the network editing and modelling program CellDesigner. Different modules will be defined in this network, covering various abiotic and biotic stresses. The response of the different Arabidopsis pathways will be tested using a series of different Arabidopsis microarray datasets. Plants have to cope with a large variety of environmental stresses like drought, heat, cold, or fungal and insect attacks, just to name a few. In agriculture, these stresses can cause great losses in production of food and feed, and plant stress response is the subject of many studies. Much of the information from these efforts is available in public literature, or in databases. The challenge is to assemble this information in pathway models that can help to understand the dynamics of stress responses. Models lie at the foundation of systems biology, and in this project we will build response models that can be tested against public and laboratory data to check the model s descriptive accuracy. Models will be built in the program CellDesigner, a software program specifically developed for biologists to build network models and analyse them by overlaying for instance microarray data, or use them for computer simulations. The project will have the following phases: -Getting familiar with CellDesigner and the various databases that contain plant stress response information. -Convert appropriate stress response information into CellDesigner models -Identify specific modules in these networks related to stress type, select a module and extensively test it for descriptive and simulation results -Further enhance a module by analysing available literature with the help of text mining tools (ihop, LitInspector) -Further enhance a module by analysing available functional genomics data, based on analysis of descriptive and simulation properties, in the framework of current experiments ongoing in the labs of Kuiper and Bones. www.celldesigner.org www.ntnu.no/systemsbiology Systems Biology

Modelling the links between carbohydrate diet and inflammatory response in humans Navn på hovedveileder: Navn på biveiledere etc. oppgaven (opptil 60 ord) Grundig beskrivelse (opptil 300 ord) Lenke 1 Lenke 2 Martin Kuiper Berit Johansen The student will model the response cascade that link carbohydrate-rich diets to known inflammatory processes. Information will come from public data sources, and a comprehensive model will be generated in the network editing program CellDesigner. Different submodules will be defined, corresponding to different steps in the signalling cascade, and model checking will be done with functional genomics datasets including microarray data. We hypothesise that a carbohydrate-rich diet may cause a major deregulation of hormonal balance, causing both acute and chronic systemic inflammatory reactions mediated by white blood cells; we have preliminary evidence that this is caused by a carbohydrate-rich diet. This project is part of an integrated multidisciplinary systems biology approach to identify the hormones, genes and pathways specifically responding to a dietary carbohydrate reduction. We will use existing small regulatory networks for macrophages, monocytes and dendritic cells that we will extend with public and project data to model onset of inflammatory cascades. We will exploit existing biomodels including those of various kinases (ERK/MAPK, insulin receptor, growth hormone), lipid kinases (ex. PI3K/AKT), JAK/STAT, WNT/B-catenin, transcription factors (NFkB, CREB, SREBP-1c, PPARa and more) pathways. The modeling will be performed with CellDesigner, a pathway editing software developed for biologists. The project has the following phases: -Getting familiar with CellDesigner and the various databases that contain plant stress response information. -Convert appropriate insulin-signaling and inflammatory response information into CellDesigner models -Identify specific modules in these networks related to signaling cascade step, select a module and extensively test it for descriptive and simulation results -Further enhance a module by analysing available literature with the help of text mining tools (ihop, LitInspector) -Further enhance a module by analysing available functional genomics data, based on analysis of descriptive and simulation properties, in the framework of current experiments ongoing in the labs of Kuiper and Johansen. www.celldesigner.org www.ntnu.no/systemsbiology Systems Biology

DNA-based Computing oppgaven (max 300 ord): Martin Kuiper Pauline Haddow The project will be the experimental part of a design and engineering project that is ongoing at the Department of Computer and Information Science of NTNU. In this project, new avenues to use DNA sequences and DNA sequence interactions will be used to emulate computational algorithms. The behaviour of the designed sequences and their interactions will be tested in this Masters project employing a variety of commonly used techniques in DNA sequence-based analysis or detection methods. Among these techniques are hybridisation, DNA tiling-based ligation and specific detection methods to analyse particular hybridisation products. These detection methods may include Atomic Force Microscopy, the use of fluorescent dyes, and specific enzymatic or chemical detection of hybridisation mismatch products. Biotechnology / Information Technology / Synthetic Biology