from arrays to understanding...

3rd CFGBC Symposium

FROM ARRAYS TO UNDERSTANDING DISEASES

June 19, 2008

Ljubljana, Slovenia

CIP - Kataložni zapis o publikaciji Narodna in univerzitetna knjižnica, Ljubljana 577:621.38(063)(082) MEDICINSKA fakulteta (Ljubljana). Inštitut za biokemijo. Center za funkcijsko genomiko in bio-čipe. Symposium (3 ; 2008 ; Ljubljana) From arrays to understanding diseases / 3rd CFGBC Symposium, Ljubljana, June 19th, 2008 ; [edited by Aljoša Bavec]. - Ljubljana : Faculty of Medicine, 2008 ISBN 978-961-6264-98-3 1. Bavec, Aljoša 239371776

3rd CFGBC Symposium FROM ARRAYS TO UNDERSTANDING DISEASES

Organized by Damjana Rozman

Centre for Functional Genomics and Bio-Chips, Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Slovenia

Edited by Aljoša Bavec

Technical Editor Aljoša Bavec

Reviewed by Radovan Komel Jože Pungerčar

Published by Faculty of Medicine, University of Ljubljana, Slovenia

Printed by Ulčakar& JK

Organizing Committee Aljoša Bavec, Petra Hudler, Peter Juvan,

Helena Klavžar, Tadeja Režen, Alja Videtič,

Sponsors of the Workshop Chemass d.o.o.

Agilents Technologies Roche d.d.

Kemomed d.o.o. Mediline d.o.o. Humos d.o.o.

Don Don d.o.o. Union d.d.

Ljubljana, 2008

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CONTENTS

General information about CFGBC vii

Programme xv

Abstracts of Lectures 1 A quantitative understanding of dynamic cellular processes during detoxification 3 in human hepatocytes (Research network within the German HepatoSys Project) Matthias Reuss Effects of PXR activation on liver metabolism in human and mice 4 Tadeja Režen

Microarray analysis in liver tissue of fat and lean mice revealed cholesterol 6 metabolic perturbations Matjaž Simončič

Toxicogenomic in drug safety assessment 8 Drago Kuzman Array-CGH analysis at the Institute of Medical Genetics: 2 years of experience 9 Luca Lovrečić Expression profiling analysis at CBM 10 Pio D’Adamo

Identification of new markers and construction of protein SPRi chip as 12 cancer diagnostic tool Damjana Kastelic Towards understanding lipid-associated disorders and neurodegenerative 14 diseases through functional genomics in yeast Saccharomyces cerevisiae Uroš Petrovič

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3rd CFGBC SYMPOSIUM ─────────────────────────────────────────────────────────────────────────

COMMERCIAL PRESENTATION Studying genomes via a systems biology focused microarray solutions 15 Wim Dorlijn

Integrative and interactive data mining approaches to bioinformatics and 16 systems biology Tomaž Curk

Experiences in data analysis and data warehousing of MA experiments 18 Andrej Blejec Finding differentially expressed genes using microarrays and data filtering: 20 a multiple testing problem. Lara Lusa High throughput SNPs genotyping and isolated populations: 21 a powerful combination to detect moleculas bases of complex and quantitative traits Paolo Gasparini

Abstracts of Posters 23 Steroltalk microarray analysis of statin-treated human primary hepatocytes 25 Juan A. Contreras, Peter Juvan, Katalin Monostory, Jean-Marc Pascussi, Tadeja Režen, Damjana Rozman Differential gene expression in mice exposed neonatally to organophosphorous 27 compound Clormephos Katerina Čeh, Tadeja Režen, Damjana Rozman, Gregor Majdič Regulation of metabolic output genes and circadian regulators by lipids and cAMP 28 Damjana Rozman, Martina Fink, Jure Ačimovič, Marko Goličnik, Rok Košir, Uršula Prosenc, Klemen Španinger, Nataša Debeljak Suppression subtractive hybridization analysis as a tool to gain insight into 30 the genome of a non-model organism Sabina Berne, Ljerka Lah, Branka Korošec, Nada Kraševec, Radovan Komel

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Polymorphisms and mutations in chromosomal segregation genes in Slovenian 31 patients with gastric cancer Petra Hudler, Radovan Komel Sequencing of melanoma susceptibility genes in Slovenian patients with familial 33 cutaneus melanoma Petra Cerkovnik, Barbara Perić, Marko Hočevar, Srdjan Novaković Genetic factors and the susceptibility to osteoporosis in the genetic 35 isolate of Carlantino Alja Videtič, Laura Esposito, Sara Bertok, Uros Hladnik, Sheila Ulivi, Antonella Fabretto, Carmen Lanzara, Francesco Bertoldo, Paolo Gasparini, Adamo Pio d'Adamo Differentially expressed genes in osteoblasts from osteoporotic bone tissue 37 Zoran Trošt, Rihard Trebše, Janez Preželj, Janja Marc

Insight into pathology of ovarian endometriosis with TaqMan® Low Density 39 Array approach Tina Šmuc, Christina Guggenberger, Martina Ribič Pucelj, Jasna Šinkovec, Bettina Husen, Hubert Thole, Pieter Houba, Jerzy Adamski, Tea Lanišnik Rižner

Towards functional systems biology of human cholesterol biosynthesis 41 Peter Juvan, Aleš Belič, Tadeja Režen, Katalin Monostory, Jean-Marc Pascussi, Damjana Rozman

dictyExpress: an interaction-rich web interface to gene expressions of 43 Dictyostelium discoideum Gregor Rot, Tomaž Curk, Anup Parikh, Gad Shaulsky, Aleš Erjavec, Blaž Zupan

Notes 45

Sponsors of the Workshop 51

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GENERAL INFORMATION

ABOUT CFGBC

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GENERAL INFORMATION ABOUT CFGBC ─────────────────────────────────────────────────────────────────────────

From the Slovenian Consortium for Bio-Chips to Centre for Functional Genomics and Bio-Chips

Damjana Rozman, Head of the Centre for Functional Genomics and Bio-Chips, Faculty of Medicine, University of Ljubljana, Slovenia. Email: [email protected] page: http://cfgbc.mf.uni-lj.si/

Introduction Organisms are complex systems where thousands of genes and their products (RNA and proteins) interact with each other and constitute the mystery of life. Genes can be thought of as words in a dictionary of genome, and the procedures for exploring their expression on a large-scale are tools for reading and understanding the book of life. The discovery of DNA structure at 1953 is a landmark of the pre-genome era where genes and their products have been studied by a »single gene – single experiment« approach. At the end the 20th century the first complete genome sequences became available which opened the venue of post-genome era. While the pre-genome period led to numerous detailed information regarding the constituents of the puzzle of life, the post-genome era benefits from the »ome« data and by applying systems biology approaches introduces holistic views on understanding the physiology and the disease. A quick development of novel experimental approaches for the transcriptome, proteome, metabolome and other »ome« analyses required a parallel development of numerous bioinformatic and statistical approaches, which is crucial for extraction of valuable information from the mass of data collected at each experiment. Benefits of the post-genome holistic “added value knowledge” are for example novel biomarkers that are useful as predictors of disease etiology, outcome, and responsiveness to therapy. Slovenian Consortium for Bio-Chips from 2001 - 2008 The Slovenian scientists have joined the world trends of the post-genomic era by organizing a “Slovenian Network for Functional Genomics”. This informal network has been constituted in 2001 at the Institute of Biochemistry, Faculty of Medicine at University of Ljubljana. The aim of the network was a virtual connection of all research groups and laboratories that work in Slovenia in the various fields of functional genomics. In December 2001 the initiators of the network from University of Ljubljana, Faculty of Medicine, Faculty of Pharmacy and the Biotechnical Faculty, called the “kick-off” meeting of the “Slovenian Consortium for Design and Analysis of Bio-Chips” that has been later renamed to the “Slovenian Consortium for Bio-Chips”. The Consortium was joined by the Slovenian academic, research and clinical institutions, as well as by pharmaceutical

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mailto:[email protected]

http://cfgbc.mf.uni-lj.si/


industry (Figure 1). Due to the fact that the neighboring countries to Slovenia at that time already had microarray platforms, the Slovenian researchers believed it is urgent to establish the post-genome infrastructure also in Slovenia. Without this, Slovenian scientists would not be competitive in the basic, applicative and clinical functional genomics research, being also one of the priorities of the EU health research areas. Major goals of the Slovenian Consortium of Bio-Chips were: • to acquire the infrastructure of the novel post-genomic wave, • to establish novel laboratory space for the post-genome technologies, • to train and employ a sufficient number of personnel that could perform experiments

and help with biological interpretations for consortium members as well as for other potential costumers.

By the financial contribution of all Consortium members, the former Ministry of Science, Education and Sports of Slovenia, the Ministry of Economy, The European Structure Funds (ESSR), donators and later the Slovenian Research Agency (ARRS) we have acquired in 2005 the first set of equipment for design and analysis of low-density microarrays. In 2006 the server for data storage and equipment for automatic hybridization of microarrays were purchased and in 2007 the entire track for processing high density microarrays, including the Affymetrix technology became available. Thanks to the great support from the Faculty of Medicine at the University of Ljubljana, novel laboratory space of the »Centre for Functional Genomics and Bio-Chips« (CFGBC, http://cfgbc.mf.uni-lj.si/) has been opened on June 16th 2005. The infrastructure belonging to the Slovenian Consortium for Bio-Chips is located at the CFGBC unit. A time frame of the Consortium activities from 2001 – 2008 is shown on Fig. 2. From the start, the CFGBC personnel performed, in addition to basic research, also research in collaboration with industrial partners and clinical institutions. A formal act »Regulations of the Activities of the Centre for Functional Genomics and Bio-Chips« was signed by all partners in November 2005. The boards of CFGBC, including the Management Board and the Scientific Board, have been established in January 2006. Even if majority of the initial goals of CFGBC have been reached, we continue the progress by working on different projects and by including novel users of the microarray technology to the Consortium. Activities of the Centre for Functional Genomics and Bio-Chips • basic, applicative and clinical post-genomic research funded by the Slovenian

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http://cfgbc.mf.uni-lj.si/


Research Agency, by ESSR, the European Framework Programs, etc. • maintenance of the existing equipment, • acquiring novel equipment of the post-genomic era, • training of students at the undergraduate, graduate and postdoctoral levels.

CFGBC hosts several projects of the Slovenian Consortium for Bio-Chips members. Research is performed mainly by students to complete their undergraduate diplomas, doctoral theses, post-doctoral training or other. One of the important activities of CFGBC is also the promotion and education of the post-genomic technologies in Slovenia, with the focus on microarray technology. We organize seminars within the series of »Scientific Seminars of Faculty of Medicine UL«. In collaboration with Slovenian companies we organize theoretical and practical seminars of the microarray technology products and applications, together with the world leading producers of microarrays. We offer guided tours of the CFGBC for high school students and their teachers as well as for University level students of bio-sciences and medicine, visiting research guests and officials from administration and industries. In 2006 – 2007 activities have been joined to the Slovenian Biochemical Society activities and co-financed by the Ministry of Higher Education. Research and Technology within the call »Promotion of Science«. Centre for Functional Genomics and Bio-Chips is located at Faculty of Medicine, University of Ljubljana. It is a consortium based unit, with a head elected at the Institute of Biochemistry, Faculty of Medicine, and the Management Board from all consortium partners. In 2004 the Centre has been included into the Network of Research and Infrastructure Centers at University of Ljubljana. Several partners of the Slovenian Consortium for Bio-Chips are also partners in the ESSR funded Centre of Excellence »Biotechnology with Pharmacy« and the Technological Platform I-TECHMED.

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PROGRAMME

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PROGRAMME ─────────────────────────────────────────────────────────────────────────

3rd CFGBC Workshop

From arrays to understanding diseases June 19th, 2008

Faculty of Medicine University of Ljubljana

Slovenia 8:00 – 9:00

Registration 9:00 – 9:20 Opening remarks: R. Komel, D. Rozman, guests 9:20 – 9:50

OPENING LECTURE Matthias Reuss, University of Stuttgart, Germany A quantitative understanding of dynamic cellular processes during detoxification in human hepatocytes (Research network within the German HepatoSys Project)

9:50 – 10:10 Tadeja Režen, Faculty of Medicine, University of Ljubljana, Slovenia

Effects of PXR activation on liver metabolism in human and mice

10:10 – 10:30 Matjaž Simončič, Biotechnical Faculty, University of Ljubljana, Slovenia Microarray analysis in liver tissue of fat and lean mice revealed cholesterol metabolic perturbations

10:30 – 10:50

Drago Kuzman, Lek Pharmaceuticals, Ljubljana, Slovenia Toxicogenomic in drug safety assessment

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10:50 – 11:20 Coffee break and posters

11:20 – 11:40

Luca Lovrečić, University Medical Center Ljubljana, Slovenia Array-CGH analysis at the Institute of Medical Genetics: 2 years of experience

11:40 – 12:00

Pio D’Adamo, University of Trieste and CBM, Italy Expression profiling analysis at CBM

12:00 – 12:20 Damjana Kastelic, Faculty of Medicine, University of Ljubljana, Slovenia Identification of new markers and construction of protein SPRi chip as cancer diagnostic tool

12:20 – 12:40

Uroš Petrovič, Institute Jožef Stefan, Ljubljana, Slovenia Towards understanding lipid-associated disorders and neurodegenerative diseases through functional genomics in yeast Saccharomyces cerevisiae

12:40 – 14:00

Free time and posters 14:00 – 14:45 COMMERCIAL PRESENTATION Wim Dorlijn, Agilent Technologies Studying genomes via a systems biology focused microarray solutions

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PROGRAMME ─────────────────────────────────────────────────────────────────────────

14:50 – 15:20 Tomaž Curk, Faculty of Computer and Information Science, University of Ljubljana, Slovenia Integrative and interactive data mining approaches to bioinformatics and systems biology

15:20 – 15:40 Andrej Blejec, National Institute of Biology, Ljubljana, Slovenia

Experiences in data analysis and data warehousing of MA experiments 15:40 – 16:00 Lara Lusa, Faculty of Medicine, University of Ljubljana, Slovenia

Finding differentially expressed genes using microarrays and data filtering: a multiple testing problem.

16:00 – 16:15 Break 16:15 – 16:45

CLOSING LECTURE Paolo Gasparini, University of Trieste, Italy High throughput SNPs genotyping and isolated populations: a powerful combination to detect moleculas bases of complex and quantitative traits

17:00 Closing of the meeting

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ABSTRACTS OF LECTURES

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ABSTRACTS OF LECTURES ─────────────────────────────────────────────────────────────────────────

A quantitative understanding of dynamic cellular processes during detoxification in human hepatocytes (Research network within the German HepatoSys Project) Matthias Reuss University of Stuttgart, Institute of Biochemical Engineering and Centre Systems Biology, University of Stuttgart, Allmandring 31, D – 70569 Stuttgart, Germany

The contribution aims at introducing the German government funding initiative on Systems Biology of Hepatocytes (HepatoSys), thereby focussing at the more detailed description of one of the networks within the initiative coordinated by the University of Stuttgart. The 12 research groups within this network are addressing the issue of detoxification processes in human hepatocytes. The contribution of the individual partners are outlined in the introduction of the lecture. The second part of the contribution focus at more specific results on dynamic modelling of the detoxification system. The detoxification metabolism shows a high inter-individual variability of the enzyme expression level, especially in the phase I catalyzing cytochrome P450 monooxygenases (CYP). This is caused by individual food and drug treatment, sex, age, diseases, or due to the polymorphism resulting in phenotype plasticity. However, the detoxification functionality has to be maintained against these external and internal perturbations, characterizing its robustness. Based on different mathematical models for structure and dynamics of the detoxification system the important issues of structural and dynamic robustness are discussed. Superimposed to the metabolism responsible for the detoxification we also tackle the complex phenomena related to the genetic regulation of the expression of the various enzymes. Based upon time series of transcript data a Boolean/Probabilistic Boolean framework is presented to reconstruct the regulatory networks governing the activity of a specific CYP in response to a specific drug. The final part of the lecture introduces and discuss a new approach of instationary 13C flux analysis for quantitatively describing the metabolic traffic within the central metabolism under different physiological conditions. This flux analysis proved a convenient basis for quantifying cell physiology in terms of engagement of metabolic pathways in overall cellular processes and also in context with detoxification.

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Effects of PXR activation on liver metabolism in human and mice 1Tadeja Režen, 2Katalin Monostory, 3Jean-Marc Pascussi, 1Jure Aćimović, 4Ingemar Björkhem, 1Peter Juvan, 1Damjana Rozman 1Centre for Functional Genomics and Bio-Chips, Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Vrazov trg 2, SI-1000 Ljubljana, Slovenia 2Chemical Research Center, Hungarian Academy of Sciences, Pusztaszeri 59-67, H-1025 Budapest, Hungary 3INSERM U632, 1919 Route de Mende, 34293 Montpellier, France 4Division of Clinical Chemistry, Karolinska University Hospital at Huddinge, S-14186 Stockholm, Sweden

Introduction: Activation of PXR (pregnane X receptor) in the liver has been shown to positively affect cholestasis. However, there are many indications that drugs inducing drug metabolism also affect other liver processes. Therefore, a union of 10 European institutions has joined in the Steroltalk project, which is aimed at deciphering the cross-talk between cholesterol homeostasis and drug metabolism. Different biological models have been used within the project as are knock-out or hyperlipidemic mice and primary human hepatocytes. Several original functional genomics and system biology tools have been developed as are microarrays, in silico model and database. The goal is also to discover new drug targets and therapeutic strategies for treatment of cardiovascular diseases. Results: We have treated mice with PXR activator PCN (pregnenolone-16α-carbonitrile) for 24 hours, and primary human hepatocytes with rifampicin for 12, 24 and 48 hours. Gene expression levels in mouse liver and human hepatocytes were measured using the Steroltalk microarrays1, and selected genes were confirmed using RT-PCR. The sterol profiles in mouse liver and human hepatocytes, and drug-metabolizing activities of hepatocytes were also measured. Transcriptome analysis show that the biggest difference is between 12 hour and 48 hour time-point. This indicates that the primary response to drug and subsequent PXR activation happens before 12 hours, and at 48 hour we observe only secondary effects. The induction of drug metabolizing genes was still increasing at 48 hours, but affect on cholesterol biosynthesis has already diminished. Sterol analyses confirm transcriptome data. Conclusions: This study for the first time elucidates the time-course changes in liver metabolism in the presence of PXR activators, and also exposes the differences between mouse and human PXR.

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Acknowledgements: This abstract and work it concerns was generated in the context of the STEROLTALK project, funded by the European Community as contract No. LSHG-CT-2005-512096. T. Režen and J. Aćimović were supported by graduate fellowships from ARRS. References: 1. Režen T, et al. (2008) BMC Genomics 9:76.

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Microarray analysis in liver tissue of fat and lean mice revealed cholesterol metabolic perturbations 1Matjaž Simončič, 2Damjana Rozman, 2Peter Juvan, 2Tadeja Režen, 3Gregor Fazarinc, 1Simon Horvat 1Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Groblje 3, 1230 Domžale, Slovenia 2Centre for Functional Genomics and Bio-Chips, Faculty of Medicine, University of Ljubljana, Zaloška 4, 1000 Ljubljana, Slovenia 3Institute of Anatomy, Histology and Embriology, Veterinary Faculty, University of Ljubljana, Gerbičeva 60, 1000 Ljubljana, Slovenia

Introduction: Metabolic syndrome in humans stems from interplay between numerous genes and environment whereas sustained mismatch of energy intake and expenditure drives the onset of pathological obesity. Consequently, concomitant serious disorders such as cholesterol metabolic perturbations, diabetes type II and coronary heart disease comprise symptoms of metabolic syndrome. Aiming to model complex genetic architecture of human obesity in animals, a long-term divergent selection experiment on body fat % in mice was initiated in 1980's at the University of Edinburgh (1). As a result of selection for 60 generations, two phenotypically distinct mouse lines were developed having 24% (fat, F-mice) and 4% (lean, L-mice) of body fat. Subsequently, at least four quantitative trait loci (QTLs) were identified to influence fat accretion in this animal model of obesity (2). Methods: In the current study »Steroltalk v2« cDNA microarrays (3) were used to measure expression changes of 321 cholesterogenic genes and others directly or indirectly involved in cholesterol regulation. Data was normalized and further analyzed by Orange (4). Differential expression of liver genes in F and L mice were tested using Student’s t-test. In order to get a thorough insight into metabolic syndrome events, transcriptome analysis was combined with a comprehensive phenotyping of these lines for several obesity-related traits including fat depot sizes, plasma lipoprotein profile, liver triglyceride content and oxidative metabolism of skeletal muscle (SDH-enzyme activity). Results: Several genes participating in de novo cholesterol biosynthesis pathway were identified as differentially expressed in the liver tissue of F and L mice. Furthermore, transcriptional levels of genes encoding nuclear receptors (Ppara, Insig-1), liver receptors (Adipor2, Ldlr) and cluster of genes involved in the uptake of plasma bile acids (Oatp family of transporters) were also shown to be significantly different. Additionally, Abcb11 gene, a potent modulator of cholesterol excretion rate from liver, was differentially expressed between the lines. As this gene maps within the previously identified QTL

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region on chromosome 2, it represents a plausible candidate gene for the causal mutation. Our liver transcriptome results along with the phenotype and plasma lipoprotein data corroborate results in skeletal muscle metabolism, where we identified differential molecular (SDH-enzyme activity) and genetic markers (Il6) of physical activity between our lines. Conclusions: Our study of liver transcriptome in F and L mice points to the fact that metabolic perturbations in our fat mice display strikingly similar pathophysiological mechanisms as observed in obese humans. According to our and previous results (2) Abcb11 gene presents a strong target for further genetic studies where potential functional single nucleotide polymorphisms (SNPs) might be identified. Our future studies at the Slovenian Center for Functional Genomics and Bio-chips involve transcriptome analyses of diet-induced obesity in our model and possible protective effects of antioxidants (vit. E, coenzyme Q) on atherosclerosis with the use of the whole-genome Affymetrix platform. Acknowledgement: This project was supported by the Slovenian Research Agency (ARRS) Young Investigator Grants (Matjaž Simončič and Tadeja Režen) and the project CRP V3-0365, also co-funded by the Slovenian Ministry of Health. The transcriptome analysis was conducted in the context of STEROLTALK project, funded by the European Community as contract No. LSHG-CT-2005-512096 under 6th Framework Programme for Research and Technological Development. References: 1. Sharp G.L. et al. (1984) Genet Res 43: p. 75-92. 2. Horvat S. et al. (2000) Mamm Genome 11: p. 2-7. 3. T. Režen, et al. D. (2008) BMC Genomics 9: 76. 4. Demšar J. et al. (2004) Orange: From Experimental Machine Learning to Interactive

Data Mining, White Paper (http://www.ailab.si/orange), Faculty of Computer and Information Science, University of Ljubljana, Slovenia.

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Toxicogenomic in drug safety assessment

Drago Kuzman Lek Pharmaceuticals d.d., Verovškova 57, SI-1526 Ljubljana, Slovenia

Introduction: Gene expression analysis applied to toxicology studies, also referred to as toxicogenomic, is rapidly being embraced by the pharmaceutical industry as a useful tool to identify safer drugs in a quicker, more cost-effective manner. Studies have already demonstrated the benefits of applying gene expression profiling towards drug safety evaluation, both for identifying mechanisms underlying toxicity, as well as classifying and ranking drug candidates according to toxicity mode of action. Furthermore, the FDA has issued a document, "Guidance for Industry: Pharmacogenomic Data Submissions" (FDA 2005), clearly indicating that the toxicogenomic studies will be soon required for drug and diagnostic registrations. Results/Plans: In Lek pharmaceuticals a platform for conducting toxicogenomic studies is establishing. So far some pilot studies have been performed, such as the global transcriptome analysis of the effects of lovastatin and fenofibrate mouse treatment on hepatic gene expression. Recently, we are evaluating gene markers for genotox prediction. The study is based on Novartis propriety database that includes global trancriptome profiles of known citotoxic and genotoxic compounds. By using bioinformatics tools like SVM and PAMR marker genes have been selected (Figure). To complement gene expression profiling, citotoxic and genotoxic compounds will be assessed by target deconvolution analysis using genetic toolbox containing S. cerevisiae knock-out library. Conclusions: However, it is evident, from researchers and regulators that toxicogenomics in particular will be part of the standard safety package of new drugs in the near future. Additionally, bioinformatic expertise for analysing and interpreting these complex data needs to be evolved and gathered in pharmaceutical companies in order to produce more effective and safer drugs.

Figure: Marker genes for genotox/citotox classification obtained by PAMR analysis.

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Array-CGH analysis at the Institute of Medical Genetics: 2 years of experience 1Luca Lovrečić, 1Borut Peterlin 1Institute of Medical Genetics, Department of Obstetrics and Gynecology, University Medical Center Ljubljana, Zaloška cesta 2, 1000 Ljubljana, Slovenia

Introduction: Array based comparative genomic hybridisation (aCGH) technique for DNA copy number analysis was developed more than a decade ago. On the other hand, only a few centers in Europe use it as a diagnostic tool in the clinical settings. We started using aCGH analysis at the Institute of Medical Genetics two years ago and more than 30 patients have been analysed so far. Here, we present our results and describe three selected cases more thoroughly. Results: Alltogether, 36 microarrays were done using two different whole human genome CGH microarray solutions from Agilent. Twelve samples were analysed on the Human Genome CGH Microarray 44K which has a 24 KB median probe spacing and 24 samples on a high-resolution Human Genome CGH Microarray 105A which has a 18.9 KB median probe spacing. The included patients can be divided into three groups: 1) patients where standard karyotyping showed chromosomal rearrangements, but the method was unable do define which bands are missing; 2) patients with unexplained mental retardation and/or dysmorphic features; 3) special cases. In all cases from group 1 we were able to define the borders of chromosomal rearrangement and have found some previously undescribed deletions. From the second group that included the majority of our patients, we found chromosomal rearrangement in three patients. The third group is still being analysed. Conclusions: Array-CGH analysis is very useful in the cases where standard cytogenetic methods show chromosomal rearrangements, but are unable to define its borders. Even more, the aCGH is clinically useful in the cases where mental retardation and/or dysmorphic features can not be explained using standard genetic tests. Acknowledgements: We thank Dr. Anamarija Brezigar, Dr. Karin Writzl and Dr. Gorazd Rudolf for clinical evaluation of the patients. Also, we thank Alenka Veble for performing standard cytogenetic analysis and dr. Peter Juvan for bioinformatic support.

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Expression profiling analysis at CBM 1,2Pio D’Adamo, 1Simeone Dal Monego, 1Maria D’Amato, 1Roberto Della Marina, 1,2Paolo Gasparini, 1,3Stefano Gustincich, 1Dejan Lazarevic, 1Danilo Licastro, 1Chiara Migliore, 1Francesca Petrera, 1Remo Sanges, 1Elia Stupka. 1CBM S.c.rl., c/o AREA SCIENCE PARK, Basovizza - SS 14, Km. 163,5, 34012 Trieste, Italy 2Unit of Medical Genetics, Department of Reproductive Science and Development, Instituto di Ricovero e Cura a Carattere Scientifico-Burlo Garofalo, University of Trieste, 34127 Trieste, Italy 3The Giovanni Armenise-Harvard Foundation Laboratory, ISAS-SISSA, AREA Science Park, SS 14, Km 163,5, Basovizza, 34012 Trieste, Italy

Introduction: CBM has recently setup a multidisciplinary laboratory which spans across genomics applications such as genotyping, expression profiling, design of custom arrays, profiling from FFPE tissues and from small laser cell dissected cell populations, as well as a complementary bioinformatics team able to analyze and integrate data from this and other laboratories at CBM. In this talk we will provide a quick overview of the services provided at CBM as well as a summary of the results of research in Expression Profiling accomplished within these laboratories. Results: The CBM Genomics & Bioinformatics Labs have produced the following results in Expression Profiling: • Expression profiling from laser cell microdissected dopaminergic neurons. The

utilization of laser cell microdissection on mouse models has been used to produce expression data utilizing Fantom2 cDNA arrays and is being optimized for use with Affymetrix arrays

• Expression profiling from FFPE tissues. Utilizing the Illumina DASL protocol, reliable expression profiling data has been obtained from colorectal cancer tissue obtained from FFPE samples, identifying known as well as novel markers.

• Expression profiling from Custom Combimatrix arrays. Custom arrays were designed to identify specific genomic portions believed to act as novel transcripts based on bioinformatics analysis, and were successfully used to verify expression at several mouse developmental stages

• Analysis and meta-analysis of gene expression data. Meta-analysis is a statistical technique for amalgamating, summarising, and reviewing previous quantitative research. Meta-analysis has been successfully applied at CBM to understand the role of the protein TBP in the regulation and degradation of transcripts during zebrafish embryo development. Novel analysis techniques were also used to identify markers in selected cell populations.

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Conclusions: The CBM genomics and bioinformatics laboratory have undertaken a very diverse set of experiments and techniques and have specialized in developing integrative and custom approaches for the analysis of complex genomics data. References: 2. R.Sanges et al, EMBO J, 2007

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Identification of new markers and construction of protein SPRi chip as cancer diagnostic tool 1,2Damjana Kastelic, 1Nina Kočevar, 3Snježana Frković-Grazio, 4Jože Balažic, 1Radovan Komel, 2Denis Pompon 1Medical Centre for Molecular Biology, Faculty of Medicine, UL, Vrazov trg 2, SI-Ljubljana, Slovenia 2CNRS, Centre de Génétique Moléculaire, Avenue de la terrasse 1, 91190 Gif-sur-Yvette, France 3Institute of Oncology, Zaloška 2, Ljubljana, Slovenia 4Institute of Forensic Medicine, Faculty of Medicine, UL, Korytkova 2, SI-Ljubljana, Slovenia

Introduction: The aim of the project is to design a protein onco-chip usable as a diagnostic tool for the early detection of differential expression patterns of protein constituting specific signatures for stomach adenocarcinoma and its precancerous lesions. The developed protein chips are based on surface plasmon resonance imagery (SPRi) which permits the simultaneous and real time monitoring of several hundreds of protein-protein interactions without need for fluorescent or enzymatic labelling. Results: Topic of the project is defined with two complementary components, one more technological for the development of dedicated protein chips for cancer diagnostic, and the other more fundamental on the search for protein markers specific to the different stages of gastric cancer. Identification of original specific markers for cancer development stages and a collection of corresponding antibodies is targeted. This collection is under development using an original approach involving construction and selection of a Cameleidae heavy chain antibodies (VHH) library. Llama heavy chain antibodies are smaller and more stable than conventional IgG antibodies and are more suitable for immobilisation on the chip surface. Protein extraction of tumourous and control tissue samples were used for immunization of llamas. After immunization response, mRNA was extracted from peripheral blood lymphocytes of treated animals and was further converted to cDNA. Genes coding for variable domains of single chain antibody (VHH) were amplified by PCR using specific primers. These genes were cloned into a prokaryotic phagemid expression vector, thereby constituting the VHH library. The construction of recombinant libraries of VHH involved phagemid vector allowing either free antibody or phages production. Library was differentially screened using healthy and tumorous protein extracts. In parallel the library was also screened for the VHH antibodies, recognizing already known purified cancer markers (p53, Bcl2, VEGF, TGFα). The protein-onco microarray will be built-up with the selected VHHs.

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To establish chip functionalization conditions, different surface chemistries and antibody immobilization techniques were tested using commercially available monoclonal antibodies (IgG). Conclusion: Antibodies giving differential response will be used for affinity purification of corresponding antigens which will be identified by 2D-electrophoresis and mass spectrometry. Developed protein chip will represent valuable prototypes for further development of research or commercial diagnostic chips.

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Towards understanding lipid-associated disorders and neurodegenerative diseases through functional genomics in yeast Saccharomyces cerevisiae 1Mojca Mattiazzi, Katja 1Škerget, 1Petra Kaferle, 1Janez Kokošar, 1Metod Prelec, 1Matej Jereb, 2Tomaž Curk, 1Igor Križaj, 2,3Blaž Zupan, 1Uroš Petrovič 1Department of Molecular and Biomedical Sciences, Jožef Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia 2Faculty of Computer and Information Sciences, University of Ljubljana, Tržaška 25, 1000 Ljubljana, Slovenia3Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA

Transcriptome analysis using DNA microarrays provides insight into phenotypic cellular response closest to the genome. Recent developments in functional genomics have provided additional methods that can analyze phenotype on the same, genomic scale, but from a different perspective. A new data mining approach that combines gene expression and genetic interaction data to infer new and useful hypotheses from such heterogeneous sources of genome-scale experimental data will be presented. The main avenue of the research of our laboratory is dedicated to trying to understand, on the molecular level, regulation of biomembrane homeostasis in eukaryotic cells, with the major aim to understand the pathogenesis of lipid-associated disorders. Transcriptome and genetic interactome data on different agents perturbing the yeast cellular membranes will be shown and discussed, with specific focus on peroxisome perturbation. This same experimental approach is used also in the studies of pathogenic protein aggregation in yeast cells, and the initial work towards trying to understand the molecular mechanisms of protein aggregation toxicity will also be presented. Future directions for using mammalian cells rather than yeast model system for the same level of comprehensive yet accurate hypotheses generation will be examined. This work has been funded by the grants J1-6507 and J2-9699 from the Slovenian Research Agency.

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COMMERCIAL PRESENTATION: Studying genomes via a systems biology focused microarray solutions Wim Dorlijn, Agilent Technologies

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Integrative and interactive data mining approaches to bioinformatics and systems biology 1Tomaž Curk, 1Minca Mramor, 1Janez Demšar, 1Lan Umek, 1Marko Toplak, 1Aleš Erjavec, 1Gregor Rot, 1Gregor Leban, 1,2Blaž Zupan 1Artificial Intelligence Laboratory, Faculty of Computer and Information Science, University of Ljubljana, SI-1000, Ljubljana, Slovenia 2Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, 77030 Houston, Texas, USA

Introduction: Modern bioinformatics approaches that address current problems in systems biology increasingly depend on integration of heterogeneous data and knowledge sources. Additionally, due to the inherent complexity of problems, it is crucial to develop tools that include easy-to-use, graphical interfaces with high degree of interactivity that seamlessly support explorative data analysis and knowledge discovery. Results: Artificial Intelligence Laboratory at University of Ljubljana has in the past years been involved in various projects that include analysis of high-throughput data and besides analyzing gathered data require integration of additional knowledge into the data analysis process. To accommodate for such an analysis, we are developing and applying various methods from data mining to solve problems related to gene expression analysis, promoter sequence analysis, gene set enrichment analysis, epistasis analysis and experiment planning, chemogenomics and drug discovery, and gene-gene interaction analysis for disease susceptibility. The result of this endeavor is a bioinformatics suite implemented as an extension of Orange, a general open-source data mining framework. In Orange the results are presented in a visually rich interface that allows a high degree of interaction and data subset selection.

Figure: A subset of widgets for chemical genomics shown in Orange’s visual programming interface.

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Conclusion: Rich software interfaces and good integration of various data and knowledge sources enable experimentalists to seamlessly navigate through their data and uncover hidden patterns. We believe that good software engineering, together with close collaboration with our partners from biology and genetics will further allow us to be productive in this area and to continue to provide innovative and useful tools. References: 1. Curk T, et al. (2005) Bioinformatics 21(3), pp. 396-8. 2. Mramor M, et al. (2007). Bioinformatics 23(16), pp. 2147-2154.

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Experiences in data analysis and data warehousing of MA experiments Andrej Blejec Department of Biotechnology and Systems biology, National Institute of Biology, Večna pot 111, SI-1000 Ljubljana, Slovenia

Introduction: In the last decade we experienced an enormous increase in popularity of MA experiments in systems biology. Increasing amounts of data are seen as a promise for possible explanation and understanding of links and networks of interrelated systems that *omics are dealing with. Data per se are unfortunately not enough. Even the most sophisticated data analysis techniques cannot reveal the way systems work. Even in single experiment we are facing large amounts of data which raises a questions and problems of presentation in a way that humans are able to absorb. More so since experiences of use of traditional statistical data analysis techniques is known to possibly lead to arguable conclusions. Application of wrong method can give “nicer” results than the appropriate ones. Experimental data are collected in publicly accessible data warehouses and are available for future research, re-analysis, and meta-analyses. The incentive of publishing data in common MIAME compliant formats is something is rather unique and that other disciplines are lacking a similar one. The researchers at the Department of Biotechnology and Systems biology at the National Institute of Biology are aware of that and we will describe some recent experiences and solutions used in our department. Results: So far our department was mostly oriented into the research of plant - pathogen/pest interactions but is also involved in the research of the pollution of the sea and its impact on the marine fish, development of new cancer therapies, and drug discovery and drug production processes. To cope with the variety of research data we are examining the applicability of different MA data analysis approaches and try to develop more robust system [1]. We are working on the development of more efficient visualization of data in their biological context and tailored the MapMan for display of pathways at different level of organization. For practical reasons of distributing data into the publicly available data repositories, we came to conclusion, that we should organize our data in similar way. We started developing the general scheme of local data warehouse that should be simple for manipulation and use, should be compatible in formats of MIAME compliant data bases, should provide easy access to raw, preprocessed and analyzed data, should enable combination of own data and data from public repositories for reanalysis and meta-analysis. The connecting link is data analysis platform R [2], which is the work horse of our data analyses.

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Conclusions: Facing the large amounts of data in MA data analyses and complexity of pathways for biological interpretation one has to be careful in selecting the appropriate methods. Understanding of their limitations or special conditions is crucial for proper analysis. Graphical visualizations of results in connection to the biological context help researchers in understanding of complex biological pathways. Growing amounts of data within laboratories need to be well organized. We are in a process of designing a local repository of experimental data and results, which will enable reanalysis and meta-analyses of combined data from our experiments and publicly available data. To achieve this, we are also working on preparation of truly reproducible research and analyses by use of available systems in R [3]. References: 1. Rotter A, et al. (2008) Omics-A Journal of Integrative Biology, in press 2. R Development Core Team (2008). R: A language and environment for statistical

computing, ISBN 3-900051-07-0. 3. Leisch F (2002) Proceedings in Computational Statistics, pp. 575–580, ISBN 3-7908-

1517-9.

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Finding differentially expressed genes using microarrays and data filtering: a multiple comparison problem Lara Lusa Institute of Biomedical Informatics, Faculty of Medicine, University of Ljubljana, Vrazov trg 2, SI-1104 Ljubljana, Slovenia

Introduction: The aim of many biomedical studies using high throughput technologies is to determine which variables, among the thousands measured, differ between some pre-specified classes or are associated to an outcome. From a statistical point of view, the data from these experiments are problematic because the number of measured variables (genes, miRNAs, SNPs, gene metilation, …) greatly exceeds the number of statistical units (patients, mice, independently grown cell lines); appropriate statistical methods are needed to control the risk of finding false positives results even when one variable at a time is analyzed (multiple comparison problem). Results: We analyzed the effects of an approach that is often used in practice to reduce the multiple comparisons problem, i.e. filtering out the variables that are considered non-informative "before" the analysis to lessen the number of comparisons being performed. We considered different commonly used filtering strategies, some of which, when naively applied, lead to an incorrect control of the number of false positives. We developed a novel method for the combination of the results deriving from a number of filtering strategies and evaluated its properties. Conclusions: In practice, deciding which and how many variables should be filtered out can be highly arbitrary and different filtering strategies result in different features being identified as differentially expressed. Naïve application of some filtering strategies can severely bias the results of the analysis. The novel method that we propose can be used to gain sensitivity in the detection of differentially expressed genes. Acknowledgements: This work is part of a collaborative project with Lisa M. McShane and Edward L. Korn (Biometric Research Branch, National Cancer Institute, National Institutes of Health).

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High-throughput SNPs genotyping and isolated populations: A powerful combination to detect molecular bases of complex and quantitative traits Pio D’Adamo, Carmen Lanzara, Sheila Ulivi, Elisa Bedin, Antonella Fabretto, Veronica Guerci, Falvio Faletra, Cristina Zadro, Paolo Gasparini Medical Genetics, Department of Reproductive Sciences and Development, IRCCS-Burlo Garofolo, University of Trieste, Via dell’Istria 65, 34100 Trieste, Italy

Introduction: Complex and quantitative traits are due to the combined effects of multiple interacting genes and environmental factors. Genetic analyses of complex diseases have not had widespread success due to genetic heterogeneity, phenotype complexity, inadequate statistical and genotyping strategies and small sample size. The identification of genetic and environmental risk factors for complex and quantitative traits can be simplified studying isolated populations since it is expected that an association can be detected with a smaller sample of patients in an inbred population than in a panmictic one, in the presence of a more homogeneous environment and genetic background. Use of these populations has already been proven in identifying associations with complex diseases and quantitative traits. The availability of high-throughput SNPs genotyping platforms such those present at BURLO-CBM genotyping service has made now possible an extensive use of such populations. Results: We have identified, on the basis of their location, history and genealogic data several villages which now are included in the Italian Network of Genetic Isolates (INGI). The villages are Campora and Gioi-Cardile, located in the Cilento National Park, both characterized by 600 inhabitants, Carlantino, a village of 1400 inhabitants located in South-East Italy, Stoccareddo, a village characterized by 400 inhabitants located on the Asiago Highlands, 6 villages in Friuli Venezia Giulia (FVG-Genetic Park Project) for an overall number of approximately 5000 individulas, and 3 villages in Val Borbera (2000 individuals). A huge amount of phenotypic data have been collected as well as genealogical information. Samples are now under analysis with the 370K SNPs arrays from Illumina Discussion: Results so far obtained as respect some common traits such as presbyacusia, taste, osteoporosis, etc. will be presented and discussed. Moreover, the European perspective on population studies as well as on biobanks will be presented and discussed.

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ABSTRACTS OF POSTERS

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ABSTRACTS OF POSTERS ─────────────────────────────────────────────────────────────────────────

Steroltalk microarray analysis of statin-treated human primary hepatocytes 1Juan A. Contreras, 1Peter Juvan, 2Katalin Monostory, 3Jean-Marc Pascussi, 1Tadeja Režen, 1Damjana Rozman 1Centre for Functional Genomics and Bio-Chips, Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Vrazov trg 2, SI-1000 Ljubljana, Slovenia 2Chemical Research Center, Hungarian Academy of Sciences, Pusztaszeri 59-67, H-1025 Budapest, Hungary 3INSERM U632, 1919 Route de Mende, 34293 Montpellier, France

Introduction: Cardiovascular diseases remain one of the major causes of mortality in the developed world. Dependence between cholesterol levels in blood and mortality is clearly established, as well as the positive influence of cholesterol lowering on slower progression of cardiovascular disease. Statins (HMG-CoA reductase inhibitors) inhibit the biosynthesis of cholesterol by the liver, leading to a reduction of the circulating cholesterol. Over a 100 million people are presently on statin treatment worldwide. Although these are still regarded as relatively safe drugs the large volume of population under statin treatment means that several million people suffer from adverse effects, that include myopathias, rhabdomyolysis, etc.,and can even lead to death. The protective effect of statins against cardiovascular episodes goes frequently beyond what can be expected from their cholesterol lowering effect alone, indicating that they have additional mechanisms of action. With the aim to elucidate some of the side effects and alternative ways of action, we study the effects of statins on the gene expression in human primary hepatocytes, by custom Steroltalk microarrays. Results: Human primary hepatocytes where incubated in the presence or absence of Rosuvastatin or Atorvastatin for 12, 24 and 48 hours. Total RNA was isolated, labeled and hybridized to a custom made microarray Steroltalk (Režen T, et al. (2008) BMC Genomics 9:76) that contains probes for 300 genes related to cholesterol, lipid and general metabolism, inflammation, transcription factors, circadian processes, etc. Rosuvastatin and Atorvastatin respectively induced the expression of 25 and 51 genes by more than 2 fold (log2ratio>1, p<0.05 vs untreated controls). As expected, most of the genes known to be regulated by the sterol content of the cells via SREBPs were upregulated by both statins, as well as genes involved in the degradation of these drugs (cytochromes P450). Several apolipoprotein genes (involved in cholesterol transport and metabolism in the blood) were also upregulated (Apolipoproteins C-I, C-III, A-I, A-IV A-V). Besides, a reduced but interesting number of genes unrelated to cholesterol metabolism were upregulated by one or both statins, like the transcription factor PPARD and a levkotriene B4 omega-

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hydroxylase, which can contribute the anti-inflammatory properties postulated for statins. The response time of the cells was different for the two drugs, Thus, while the effect of Rosuvastatin peaked at 24h to decline slightly at 48h, Atorvastatin showed its maximal effect after 48h of treatment. Only Rosuvastatin decreased the expression of 4 genes. Conclusion: We have investigated for the first time the effect of statins on the expression of genes in human primary hepatocytes by means of microarray technology. Genes predicted to be upregulated by statins were indeed overexpressed, confirming the validity of the model. Besides, a reduced but interesting number of unanticipated genes were found to be upregulated by these drugs, which advocates for the more extensive use of this approach to investigate the interactions and effect of statins at the gene expression level. Acknowledgements: This abstract and work it concerns was generated in the context of the STEROLTALK project, funded by the European Community as contract No. LSHG-CT-2005-512096. T. Režen and J. Ačimovič were supported by graduate fellowships from ARRS.

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Differential gene expression in mice exposed neonatally to organophosphorous compound Clormephos 1Katerina Čeh, 2Tadeja Režen, 2Damjana Rozman and 1Gregor Majdič 1Centre for Animal Genomics, Veterinary faculty, University of Ljubljana, Slovenia 2Centre for Functional Genomics and Biochips, Faculty of Medicine, University of Ljubljana, Slovenia

Introduction: Organophosphorous compounds are chemical substances, widely used as pesticides and also as chemical weapons. Their acute mode of action is well known, they inhibit acetylcholine esterase in the central nervous system and at the neuromuscular junction. Some studies in humans exposed to high doses of organophosphorous pesticides revealed also effect on the functioning of the male reproductive system, as well as psychological effects such as depression and anxiety, which most likely occur not due to inhibition of acetylcholine esterase, but through some other, yet unknown mechanism. However, there are no studies reporting long-term effects of exposure to low levels of organophosphorous substances on development of reproductive and nervous system. In our studies we examined development of male reproductive tract and some aspects of brain functioning in adult mice. Adult mice pairs were exposed to low levels (10x and 100x lower than LD50) of clormephos, an organophosphorous compound, before mating and throughout pregnancy. After birth, mothers received Clormephos in drinking water until weaning, and after weaning at 21 days, pups were not exposed any more. Results: Several reproductive parameters such as daily sperm production, seminiferous lumen diameter and seminiferous lumen opening, as well as expression of some markers of testis development were similar between control and treated mice. However, in mice treated neonatally with high dose of Clormephos, we observed increased anxiety – like behavior determined on elevated plus maze test. Microarray analyses were performed using Affymetrix global mouse expression microarrays with brain, testis and liver tissue from 70 days old mice (that were treated neonatally only through the mothers). The results from microarray analyses are still under evaluation. Conclusions: Superficial analyses of brain data revealed some interesting candidates for differences in gene expression caused by Clormephos. These include serotonin 5-1a receptor, known to be involved in anxiotic behavior, and cadherin 7, which is important part of cell junctions including cell junctions in the brain-blood barrier. A detailed expression profile analysis of the brain, liver and testis is needed to reach conclusions regarding the Clormephos neonatal effect on the transcriptome.

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Regulation of metabolic output genes and circadian regulators by lipids and cAMP 1,2Damjana Rozman, 1,2Martina Fink, 2Jure Ačimovič, 2Marko Goličnik, 1,2Rok Košir, 1,2Uršula Prosenc, 1,2Klemen Španinger,

1,2Nataša Debeljak 1Centre for Functional Genomics and Bio-Chips, Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Vrazov trg 2, SI-1000 Ljubljana, Slovenia 2Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Vrazov trg 2, SI-1000 Ljubljana, Slovenia

Introduction: The inter-relationships between circadian rhythm and the metabolism are becoming accepted in medical research. For example, hormones, xenobiotics or disease conditions (hyperlipidemia, cancer) can influence the expression of circadian genes. On the other hand, homeostatic processes that are maintained by different signaling pathways are prone to circadian regulation. Disturbance of a homeostatic process can transform a physiological state into a patophysiological condition. The lipid homeostasis is regulated by the SREBP-mediated feedback loops, by cAMP-signaling and by the circadian rhythm. We investigate the influence of the above three pathways on the model output genes from cholesterol synthesis and study also the role of the cAMP-responsive element modulator CREM on the expression of circadian regulators. CREM is a CRE-binding transcription factor that encodes activators and repressors. The Crem-encoded inducible cAMP early repressor ICER has been implicated in the molecular mechanisms controlling circadian rhythms in mammals. ICER represses its own cAMP-induced transcription and completes the cAMP-CREM feedback loop. Results: In the mouse hepatoma cells cholesterol (SREBP-2 pathway) represses Hmgcr and Cyp51 but linoloeic acid (SREBP-1 pathway) represses only Hmgcr. This indicates that Hmgcr responds to both SREBP signaling pathways while Cyp51 is regulated primarily by SREBP-2. In the wild type mice the expression of cholesterogenic Hmgs, Fpps, Sqs, Cyp51 is minimal between CT12 - CT16 and peaks between CT20 – CT24. Fpps, Sqs and Cyp51 lost the circadian behavior in Crem -/- livers, Hmgs amplitude is diminished. Deletion of Crem results in a phase advance of cholesterol synthesis. The peak of the major regulatory gene Hmgcr is shifted from CT20 in w.t. to CT12-16 in knockouts. Accordingly, the peak of lathosterol/cholesterol, which represents a valuable measure of de novo cholesterol synthesis, is shifted from CT20 in w.t. to CT16. Overexpression of CREMτ and ICER has little effect on the Hmgcr proximal promoter while influences the expression from the CYP51 promoter. The phases of circadian regulators Per1, Per2, Per3, Bmal1 and Dbp seem to remain unchanged in livers of w.t. and Crem -/- mice while the

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amplitude of Per1 is decreased and of Per2 increased. CREMτ transactivates Per1,2 promoters, but surprisingly, ICER does not repress Per2 and even transactivates Per1. Conclusions: We show that isoforms of CREM contribute to the circadian expression in the mouse liver. CREM-mediated circadian expression of cholesterogenic output genes is reflected also on the metabolite level. Biological experiments in progress will add to the statistical power and lead to stronger biological conclusions. Acknowledgements: This work has been generated in the context of the STEROLTALK project LSHG-CT-2005-512096 under 6th Framework Programme. and by ARRS grants P1-0104 and J1-9438. J. Ačimovič, U. Prosenc, K. Španinger and R. Košir are supported by the ARRS graduate fellowships.

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Suppression subtractive hybridization analysis as a tool to gain insight into the genome of a non-model organism 1Sabina Berne, 2Ljerka Lah, 2Branka Korošec, 2Nada Kraševec, 1,2Radovan Komel 1Medical Centre for Molecular Biology, Faculty of Medicine, University of Ljubljana, Vrazov trg 2, SI-1000 Ljubljana, Slovenia 2National Institute of Chemistry, Hajdrihova 19, SI-1000 Ljubljana, Slovenia

Suppression subtractive hybridization (SSH) was employed to study differential gene expression upon progesterone treatment of the filamentous fungus Cochliobolus lunatus, a plant and opportunistic human pathogen. The transcription profile of progesterone-induced vs. non-induced C. lunatus revealed changes in the number of genes involved in facilitated and vesicle mediated transport, amino acid and derivative metabolism, protein biosynthesis, cell wall biogenesis, lipid metabolism, carbohydrate metabolism, and generation of precursor metabolites and energy. These results suggest that progesterone induces a global adaptive stress response in the organism. Such a response is not surprising, as the steroidal ring structure is similar to certain antifungal plant defense compounds. In C. lunatus, the conversion of such molecules to hydroxylated and less-toxic substances is mediated by enzymes of the cytochrome P450 superfamily, however little is known of the genes encoding them. We identified several putative cytochrome P450 cDNA sequences and quantitatively analyzed their relative mRNA levels upon progesterone induction using Real-time RT PCR. None of the selected cytochromes P450 showed significant up-regulation (more than 2 fold induction). As an additional inevitable consequence of the large-scale sequencing of cDNA clones, valuable insight into the genome of this non-model organism was obtained.

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Polymorphisms and mutations in chromosomal segregation genes in Slovenian patients with gastric cancer Petra Hudler, Radovan Komel Medical Centre for Molecular Biology, Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Vrazov trg, SI-1000 Ljubljana, Slovenia

Introduction: Gastric cancer is due to high mortality one of major oncological problems in Slovenia. It is genetically heterogeneous disease and although many genes, probably implicated in its pathogenesis, have been studied, the exact mechanisms of carcinogenesis remain unclear. Studies have shown that genetic changes, lifestyle, age and genetic background of individuals are implicated in its development and progression. The last characteristic, genetic background is largely unknown in Slovenian patients. Recent studies showed that changes in gene expression are not only responsible for development of gastric adenocarcinoma, but also subtle changes in nucleotide sequences of "modifier" genes which do not confer to phenotypic changes. The possible consequences of modified activity of these genes are chromosomal instability and aneuploidy, which are common in several types of cancer, among them also in gastric cancer. Recent studies indicated that various mutations or polymorphisms, found in these genes, could probably induce chromosome aberrations. Plans: We want to identify polymorphisms in selected genes in Slovenian patients with gastric cancer and to compare this group of patients with healthy control group. We will use CGH microarrays (Agilent) for identifying new nucleotide changes in a selected sample of patients. We will also conduct a haplotype analysis on a larger scale, in order to discern information about simultaneous involvement of more polymorphisms in different candidate genes and their possible additive effect on the disease development. We will use restriction fragment length polymorphism analyses, allele determination with AbiPrism™5700 (Applied Biosystems) and high resolution DNA melting (HR-1 melter, Idaho Technology Inc.), followed by sequencing for SNP detection. Conclusions: We expect to gain new information on genetic predisposition for gastric cancer and find new possible cellular targets that may yield broadly applicable therapies. We will introduce detection methods for chromosomal instability into our laboratory and because these techniques are very important in research of genomic changes, they could also be of use for the research of other genetic diseases. Acknowledgments: This study is supported by the ARRS postdoctoral grant to Petra Hudler. The authors wish to acknowledge Prof. Stanislav Repše, MD, PhD from the

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Clinical department for the abdominal surgery, University Medical Centre of Ljubljana and Dr. Snježana Frković-Grazio, MD, PhD from the Department for Pathology, Institute of Oncology for providing gastric cancer tissues. References: 1. Castro dIP, et al. (2007) Carcinogenesis, Advance Access. 2. Duesberg PH. (2003) Cancer Genet Cytogenet 143(1), 89-91. 3. Kops GJ, et al. (2005) Nat Rev Cancer 5(10): 773-85.

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Sequencing of melanoma susceptibility genes in Slovenian patients with familial cutaneus melanoma 1Petra Cerkovnik, 2Barbara Perić, 2Marko Hočevar and 1Srdjan Novaković 1Department of Molecular Diagnostics, Institute of Oncology Ljubljana, Zaloška 2, Ljubljana, Slovenia 2Department of Surgical Oncology, Institute of Oncology Ljubljana, Zaloška 2, Ljubljana, Slovenia

Introduction: Cutaneous melanoma (CM) is the most lethal form of all skin cancers. According to epidemiologic studies, the risk of CM is influenced by both genetic and environmental factors. The exposure to UV radiation is the main environmental factor, while genetic basis of CM is complex and appears to involve multiple genes. Two high penetrance melanoma susceptibility genes CDKN2A (cyclin-dependent kinase inhibitor 2A) and CDK4 (cyclin-dependent kinase 4) and low penetrance MC1R (melanocortin receptor 1) gene have been identified. The aim of our study was to determine the prevalence of mutations (variants) in melanoma susceptibility genes among Slovenian patients with familial CM and patients with multiple primary CM. The group of healthy individuals was also included. Results: Using direct sequencing we determined 12 different variants in CDKN2A p16INK4a gene. We identified 7 different mutations in 8 families (among 28 families) with CM (28.7%). Among 40 patients with familial CM there was 37.5% positive for CDKN2A p16INK4a mutation. In group of patients with multiple primary CM, we determined 2 different allelic variants in coding region – 1 polymorphism and 1 unclassified variant in 3/30 patients (10.0%). Two of 54 healthy individuals were identified to have allelic variant in CDKN2A p16INK4a gene. None of these variants were previously described as mutation. In CDK4, the mutations were not detected (in all three tested groups). Analysis of the MC1R gene revealed 14 different variants. The allele frequency was not statistically significant different between patients and healthy individuals, which is in accordance with the reports in other European populations. Conclusions: Since there is still high number of families with unidentified mutation in known melanoma susceptibility genes (71.3%), there is a need to continue with the searching of new melanoma susceptibility genes. Therefore, Institute of Oncology Ljubljana, as a member of GenoMEL (Melanoma Genetics Consortium) is included in searching for genes associated with familial CM using Ilumina Platform. References:

1. Bishop DT, et al. (2002) J of National Cancer Institute 94 (12), pp. 894-903. 2. Harland M, et al. (2008) Eur J of Cancer doi:10.1016/j.ejca.2008.03.005.

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Kanetsky PA, et al. (2004) Cancer Epidemiol Biomarkers Prev 13, pp. 808–19. 3. Zuo L, et al. (1996) Nature Genetics 12, pp. 97-9. 4. Box NF, et al. (2001) Am. J.Hum.Genet. 69, pp. 765-73. 5. Bressac-dePaillerets B, et al. (2002) Biochimie 84, pp. 67-74.

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Genetic factors and the susceptibility to osteoporosis in the genetic isolate of Carlantino 1,2Alja Videtič, Laura Esposito, 3Sara Bertok, 3Uros Hladnik, 3Sheila Ulivi, 3Antonella Fabretto, 3Carmen Lanzara, 4Francesco Bertoldo, 2,3Paolo Gasparini, 2,3Adamo Pio d'Adamo 1Instutute of Biochemistry, Faculty of Medicine, Vrazov trg 2, SI-1000 Ljubljana, Slovenia 2CBM Scrl - Consorzio per il Centro di Biomedicina Molecolare, AREA Science Park, Basovizza - ss.14, km. 163,5, I-34012 Trieste, Italy 3Servizio di Genetica, IRCCS "Burlo Garofolo", via Dell'Istria 65/1, I-34137 Trieste, Italy 4Dipartimento di Scienze Biomediche e Chirurgiche, Universita' di Verona, Italy

Introduction: In 1994, a WHO study group defined osteoporosis as ‘’a systemic skeletal disease characterized by low bone mass and micro-architectural deterioration of bone tissue, with a consequent increase in bone fragility and susceptibility to fractures’’. Osteoporosis is becoming an increasing world burden; it affects more than 75 million people in Europe, Japan and the USA. In Europe the number of women over 50 years of age is projected to increase by 30–40% between 1990 and 2025. Although estimates suggest 50% of the variance in peak bone mass is due to genetics, it is also estimated that 30-50% of the genetic factors that influence bone strength can be affected by environmental factors. The genetically isolated populations (like the village of Carlantino in Italy) so far seem to be a good model to study the heritability of complex diseases (eg. osteoporosis). Results: Blood samples and demographic data were collected from the inhabitants of the genetic isolate Carlantino. DNA samples are currently being genotyped with

HumanCNV370−Duo Genotyping BeadChip slides. Availability of genotypes and

pedigrees will allow us to perform a two-step linkage analysis: i) Cutting the whole

pedigree of Carlantino into small and manageable pedigrees using the software PEDCUT

and jenti. ii) Performance of standard linkage analysis using SOLAR, MERLIN and

SIMWALK2. We will define genomic regions with LOH and CNV using QuantiSNP and

PennCNV that can eventually explain the phenotype. The analysis of pedigrees for the co-

segregation between CNVs or LOHs and bone density will be performed. Currently ~160

individuals are genotyped and preliminary analysis indicates that there are four interesting

loci for bone density on chromosomes 17, 19, 14 and 3.

Conclusions: So far, genome-wide scans are giving good results in identification of risk alleles for complex diseases. Present work on an isolated population is in progress, and it is likely it will lead to more concrete results (and less loci).

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References: 3. Falchi M. et al Bioinformatics 2008 24: 724-726. 4. McCormick RK, (2007) Aletrn Med Rev 12(2), pp. 113-145.

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Differentially expressed genes in osteoblasts from osteoporotic bone tissue 1Zoran Trošt, 2Rihard Trebše, 3Janez Preželj, 1Janja Marc

1Chair of Clinical Biochemistry, University of Ljubljana, Faculty of Pharmacy, Aškerčeva 7, SI-1000 Ljubljana, Slovenia 2Ortopaedic Hospital Valdoltra, Jadranska cesta 31, SI-6280 Ankaran, Slovenia 3Department of Endocrinology, Diabetes and Metabolic Diseases, University Medical Centre Ljubljana, Zaloška 7, SI-1000 Ljubljana, Slovenia

Introduction: Osteoporosis is a systemic disorder of bone metabolism with a strong genetic component (1). Despite intensive research, key genes responsible for osteoporosis have still not been revealed (2). Osteoporosis develops due to an imbalance between bone formation, mediated by osteoblasts, and bone resorption, mediated by osteoclasts. The aim of present work was to analyse the differences between the transcriptomes of osteoblasts from osteoporotic and non-osteoporotic bone tissue. Results: Three postmenopausal patients undergoing hip arthroplasty were enroled in the study. According to heel bone mineral density (BMD) one was osteoporotic (sample 1: heel t-score -3.0; age 70), one nearly osteoporotic (sample 2: heel t-score -2.4; age 72) and one with normal BMD (sample 3: heel t-score +0.2; age 70). Primary osteoblast cultures were prepared from femoral neck trabecular bone explants of each patient. At 90% confluency cells were harvested and RNA was isolated, amplified and labelled for two color microarray experiment. Sample pair »a« were samples 1 and 3, and sample pair »b« were samples 2 and 3. Samples were hybridized on Agilent 44k Whole Human Genome Oligo Microarrays and analyzed with GenePix Pro 6.0, MS Office Excell 2003, NMC Annotation Tool (3) and Reactome Skypainter (4). After normalization of feture intensities and consideration of feature exclusion criteria, 454 features remained in pair »a« (178 showing up-regulation and 276 showing down-regulation) and 567 features remained in pair »b« (290 showing up-regulation and 279 showing down-regulation). COL15A1 was the most up-regulated gene in both pairs (42.2 and 64.9-fold upregulation in pairs »a« in and »b«, respectively). Among the highly up-regulated genes in both pairs were also EGR2 (mean 25.8-fold up-regulation) and PSAT1 (mean 20.4-fold up-regulation). On the other hand, CLDND and APOBEC3D were among the most down-regulated genes in both pairs (mean 15.0 and 13.4-fold down-regulation, respectively). In the biological process ontology, cell cycle, mitosis and cell division were the most frequent annotation terms. Similar results were obtained after the analysis with Reactome Skypainter. Conclusions: Preliminary results indicate that the majority of differentially expressed genes in osteoblasts from osteoporotic bone tissue is involved in mitotic cell division. In

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order to confirm our results, more patients have to be analyzed and the expression of individual genes needs to be measured. References: 5. Liu YJ, et al. (2006) J Bone Miner Res 21(10), pp. 1511-35. 6. Ralston SH (2007) Proc Nutr Soc 66(2), pp. 158-65. 7. Beisvag V, et al. (2006) BMC Bioinformatics 7, pp. 470. 8. Vastrik I, et al. (2007) Genome Biol 8(3), pp. R39.

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Insight into pathology of ovarian endometriosis with TaqMan®

Low Density Array approach 1Tina Šmuc, 2Christina Guggenberger, 3Martina Ribič Pucelj, 3Jasna Šinkovec, 4Bettina Husen, 4Hubert Thole, 5Pieter Houba, 2Jerzy Adamski and 1Tea Lanišnik Rižner

1Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Vrazov trg 2, 1000 Ljubljana, Slovenia 2Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Institute for Experimental Genetics, Genome Analysis Center, Neuherberg, Germany 3 Department of Obstetrics and Gynecology, University Medical Centre, Zaloška 4, 1000 Ljubljana, Slovenia

4 Solvay Pharmaceuticals Research Laboratories, Hannover, Germany and Weesp, The Netherlands

Introduction: Endometriosis, defined as the presence of uterine glands and stroma outside uterine cavity, is a complex disorder. Risk factors for developing this disease are distinctive genetic, environmental and immunological factors. The alternations in the expression levels of specific genes are involved in endometriosis, however the etiology and pathogenesis are not yet fully understood. The aim of our study was to define differentially expressed genes in ectopic compared to eutopic endometrium. Results: 20 premenopausal women were included in the study: 11 patients with ovarian endometriosis stage II to IV and 9 patients with Uterus myomatosus or Myoma uteri. After RNA extraction the expression profiles were examined with TaqMan® Low Density Arrays. The identification of the optimal set of normalization controls was made with GeNorm and the geometric mean of the best three genes (YWHAZ, SDHA, RPL0) was used as a normalization factor. The differences in the expression levels of the selected genes in the tissue samples were analyzed with the Mann-Whitney U test. Regulated genes were found applying the following filter steps: differences in p values of less than 0.05 and the fold change between endometriosis and control group medians more than 3. Of the173 genes studied, 75 genes were differentially expressed, 16 genes were found downregulated and 59 genes were found upregulated in ectopic tissue compared to eutopic. Moreover, based on the existing pathway information genes were arranged in different groups according to biological processes and pathways. Many of the deregulated genes were linked to endometriosis for the first time. Separate evaluation was performed also for the proliferative and the secretory phase, but only 8 genes revealed differences in the expression levels between menstrual phases. Conclusions: Our results show that many biological processes are disturbed in endometriotic tissue, including cell adhesion, cell migration, structural changes of extracellular matrix, steroid metabolism and action, angiogenesis, cancer-related genes, the immune response, and inflammation. Our study also revealed some new potential

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molecular markers and drug targets that may be helpful for the diagnosis and treatment of endometriosis.

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Towards functional systems biology of human cholesterol biosynthesis 1Peter Juvan, 2Aleš Belič, 1Tadeja Režen, 3Katalin Monostory, 4Jean-Marc Pascussi, 1Damjana Rozman 1Centre for Functional Genomics and Bio-Chips, Faculty of Medicine, University of Ljubljana, SI-1000 Ljubljana, Slovenia 2Laboratory of Modelling, Simulation and Control, Faculty of Electrical Engineering, University of Ljubljana, SI-1000 Ljubljana, Slovenia 3Chemical Research Center, Hungarian Academy of Sciences, H-1025 Budapest, Hungary 4INSERM UMR-U632, F-34293 Montpellier, France

Introduction: Within the EU FP6 STEROLTALK project we study the mechanism of cholesterol regulation, its response to drugs and modulations in pathologies. It has long been demonstrated that the level of cholesterol in cells regulates the cholesterol biosynthesis through SREBF transcription factors. Lately it has been shown that other factors are also important as well as their interactions. Many computational tools from the fields of systems biology and functional genomics are available to investigate such biological systems. Combining them we gained broader knowledge of the cholesterol biosynthesis and its regulation (1). Results: To study the cholesterol biosynthesis system we employed and combined mathematical modeling and simulation using differential equations, and inference of genetic interactions using Bayesian approach. We constructed a mathematical model of cholesterol biosynthesis and studied its properties through simulation. We measured transcriptional changes of cholesterogenic genes using the Steroltalk microarray (2) and treated human hepatocyte samples, and employed Bayesian approach to construct gene interaction network from that data. To combine the two approaches we used the mathematical model to simulate gene expression measurements and Bayesian inference to construct gene interaction networks from the simulated data. We compared the simulated networks to the network identified from the microarray measurements and considered various structural changes of the mathematical model. Conclusions: Simulations showed that a large number of perturbations of the system are critical for identification of genetic interactions, and that differences in gene expression between human individuals pose a serious problem. The Bayesian networks obtained from the measured and the simulated data both show that expression of cholesterogenic genes can not be predicted solely from the expression of SREBF2, but the expression of minimum 4 genes is needed, one of them being SREBF2. Networks also indicated a strong genetic interaction between SREBF2 and CYP51A1, but not between SREBF2 and

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HMGCR, the rate-limiting enzyme, whose expression seems to be regulated by other factor(s). We identified a potential transcription factor that may have an important role in regulation of cholesterol biosynthesis, and predicted its regulatory influences. We demonstrated how systems biology and functional genomics tools may be combined to gain novel perspective of a biological system of interest. Acknowledgements: The data used for demonstration of the approaches were generated in the context of the STEROLTALK project, funded by the European Community as contract No. LSHG-CT-2005-512096 under the 6th Framework Programme. References: 1. Juvan P, et al. (2008) Acta Chimica Slovenica 55(2), in press. 2. Režen T, et al. (2008) BMC Genomics 9(76).

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dictyExpress: an interaction-rich web interface to gene expressions of Dictyostelium discoideum 1Gregor Rot, 1Tomaž Curk, 2Anup Parikh, 2Gad Shaulsky, 1Aleš Erjavec, 1,2Blaž Zupan 1Artificial Intelligence Laboratory, Faculty of Computer and Information Science, University of Ljubljana, SI-1000, Ljubljana, Slovenia 2Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, 77030 Houston, Texas, USA

Introduction: Web-based interfaces to bioinformatics data bases have always been highly appreciated by the biomedical community, but only recently has the technology evolved to enable us in designing the systems that aside mere data retrieval support also interaction and explorative data analysis. For the community involved in research of the social amoeba Dictyostelium discoideum, the central server is www.dictybase.org, providing sequence, annotation and additionally also gene expression information. The latter is available on the page that shows detailed information of a specific gene, and is presented in the form of a graph showing the wild-type gene expression during the time course of 24 hour development. The information provided in this way is static, does not allow the user to visualize expression of several genes at the time, and given the state of technology, could be significantly improved.

Figure: Snapshot of dictyExpress rendering information on five genes from pkaR knock-out mutant. Results: We have developed dictyExpress, an interactive web-based (client) application that accesses Baylor College of Medicine’s expression database and analytical server with an interface to Orange data mining suite. dictyExpress renders the data in different ways to support basic data exploration and analysis. Client application was developed in Adobe’s Flex and runs in the Flash player. It supports data retrieval, gene selection, display of

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http://www.dictybase.org/


expression time courses, gene ontology enrichment analysis, hierarchical clustering, and retrieval of genes correlated with a given target profile, which can also be hand-drawn by the user. Conclusion: dictyExpress is in the stage of the final ntesting, its production version and availability to Dictyostelium community is planned for the summer 2008. The application can be easily adapted to host data from other gene expression data bases. References: 1. Chisholm RL (2006) Nucleic Acids Res. 34 (Database issue): D423-7. 2. Curk T, et al. (2005) Bioinformatics 21(3), pp. 396-8.

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from arrays to understanding...

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