CIESCI


CIESCI Project Partner Updates

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CIESCI Project Partner Updates (March 2011):

 

IDIBELL Partner Update:

In order to assess the methylation profile of the skin cancer cell lines we decided to employ the new method called MethylCap, which is based in the use of the methyl binding domain (MBD) of the human MeCP2. We aim to use MethylCap because it has been found from recent investigations that the genomic coverage of MethylCap is higher than other methodologies. MethylCap is also able to detect more DMRs (Differentially Methylated Regions) at comparable sequencing depths. Elution of the captured methylated DNA is done in steps using a salt gradient, which allows stratifying the genome into fractions with different CpG density. The profiles together yield a detailed genome-wide map of methylated regions.

We first have to set up the methodology in our lab, specifically the sonication, the whole genome amplification and validation of enrichment in methylated regions. Once we have checked that these steps are working we are planning to proceed to the next step, hybridization with the Mouse DNA Methylation 385K RefSeq Promoter Arrays from the Nimblegen platform.

 

BIIT Partner Update:

We are putting our efforts to understand different datasets that will be produced from inter-disciplinary epigenetic research. Our first model datasets were provided as public existing data sets until the first project specific data will be generated by partner IDIBELL. The example datasets proposed by IDIBELL researcher Balint Balazs originate from experiments such as DNA methylation analysis, gene expression analysis and chromatin immunoprecipitation analysis. In addition datasets from public repository are also being analyzed. These datasets were generated using different platforms such as Nimblegen, Affymetrics, Agilent arrays and Illumina genome analyzer. The above datasets were analyzed using Bioconductor packages such as affy, Ringo, rMAT, oligo etc. Tools such as MACS, SISSRs and FindPeaks were tested for chip-seq peak identification. To summarize, we are mining the data from epigenetics research, testing different tools and designing workflows for the data analysis.

In the context of other projects BIIT members have been studying histone modifications: how they are correlated with each other, how their changes are correlated with differentiation of immune cells and if its possible to use them for predicting expression of nearby genes. From these projects we have obtained the know-how about the underlying biology, but also technical skills about handling the data and detecting the modifications.

We have developed several bioinformatics tools at BIIT to manage, analyze and visualize large-scale data from gene expression, gene ontologies, biological pathways etc (MEM, g:Profiler, KEGGanim and GraphWeb). These can be accessed from the website http://biit.cs.ut.ee/. If required, the above tools can be customized for epigenetics research. 

Publications: 

Reimand, J.; Arak, T., Vilo, J.:  g:Profiler --- a web server for functional interpretation of gene lists (2011 update)  (submitted to NAR 2011 Web server issue)

 

 

 

SCI-SYM Centre Update:

 

Publications:

 

Shakya, K., O'Connell, M. J., Ruskin, H. J. The landscape for epigenetic/epigenomic biomedical resources, Epigenetics, 7 (9): 982 – 986, 2012. 

Morgan, C. C.*, Shakya, K.*, Webb, A. E., Walsh, T. A., Lynch, M., Loscher, C. E., Ruskin, H. J., O'Connell, M. J. Colon cancer associated genes exhibit signatures of positive selection at functionally important positions, BMC Evol Biol. 2012, 12:114, doi:10.1186/1471-2148-12-114, PMID: 22788692.

Raghavan, K., and Ruskin, H.J., Modeling DNA Methylation Dynamics, in Dr. T. Tatarinova and Dr. O. Kerton, DNA Methylation - From Genomics to Technology, (ISBN-9789535103202, 1st Ed., 3-28), InTech Publications, 2012.

Raghavan, K., Roznovăţ, I., and Ruskin, H.J., Complex Interdependent Epigenetic Signals in Cancer Initiation. CSS Assyst Newsletter, 22, September 2011.

Barat A., Ruskin H.J. A Manually Curated Novel Knowledge Management System for Genetic and Epigenetic Molecular Determinants of Colon Cancer, The Open Colorectal Cancer Journal, 3, pp36-46, 2010.

Perrin, D. and Ruskin, H. J., Cell type-dependent, infection-induced, aberrant DNA methylation in gastric cancer. Journal of Theoretical Biology 264(2):570–577, 2010.

Perrin, D. and Ruskin, H. J. (2010)., Modelling complex epigenetic changes. Epigenetics Europe, 14-15 September 2010, Dublin, Ireland.

Raghavan K., Ruskin, H.J., Perrin, D., Goasmat, F., Burns, J., Computational Micromodel for Epigenetic Mechanisms. PLoS ONE 5(11): e14031. doi:10.1371/journal.pone.0014031, 2010.

Roznovăţ, I. and Ruskin, H.J., A Computational Model for Genetic and Epigenetic Signals in Colon Cancer, Interdisciplinary Sciences: Computational Life Sciences, 5 (3), pp. 175 - 186, 2013. Springer Berlin Heidelberg. DOI: 10.1007/s12539-013-0172-y.

 

Conference Proceedings:

Szczesna, K., Sandoval, J., Modhukur, V., Kull, M., Rajashekar, B., Perrin, D., Barat, A., Raghavan, K., Roznovăţ, I., Huertas, D., Vilo, J. and Ruskin, H.J., "Complexity of Interdependent Epigenetic Signals in Cancer Initiation", Book of abstracts for the "Complexity-NET projects: Interdisciplinary Challenges for Complexity Science" Workshop, European Conference on Complex Systems (ECCS'13), Barcelona, Spain, 16th - 20th of September 2013, pp. 16 - 23.

Roznovăţ, I. and Ruskin, H.J., A Computational Model for Genetic and Epigenetic Signals in Colon Cancer, Proceedings of the 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW), Philadelphia, USA, 4th-7th October 2012, pp. 188 - 195. doi 10.1109/BIBMW.2012.6470302.

Roznovăţ, I. and Ruskin, H.J., Modelling the Genetic and Epigenetic Signals in Colon Cancer using a Bayesian Network, Proceedings of the 12th European Conference on Complex Systems (ECCS'12), Springer Proceedings in Complexity, Brussels, Belgium, 3rd-7th September 2012, pp. 1059-1062. doi 10.1007/978-3-319-00395-5_126.

Raghavan, K. and Ruskin, H.J., Computational Epigenetic Micromodel - Framework for Parallel Implementation and Information Flow. Proceedings of 8th International Conference on Complex Systems 2011 (ICCS) , Boston, USA, June 2011. 

Raghavan, K., Ruskin, H. J., and Perrin, D., Computational analysis of epigenetic information in human DNA sequences. Proceedings of the International Conference on Bioscience, Biochemistry and Bioinformatics, IEEE, 2011.

 

Presentations:

Roznovăţ, I.A. and Ruskin, H.J., Methylation Inhibitors and Carcinogens in an Agent-Based Model for Colon Crypt Dynamics during Cancer Development, UKSim/AMSS 7th European Modelling Symposium (EMS2013), Manchester, UK, 20th-22nd November 2013.

Roznovăţ, I. and Ruskin, H.J., Dynamics of Genetic and Epigenetic Events in a Network-based framework for Colon Cancer Initiation, European Conference on Complex Systems 2013 (ECCS'13), Barcelona, Spain, 16th - 20th September 2013.

Roznovăţ, I. and Ruskin, H.J., Interdependencies of Genetic and Epigenetic Mechanisms in a framework for Colon Cancer Dynamics, Workshop "Young Researchers Network on Complex Systems (YRNCS)", European Conference on Complex Systems 2013 (ECCS'13), Barcelona, Spain, 16th - 20th September 2013.

Szczesna, K., Sandoval, J., Modhukur, V., Kull, M., Rajashekar, B., Perrin, D., Barat, A., Raghavan, K., Roznovăţ, I., Huertas, D., Vilo, J. and Ruskin, H.J., , Complexity of Interdependent Epigenetic Signals in Cancer Initiation, "Complexity-NET projects: Interdisciplinary Challenges for Complexity Science" Workshop, European Conference on Complex Systems 2013 (ECCS'13), Barcelona, Spain, 16th - 20th September 2013, presented by Roznovăţ, I.

Roznovăţ, I. and Ruskin, H.J., Dynamics of Genetic and Epigenetic Signals in Colon Cancer, Poster, Workshop "Young Researchers Network on Complex Systems (YRNCS)", European Conference on Complex Systems 2013 (ECCS'13), Barcelona, Spain, 16th - 20th September 2013.

Roznovăţ, I. and Ruskin, H.J., Interdependencies of Micromolecular Events in a framework for Colon Cancer Dynamics, 3-min-thesis Presentation, SCI-SYM Research Day, DCU, Dublin, Ireland, 11th June 2013.

Roznovăţ, I. and Ruskin, H.J., Ageing and micromolecular events in a Bayesian Network for Colon Cancer, The Virtual Institute of Bioinformatics (VIBE 2012), Dublin, Ireland, 2nd November 2012.

Roznovăţ, I. and Ruskin, H.J., A Computational Model for Genetic and Epigenetic Signals in Colon Cancer, The Fifth International Workshop on Biomolecular Network Analysis (IWBNA), The IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2012), Philadelphia, USA, 4th-7th October 2012.

Roznovăţ, I. and Ruskin, H.J., Bayesian Network for Interdependent Genetic and Epigenetic Signals in Colon Cancer, The 23rd Irish Conference on Artificial Intelligence and Cognitive Science (AICS 2012), Dublin, Ireland, 17th-19th September 2012. 

Roznovăţ, I. and Ruskin, H.J., Modelling the Genetic and Epigenetic Signals in Colon Cancer using a Bayesian Network, ECCS'12 (European Conference on Complex Systems 2012), Brussels, Belgium, 3rd - 7th September 2012.

Roznovăţ, I. and Ruskin, H.J., Complexity of Interdependent Epigenetic Signals in Cancer Initiation, Poster Presentation, Computational Biology and Innovation - PhD Symposium, UCD, Dublin, Ireland, 6th-7th December 2011. 

Shakya, K., O' Connell, M. J. and Ruskin, H. J., Data mining in Colon Cancer Research, Poster Presentation, Computational Biology and Innovation - PhD Symposium, UCD, Dublin, Ireland, 6th-7th December 2011. 

Raghavan, K. and Ruskin, H.J., Computational Epigenetic Micromodel - Framework for Parallel Implementation and Information Flow. International Conference on Complex Systems 2011 (ICCS) , Boston, USA, June 2011.

Raghavan, K., Ruskin, H. J. and Perrin, D., Computational Analysis of Epigenetic Information in Human DNA Sequences. International Conference on Bioscience, Biochemistry and Bioinformatics 2011, February 2011. 

Ruskin, H.J., Perrin, D., Raghavan, K., Goasmat, F., Modelling Complex Epigenetic Changes, Poster Presentation, ECCS 2010, Lisbon, Portugal, September 2010.

Ruskin, H.J., Presentation Brussels Nov. 8th on CIESCI project to ERA-Net Symposium Nov. 9th 2010.

Ruskin, H.J. Presentation at Royal Irish Academy as part of Complexity Science annual event. Nov. 11th 2010.

 

Visits:

Visit to IDIBELL and Spanish partner, December 20th by Sci-Sym centre researcher (A. Barat):

Dr. Ana Barat, from SCI-SYM, met with Manel Esteller and Dori Huertas. Discussions took place on the nature of the data currently available to Sci-Sym modellers, which is predicated on published literature and the creation of their own database, StatEpigen is based on a relational data model and focuses on storing epigenetic/genetic events and their inter-dependencies. Captured and integrated are diverse data, corresponding to different stages of pathology development, with flexibility to include more complex background information. Colon cancer is the initial pathology considered. The IDIBELL team discussed their new cell line work to provide a genome-wide profile of methylation information with a view to obtaining the epigenome signature. This will provide complementary information, since DCU’s StatEpigen focus is population and functional information, while IDIBELL are focused on detailed individual information spanning the genome.

 

Last Updated ( Monday, 09 December 2013 11:17 )
 

Funded by 

     

 

Project Title: Complexity of Interdependent Epigenetic Signals in Cancer Initiation (CIESCI)

 

Link to calendar of events for CIESCI Project

 

Researchers Names and Affiliations:

Heather J. Ruskin (contact) and Dimitri Perrin (contact), Centre for Scientific Computing and Complex Systems Modelling, (Sci-Sym), Dublin City University, Glasnevin, Dublin 9, Ireland.
Manel Esteller (contact) and Dori Huertas (contact), Bellvitge Institute for Biomedical Research, (IDIBELL), Barcelona, Spain.
Jaak Vilo (contact), Bioinformatics, Algorithmics, and Data Mining Research Group (BIIT), Inst. of Computer Science and Estonian Biocenter, University of Tartu, Liivi 2, 50409 Tartu, Estonia

 

Project Overview:

Recent biomedical research has shown that phenotype of living organisms depends on complex interdependent mechanisms, deriving not only from genotypical and environmental, but also from a large set of interactions modifying gene expression without alteration of the DNA sequence, a phenomenon called Epigenetics. Epigenetic mechanisms involve heritable alterations in chromatin structure, (e.g. DNA methylation and histone acetylation), amongst other epigenetic “signatures”. In turn these regulate transcriptional activation of protein- and RNA-encoding genes (gene expression). Epigenetic signals are not observable from raw genomic DNA sequence alone, since they do not involve changes in coding. Nevertheless, these “stable and dynamic alterations” arise during development and cell proliferation and persist through cell division. While information within the genetic material is not changed, instructions for its assembly and interpretation may be.

Alterations in DNA methylation, imprinting and chromatin structure are common in cancer [2-6], and links to epigenetic changes have been established in several cases, e.g. in Wilm's tumour and colon cancer. Epigenetic mechanisms are also studied in other medical fields because of association with obesity, abnormal neural development, mood disorders such as stress vulnerability and bipolar disorder, or risk of heart failure. The balance of DNA methylation is altered in human cancers: there is hypomethylation of repetitive sequences that account for chromosomal instability, and hypermethylation of CpG islands in the promoters of tumour-supressor genes, which is a major event in the origin of many cancers. The key enzymes that regulate the balance of DNA methylation are DNA methylatransferases (DNMTs), which introduce methyl groups to DNA, and methyl-CpG-binding domain proteins (MBDs), which recognize and bind DNA methyl groups. 1 Laboratory research on epigenetic mechanisms is costly, time-consuming, and, of necessity focused on investigation of specific changes. Consequently, technical constraints mean that explanation of system-wide complex interactions is out of reach.

The capability of hybridised models, combining agent-based and network approaches to bridge scale transitions and it is this novel multi-layered approach that we aim to bring to the present problem. Bioinformatics methods: e.g. on management and analysis of massive datasets, in the international context and on development of bioinformatics methods and tools, spanning a range of data types, and novel data being captured by researchers at IDIBELL. Their ground-breaking work, focuses in particular on a comprehensive study of the epigenome-wide profile that integrates DNA methylation and histone modification, as well as chromatin modifier enzymes during different stages of cancer initiation and progression.

Keywords: Complex biomedical system; gene expression; Epigenetics; cancer initiation

 

Project Goals:

The overall objective of this study is, therefore, to investigate the interactions of DNMTs and MBDs, as well as histone modification enzymes, implicated in cancer initiation. This will be achieved through efforts on three interconnected layers, namely:

(A) wet-lab experiments,
(B) bioinformatics assisted analysis,
(C) computer-based modelling.

No such large-scale, inter-disciplinary, efforts on epigenetic research, across multiple scales, have been reported in the scientific literature to date. These three layers are intrinsically interconnected. Hypothesis formulation on correlations between elements of the epigenome profile will result from the first two layers, analysis carried out through layers (B) and (C) will lead to new experiments, while validation of the formulated hypotheses will involve all three layers. Additionally, computer-based modelling of these epigenetic profiles can provide a potent tool to understand and predict how genes are targeted for aberrant methylation. There are four epigenetic mechanisms that modify chromatin structure: DNA methylation, histone modification, histone variants and nucleosome remodeling, and non-coding RNAs. The cancer epigenome is characterised by global changes in DNA methylation and histone modification patterns, as well as altered expression profiles of chromatin-modifying enzymes. However, events that lead to initiation of these epigenetic abnormalities are still not understood.

 

Scientific Track Record of Participants:

 

Manel Esteller and his group at the Bellvitge Institute for Biomedical Research, (IDIBELL), are leaders in research on Epigenetics and cancer, and will take responsibility for work described in layer (A). Their previous work has led to over 50 publications in leading international journals in the last three years, including articles in Nature Genetics, Science, Nucleic Acids Research and Oncogene. Since October 2008, Dr Esteller has been Director of the Cancer Epigenetics and Biology Program of the Bellvitge Institute for Biomedical Research in Barcelona and leader of the Cancer Epigenetics Group.

Jaak Vilo and his group at the University of Tartu have a solid expertise in bioinformatics, in particular in its application to gene expression and regulation data-mining cancer-related studies, and are therefore well-equipped to take care of layer (B). Experience includes gene expression data analysis, biological data mining, combinatorial pattern matching, and software development for biomedical research databases. Existing tools (g:Profiler, MEM, GraphWeb, KEGGanim, FunGenES atlas, ESCD) provide crucial experience, and may also be adapted to the context of this study. Current projects include participation EU FP6 STREP “Colon and Breast cancer Diagnostics” and a NoE ENFIN.

Heather J. Ruskin, Dimitri Perrin and the Sci-Sym Centre at Dublin City University provide well recognised expertise in analysing and modelling complex systems, in particular in the biomedical but also social context, and will focus on layer (C). They are currently developing a multi-approach model of epigenetic changes, (funded by Science Foundation Ireland under the Research Frontiers Program). This study is the first attempt, worldwide, to directly model these interactions, and includes a representation of infection-induced aberrant DNA methylation in gastric cells, developed in collaboration with the National Cancer Center (Tokyo, Japan), and used as a proof of concept for the present proposal.

 

Last Updated ( Monday, 21 February 2011 15:51 )
 
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