BiGCaT Science Cafe
|07 Dec||16:00-17:00||TBA||Nasim Sangani|
|23 Nov||16:00-17:00||TBA||Alexander Koch (PATH)|
|09 Nov||16:00-17:00||TBA||Martina Summer-Kutmon|
|12 Oct||16:00-17:00||UNS50/4.140a||Ryan Miller||Using WikiPathways directional and connectivity information to guide a mathematical model to make predictions about drug combination synergy|
|28 Sep||16:00-17:00||UNS50/4.140a||Lars Eijsen||The multi-omics of stress||Abstract|
|14 Sep||16:00-17:00||UNS50/4.140a||Samar Tareen||From expression data to network modelling – a case study on metabolic flexibility||Abstract|
|13 Jul||16:00-17:00||UNS50/3.142A||Mirella Kalafati||Adipose tissue-gene expression in tissue specific insulin resistance in human obesity||Abstract|
|29 Jun||16:00-17:00||UNS50/4.140a||Amadeo Muñoz García||New insights into the innate immune effects of vitamin D: a meta-analysis of transcriptomics data at pathway level||Abstract||Slides|
|01 Jun||16:00-17:30||UNS50/4.140a||Elisa Cirillo||The system biology concept applied to a secondary analysis of Body Mass Index GWAS data||Abstract||Slides|
|18 May||16:00-17:30||UNS50/4.140a||Denise Slenter||A (FAIR) new view on dataset MTBLS1||Abstract||Slides|
|04 May||16:00-17:30||UNS50/4.140a||Marvin Martens||The future of regulatory risk assessment||Abstract||Slides|
|13 Apr||16:00-17:30||UNS50/4.140a||Ilona Liesenborghs||Challenges to see patterns in reused data; Identifying molecular pathways that characterize the trabecular meshwork tissue of the eye.||Abstract||Slides|
|12 Jan||16:00-17:30||UNS50/4.140a||Friederike Ehrhart||Rett syndrome – a meta study on human raw transcriptomics data||Abstract||Slides|
28 September 2017 – Lars Eijssen
Title: The multi-omics of stress
Within the PRISMO consortium, samples have been collected from Dutch soldiers who have been deployed to Afghanistan. Using blood samples we have analysed the changes in methylation patterns before and after deployment between soldiers who have experienced stressful events and developed Post Traumatic Stress Disorder (PTSD), and those who haven’t developed PTSD after stressful experiences. Genes with methylation changes were biologically characterised and significant differentially methylated regions (DMRs) were extracted after processing and statistical analysis of the data. Genes in the DMRs were further explored by targeted methods and analysis.
Furthermore, other levels of –omics data have been generated, including genetic variations, protein expression, and metabolite abundance. These data sets are currently being processed. Furthermore, transcriptomics profiling of blood samples has been planned for the future. As soon as additional layers of processed data become available, we will explore multivariate and bioinformatics methods to integrate those layers and extract knowledge from the merged data extended with biological information from online resources. Also we will identify potential improvements in the tools and data sources.
In this talk, the findings of the epigenetics studies as well as the future plans will be discussed and there will be plenty room for discussion.
Reference: https://www.ncbi.nlm.nih.gov/pubmed/28630453 – doi: 10.1038/mp.2017.120
14 September 2017 – Samar Tareen
Title: From expression data to network modelling – a case study on metabolic flexibility
Obesity and its co-morbidities, such as insulin resistance and metabolic syndrome, are the chief contributors to a number of chronic diseases including cardiovascular diseases and type 2 diabetes. Therefore, in recent decades, the focus for combating these conditions have moved towards metabolic health, a chief component of which is metabolic flexibility – the ability of the organism to switch between glucose and fatty acids as the primary source of energy substrate in the tricarboxylic acid cycle for cellular respiration. Metabolic inflexibility, a state where this switching is impaired, has long been suspected of contributing to insulin resistance. Here we focus on the infrastructure of metabolic flexibility in the subcutaneous adipose tissue, and see how we can use qualitative models to study the behaviours and patterns in the system.
13 July 2017 – Mirella Kalafati
Title: Adipose tissue-gene expression in tissue specific insulin resistance in human obesity
29 June 2017 – Amadeo Muñoz García
Title: New insights into the innate immune effects of vitamin D: a meta-analysis of transcriptomics data at pathway level
In the last decade a wide range of studies have highlighted a role for vitamin D in human immune responses, but the precise mechanisms by which vitamin D achieves these effects is much less clear. Recent reports have documented regulation of gene expression in immune cells by the active form of vitamin D, 1,25-dihydroxyvitamin D (1,25D), using candidate gene or unbiased genomic screening strategies to provide cell model-specific data. The current study utilised existing gene expression databases from multiple related monocyte models (the THP-1 monocytic cell line (THP-1), monocyte-derived dendritic cells (DCs), and monocytes) to provide a broader perspective on common gene regulatory pathways associated with innate immune responses to 1,25D. A bioinformatic workflow incorporating pathway analysis using Pathvisio and WikiPathways was utilised to compare each set of gene expression data based on pathway level context. Using this strategy, pathways related to the TCA cycle, oxidative phosphorylation and ATP synthesis and metabolism were shown to significantly regulated by 1,25D in each of the repository models (Z scores 3.52 – 8.22). Common regulation by 1,25D was also observed for pathways associated with apoptosis and the regulation of apoptosis (Z scores 2.49 – 3.81). In contrast to the primary culture DC and monocyte models, the THP-1 myelomonocytic cell line showed strong regulation of pathways associated with cell proliferation and DNA replication (Z scores 6.1 – 12.6). VDR expression is common to multiple immune cell types and thus pathway analysis of gene expression using data from multiple related models provides an inclusive perspective of the immunomodulatory impact of vitamin D. In particular, analyses presented here support a fundamental role for active 1,25D as a pivotal regulator of immunometabolism.
01 June 2017 – Elisa Cirillo
Title: The system biology concept applied to a secondary analysis of Body Mass Index GWAS data
Elisa’s talk will explain the current project related to the secondary analysis of BMI GWAS study. She will give an overview of three different projects that combined several types of data (SNPs associated to BMI, pathways, eQTLS and epigenetics information) in order to elucidate the genetic influence of SNPs in obesity.
18 May 2017 – Denise Slenter
Title: A (FAIR) new view on dataset MTBLS1
Metabolights is a database where metabolomic datasets can be stored with the intention that other researchers can (re)use them. In order to test how FAIR (https://www.nature.com/articles/sdata201618) this database is, we performed a review on the first dataset entered in here (MTBLS1), in the hopes of obtaining a new view on this dataset.
4 May 2017 – Marvin Martens
Title: The future of regulatory risk assessment.
In order to decrease costs, lower the animal use and iprove the overall effectiveness of regulatory risk assessment, Adverse Outcome Pathways (AOPs) emerged to fascilitate the descision making in risk assessment. This presentation will serve as an explanation on the concept of AOPs, explaining their general layout, purpose and creation. Besides, the project of Marvin will be introduced on the topic of AOPs.
13 April 2017 – Ilona Liesenborghs
Title: Challenges to see patterns in reused data; Identifying molecular pathways that characterize the trabecular meshwork tissue of the eye.
Ilona would like to discuss the research she is currently performing on 16 different gene expression datasets of healthy eye tissue (more specified, the trabecular meshwork): the methods, the problems we experienced in analysing and combining the data, the ‘solutions’ and the preliminary results.
12 January 2017 – Friederike Ehrhart
Title: Rett syndrome – a meta study on human raw transcriptomics data
Rett syndrome is a rare disorder causing severe intellectual and physical disability. The cause of the disorder is a mutation in one single gene, methyl-CpG binding protein 2 (MECP2). This gene is a multifunctional regulator of gene transcription, translation and epigenetic transcriptional regulation. Purpose of the study was to investigate changed gene expression in human cells with an impaired MECP2 gene to identify the downstream effects. For this we used raw transcriptomics data from five previously published studies. We extracted information about changed gene expression for each of the twelve experimental subgroups and identified the genes and biological pathways which are overlappingly affected by an impaired MECP2 gene using a hypothesis free data-driven approach. We checked the changed gene expression of known downstream targets of MECP2 and found rarely significant changes in the different experimental groups. There were no genes which are changed in all experimental groups but we identified a set of genes which are significantly changed in several transcriptomics datasets but not mentioned in the context of Rett syndrome before. Using pathway and network approaches (including network extension) we found that these genes are involved in several processes and molecular pathways which are known to be affected in Rett syndrome. We suspect these genes to be the links between gene and phenotype pathways.