Project Details
Projekt Print View

E Pluribus Unum: Understanding and Influencing Pluripotency & Reprogramming by Integrative Bioinformatics

Subject Area Bioinformatics and Theoretical Biology
Term from 2008 to 2015
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 66373205
 
Final Report Year 2014

Final Report Abstract

The SPP 1356 enabled the Rostock medical bioinformatics group to codify knowledge about the functional network underlying pluripotency (PluriNetWork, in mouse and human), to develop and test data analysis pipelines (based on R) and standalone software (ExprEssence, CellFateScout) with a focus on stem cell data, and to engage in intense interdisciplinary collaborations (“Bioinformatics Helpdesk”). The main aim of the software is the highlighting of mechanisms by mapping omics data onto functional networks. Most importantly, network knowledge and data analysis efforts laid the foundation for the group’s current main grant (BMBF-VIP) aimed at the technology transfer of bioinformatics support for small-molecule intervention design to trigger changes of cell fate. For example, CellFateScout revealed that Trichostatin A is the best small molecule to activate pluripotency pathways, based on Connectivity Map and GEO data. “Helpdesk” collaborations exposed the mouse oocyte’s ‘reprogrammome’, i.e. the part of the proteome that is supposed to enable somatic reprogramming. Ageing-related effects on the reprogrammome were also investigated, as well as metabolic constraints, pluripotency biomarkers, and various aspects of gene regulation in stem cells. Work in the context of the “Bioinformatics Helpdesk” turned out to be much more demanding and intense, but also very rewarding in terms of insight and publications. Small-molecule effects became more and more relevant, not least due to a publication by Hou et al (Science 2013) on this topic. Followup-work on ExprEssence also focused more on small molecules than originally planned. The referees’ comment on curated (hypothesis-driven) versus omics (exploratory) data was appreciated, and influenced the development of ExprEssence, to speed it up and apply it to larger networks providing a more unbiased view to begin with. ExprEssence analyses based on integrating network knowledge of mouse and human took longer than expected, and its use for (oocyte) proteomics data is not published yet. For even more omics layers, its use was investigated, but insights were scarce due to the unanticipated difficulties posed by omics data, e.g. the presence of noise that affects different network regions in different layers, thus rendering integration difficult. For analyzing and visualizing time series, the ExprEssence MovieMaker is still unpublished. Method comparison was published for small-molecule effect as well as breast cancer transcriptomics data, and the link to systems biology modelers is still in its infancy.

Publications

 
 

Additional Information

Textvergrößerung und Kontrastanpassung