E Pluribus Unum: Understanding and Influencing Pluripotency & Reprogramming by Integrative Bioinformatics
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
- ExprEssence—revealing the essence of differential experimental data in the context of an interaction/regulation network. BMC Syst Biol. 2010 Nov 30;4:164
Warsow G, Greber B, Falk SS, Harder C, Siatkowski M, Schordan S, Som A, Endlich N, Schöler H, Repsilber D, Endlich K, Fuellen G
(See online at https://doi.org/10.1186/1752-0509-4-164) - The PluriNetWork: an electronic representation of the network underlying pluripotency in mouse, and its applications. PLoS One. 2010 Dec10;5(12):e15165
Som A, Harder C, Greber B, Siatkowski M, Paudel Y, Warsow G, Cap C, Schöler H, Fuellen G
(See online at https://doi.org/10.1371/journal.pone.0015165) - Evolution of gene regulation--on the road towards computational inferences. Brief Bioinform. 2011 Mar;12(2):122-31
Fuellen G
(See online at https://doi.org/10.1093/bib/bbq060) - Learning biomarkers of pluripotent stem cells in mouse. DNA Res. 2011;18(4):233-51
Scheubert L, Schmidt R, Repsilber D, Lustrek M, Fuellen G
(See online at https://doi.org/10.1093/dnares/dsr016) - Proteomic Analysis of Mouse Oocytes Reveals 28 Candidate Factors of the "Reprogrammome". J Proteome Res. 2011 May 6;10(5):2140-53
Pfeiffer MJ, Siatkowski M, Paudel Y, Balbach ST, Baeumer N, Crosetto N, Drexler HC, Fuellen G, Boiani M
(See online at https://doi.org/10.1021/pr100706k) - Visualization and exploration of conserved regulatory modules using ReXSpecies 2. BMC Evol Biol. 2011 Sep 24;11:267
Struckmann S, Esch D, Schöler H, Fuellen G
(See online at https://doi.org/10.1186/1471-2148-11-267) - Derivation of an interaction/regulation network describing pluripotency in human. Gene. 2012 Jul 10;502(2):99-107
Som A, Lustrek M, Singh NK, Fuellen G
(See online at https://doi.org/10.1016/j.gene.2012.04.025) - Mitochondrial physiology and gene expression analyses reveal metabolic and translational dysregulation in oocyte-induced somatic nuclear reprogramming. PLoS One. 2012;7(6):e36850
Esteves TC, Psathaki OE, Pfeiffer MJ, Balbach ST, Zeuschner D, Shitara H, Yonekawa H, Siatkowski M, Fuellen G, Boiani M
(See online at https://doi.org/10.1371/journal.pone.0036850) - Nuclear reprogramming: kinetics of cell cycle and metabolic progression as determinants of success. PLoS One. 2012;7(4):e35322
Balbach ST, Esteves TC, Houghton FD, Siatkowski M, Pfeiffer MJ, Tsurumi C, Kanzler B, Fuellen G, Boiani M
(See online at https://doi.org/10.1371/journal.pone.0035322) - CellFateScout - a bioinformatics tool for elucidating small molecule signaling pathways that drive cells in a specific direction. Cell Commun Signal. 2013 Nov 8;11(1):85
Siatkowski M, Liebscher V, Fuellen G
(See online at https://doi.org/10.1186/1478-811X-11-85) - Bioinformatics approaches to single-blastomere transcriptomics. Mol Hum Reprod. 2014 Sep 19
Taher L, Pfeiffer MJ, Fuellen G
(See online at https://doi.org/10.1093/molehr/gau083) - Maternal age effect on mouse oocytes: new biological insight from proteomic analysis. Reproduction. 2014 Jul;148(1):55-72
Schwarzer C, Siatkowski M, Pfeiffer MJ, Baeumer N, Drexler H, Wang B, Fuellen G, Boiani M
(See online at https://doi.org/10.1530/REP-14-0126)
