AMBICON · Automated multi-level modeling of biological systems considering physico-chemical constraints

Automated multi-level modeling of biological systems considering physico-chemical constraints

Predicting the outcome of an observable phenomenon belongs to the key disciplines of natural sciences. While most scientific disciplines can look back to a long tradition of theoretical analysis, such an endeavor has only begun relatively recently within the field of biology. This development has been driven by the increasing availability of high-quality biological information, which nowadays covers a large variety of different data sets across all different levels and scales. This includes genomic information, i.e., the sequence of the DNA that encodes for all genetic functions, transcriptomic data describing the amounts of active mRNA molecules, proteomic data that provides information about proteins and enzymes available, fluxomic data, i.e., the velocities of reactions, metabolomic data, which is the abundance of small molecules within particular cells, and many more. This plethora of data can now be organized into a coherent model that precisely describes the structure of cells and enables computer simulations and analysis of the systems. Building highly detailed computer models of biological systems is a laborious and difficult endeavor. The EU-funded AMBiCon project ("Automated multi-level modeling of biological systems considering physico-chemical constraints") has been established as a collaborative effort between the University of California, San Diego, USA, and the University of Tuebingen, Germany with the aim to develop and provide computational tools that facilitate such efforts. Besides the development of new algorithms and computational tools, this also included education of the fellow, Dr. Andreas Dräger, to independently conducting laboratory work and organizing his own lab space. As a result, progress has been achieved on multiple crucial cornerstones as the following numbers outline: 17 articles were published in reputable scientific journals and two within a Springer encyclopedia on systems biology, two new modeling standards were released for the file format SBML (Systems Biology Markup Language), 19 software releases were developed, including new software and improved versions of existing tools. In order to disseminate the results and findings of this project, the fellow taught three classes over the course of the project and participated in 15 international conferences and meetings, thereby giving talks, presenting posters or educating other fellows. Dr. Dräger contributed to establishing the new scientific Special Interest Group (SIG) SysMod about systems modeling as part of the ISMB (annual international conference on Intelligent Systems in Molecular Biology). The scholar was awarded for his presentation skills by the F1000 journal and obtained a gold medal for mentoring a group of students at UC San Diego for their participation at the iGEM competition. Finally, Dr. Dräger created the new YouTube channel https://www.youtube.com/channel/UCp7fWtXGFOIjV35u7ONiVbg with animation videos about this project, which make the achievements of this project available to a broader audience. The scientific community elected Dr. Andreas Dräger as an editor for the development of the SBML standard. In this role, he actively contributed to the specification of an improved standard for constraint-based models in SBML, leading to a new version of the flux-balance constraint package. This new standard was directly adopted by the leading software developers in the field and implemented in both, the COBRA Toolbox for MATLAB as well as COBRApy. He also contributed to the specifications of SBML Level 2 Version 5 and Level 3 Version 2. Dr. Dräger contributed to an application of the new ME model approach (Metabolism and Expression), in which Yang et al. (2015) could for the first time calculate the core proteome of bacterial cells (including E. coli) based on a systems biology approach. This study has gained much attention in media because this new method opens the door to better design genetically engineered organisms for the production of desired substances (see the press releases https://www.uni-tuebingen.de/aktuelles/pressemitteilungen/newsfullview-pressemitteilungen/article/minimalausstattung-fuer-den-mikroorganismus.html and http://www.jacobsschool.ucsd.edu/news/news_releases/release.sfe?id=1790). During this project, Dr. Dräger was able to gain experience in organizing and conducting wet lab experiments. Together with Dr. Neema Jamshidi, Douglas McCloskey, and three undergraduate students, he learned how to process blood samples from eight human donors. DNA profiles were determined, and metabolomics samples were taken from red blood cells, plasma, and platelet fractions under varying conditions. This allows the team to construct personalized models of the donors across multiple cell types and to incorporate genetic regulation into these models. Summarizing, this project yielded promising results on multiple aspects of systems biology. 1) Limitations of existing model representation standards were identified and solved. 2) A new predictive method was developed that allows experimentalists to identify potential bacterial transcription factors for targeted experiments. 3) A new model-based approach has shown that it is possible to calculate the minimal protein equipment of bacterial cells. 4) Personalized blood models across multiple cell types have been prepared. 5) Contributions to a new visualization method for metabolic networks as well as the significantly updated and improved BiGG Models knowledge-base of models were made. 5) Finally, the outcomes of this project were not only published in scientific articles, but also through social media (blog posts, Twitter, Facebook, YouTube) and spread as part of multiple international workshops, conferences, and competitions. For more information, visit the project's website at http://systems-biology.info and watch the video clips available in the YouTube channel https://www.youtube.com/channel/UCp7fWtXGFOIjV35u7ONiVbg. Contact Dr. Andreas Dräger Sand 14 72076 Tübingen Germany E-Mail: draeger@informatik.uni-tuebingen.de Twitter: @dr_drae

Data: CORDIS, © European Union