RNAct · Enabling proteins with RNA recognition motifs for synthetic biology and bio-analytics.

Enabling proteins with RNA recognition motifs for synthetic biology and bio-analytics.

The biological sciences are advancing at breakneck speed, with a flood of unprecedented insights in the functioning and complexity of cells at the molecular level. Even the active engineering of cells is now possible in synthetic biology, where cells can be modified to perform new functions, for example the synthesis of molecules that are otherwise difficult to produce. Synthetic biology promises many such innovations, for example in the field of green energy, and is of crucial importance to the future European bio-economy. Because of the complexity involved, developments in synthetic biology require a tight interplay between large scale experimental bio-data and computational analysis and modelling. One fundamental way to achieve breakthroughs in this field is through the (re-)design of proteins, the molecular machines that make cells work. By manipulating the function of proteins, new components can be created that can then be inserted into cells, giving them new functions such as the synthesis of a small therapeutic molecule. The economic importance is evident: the emerging synthetic biology market, with related analytical approaches, is predicted to reach tens of billions of euros by 2020, with the bio-analytical and protein engineering markets expected to be worth billions of euros at that point. Currently, education and research in this field are concentrated in the US and the UK, and are less well established in continental Europe. An urgent need therefore exists to train European researchers in the expertise that drives innovation in synthetic biology and related bio-analytics approaches, and in particular the ability to solve complex challenges in the design of relevant proteins. This requires interdisciplinary skills covering biology, biochemistry and computational sciences combined with the principles of engineering. With the RNAct project, we provided a training programme that ensured scientists acquired: i) an excellent understanding of both computation and experiment and ii) the ability to solve bio-analytics and synthetic biology challenges at the molecular level. RNAct addressed this need by combining i) a measured consortium of European participants at the forefront of their research with ii) relevant, well-formulated research with bio-analytics and synthetic biology impact. To do so, we focussed on proteins containing RNA Recognition Motifs (RRM) to regulate cells by detecting specific fragments of RNA, the molecules that encode the sequence of proteins. The ability to manipulate these RRMs has wide application potential in bio-analytics and for the creation of synthetic pathways in cells, for example by enabling their activation via small molecule triggers. To achieve this goal, RNAct has provided the most detailed compendium of RRMs and their interactions with RNA to date in the InteR3MDB database, which enabled ‘cracking’ the RRM-RNA binding code for the most common way RNA binds RRMs, encompassed in the RRMscorer tool. In parallel, RRM domains were studied to understand their RNA binding preferences, as well as changing these preferences by modifying RRM. The project enabled the study of RRM-RNA interactions in live microbial cells and importantly demonstrated that it is possible to use RRMs as a tool for synthetic biology. This goal was achieved by incorporating RRMs in bacteria, where they were able to regulate how the bacteria behaved based on an external small molecule trigger. The 10 Early Stage Researchers (ESRs) trained through RNAct worked closely together throughout the project, and therefore acquired proficiency for molecular level work on proteins, with an understanding of both experiment and computation. In combination with the complementary transversal and entrepreneurial skills training they received, the ESRs will be able to constructively contribute to the European bio-economy in both academic and industry settings.

Data: CORDIS, © European Union