A SPATIO-TEMPORAL MAP OF THE DEVELOPMENTAL FLY INTERACTOME

Development, the process by which cells differentiate and divide to create new life is a fascinating process that is governed by the complex interplay between our genes. Careful control of these genes, and more specifically their protein products, by altering their levels and specific nature over time dictates the fate of cells and what tissues they will form. As well as the timing, the location within the cell where a gene is expressed and its protein product is active is also important in determining function. The information needed to solve this puzzle is, in principle, contained within the genome sequence. However, we currently lack the full picture of what happens during the course of development for several reasons: we don't know how much of each gene is expressed at each time point, we don't know which version (isoform) of each gene is expressed, and we don't know which other partner genes each gene interacts with nor where in the cell this happens. Although some of this information is known, much of the relevant knowledge needed to properly understand developmental signalling is missing. Crucially, and perhaps mostly importantly for this proposal, we lack comprehensive data specifically at the *protein* level (where function is really determined).

In this proposal we aim to close the gap, using both experimental and computational post-genome science, to study specific signalling pathways in a model organism (the fruit fly). Importantly, we already have the necessary methods in place to do this, bringing together UK experts in proteomics (both experimental and computational) with fly genomics and signalling experts to tackle this challenge. This includes state-of-the-art bioinformatics tools from groups who lead the way in the annotation of genome sequences and predicting protein function. Importantly, they are now able to consider the "unknowns" discussed above, such as different isoforms and their likely effects on interacting partner proteins.

We will characterise the developmental fly proteome, in terms of the levels, isoforms, interactions and locations of the important signalling proteins in order to generate a developmental spatio-temporal map. This will be a major advance in both developmental biology and genome science, which we hope will form an important resource for all biologists interested in gene function and development, as well as advancing and integrating the technologies needed to study it.

We will perform a comprehensive temporal characterisation of the Drosophila embryonic isoformal proteome, followed by a focused quantitative analysis of the Wnt, RTK and Notch signalling pathway proteome. Using SILAC-IPAC and LOPIT technologies we will characterise the dynamic interactome and subcellular localisation for key signalling pathway components. Proteomics analysis will employ Data Dependent strategies via MuDPIT LC-MS/MS, Data Independent analysis via SWATH-MS and fully quantitative characterisation via QconCAT Selective Reaction Monitoring. Proteomics data will be collected across 12 embryonic timepoints, matching published high coverage RNA-seq data, to provide a community resource of great utility. Along with established in vivo tagged fly lines we will use recombineering technology to generate isoform-specific tagged forms of key signalling pathway components predicted to dynamically change interaction partners across embryonic development.

Tightly integrated with our experimental work, bioinformatics will generate an open datawarehouse, providing community access to our data. From this we will generate new network-based views of the Drosophila proteome, incorporating our isoformal proteome and public data, which will be exploited in state-of-the-art function prediction tools to predict novel signalling pathway protein interactions. We will use in vivo tagged lines to test interaction and subcellular localisation predictions by targeted SILAC-iPAC experiments. Using these data we will advance a new protein interaction prediction tool, accounting for isoforms.

To encourage uptake we will disseminate our data widely, making raw and processed views of the dynamic embryonic fly proteome available via web servers, web services and existing community databases. In consultation with the research community we will develop data visualisation tools to facilitate non-expert data access, and comprehensive training courses to disseminate expertise.

We plan to deliver impact in 4 areas, with particular emphasis on advanced training to our staff and the wider research community, and dissemination of data, tools and technology. In addition we will engage in extensive public engagement activities and explore industrial take-up of technologies we develop, primarily through the Lilley lab and their good links with industry.

Our project seeks to address fundamental questions in the molecular biology of embryonic development using the latest cutting-edge post-genomic science. It is therefore highly multi-disciplinary and requires researchers with quite disparate backgrounds and skills, yet with open minds and collaborative mind-sets. We are confident, based on our track records, that this exists for the principal investigators but we aim to enthuse our research staff with this ethos and spread the word to others through workshops/training courses that we will run. We argue too that we will be pioneering in terms of the extra dimensions that our proteomics studies will generate, and this will necessitate innovations in the attendant bioinformatics - both to process and acquire the data, and to exploit it and learn from it to develop novel prediction tools. This should set new paradigms in the computational biology field and encourage other groups to consider similar approaches, and we hope our training and dissemination activities will achieve this aim.

In parallel, we plan to communicate the advances we make in both the developmental cell biology and post-genomic technologies to the wider public, via a variety of sources. This will include open days and talks, as well as more 21st century means (wikis, twitter and You Tube videos).

Finally, we will explore exploitation opportunities of our software and proteomic technologies where appropriate (though much of our informatics will be open source, and all of it free to academics). The Lilley lab will continue to present updates to industrial colleagues, as detailed in our Pathways to Impact statement.