Proceedings of The Nice Spring School on Avancesin Systemsand Synthetic Biology March 25th - 29th, 2013 Edited by Patrick Amar, Franc¸ois Kep´ es,` Vic Norris “But technology will ultimately and usefully be better served by following the spirit of Eddington, by attempting to provide enough time and intellectual space for those who want to invest themselves in exploration of levels beyond the genome independently of any quick promises for still quicker solutions to extremely complex problems.” Strohman RC (1977) Nature Biotech 15:199 FOREWORD Systems Biology includes the study of interaction networks and, in particular, their dy- namic and spatiotemporal aspects. It typically requires the import of concepts from across the disciplines and crosstalk between theory, benchwork, modelling and simu- lation. The quintessence of Systems Biology is the discovery of the design principles of Life. The logical next step is to apply these principles to synthesize biological systems. This engineering of biology is the ultimate goal of Synthetic Biology: the rational concep- tion and construction of complex systems based on, or inspired by, biology, and endowed with functions that may be absent in Nature. Just such a multi-disciplinary group of scientists has been meeting regularly at Geno- pole, a leading centre for genomics in France. This, the Epigenomics project, is divided into five subgroups. The GolgiTop subgroup focuses on membrane deformations involved in the functionning of the Golgi. The Hyperstructures subgroup focuses on cell division, on the dynamics of the cytoskeleton, and on the dynamics of hyperstructures (which are extended multi-molecule assemblies that serve a particular function). The Observability subgroup addresses the question of which models are coherent and how can they best be tested by applying a formal system, originally used for testing computer programs, to an epigenetic model for mucus production by Pseudomonas aeruginosa, the bacterium involved in cystic fibrosis. The Bioputing group works on new approaches proposed to understand biological computing using computing machine made of biomolecules or bacterial colonies. The SMABio subgroup focuses on how multi-agents systems (MAS) can be used to model biological systems. This annual School started in 2002. It was the first School dedicated to Systems Biology in France, and perhaps in Europe. Since 2005, Synthetic Biology has played an increasingly important role in the School. Generally, the topics covered by the School have changed from year to year to accompany and sometimes precede a rapidly evolving scientific landscape. Its title has evolved in 2004 and again in 2012 to reflect these changes. The first School was held near Grenoble after which the School has been held in various locations. It started under the auspices of Genopole R , and has been supported by the CNRS since 2003, as well as by several other sponsors over the years. This book gathers overviews of the talks, original articles contributed by speakers, subgroups and students, tutorial material, and poster abstracts. We thank the sponsors of this conference for making it possible for all the participants to share their enthusiasm and ideas in such a constructive way. Patrick Amar, Gilles Bernot, Marie Beurton-Aimar, Attila Csikasz-Nagy, Jurgen¨ Jost, Ivan Junier, Marcelline Kaufman, Franc¸ois Kep´ es,` Pascale Le Gall, Reinhard Lipowsky, Jean-Pierre Mazat, Victor Norris, William Saurin, El Houssine Snoussi. ACKNOWLEDGEMENTS We would like to thank the conference participants, who have contributed in a way or another this book. It gathers overviews of the talks, discussions and roundtables, original articles and tutorial material contributed by speakers, abstracts from attendees, posters and lectures proposed by the epigenesis groups to review or illustrate matters related to the scientific topic of the conference. Of course the organisation team would like to express gratitude to all the staff of the Club Belambra “La Bergerie” hotel for the very good conditions we have found during the conference. Special thanks to the Epigenomics project for their assistance in preparing this book for publication. The cover photography shows a view of the Arc de Venet, Jardin Albert 1ier in the town center of Nice. We would also like to express our thanks to the sponsors of this conference for their financial support allowing the participants to share their enthusiasm and ideas in such a constructive way. They were: Centre National de la Recherche Scientifique (CNRS): • http://www.cnrs.fr R Genopole Evry:´ • http://www.genopole.fr GDRE CNRS 513 Biologie Systemique:´ • http://www.mpi-magdeburg.mpg.de/CNRS MPG Consortium BioIntelligence (OSEO) • Institut National de Recherche en Informatique et en Automatique (INRIA): • http://www.inria.fr/ GDR CNRS 3003 Bioinformatique Moleculaire:´ • http://www.gdr-bim.u-psud.fr THE EDITORS INVITED SPEAKERS MARK BEDAU, Reed College, Portland, OR, USA HELEN BYRNE, OCCAM, U. Oxford, UK ANDREAS DRESS, CAS-MPG, SIBS, Shanghai, CN RACHEL GILES, U. Medical center, Utrecht, NL RICHARD KITNEY, Imperial College London, UK DOMINIQUE SCHNEIDER, U. Joseph Fourier, Grenoble, FR WALTER SCHUBERT, CAS-MPG, Shanghai, CN & U. Magdeburg, DE RICARD SOLE,´ U. Pompeu Fabra, Barcelona, ES ORKUN SOYER, U. Exeter, UK BIRGIT WILTSCHI, Austrian Center of Industrial Biotechnology, Graz, AT CONTENTS ADVANCES IN SYSTEMS AND SYNTHETIC BIOLOGY 9 To be announced Richard Kitney1 1 Imperial College London, UK Abstract ADVANCES IN SYSTEMS AND SYNTHETIC BIOLOGY 11 Non-canonical amino acids as building blocks Birgit Wiltschi1 1 Junior Group Synthetic Biology, Austrian Centre of Industrial Biotechnology ACIB GmbH, Graz, Austria Abstract Non-canonical amino acids (ncAAs) can be used as building blocks for the biosynthesis of synthetic proteins. Though not encoded by the genetic code, these analogs of the canonical amino acids participate in ribosomal protein translation under tightly controlled conditions. Most of the ncAAs carry un- usual side chains. Their translation into a target protein sequence can provoke structural, chemical, or functional modifications normally not found in nature. Thus, protein engineering with ncAAs offers an extension to classical genetic engineering approaches for protein modification. It is an emerging research area in the field of synthetic biology at the interface of biology and chemistry that bears unprecedented biotechnological potential. The incorporation of ncAAs into proteins requires the reprogramming of protein biosynthesis. This can be achieved by skillful manipulation of the different components of the translational machinery. Aminoacyl-tRNA syn- thetases (AARSs) are crucial players in the genetic code interpretation and, therefore, represent a main target for engineering efforts. The manipulation of the catalytic activity of these enzymes provides the clue for the efficient incorporation of ncAAs into target proteins. Currently, two approaches for controlling amino acid selection and catalytic turnover are employed. The first exploits the natural substrate tolerance of the AARSs in the context of amino acid auxotrophies for global substitution of an amino acid by its non-canonical analog. Alternatively, site-specific introduction of an ncAA is achieved by in- frame stop codon suppression in combination with the mutation of the sub- strate specificity of an AARS. This approach requires the development of AARS/suppressor tRNA pairs that are orthogonal. The orthogonal pair must be specific for its cognate amino acid and must not exhibit cross-reactivity with AARS/tRNA pairs of the host. In my presentation, I will focus on the basic requirements for the modifi- cation of proteins with ncAAs by the two complementary approaches. Using examples from the literature and from our own work, I will illustrate the potentials of protein engineering with ncAAs. ADVANCES IN SYSTEMS AND SYNTHETIC BIOLOGY 13 Beyond BioBricks: Using machine learning methods to discover and optimize complex systems in synthetic biology Mark Bedau1 1 Reed College, Portland OR, USA Abstract This talk has two main messages. The first is that emergence plays a cen- tral role in complex synthetic biology mechanisms. Emergence has a con- troversial history in both philosophy and science, but the controversy is now dissipating, in part because of growing awareness of a new conception of emergence (termed ”weak” emergence) concerning global states produced by complex causal networks. Complex causal networks are characterized by high parallelism (many independent variables), high nonlinearity (of response of each variable), and high synergy (the response of a variable depends on the responses of other variables). One main way to understand and control the emergent properties produced by complex causal webs is through Edisonian trial and error, involving extensive empirical observation and experimentation. (Another is by means of computer simulations.) The mechanisms constructed in synthetic biology are typically very complex, and the resulting weak emer- gent properties explain why experimental troubleshooting dominates work in synthetic biology laboratories. Hence my first main message: synthetic biolo- gists should embrace rather than ignore the emergent properties in the complex biochemical systems that they synthesize. My second main message is to demonstrate a new and powerful method to engineer systems to have desired emergent properties. This method puts machine-learning algorithms in control of high-throughput experimental