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Synthetic Biology The engineering of biology Systems Biology Seminar Linköping University 2012-04-25 Erik Gullberg Dept. of Medical Biochemistry and Microbiology Uppsala University Synthetic Biology – definitions “Synthetic biology is a new area of biological research that combines science and engineering.” “… emphasis on developing foundational technologies that make the engineering of biology easier and more reliable.” Wikipedia – Synthetic Biology Synthetic Biology – definitions “The engineering of biology: the synthesis of complex, biologically based (or inspired) systems which display functions that do not exist in nature.” “… synthetic biology will enable the design of ‘biological systems’ in a rational and systematic way.” European Commission, 2005 An engineering view on biology • Cells work like machines, or computers • DNA is a programming language – Controls not only how they process information, but also the hardware. • A transition from Science – knowledge to Engineering - building Illustration by Harry Campbell Prokaryotic systems • Genes expressed in operons – Several genes transcribed to one mRNA • Coupled transcription and translation • Splicing of mRNA is very rare • No mRNA cap or added poly(A) tail • Little or no compartmentation History of Synthetic Biology • 2000 – Genetic toggle switch and repressilator • 2002 – Stochastic gene expression measured • 2003 – Registry of Standard Biological Parts • 2004 – First iGEM held at MIT • 2006 – Production of artemisinin drug precursor • 2010 – First synthetic genome assembled Genetic Engineering vs. Synthetic Biology • Reading DNA • Cutting and pasting DNA Genetic Engineering --------------------------------• Writing DNA • Abstraction and design • Standardization Synthetic Biology Writing DNA – gene synthesis • Gene synthesis prices are decreasing • Enormous amount of genetic information • Much time is spent on DNA construction • Fast and cheap DNA synthesis is increasing general research productivity • Simplifies ”genetic programming” Illustration from Carlson, Nature Biotechnology, May 2009 Abstraction and design • Designing genetic circuits should be like programming a computer. – No one programs a computer in binary 101010101001110010110010110 – Don t design devices on sequence level TTGACATGAGGCAGTATTGAGC – Design using characterized parts DNA based devices • DNA circuits based on standardized parts • What is a standard biological part? ”A genetically encoded object that performs a biological function and that has been engineered to meet specified design or performance requirements” Drew Endy, 2008 • Parts can be genes, promoters, RNA… Abstraction hierarchy • DNA ”TTGACATGAGGCAGTATTGAGC…” • Parts Gene = coding sequence • Devices Inverter = logic NOT gate • Systems Sender Receiver Inverter Output Engineering workflow • Specification • Design • Modeling • Construction • Testing and validation Decoupling! Synthetic biosensors • Transcriptional • Translational • Logic gates Illustrations from Khalil and Collins, Nature Reviews Genetics May 2010 Standardization • Standardized assembly of parts – How do we put different parts together? • Defining function – How to quantify i.e. promoter strength? • System operations parameters – Organism (“chassi”), media, temperature? Standards for assembly • How to physically connect different parts • Often defining flanking restriction sites • BioBrick standard 10 – The most widely used standard so far Illustration from Canton et al., Nature Biotechnology July 2008 Registry of Standard Biological Parts • Registry with thousands of standardized parts, open for everyone to access Defining function – data sheets Reciever BBa_F2620 3OC6HSL -> PoPS • Static performance – Transfer function • Dynamic performance – Response time • Reliability – Genetic stability • Compatibilities – Genetic crosstalk • Conditions – chassi, plasmid, medium, T Illustration from Canton et al., Nature Biotechnology July 2008 Static performance • Transfer function Illustration from Canton et al., Nature Biotechnology July 2008 Dynamic performance • Response time to step increase in input Illustration from Canton et al., Nature Biotechnology July 2008 Reliability – genetic stability • Limited by a “metabolic budget” • Many promoters used are very strong • High expression or toxic product – High fitness cost -> selection pressure – Evolution leads to loss of function “How many generations of growth before a mutant device represents at least 50% of the population?” Drew Endy, 2008 Compatibilities • Very few well defined regulators • Often using native systems -> Crosstalk • Need more regulators orthogonal to – Native systems – Each other Illustration from Rao, Current Opinion in Biotechnology, 2011 Conditions • Organism / chassi – E coli? Bacillus subtilis? Yeast? • Plasmid / genomic – Copy number • Growth medium – Rich / poor? – Well defined? Chassis – minimal systems • Desired properties of a chassi – Robust – Well defined • Ideal - minimal cell – Top-down - minimize existing cells by deleting non-essential genes – Bottom-up - construct minimal cell from well defined parts Examples of DNA circuits • Early switches and oscillators Illustrations from Khalil and Collins, Nature Reviews Genetics May 2010 Synthetic metabolic pathways • Artemisinin drug precursor synthesis in yeast • The synthesized artemisinic acid is transported out and retained on the outside of the engineered yeast Illustration from Ro et al., Nature April 2006 International Genetically Engineered Machine (iGEM) • A worldwide Synthetic Biology competition aimed at undergraduate university students. • Student teams are given a kit of biological parts at the beginning of the summer from the Registry of Standard Biological Parts. • They use these parts and new parts of their own design to build biological systems and operate them in living cells. Examples of iGEM projects • Cambridge 2010 – “E glowli” – Moved genes from fireflies and bioluminescent bacteria into E coli – Codon optimization and single amino acid mutagenesis allowed them to generate bright light output in a range of different colors Images from iGEM team Cambridge 2010 Examples of iGEM projects • University of Washington 2011 – Diesel – Constructed a strain of Escherichia coli that produces a variety of alkanes, the main constituents of diesel fuel, by introducing a pair of genes shown to convert fatty acid synthesis intermediates into alkanes. • Imperial College London 2011 – Auxin – E coli that accelerate plant root development – Engineered bacteria swim towards plant roots – Inside the roots the bacteria release auxin iGEM 2011 – Uppsala University • The idea – show color with color! • The system was designed to regulate the expression of three different genes independently from each other using three different wavelengths of light iGEM 2011 – Uppsala University • The design of the system Illustration from iGEM team Uppsala-Sweden 2011 iGEM 2011 – Uppsala University • The result – too complex system! • Problems with fitness costs and crosstalk • New color output parts sent to registry • The team went on to the world final at MIT Images from iGEM team Uppsala-Sweden 2011 The future of Synthetic Biology • Sequencing - parts from all life in nature • Advances in protein engineering will give new synthetic parts • Can have a wide range of applications – New biomaterials and drugs – Energy production and storage – Medical applications and biosensors • The minimal cell – first synthetic life The future of Synthetic biology • Orthogonal “unnatural” systems – Stop codon replacement – Alternative genetic code – Barrier to horizontal gene transfer – safety • Unnatural amino acids – New physiochemical properties in proteins • Unnatural nucleotides – New base pairs? Thank you for listening! "What I cannot create, I do not understand." Richard Feynman