synthetic)biology)– trends)and)updates · 2high throughput biology center, johns hopkins...
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Synthetic Biology – Trends and UpdatesEC WORKSHOP ON SYNTHETIC BIOLOGY -‐
FROM SCIENCE TO POLICY AND SOCIETAL CHALLENGESLuxembourg 9th Dec 2015
Professor Paul Freemont @paulfreemontCo-‐director and Co-‐founder EPSRC Centre for Synthetic Biology and InnovationCo-‐director and Co-‐founder of UK National Innovation and Knowledge Centre for Synthetic Biology Imperial College London, UK
WHAT IF ?
E. chromi, 2009 University of Cambridge iGEM team
WHAT IF ?
Plasticity 2013 Imperial College iGEM team http://2013.igem.org/Team:Imperial_College
WHAT IF ?
Aqualose 2014 Imperial College iGEM team http://2014.igem.org/Team:Imperial
Gluconacetobacter xylinus
Gluconacetobacter xylinus + yeast
Suzanne Lee
Imperial College IGEM 2014 Aqualose
Genetic engineering of the cellulose-‐producing bacterium Komagataeibacter rhaeticus for production of novel biomaterials.Florea et al 2015 in press
WHAT IF ?
viruses
parasites
bacteria
Infector Detector 2007 Imperial College iGEM team http://2007.igem.org/Imperial/Infector_Detector/Introduction
coal
petroleum
natural gas
Carbon feedstocks Building blocks Value - added chemicals
ethylene / propylene / butadiene
benzene / toluene / xylene
WHAT IF ?
Building blocks Value - added chemicals
ethylene / propylene / butadiene
benzene / toluene / xylene cellulosic crops
Biomass feedstocks
CO2
lignocellulosicwaste
WHAT IF ?
S. cerevisiae secreting farnesene/biodiesel
~112K bases added~41K bases removed~450 single nucleotide changes
~1.25% of the genome!
DNA as a programmable material
WHAT IF ? Eau de Yeast
GenSpace’s
DIY-‐Bio, Biohackers and the Growth of Community Labs
(adapted from Science 333: 6047 (2011); http://www.wisegeek.com/what-‐are-‐cold-‐forceps.htm); http://www.webmd.com/colorectal-‐cancer/ss/slideshow-‐colorectal-‐cancer-‐overview)
Engineered bacteria to detect and kill cancer cells
Engineered E. coliColorectal cancer
Healthy colon
WHAT IF ?
(adapted from Science 333: 6047 (2011); http://www.sciencephoto.com/)
bacteriophageAttacking bacterium Bacteria cell lyses and dies
Engineered phage and bacteria to target pathogens
Engineered E. coli
WHAT IF ?
Porter et al. N. Eng. J. Med., 365 (2011), pp. 725–733
T cell engineering
Engineered T-‐cells to target cancerWHAT IF ?
Warren et al. Cell Stem Cell 7, 618 (2010)
Cell therapy and regenerative medicine
Systematic cellular reprogramming
Induced pluripotent stem cells
WHAT IF ?
October 2015
WHAT IF ?
https://www.youtube.com/watch?v=ylSZN-‐1hhoY
“Synthetic biology aims to design and engineer biologically based parts, novel devices and systems as well as redesigning existing, natural biological systems”
So why is synthetic biology causing such a big fuss?
“SynBio is the application of science, technology and engineering to facilitate and accelerate the design,
manufacture and/or modification of genetic materials in living organisms.”
SCHER, SCENIHR, SCCSoperational definition for Synthetic Biology
Synthetic Biology is a rapidly growing field
Citations of papers containing key works synthetic biology 70256 -‐ 47,000 papers since 2001
A growing community of student researchers – growth of iGEMInternational Genetically Engineered Machine Competition
280 teams are registered for 2015259 teams at the Jamboree~15,000 iGEM alumni
Synthetic Biology has a powerful vision for merging engineering design practice into the construction of
biology systems and cells at the genetic level
In engineering systems, robustness and stability are achieved by
(1) System control(2) Redundancy(3) Modular design(4) Structural stability
Basics of an engineering design frameworkBasics of an engineering design framework
(1) System control (feed-‐back/ feed-‐forward biological control networks )(2) Redundancy (gene duplication/ multiple regulatory pathways )(3) Modular design (evolutionary robust / multi-‐functional / compartmental)(4) Structural stability (homeostasis)
Hypothesis – Are these also intrinsic features of complex natural living systems?
A systematic engineering framework for biological systems aims to test the hypothesis
An engineering design framework for Synthetic Biology
An engineering design framework for Synthetic Biology
Can we use Biology to Build new Biology?Can we learn about biology through
design and construction?
• Biological systems are modular • Biological function is primarily encoded in DNA• Large knowledge base of genome sequences• Large diversity of biological parts (genes/regulatory)• Increased understanding of molecular / cell biology• New technologies to synthesize and assemble DNA
However……
Standardising biology poses challenges
• Biology is not fully ‘plug and play’– Context dependency– Evolution, adaptation and natural selection– Non-‐predictive stochastic behaviour– Self assembly and emergent properties– Non-‐linear dynamical processes –Multi-‐scale interactions
• Living cells have constrained volumes and high concentrations of biochemical components
x
One approach to overcome biological complexity in
engineering biology is the use of Systematic Design
What is Systematic Design ? Systematic design is founded on the following
engineering principles
• Modularisation – interchangeable modules• Standardisation – standard parts and processes• Abstraction – reducing complexity
Systematic design aims to achieveRobustness and Reproducibility
Key requirement is interoperability
A systematic design framework using genetic parts that encode biological function
DNA
Parts
Devices
Systems
ATCGGTCAAGTGCCT
lacI
SLacI
PlaclacI
SLacI
Plac
hrpR
hrpS
R
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S PhrpL
hrpR
hrpS
R
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Typical gene transcription module
Ribosome binding site
Protein coding sequence
Terminator
Transcription factorTF
TF protein
promoter gene
Abstraction hierarchy
Modularity
ResponsibleResearch & Innovation
A systematic DESIGN CYCLE for Synthetic BiologyA systematic DESIGN CYCLE for Synthetic Biology
Design
Build
Specification
Parts
DNA Assembly
Test
Devices & Systems
Learn
Can we build new biological systems with standardised DNA Parts?
To enable forward engineering the synthetic biology field needs to develop standards
The first standard thread Sir Joseph Whitworth 1841
How do we standardise the construction of living matter?
E. coli Bacillus megateriumB. subtilis
Standards development in synthetic biology
• Standard interchangeable biological parts
• Physical standards (DNA)-‐ Assembly standards (may not be needed with increasing DNA synthesis)
• Functional standards-‐ Standard culture conditions (media/temp/volume)-‐ Standard measurements (e.g. Flow cytometry)-‐ Standard strains of cell hosts or chassis
• Digital Information standards-‐SBOL-‐SBML-‐DICOM-‐SB
Synthetic Biology Foundational Technology
Different applications
Part / DeviceCharact.
Bio-‐CAD Design tools
Chassis/ Host cellCharact.
Genomeediting /screens
DNA Synthesis And Assembly
Current Synthetic Biology research trends
• Engineering of biological systems– Refactoring and Redesigning– Genome editing– Genome construction– Automation, standards and tools– Deskilling and open source
• Creating alternative biological systems– exobiology/XNA– Artificial cell and Cell free systems
Synthetic Biology Foundational Technology
Therapeutics& Novel Drug Delivery systems
FineSpeciality Chemicals
Commoditychemicals
Biomaterials
Foundational tools
Bio-manufacturingprocesses
Agri-Science
Synthetic Biology application trends
DESIGN
Available Bio-‐Design Tools Pathway and circuit designMATLAB: Simbiology http://www.mathworks.co.uk/products/simbiology/OptCom http://maranas.che.psu.edu/software.htmGenetic Engineering of Cells (GEC) http://research.microsoft.com/en-‐us/projects/gec/Cell designer http://www.celldesigner.org/ProMoT http://www.mpi-‐magdeburg.mpg.de/projects/promot/GenoCAD http://www.genocad.org/Operon calculator https://salis.psu.edu/software/OperonCalculator_EvaluateMode
Biopart designRosetta. http://maranas.che.psu.edu/software.htmCadnano. http://cadnano.org/NUPAC http://www.nupack.org/RNA Designer http://www.rnasoft.ca/cgi-‐bin/RNAsoft/RNAdesigner/rnadesign.plmfold/UNAfold http://mfold.rna.albany.edu/RBS Calculator https://salis.psu.edu/softwareRBS Designer http://rbs.kaist.ac.krUTR designer http://sbi.postech.ac.kr/utr_designer
MiscellaneousR2oDNA Designer http://r2odna.com/SBOL http://www.sbolstandard.org/SBOLv http://www.sbolstandard.org/visual
Part registries worldwide
BUILD
Parts
Costs of DNA synthesis is driving the field
Cost per base – sequencing ~0.000001 $– synthesis ~0.10 – 0.28 $Rob Carlson http://www.biodesic.com/
Reading DNA
Writing genesWriting short
DNA
?
DNA assembly Standards Tom Ellis, Geoff Baldwin
MODAL – Modular Overlap Directed Assembly with Linkers
(A. Casini et al NAR 2014a and 2014b) P S
P S
P S1 2
P S2 3
P S3 4
P S4 1
P S
1
2 P S3
P
BASIC -‐ Biopart Assembly Standard for Idempotent CloningM. Storch et al ACS Synbio 4 :791 (2015)
part AP S
part BP S
part CP S
parts ligation
part B
part C part A
Long-‐overhang assembly No PCR!Robust reactions easy to automate
Interoperability
Constructing Synthetic Yeast: Sc2.0
www.syntheticyeast.orgwww.syntheticyeastresource.com
Jef Boeke (NY Medical School)
Design, Synthesise & Assemble a modified version of the S. cerevisiae genome 12 million bp and 16 chromosomes
NYUUSA
BGICHINA
Johns HopkinsUSA
JGIUSA
TianjinChina
EdinburghUK
ImperialUK
TsinghuaChina
MacQuarieAustralia
Aus Wine Res InstAustralia
NUSSingapore
A global synthetic biology project
Sc2.0: 16 chromosomes, 12 million bp
MacQuarie U
2014 – Completed Syn Chromosome III
Research Articles
/ http://www.sciencemag.org/content/early/recent / 27 March 2014 / Page 1 / 10.1126/science.1249252
Saccharomyces cerevisiae has a ge-nome size of ~12 megabases (MBs) distributed among 16 chromosomes. The entire genome encodes ~6000 genes of which ~5000 are individually nonessential (1). Which of these non-essential genes are simultaneously dis-pensable? While a number of studies have successfully mapped pairwise “synthetic lethal” interactions between gene knockouts, those methods do not scale well to 3 or more gene combina-tions because the number of combina-tions rises exponentially. Our approach to address this question is to produce a synthetic yeast genome with all nones-sential genes flanked by loxPsym sites to enable inducible evolution and ge-nome reduction (a process referred to as SCRaMbLEing) in vivo (2, 3). The availability of a fully synthetic S. cere-visiae genome will allow direct testing of evolutionary questions such as “what is the maximum number of nonessential genes that can be deleted without a catastrophic loss of fitness?” and “what is the catalog of viable 3-gene, 4-gene, … n-gene deletions that survive under a given growth condition?” that are not otherwise easily approachable in a sys-tematic unbiased fashion. Engineering and synthesis of viral and bacterial genomes have been reported in the literature (4–11). An international group of scientists, has embarked on constructing a designer eukaryotic ge-nome, Sc2.0 (www.syntheticyeast.org), and here we report the total synthesis of the first complete designer yeast chro-mosome.
Yeast chromosome III, the third smallest in S. cerevisiae (316,617 bp), containing the MAT locus determining mating type, was the first chromosome sequenced (12). We designed synIII according to fitness, genome stability and genetic flexibility principles devel-oped for the Sc2.0 genome (2). The native sequence was edited in silico using a series of deletion, insertion, and base substitution changes to produce the desired “designer” sequence (Figs. 1, S1, S2 and Supplementary Text). The hierarchical wet-lab workflow used to construct synIII (Fig. 2) consisted of three major steps: 1) The 750 bp “build-ing blocks” (BBs) were produced start-ing from overlapping 60- to 79-mer oligonucleotides and assembled using standard PCR methods (13, 14) by un-dergraduate students in the Build-A-Genome class at Johns Hopkins Uni-versity (Fig. 2A) (15). The arbitrary
Total Synthesis of a Functional Designer Eukaryotic Chromosome Narayana Annaluru,1* Héloïse Muller,1,2,3,4* Leslie A. Mitchell,2 Sivaprakash Ramalingam,1 Giovanni Stracquadanio,2,5 Sarah M. Richardson,5 Jessica S. Dymond,2,6 Zheng Kuang,2 Lisa Z. Scheifele,2,7 Eric M. Cooper,2 Yizhi Cai,2,8 Karen Zeller,2 Neta Agmon,2 Jeffrey S. Han,9 Michalis Hadjithomas,10 Jennifer Tullman,5 Katrina Caravelli,1 Kimberly Cirelli,1 Zheyuan Guo,1 Viktoriya London,1 Apurva Yeluru,1 Sindurathy Murugan,5 Karthikeyan Kandavelou,1,11 Nicolas Agier,12,13 Gilles Fischer,12,13 Kun Yang,2,5 J. Andrew Martin,2 Murat Bilgel,1 Pavlo Bohutski,1 Kristin M. Boulier,1 Brian J. Capaldo,1 Joy Chang,1 Kristie Charoen,1 Woo Jin Choi,1 Peter Deng,1 James E. DiCarlo,1 Judy Doong,1 Jessilyn Dunn,1 Jason I. Feinberg,1 Christopher Fernandez,1 Charlotte E. Floria,1 David Gladowski,1 Pasha Hadidi,1 Isabel Ishizuka,1 Javaneh Jabbari,1 Calvin Y. L. Lau,1 Pablo A. Lee,1 Sean Li,1 Denise Lin,1 Matthias E. Linder,1 Jonathan Ling,1 Jaime Liu,1 Jonathan Liu,1 Mariya London,1 Henry Ma,1 Jessica Mao,1 Jessica E. McDade,1 Alexandra McMillan,1 Aaron M. Moore,1 Won Chan Oh,1 Yu Ouyang,1 Ruchi Patel,1 Marina Paul,1 Laura C. Paulsen,1 Judy Qiu,1 Alex Rhee,1 Matthew G. Rubashkin,1 Ina Y. Soh,1 Nathaniel E. Sotuyo,1 Venkatesh Srinivas,1 Allison Suarez,1 Andy Wong,1 Remus Wong,1 Wei Rose Xie,1 Yijie Xu,1 Allen T. Yu,1 Romain Koszul,3,4 Joel S. Bader,2,5 Jef D. Boeke,2,10,14† Srinivasan Chandrasegaran1† 1Department of Environmental Health Sciences, Johns Hopkins University School of Public Health, Baltimore, MD 21205, USA. 2High Throughput Biology Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA. 3Institut Pasteur, Group Spatial regulation of genomes, Department of Genomes Genetics, F-75015 Paris, France. 4CNRS, UMR 3525, F-75015 Paris, France. 5Department of Biomedical Engineering and Institute of Genetic Medicine, Whiting School of Engineering, JHU, Baltimore, MD 21218, USA. 6Johns Hopkins University Applied Physics Laboratory, Research and Exploratory Development Department, Biological Sciences, Laurel, MD 20723, USA. 7Department of Biology, Loyola University Maryland, Baltimore, MD 21210, USA. 8University of Edinburgh, Edinburgh, Scotland, UK. 9Carnegie Institution of Washington, Baltimore, MD 21218, USA. 10Department of Biology, Johns Hopkins University, Baltimore, MD 21218, USA. 11Pondicherry Biotech Private Limited, Pillaichavady, Puducherry 605014, India. 12Sorbonne Universités, UPMC, Univ Paris 06, UMR 7238, Génomique des Microorganismes, F-75005 Paris, France. 13CNRS, UMR7238, Génomique des Microorganismes, F-75005 Paris, France. 14NYU Langone Medical Center, New York, NY 10016, USA.
*These authors contributed equally to this work.
†Corresponding author. E-mail: [email protected] (J.D.B.); [email protected] (S.C.)
Rapid advances in DNA synthesis techniques have made it possible to engineer viruses, biochemical pathways and assemble bacterial genomes. Here, we report the synthesis of a functional 272,871–base pair designer eukaryotic chromosome, synIII, which is based on the 316,617–base pair native Saccharomyces cerevisiae chromosome III. Changes to synIII include TAG/TAA stop-codon replacements, deletion of subtelomeric regions, introns, transfer RNAs, transposons, and silent mating loci as well as insertion of loxPsym sites to enable genome scrambling. SynIII is functional in S. cerevisiae. Scrambling of the chromosome in a heterozygous diploid reveals a large increase in a-mater derivatives resulting from loss of the MATĮ�DOOHOH�RQ�V\Q,,,��7KH�FRPSOHWH�GHVLJQ�DQG�V\QWKHVLV�RI�V\Q,,,�establishes S. cerevisiae as the basis for designer eukaryotic genome biology.
EMBARGOED UNTIL 2:00 PM US ET THURSDAY, 27 MARCH 2014
TEST
Automation characterisation platform v1.0
C. Hirst, R. Kitney, G. Baldwin
Sample prep
Outgrowth and arrangement
Culture maintenance, sampling and measurement
� Cells kept at similar phase of growth◦ Ensure high quality data◦ Ensures cells are at an appropriate
population for assay
� Growth and measurement separated◦ Reduces noise in data◦ Greatly reduces evaporation
Sample prep
Outgrowth and arrangement
Culture maintenance, sampling and measurement
0Time hours: 1 2 3 4 5 76
Flow Cytometry
Flow Cytometry
Induction
Dilution
8
Dilution
Automation characterisation platform v1.0
C. Hirst, R. Kitney, G. Baldwin
Anderson 22x promoter characterisation
0
0.5
1
1.5
2
2.5
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Prom
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t (RP
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Pearson's coefficient = 0.996
y = 0.9699xR² = 0.99292
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Cytom
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Plate Reader RPU
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Single cell versus population measurements show high degree of correlation C. Hirst, R. Kitney, G. Baldwin
Data Sheets for Parts and SynBIS
Automation characterisation platform v2.0 @Imperial College
Summary• Automation and standardised metrology is accelerating the application of synthetic biology
• Data for part / device characterisation is being shared openly
• New chassis are being constructed e.g. Sc2.0• Standards are being developed and shared • Huge growth and interest by younger researchers• Non-‐biologists are now doing synthetic biology e.g. Engineers
• Significant growth of community labs worldwide-‐see (www.biobuilder.org)