Synthetic Biology Synthetic Biology Engineering BiologicallyEngineering Biologically--based Devices and Systemsbased Devices and Systems
Professor Richard I Kitney
Imperial College London
Developments in Biology
The Molecular Biology The Molecular Biology Revolution 1953Revolution 1953--20032003
April 25April 25thth 19531953
The Double Helix Model
Scanning Tunnelling MicrographWatson and Crick – Nature 25th April 1953
Inventing the Information Age
Norbert Wiener
Cybernetics
Cybernetics (1948)
Claude Shannon
A Mathematical Theory of Communication in the Bell System Technical Journal (1948)
Information Theory
Sampling Theory
A sample
The Molecular Biology The Molecular Biology Revolution 1953Revolution 1953--20032003
April 25April 25thth 19531953
The Molecular Biology Revolution 1953-2003
1960 Sydney Brenner, et al prove the existence of mRNA
1961 Brenner and Crick determine how DNA instructs cells to make specific proteins
The Molecular Biology Revolution 1953-2003
1973 Genes are transferred to bacteria, which reproduce, generating multiple copies
1977 Fred Sanger and Walter Gilbert independently develop a technique to read the DNA chemical bases
We stand at the dawn of a new understanding of disease…
Nature 409, 860 - 921 (2001)Initial sequencing and analysis of the human genomeInternational Human Genome Sequencing Consortium The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.
The dawn of molecular based medicine
The Tools and Techniques of The Tools and Techniques of Modern BiologyModern Biology
The Biological Continuum
• Systems• Viscera• Tissue• Cells• Proteins• Genes
• Systems• Visera• Tissue• Cells• Proteins• Genes
...
Interface
...Interface
Visualisation2
...
Interface
...Interface
Database
...Interface
User Input
DisplayVisualsation
1...
Display
... ...
Interface
...
Interface
User Input
Model 1
... ...
Interface
Model 2
Interface
Database
...
Interface
Advanced Web-based Information Systems
• Gel Electrophoresis • Western Blot• 1D Gel• 2D Gel
• Flow Cytometry / FACS• Microarray Experiments• Mass Spectrometry• Microscope Images
Techniques for Biological Data
Biology Levels
• Systems• Visera• Tissue• Cells• Proteins• Genes
Multi-scale Modelling
Network dynamicNetwork dynamicNetwork dynamic
Population
Cell-Agent
Petri Netsgene expression
modelling
within a diffusive environment
emergent properties due to interactive cell-agents
death
division
secretion
uptak
e
migration
differentiation
death
division
secretion
uptak
e
migration
differentiation
Population behaviourPopulation behaviourPopulation behaviour
So, what is Synthetic Biology?
Taking an engineering approach to design and applying it to Biology
The Engineering Approach to Design
• Abstraction• Decoupling• Standardisation
Implementation Modelling
Design
Specifications
Testing/Validation
The Engineering Approach
Standard
Engineering
PracticeCertified
The Engineering Approach to Design
• Engineering systems are built from a hierarchy PartsDevicesSystem
• At each level the characteristics of the Part, Device or System are well defined and reproducible
• In engineering the aim is to build a system on the basis of devices which comprise standard parts
Synthetic Biology: aims to build applications from Biobricks
• Parts – encode biological functions• Devices – made from a collection of
parts and encode human-defined functions (eg logic gates)
• Systems – perform tasks, eg counting
Programmed pattern formation (Basu, 2005)Image recording multi-cellular system (Levskaya, 2005)Terpenoids production system (Martin, 2003)Cancer-fighting drugs synthesis (Pfeifer, 2001)Biofilm formation (Kobayashi, 2004)Programmed cell population control (You, 2004)Controlled invasion of cancer cells (Anderson, 2006) …
Multicellular Systems
Inverters (Yolobayashi, 2002; Karig, 2004)Biophasic switch (Michalowski, 2004)Toggle switch (Gardner, 2000) Logic gates: AND and OR gates (Rackham, 2005) Oscillators (Elowitz, 2000; Fung, 2005)Pulse generator (Basu, 2004) …
Biological Devices
The MIT Registry of Standard Biological Parts (700+)PromotersTranscriptional regulators/terminatorsProtein coding regions Ribosome binding sites …
Biological Parts
ExamplesCategories
Genetic Circuits – Switches and Logic
After Christopher A Voigt 2006
Synthetic Biology - Building Parts, Devices and Systems
Modelling Underpinning Technology
Quality Assurance
Engineering Design Applications
Modelling (examples)– Part behaviour– Engineering modelling– Flux modelling– Stability (of living devices)– Metabolic engineering– Protein networks
The Key Components
Underpinning Technology– Part categorisation– DNA synthesis– Micro fluidics– Parts into single cells– Minimal organisms (synthetic host organisms)– Imaging
Quality Assurance– Adaptation evaluation– Engineering Design
» Circuits» Fabrication
Carlson R (2003). The Pace and Proliferation of Biological Technologies. Biosecurity and Bioterrorism: Biodefense Strategy, Practice, and Science, Vol. 1, No. 3, pp. 1-12.
The Synthetic Biology Pipeline ?
SoftwareOligio Micro
ArraysAssemble DNA
ConstructsDNA Error Correction
Large Scale Assembly
Data Devices Molecules
The MIT Registry
Examples of Parts
To see the catalogue of standard parts from the diagram above, hover over the part at the website below
http://parts2.mit.edu
Implementation Modelling
Design
Specifications
Testing/Validation
The Engineering Approach
Standard
Engineering
PracticeCertified
A Case Study
Engineering a Molecular Predation OscillatorEngineering a Molecular Predation Oscillator
BiomedicalEngineers
Biochemists
iGEM 2006 @ Imperial
Biologists
Biochemist
BiomedicalEngineers
ElectricalEngineer
Dr Mann
• Sustained Oscillations
• High Signal to Noise Ratio
• Controllable Oscillations
• Standardized Device forEasy Connectivity
Requirement for a typical engineering oscillatorOur Specifications:
• Stability: >10 periods• SNR: High• Flexibility: ControllableAmplitude and Frequency• Modular Design• Easy Connectivity
The Main Challenges Main challenges of past oscillators:
Figure Reference : Michael B. Elowitz & Stanislas Leibler Nature 2000
• Unstable
• Noisy
• Inflexible
Time (min.)
Fluo
resc
ence
Repressilator
Initial Design Ideas
• Large populations of molecules to reduce influence of noise
• Oscillations due to population dynamics• A well characterized model
Molecular Predator Molecular Predator -- Prey Prey
Based on
X
Y
bXY
The Lotka-Volterra Modelddt
ddt
TimeTime
Population Size
aX
cXY dY
Prey Killingby PredatorPrey Growth
Predator Growth Predator Death
: Prey
: Predator
X
Y
Typical LV Simulations
Small
Amplitude
Graph of Prey vs. Time
Large
Amplitude
Low Frequency High Frequency
prey prey
prey prey
time time
timetime
Prey Killingby PredatorPrey Growth
A
Required Biochemical Properties
TimeTime
Population Size
A
B
B
Predator Growth Predator Death
A A
AB B
B
ddtddt
Self promoted expression of A
Degradation of A by B
Expression of B promoted by AB interaction
Degradation of B
Molecular System
A
B
A
A
B
B
Self promotedexpression of A
Expression of B promoted by AB
interaction
Degradationof A by B
Degradation of B
A
• Cell-cell communication• Constraint: Chemostat• Flexibility: Ratio of populations
Prey Generator Prey Generator CellCell
Predator Predator Generator CellGenerator Cell
Designing the Prey Generator
RequiredDynamic
UsefulBioBricks
FinalConstruct
LuxILuxRtetR pLux
Self promoted expression of A
LuxIC0061
LuxRtetR pLuxF2620
LuxILuxR
LuxR AHL AHL
AHL
Degradation of B
Degradation of A by B
Expression of B promoted by AB interaction
AHLAHL
Lactonase
AHL
Killing
LuxRLuxR
AHL
AHLAHL
Sensing
Designing the Predator Generator
RequiredDynamic
pLuxLuxR aiiA
NaturaldegradationLuxR
C0062pLux
R0062
aiiAC0060
UsefulBioBricks
FinalConstruct
Prey Generator Cell
System Overview
LuxI
pLux
LuxR
pTet
LuxILuxR
LuxR AHL
AHL
AHL
LuxR
pLux
LuxR aiiA
LuxR AHL Lactonase
AHL
AHLAHL
Pool of AHL will Pool of AHL will oscillateoscillate
Predator Generator Cell
Full System set-up
Well mixed cultureIn chemostat
LuxILuxR
tetR pLux
pLuxLuxR aiiA
Prey molecule generator
Predator molecule generator
Wash-out
reservoir
In-flow
time
Change in population ratio
[AHL] Output signal
Cell population
time
Input signal
Full System set-up
Well mixed cultureIn chemostat
LuxILuxR
tetR pLux
pLuxLuxR aiiA
Prey molecule generator
Predator molecule generator
Wash-out
reservoir
In-flow
[AHL]
Cell population
time
time
Output signal
Change in population ratio
ddt
Modelling the Full System
Expression of aiiA
Degradation of AHL
Self promoted expression of
AHL
Degradation of AHL by
aiiA
AHL
LuxR
aiiA
ddt
ddt
Expression of LuxR
Degradation of aiiA
Degradation of LuxR
Modelling the Full System
aiiA Expression of aiiA
Degradation of AHL
Self promoted expression of
AHL
Degradation of AHL by
aiiAAHL
LuxR
dtAHLd ][
dtLuxRd ][
dtaiiAd ][
Expression of LuxR
Degradation of aiiA
Degradation of LuxR
Modelling the Full System
aiiA Production of aiiA
Degradation of AHL
Degradation of AHL by
aiiA
Production of LuxR
AHL
LuxR
dtAHLd ][
dtLuxRd ][
dtaiiAd ][
[ ][ ][ ][ ]LuxRAHLc
LuxRAHLc+0
[ ][ ][ ][ ]LuxRAHLc
LuxRAHLc+0
Gene Expression
[ ][ ]AHLa
AHLa+0
Degradation of aiiA
Degradation of LuxR
Modelling the Full System
aiiA Production of aiiA
Degradation of AHL
Production of LuxR
AHL
LuxR
dtAHLd ][
dtLuxRd ][
dtaiiAd ][ [ ][ ]
[ ][ ]LuxRAHLcLuxRAHLc
+0
Gene Expression
[ ][ ][ ]AHLb
AHLaiiAb+0
Enzymatic Reaction
[ ][ ][ ][ ]LuxRAHLc
LuxRAHLc+0
[ ][ ]AHLa
AHLa+0
Degradation of aiiA
Degradation of LuxR
Modelling the Full System
aiiA Production of aiiA
Degradation of AHL
Production of LuxR
AHL
LuxRdt
LuxRd ][
dtaiiAd ][ [ ][ ]
[ ][ ]LuxRAHLcLuxRAHLc
+0
Gene Expression Enzymatic Reaction
[ ]AHLe
[ ]LuxRd1
[ ]aiiAd2
Degradation
dtAHLd ][
[ ][ ][ ][ ]LuxRAHLc
LuxRAHLc+0
[ ][ ][ ]AHLb
AHLaiiAb+0
[ ][ ]AHLa
AHLa+0
Full System Simulations
Small
Amplitude
Graph of Prey vs. Time
Large
Amplitude
Low Frequency High Frequency
prey prey
prey prey
time time
timetime
Typical System BehavioursOscillations with limit cycles No oscillations
Prey
Predator
Prey
Time
Predator
Prey
Prey
Time
[ ][ ]AHLa
AHLa+0
Modelling the Full System
aiiA Production of aiiA
Degradation of AHL
Production of LuxR
AHL
LuxRdt
LuxRd ][
dtaiiAd ][ [ ][ ]
[ ][ ]LuxRAHLcLuxRAHLc
+0
Gene Expression Enzymatic Reaction
[ ]AHLe
[ ]LuxRd1
[ ]aiiAd2
Degradation
dtAHLd ][
[ ][ ][ ][ ]LuxRAHLc
LuxRAHLc+0
[ ][ ][ ]AHLb
AHLaiiAb+0
Populationdependent
Constant
Wash-outrelated
Characterisation Predator Sensing
Test part
Predictive model transfer function
Experimental data
[AHL]
[GFP
]
Experimental Data
Average with variance and curve fit
Characterisation Predator Sensing
Test part
Predictive model transfer function
Experimental data
Fitting model to data
Parameter extractions
[AHL]
[GFP
]
Average with variance and curve fitting
Implementation
Prey
Prey with Riboswitch
Sensing predator
Sensing predator
Final predator
J37034
J37033J37019
J37031
J37032
++
++
++
+
+
+
++
RS+J37034
J37025
J37024AiiA Test
Construct
J37023
++
+
Registry Catalogue
PartsAssembly process
Implementation Modelling
Design
Specifications
Testing/Validation
The Project Cycle
The Wiki
• Documentation• Communication• Organization
http://openwetware.org/wiki/IGEM:IMPERIAL/2006
A 3rd Industrial Revolution in the Making (?)
• Parts, Devices and Systems
• Biofuels • Biomaterials • Medicines/Drugs/Vaccines • Biosensors
Synthetic Biology promises a shift comparable in importance to the ICT revolution with the power to revolutionise many sectors of the economy including:
The Companies
John Mulligan – Genetics Engineer
“It is possible to design a protein with a specific configuration on a computer and hen to access Blue heron’s software system to construct the DNA sequence that would produce it inside the cell.The protein and DNA may not exist in nature”
http://www.raeng.org.uk/policy/engagement/pdf/Systems_Biology_Report.pdf
The Hierarchy of Synthetic Biology and Quantitative Systems Biology
Now
Next 10yrs and beyond
Level 1
Level 2
Synthetic BiologySynthesis of Engineering
Devices and Systems – and industrial applications
Synthetic BiologySystems, Devices, Parts -Engineering Specification
Systems Biology
Engineering Systems and Signal Theory
Biology and Basic Medical Science
Systems BiologyHealthcare Applications Level 3
Educational AspectsEducational Aspects
Some thoughts from the UK
1. BSc/BEng - three years, e.g. a first degree in engineering or physics
2. MSc - two years, a masters in biology or basic medical science
3. PhD - three years (minimum), a doctorate in Systems Biology
Systems biology training based on the Bologna model
Concluding Remarks• We are now at a similar point to the late
19th Century where the great industries of the 20th Century (automotive, aircraft, ICT etc) did not exist
• Synthetic Biology, coupled to Systems Biology, will produce a third industrial revolution
The EndThe End
