Infobiotics workbench, a computational framework for ...fran/TIB/semana9.pdf · 2 Synthetic Biology...
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Infobiotics workbench, a computational framework for systems and synthetic biology
modelshttp://www.infobiotic.org/
Fran Romero
Dpt Computer Science and Artificial Intelligence
University of Seville
[email protected]/~fran
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Synthetic Biology is …A) the design and construction of new biological parts, devices, and systems, and
B) the re-design of existing, natural biological systems for useful purposes.
C) Through rigorous mathematical, computational & engineering routes
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Top-Down Synthetic Biology: An Approach to Engineering Biology
Cells are information processors. DNA is their programming language.
DNA sequencing and PCR: Identification and isolation of cellular parts.
Recombinant DNA and DNA synthesis : Combination of DNA and construction of new systems.
Tools to make biology easier to engineer: Standardisation, encapsulation and abstraction (blueprints).
E. coli
Vibrio fischeri
Pseudomonas aeruginosa
plasmids
DNA synthesis
Discosoma sp.
Aequoreavictoria
Circuit BlueprintChassis
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Infobiotics: An Integrated Framework
http://www.infobiotics.org/infobiotics-workbench/
Synthetic Multi-cellular Systems
Libraries of Modules
P systems LPP systems
Multi Compartmental Stochastic Simulations
based on Gillespie’s algorithm
Spatio-temporal Dynamics Analysis
using Model Checking with PRISM and MC2
Automatic Design of Synthetic Gene
Regulatory Circuits using Evolutionary Algorithms
A compiler based on a BNF grammar
Single Cells
Cellular Parts
Synthetic Circuits
Module Combinations
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Ron Weiss’ Pulse Generator
gfpcI
luxR
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Two different bacterial strains carrying specific synthetic gene regulatory networks are used.
The first strain produces a diffusible signal AHL.
The second strain possesses a synthetic gene regulatory network which produces a pulse of GFP after AHL sensing.
These two bacterial strains and their respective synthetic networks are modelled as a combination of modules.
Ron Weiss‘ Pulse Generator
S. Basu, R. Mehreja, et al. (2004) Spatiotemporal control of gene expression with pulse generating networks, PNAS, 101, 6355-6360
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Infobiotics: An Integrated Framework
http://www.infobiotics.org/infobiotics-workbench/
Synthetic Multi-cellular Systems
Libraries of Modules
P systems LPP systems
Multi Compartmental Stochastic Simulations
based on Gillespie’s algorithm
Spatio-temporal Dynamics Analysis
using Model Checking with PRISM and MC2
Automatic Design of Synthetic Gene
Regulatory Circuits using Evolutionary Algorithms
A compiler based on a BNF grammar
Single Cells
Cellular Parts
Synthetic Circuits
Module Combinations
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Characterisation/Encapsulation of Cellular Parts: Gene Promoters
A modeling language for the design of synthetic bacterial colonies.
A module, set of rules describing the molecular interactions involving a cellular part, provides encapsulation and abstraction.
Collection or libraries of reusable cellular parts and reusable models.
LuxRAHL
CI
PluxOR1({X},{c1, c2, c3, c4, c5, c6, c7, c8, c9},{l}) = {
type: promoter
sequence: ACCTGTAGGATCGTACAGGTTTACGCAAGAA ATGGTTTGTATAGTCGAATACCTCTGGCGGTGATA
rules: r1: [ LuxR2 + PluxPR.X ]_l -c1-> [ PluxPR.LuxR2.X ]_l r2: [ PluxPR.LuxR2.X ]_l -c2-> [ LuxR2 + PluxPR.X ]_l ... r5: [ CI2 + PluxPR.X ]_l -c5-> [ PluxPR.CI2.X ]_l r6: [ PluxPR.CI2.X ]_l -c6-> [ CI2 + PluxPR.X ]_l ... r9: [ PluxPR.LuxR2.X ]_l -c9-> [ PluxPR.LuxR2.X + RNAP.X ]_l}
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Module Variables: Recombinant DNA, Directed Evolution, Chassis
selection
A
Directed evolution: Variables for stochastic constants can be instantiated with specific values.
Recombinant DNA: Objects variables can be instantiated with the name of specific genes.
PluxOR1({X=tetR})PluxOR1({X=GFP})
PluxOR1({X=GFP},{...,c4=10,...}) Chassis Selection: The variable for the label can be instantiated with the name of a
chassis.
PluxOR1({X=GFP},{...,c4=10,...},{l=DH5α })
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Characterisation/Encapsulation of Cellular Parts: Riboswitches
A riboswitch is a piece of RNA that folds in different ways depending on the presence of absence of specific molecules regulating translation.
ToppRibo({X},{c1, c2, c3, c4, c5, c6},{l}) = {
type: riboswitch
sequence:GGTGATACCAGCATCGTCTTGATGCCCTTGG CAGCACCCCGCTGCAAGACAACAAGATG rules: r1: [ RNAP.ToppRibo.X ]_l -c1-> [ ToppRibo.X ]_l r2: [ ToppRibo.X ]_l -c2-> [ ]_l r3: [ ToppRibo.X + theop ]_l –c3-> [ ToppRibo*.X ]_l r4: [ ToppRibo*.X ]_l –c4-> [ ToppRibo.X + theop ]_l r5: [ ToppRibo*.X ]_l –c5-> [ ]_l r6: [ ToppRibo*.X ]_l –c6-> [ToppRibo*.X + Rib.X ]_l}
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Characterisation/Encapsulation of Cellular Parts: Degradation Tags
Degradation tags are amino acid sequences recognised by proteases. Once the corresponding DNA sequence is fused to a gene the half life of the protein is reduced considerably.
degLVA({X},{c1, c2},{l}) = {
type: degradation tag
sequence: CAGCAAACGACGAAAACTACGCTTTAGTAGCT
rules: r1: [ Rib.X.degLVA ]_l -c1-> [ X.degLVA ]_l r2: [ X.degLVA ]_l -c2-> [ ]_l}
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Infobiotics: An Integrated Framework
http://www.infobiotics.org/infobiotics-workbench/
Synthetic Multi-cellular Systems
Libraries of Modules
P systems LPP systems
Multi Compartmental Stochastic Simulations
based on Gillespie’s algorithm
Spatio-temporal Dynamics Analysis
using Model Checking with PRISM and MC2
Automatic Design of Synthetic Gene
Regulatory Circuits using Evolutionary Algorithms
A compiler based on a BNF grammar
Single Cells
Cellular Parts
Synthetic Circuits
Module Combinations
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Gene Constructs
Promoter Gene(s) RBS Term TAATAA
Transcription Initiation
TranscriptionTermination
Translation Initiation
Translation Initiation
Genes
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Higher Order Modules: Building Synthetic Gene Circuits
PluxOR1 GFPToppRibo degLVA
3OC6_repressible_sensor = { PluxOR1({X=ToppRibo.GFP.degLVA},{...},{l=DH5α}) ToppRibo({X=GFP.degLVA},{...},{l=DH5α}) degLVA({X=GFP},{...},{l=DH5α})}
X=GFP
Plux({X=ToppRibo.geneCI.degLVA},{...},{l=DH5α}) ToppRibo({X=geneCI.degLVA},{...},{l=DH5α}) degLVA({CI},{...},{l=DH5α})
PtetR({X=ToppRibo.geneLuxR.degLVA},{...},{l=DH5α}) Weiss_RBS({X=LuxR},{...},{l=DH5α}) Deg({X=LuxR},{...},{l=DH5α})
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• Using P systems modules one can model a large variety of commonly occurring BRN: Gene Regulatory Networks, Signaling Networks and Metabolic Networks
• This can be done in an incremental and parsimonious way.
F. J. Romero-Campero, J. Twycross, M. Camara, M. Bennett, M. Gheorghe, and N. Krasnogor. Modular assembly of cell systems biology models using p systems. International Journal of Foundations of Computer Science, 2009
Rapid Model Prototyping
Co-design of parts and their models hence improves and makes both processes more reliable
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Infobiotics: An Integrated Framework
http://www.infobiotics.org/infobiotics-workbench/
Synthetic Multi-cellular Systems
Libraries of Modules
P systems LPP systems
Multi Compartmental Stochastic Simulations
based on Gillespie’s algorithm
Spatio-temporal Dynamics Analysis
using Model Checking with PRISM and MC2
Automatic Design of Synthetic Gene
Regulatory Circuits using Evolutionary Algorithms
A compiler based on a BNF grammar
Single Cells
Cellular Parts
Synthetic Circuits
Module Combinations
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Sending Cells
Pconst
LuxI AHL
AHL
Pconst({X = luxI },…)
PostTransc({X=LuxI},{c1=3.2,…})
Diff({X=AHL},{c=0.1})
luxI
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luxRPconst
cIPlux
gfpPluxOR1
LuxR
CI
GFPAHL
AHL
Pconst({X=luxR},…)
PluxOR1({X=gfp},…)
Plux({X=cI},…)
…
…
Diff({X=AHL},…)
Pulse Generating Cells
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Infobiotics: An Integrated Framework
http://www.infobiotics.org/infobiotics-workbench/
Synthetic Multi-cellular Systems
Libraries of Modules
P systems LPP systems
Multi Compartmental Stochastic Simulations
based on Gillespie’s algorithm
Spatio-temporal Dynamics Analysis
using Model Checking with PRISM and MC2
Automatic Design of Synthetic Gene
Regulatory Circuits using Evolutionary Algorithms
A compiler based on a BNF grammar
Single Cells
Cellular Parts
Synthetic Circuits
Module Combinations
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Specification of Multi-cellular Systems: LPP systems
luxIPconst
LuxI AHL
AHL
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luxIPconst
LuxI AHL
AHL
luxRPconst
cIPlux
gfpPluxOR1
LuxR
CI
GFPAHL
AHLSpecification of Multi-cellular
Systems: LPP systems
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Simulation of the propagation of a wave of gene expression
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A Step forward in Synthetic Biology: Controlling Cell Differentation
Validation of hypothesis about the functioning of cellular systems by implementing them in vivo.
Specific pattern formation in several organisms is produced by transcriptional networks with a double negative feedback loop at their core.
The ZEB/miR-200 feedback loop—a motor of cellular plasticity in development and cancer?Simone Brabletz & Thomas BrabletzEMBO reports (2010) 11, 670 - 677
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PLtet01 luxR cI
Ptac rhlR cI434
Plux,R lacI cherry
PrhlA tetR gfp
PR luxI
PR434 rhlI
LuxR
RhlR
CI
CI434
LacI
TetR
3OC6
C4
Synthetic Double Negative Feedback Loop
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PLtet01 luxR cI
Ptac rhlR cI434
Plux,R lacI cherry
PrhlA tetR gfp
PR luxI
PR434 rhlI
LuxR
RhlR
CI
CI434
LacI
C4
3OC6 C4
C4
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PLtet01 luxR cI
Ptac rhlR cI434
Plux,R lacI cherry
PrhlA tetR gfp
PR luxI
PR434 rhlI
LuxR
RhlR
CI
CI434
TetR
3OC6
3OC6 3OC6 3OC6
3OC6 3OC6
C4 C4
C4C4
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Ondas de Expresión Génica en Colonias de Bacterias Sintéticas
Pattern Formation in synthetic bacterial colonies