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AI for Synthetic Biology · Mazzoldi, E. Groban Autodesk Research, USA 4:20 MDP-based Planning for...
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[email protected] AI for Synthetic Biology @ IJCAI 2016 Aaron Adler Fusun Yaman 1 This document does not contain technology or Technical Data controlled under either the U.S. Interna9onal Traffic in Arms Regula9ons or the U.S. Export Administra9on Regula9ons.
Transcript of AI for Synthetic Biology · Mazzoldi, E. Groban Autodesk Research, USA 4:20 MDP-based Planning for...
AI for Synthetic Biology @ IJCAI 2016
Aaron Adler Fusun Yaman
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ThisdocumentdoesnotcontaintechnologyorTechnicalDatacontrolledundereithertheU.S.Interna9onalTrafficinArmsRegula9onsortheU.S.ExportAdministra9onRegula9ons.
[email protected] Workshop Goals
• Expose AI researchers to a new domain • Bring new tools and techniques to Synthetic
Biologists to help address hard problems • Cross pollenate the AI and SynBio communities • Develop collaborations between the
communities • Discuss next steps
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[email protected] Schedule
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Time Title Authors Affilia0ons
1:30 Welcome A.Adler,F.Yaman
1:40 Introduc9ontoSynthe9cBiology A.Adler,F.Yaman BBN,USA
2:00 AIforSynthe9cBiology
F.Yaman,A.Adler
BBN,USA
2:25 Automatedreading,assemblyandexplana9ontoguidebiologicaldesign
N.Miskov-Zivanov
UniversityofPiTsburgh,USA
2:50 DebuggingGene9cProgramswithBayesianNetworks
G.Karlebach,L.Woodruff,C.VoigtandB.Gordon
MITBroadFoundry,USA
3:10 MolecularRobotsObeyingAsimov'sThreeLawsofRobo9cs
G.Kaminka,R.Spokoini-Stern,Y.Amir,N.AgmonandI.Bachelet
BarIlanUniversity&Augmanity,Israel
3:30 CoffeeBreak
4:00 ACombinatorialDesignWorkflowforSearchandPriori9za9oninLarge-ScaleSynthe9cBiologyConstructAssembly
J.Ng,A.Berliner,J.Lachoff,F.Mazzoldi,E.Groban
AutodeskResearch,USA
4:20 MDP-basedPlanningforDesignofGene-RepressionofCircuits
T.AmimeurandE.Klavins UniversityofWashington,USA
4:40 UsingMachineLearningtoInterpretUntargetedMetabolomicsintheContextofBiologicalSamples
A.Tong,N.Alden,V.Porokhin,N.Hassanpour,K.LeeandS.Hassoun
TucsUniversity,USA
5:00 Discussionandclosingremarks
5:30 Workshopends
Introduction to Synthetic Biology
Aaron Adler Fusun Yaman
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ThisdocumentdoesnotcontaintechnologyorTechnicalDatacontrolledundereithertheU.S.Interna9onalTrafficinArmsRegula9onsortheU.S.ExportAdministra9onRegula9ons.
Workpar9allysponsoredbyDARPAundercontractHR0011-10-C-0168.TheviewsandconclusionscontainedinthisdocumentarethoseoftheauthorsandnotDARPAortheU.S.Government.
[email protected] What is Synthetic Biology?
• “… a maturing scientific discipline that combines science and engineering in order to design and build novel biological functions and systems” [SynBERC]
• Synthetic biologists are working on diverse applications: – New medical diagnostics and therapies – Extract harmful pollutants from the ground – Chemical production or detection
• Synthetic Biology is at a crossroads: AI can help!
Program CellsExecu9ngProgram
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[email protected] Synthetic Biology vs. Genetic Engineering
• Genetic Engineering is the ability to read, copy, and edit DNA so that controlled changes can be made to organisms
• Engineering is the application of scientific, economic, social, and practical knowledge in order to invent, design, build, maintain, and improve structures, machines, devices, systems, materials, and processes. (Wikipedia)
• Understand the design enough to make a prediction about how it will behave
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Synthetic Biology as an Engineering Discipline
• Goal: Design sophisticated biological systems in a reliable, efficient, and predictable manner
• Useful engineering practices: – Libraries of “parts”, Component testing, Standards &
interfaces, Decoupling, Modularity, Computer aided design • Issues in engineering biological systems:
– Device characterization, Impedance matching, Rules of composition, Noise, Cellular context, Environmental conditions, Rational design vs. directed evolution, Persistence, Mutations, Crosstalk, Cell death, Chemical diffusion, Motility, Incomplete models
• A discipline that needs new engineering rule – The rules don’t have to be identical to natural evolution
[Weiss] 8
[email protected] Why is this Important?
• Breaking the complexity barrier:
• Multiplication of research impact • Reduction of barriers to entry
*Samplingofsystemsinpublica9onswithexperimentalcircuits
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2,100 2,7007,500 14,600
32,000
583,0001,080,000
100
1,000
10,000
100,000
1,000,000
1975 1980 1985 1990 1995 2000 2005 2010
Lengthinbasepa
irs
Year
DNA synthesis Circuit size ?
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[Purnick&Weiss,‘09]
Systemintegra0on
Gene0cparts
Modules
Applica0ons
HierarchicalOrganiza9oninSynthe9cBiology
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[email protected] DNA, RNA, Proteins • DNA (Deoxyribonucleic acid)
is a double helix encoding genetic instructions – Composed of nucleotides:
adenine (A), cytosine (C), guanine (G), or thymine (T)
• RNA (Ribonucleic acid) is usually single stranded – Composed of nucleotides:
adenine (A), cytosine (C), guanine (G), or uracil (U)
• RNA can encode an amino acid sequence that can in turn produce a protein
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[Wikimedia]
• Expression dependent on cellular platform, e.g., animal, yeast, bacteria, and cellular context, e.g., heart vs. skin cell
Common Machinery: Transcriptional Logic
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Transcrip)onisthecopyingofaregionofDNA,themoleculeinwhichgene9cinforma9onisencodedasasequenceofnucleo9des,intoastrandofRNA.
Transla)onisthedecodingoftheaminoacidsequenceofanRNAsequencetoproduceaprotein,therebyincreasingtheconcentra9onofthatprotein.Proteinsarethemain“machinery”ofacell.Amongotherthings,theyactassensors,asactuators,andasregulatorsofotherbiologicalprocesses.
Degrada)onandDilu)onaretheprocessesbywhichtheconcentra9onofproteinsandRNAtranscriptsdecrease.Degrada9onisthechemicalbreakdownofamoleculebycellularprocessesorbyitsowninstability.Dilu9onisthesideeffectofcellsgrowinganddividing:theeffec9veconcentra9onofanymoleculedropspropor9onaltotheamountthatthevolumeofthecellincreases.
Regula)onistheinterac9onofaproteinwiththepromoterregionofaDNAsequence,therebymodula9ngtherateatwhichtranscrip9onactsontheregionofDNAcontrolledbythepromoter.Theproteinmayrepressthepromoter,inhibi9ngtranscrip9on,orismayac)vatethepromoter,enhancingtranscrip9on.
Timeconstantsoftheseprocessesareocenquiteslow,ac9ngontheorderofminutes,hours,or(insomecases)days.
Structural
Chemical
Informa0onal
Proteins
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2
3
RNADNA
promoter
Degrada0on&Dilu0on
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RNApolymerase
ribosome
Focus on Information / Control
Most complex applications will require all three
Informa9onal:Representprocessesasdigitallogic,dataflowsChemical:Cellularreac9onsarefundamentallyprobabilis9candchemicalStructural:Reac9onsdependonthephysicalstructureofDNA/RNA/Proteins/Cells
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Cellularcontext
System Design
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SENSORS PROCESSING ACTUATION
Environment
Synthe0ccircuit
• Number?• Types?
• Sophis9ca9on?§ Timing§ States§ Lookuptables§ …
• Number?• Types?
Highlevelgoal:developanengineeringdisciplineforbiology
temperature,pH,light,chemicalsignals,mechanicalforce
fluorescence,movement,electricalac9vity,chemicalproducts
[email protected] Building Blocks
• Features (Parts) are previously identified DNA sequences that perform a specific biological function – promoter initiates transcription – coding sequence for a protein – terminator that halts transcription
• Parts used as basis for engineering • Fluorescent proteins can be observed and used
to help understand what is going on in a cell
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Promoter CDS Terminator
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[email protected] Genetic Regulatory Networks • A collection of DNA regions and their regulatory
interactions is called a genetic regulatory network (GRN) – Takes advantage of the modularity of the DNA molecule – Design of a desired computation
• The GRN may be designed as a single DNA sequence or as multiple separate sequences – Can operate as an insertion into the organism’s existing DNA, as
a virus, or as independent free-floating DNA loops (known as plasmids)
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Key
Promoter
Protein
Repress
Ac9vate
pTrepHef1a pTrertTA CFP LacI EYFP
Dox
pHef1a-LacO1Oid
IfthereisDoxThenglowCyanElseglowYellow
[email protected] Biological Circuits
• Various forms of interaction can be used as computational building blocks for building more complex biological circuits – Deliberately analogous to electronic circuits
• Loops in the regulatory network can be used for feedback control or to create state memory
• Allows an extremely wide variety of computational and control systems to be implemented as genetic regulatory networks
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Input Concentration
Out
put C
once
ntra
tion
Digital Logic in an Analog World
• Biological processes can support digital logic devices!
ideal (step fn)
reality (sigmoidal)
“0” “1”
“1”
“0”
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Genetic Building Block – Digital Inverter
0 1
CDS P
Transcription / Translation
output protein input protein (repressor)
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Gene9cBuildingBlock–DigitalInverter
1 0
CDS P
Transcription / Translation
output protein input protein (repressor)
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[email protected] Interac9ngwithCells–IMPLIESGate
CDS P
Transcription / Translation
output protein input protein (repressor)
Repressor Inducer Output
Repressor Inducer Output0 0 10 1 11 0 01 1 1
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[email protected] Interac9ngwithCells–IMPLIESGate
CDS P
Transcription / Translation
output protein inactive repressor
Repressor Inducer Output
Repressor Inducer Output0 0 10 1 11 0 01 1 1
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[email protected] Abstract Genetic Regulatory Network (A-GRN)
• Defines logical relationship between abstract parts • The GRN above
– Y induces and Z represses the transcription of X
• The overall behavior depends on chemical properties – degradation (γ ), dissociation (D), fold activation (K), basal
expression (α), cooperativity (H)
Y
Z
X
Kz Hz Dz αz γz
Kx Hx Dx αx γx
Ky Hy Dy αy γy
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[email protected] Simulating System Behavior
• Change in concentration of the chemicals approximated using differential equations
• The input/output relationship between X&Y and X&Z
( Kz , Hz , Dz )
(αx , γx ) ( Ky , Hy , Dy )
X
Y Z 26
[email protected] DNA Assembly Techniques
• BioBricks • Magnetic Beads • Gateway-Gibson • Golden Gate • Enzymes break DNA
apart allowing parts to join together
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[igem.org]
[email protected] Getting the New DNA into Cells
• How do you get new DNA into the cell? – Transfection
• Chemical and non-chemical methods – Lipofection – Virus delivery
• DNA can be: – chromosomally integrated OR – transiently transfected OR – on a separate plasmid
• How do you measure the results? – fluorescence – mass spectrometry – anti-body assays – cells emit other chemicals – RNA/DNA assays, …
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GFP
“Fluoresce green when doxycycline is present”
Currently, even something this simple isn’t easy…
rtTA
Dox
Simple Circuit Example
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[email protected] Sense/Actuate Example
NoArabinose HighDoseArabinose
Ara
AraC pBAD GFP TetR pTet RFPpBAD
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OutlookforApplica9ons
Microbialbiochemical
synthesis• artemisinin• otherpharmaceu9cals
Environmentalapplica0ons• environmentalremedia9on• toxinsensing• explosivesensing
Bioenergyproduc0on• biodiesel• hydrogen• methane• …
Biomedicalapplica0ons• cancertherapeu9cagents• ar9ficial9ssuehomeostasis• programmed9ssueregenera9on• ar9ficialimmunesystem
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