Master of Regulation Tandem Promoters & dCas9-based - PowerPoint PPT Presentation

Master of Regulation Tandem Promoters & dCas9-based Multi-level Promoters 2013 iGEM EM of Wuhan University

Proper Promoter is crucial to ideal performance of Genes Just like Power Source to Equipments 375V 4V 25000V Tesla S iPhone HighSpeed rail

Brainstorming VS

Multi-level Regulator Brainstorming Expression at any-amount, any-where Expression Control in non-model species is hard Algea Flower Fungus

Multi-level Regulator Brainstorming Sliding Scribing Resistance Base of Rheostat Multilevel Resistance

The Base Tandem Promoters Sliding Scribing Modeling Human Practice

Tandem Promoters - The Base Employ limited promoters to reach various expression levels Promoter1 Promoter2 RFP S P X E P1:J23102 P2:J23106 P3:J23116

Tandem Promoters - The Base Employ limited promoters to reach various expression levels P3:J23116 P1:J23102 P2:J23106 P1:J23102 Promoter1 P2:J23106 P2:J23106 P1:J23102 P2:J23106 P3:J23116 P1:J23102 RFP Promoter2 S P X E * BBa_K1081002 P1:J23102 P2:J23106 P3:J23116 (* One of Our Seven Biobricks)

Tandem Promoters - The Base Employ limited promoters to reach various expression levels BBa_K1081002 BBa_K1081003 BBa_K1081004 BBa_K1081005 BBa_K1081006 BBa_K1081007 BBa_K1081008

Expression Assay ● Diverse Combinations ● Broader Strength Range

Primary Achievements Seven New Biobricks ( From K1081002 to K1081008 ) Tandem Promoters with Higher Strength Threshold More Levels for Potential Regulations

The Base Sliding Scribing Cas9-based Regulation Modeling Human Practice

dCas9 - Sliding Scribing Tandem Promoter Sequence-specific Targeting Multilevel Promoter

dCas9 - Sliding Scribing CRISPR System ● Simple ● Convenient ● Stable System

dCas9 - Sliding Scribing dCas9 RNA Pol ● Repress RNAP binding & Initiation

dCas9 Construction & Expression One of Our Biobricks: BBa_K1081000

Multi-level Regulation

Multi-level Regulation Result 1 J23106-116 J23106-116 J23106-116 +dCas9 +dCas9 +gRNA +dCas9 +gRNA (Repress J23116) (Repress J23106)

Multi-level Regulation Result 2 J23106-102 J23106-102 +dCas9+gRNA +dCas9 (Repress J23106)

Improve Regulation by aCas9 α subunit RNA Pol RNAP Transcription Recruited Activated

More levels

aCas9 Construction

Primary Achievements Applications of dCas9: Multi-level regulator Constructed an aCas9 plasmid

Future Work Sliding Scribing P1 P2 P3 P4 P5 Changes of Number, Type and Order More Regulatory Sites

The Base Sliding Scribing Modeling Design your own Multilevel Promoter Human Practice

Modeling Design Your Own Multilevel Promoter (MP) 1.Determine the required expression levels 2.Design the tandem-repeat promoter(TRP) 3.Design the targeting sequence and gRNA

1. Expression Level of MP -35 -35 no gRNA dCas9 gRNA1 Level1: No inhibition Level2: Inhibit one sub-promoter Level3: Inhibit both sub-promoter gRNA2 0.6 90% inhibition Example. 0.5 trenght ht TRP Before Target 0.4 omoter Str Regulation 0.3 P1: J23106 Level1: 0.06 Total: 0.6 P2: J23116 Prom 0.2 Pr Level2: 0.33 sub: 0.3 0.1 0 Level3: 0.6 Level 1 Level 2 Single Level 3 P1-P2 + dCas9 P1-P2 + dCas9 P1-P2 + dCas9 Promoter + gRNA(Rep.P1) P2 + dCas9 + gRNA(Rep.P2)

Modeling Design Your Own Multilevel Promoter (MP) 1.Determine the required expression levels 2.Design the tandem-repeat promoter(TRP) 3.Design the targeting sequence and gRNA

Normalize strength 2.Tandem-repeat Promoter Model n     j Strength ' 1 (1 p n ) i i Promoter number (data from [18]) Compared with error less than 10% published data Compared with our data

2.Tandem-repeat Promoter Model The Derivation of the model Kinetic part 1. Transcription-Translation analysis d mRNA [ ]     [ RP ] [ mRNA ]  v dt    Strength [ RP ] [ RP ]  k d protein [ ]   v mRNA [ ] k protein [ ] dt 2. Time scale seperation of Transcription initiation and RNAP binding       K k k   1    2  3  DNA RNAP RP RP RP c i o k k       1 3 K K DNA RNAP RP protein 1 slow   DNA RNA protein So p i is propotional to [RP]

2.Tandem-repeat Promoter Model The Derivation of the model Thermodynamic part 3. RNAP binding Boltzmann equilibrium probability analysis N ! N !          p Z P ( 2) Z ( P 2)!( N P 2)! P N !( P )! ( N P 1)( P 1) NP      ij tot 1    2 N ! p p Z P ( 1) ( N P 2) P NP 2 i j ( )    ( P 1)!( N P 1)! 4. RNAP binding probablity to tandem promoter n      q 1 p ; p 1 q i i tot i i 5. Tandem promoter strength adjustment  n n  u        j j p 1 (1 p n ) Strength [1 (1 p n )] tot i i V i i

Modeling Design Your Own Multilevel Promoter (MP) 1.Determine the required expression levels 2.Design the tandem-repeat promoter(TRP) 3.Design the targeting sequence and gRNA

3.Cas9 Off-target Model Requirement of regulation: Simplicity & Orthogonality Target site d/aCas9 gRNA Potential off-target site in genome • If possible, choose a target that has at least 4bp difference with its most similar sequence. • Otherwise, employ our model to find out a relatively better choice.

3.Cas9 Off-target Model 1. All target can be divided to two groups. The energy fuction △ G'=F() may be a sigmoid function, result in insensitive to energy change at two extremes. Sequence Single Mismatch tolerance G/C Ref. TCATGCTGTTTCATATGATC low 7 [4] AACTTTCAGTTTAGCGGUCU low 8 [3] TGTGAAGAGCTTCACTGAGT low 9 [1] GATGCCGTTCTTCTGCTTGT low 10 [8] AGTCCTCATCTCCCTCAAGC low 10 [1] GAGATGATCGCCCCTTCTTC low 11 [2] CTCCCTCAAGCAGGCCCCGC low 15 [1] Ave. G/C 10.0 GCAGATGTAGTGTTTCCACA medium 9 [1] GGTGGTGCAGATGAACTTCA high 10 [8] GGGGCCACTAGGGACAGGAT high 13 [2] GTCCCCTCCACCCCACAGTG high 14 [2] GGGCACGGGCAGCTTGCCGG high 16 [8] Ave. G/C 12.4

3.Cas9 Off-target Model 2.The binding energy between gRNA and DNA determine the targeting efficiency. Different position on gRNA has different weight (importance). Calculate △ G(i) according to NN nearest neighbor model ATCG.............CCGG (G) gRNA TGGC.............GCCC (A) potential off-target DNA AT terminal+ GG + CG +....... CC + CC + GG terminal TG terminal+ CT + GC +....... GC + GC + CC terminal : : : : : : △ G(1), △ G(2), △ G(3) △ G(17), △ G(18), △ G(19)              T ' ( ) ( [ (1), (2), (3)...., (19)] ) G F a b F G G G G b

3.Cas9 Off-target Model 2. △ G(i) determines the targetting efficiency in the mismatch sensitive case Our result based on DNA thermodaynamic model and data from [1] The data of Single- nucleotide specificity of Cas9 from [7]

3.Cas9 Off-target Model 3. Derive the kinetic functions of Cas9 binding.   G 2     G G [measurement ] [ TF ] [ E S ] K e RT 2 1      1 1 1 d 2 e RT   [0.21, 0.25, 0.30, 0.39, 0.36, 0.32,   G [measurement ] [ TF ] [ E S ] K 1 2 2 2 d 1 e RT   0.35, 0.39, 1.04, 1.19, 1.20, 1.05, G w   p [ E ] [ E ] [ E ] K [ E ] e RT   1.22, 2.80, 1.83, 1.92, 2.30, 2.36, 2.09 ] b w 0 0 0 dw 0 / =      G p [ E ] K [ E ] K [ E ] K r  br 0 dw 0 dr 0 dr [ E ] e RT 0 Model prediction vs. data from [3] and [4]

3.Cas9 Off-target Model 4. Kinectic analysis show expression time of Cas9 is also crucial for off-target control in editing.      Reversible binding Irreversible enzymatic reaction Cas9+DNA Cas9-DNA Double strand break DNA Cas9 1       k t k t [ ] [ ][1 ( )( )] C A k e k e a b  0 b a k k a b    G k k k  * * k [ ] E k [ ] E       1 cat 1 K , K e RT cat 1 cat 2 k ; k M a a b k k K K  1 1 M M Boundary conditions were set as [A0]=1.0, [B0]=[C0]=0, ka=0.2 min-1,kb=0.1 min-1 for blue line; And [A0]=1.0, [B0]=[C0]=0, ka=0.1 min-1,kb=0.05 min-1 for red line.

Modeling Conclusion … Promoter 1 N20(1) Promoter 2 N20(2) Promoter 3 • Produce designed expression level • Switch between serveal expression levels • Explore the best output in a systematic way

The Base Sliding Scribing Modeling Human Practice

iGEM Popularization Display during the Forum in Wuhan Communication with Science Festival 2013-HUST & HZAU Lectures for Bio Lectures for Chem Communication Communication students students with CAU team with USTC team

Helping Others To iGEM-2013 Shenzhen_BGIC_ATCG Constructed a functional dCas9 plasmid for their project