In prokaryotic cells (which are widely used as host cells in bio- - PowerPoint PPT Presentation

Ø In prokaryotic cells (which are widely used as host cells in bio- engineering), enzymes are often widely separated among the cytoplasm.

Ø Traditional ways to elevate the concentration of substrates and enzymes in the specific area of the prokaryotic cells include: • DNA scaffolds • RNA scaffolds • Protein scaffolds Synthetic protein scaffolds provide modular control over metabolic flux ( Dueber et al. 2009 ). ¡

Current method Drawbacks DNA scaffolds • Hard to assemble • Rely on single-strain Stem-loop Structure RNA scaffolds • Lack of corresponding ligadin • The fragility of RNA • Protein scaffolds The protein structure is too complex • Often hard for prokaryotic cells to correctly fold

Ø The transcription activator-like (TAL) effectors is a family-III effector in Xanthomonas that helps when they infect various plant species (Boch et al., 2010). Fig.1 (A) The basic structure of TAL effectors. (B) 3D structure of the TAL effector bond with DNA (Deng et al., 2012) .

Ø We engineered several TALE proteins by fusing them with the enzymes from the multi-enzymatic system we try to accelerate.

Ø Through this way we can “tie” those enzymes together around the plasmid backbone to elevate the local enzyme concentration, thus accelerates the reaction.

Ø Aim • This model tries to theoretically prove the TALE-based scaffold system can improve the multi-enzyme reaction efficiency. Ø Method • The core idea is to simulate multi-enzyme reaction process and compare the behavior of TALE-based scaffold system and the none-scaffold system.

Ø The stochastic simulation starts from COLLISION while the Michaelis-Menten equation basic on the CONCENTRATION. The transform from COLLISION to CONCENTRATION requires uniform condition. Condition: None COLLISION REACTION stochastic simulation MOLECULER DYNAMICS Condition: Condition: None Uniform COLLISION REACTION CONCENTRATION Michaelis-Menten Figure 2. The compare between two methodologies.

Ø Simplifying & Behavior Assumptions Ø Parameters Setting Ø Result & Analysis Ø Conclusion Ø Postscript

Ø Object • E. coli , reactants, scaffolds and enzymes (on or off scaffolds) Ø Geometric simplification (2D) • Circles: E. coli , reactants and enzymes • Lines: scaffolds Scaffold Resultant/ Intermediate ¡ Enzyme ¡1 Substrate Resultant Enzyme ¡3 Intermediate ¡ Product Enzyme ¡2 Product

Ø Geometric simplification (2D) (b) Simplified E. coli with scaffold (c) Simplified E. coli without scaffold (a) E.coli

Ø Behavior (time driven) • Fixed: enzymes (on and off scaffolds) • Random thermal motion: Reactants § The motion direction and speed in a time step both obey uniform distribution . § All objects are restricted to move within on E. coli . § Reactants can overlap the enzymes. • Reaction § Matched overlap (collision) = reaction § Once collide, reaction finished instantaneously .

Ø Behavior (time driven) Enzyme ¡1 ​𝜒↓𝑠𝑏𝑜𝑒 • Demo (scaffold system) The smaller blue dots are substrates ​𝑤↓𝑠𝑏𝑜𝑒 and the linked larger blue and red dots are different enzymes. Reactant ¡mo<on ¡and ¡interac<on ¡(First ¡30 ¡<me ¡step) ¡

Diameter PARAMETERS VALUE Scaffold Simula<on ¡Time ¡Step 1 Simula<on ¡Total ¡Time ¡ 2000 Enzyme ¡1 Enzyme ¡3 Reactant ¡speed ¡lower ¡limit Enzyme ¡2 0.3 (<mes ¡to ¡reactant ¡diameter) ENZYME Reactant ¡speed ¡upper ¡limit GROUP 2 (<mes ¡to ¡reactant ¡diameter) Types ¡ Distance Diameter ¡ Scaffold ¡Quan<ty 4 1 2 8 [6,8] Ini<al ¡Reactant ¡Quan<ty 150 2 2 12 [6,8] Reactant ¡Diameter 3 3 2 18 [6,8] Cell ¡Diameter 200 4 3 [12,12] [6,8,10] The ¡ Constant ¡Parameters ¡ SeKng ¡ The ¡ Variable ¡Parameters ¡SeKng ¡

none-­‑Scaffold Reactants ¡ 1. The ¡substrates ¡are ¡consumed ¡in ¡ Quan<ty Scaffold similar ¡speed. ¡ 2. With ¡scaffold ¡the, ¡the ¡ intermediate ¡products ¡are ¡ transformed ¡to ¡resultant ¡faster. Time

none-­‑Scaffold Reactants ¡ 1. The ¡distance ¡between ¡enzyme ¡ Quan<ty Scaffold sites ¡is ¡larger. 2. Similarly, ¡the ¡substrates ¡are ¡ consumed ¡in ¡nearly ¡same ¡speed. ¡ 3. With ¡scaffold ¡the, ¡the ¡ intermediate ¡products ¡are ¡ transformed ¡to ¡resultant ¡faster ¡ than ¡that ¡without ¡scaffold. ¡ Time

none-­‑Scaffold none-­‑Scaffold Reactants ¡ Reactants ¡ 1. The ¡distance ¡between ¡enzyme ¡ Quan<ty Quan<ty Scaffold Scaffold sites ¡is ¡enlarged ¡on. ¡ 2. Differently, ¡the ¡scaffold ¡design ¡ and ¡none-­‑scaffold ¡design ¡have ¡ similar ¡reac<on ¡efficiency. Time Time

Resultant ¡ 1. With ¡the ¡distance ¡between ¡ Quan<ty different ¡enzymes ¡sites ¡on ¡one ¡ scaffold ¡enlarging, ¡the ¡the ¡effect ¡ of ¡the ¡scaffold ¡decreasing. Enzyme ¡Distance: ¡8 Enzyme ¡Distance: ¡12 Enzyme ¡Distance: ¡18 Time

none-­‑Scaffold Reactants ¡ 1. The ¡mul<-­‑enzyme ¡reac<on ¡series ¡ Quan<ty Scaffold increases. ¡ 2. The ¡substrates ¡are ¡also ¡ consumed ¡in ¡nearly ¡same ¡speed. ¡ 3. But ¡the ¡effect ¡of ¡the ¡scaffold ¡is ¡ more ¡obvious ¡than ¡that ¡above. Time

Ø Based on our simulation, we came to the conclusion that: • The TALE-based scaffold system can improve the multi-enzyme reaction efficiency. • With the multi-enzyme reaction series increasing, the effect of the scaffold is brought out. • With the distance between different enzymes sites on one scaffold enlarging, the the effect of the scaffold decreasing.

Enzyme ¡1 ​𝜒↓𝑠𝑏𝑜𝑒 Ø Equations • Motion of reaction ​𝑤↓𝑦 = ​ cos ⁠ ​ ( 𝜒↓𝑠𝑏𝑜𝑒 ) × ​𝑤↓𝑠𝑏𝑜𝑒 ​𝑤↓𝑧 = ​ sin( ⁠ ​𝜒↓𝑠𝑏𝑜𝑒 ) × ​𝑤↓𝑠𝑏𝑜𝑒 ​𝑤↓𝑠𝑏𝑜𝑒 • Collision ​ ( 𝑦↓𝑠𝑓𝑏 − ​𝑦↓𝑓𝑜𝑨 ) ↑ 2 + ​ ( 𝑧↓𝑠𝑓𝑏 − ​𝑧↓𝑓𝑜𝑨 ) ↑ 2 ≤ ​ ( ​𝑠↓𝑠𝑓𝑏 + ​𝑠↓𝑓𝑜𝑨 ) ↑ 2 Ø Simulation Environment/Platform • MATLAB & MacBook Pro 2.8 GHz Intel Core i7 (4 core & 16G Memory)

Ø Scaffold • TALE recognition sites (BMs) ¡BM1: ¡5’-­‑GGAGGCACCGGTGG-­‑3’ ¡ ¡BM2: ¡5’-­‑GATAAACACCTTTC-­‑3’ ¡ Ø Corresponding TALEs • TALE1/T1 (Recognizing BM1) • TALE2/T2 ¡(Recognizing ¡BM2) ¡ • TALE3/T3 ¡(Recognizing ¡reversed ¡ BM2) ¡ ¡

Ø Scaffold SCAF1 ¡(S1): ¡ SCAF2 ¡(S2): ¡ SCAF3 ¡(S3): ¡

Ø TALE/Scaffold pairs I. TALE1/TALE3 with SCAF1 II. TALE1/TALE2 with SCAF2 III. TALE1/TALE2 with SCAF3

Ø Prototypes • Split GFP • TALE1-GFP1/TALE2-GFP2 S2 • TALE1-GFP1/TALE2-GFP2 S3 • TALE1-GFP1/TALE3-GFP2 S1

Ø Prototypes • IAA production

Ø Prototypes • IAA production • TALE1-IAAM/TALE2-IAAH S2 • TALE1-IAAM/TALE2-IAAH S3

Ø Results • Evaluation of the binding ability of TALE-GFP1/2 to the DNA scaffold. Figure 1. ChIP-PCR assay of TALE-GFP binding to the scaffold in E.coli . ¡

Ø Results v Evaluation of the binding ability of TALE-GFP1/2 to the DNA scaffold. Figure 2. Evaluation of the TALE-DNA scaffold system by split GFP assay. ¡

Ø Results v The function of TALE- DNA scaffold system on IAA production Figure ¡3. ¡Increase ¡of ¡IAA ¡produc<on ¡by ¡incorpora<ng ¡the ¡IAAM ¡and ¡IAAH ¡ into ¡TALE-­‑DNA ¡scaffold ¡system. ¡ ¡

Ø TALE can be fused with other proteins WITHOUT affecting its DNA-binding ability. Ø The TALE-DNA scaffold system can effectively meet our requirement of MULTI-ENZYMATIC SYSTEM COMPARTMENTATION in prokaryotic cells. Ø The exist of this scaffold system can remarkably ACCELERATE MULTI-ENZYMATIC REACTION . Ø The length of INTERVENING SEQUENCE between BMs may affect the function of the scaffold system.

Ø To our knowledge, this is the first report using TALE system as scaffolds for the spatial organization of bacterial metabolism

Ø The application of this method might be extend to the eukaryotic biofactory as well. Ø We also would like to introduce this technique in manufacturing of bio- fuels, bio-materials, medicine, and even in pollutant disposal in future work.

Ø NJU_CHINA We performed nanoparticle tracking analysis (NTA) for NJU_CHINA to help them to have a more precise determination of the quantity and size of secreted exosomes. Figure 4. Characterization of secreted exosomes after overexpression of nSMase2 in HEK293 cells. ¡

Ø NEFU_China: Flight iGEM • “Flight iGEM” platform aims to build a friendly website to make the wiki development easier. • We participated in the “Flight iGEM” beta test to § improve the Human-Computer Interaction (HCI) § debug for the login bar § make sure the feasibility of cleariGEM template.