Constructing Multi-State Computational Modules using Nucleotide - PowerPoint PPT Presentation

University of Pune, INDIA Constructing Multi-State Computational Modules using Nucleotide & Protein Mediated Cell-Cell Signalling Institute of Bioinformatics & Biotechnology Institute of Bioinformatics and Biotechnology, University of Pune, INDIA

Road M ap University of Pune, INDIA • Team IBB • Conceptualization: Turing Machines The Complete Construct i. Strategy 1 : Simplified Construct Design ii. Strategy 2 : Modularity Design a . Protein based signaling a . Protein based signaling b. Nucleic acid Signaling & Riboswitches Results • BioBricks Submitted to the Registry • Our experiences • Acknowledgements • References 2

University of Pune, INDIA Conceptualization: Turing M achines Turing M achines 3

University of Pune, INDIA Genesis: The Turing Machine 4

University of Pune, INDIA 1 = 1 2 = 11 3 = 111 3 = 111 4 = 1111

Turing M achines - Unary Adder University of Pune, INDIA 6

Biological implementation University of Pune, INDIA Tape input Cell Cell Cell (Final State) (Final State) (Initial State) Tape output Mechanical design Biological analogs Genetic constructs 96 well plate like apparatus Medium components 7

Design considerations University of Pune, INDIA • Inputs (reading a tape) - should be synthesizable and degradable, available, freely diffusible. degradable, available, freely diffusible. • State switching • Independence of states • Only one state is “ON” at any point in time. First attempt towards demonstration in bacterial systems! 8

University of Pune, INDIA THE CONSTRUCT THE CONSTRUCT THE CONSTRUCT THE CONSTRUCT 9

State Symbol State Symbol Direction A 0 A 0 R University of Pune, INDIA A 1 B 1 R B 0 H 1 H B 1 B 1 R 10

THE PROBLEM University of Pune, INDIA • Too LENGTHY • Many assembly steps • Dead end construct • Dead end construct • THE SOLUTION- Try different approaches!!! 11

The Solution! University of Pune, INDIA • Simplifying the construct itself in such a way that the phenotypic output remains the same • Breaking up the system into modules situated into different strains that interact with each other. 12

University of Pune, INDIA Strategy 1 : The SIM PLIFIED Construct The SIM PLIFIED Construct 13

Simplify construct University of Pune, INDIA State Symbol State Symbol Direction A 0 A 0 R A 1 B 1 R B 0 H 1 H B 1 B 1 R State “A” and 0 = No response State “A” and 1 = Switch to state “B’ (AHL production) State “B” and 1 = auto-induced AHL production. State “B” and 0 = AHL production and degradation of 14 Lactose

University of Pune, INDIA Strategy 2 : M odular Design M odular Design 15

M odular approach University of Pune, INDIA a) Protein based signaling b) Nucleotide based signaling b) Nucleotide based signaling 16

a. Protein Based Signaling University of Pune, INDIA HaltState State A State B 17

Export tags University of Pune, INDIA • The Twin Arginine Translocation pathway SRRRFLK, SRR XFLX, TRRXFLX, TRRXFLX, SRRXXLK, SRRXXLA, TRRXXLK, TRR XXLA, SRRXXLT, 18

University of Pune, INDIA • Tor A and YcdB • N terminal attachment • N terminal attachment • Fusion… 19

Solving the Scar Problem… University of Pune, INDIA 20

University of Pune, INDIA • ATGCAGTA-----------ACTCAATCTGC • ATGCAGTA-----------ACTCAATCTC ’C’ 21

SOPMA Analysis University of Pune, INDIA YcdB with the added base YcdB without the added base ’C’ ’C’ 22 TorA with the added base TorA without the added base ’C’ ’C’

Proof of concept University of Pune, INDIA 23

University of Pune, INDIA b. Nucleic Acid Based Signaling b. Nucleic Acid Based Signaling 24

University of Pune, INDIA 25

University of Pune, INDIA • DNA uptake – Competence related genes enable uptake of DNA. • DNA secretion • DNA secretion – Cell lysis – Naturally competent strains show the property of DNA secretion. – Genetically regulated ‘cell sacrifice’ 26

Riboswitch Lock & Key System Hypothetical Unary Adder Circuit University of Pune, INDIA State Symbol State Symbol Direction Strain A A 0 A 0 R Strain B A 1 B 1 R B 0 H 1 H B 1 B 1 R Strain B Strain B A B Term pLuxR RBS Key Riboswitch pLac RBS Lock LuxI Term B B pLuxR RBS Lac O Lysis Term Term Promoter RBS Com 27

University of Pune, INDIA SNOWDRIFT GAME Co-operators Defectors Co-operators (B-C)/2, (B-C)/2, B-C,B Defectors B,B-C 0,0 28

University of Pune, INDIA Two strains – Co-operator and Defector Strains Co-operator pLacI GFP TorA β - gal RBS Term / Y cdB Defector Defector Co-operator Co-operator GFP producing Cooperator 29 Lactose β -galactosidase Glucose

University of Pune, INDIA The Model Assumptions • At time t=0; • There are ' k' co-operators and ' N-k' defectors • Medium contains ' L' mg/ml of lactose, glucose conc. (g) = 0 • Culture is well mixed. • Extracellular Enzyme conc ( Ec ) = 0 units/ml • Extracellular Enzyme conc ( Ec ) = 0 units/ml • The rate constant for the conversion of Lactose to glucose plus galactose is ‘ k2 ’ Artificial assumptions • Glucose is consumed by all cells. Galactose is also consumed at the same rate Gc mg/cell/min/ml. • The metabolic benefit due to glucose and Galactose is same. So effectively each lactose molecule gives rise to 2 glucose molecules • There is no intracellular lactose metabolism (only extracellular). • There is no lag in enzyme production and secretion. 30 • Rate of degradation of enzyme is zero.

University of Pune, INDIA g = (k2)*(Ec)*(L) mg/ml/min .... (1) r = (R)*(g)*(Gc) .... (2) D(t) = D(t-1)+ r * D(t-1) .... (3) Defector population (t) k(t) = k(t-1) + (r-c) * k(t-1) .... (4) Co-operator population (t) L = L - L * Ec * k2 .... (5) G = G +(( 2* L* Ec* k2)-( N * Gc) .... (6) 31

University of Pune, INDIA 25000 200 Results Lactose 180 Co- conc (L) 160 20000 operators k / mg/ml ml 140 120 15000 Glucose Defectors d / 100 conc (g) ml mg/ml 80 10000 60 40 Total N /ml Extracellula 5000 20 r enzyme units (Ec) 0 /ml 0 -20 0 0 200 200 400 400 600 600 -20 0 100 200 300 400 500 600 C/D ratio 1.2 1 0.8 0.6 C/D ratio 0.4 0.2 0 0 100 200 300 400 500 600 32

University of Pune, INDIA BioBricks Submitted to the Registry BioBricks Submitted to the Registry 33

University of Pune, INDIA Biobricks YcdB YcdB GFP Cprom RBS YcdB GFP Cprom RBS GFP BBa_K233306 BBa_K233309 BBa_K233312 BBa_K233312 BBa_K233310 BBa_K233310 TorA TorA GFP Cprom RBS TorA GFP BBa_K233308 BBa_K233307 BBa_K233311 34

University of Pune, INDIA Biobricks Snowdrift 2 Snowdrift 1 pLL LacO AND GATE 2 pT7 LacO AND GATE 3 35

University of Pune, INDIA Biobricks LacO pLuxR LacO Const. LacO BBa_K233004 BBa_K233004 Prom Prom BBa_K233003 BBa_K233316 Const RBS- TERM pLuxR RBS-LuxI Prom mRFP Const.P RBS LuxR BBa_K233313 BBa_K233317 BBa_K233314 36

University of Pune, INDIA Biobricks Turing machine- Unary adder Turing machine- Unary adder Turing machine cassette 2 AHL+Lactose Mediated Cell Lysis 37

University of Pune, INDIA What we gained from iGEM … • Looking at bacteria from a synthetic biology point of view. • Awareness in our Institute. • Experience 38

Summing up… University of Pune, INDIA • We worked on making multi- state, signalling ,modules. • 26 new parts added to the registry • A novel fusion strategy, characterisation underway… • Modeling the snowdrift game • And a cool time ;-) 39

University of Pune, INDIA Acknowledgements • To our Advisors: – Professor B.A. Chopade – M r. Praveen K Sahu • IBB, University of Pune, INDIA • IBB, University of Pune, INDIA • Department of Chemistry, University of Pune • ‘Sakal’, ‘Times of India’ • Friends, Colleagues and Family back home • Meagan, Vinoo, Randy and the entire iGEM family! 40

We thank our sponsors: University of Pune, INDIA University of Pune, INDIA 41

Team IBB_Pune University of Pune, INDIA 42

References: University of Pune, INDIA • Turing, Alan M. (1936), "On computable numbers, with an application to the Entscheidungsproblem," Proc. London Math. Soc., Ser. 2--42, 230--265. • Turing, Alan M. (1950), "Computing Machinery and Intelligence," Mind 59 (n.s. 236) 433--460, also The World of Mathematics 4, Simon and Schuster, 1954. • Spatial structure often inhibits the evolution of cooperation in the snowdrift game,C Hauert, M Doebeli - Nature, 2004. game,C Hauert, M Doebeli - Nature, 2004. • David Dubnau. DNA UPTAKE IN BACTERIA ,Annual Review of Microbiology, Vol. 53: 217-244 (Volume publication date October 1999) • Steinmoen, H., Knutsen, E. & Havarstein, L. S. Induction of natural competence in Streptococcus pneumoniae triggers lysis and DNA release from a subfraction of the cell population. Proc. Natl Acad.Sci. USA 99, 7681–7686 (2002). • Miller, Melissa B. & Bassler Bonnie L. Quorum Sensing in Bacteria, Annual Review of Microbiology, 2001. 55:165–99 43