biologia sintetica - igem team argentina (2012)

iGEM Buenos Aires 2012

Manuel Gimenez

Luciano Morosi

Verónica Parasco

Ma. Alejandra Parreño

Mario Rugiero

iGEM is the international Genetically Engineerd Machines competition

• Meant for students from all around the world

• To share freely

• To combine

• To contribute

• To learn

• To solve

Some projects over the past years UT Austin 2004

University of Washington 2011

UC Berkeley 2007

Biosensors Cambridge 2009

Groningen 2009

Ar(III), Cu(I o II), Zn(II)

Arsenic conc. (ppb) pH Colony colour

0 9.5 none

5 7 none

10 7 green

20 4.5 green

30 4.5 red

Edinburgh 2006

iGEM and BioBricks

Why synthetic biology in Argentina and Latin America?

• New ways of solving practical problems

• Standardization & knowledge sharing

• Old iGEM projects might have immediate application in our country

• Free and public access technology

• Technology independence

Our project is “Tunable Synthetic Ecology”

Goal:

Co-culture genetically engineered machines at tunable proportions

while using re-utilizable and well-characterized parts and modules

Uses elements from

Ecology Classic Genetics Bioinformatics

Molecular Genetics Synthetic Biology

Systems Biology

Or... Synthetic Design of Communities

Color Palette

Synthetic Oenology

Optimization of Bioreactor Output

Circuit Isolation

Circuit Integration

To co-culture several strains in tunable proportions has interesting applications

To co-culture several strains allows to break the “6 promoters barrier”

Purnick, P.E. and R. Weiss, The second wave of synthetic biology: from modules to systems. Nat Rev Mol Cell Biol, 2009. 10(6): p. 410-22.

To co-culture several strains introduces a new layer of modularity

Andrianantoandro, E., et al., Synthetic biology: new engineering rules for an emerging discipline. Mol Syst Biol, 2006. 2: p. 2006 0028.

A

Rhl R Rhl I

I R

E Prhl

R

E

C4HSL

B

Las R Las I

I R

E Plas

R

E

3OC12HSL

Design 1: Independent Population Control

Pros and cons: + The system is already implemented for one

strain and can be re-utilized. + Easily scalable, as many strains as

independent QS systems can be added. + The system can be set with a small initial

inoculum of each strain. + Stabilization at sub-saturation OD could be

achieved. - A new QS mechanisms is required for each strain.

3OC12HSL

A

Rhl I

I

C4HSL

B

Las I

I

A

B

C

A

B

C

Design 2: Cross-Population Control

Pros and cons:

+ Required parts are available and well characterized.

+ Stabilization at sub-saturation OD could be achieved.

+ Should work in complex mediums. + Interesting dynamics as oscillations could

arise. - A new QS mechanisms is required for each strain. - Not scalable, modifications to several or all strains are required each time a new strain is added. - A minimum OD is required for the system to work.

-LYS

+TRP

Lysine

Tryptophane

+LYS

-TRP Export

Export A

B

Design 3: Crossfeeding

Pros and cons: + Relatively easy to implement, but new parts would need to be created. + Feasible based on previous studies (Shou et. al., 2006) + Easily scalable, as many strains as initial amino acid auxotrophies can

be added - Doesn’t work at very low or very high cell densities. - Only works in synthetic defined mediums. - A considerable initial cell density is required to start the system

A B States

A B

Ener

gy

Lan

dsc

ape

States

Gene A P(A)

Gene B P(B)

Gene A P(A)

Gene B P(B)

Ener

gy

Lan

dsc

ape

Design 4: Stochastic States Transitions

Pros and cons: + Completely independent of cell density.

+ If a rare state induces death, a slow population growth could be

achieved - All components need to be incorporated in the same strain, thus no

circuit integration or isolation is possible (see applications section).

Acknowledgments

• UNU BioLAC • FCEN UBA • Advisors German Sabio Alan Bush • Instructors Alejandro D. Nadra Ignacio E. Sánchez • External advisors Raik Grümberg Fernan Federici