Past iGEM Projects: Case Studies

2006 Projects:Neat Gadgets• University of Arizona: Bacterial water color • BU: Bacterial nightlight• Brown: Bacterial freeze tag, tri-stable toggle switch• University of Calgary: Dance with swarms• Chiba University, Japan: Swimmy bacteria, aromatic bacteria• Davidson: Solving the pancake problem• Duke: Underwater power plant, cancer stickybot, human encryption,

protein cleavage switch, xverter predator/prey • Missouri Western State University: Solving the pancake problem• MIT: Smelly bacteria (best system)• Penn State: Bacteria relay race (passing QS molecules off as batons)• Purdue: Live color printing• Tokyo Alliance: Bacteria that can play tic-tac-toe• UCSF: Remote control steering of bacteria through chemotaxis

2006 Projects:Research Tools• Bangalore: synching cell cycles, memory effects of UV exposure• Berkeley: riboregulator pairs, bacterial conjugation• University of Cambridge: Self-organized pattern formation• Freiburg University: DNA-origami• ETH: Bacterial adder• Harvard: DNA nanostructures, surface display, circadian oscillators• Imperial College: oscillator (great documentation)• University of Michigan: algal bloom, Op Sinks, • McGill: Split YFP / Repressilator• Rice: quorumtaxis• University of Oklahoma: Distributed sensor networks• IPN_UNAM, Mexico: cellular automata (simulations)• University of Texas: Edge detector

2006 Projects:Real World• University of Edinburgh: arsenic detector, (best real world,

3rd best device)• Slovenia: Sepsis prevention (grand prize winner, 2nd best

system)• Latin America: UV-iron interaction biosensor

• Mississippi State University: H2 reporter

• Prairie View: Trimetallic sensors• Princeton: Mouse embryonic stem cell differentiation using

artificial signaling pathways (2nd runner up)• University of Toronto: Cell-see-us thermometer

Edinburgh: Arsenic Biosensor

• Goal: Develop a bacterial biosensor that responds to a range of arsenic concentrations and produces a change in pH that can be calibrated in relation with the arsenic concentration.

• Lots of previous research into arsenic biosensors– Gene promoters that respond to presence of arsenic

– Different outputs available

– pH is easy, practical, and cheap to measure

– Signal conversion: ABC where C is easy to detect

• System: Arsenate/arsenite detector reporter (pH change)

arsR gene codes for repressor that bind to arsenic promoter in absence of arsenate/arsenite

Basic Parts

Link to LacZ, metabolism of lactose creates acidified medium decreased pH

ArsR sensitive promoter

arsR gene

Arsenate/arsenite

Pars arsR lacZ

Sensitivity!!

Lac regulator Activator gene

Activator molecule A1

Lactose

|A| |R|Promoter

Urease gene

A1 binding site

Urease enzyme

(NH2)2CO + H2O = CO2 + 2NH3

Ars regulator 1 Repressor gene R1Arsenic (5ppb)

Ars regulator 2 LacZ gene

Repressor molecule R1

Arsenic (20ppb) LacZ enzyme

R1 binding site

Arsenic sensor system diagram 8.5

7.0

6.0

4.5

pH:

Ammonia

Lactic Acid

System Design

Results:

• Can detect WHO guideline levels of arsenate

• Average overnight difference of 0.81 pH units

• Response time of 5 hrs

Take Home Message (part 1):

• Sensors are relatively straight-forward in design (ABC)

• I/O signal sensitivity is key• Tight regulation of detector components• Most of the components were available

(engineering vs. research)• Real world applications

Slovenia: Sepsis PreventionGoal: Mimic natural tolerance to bacterial infections by building a feedback loop

in TLR signaling pathway, which would decrease the overwhelming response to the persistent or repeated stimulus with Pathogen Associated Molecular Patterns (PAMPs).

• Engineering mammalian cells

• Medical application

Altering Signaling Pathway

• MyD88: central protein of TLR signaling pathway that transfers signal from TLR receptor to downstream proteins (IRAK4) resulting in the NFκB activation

• Method: – Use dominant negative

MyD88 to tune down signaling pathway to NF-κB

– Addition of degradation tags to dnMyD88 with PEST sequence temporary inhibition to NF-κB

CellDesigner:http://www.systems-biology.org/cd/

PAMPs TLR MyD88 IRAK4 NFκB cytokines

Measurements / Results• Flow cytometry: antibody to phosphorylated ERK kinase to detect TLR

activation

• Luciferase and ELISA assays: level of NF-kB

• Microscopy

26 new BioBricks for Mammalian Cells

Registration number Part's Name

BBa_J52008 rluc

BBa_J52010 NFκB

BBa_J52011 dnMyD88-linker-rLuc

BBa_J52012 rluc-linker-PEST191

BBa_J52013 dnMyD88-linker-rluc-link-pest191

BBa_J52014 NFκB+dnMyD88-linker-rLuc

BBa_J52016 eukaryotic terminator

BBa_J52017 eukaryotic terminator vector

BBa_J52018 NFκB+rLuc

BBa_J52019 dnTRAF6

BBa_J52021 dnTRAF6-linker-GFP

BBa_J52022 NFκB+dnTRAF6-linker-GFP

BBa_J52023 NFκB+rLuc-linker-PEST191

BBa_J52024NFκB+dnMyD88-linker-rLuc-link-

PEST191

BBa_J52026 dnMyD88-linker-GFP

BBa_J52027 NFκB+dnMyD88-linker-GFP

BBa_J52028 GFP-PEST191

BBa_J52029 NFκB+GFP-PEST191

BBa_J52034 CMV

BBa_J52035 dnMyD88

BBa_J52036 NFκB+dnMyD88

BBa_J52038 CMV-rLuc

BBa_J52039 CMV+rLuc-linker-PEST191

BBa_J52040 CMV+GFP-PEST191

BBa_J52642 GFP

BBa_J52648 CMV+GFP

Take Home Message (part 2):

• Lessons from their team:

– Use reliable oligo vendors

– Double check biobrick parts for incorrectly registered parts

• Lot of work to find out optimal parameters for cell activation (inducer conc., etc.)

• Mammalian cells are more challenging to work with

• Requires more sophisticated readouts

• Make new biobricks!

• Reward is great