past igem projects: case studies. 2006 projects: neat gadgets university of arizona: bacterial water...
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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
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