1 / 15

Past iGEM Projects: Case Studies

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

andrew
Download Presentation

Past iGEM Projects: Case Studies

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Past iGEM Projects: Case Studies

  2. 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

  3. 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

  4. 2006 Projects: Real World • University of Edinburgh: arsenic detector, (best real world, 3rd best device) • Slovenia: Sepsisprevention (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

  5. 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: ABC where C is easy to detect • System: Arsenate/arsenite  detector  reporter (pH change)

  6. Arsenate/arsenite ArsR sensitive promoter arsR gene Basic Parts • arsR gene codes for repressor that bind to arsenic promoter in absence of arsenate/arsenite • Link to LacZ, metabolism of lactose creates acidified medium  decreased pH Pars arsR lacZ Sensitivity!!

  7. Arsenic sensor system diagram 8.5 Activator molecule A1 pH: 7.0 Activator gene Lac regulator 6.0 4.5 A1 binding site Lactose Urease gene Promoter |A| |R| (NH2)2CO + H2O = CO2 + 2NH3 R1 binding site Repressor molecule R1 Ammonia Arsenic (5ppb) LacZ gene Repressor gene R1 Ars regulator 1 Urease enzyme LacZ enzyme Lactic Acid Arsenic (20ppb) Ars regulator 2

  8. System Design

  9. Results: • Can detect WHO guideline levels of arsenate • Average overnight difference of 0.81 pH units • Response time of 5 hrs

  10. Take Home Message (part 1): • Sensors are relatively straight-forward in design (ABC) • I/O signal sensitivity is key • Tight regulation of detector components • Most of the components were available (engineering vs. research) • Real world applications

  11. Slovenia: Sepsis Prevention Goal: 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

  12. Altering Signaling Pathway PAMPs  TLR MyD88  IRAK4  NFκB  cytokines • 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/

  13. Measurements / Results • Flow cytometry: antibody to phosphorylated ERK kinase to detect TLR activation • Luciferase and ELISA assays: level of NF-kB • Microscopy

  14. 26 new BioBricks for Mammalian Cells

  15. 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

More Related