Julius B. Lucks/Meetings and Notes/01212008 Arkin: Difference between revisions

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** not necessarily orthogonal
** not necessarily orthogonal
** to build something up, have to do massive characterization, then put together, then tweak to get to work together
** to build something up, have to do massive characterization, then put together, then tweak to get to work together
* parts proliferation problem
** every gate in the system has to be made up of a different non-interacting promoter, etc.
** still need to be tuned
* one approach is the big FAB approach (Knight, Endy) -  
* one approach is the big FAB approach (Knight, Endy) -  
** build massive libraries of promoters and characterize them all in different cell contexts
** build massive libraries of promoters and characterize them all in different cell contexts
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* what if we could use antisense interaction (like RNAi) to control transcritption
* what if we could use antisense interaction (like RNAi) to control transcritption
* see image to understand the system
* see image to understand the system
** ColE1 - high copy number replication origin in E. coli (we actually use this in the lab)
** ColE1 (72 bp region) - high copy number replication origin in E. coli (we actually use this in the lab)
** when transcribed, forms some complicated secondary structure that allows polymerase to carry on, so ON by default
** when transcribed, forms some complicated secondary structure that allows polymerase to carry on, so ON by default
** if certain antisense piece of RNA added, will bind to this, causing a DIFFERENT RNA secondary structure down the line, which does not allow polymerase to pass
** if certain antisense piece of RNA added, will bind to this, causing a DIFFERENT RNA secondary structure down the line, which does not allow polymerase to pass
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** to get this to work, would have to make sure the system is cooperative
** to get this to work, would have to make sure the system is cooperative
** would need to measure the induction curve - if sigmoidal, see what can do with it
** would need to measure the induction curve - if sigmoidal, see what can do with it
== Applications ==
* since this is RNA mediated, doesn't matter where the RNA comes from
** could come from cancer cells (which are known to over-express certain RNAs)
** would have to design ColE1s to recognize these specific sequences
* the best papers make a new type of part - more powerful - more computation power - some application for these cells
** RNAi logic, Molecular turing machines - Kobi Benenson
** lots of power
** beyond Adelman
** more towards what I want to do
* figure out need computational power X to do thing Y - put in an application context


== Problems ==
== Problems ==
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== TOREAD ==
== TOREAD ==
* talk to Anthony Carruthers (looking at changing mRNA degradation rates)
* talk to Anthony Carruthers (looking at changing mRNA degradation rates)
** alos Jonathan Golder
** also Jonathan Golder
** also David Tulga - works w/ Anderson - Xis and Int recombination systems
** alos Chris Anderson about RNA genes
* big ColE1 people in europe
* big ColE1 people in europe
** Sabin Brandtl
** Sabin Brandtl
** Gerhard Wagner
** Gerhard Wagner
* which papers like and why - which ones are the most exciting


* which papers like and why - which ones are the most exciting
== Random Notes ==
* other systems kind of like this
** SacT terminator of B. subtilis - sacT binds to hairpin and opens
*** anti-termination with no modifications of the polymerase
* iGEM - FMN - translational control
** were trying to avoid the protein part - just another step to worry abou engineering
* Niles Pierce - multi-stranded RNA systems

Revision as of 15:40, 21 January 2008

ColE1 System - Engineerable transcriptional control

  • idea - want to genericise transcriptional control
  • currently, theoretically, if want to build more complicated genetic networks, need more parts (promoters, terminators, etc.)
    • problems - each have their own kinetics
    • not necessarily orthogonal
    • to build something up, have to do massive characterization, then put together, then tweak to get to work together
  • parts proliferation problem
    • every gate in the system has to be made up of a different non-interacting promoter, etc.
    • still need to be tuned
  • one approach is the big FAB approach (Knight, Endy) -
    • build massive libraries of promoters and characterize them all in different cell contexts
    • then in multiple RBS contexts
    • then in multiple terminator contexts
    • might have enough characterization then to be able to build something up
    • HUGE cost, and not sure will work
    • probably something like will first do on 10 most popular things, then stop there
  • want to make the building of complicated system more amenable to predictable design
  • another approach via RNA engineering - translational control
    • Smolke - ribozymes - recognize metabolite - change conformation - allow translation
    • Benenson - RNAi governing transcript stability
    • these have been working in eukaryotes - mostly metazoans actually

ColE1 - RNA control of transcription via antisense interaction

  • what if we could use antisense interaction (like RNAi) to control transcritption
  • see image to understand the system
    • ColE1 (72 bp region) - high copy number replication origin in E. coli (we actually use this in the lab)
    • when transcribed, forms some complicated secondary structure that allows polymerase to carry on, so ON by default
    • if certain antisense piece of RNA added, will bind to this, causing a DIFFERENT RNA secondary structure down the line, which does not allow polymerase to pass
      • natural NOT gate
    • true antisense mechanism - does not require other proteins to work
    • looks designable
      • could change the ColE1 sequence to recognize different key anti-sense sequences
      • hopefully be able to do this with simple anti-sense matching
      • hopefully be able to keep GC-content the same so that the thermodynamics would not change too much
      • want many different (so orthogonal) ColE1 regions so can put them together in different ways

Initial Targets

  • recreate original experiments
  • try to find a sequence with a stronger repression factor
  • prove orthogonal
    • put 2 orthogonal ColE1s behind two genes - 2 diff inputs, make sure only one on for each input
  • reconstruct collins switch
    • get one system to produce anti-sense of the other
    • to get this to work, would have to make sure the system is cooperative
    • would need to measure the induction curve - if sigmoidal, see what can do with it

Applications

  • since this is RNA mediated, doesn't matter where the RNA comes from
    • could come from cancer cells (which are known to over-express certain RNAs)
    • would have to design ColE1s to recognize these specific sequences
  • the best papers make a new type of part - more powerful - more computation power - some application for these cells
    • RNAi logic, Molecular turing machines - Kobi Benenson
    • lots of power
    • beyond Adelman
    • more towards what I want to do
  • figure out need computational power X to do thing Y - put in an application context

Problems

  • currently only about a 3-fold repression - not that much
  • may not be an anti-sense thing - could be something more complicated (Chris Anderson seemed to indicate)
  • could be that the dynamic range is poor
  • kinetics could be poor
  • could be good for a NOT gate, but might need more logic on the promoter (like promoters that have several inputs - do an integration right there)

TOREAD

  • talk to Anthony Carruthers (looking at changing mRNA degradation rates)
    • also Jonathan Golder
    • also David Tulga - works w/ Anderson - Xis and Int recombination systems
    • alos Chris Anderson about RNA genes
  • big ColE1 people in europe
    • Sabin Brandtl
    • Gerhard Wagner
  • which papers like and why - which ones are the most exciting

Random Notes

  • other systems kind of like this
    • SacT terminator of B. subtilis - sacT binds to hairpin and opens
      • anti-termination with no modifications of the polymerase
  • iGEM - FMN - translational control
    • were trying to avoid the protein part - just another step to worry abou engineering
  • Niles Pierce - multi-stranded RNA systems