Team:BostonU/Backbones

From 2014.igem.org

• TEAM
• PROJECT
  • Overview
  • Priority Encoder
  • MoClo Assembly Method
  • Low Copy Backbones
  • Tandem Promoters
  • Fusion Proteins
  • Repressor Proteins
  • Multiplexing
  • BioDesign Automation Tools
  • Future Work
• ACHIEVEMENTS
  • Data Collected
  • Parts Submitted
  • Chimera Workflow
  • Chimera Example
  • Medal Fulfillment
• NOTEBOOK
  • Training
  • Protocols
  • Backbones
  • Tandem Promoters and Repressors
  • Fusion Proteins
• CONSIDERATIONS
  • Collaborations
  • Measurement Track
  • Safety
  • Interlab Study
  • NEGEM
  • Policy and Practices
• ACKNOWLEDGEMENTS

Lower Copy Backbones

Why Lower Copy Count Origins of Replication? The work carried out by previous BU iGEM teams used destination vectors, or plasmid backbones, with high-copy origins of replication. Having only these high-copy plasmids as an option in our library would not allow for optimal performance of our multiplexed transcriptional units and larger constructs. Additionally, works upon which we are basing our complex circuit assembly do not use high copy origins for all plasmids in their devices. Circuit behavior can be desynchronized with the use of a high copy origins for all plasmids, as it causes over-expression of the plasmid in a cell, leading to a high amount of transcription and protein expression, which can sometimes be toxic or problematic for complex device function. For more complex circuits, this over-expression pushes the limit of the amount of ribosomes that can be sequestered for translation, in addition to straining the cell's protein degradation mechanisms. Published complex genetic circuits, for example the NOR gates [1] and the Collins counter [2], are often in cloned in medium or low copy vectors, using the ColE1 or p15A origin of replication, respectively. The plasmid maps shown below are from those papers and show the origins of replication used for their work. The image above shows two plasmid maps from the NOR paper [1] (right and middle) and one of the counters [2] (left). These were obtained from the Supplemental Information for both publications. Detailed progress on new vector backbone creation can be found in the backbones notebook.

Design and Assembly

The origins we selected were sourced from plasmids employed in Prof. Chris Voigt's work on layered logic gates [3]. We selected the ColE1, p15A, and pSC101 origins because they are commonly used origins of replication in the literature for high, medium, and low copy number respectively. The cloning strategy involved using PCR to amplify out the desired backbone from our library without its high copy origin, in addition to the desired origin from its parent construct. The PCR primer sequences added restriction endonuclease sites on each end of the amplicons, one for the enzyme MfeI and the other for AscI These were selected because neither the backbone nor any of the origins contained restriction sites for these endonucleases. The amplicons were digested with both enzymes, and were ligated and transformed.

Schematic of origin cloning - The PCR primer design added restriction sites for the MfeI and AscI restriction enzymes, which would give the ends of each of the amplified fragments compatible 4bp overhangs suitable for ligation. (Detailed primer design available here).

Testing Flow cytometry testing of new low copy backbones has been carried out for the p15A origin against the pMB1 origin, using the flow cytometry controls. MoClo was used to replace the LacZ fragment of the new backbone with a transcriptional unit constitutively expressing fluorescence - all the combinations of fluorescent proteins and origins of replications are found below. More information on the flow cytometry experiments for the backbones can be found in the backbones notebook. The combinations of plasmid origins of replication and fluorescent reporters used for testing the function of the p15A origin of replication against the high-copy pMB1 origin.

References [1] A. Tamsir, J. Tabor, C. Voigt (2011). “Robust multicellular computing using genetically encoded NOR gates and chemical ‘wires’.” Nature 469: 212-215 [2] A. Friedland, T. Lu, X. Wang, D. Shi, G. Church, J. Collins (2009). "Synthetic Gene Networks That Count." Science 324:1199-1202 DOI: 10.1126/science.1172005 [3] T. S. Moon, C. Lou, A. Tamsir, B. C. Stanton, C. A. Voigt (2012). "Genetic programs constructed from layered logic gates in single cells" Nature 491, 249.

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