Difference between revisions of "Part:BBa K2549021"

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LaG16-2-mN1c-GV2 ([[Part:BBa_K2549020]]) and αCD19-mN1c-tTAA ([[Part:BBa_K2549021]]) perform well together, which were used as our common Receptors for ENABLE 16 logic gates.
 
LaG16-2-mN1c-GV2 ([[Part:BBa_K2549020]]) and αCD19-mN1c-tTAA ([[Part:BBa_K2549021]]) perform well together, which were used as our common Receptors for ENABLE 16 logic gates.
  
[[Part:BBa_K2549006]] is exactly as the published version, and results are shown below. Our early results show three things: (1) SynNotch background activation is very high, which is why we put a lot effect in http://2018.igem.org/Team:Fudan/Optimization ; (3) mN1c might be better than mN1ce, not only shorter but a little higher signal-noise-ratio; (3) LaG17 is NOT a good extracellular antibody for SynNotch. <i>Use our improved sets, if you want to SynNotch!</i>
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[[Part:BBa_K2549006]] is exactly as the published version, and results are shown below. Our early results demonstrate three things: (1) SynNotch background activation is very high, which is why we put a lot effect in http://2018.igem.org/Team:Fudan/Optimization ; (3) mN1c might be better than mN1ce, not only shorter but a little higher signal-noise-ratio; (3) LaG17 is NOT a good extracellular antibody for SynNotch. <i>Just use our improved sets, if you want to SynNotch!</i>
  
 
[[File:MouseN1ce1c.png|none|333px|thumb|'''Flow cytometry results of the original published SynNotch - not good comparing with ours.''' surEGFP is the surface expressed EGFP, which was used as the antigen. Without antigen (+Mock), the EGFP (Y axis, driven by tTAA released after SynNotch activation) was low, and it went "high" after adding the antigen. More details please visit http://2018.igem.org/Team:Fudan/Results and http://2018.igem.org/Team:Fudan/Optimization .]]
 
[[File:MouseN1ce1c.png|none|333px|thumb|'''Flow cytometry results of the original published SynNotch - not good comparing with ours.''' surEGFP is the surface expressed EGFP, which was used as the antigen. Without antigen (+Mock), the EGFP (Y axis, driven by tTAA released after SynNotch activation) was low, and it went "high" after adding the antigen. More details please visit http://2018.igem.org/Team:Fudan/Results and http://2018.igem.org/Team:Fudan/Optimization .]]

Revision as of 02:07, 18 October 2018


aCD19-mN1c-tTAA

This part is one of our SynNotch receptors, similar to the original published version[1]. It is our favorite. αCD19 (Part:BBa_K2549005) is used as the extracellular sensor module to receive the signal input from surface-expressed CD19. mN1c (Part:BBa_K2549006) is served as the transmembrane core domain of SynNotch, which is evident to have a low basal expression and a high activation efficiency. tTAA (Part:BBa_K2446057) is an improved tetracycline-controlled transactivator[2], which is cleaved after SynNotch activation and drives the expression of the amplifier. Besides, a CD8α signal peptide (Part:BBa_K2549044) and a Myc-tag (Part:BBa_K823036) are added to the N terminal of αCD19 (Part:BBa_K2549005) for membrane targeting and easy determination of surface expression.

Sequence and Features


Assembly Compatibility:
  • 10
    COMPATIBLE WITH RFC[10]
  • 12
    COMPATIBLE WITH RFC[12]
  • 21
    COMPATIBLE WITH RFC[21]
  • 23
    COMPATIBLE WITH RFC[23]
  • 25
    INCOMPATIBLE WITH RFC[25]
    Illegal NgoMIV site found at 2493
  • 1000
    INCOMPATIBLE WITH RFC[1000]
    Illegal BsaI site found at 534
    Illegal SapI.rc site found at 1408


Biology

Our characterization
Flow cytometry results of SynNotch activation. surAg, surface antigens, which was surface-expressed CD19 for αCD19-SynNotch or surface-expressed EGFP for LaG-SynNotch, respectively. Without surAg, the EGFP (Y axis, driven by tTAA released after SynNotch activation) was low, and it went high after adding surAg. More details please visit http://2018.igem.org/Team:Fudan/Results and http://2018.igem.org/Team:Fudan/Optimization .

It is obvious that αCD19-mN1c-tTAA can be significantly activated by surface-expressed CD19. It also has the highest signal-to-noise ratio among all the SynNotch receptors that we submitted. Besides, it has a lower background activation ratio comparing to others.

LaG16-2-mN1c-GV2 (Part:BBa_K2549020) and αCD19-mN1c-tTAA (Part:BBa_K2549021) perform well together, which were used as our common Receptors for ENABLE 16 logic gates.

Part:BBa_K2549006 is exactly as the published version, and results are shown below. Our early results demonstrate three things: (1) SynNotch background activation is very high, which is why we put a lot effect in http://2018.igem.org/Team:Fudan/Optimization ; (3) mN1c might be better than mN1ce, not only shorter but a little higher signal-noise-ratio; (3) LaG17 is NOT a good extracellular antibody for SynNotch. Just use our improved sets, if you want to SynNotch!

Flow cytometry results of the original published SynNotch - not good comparing with ours. surEGFP is the surface expressed EGFP, which was used as the antigen. Without antigen (+Mock), the EGFP (Y axis, driven by tTAA released after SynNotch activation) was low, and it went "high" after adding the antigen. More details please visit http://2018.igem.org/Team:Fudan/Results and http://2018.igem.org/Team:Fudan/Optimization .
Clinical significance of anti-CD19

Please refer to our basic Part:BBa_K2549005 for more details.

SynNotch receptors function well in Morsut L et al 2016
Morsut L et al stated:SynNotch receptors provide extraordinary flexibility in engineering cells with customized sensing/response behaviors to user-specified extracellular cues.
Morsut L et al have shown that modularity of the synNotch platform. They stated: the input and output domains from Notch can be swapped with diverse domains. On the extracellular side, diverse recognition domains can be used (antibody based, or peptide tags are shown) and on the intracellular side, diverse effector can be used (transcriptional activators with different DNA-binding domains are shown, as well as a transcriptional repressor).

Please refer to the original article for more details.


References

  1. Engineering Customized Cell Sensing and Response Behaviors Using Synthetic Notch Receptors. Morsut L, Roybal KT, Xiong X, ..., Thomson M, Lim WA. Cell, 2016 Feb;164(4):780-91 PMID: 26830878; DOI: 10.1016/j.cell.2016.01.012
  2. Exploring the sequence space for tetracycline-dependent transcriptional activators: novel mutations yield expanded range and sensitivity. Urlinger S, Baron U, Thellmann M, ..., Bujard H, Hillen W. Proc Natl Acad Sci U S A, 2000 Jul;97(14):7963-8 PMID: 10859354