Team:Fudan/Acknowledgement

2018 iGEM Team:Fudan - Acknowledgement

Acknowledgement

Let us express the most sincere thanks to those who rendered their warm help to us. A successful team can’t be constructed without them.

Acknowledgement

Let us express the most sincere thanks to those who rendered their warm help to us. A successful team can’t be constructed without them.

2018 team Fudan title acknowledgement

Acknowledgement

  • We thank Yiheng Wang for teaching us to model DNA and transcription factor binding using his previous model.
  • We thank Tian Huang for providing us with a Materialize based wiki template and teaching us with basic knowledge about HTML and CSS.
  • We thank Yiming Cai for giving us advice on purifying EGFP protein, which was used in the beads assay at the early stage of the project.
  • We thank Yijie Pan for giving us practical suggestions on repeated fragment molecular cloning and BioBrick parts documentation.
  • We thank Xinxuan Xiong and Xinyi Xu for giving us useful advice about the Bio-ART display and actively helping us in preparation for the display.
  • We thank Ao Feng for helpful discussions on human practice.
  • We thank Jingyi Hu for helping us taking bacteria on the morning, and playing an active role in some of our human practice.
  • We thank Haotian Guo for incisive comments on refining our presentation during and immediately after CCiC.
  • We thank Professor Xu Wei’s advice on performing flow cytometry and doing the flow data analysis.
  • We thank Professor Yufang Zheng for helpful discussions on the known Notch regulation and unpublished insight from her study with metalloprotease [ADAM10] and [ADAM17].
  • We thank Professor Roman Jerala on email and face-to-face discussions on designing TALE based logic gates.
  • We thank Professor Stephen Blacklow on email and face-to-face discussions on engineered Notch receptor optimization.
  • We thank Doctor Lixin Yang, Doctor Ganjun Yu, Doctor Xiaoying Bi, and Doctor Pengfei Luo for sparing precise time to have the discussion on Interview doctors.
  • We thank Professor Xin Yuan, in the Department of Philosophy, for attending our Bio-Ethic debate and his comments enriched our understanding.
  • We thank Professor Jiang Zhong, Professor Xiaoming Ding, Professor Qiang Huang, and Professor Ting Ni for giving us valuable suggestions and feeds at different stages of the project, from the initial brainstorm to the middle project progress and the pre-departure presentations.
  • We thank the Club of FDU Bertalanffy Society for helping to rent the space for Bio-ART display.
  • We thank teachers in Qibao Dwight High School, Shanghai Jincai High School, the High School Affiliated to Fudan University for offering us with opportunities to implement our HP.
  • We thank Team:Fudan_China for teaching us how to use the plate reader.

Photos

People

Listed by alphabetical order of surnames.

doctor Bi Xiaoying Bi
Blacklow S Stephen Blacklow
Cai Yiming Cai
Ding Xiaoming Ding
Feng Ao Feng
Guo Haotian Guo
Hu Jingyi Hu
Huang Q Qiang Huang
Huang T Tian Huang
Jerala Jerala Roman
Luo Pengfei Luo
Ni Ting Ni
Pan Yijie Pan
Wang Yiheng Wang
Xiong Xinxuan Xiong
Xu W Wei Xu
Xu X Xinyi Xu
doctor Yang L Lixing Yang
doctor Yang S Shunhua Yang
doctor Yu Ganjun Yu
doctor Yuan Xin Yuan
Zhong Jiang Zhong
Zheng Yufang Zheng

Labs, Organizations & Schools

Changhai Changhai Hospital
Jincai Jincai High School
Fuzhong High School Affiliated to Fudan University
Qibao Shanghai Qibao Dwight High School

iGEM Teams

2018 Fudan-CHINA Fudan-CHINA 2018
2017 Fudan Fudan 2017
2017 Fudan_China Fudan_China 2017
2018 team Fudan abstract

Abstract

Contact-dependent signaling is critical for multicellular biological events, yet customizing contact-dependent signal transduction between cells remains challenging. Here we have developed the ENABLE toolbox, a complete set of transmembrane binary logic gates. Each gate consists of 3 layers: Receptor, Amplifier, and Combiner. We first optimized synthetic Notch receptors to enable cells to respond to different signals across the membrane reliably. These signals, individually amplified intracellularly by transcription, are further combined for computing. Our engineered zinc finger-based transcription factors perform binary computation and output designed products. In summary, we have combined spatially different signals in mammalian cells, and revealed new potentials for biological oscillators, tissue engineering, cancer treatments, bio-computing, etc. ENABLE is a toolbox for constructing contact-dependent signaling networks in mammals. The 3-layer design principle underlying ENABLE empowers any future development of transmembrane logic circuits, thus contributes a foundational advance to Synthetic Biology.