Bluprint of our project

If people want to drive a system to work for them, even if the system is a simple one, simply keep pushing the system toward the goal may not be the best shoot. For example, if a professor is too pushing, his students may, on the contrary, unable to perform their best; if a farmer adding too much fertilizer, the land may be damaged in the long run, etc.

Biological systems are extremely complex, and the components in the system are intensely interconnected. So in order to exploit the maximum potentiality of a biological system, we'll have to keep the protein or metabolic product production in a desired range. Not too high, as it may hurt the cell or inhibit its growth; either not too low, as it will be economically inefficient.

So how can we reach a desired range of expression? We need to properly combine the transcription and translation initiation elements, just as an recent published Nature article suggested[1]. But that paper just used the throughly studied E.coli expression elements in E.coli. What if we are doing engineering in a non-model organism that we just have data about a handful of expression elements, can we create the elements we need?

Our project proposed a way to employ a limited set of promoters to reach any desired expression level, or even switch between several expression level.

Fig.1 Tandem promoter
First, we combined the known promoter into tandem promoter system. We've done experiments and modeling to show how can we use a 0.1 promoter and a 0.3 promoter to reach expression level from 0.1 to the maximum. Please check experiment here and modeling here.

Fig.2 Cas9 regulated multistage promoter
Fig 3. An analog to slide rheostat
Then, we made the tandem promoter a “slide rheostat” by using d/aCas9 to regulate it. This enable the tandem promoter to switch between several designable expression level, and become a multistage promoter. This is different from the normal regulated promoter that usually has only two stage: on and off (Fig.4). To see our experiment about this multistage promoter, please click here. It's also important to ensure the orthogonality of this multistage promoter. So the off-target tendency of Cas9 is modeled and analyzed by combining the data of six paper about Cas9 off-target. For the modeling result, please click here.

Fig 4. Bi-stage promoter and multistage promoter

Reference

[1]Mutalik, Vivek K., et al. "Precise and reliable gene expression via standard transcription and translation initiation elements." Nature methods 10.4 (2013): 354-360.