Team:NUS Singapore/Model
Modelling
Overview
With the advancement in the field of synthetic biology, scientists have successfully engineered microbes to combat challenges in various fields such as medicine, energy, and environment. An important challenge hindering the translation of such genetically engineered microbes into the market is the risk of bacteria escaping from the targeted host into the environment. To address this issue, we develop an NUSgem Kill-switch Toolkit that enables users to build customized and effective kill-switches for different applications. This toolkit consists of a library of characterized sensors, logic gates, and killing systems.
Our intent is to make engineering of kill switches for different applications easier. To this end, we devised the following protocol which involves the use of computer aided design and modelling tools together with the toolkit.
- Choose a combination of input sensors from our library/iGEM registry. Input sensors should enable scientists to differentiate different environments which bacteria live.
- Characterize and calculate the Relative Promoter Unit (RPU) of sensors if sensors are not available in our toolkit. The protocol can be found here.
- Create a truth table and a timing diagram mapping input sensors and toxin-antitoxin products for various stages.
- Generate kill-switch circuits on CELLO.
- Model circuit and run simulation on Advancesyn to verify the performance of these circuits.
- Run sensitivity analysis and combinatorial analysis to optimize circuit design based on the following criteria:
- Response time (how fast the bacteria die)
- Metabolic stress on cells
- Toxin – antitoxin production
- Integrate circuit into plasmid and perform experiment.
We will demonstrate the use of NUSgem Kill-switch Toolkit in the following case studies:
Kill-switch for probiotics (Shawn & Wilbert)
Kill-switch for BeeT (Wageningen_UR iGEM 2016)
NUSgem Kill-switch Toolkit can also be applied to environmental applications such as the engineered bacteria BeeT from Wageningen_UR iGEM team. The engineered bacteria BeeT is programmed to release toxin that kill the parasitic mites Varroa destructor in beehive. Upon their release into the external environment, the two kill-switch will be activated to kill bacteria, thereby preventing the spread of genetically modified genes into the ecosystem [1].
- Optogenetic kill-switch consists of the pDusk/pDawn blue-light sensing system and the mazEF toxin-antitoxin system. When blue light is present, more toxin is produced. The accumulation of toxin in BeeT will degrade mRNA and cause cell death [2].
- Cas9 kill-switch is auxotrophic for a synthetic amino acid, para-L-biphenylalanine (BipA). In the absence of BipA, the activated kill-switch degrades DNA [2].
The proposed kill-switches is indeed robust, yet it still has some limitations. Firstly, it requires the production of many proteins in the cascaded pDusk/pDawn system for the optogentetic kill-switch to function. This may increase metabolic burden on cells. Secondly, the cascaded pDusk/pDawn and Cas9 systems are large. Hence, it may be difficult to integrate both kill-switches into one plasmid. Thirdly, it requires additional resources and effort to produce and apply synthetic amino acid, BipA to beehive for the Cas9 kill-switch to work.
In light of the abovementioned limitations, we propose three modifications for the current kill-switch. Firstly, we replace the pDusk/pDawn system with the BLind-v1 blue-light sensor promoter, which is smaller and has similar effectiveness in detecting blue light [3]. Secondly, E2-IM2 killing mechanism is adopted since it can degrade both mRNA and DNA [4]. This eliminates the need for the two kill-switch systems, hence alleviating the metabolic burden on cells. Lastly, we choose pH (e.g. Pasr) as the second sensor since it best characterizes the environmental condition inside and outside beehive. The use of the second sensor also make our kill-switch more specific. In addition, for E2-IM2 killing system to function properly, we develop a NAND gate, with pH and blue light as the two inputs. Similar to the first case study, E2 toxin is constitutively produced in all environments and its toxicity is neutralized when IM2 antitoxin is produced.
Due to time constraint, we were unable to characterize the blue light sensor. Assuming that the BLind-v1 and pH sensor promoter are of medium strength, the following NAND gate, which controls the production of IM2, is generated from CELLO.
