In a few decades, we’ll have synthetic bacteria functioning like autonomous robots. They’ll produce bioplastics, food, electricity all on their own. These smart designer bacteria will also be able to sense and precisely differentiate cancer cells from normal cells and eliminate them from the affected human body. Keeping this in mind, we wish to make logic based computations in cells as precise and predictive as we have them in our laptop chips. We seek to apply efficient methods and technology to assess, predict and control the variability in cells. Keeping these points in mind, we had started working on our project design.

To construct a biological oscillator, we would require various genetic parts with different strengths to function like an oscillator. Our oscillator would work only when we make it using modular parts, which provide complete information about their behavior with respect to other parts. Generally, we use a reporter protein to characterize the functionality of a device and don’t pay much attention to proper controls, which can lead to erroneous results. We can also have variation in a device's behavior due to intrinsic and extrinsic factors leading to a badly correlated function. We call this the noise associated with the device.

Noise in Devices

Experimental Design

Noise in any genetic device arises due to various inherent properties of the device. Our study aimed to address these issues using a device, which was designed to have two genetic components. The first component of the device consisted of the genetic part (promoter-RBS), required to be characterized. It was placed in conjunction with a GFP (green fluorescent protein) producing ORF (open reading frame). Whereas the second component of the device comprised of a RFP (red fluorescent protein) producing unit placed under a fixed promoter-RBS part. Thus, the expression level of the second component would not vary much- it could act as an internal control. These two genetic components of our device were cloned one after another in the same expression plasmid. The biological parts used in our device for the measurement of inherent noise and efficient characterization were comprised of different promoters, ribosomal binding sites (RBSs), two protein coding part (GFP, RFP) and terminators. Our device was constructed using pSB1A2 plasmid backbone and transformed in E. coli DH5 alpha cells.

According to the characterization done by William & Mary iGEM 2015 team, R0010 is more noisy than R0011 promoter, while RBSs role in noise estimation was not taken into account in the characterization. While building upon William & Mary 2015's project, we were prompted to see the role of RBSs and different promoters on intrinsic noise. Also, we wanted to see how do the intrinsic noise of individual parts give rise to intrinsic noise of complex devices. Therefore, we made six different devices. All of these six devices had same RFP expressing device. Out of the 6 devices, four GFP expressing devices had same IPTG inducible promoter but variations in RBS parts. Whereas in other two devices, GFP expressing component had different constitutive promoters.

In this experiment of ours, we have done better characterization by using an internal control (RFP producing module) of the strength of promoter-RBS composite parts K1956001, K1956002, K1956003, K1956004, J23151-B0032 and J23117-B0034. Also in our modelling section, we have estimated the strength and quantified the non-modularity of RBS part: B0030, B0032 and B0034.

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We have successfully constructed and cloned all of these devices. We have estimated cumulative intrinsic and extrinsic noise for all the six devices. We have observed a trend that intrinsic noise increases as protein expression from device increases. The obtained noise data provides a deeper insight into the origins of noise in genetic devices. These experiments helped us in assessing and understanding the impact of noise.




In order to make precise and predictable biological devices, which can be controlled at will, we have designed a ribo-regulatory switch and named it RIBOS (RNA Inducible Boolean Output like Switch). RIBOS works on the principle of Watson-Crick base pairing between trigger RNA and switch mRNA. RIBOS has been designed in such a way that whenever we want expression of the gene placed downstream, we just need to supply the trigger RNA molecules. The designed RIBOS which leads to expression of the downstream gene in the presence of trigger RNA has been named RIBOS-ON (or RIBOSON). Similarly, we designed another RIBOS using which we can halt the expression of the downstream gene at our will. The RIBOS designed by us to halt the expression of the gene under its control has been designated by us as RIBOS-OFF (or RIBOSOFF). Both of these RIBOS devices are great tools in controlling the expression of any gene of interest at our will through ribo-regulation. It has a huge potential applications ranging from detection and quantification of mRNA molecules to the design of independent and modular genetic circuits in limitless number using forward engineering. As a deliverable, the algorithm can be used by future iGEM teams to design RIBOSON and RIBOSOFF for any trigger sequence.



We have successfully cloned trigger RNA and switch RNA for RIBOSON and RIBOSOFF devices.

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We started working on our project in April. After ideating with our mentors for a few weeks, we drew up a detailed protocol for our project, and the experiments we would need to do to validate. We also maintained a diary where we noted down all of our observations and work done everyday. We had quite an eventful summer - the Indian iGEM team meet up happened in July, and we also came up with the idea for our game 'Codonut' and the GM survey during the same time. By August, most of the project work was done, and we began to work on the game and the GM survey.