Introduction

To make our project more robust, we aimed to pass our builds through multiple design cycles based on experimental results, modelling input and guidance from stakeholders. Each engineering cycle would closely follow the iGEM engineering process, which involves deciding what we wanted our sensing system and E. coli to be capable of, assembling and testing its capabilities, before analysing the results to better inform the next cycle.

Due to unprecedented delays in shipping and handling, we had a smaller window to explore what could be done better. In an effort to refine our project to fit within the bounds of the competition, we were unable to put our project through the desired rigour. However, we were able to make some important decisions during the course of the project to increase the likelihood of success within the iGEM timeframe.

Composite Geneblock with Repeater Sequence

During initial dry lab planning, we designed Pyre1 with BsaI flanking sites to ensure compatibility with basic parts from the iGEM distribution kit. We ordered our gblocks from IDT, which was used during a one-pot Golden Gate cloning reaction into storage vector pJET. After low success with the assembly of the individual basic parts, we went back to the drawing board to consider alternatives. We concluded that there was little value in assembling the transcriptional unit in-house from individual parts. In the interest of time, we decided to design a composite part containing a promoter, RBS, Pyre1 and a terminator (Parts Overview). At the same time, our initial protein simulations showed low confidence in terms of folding. As a precaution, we added a repeater sequence to Pyre1 to minimise unintended amino acid interaction between CarCB2 and the ice nucleation protein.

With both a repeater and a linker sequence, we increased the likelihood of Pyre1 folding into its native conformation and its insertion into the membrane without creating any spatial hindrances. Apart from engineering the composite gene to include a repeater sequence, it was found that incubation at a lower temperature of 30°C also increased the likelihood of membrane insertion.

Optimising Aptamer Sensing System

To ensure a complete aptamer-based biosensing system is devised for our target pesticide, it was essential that each step and reagent involved went through optimisation cycles to ensure an accurate, and highly efficient detection system during implementation. When we used the initial protocol from existing literature, it failed to produce results. Subsequently, we returned to the drawing board, breaking apart our protocol into its constitutive parts. and run multiple cycles of optimisation tests for each of the reagents involved, including gold nanoparticles (AuNP), PDDA, aptamers, and varying concentrations of the pesticide (Results).

These sequential optimisation tests increased the likelihood of success with the implementation of our aptamer-based biosensor, especially within the iGEM timeframe. However, it is important to note that further optimisation tests are required, especially regarding increasing the sensitivities of the sensing system, so that pesticide levels much closer to the legal limit of lambda-cyhalothrin can be detected. This would be within the next engineering cycle. However, at present, this could not be conducted due to constraints of the iGEM timeframe.

Modelling

The modelling team made recommendations to copy numbers and transcription rates based on growth data collected in the lab for further optimisation of colony degradation rates. This was due to well understood molecular biology trade-offs and a phenomenon known as “burden”. A brief overview of findings shows that increased transcription rates did not always lead to increased degradation due to negative impacts on growth rates. For more information and a greater insight into the modelling approach please see the modelling page.

Test of Enzyme Activity

One of the biggest challenges throughout the project was designing a suitable enzyme assay to test for degradation of λ-cyhalothrin. This was primarily due to the chemical properties of both λ-cyhalothrin and 3-phenoxybenzaldehyde, the primary degradation product. These compounds are both hydrophobic and therefore have to be dissolved in organic solvents. This posed a challenge when used in living biological systems. Secondly, these difficulties were exacerbated by the time constraints imposed by delays in receiving the distribution kit and the timeline for obtaining successful transformation.

Initial tests were conducted using GC/MS, which failed to detect standards of our pesticide. Following discussions with Dr Lijiang Song (Head of Mass Spectrometry Facility), the susceptibility of GC/MS to water meant sample preparation would be difficult and the concentrations required were far too low to be confident in successful dilution of oils. Although this method is used in industry for pesticide screening in this use case it would require a large time investment to optimise and troubleshoot GC/MS results.

We later moved to working with TLC, designing protocols to screen multiple solvent systems (ethyl acetate, hexane and petroleum ether in varying ratios) as well as varying concentrations of λ-cyhalothrin and 3-phenoxybenzaldehyde to produce standards. Based on troubleshooting results we were able to visualise both compounds under UV at 254 nm. However, we discovered they held similar RF values, meaning it would be hard to distinguish mixed sample results from any enzyme assay.

Next, we tested with HPLC, this would be forgiving during our sample preparation, at the compromise of sensitivity. We were able to successfully detect both compounds in a methanol solvent, however we were not confident in the results due to errors between replicates. We discussed this with Christopher de Wolf (WISB Senior Technician), and redesigned our HPLC method changing solvent systems to acetonitrile with formic acid. Testing with this solvent system reduced the length of each run as the retention times were lower, saving us valuable time. We also moved to working over a larger range of concentration using standard dilutions to improve the reliability of our standard curves. We successfully developed standard curves for both compounds and therefore could set up an enzyme assay within this concentration range.

Despite what we have done so far, the iteration process is far from complete and there is potential for major improvements in the product development cycle before we are confident in presenting it as a minimum viable product.