Overview of Engineering

The essential part of our project is the production of a quantitative rapid test against the skin microbial community. For our test we focus on two parts, firstly targeting the dominant species of C. acnes and all Gram-positive skin bacteria by using SELEX in Aptamer technology and secondly the creation of a colorimetric detection method using PCDA polymer to observe binding of the aptamer to the ligand.

Aptamer Production

Research

Aptamers are small, single-stranded oligonucleotide (RNA or ssDNA) molecules that can hybridise to form complex structures. These folded three-dimensional structures form interactions with small molecule targets which can be detected,1 as shown in Fig. 1. The aptamer libraries are obtained using the Systematic Evolution of Ligands by Exponential enrichment (SELEX) technology. SELEX is a basic technique for the selection of aptamers in vitro against various targets, ranging anything from small molecules like ATP to proteins to even whole cells. The interaction between the aptamer and its target involves different intermolecular interactions including van der Waal’s forces, electrostatic interactions between charged groups and three-dimensional shaping by hydrogen bonds.

Due to the ability of aptamers to recognize targets and binding specificity, they are often compared to antibodies, but the former can be crafted to bind to multiple different targets unlike antibodies which can only bind to proteins. These aptamers are also much smaller than antibodies, easier to work with as they are more stable to heat and organic solvents and can be readily chemically synthesized. These properties provide a huge market for aptamers to be used in the field of diagnostics, biomarkers for different diseases including cancer and drug delivery.

Figure 1: What are aptamers? The structure was generated in BioRender using reference

Design

In our project, we aimed to develop two aptamers, one is targeting teichoic acid that is present in the cell wall of all gram-positive bacteria, these being dominant on the skin can be used for quantification of the skin microbiota. The second is a cell-based aptamer is targeting a strain of C. acnes, which is dominant in acne-prone skin, according to research2. These SELEX libraries are amplified with their respective targets by running them for several cycles of PCR. Eventually, the optimal number of PCR cycles is obtained which shows high-affinity binding of the library to the desired target and gives our aptamer! SELEX is therefore a process of directed and targeted in vitro evolution.

Building and Testing

In the lab, we have created our own protocol for the production of the two aptamers. We have consulted with our instructor, Dimitri Van Simaeys, and referred to research papers to find the optimal protocols for aptamer selection. We have faced a lot of problems while designing the aptamers, a series of feedback loops between bench and bedside, starting from ordering the wrong primers to the PCR not working at all for over 2 months. We have hypothesized and tested several protocols over the months in the lab when sometimes our PCR components would be contaminated, or the library would not be amplified enough, or even have amplification in non-template control.

Recently, we have had some success with the amplification of the library after we completely altered the concentrations of the PCR components, decreasing the template by 3000x to increase the primer volumes, closely following the protocols by Takara HS Taq.

Learning and Improving

In our journey in the lab, we have learned a lot about troubleshooting techniques when comes to PCR reactions and emerged victorious towards the end. However, we did not have enough time to have produced our aptamers but eventually, we improved our techniques such that future iGEM teams working with aptamers will be greatly benefiting from them.

Detection using PCDA

Research

After researching ways to create the quantitative test to examine the dysbiosis in the skin microbiome, we decided to base our detection tool on a colorimetric method. We have used the property of polydiacetylene (PCDA) polymers to change colour under stress conditions like chemical, mechanical, heat, or radiation.

Design

In our project, we are detecting the specific species of bacteria present on the skin. The idea of this detection method is based on the fact that when there is the binding of our PCDA bound aptamer to the target, be it teichoic acid or C. acnes cell, there will be a structural change in the polymeric PCDA due to stress. This structural change can be observed with a colour change from blue (monomeric solution) to red (polymerized) which will be proportional to the amount of detected target. We can then detect it by measuring the absorbance using a spectrophotometer, and thereby use it as a quantification test for dysbiosis.

Figure 2: Polymerization of crystalline diacetylene monomers under heat stress. The structure was generated in ChemDraw using reference

Building and Testing

We initially tested this detection method by inducing UV radiation overnight to the PCDA polymeric solution and observed colour change. This produced a subtle colour change. We then moved on to test our quantification method by inducing heat stress from a Bunsen burner for a few seconds. This caused the colour change to be way faster into a bright orange, and easily detectable.

Learning and Improving

From this improvement in the operationalization technique, we found a better detection approach. We think it might be because there is a higher energy flux transfer when heating for a few seconds rather than placing the polymeric solution under UV radiation overnight. We can also use this rapid detection test for any new developing aptamer, so it can be used as a high throughput test depending on the number of targets.

References

https://doi.org/10.1038/nrd3141

https://doi.org/10.1007/s40257-020-00531-1

10.1038/mtna.2014.32

10.1016/j.forsciint.2011.09.019

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In text citation for a research article with a DOI. Rosano et al., 2019

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References

1. Allen, M. J., & Sheridan, S. C. (2015).

   Mortality risks during extreme temperature events (ETEs) using a distributed lag non-linear model.

   International Journal of Biometeorology 62(1), 57-67.

   CrossRefGoogle ScholarBack to text

2. Rosano, A., Bella, A., Gesualdo, F., Acampora, A., Pezzotti, P., Marchetti, S., ... & Rizzo, C. (2019).

   Investigating the impact of influenza on excess mortality in all ages in Italy during recent seasons (2013/14-2016/17 seasons).

   International Journal of Infectious Diseases 88, 127-134.

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3. Ingalls, B. P. (2013).

   Mathematical modeling in systems biology: An introduction.

   MIT Press.

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4. Agriculture: Crop production: Sugarcane. TNAU Agritech Portal.

   (March 15, 2019). Retrieved on June 22, 2020. from https://google.com

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   Agriculture: Crop production: Sugarcane. TNAU Agritech Portal.

   Retrieved on June 22, 2020. from https://google.com

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