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Engineering

Introduction

Construction of the NanoFind system was carefully built upon good engineering practices to maximize the efficiency of the development process and quality of the final system. During the project, multiple iterative engineering cycles (design, build, test, learn) were executed to build a reliable system. These principles have allowed us to successfully build our proof-of-concept nanoplastic detection system. In the following page, these principles and steps are described in more detail.

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Peptide detection

Overview

After learning about the increasing global problem of nanoplastic pollution, its harsh potential consequences and the current lack of detection tools, our team has decided to develop a robust, easy-to-use nanoplastics detection system that would open up new ways in solving this rising issue.

The first step after choosing our goal was to develop the concept for the NanoFind detection system. Our main priority while creating the strategy was to define some initial parameters of this tool. First, we understood that we need to create a relatively cheap detection platform, thus making the usage of such a system as wide as possible with minimal financial restrictions. Second, it was important that this test would be applicable for aqueous samples since nanoplastics can be found in different types of water. The last important aspect while creating the concept of the NanoFind diagnostic tool was to make it orthogonal - by enabling it to detect and differentiate frequently used plastics in real time.

With the aim to have a good starting point for our system, we did an in-depth research where we analyzed different detection systems that can detect various materials. We have selected binding peptides as the base for our concept system for two reasons. First, we have seen proof from literature that peptides have already gained traction for solving different detection problems and showed exceptional results in this field [1][2][3][4][5]. Secondly, there was fundamental research done describing how some peptides can distinct different plastics of interest with high affinity [6][7]. Due to these findings, we have decided to base our detection system NanoFind on peptides that would be specific to different plastics. We chose peptides LCI and TA2 [7][8] that can be successfully synthesized and tested in a laboratory as it was previously shown in literature.

We also needed to think of a way to get an output from a system. Ideally, this would be an output that could be easily measured with standard laboratory equipment. Fluorescence based methods fulfill such requirements. By keeping this in mind, we have included an immobilization unit and a fluorescent protein into our system concept.

Therefore, the final concept of the system was an immobilized peptide based assay with fluorescence output, capable of discriminating different nanoplastics found in various water samples.

Protein purification and testing

In order to test our detection system, we needed to successfully purify proteins, test their functionality, quantify domain activity and determine whether our peptide-domain fusion proteins are able to attach to plastics.

To see different iteration phases, click on the grey arrows below.
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ITERATION 1
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Design

For NanoFind system to work, our team designed several plastic binding peptide (PBP)-protein fusion proteins:

Cellulose binding domain + plastic binding peptide → for immobilization (Parts: BBa_K4380015, BBa_K4380017)

Green fluorescent protein + plastic binding peptide → for signal report (Parts: BBa_K4380016, BBa_K4380018)

These two proteins would form a "sandwich" complex - two plastic binding peptides would surround the nanoplastic particle, present in the water sample, detect and differentiate frequently used plastics in real time.

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ITERATION 2.1
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CBD fusion protein - Design

In this protein synthesis iteration we decided to test whether we can synthesize higher yield of soluble Peptide-CBD fusion proteins by using different protein synthesis platforms.

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ITERATION 2.2
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GFP fusion protein - Design

After trying different protein synthesis optimization approaches, we saw that our protein sequence is lacking two essential amino acids that are needed for the correct folding as well as for the desired function of the protein - fluorescence.

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ITERATION 3
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Design

Even though the synthesis and purification of target proteins were successful, we saw that the concentration of these proteins is too low and inconsistent.

Testing domain functionality

Research

To test whether our system has a potential to work, we needed to test its separate domains and answer very important questions:

  • 1) Do our plastic binding peptide (PBP) fusion proteins are able to bind specific plastic?
  • 2) Is our cellulose binding domain attached to cellulose and has the ability to immobilize our plastic binding peptides?
  • 3) Is our GFP sufficient enough to give fluorescence after our peptide is bound to a plastic molecule?

For this, we found, used or invented several different methods for separate domain testing.

Cellulose binding fusion protein binding assays

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ITERATION 1
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Design

In order to test the CBD binding domain we needed to design several strategies. Since the system includes peptides, which are known to have a high affinity for plastic, there was also a need to be certain that our cellulose binding domain can be attached to cellulose.

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ITERATION 2
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Design

We designed an experiment based on Miller et al. 2018 [10], to see whether our CBD has the ability to bind cellulose and measure, what is the sufficient protein amount needed to fully saturate cellulose. For this test, purified proteins were needed.

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ITERATION 3
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To measure at what concentration our cellulose gets fully saturated with CBD, we decided to use a higher amount of purified protein and measure, at what point our cellulose binding domain starts showing full saturation.

GFP bound fusion protein testing

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A crucial part of our project is the peptide ability to attach to a certain plastic. Although the peptides by themselves are shown to bind to plastic, they cannot give a signal by themselves, therefore, by attaching peptides to a certain reporter protein (in our case- GFP), we are able to visualize whether fusion proteins are bound to plastic.

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ITERATION 2
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Design

For this, we used a glass bottle experiment and our "newly made" homemade glass bottle columns (see Contribution).

Nanoplastic detection system using peptides

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Design

The NanoFind detection system was designed as a formation of sandwich-like complexes upon interactions between fusion peptides and plastic nanoparticles. Since we have successfully shown that all our system components work as expected and efficiently, the next step was to test the ability of our system to function as a unit, providing easy-to-interpret, light-based results.

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ITERATION 2
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Design

The design flow stayed the same as it was in the first cycle, yet we also included more steps - lower concentration of nanoplastic samples were tested with the higher ones, more comprehensive washing iterations were included, we also tested the fluorescence signal at every washing step.

Bacterial detection

Overview

During the development of the NanoFind detection system, we did encounter many problems, which needed creative and novel solutions. One of them was that our nanoplastic detection system might not be able to produce a signal, when nanoplastic concentrations are extremely low. To solve this, we might need a certain signal amplification system, if nanoplastics are present in the sample.

As a solution for this problem we developed an alternative way to detect nanoplastics - bacterial detection.

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Design

Our team designed a cell surface display system based on the protein of Pseudomonas aeruginosa EstA (BBa_K2694001) and added a sequence that would be identified with an antibody (BBa_K4380002), which can be used to evaluate bacterial expression of cell surface display proteins. This type of cell surface display system allows our plastic binding peptides to be expressed onto bacterial membranes.

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ITERATION 2
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To check if our system is expressed onto a bacterial membrane, the next engineering step was to use an epitope, which would be inserted into the same genetic circuit as our bacterial surface display protein. By doing this, the epitope would be expressed onto the cell surface and would be attainable by an antibody.

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ITERATION 3
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After our findings have shown that our bacterial cell surface display system cannot be evaluated by antibody binding fluorescent signal quantitative result, we decided to see whether qualitative data can prove that our system is working.

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ITERATION 4
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After the 3rd iteration, we found out that our system cannot be successfully controlled with induction and evaluated using antibodies. For this, we looked at alternative ways to express our system on bacterial membranes and evaluate the true fluorescence of plastic attached bacterial presence.

Peptide evolution

Overview

Although using known peptides for a detection system already is a huge challenge in itself, we wanted to characterize novel peptides and create huge peptide libraries, which could be used for specific plastic binding in our detection system. Therefore, we decided to do a peptide evolution, specifically designed for plastic-binding peptides.

Robust directed evolution protocol enables to tailor polymer binding peptides for efficient binding to polymer plastics. The key to a successful evolution campaign is to develop mutation-prone methods to ensure efficiency in the diversity of polymer-binding peptides. For this kind of assay, a high mutation rate is needed.

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Design

To start, our team decided to test whether peptides that we were already using can successfully go through peptide evolution protocol and potentially have a higher binding affinity than the ones we already tested. Our team designed a cell surface display system, based on the protein of Pseudomonas aeruginosa EstA (BBa_K2694001). The system contained a couple of sequences, which stayed the same between the different plasmid constructs. By utilizing these sequences, and creating primers based on them, our peptide sequences can be successfully amplified by different error-prone PCR (epPCR) approaches.

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The method utilized for peptide library cloning into bacterial plasmid vectors was megaprimer PCR. The megaprimer method is a simple and versatile approach that can be adopted for mutation cloning into plasmid vectors. DNA template containing the mutated gene goes through the second round of PCR and can be successfully cloned into plasmid vectors.

Nanoplastic sample preparation

Overview

Degradation of plastic waste in the environment leads to the formation of microplastics and nanoplastics. To better understand the behavior of nanoplastics, it is essential to conduct experiments with representative and well-characterized nanoplastics. Since meeting with various experts, working in the nanoplastic research field, we have decided that in order to imitate environmental samples, we need to make our own nanoplastic samples. These nanoplastics may share similarities with environmental nanoplastics as referred to by their chemical nature and morphology. Thus, to create a system with the purpose of detecting nanoplastics in the environment, we needed to find and optimize methods for nanoplastic preparation.

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Design

According to an article by Hadri et al., 2020 [11], we have created a protocol to make nanoplastics by mechanical fragmentation of bigger plastic particles.

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ITERATION 2
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To be able to use samples for testing our detection tool, we needed to make aqueous dispersions of nanoplastics. The dispersions had to be stable, but also they shouldn't have contained aggregated particles.

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ITERATION 3
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In this iteration, we thought of mixing lower amounts of plastics with the same volume of buffer and adjusting the surfactant concentration as well to disperse as many plastic particles as possible. After leaving dispersions to form layers with different stability we took samples from the stable middle fraction.

Conclusions

During the project, multiple iterative engineering cycles (design, build, test, learn) were executed to build a reliable system. The project went through different stages, in which engineering a synthetic biology based system required ingenuity, well thought decisions and precise measurements. These principles have allowed us to successfully build our proof-of-concept nanoplastic detection system.

Final concept of the "NanoFind" detection system:
final-concept-nanofind
References:
[1] Bromley, E. H. C., Channon, K., Moutevelis, E., & Woolfson, D. N. (2008). Peptide and protein building blocks for synthetic biology: From programming biomolecules to self-organized biomolecular systems. ACS Chemical Biology, 3(1), 38-50. https://doi.org/10.1021/cb700249v
[2] González-Cruz, A. O., Hernández-Juárez, J., Ramírez-Cabrera, M. A., Balderas-Rentería, I., & Arredondo-Espinoza, E. (2022). Peptide-based drug-delivery systems: A new hope for improving cancer therapy. Journal of Drug Delivery Science and Technology, 72, 103362. https://doi.org/10.1016/j.jddst.2022.103362
[3] Nagy, K., McBride, R., Head, S. R., Ordoukhanian, P., & Law, M. (2023). Low-cost peptide microarrays for mapping continuous antibody epitopes. M. Cretich & A. Gori (Sud.), Peptide Microarrays: Methods and Protocols (p. 63-81). Springer US. https://doi.org/10.1007/978-1-0716-2732-7_6
[4] Srila, W., Baumann, M., Borth, N., & Yamabhai, M. (2022). Codon and signal peptide optimization for therapeutic antibody production from Chinese hamster ovary (Cho) cell. Biochemical and Biophysical Research Communications, 622, 157-162. https://doi.org/10.1016/j.bbrc.2022.06.072
[5] Tan, Y., Wang, M., & Chen, Y. (2022). Reprogramming the biosynthesis of precursor peptide to create a selenazole-containing nosiheptide analogue. ACS Synthetic Biology, 11(1), 85-91. https://doi.org/10.1021/acssynbio.1c00578
[6] Apitius, L., Rübsam, K., Jakesch, C., Jakob, F., & Schwaneberg, U. (2019). Ultrahigh-throughput screening system for directed polymer binding peptide evolution. Biotechnology and Bioengineering, 116(8), 1856-1867. https://doi.org/10.1002/bit.26990[7] Rübsam, K., Davari, M. D., Jakob, F., & Schwaneberg, U. (2018). Knowvolution of the polymer-binding peptide lci for improved polypropylene binding. Polymers, 10(4), 423. https://doi.org/10.3390/polym10040423[8] Rübsam, K., Weber, L., Jakob, F., & Schwaneberg, U. (2018). Directed evolution of polypropylene and polystyrene binding peptides. Biotechnology and Bioengineering, 115(2), 321-330. https://doi.org/10.1002/bit.26481[9] El Hadri, H., Gigault, J., Maxit, B., Grassl, B., & Reynaud, S. (2020). Nanoplastic from mechanically degraded primary and secondary microplastics for environmental assessments. NanoImpact, 17, 100206. https://doi.org/10.1016/j.impact.2019.100206[10] EMiller, E. A., Baniya, S., Osorio, D., Maalouf, Y. J. A., & Sikes, H. D. (2018). Paper-based diagnostics in the antigen-depletion regime: High-density immobilization of rcSso7d-cellulose-binding domain fusion proteins for efficient target capture. Biosensors & bioelectronics, 102, 456-463. https://doi.org/10.1016/j.bios.2017.11.050[11] El Hadri, H., Gigault, J., Maxit, B., Grassl, B., & Reynaud, S. (2020). Nanoplastic from mechanically degraded primary and secondary microplastics for environmental assessments. NanoImpact, 17, 100206. https://doi.org/10.1016/j.impact.2019.100206[12] Nicolay, T., Lemoine, L., Lievens, E., Balzarini, S., Vanderleyden, J., & Spaepen, S. (2012). Probing the applicability of autotransporter based surface display with the EstA autotransporter of Pseudomonas stutzeri A15. Microbial Cell Factories, 11, 158. https://doi.org/10.1186/1475-2859-11-158
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