Contribution

From the beginning of our project, human practices (HP) and wet team have been in a spiral of complementary development: HP's interviews, research and data collection are based on the progress and problems encountered by wet team. Simultaneously, the design of experimental ideas for wet Team is based on the feedback from the human practices for modification and improvement.

Therefore, these two components complement each other, serving as a crucial collaborative model for the successful progression of our project

During the first half of the project, we encountered inevitable issues when using binary oscillations as a key experiment. After an interview with Dr. Boxiang Wang(one of the founder and CTO of Shenzhen Lingula Technology Co., Ltd.), it was confirmed that this approach was not suitable for our project at this stage and had many uncertainties that were beyond our current capabilities to address. This setback placed our project's experiment design in a significant crisis. Subsequently, with extensive literature review and expert interviews, a new experiment plan was devised.

Throughout the development of our project, on-site research conducted in the realm of HP repeatedly led to the rejection of experiment plans and design concepts or encountered bottlenecks. However, through information feedback and timely updates, we established an effective feedback mechanism, which is also the practical experience we aim to convey to the public through our HP efforts.

We have summarized two frameworks for conducting HP activities by referencing several outstanding teams.

Firstly, we focus on stakeholders and collect and organize information about stakeholders who have an impact on our project. This approach provides us with a broad direction to conduct HP activities with a specific purpose. It helps us maintain the project's logical coherence and enables us to provide targeted feedback to the wet team component.

The second framework involves planning tasks on a timeline for each project phase. This approach helps us gain a clearer understanding of the project's development and facilitates the organization and prioritization of project tasks in later stages. These two framework models have helped us conduct HP activities and research results more efficiently. We hope that our experiences can be of assistance to others.

The following are the parts we have modified:

We have added the Cry3A-like protein to the component library, which has been successfully expressed it in E. coli, and conceptually validated that the expressed toxin protein retains activity for killing S.invicta. You can find more information about the Cry3A-like protein on the [Cry3A-like protein part page]parts, the experimental results on the results, and information on the dry protein docking on the [Dry Protein Docking page].

We propose the idea of utilizing a population sensing threshold with a cleavage gene to control the amount of protein released into the environment, where the rate of increase in production decreases dramatically when a value is reached. This idea can be extended to a wide range of chassis organisms. In addition, cascading gene routes can be introduced to control the order of product release and also limit the expression of multiple products at the same time. For example, two quorum sensing systems have been introduced in this project to realize the sequential expression of protease inhibitors and toxic proteins as well as the limitation of the amount of expression. In the future, we hope that this idea can play a greater role in metabolic regulation.

Based on the behaviors of S.invict, we have proposed a concept for expressing low doses of toxin in the larvae, enriching to high doses in the queen through food transmission. This approach forms a model for effective colony eradication. Our Dry team has conducted modeling and validation of this concept. For more details, please refer to the [Concept Validation page].

We used the Blast tool from the NCBI database to match 33 proteins in S.invicta that are homologous to the calcineurin-like protein BT-R1 of the tobacco moth (Manduca sexta), which may bind to the Cry3A like protein and thus produce toxicity to red fire ants.

In addition, we have used computer simulations to preliminarily verify the potential binding between cadherin-23 and Cry3A-like protein. We have simulated two possible docking poses and their respective binding sites. The specific docking information is provided as follows:

Fig 1.Docking attitude 1

Fig 2.Docking site of Attitude 1

Fig 3.Docking attitude 2

Fig 4.Docking for Attitude 2

Indispensably, our homology modeling of Cry3A like protein and cadherin-23 using Swiss-model yielded their protein 3D structures, which can be used by future researchers.

Fig 5.3D structure of cadherin-23 protein

Fig 6.3D structure of Cry3A like protein