Overview

iGEM teams contribute to the iGEM community by openly sharing knowledge, insights, and products developed through their projects. Our team has contributed by releasing machine learning models, software, and the parts generated through these tools. We have also shared hardware applicable to wet laboratory experiments, an education rubric, and a system that facilitates Wiki writing, all of which contribute to the community.

Model

We developed LEAPS, a protein engineering model that enables efficient exploration of high-performance amino acid sequences and reduces the financial and temporal burden of wet laboratory experiments.

LEAPS efficiently explores sequence space. A typical protein contains 250 amino acid residues, and the possible combinations are astronomically large, making exhaustive search impossible. While multi-objective optimization is ideal in protein research, existing methods face significant challenges in achieving this goal due to various constraints.

LEAPS employs machine learning models to enable efficient space exploration and generate higher-performance amino acid sequences. This capability makes optimization achievable, even when multiple target functions must be simultaneously improved. Additionally, LEAPS can generate predictions from as few as 40 sequences. This enables cost-effective and rapid protein engineering, making LEAPS a revolutionary system for iGEMers who must execute projects under significant temporal and financial constraints.

For more details about the model, please refer to this page.

Software

We have released our protein engineering model as LEAPS-Software. While LEAPS is a revolutionary protein engineering model, its use requires both understanding of protein science and proficiency in machine learning. Our software features a step-form UI that allows users to perform protein engineering simply by following progressively displayed instructions to input and upload necessary data. By releasing this software, iGEM members can reduce the costs associated with mutant screening, which previously required extensive experimental work. Furthermore, because protein sequences can be easily generated, iGEM members can obtain sequences for high-performance proteins required in their projects. This acceleration of protein engineering is expected to improve project completion rates across iGEM.

For more details about the software, please refer to this page.

Safety and Security

LEAPS-Software is a valuable tool for various protein applications, including iGEM projects. However, because it can optimize target functions for any protein, malicious actors could potentially use it to engineer high-risk proteins such as toxins or viral spike proteins. Additionally, users may have concerns about inputting unpublished data into AI systems.

We therefore implemented various safety and security measures in LEAPS-Software. As a result of findings from our Human Practices, we designated high-risk proteins as a “blacklist” and subjected them to filtering based on sequence homology and structural similarity. We also aimed to create software that protects both safety and user rights through mechanisms including agreement to terms of use, confidentiality pledges, and required checkbox responses.

These measures will be important references when other iGEM teams release similar software. Moreover, raising awareness of these risks itself holds significant value for the iGEM community, which handles genes and proteins.

For more details about safety and security, please refer to this page.

Hardware

We have developed two hardware systems and share their designs and protocols with the iGEM community. These hardware systems were designed under the philosophy of laboratory automation. Laboratory automation aims to automate operations involved in wet experiments, thereby enabling high-throughput and efficient experimentation. Our hardware systems also automate certain experimental operations, which can reduce the burden of transformation and reagent preparation required in iGEM projects. This is expected to improve both the quality and quantity of experiments in iGEM.

Automated Electrophoresis Device and Inversion Mixer

To automate operations in wet experiments, we developed an electrophoresis device and an inversion mixer. The electrophoresis device automatically performs electrophoresis, captures gel images, and transfers them to a computer. The inversion mixer automatically performs inversion mixing when tubes after dispensing are set into the device. The inversion speed and mixing time are adjustable, enabling automated inversion mixing of large volumes of prepared reagents. Both hardware systems we developed reduce the burden of wet experiments and contribute to high-throughput experimentation through automation.

For more details about the hardware, please refer to this page.

Education

We implemented and shared a new education model case. Additionally, we created and released to iGEM a rubric that can evaluate each education activity regardless of content or approach. In iGEM, projects change annually and teams are reorganized, often resulting in lost connections with education partners. Our model case and evaluation criteria reduce this problem and contribute to sustainable education activities in iGEM.

Model of Local and Community-based Education

We share our activities with the iGEM community as a model case for local and community-based education, aiming for sustainability. In most cases, when an iGEM project ends, new members formulate different projects and begin new activities. This breaks connections with education partners established the previous year, generating annual costs and communication tasks for finding new partners. iGEM TSUKUBA therefore conducted community-rooted education to achieve sustainable educational activities.

Rubric

iGEM teams often conduct multiple education activities within a year. In such cases, the content of each education activity typically differs. While these activities can be evaluated and improved through surveys, the surveys differ for each activity, making consistent evaluation difficult. We created an original rubric. The rubric references evaluation criteria and curriculum guidelines from Japanese schools, making it a robust standard built upon the foundation established by Japanese school education. It enables multifaceted reflection on education activities, from knowledge and understanding of synthetic biology to collaboration with education partners. This allows education activities to be compared under unified evaluation criteria, making feedback on iGEM education activities more effective.

For more details about education, please refer to this page.

Wiki

We created and released tools to simplify Wiki writing and submission. All teams must write Wikis that meet evaluation criteria while handling coding requirements. Our tools effectively address these challenges. A system that checks compliance with Wiki requirements addresses human error, while an intuitive writing tool enables assigned members to immediately begin Wiki creation. These tools help iGEM teams write higher-quality Wikis.

Editor

The Editor is primarily a tool for simplifying Wiki writing. It enables writing in markdown format for intuitive operation. Additionally, it supports image and video uploads, text and heading switching, mathematical expression insertion, and most other formats required for Wiki writing. File path names for multiple Wiki pages are read by the Wiki Submission System described below. Because it supports simultaneous editing, multiple people can write without conflicts. This tool enables people without coding knowledge to participate in Wiki writing. This allows members who contributed to page content to directly write pages, enabling creation of higher-quality content. This tool contributes to the iGEM community by lowering the barrier to Wiki writing for iGEM members.

Wiki Submission System

The Wiki Submission System monitors whether Wiki pages written in the Editor violate Wiki regulations and bridges the process to page publication. When page publication or posting is selected in the Editor, this system detects image formats and GitLab uploads, notifying users if any regulation violations exist. This reduces the risk of disqualification due to regulation violations and is expected to help teams receive iGEM evaluation.

For more details about Wiki writing, please refer to this page.