Through the iGEMer wechat communication group in China, we have communicated with other IGEM teams in China, especially NNU from Nanjing Normal University. Through in-depth exchanges with NNU, we learned that the core of their project is to construct an engineering strain capable of co-producing DHA and EPA to obtain OMAGE-3 eggs, among which there were several important core reactions that needed to be catalyzed by enzymes. Our platform is a website for screening and predicting the enzymes required for single-step reactions. So we realized that we could collaborate on the part of enzyme screening.

After building our project, we invited NNU to test our tools. They used our platform, made predictions, and compared our results with the enzyme that they actually used. Besides, they gave us a lot of advice on how to upgrade our program. We sincerely appreciate their feedback.

Fig.1 User feedback from NNU

We have hosted an online meetup with Tongji-Software, and we introduced the project to each other in detail. We shared the modeling ideas and prediction algorithms and members of both teams discussed the specific algorithms used and the flaws. The Tongji-Software team provided us with many valuable suggestions to make our software more stable and robust.

Fig.2 Online meeting with Tongji-Software

We are closely associated with USTC, which is our school's wet team. USTC focuses on biology, so most of their members are biology majors. We have had a lot of meaningful communication throughout the project.

Initially, members of USTC-Software came up with ideas for a topic and set a general direction, which we then discussed with the wet team. Our initial idea was to develop a platform to analyze and predict protein interactions using transcriptomes. Discussions with them allowed us to further clarify the feasibility and significance of the idea and to understand the needs of biologists.

Fig.3 Joint meeting between USTC and USTC Software

We also listened carefully to the USTC team's ideas. Because most of us are familiar with mathematical and computer models, we quickly found some flaws in their existing models and proposed better models to replace them. They all admitted that the problem did exist and decided to take our advice.

Fig.4 USTC Presentation

After the discussion, we made appropriate adjustments to our direction. The USTC team members also made suggestions to us. From the perspective of a synthetic biologist, they put forward some practical suggestions. On this basis, we optimize the design of our software and add some practical small functions on the interface

Since the beginning of the project, we have had a lot of communication both online and offline. Because most of our software team members were computer science majors, we usually encountered some problems that our biological team could not solve in the whole process of designing our software. Often at this time, the wet team provided us with help, such as answering some questions on common properties of biomolecules, suggesting suitable databases, which provided the fundamental support for the operation of our software.

Fig.5 USTC team members made suggestions for us

Due to the project of USTC, which is to select the most productive enzyme after transfection, we invited them to test our platform. They tested their manual screening results of enzymes on our website. Finally, they confirmed their choice and retrieved several similar enzymes with equal function. We are glad that our software is helpful.

Fig.6 The results of the tests USTC ran using our software