The Strain Database has been a cornerstone of daily operations in the Cai Lab in Manchester Institute of Biotechnology for over a decade, helping researchers track thousands of yeasts, primer and bacterial samples stored in lab freezers. While a large spreadsheet could have served a similar purpose, the system’s built-in access controls—preventing non-administrators from modifying others’ records—have made it an essential tool for proper record keeping. With up to 20 active users relying on it daily, the need for a modern, scalable, and maintainable solution became increasingly clear.

To meet these evolving needs, the Research Software Engineering (RSE) department partnered closely with the lab to carry out a full revamp of the system in two phases. The project was developed by RSEs Hiu Fung (Hugo) Chu and Yat Him (Justin) Leung, and managed by Dr. Jia Wu, with continuous input from the researchers to ensure the system remained aligned with real-world workflows.

Phase 1: Rebuilding the Foundation Together

The original system, built using Ruby on Rails and a PostgreSQL database within a Docker environment, had become difficult to maintain due to outdated dependencies and declining community support. The original developer had also moved to another place of employment. After a thorough assessment and collaborative requirement-gathering process, the team decided to rebuild the system from the ground up using Spring Boot (Java)—a robust, enterprise-grade framework.

The database was migrated to MySQL, a lighter and more maintainable solution for the lab’s scale. Features were modularised using the Model-View-Controller (MVC) architecture, and the database was restructured to improve data integrity, indexing, and future extensibility. Sanity checks were implemented using both Perl scripts and Spring Boot libraries to ensure clean, complete data entry.

The frontend was redesigned using Bootstrap, improving responsiveness and accessibility across devices. New features included DataTable integration for filtering and sorting, password reset functionality, and a secure login system using Spring Security. Comprehensive documentation was provided for users, system admininstrators, and developers, ensuring the system could be maintained and extended over time.

Since the new system was deployed in February 2024, it has supported the addition of 1,790 bacterial and 1,304 yeast records—demonstrating its reliability and continued relevance. No downtime has been reported since the system went live, highlighting its robustness and stability.

Phase 2: Extending Functionality Through Continued Collaboration

Building on the success of Phase 1, the second phase focused on expanding the system’s capabilities and making it more adaptable for broader use. This phase was shaped by ongoing collaboration with the lab, ensuring that every enhancement reflected both current needs and future directions.

Support for two new sample types was added, reflecting the lab’s expanding research scope. Improvements were made to the sample sequence upload process, resolving naming issues and streamlining data entry. To improve consistency, the structure of existing tables was standardised, making the interface more intuitive and reducing user error.

Recognising the potential for wider adoption, the system was generalised beyond its original lab context. Lab-specific identifiers and branding were removed or documented, allowing other research groups to deploy and customise the system with ease. This included clear guidance on which files and lines of code to modify when setting up a new instance. The system is available from GitHub with an Apache licence.

Conclusion

This two-phase revamp transformed a legacy application into a robust, modern platform through close collaboration between researchers and the RSE team. By combining technical upgrades with thoughtful design and continuous feedback, the new Strain Database is now more secure, scalable, and adaptable—ready to support the lab’s research for years to come.

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