SGDB: a database of synthetic genes re-designed for optimizing protein over-expression

Area of Science:

• Bioinformatics
• Molecular Biology
• Synthetic Biology

Background:

• Synthetic genes are artificially engineered DNA sequences.
• Understanding factors influencing synthetic gene expression is crucial for various applications.
• A centralized repository for synthetic gene data is lacking.

Purpose of the Study:

• To introduce the Synthetic Gene Database (SGDB), a comprehensive resource for synthetic gene information.
• To provide a platform for experimentalists and bioinformaticians to access and analyze synthetic gene data.
• To facilitate the design of improved synthetic genes for enhanced protein expression.

Main Methods:

• Developed a relational database using the MySQL management system.
• Compiled data from over 200 peer-reviewed studies on synthetic genes.
• Created an XML schema for standardized data description.

Main Results:

• The SGDB houses sequences and experimental data for synthetic genes.
• The database serves as a reference for designing new genes and analyzing gene expression.
• Integrated web tools for sequence comparison and an e-forum for discussion are available.

Conclusions:

• The SGDB is a valuable resource for the synthetic biology community.
• It supports both experimental design and bioinformatic analysis of synthetic genes.
• The database promotes advancements in understanding and engineering gene expression.