Pan-BGC Atlas: An in-depth visual analysis of biosynthetic gene cluster families

Due to environmental pressures such as microbial competition and adaptation to diverse ecological niches, biosynthetic gene clusters (BGCs) in microorganisms have evolved a remarkable natural diversity. This diversity enables microbes to produce a wide array of structurally and functionally similar yet distinct secondary metabolites, many of which play essential roles in survival and interaction within their environments.

Using bioinformatics tools, we can group BGCs into gene cluster families (GCFs) based on genetic similarity. GCFs can vary widely in size, ranging from single clusters per family to hundreds. Compounds produced by BGCs within a family typically share a core chemical structure with only slight variations. This raises important questions: What are the underlying mechanisms and building blocks that lead to this diversity? Can we harness this potential, and gather more insights into selection mechanisms?

To better understand and systematically explore the natural diversity in GCFs, we developed a comprehensive visual GCF database, the Pan-BGC Atlas, by adapting the pangenome concept to BGCs. Our approach involved grouping bacterial BGCs from the antiSMASH database into similarity-based families, followed by a series of bioinformatics analyses. In the Pan-BGC Atlas, each GCF is visually represented and can be easily adjusted, allowing for rapid and intuitive analysis.

The Atlas includes both an "open" BGC, encompassing all possible genes within a GCF, and a "closed" BGC, representing the minimal set of genes needed to produce the core chemical structure shared across the family. Comparing the open and closed BGCs, along with other information, reveals enzymatic diversity and could offer new insights for synthetic biology.

Beyond exploration, users can compare their own BGCs against the database to identify the closest matching families. Additionally, a downloadable pipeline enables users to create similar visual analyses for their own gene cluster families, fostering reproducibility and broader application of these tools. This platform is a valuable resource for microbial genomics and natural product research, enhancing navigation and interpretation within GCFs.