The fight against antibiotic resistance might seem to be a losing one at the moment, but a team of US researchers is hitting back using a bacterial genome road map based on data mining to find new drugs.
Many antibiotics are derived from natural products created by bacteria and other microbes to defend themselves against attack. This makes bacteria, such as the Gram-positive bacteria actinobacteria, valuable sources of natural products that have potential in the treatment of a wide range of diseases, including bacterial, viral and fungal infections, immune-related disorders and cancer.
Many existing drugs are based on natural products, but in recent years there has been a move away from this approach, as the ‘low hanging fruit’ – the compounds that were easy to find and develop – have largely been exhausted. However, understanding more about the biosynthetic gene clusters behind the production of these natural products could improve drug developers’ access to important and potent drug leads.
To this end, a US team, including researchers from the Institute for Genomic Biology, has developed an algorithm to mine and analyse microbial genomic data, creating a searchable reference that drug developers can scan for promising gene clusters. This involved sorting through 11,422 gene clusters from 830 bacterial genomes, finding gene clusters predicted to make very similar products and creating 4122 gene cluster families (GCFs).
To validate the database, the team used a high-precision analytical technique to link gene cluster families to potential new antibiotics. By comparing the distribution of gene cluster families across bacterial species, researchers can use this knowledge to predict which species are most likely to contain novel antibiotics, and therefore target the richest strains.
“We’ve got the framework, we know the number of gene clusters, we know who has them and therefore we know where to look to find new drugs,” says Bill Metcalf, microbiologist and molecular and cellular biologist Bill Metcalf. “It clearly leads to discovery.”