Dr David Ussery | Discovering New Groups of E. Coli Bacteria

Historically, these strains have been separated into 7 different groups, often reflecting their different life strategies – such as whether they cause disease. Understanding the characteristics of E. coli strains, and the relationships between them, is an important objective for medical research. For example, comparing E. coli genomes could reveal genes involved in antibiotic resistance.

In recent research, Dr David Ussery and his colleagues at the University of Arkansas for Medical Sciences used a powerful computing method to analyse the largest set of E. coli genomes yet. The team included over 10,000 E. coli genomes. In doing so, they identified 14 different groups – double the number previously recognised – and used these groups to classify a larger set of almost 100,000 E. coli genomes.

A key limitation in all genomic studies is the sheer volume of data generated for analysis. Although modern technologies have made studying genomes faster and more efficient than ever before, larger numbers of genomes still require immense processing power to analyse.

Dr Ussery and his colleagues used a computer program called Mash, which streamlines the process of comparing genomes. This new tool could open up new avenues for investigating other large genomic datasets.