Dr David Ussery | Discovering New Groups of E. Coli Bacteria
About this episode
Escherichia coli – more commonly known as E. coli – is a leading cause of diarrhoea-associated hospitalisation. However, E. coli does not always cause disease. Alongside thousands of other bacterial species, E. coli lives inside and on the surface of the human body. Numerous different strains of E. coli have been identified by analysing their genomes. Read More
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.
Original Article Reference
Summary of the paper ‘Mash-based analyses of Escherichia coli genomes reveal 14 distinct phylogroups’, in Communications Biology, doi.org/10.1038/s42003-020-01626-5. A video of the clustering can be found here: figshare.com/articles/media/Supplementary_Movie_1/13105235
Financial support for the research described in this project was provided by the National Institute of Health / National Institute of General Medical Sciences, the National Science Foundation, Award No. OIA-1946391, and the Helen G. Adams and Arkansas Research Alliance Endowment.
For further information, you can connect with Dr David Ussery at DWUssery@uams.edu
This work is licensed under a Creative Commons Attribution 4.0 International License.
What does this mean?
Share: You can copy and redistribute the material in any medium or format
Adapt: You can change, and build upon the material for any purpose, even commercially.
Credit: You must give appropriate credit, provide a link to the license, and indicate if changes were made.
Are you ready to increase the impact of your research?
Stay Up To Date With SciTube
Subscribe to receive our latest videos straight to your mailbox