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Bacterial Genomics
Together with the UK Health Security Agency, Huber's group is collaborating with Dicks to develop novel computational approaches and software tools for analysing bacterial genomes.
Participants
Collaborators
Dr Katie Hopkins, UKHSA
Dr Daniele Meunier, UKHSA
Dr Richard Leggett, Earlham Institute
PhD Students
Summary
Bacteria are everywhere, within and around us. They have adapted to live in numerous habitats on earth, from cold to hot, acidic to alkaline and even in highly irradiated regions. Amongst the predicted millions of bacterial species now living, some have highly useful capabilities, such as the ability to break down toxic waste products. However, others are bacterial pathogens, causing illness and even death to humans and animals. Bacterial genomes are typically small and therefore amenable to whole genome sequencing. Millions of bacterial strains have therefore already been sequenced and the resulting sequence reads and genome assemblies made publicly available. We are interested in mining this rich data source in order to answer a range of questions on bacterial identity, evolution and function.
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Our current projects include the analysis of datasets and the development of novel computational approaches and software tools for
the rapid and precise identification of bacterial strains from their genome sequence, or a subset of it, is essential for countering numerous bacterial threats. However, commonly used bacterial databases to which we match these sequences may contain both “correct” and “erroneous” information, making results potentially unreliable. We are investigating new approaches to producing more reliable databases which can be used for future strain identification.
since the 1960s an increasing number of bacteria have become resistant to certain antibiotics, meaning that they no longer work in some cases. We are analysing a wide range to bacterial genomes to investigate how the mechanisms of antimicrobial resistance acquisition have changed over time and between species.
certain bacteria can produce and secrete toxins, causing mild to severe illness in the humans or animals than inhale or ingest them. We are using machine learning approaches to analyse patterns of lineage-toxin associations in a large dataset of bacterial genomes.
Partners
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Publications
[1] Dicks J, Turnbull J, Russell J, Parkhill J and Alexander S. (2021) Genome sequencing of an historic Staphylococcus aureus collection reveals new enterotoxin genes and sheds light on the evolution and genomic organisation of this key virulence gene family. Journal of Bacteriology 203(10):e00587-20.
[2] Cazares A, Figueroa W, Cazares D, Lima L, Turnbull JD, McGregor H, Dicks J, Alexander S, Iqbal Z, Thomson NR (2024) Pre and Post antibiotic epoch: insights into the historical spread of antimicrobial resistance. bioRxiv https://doi.org/10.1101/2024.09.03.610986