AI mining of the bacteriophages metagenome

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Bacteriophages, viruses that infect bacteria and archaea, are the most common and most diverse biological entities representing the largest reservoir of unknown genetic material on the planet. Bacteriophages can be found in all conceivable eco-systems including extreme habitats (high and low temperature, pH and salinity etc). The development of next-generation sequencing (NGS) has led to an explosion of metagenomic data including from a plethora of novel bacteriophages. In this project we will employ high-performance computing to predict the 3D structures of entire metagenomics data sets from by our partners at Prozomix and Insiligence to identify novel targets with potential in the bio-economy. The initial target enzyme family comprise phage-encoded lytic enzyme, endolysins, a highly diverse group of enzymes that break down the bacterial (or archaeal) peptidoglycan layer and thus enable cell lysis. Due to their broad activity under a wide range of conditions, endolysins have emerged as one of the most promising antimicrobial agents in application ranging from human and veterinary medicine, agriculture, biotechnology and the prevention of biofilms in food production. These wide-ranging applications require specific enzyme properties, which can include thermostability and high activity in extreme pH, high salt and/or low temperature conditions. While the structural traits of ultra-high thermophilicity have been investigates in a lot of detail, the molecular basis of adaption to cold environments remains elusive. Psychrophilic enzymes are highly sought after in the bio-economy as being able to lower reaction temperatures in biotechnology is key to achieving our net-zero goal. The characterisation of selected protein targets encompasses biochemical, biophysical and structural methods