Abstract
As the rapid evolution of multi-drug-resistant bacteria inflict public health and environmental crises, the need for alternatives to convention antibiotics is necessary. Bacteriophage (phage) interventions has resurfaced as a prospective avenue of study. However, these viruses that are capable of infecting and killing bacteria are widely undiscovered and lack genetic characterization. Current methods utilize bioinformatics and comparative tools to identify genes and protein functions. Unfortunately, functional classification of phage proteins is difficult with limited experimental data. As a result, functional assignments are often made on synteny using genetically similar bacteriophages. However, many proteins are assigned “hypothetical” functions as no comparative or experimental data exits. The emergence of artificial intelligence (AI) programs such as Google DeepMind’s AlphaFold is capable of generating high probability protein folding predictions creating an interesting opportunity to make more informed functional assignments. The aim of this research was to reassess protein functions of cluster DV Gordonia bacteriophages DaviePasture, Alyssamiracle, Genamy16 and NovaSharks, previously annotated and published in GenBank by Nova Southeastern University in collaboration with SEAPHAGES, to confirm or reassign protein function via AI software. Four gene phams were investigated. AI protein models guided the conclusion that three “hypothetical” proteins could instead be given a functional assignment based on similar folding when compared to proteins of known functions. Additionally, AlphaFold output informed that one protein was incorrectly assigned HNH endonuclease and should instead be called endonuclease VII. These are novel conclusions regarding the function of bacteriophage proteins that previous bioinformatics tools were unable to provide insights on.
Faculty Sponsors
Dr. Katie Crump
Project Type
Event
Location
Alvin Sherman Library
Start Date
4-2-2025 2:15 PM
End Date
4-3-2025 12:00 AM
Investigation and Reclassification of Gordonia Bacteriophage Protein Folding and Function with Google DeepMind's AlphaFold Artificial Intellifence Software
Alvin Sherman Library
As the rapid evolution of multi-drug-resistant bacteria inflict public health and environmental crises, the need for alternatives to convention antibiotics is necessary. Bacteriophage (phage) interventions has resurfaced as a prospective avenue of study. However, these viruses that are capable of infecting and killing bacteria are widely undiscovered and lack genetic characterization. Current methods utilize bioinformatics and comparative tools to identify genes and protein functions. Unfortunately, functional classification of phage proteins is difficult with limited experimental data. As a result, functional assignments are often made on synteny using genetically similar bacteriophages. However, many proteins are assigned “hypothetical” functions as no comparative or experimental data exits. The emergence of artificial intelligence (AI) programs such as Google DeepMind’s AlphaFold is capable of generating high probability protein folding predictions creating an interesting opportunity to make more informed functional assignments. The aim of this research was to reassess protein functions of cluster DV Gordonia bacteriophages DaviePasture, Alyssamiracle, Genamy16 and NovaSharks, previously annotated and published in GenBank by Nova Southeastern University in collaboration with SEAPHAGES, to confirm or reassign protein function via AI software. Four gene phams were investigated. AI protein models guided the conclusion that three “hypothetical” proteins could instead be given a functional assignment based on similar folding when compared to proteins of known functions. Additionally, AlphaFold output informed that one protein was incorrectly assigned HNH endonuclease and should instead be called endonuclease VII. These are novel conclusions regarding the function of bacteriophage proteins that previous bioinformatics tools were unable to provide insights on.
