MCA: Genomic algorithms and statistical models for gene transfer in naturally transformable bacteria

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Bacteria, which often live in complex multi-species communities, are not limited to acquiringtheir genes from prior generations. Using a process called natural transformation, bacteria canalso acquire new genetic elements from neighbors and even from free DNA in the environment.It is currently unknown which genetic sequences are most readily transferred via transformation.Understanding natural transformation at the genome and community scale requires developmentand application of novel algorithms to address this previously unexplored space. This project willdevelop computational methods to identify and predict which genetic functions are likely to spreadthrough bacterial populations by natural transformation. Application of these computationalmethods will help fill a void in understanding genetic evolution in bacterial communities which maybe overlooked by taxonomic identification. This in turn can lead to better assessment of risks orbenefits associated with bacterial community members and improved planning of syntheticbacterial communities. The project workflow will enable new capstone research experiences forundergraduates from multiple STEM majors on campus.The connections between molecular and biological parameters that drive genome-wide genetransfer preferences during bacterial natural transformation have been unexplored due to lack ofgenome level experimental and computational analyses. The PI’s laboratory has developedexperimental molecular genetic tools to collect and map natural transformation gene transfer sitesacross diverse pairs of donor and recipient bacteria. However, the computational methods toquantify the driving functional parameters and ultimately to predict gene transfer dynamicsassociated with natural transformation do not yet exist. Collaboration with the partner will use theexperimental data to generate genome scale statistical algorithms and computational tools for (i)global analysis of molecular and biological parameters governing gene transfer events, and (ii)prediction of gene transfer events that result specifically from natural transformation. This projectwill enable expansion of the work beyond current molecular genetic analysis of naturaltransformation to the genome and community scale.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.