Collaborative Research: RUI: A multiscale quantification of plasmid acquisition in Escherichia coli pathogens

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The overall goal of this project is to better understand what enables some bacteria to adapt more successfully than others. Bacterial pathogens often share beneficial genetic material amongst themselves, enabling them to quickly adapt to their surroundings. The process of sharing genetic material, known as horizontal gene transfer (HGT), is the most common way that bacteria rapidly adapt to diverse environments. While much focus has been placed on characterizing pathogens that have already acquired beneficial traits via HGT, relatively little is known about the immediate adaptation that cells must undergo to successfully acquire such traits. This project investigates the adaptation process following HGT to provide insights into why certain pathogens are more successful (and therefore, prevalent) than others. The results and insights generated are applicable to a wide variety of biological areas and open questions and promotes ongoing and future collaborative efforts across the microbiology research community. In addition to its scientific objectives, this project facilitates significant educational opportunities for undergraduate students, particularly women and those from backgrounds underrepresented in STEM disciplines. Specifically, this project closely integrates research methods and results into a newly developed Computational Biology major and associated upper-level courses. Students are empowered with vital computational skills as well as an understanding and appreciation of cutting-edge research techniques. This project supports four students to pursue hands-on research year-round, benefiting from close guidance from the principal investigator.Horizontal gene transfer, (HGT), particularly through the transfer of plasmids via direct cell-cell contact (termed "conjugation"), is the most common way that bacterial pathogens adapt to environmental stressors by acquiring catabolic, virulence, or antibiotic resistance genes. Previous studies have primarily focused on the plasmid fitness cost as a determinant of plasmid-strain success: strains bearing high-cost plasmids are either out-competed or evolve compensatory mutations that ameliorate the plasmid's metabolic burden. In addition to the fitness cost, acquiring a plasmid introduces an immediate, but transient, disruption to metabolism which also impacts population growth dynamics. The impacts of these short-term effects remain an understudied feature of conjugation dynamics. This project synergistically leverages longitudinal transcriptomics, computational modeling, and whole-genome sequencing to investigate the mechanistic underpinnings of this acquisition cost. In so doing, the project directly connects gene expression patterns, arising as a consequence of plasmid acquisition, to their population-level effects. The first objective elucidates the mechanistic determinants that lead to plasmid acquisition cost for the representative plasmid RP4, using a combination of transcriptomics, genetic/biochemical validation, and metabolic network modeling. The second objective determines how plasmid acquisition impacts population dynamics and clonal dominance of Escherichia coli pathogens isolated from wastewater using conjugation experiments, genomics, and mathematical modeling. By combining multiple scales of data, this project elucidates the genetic determinants underlying plasmid acquisition, and leverages this knowledge to predict the short-term, long-term, and competitive dynamics of populations undergoing conjugation.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.