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PHYLOGENETIC ANALYSIS OF THE GENETIC EVOLUTION OF MULTI-DRUG RESISTANT ESCHERICHIA COLI

Kevin Smith (1), Gabriel Zenarosa (1), Colby Ford (2), John Williams (2), Daniel Janies (2), 1) Systems Engineering and Engineering Management 2)Department of Bioinformatics and Genomics, University of North Carolina at Charlotte 9201 University City Blvd. Charlotte, NC 28223

Antimicrobial resistance (AMR) in pathogens such as Escherichia coli (E. coli) adversely impacts health care and food safety on a global scale. In this study, our group is examining two competing hypotheses: 1) "genetic capitalism" in which genes that confer antibiotic resistance are gained and not often lost and 2) "purifying selection" in which genes that confer antibiotic resistance are gained and lost near equal rates. To test these ideas, we used the National Center for Biotechnology Information (NCBI) Pathogen Detection Database. We collected genotype-level data of 29,252 E. coli isolates from the NCBI database on October 8, 2018. We analyzed these data for the number of gains and losses of 409 AMR genotypes on a phylogenetic tree generated using the FastME algorithm. Three broad categories of genotypes that our analysis found include 328 genes that are gained but never lost, 79 genes have at least one loss but more gains than losses and only two genes that have more losses than gains across the tree. Considerably stronger selective forces are delineated by our lack of results indicating flux between gains and losses of AMR genotypes. The selective pressure to add resistance genes shows minimal signs of weakening. We seek to inform the development of potential treatment pathways for combating AMR. Thus, we have set out to address why genomes more likely to add AMR genotypes when some believe that there is an energetic cost to carrying the AMR genes. We are continuing to investigate how sets of genes are acquired and maintained in multidrug resistant organisms. Further analyses will highlight the transience, recurrence, and robustness of specific AMR genotype sets.


Additional Abstract Information

Presenter: Kevin Smith

Institution: University of North Carolina at Charlotte

Type: Oral

Subject: Nursing & Public Health

Status: Approved