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Dissertation/Thesis Abstract

Towards a Better Resolution in Microbial Taxonomy: 16s rRna Trees Vs. Ribosomal Protein Trees
by Connor, Skylar, Ph.D., University of Arkansas at Little Rock, 2020, 103; 28089989
Abstract (Summary)

Millions of people in the U.S. are infected every year, with foodborne pathogens. In 2019, the CDC’s Foodborne Disease Active Surveillance Network reported a total of 25,866 infections, 6,164 hospitalizations, and 122 deaths caused by eight enteric pathogens commonly transmitted through food in 15% of the U.S. population. Traditionally, Culture Independent methods and 16S ribosomal RNA amplicon sequencing were viewed as the most promising approach to identify bacterial organisms present during these outbreaks. Current amplicon sequencing techniques are limited by their ability to provide species level resolution based on the standard single-gene approach. In general, the simultaneous use of multiple genes has been found to be more accurate than that of single gene methods (such as 16S rRNA). The use of multiple ribosomal protein sequences as phylogenetic markers has consistently yielded a higher-resolution phylogeny when compared to single gene sequence methods like the standard 16S rRNA gene.

Our results indicate that phylogenetic trees based on 21 ribosomal protein genes provide a high-level resolution of species from common enteric pathogens, as reported by the CDC. These 21 ribosomal proteins form the two major ribosomal protein operons, spc and S10. With this method we have been able to obtain a level of accuracy capable of providing strain level resolution. We offer both experimental and computational methods for the extraction and use of a long ribosomal protein multi-gene cluster in determining better resolution in the area of pathogenic classification and the field of Public Health.

Indexing (document details)
Advisor: Ussery, David
Commitee: Compadre, Cesar, Haselow, Dirk, Jun, Se-Ran, McGehee, Robert E., Jr., Robeson, Michael S., II
School: University of Arkansas at Little Rock
Department: Information Science
School Location: United States -- Arkansas
Source: DAI-B 82/3(E), Dissertation Abstracts International
Subjects: Bioinformatics
Keywords: Foodborne Pathogens, Oxford Nanopore Sequencing, Phylogenetics, Primer Development, Ribosomal Protein Operons, Ribosomal Proteins
Publication Number: 28089989
ISBN: 9798672148861
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