Our contemporary, comprehensive phylogenetic study spans all domains to understand the Resistance-Nodulation-Cell Division (RND) superfamily’s evolution and points of divergence. Several members of the superfamily are involved in both the acquisition and intrinsic resistance to antibiotics despite origins that are ubiquitous and ancient compared to modern-day antibiotic use (Nikaido 2018). Exhaustive searches of selected representative sequences through BLAST (Mistry et al. 2013) and HMMSearch (Camacho et al. 2009) created the most comprehensive and up-to-date dataset to establish all possible RND homologs. CD-HIT, a clustering software, was used to refine our dataset (Pearson 2013). Multiple sequence alignments like CLUSTAL (Sievers et al. 2011) and MUSCLE (Edgar 2004) were utilized. Each alignment had differing computational methods used by these programs to offer significant information about the structure and evolution of RNDs that gave collective insight. Phylogenetic trees produced from PhyML, a program based on maximum-likelihood algorithm, were our final products to characterize novel members and sub-families of the RND superfamily (Letunic & Bork, 2021). Evolutionary pathways were elucidated through highly likely clustering and branch lengths. Overall, the study provides a significant update to our understanding of the RND superfamily giving rise to previously uncharacterized members and families.
","abstract_html":"<p>Our contemporary, comprehensive phylogenetic study spans all domains to understand the Resistance-Nodulation-Cell Division (RND) superfamily’s evolution and points of divergence. Several members of the superfamily are involved in both the acquisition and intrinsic resistance to antibiotics despite origins that are ubiquitous and ancient compared to modern-day antibiotic use (Nikaido 2018). Exhaustive searches of selected representative sequences through BLAST (Mistry et al. 2013) and HMMSearch (Camacho et al. 2009) created the most comprehensive and up-to-date dataset to establish all possible RND homologs. CD-HIT, a clustering software, was used to refine our dataset (Pearson 2013). Multiple sequence alignments like CLUSTAL (Sievers et al. 2011) and MUSCLE (Edgar 2004) were utilized. Each alignment had differing computational methods used by these programs to offer significant information about the structure and evolution of RNDs that gave collective insight. Phylogenetic trees produced from PhyML, a program based on maximum-likelihood algorithm, were our final products to characterize novel members and sub-families of the RND superfamily (Letunic & Bork, 2021). Evolutionary pathways were elucidated through highly likely clustering and branch lengths. Overall, the study provides a significant update to our understanding of the RND superfamily giving rise to previously uncharacterized members and families. </p>","abstract_has_math":false,"creators":["McGrath, Daisy","Tseng, Tsai-Tien"],"institution":null,"degree_name":"Master of Science in Integrative Biology (MSIB)","degree_level":"Thesis","degree_discipline":"Biology","degree_department":null,"school":null,"contributors":["Dr. Tsai-Tien Tseng","Dr. Melanie Griffin","Dr. Thomas McElroy"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-11-16T08:00:00Z","date_published":"2022-11-16T08:00:00Z","updated_at":"2026-07-24T02:43:58Z","subjects":["antibiotic resistance","membrane transport","phylogeny","Biodiversity","Bioinformatics","Biology","Computational Biology","Evolution","Integrative Biology"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.kennesaw.edu/integrbiol_etd/91","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Dr. Tsai-Tien Tseng","Dr. Melanie Griffin","Dr. Thomas McElroy"]},{"key":"dc:creator","label":"Author","values":["McGrath, Daisy","Tseng, Tsai-Tien"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2027-11-17T08:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Biology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Integrative Biology (MSIB)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["antibiotic resistance","membrane transport","phylogeny","Biodiversity","Bioinformatics","Biology","Computational Biology","Evolution","Integrative Biology"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.kennesaw.edu/integrbiol_etd/91"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Our contemporary, comprehensive phylogenetic study spans all domains to understand the Resistance-Nodulation-Cell Division (RND) superfamily’s evolution and points of divergence. Several members of the superfamily are involved in both the acquisition and intrinsic resistance to antibiotics despite origins that are ubiquitous and ancient compared to modern-day antibiotic use (Nikaido 2018). Exhaustive searches of selected representative sequences through BLAST (Mistry et al. 2013) and HMMSearch (Camacho et al. 2009) created the most comprehensive and up-to-date dataset to establish all possible RND homologs. CD-HIT, a clustering software, was used to refine our dataset (Pearson 2013). Multiple sequence alignments like CLUSTAL (Sievers et al. 2011) and MUSCLE (Edgar 2004) were utilized. Each alignment had differing computational methods used by these programs to offer significant information about the structure and evolution of RNDs that gave collective insight. Phylogenetic trees produced from PhyML, a program based on maximum-likelihood algorithm, were our final products to characterize novel members and sub-families of the RND superfamily (Letunic & Bork, 2021). Evolutionary pathways were elucidated through highly likely clustering and branch lengths. Overall, the study provides a significant update to our understanding of the RND superfamily giving rise to previously uncharacterized members and families.
"]},{"key":"dc:title","label":"Title","values":["Phylogeny of the Resistance-Nodulation-Cell Division (RND) Superfamily"]}]}],"canonical_facts":{"dc:contributor":["Dr. Tsai-Tien Tseng","Dr. Melanie Griffin","Dr. Thomas McElroy"],"dc:creator":["McGrath, Daisy","Tseng, Tsai-Tien"],"dc:date.available":["2027-11-17T08:00:00Z"],"dc:description.abstract":["Our contemporary, comprehensive phylogenetic study spans all domains to understand the Resistance-Nodulation-Cell Division (RND) superfamily’s evolution and points of divergence. Several members of the superfamily are involved in both the acquisition and intrinsic resistance to antibiotics despite origins that are ubiquitous and ancient compared to modern-day antibiotic use (Nikaido 2018). Exhaustive searches of selected representative sequences through BLAST (Mistry et al. 2013) and HMMSearch (Camacho et al. 2009) created the most comprehensive and up-to-date dataset to establish all possible RND homologs. CD-HIT, a clustering software, was used to refine our dataset (Pearson 2013). Multiple sequence alignments like CLUSTAL (Sievers et al. 2011) and MUSCLE (Edgar 2004) were utilized. Each alignment had differing computational methods used by these programs to offer significant information about the structure and evolution of RNDs that gave collective insight. Phylogenetic trees produced from PhyML, a program based on maximum-likelihood algorithm, were our final products to characterize novel members and sub-families of the RND superfamily (Letunic & Bork, 2021). Evolutionary pathways were elucidated through highly likely clustering and branch lengths. Overall, the study provides a significant update to our understanding of the RND superfamily giving rise to previously uncharacterized members and families.
"],"dc:identifier":["https://digitalcommons.kennesaw.edu/integrbiol_etd/91"],"dc:subject":["antibiotic resistance","membrane transport","phylogeny","Biodiversity","Bioinformatics","Biology","Computational Biology","Evolution","Integrative Biology"],"dc:title":["Phylogeny of the Resistance-Nodulation-Cell Division (RND) Superfamily"],"thesis:degree_discipline":["Biology"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Science in Integrative Biology (MSIB)"]},"updated_at":"2026-07-24T02:43:58Z"}