Bartonella bacteria are widespread zoonotic pathogens that infect a diverse range of small mammals, yet their prevalence and distribution remain understudied in many host species. In this study, Bartonella infection was assessed across multiple small mammal species, revealing an overall prevalence of approximately 37% based on droplet digital PCR (ddPCR) screening. Following ddPCR screening, individuals that yielded positive results were selected for further analysis including genetic sequencing of the RNA polymerase b-subunit (rpoB) gene. While 116 individuals of 313 tested positive, only 63 samples were successfully sequenced, likely due to low infection loads. BLAST analysis suggested the presence of several Bartonella species among the infected samples, with B. grahamii and B. washoensis being the most frequently detected. Phylogenetic analyses using both Bayesian inference (MrBayes) and maximum likelihood (IQ-TREE) approaches demonstrated strong host-associated clustering of known Bartonella species. These findings provide important insights into Bartonella prevalence, distribution, diversity, and host specificity.
","abstract_html":"<p><em>Bartonella</em> bacteria are widespread zoonotic pathogens that infect a diverse range of small mammals, yet their prevalence and distribution remain understudied in many host species. In this study, <em>Bartonella</em> infection was assessed across multiple small mammal species, revealing an overall prevalence of approximately 37% based on droplet digital PCR (ddPCR) screening. Following ddPCR screening, individuals that yielded positive results were selected for further analysis including genetic sequencing of the RNA polymerase b-subunit (<em>rpoB</em>) gene. While 116 individuals of 313 tested positive, only 63 samples were successfully sequenced, likely due to low infection loads. BLAST analysis suggested the presence of several <em>Bartonella</em> species among the infected samples, with <em>B. grahamii</em> and <em>B. washoensis</em> being the most frequently detected. Phylogenetic analyses using both Bayesian inference (MrBayes) and maximum likelihood (IQ-TREE) approaches demonstrated strong host-associated clustering of known <em>Bartonella </em>species. These findings provide important insights into <em>Bartonella</em> prevalence, distribution, diversity, and host specificity.</p>","abstract_has_math":false,"creators":["Greenman, Emily"],"institution":null,"degree_name":"Master of Science","degree_level":"Thesis","degree_discipline":"Biology","degree_department":null,"school":null,"contributors":["Josh Sharp"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-05-01T07:00:00Z","date_published":"2025-05-01T07:00:00Z","updated_at":"2026-07-24T03:24:36Z","subjects":[],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.nmu.edu/theses/872","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Josh Sharp"]},{"key":"dc:creator","label":"Author","values":["Greenman, Emily"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2030-03-31T07:00:00Z"]},{"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"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.nmu.edu/theses/872"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Bartonella bacteria are widespread zoonotic pathogens that infect a diverse range of small mammals, yet their prevalence and distribution remain understudied in many host species. In this study, Bartonella infection was assessed across multiple small mammal species, revealing an overall prevalence of approximately 37% based on droplet digital PCR (ddPCR) screening. Following ddPCR screening, individuals that yielded positive results were selected for further analysis including genetic sequencing of the RNA polymerase b-subunit (rpoB) gene. While 116 individuals of 313 tested positive, only 63 samples were successfully sequenced, likely due to low infection loads. BLAST analysis suggested the presence of several Bartonella species among the infected samples, with B. grahamii and B. washoensis being the most frequently detected. Phylogenetic analyses using both Bayesian inference (MrBayes) and maximum likelihood (IQ-TREE) approaches demonstrated strong host-associated clustering of known Bartonella species. These findings provide important insights into Bartonella prevalence, distribution, diversity, and host specificity.
"]},{"key":"dc:title","label":"Title","values":["Bartonella in Small Mammals from Montana and Idaho"]}]}],"canonical_facts":{"dc:contributor":["Josh Sharp"],"dc:creator":["Greenman, Emily"],"dc:date.available":["2030-03-31T07:00:00Z"],"dc:description.abstract":["Bartonella bacteria are widespread zoonotic pathogens that infect a diverse range of small mammals, yet their prevalence and distribution remain understudied in many host species. In this study, Bartonella infection was assessed across multiple small mammal species, revealing an overall prevalence of approximately 37% based on droplet digital PCR (ddPCR) screening. Following ddPCR screening, individuals that yielded positive results were selected for further analysis including genetic sequencing of the RNA polymerase b-subunit (rpoB) gene. While 116 individuals of 313 tested positive, only 63 samples were successfully sequenced, likely due to low infection loads. BLAST analysis suggested the presence of several Bartonella species among the infected samples, with B. grahamii and B. washoensis being the most frequently detected. Phylogenetic analyses using both Bayesian inference (MrBayes) and maximum likelihood (IQ-TREE) approaches demonstrated strong host-associated clustering of known Bartonella species. These findings provide important insights into Bartonella prevalence, distribution, diversity, and host specificity.
"],"dc:identifier":["https://commons.nmu.edu/theses/872"],"dc:title":["Bartonella in Small Mammals from Montana and Idaho"],"thesis:degree_discipline":["Biology"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Science"]},"updated_at":"2026-07-24T03:24:36Z"}