{"664013":{"#nid":"664013","#data":{"type":"event","title":"PhD Dfefense by Juan C. Castro","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EJuan C. Castro\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDefends his thesis:\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EProbing genomic, metabolic, and phenotypic evolution in microbes using comparative and experimental evolution data\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EThursday, January 12, 2023\u003C\/p\u003E\r\n\r\n\u003Cp\u003E10:00 AM Eastern Time\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMarcus Nanotechnology Building Conference Room (room #1117-1118)\u003C\/p\u003E\r\n\r\n\u003Cp\u003EZoom link: \u003Ca href=\u0022https:\/\/gatech.zoom.us\/j\/99028783106?pwd=RUpZd1RnWDFrMXUzdzhkaFJtR1I4Zz09\u0022 target=\u0022_blank\u0022\u003Ehttps:\/\/gatech.zoom.us\/j\/99028783106?pwd=RUpZd1RnWDFrMXUzdzhkaFJtR1I4Zz09\u003C\/a\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003EThesis Advisor:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Sam P. Brown\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESchool of Biological Sciences\u003C\/p\u003E\r\n\r\n\u003Cp\u003EGeorgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ECommittee Members:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Marvin Whiteley\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESchool of Biological Sciences\u003C\/p\u003E\r\n\r\n\u003Cp\u003EGeorgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Neha Garg\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESchool of Chemistry \u0026amp; Biochemistry\u003C\/p\u003E\r\n\r\n\u003Cp\u003EGeorgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Peng Qiu\u003C\/p\u003E\r\n\r\n\u003Cp\u003ECoulter Department of Biomedical Engineering\u003C\/p\u003E\r\n\r\n\u003Cp\u003EGeorgia Institute of Technology\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EDr. Timothy D. Read\u003C\/p\u003E\r\n\r\n\u003Cp\u003ESchool of Medicine\u003C\/p\u003E\r\n\r\n\u003Cp\u003EEmory University\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cstrong\u003ESummary:\u003C\/strong\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003EMicrobial model systems offer unique opportunities for evolutionary biologists, due to the ability to probe evolutionary dynamics using both comparative and experimental evolution techniques. This thesis leverages these opportunities to address questions on genomic, metabolic, and phenotypic evolution in bacteria.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFirst, we exploit the growing availability of closed genomes for model bacteria (\u003Cem\u003EE. coli\u003C\/em\u003E and \u003Cem\u003EP. aeruginosa\u003C\/em\u003E) to build pan-genomes where we can track the physical linkage of all genes. Through a combination of evolutionary simulations and data-analysis, we ask how mutation, selection and gene interactions combine to shape genome structural organization (linkage) and variation (co-segregation) across strains. We show that co-segregation networks are modular, associate with physical linkage, and map to metabolic (for \u003Cem\u003EP. aeruginosa\u003C\/em\u003E) and regulatory networks (for E. coli). The results imply that modular gene interactions are sufficient to guide the evolution of persistent gene clusters and are the primary force shaping genome structural evolution.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003ENext, we focus on metabolic network evolution, and assess whether we can predict the metabolic wiring of \u003Cem\u003EP. aeruginosa\u003C\/em\u003E, both before and after experimental evolution in defined environments. Standard flux-balance analysis (FBA) models have weak predictive value for ancestral strains both before and after experimental evolution adaptation to a novel defined environment. We reasoned that FBA models are limited by their focus on primary metabolic processes, and therefore fail to capture adaptation of secondary metabolism. By incorporating Tn-seq data on gene essentiality into our FBA model predictions we build metabolic predictions spanning primary and secondary metabolism. Our enhanced FBA models show (1) consistent predictive improvements following experimental evolution, and (2) highest predictive performance in the specific environment in which the Tn-seq data was generated.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EFinally, we turn to a phenotypic scale of evolutionary analysis, with a focus on biofilm production. Using a combination of theory and comparative data, we ask how biofilm investment strategies vary across strains of \u003Cem\u003EP. aeruginosa\u003C\/em\u003E and are shaped by population dynamical processes and phylogenetic constraints. Our data illustrates substantial variation in biofilm allocation, with the proportion of biofilm cells varying from ~5 to 55%. Our data analysis allows us to reject a simple allocation tradeoff model and favors the \u0026lsquo;growth engine\u0026rsquo; model introduced in earlier work (Lowery ref). Under the growth engine model, maximal biofilm production requires robust planktonic growth, generating a hump-shaped relationship between the total abundance of biofilm cells and planktonic cells. Finally, our heritability analysis indicates that biofilm phenotypic variation is substantially determined by phylogeny.\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Probing genomic, metabolic, and phenotypic evolution in microbes using comparative and experimental evolution data"}],"uid":"27707","created_gmt":"2022-12-21 13:51:02","changed_gmt":"2022-12-21 13:51:02","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-01-12T10:00:00-05:00","event_time_end":"2023-01-12T12:00:00-05:00","event_time_end_last":"2023-01-12T12:00:00-05:00","gmt_time_start":"2023-01-12 15:00:00","gmt_time_end":"2023-01-12 17:00:00","gmt_time_end_last":"2023-01-12 17:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}