{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/86708"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/86708","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Improving Our Comprehension of Microbial Communities","abstract":"This study details the evaluation of three commonly used methodologies for characterizing microbial communities. The use of universal genes, such as those for small subunit ribosomal ribonucleic acid (SSU rRNA), or randomly sequenced genome fragments form the foundation upon which a majority of microbiologists evaluate community structure, metabolic capabilities and community dynamics. SSU rRNA sequence-based studies, which are the most common methods for providing a microbial census, rely upon the faithful amplification of the corresponding genes from the original DNA sample. Chapter 2 provides a comprehensive reevaluation of the most commonly used amplification primers and presents a pair of formulations corresponding to the common 27f and 1492r sites that better maintain original SSU rRNA gene ratios. Other SSU rRNA-based studies, such as denaturing gradient gel electrophoresis (DGGE), have been used as an alternative to SSU rRNA gene sequencing because they can provide many community profiles for a fraction of the time, effort and money required for sequencing. Chapter 3 provides a comparison of DGGE community profiles and sequence-based analyses of the same samples demonstrating the limitations of DGGE in evaluating community structure. During the last decade, community analyses have expanded from single genes to microbial community genomics in which the gene content of an environment can provide not only a census, but also direct information on metabolic capabilities of community members. Chapter 4 describes computational tools developed for processing and analyzing multiple forms of sequence data.","abstract_html":"This study details the evaluation of three commonly used methodologies for characterizing microbial communities. The use of universal genes, such as those for small subunit ribosomal ribonucleic acid (SSU rRNA), or randomly sequenced genome fragments form the foundation upon which a majority of microbiologists evaluate community structure, metabolic capabilities and community dynamics. SSU rRNA sequence-based studies, which are the most common methods for providing a microbial census, rely upon the faithful amplification of the corresponding genes from the original DNA sample. Chapter 2 provides a comprehensive reevaluation of the most commonly used amplification primers and presents a pair of formulations corresponding to the common 27f and 1492r sites that better maintain original SSU rRNA gene ratios. Other SSU rRNA-based studies, such as denaturing gradient gel electrophoresis (DGGE), have been used as an alternative to SSU rRNA gene sequencing because they can provide many community profiles for a fraction of the time, effort and money required for sequencing. Chapter 3 provides a comparison of DGGE community profiles and sequence-based analyses of the same samples demonstrating the limitations of DGGE in evaluating community structure. During the last decade, community analyses have expanded from single genes to microbial community genomics in which the gene content of an environment can provide not only a census, but also direct information on metabolic capabilities of community members. Chapter 4 describes computational tools developed for processing and analyzing multiple forms of sequence data.","abstract_has_math":false,"creators":["Frank, Jeremy"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Microbiology","degree_department":null,"school":null,"contributors":["Gary Olsen"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-09-28T15:17:32Z","date_published":"2015-09-28T15:17:32Z","updated_at":"2026-07-22T22:26:27Z","subjects":["Biology, Microbiology"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["(MiAaPQ)AAI3347383"],"render_values":[{"text":"(MiAaPQ)AAI3347383","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/86708","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Gary Olsen"]},{"key":"dc:creator","label":"Author","values":["Frank, Jeremy"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015-09-28T15:17:32Z","10000-01-01","2008"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Microbiology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Biology, Microbiology"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/86708","(MiAaPQ)AAI3347383"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This study details the evaluation of three commonly used methodologies for characterizing microbial communities. The use of universal genes, such as those for small subunit ribosomal ribonucleic acid (SSU rRNA), or randomly sequenced genome fragments form the foundation upon which a majority of microbiologists evaluate community structure, metabolic capabilities and community dynamics. SSU rRNA sequence-based studies, which are the most common methods for providing a microbial census, rely upon the faithful amplification of the corresponding genes from the original DNA sample. Chapter 2 provides a comprehensive reevaluation of the most commonly used amplification primers and presents a pair of formulations corresponding to the common 27f and 1492r sites that better maintain original SSU rRNA gene ratios. Other SSU rRNA-based studies, such as denaturing gradient gel electrophoresis (DGGE), have been used as an alternative to SSU rRNA gene sequencing because they can provide many community profiles for a fraction of the time, effort and money required for sequencing. Chapter 3 provides a comparison of DGGE community profiles and sequence-based analyses of the same samples demonstrating the limitations of DGGE in evaluating community structure. During the last decade, community analyses have expanded from single genes to microbial community genomics in which the gene content of an environment can provide not only a census, but also direct information on metabolic capabilities of community members. Chapter 4 describes computational tools developed for processing and analyzing multiple forms of sequence data.","Made available in DSpace on 2015-09-28T15:17:32Z (GMT). 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The use of universal genes, such as those for small subunit ribosomal ribonucleic acid (SSU rRNA), or randomly sequenced genome fragments form the foundation upon which a majority of microbiologists evaluate community structure, metabolic capabilities and community dynamics. SSU rRNA sequence-based studies, which are the most common methods for providing a microbial census, rely upon the faithful amplification of the corresponding genes from the original DNA sample. Chapter 2 provides a comprehensive reevaluation of the most commonly used amplification primers and presents a pair of formulations corresponding to the common 27f and 1492r sites that better maintain original SSU rRNA gene ratios. Other SSU rRNA-based studies, such as denaturing gradient gel electrophoresis (DGGE), have been used as an alternative to SSU rRNA gene sequencing because they can provide many community profiles for a fraction of the time, effort and money required for sequencing. Chapter 3 provides a comparison of DGGE community profiles and sequence-based analyses of the same samples demonstrating the limitations of DGGE in evaluating community structure. During the last decade, community analyses have expanded from single genes to microbial community genomics in which the gene content of an environment can provide not only a census, but also direct information on metabolic capabilities of community members. Chapter 4 describes computational tools developed for processing and analyzing multiple forms of sequence data.","Made available in DSpace on 2015-09-28T15:17:32Z (GMT). No. of bitstreams: 2 license.txt: 4848 bytes, checksum: 96035ab3f5e1c23cc7138a224ce498bd (MD5) 3347383.pdf: 2284772 bytes, checksum: b45fdfffefd31e643e9b20074bb68c8a (MD5) Previous issue date: 2008","Embargo set by: Seth Robbins for item 87989 Lift date: Forever Reason: Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","Restricted to the U of I community idenfinitely during batch ingest of legacy ETDs","U of I Only","138 p.","Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2008."],"dc:identifier":["http://hdl.handle.net/2142/86708","(MiAaPQ)AAI3347383"],"dc:language":["eng"],"dc:subject":["Biology, Microbiology"],"dc:title":["Improving Our Comprehension of Microbial Communities"],"dc:type":["text"],"thesis:degree_discipline":["Microbiology"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:26:27Z"}