<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-21T00:28:04Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/113437" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/113437</identifier><datestamp>2026-06-16T18:54:31Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131022</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Eric Alm.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Spencer, Sarah Jean</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Computational and Systems Biology Program.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Computational and Systems Biology Program</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2018-02-08T15:57:42Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2018-02-08T15:57:42Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2017</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2017</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/113437</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">1020068595</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, 2017.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">This electronic version was submitted by the student author.  The certified thesis is available in the Institute Archives and Special Collections.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from student-submitted PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 129-140).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">Microbial genomes show high plasticity due to horizontal transfer, large community sizes, and rapid growth paired with adaptive mutations. Despite this mutability of gene content, most studies of microbial communities still rely on bulk, single-gene amplicon sequencing. In this thesis, I present methods that interrogate the gene content of single cells derived from complex natural communities. In the first project, I present a novel molecular biology method to link a bacterial functional gene to its host species with single-cell resolution. This high-throughput protocol is applied to assess the distribution of anaerobic respiration genes in a lake ecosystem. In the second project, I demonstrate extensions of this methodology to link genes between spatially proximal microbial cells, and apply this approach to probe the spatial organization of human dental plaque using DNA sequencing. In the final project, I completed whole-genome sequencing of environmental isolates derived from single, cultivable cells and employ mutational and horizontal transfer analysis to demonstrate adaptation to harsh environmental conditions in contaminated groundwater. These projects demonstrate the rich information stored within each microbial genome and the impact of spatial distribution in the environment. Each effort also contributes or highlights new molecular biology techniques to generate genomic data from individual microbial cells.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Sarah Jean Spencer.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">Ph.D.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">140 pages</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Computational and Systems Biology Program.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Linking sequence to function in microbial genomics</dim:field>
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   	&lt;Title>Linking sequence to function in microbial genomics&lt;/Title>
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   	&lt;PublicationDate>2017&lt;/PublicationDate>
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        	&lt;DisplayName>Spencer, Sarah Jean&lt;/DisplayName>
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    &lt;Keyword>Computational and Systems Biology Program.&lt;/Keyword>
   	&lt;Abstract>Microbial genomes show high plasticity due to horizontal transfer, large community sizes, and rapid growth paired with adaptive mutations. Despite this mutability of gene content, most studies of microbial communities still rely on bulk, single-gene amplicon sequencing. In this thesis, I present methods that interrogate the gene content of single cells derived from complex natural communities. In the first project, I present a novel molecular biology method to link a bacterial functional gene to its host species with single-cell resolution. This high-throughput protocol is applied to assess the distribution of anaerobic respiration genes in a lake ecosystem. In the second project, I demonstrate extensions of this methodology to link genes between spatially proximal microbial cells, and apply this approach to probe the spatial organization of human dental plaque using DNA sequencing. In the final project, I completed whole-genome sequencing of environmental isolates derived from single, cultivable cells and employ mutational and horizontal transfer analysis to demonstrate adaptation to harsh environmental conditions in contaminated groundwater. These projects demonstrate the rich information stored within each microbial genome and the impact of spatial distribution in the environment. Each effort also contributes or highlights new molecular biology techniques to generate genomic data from individual microbial cells.&lt;/Abstract>
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