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   <dim:field mdschema="dc" element="contributor" qualifier="advisor">Blainey, Paul C.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="advisor">Hacohen, Nir</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author">Carlson, Rebecca J.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Harvard-MIT Program in Health Sciences and Technology</dim:field>
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   <dim:field mdschema="dc" element="date" qualifier="issued">2023-06</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="submitted">2023-06-13T20:48:46.636Z</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">https://hdl.handle.net/1721.1/164474</dim:field>
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   <dim:field mdschema="dc" element="description" qualifier="abstract">Host-pathogen interactions represent a complex interplay between hosts and pathogens that can evolve over millions of years. Interactions between bacteria or viruses and human cells, and the resulting evolved antipathogenic signaling pathways, are processes responsible for pathologies ranging from infectious diseases to autoimmune conditions and cancer. In addition, engineered designs inspired by pathogen interactions with hosts are increasingly being used to both treat and diagnose many pathologies that need not originate from infection with a pathogen. Therefore, it is critical to build and deploy scalable tools to better understand host-pathogen dynamics in order to both better treat conditions where pathogens or antipathogenic signaling contribute directly to disease pathology as well as to engineer new treatments to address a broader range of disease states.&#xd;
&#xd;
In this thesis, I describe approaches to leverage functional genomics and image-based screening to perturb and profile host-pathogen interactions, including responses to two RNA viruses, Sendai virus and Ebola virus. These provide case studies highlighting the utility of high-content image-based screening for revealing new genes regulating predefined phenotypes of interest as well as for generating single-cell imaging profiles that can be used to infer new genetic functions and phenotypic states directly from screening data without a priori specification. I also highlight an example of a genetic screen that revealed a robust negative result, leading to hypothesis and validation of a novel function of the STING protein as a proton channel.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree">Ph.D.</dim:field>
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   <dim:field mdschema="dc" element="title">Functional Genomic and Image-Based Screening Approaches for Probing Host-Pathogen Interactions</dim:field>
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   	&lt;Title>Functional Genomic and Image-Based Screening Approaches for Probing Host-Pathogen Interactions&lt;/Title>
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   	&lt;PublicationDate>2023-06&lt;/PublicationDate>
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        	&lt;DisplayName>Carlson, Rebecca J.&lt;/DisplayName>
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   	&lt;Abstract>Host-pathogen interactions represent a complex interplay between hosts and pathogens that can evolve over millions of years. Interactions between bacteria or viruses and human cells, and the resulting evolved antipathogenic signaling pathways, are processes responsible for pathologies ranging from infectious diseases to autoimmune conditions and cancer. In addition, engineered designs inspired by pathogen interactions with hosts are increasingly being used to both treat and diagnose many pathologies that need not originate from infection with a pathogen. Therefore, it is critical to build and deploy scalable tools to better understand host-pathogen dynamics in order to both better treat conditions where pathogens or antipathogenic signaling contribute directly to disease pathology as well as to engineer new treatments to address a broader range of disease states.&#xd;
&#xd;
In this thesis, I describe approaches to leverage functional genomics and image-based screening to perturb and profile host-pathogen interactions, including responses to two RNA viruses, Sendai virus and Ebola virus. These provide case studies highlighting the utility of high-content image-based screening for revealing new genes regulating predefined phenotypes of interest as well as for generating single-cell imaging profiles that can be used to infer new genetic functions and phenotypic states directly from screening data without a priori specification. I also highlight an example of a genetic screen that revealed a robust negative result, leading to hypothesis and validation of a novel function of the STING protein as a proton channel.&lt;/Abstract>
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