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Feng Zhang. Li, Yinqing, Ph. D. Massachusetts Institute of Technology Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2016-12-22T16:28:12Z 2016-12-22T16:28:12Z 2016 2016 http://hdl.handle.net/1721.1/106081 965242528 Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016. Cataloged from PDF version of thesis. Includes bibliographical references (pages 217-235). The recent development of genetic neural modulation technologies has brought about a renaissance in systems neurobiology, where manipulation of specific neural ensembles coupled with measurements of the resulting behavioral changes have begun to chart the functional organization of the brain. However, the scope of the application of this emerging paradigm depends critically on the ability to systematically identify and manipulate specific neural ensembles, which is currently lacking. In this thesis, we focus on the development of technologies towards systematic identification and targeting of specific neural ensembles. First, we present the development of single nuclei RNA sequencing methods and the application of the methods to chart the cellular diversity and its signature gene expression patterns in the adult mouse hippocampus. Second, we introduce rational design and predictable implementation of ultrasensitive synthetic gene circuits that can sense expression levels of cell-type specific marker genes and compute complex Boolean logic to label these cells specifically. As a proof of principle, we demonstrate that the synthetic circuit achieves classification of two cell lines based on their gene expression profiles with high accuracy. Third, we provide a design of gene circuits that can compute the strength of correlation of neural activity to an external stimulus using immediate early genes. As a proof of principle, we demonstrate that the synthetic gene circuit can be used to label cells that respond to exogenously controlled chemical stimuli as an analog to neural activity. Finally, we describe a streamlined framework for modular construction of large synthetic gene circuits on single vectors and their targeted delivery into mammalian cells. by Yinqing Li. Ph.D. 235 pages eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Electrical Engineering and Computer Science. Towards dissecting neural ensembles : development of genetic profiling and targeting approaches Thesis application/pdf Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="f6ebff44-9383-4265-90c5-54ad121f190a"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Towards dissecting neural ensembles : development of genetic profiling and targeting approaches</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2016</PublicationDate> <Authors> <Author> <DisplayName>Li, Yinqing, Ph. D. Massachusetts Institute of Technology</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Electrical Engineering and Computer Science.</Keyword> <Abstract>The recent development of genetic neural modulation technologies has brought about a renaissance in systems neurobiology, where manipulation of specific neural ensembles coupled with measurements of the resulting behavioral changes have begun to chart the functional organization of the brain. However, the scope of the application of this emerging paradigm depends critically on the ability to systematically identify and manipulate specific neural ensembles, which is currently lacking. In this thesis, we focus on the development of technologies towards systematic identification and targeting of specific neural ensembles. First, we present the development of single nuclei RNA sequencing methods and the application of the methods to chart the cellular diversity and its signature gene expression patterns in the adult mouse hippocampus. Second, we introduce rational design and predictable implementation of ultrasensitive synthetic gene circuits that can sense expression levels of cell-type specific marker genes and compute complex Boolean logic to label these cells specifically. As a proof of principle, we demonstrate that the synthetic circuit achieves classification of two cell lines based on their gene expression profiles with high accuracy. Third, we provide a design of gene circuits that can compute the strength of correlation of neural activity to an external stimulus using immediate early genes. As a proof of principle, we demonstrate that the synthetic gene circuit can be used to label cells that respond to exogenously controlled chemical stimuli as an analog to neural activity. Finally, we describe a streamlined framework for modular construction of large synthetic gene circuits on single vectors and their targeted delivery into mammalian cells.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>