The ability to engineer programmable biological systems using complex artificial gene networks has great potential to unlock important innovative solutions to many biotechnological challenges. While cells have been engineered to implement complex information processing algorithms and to produce food, materials, and pharmaceuticals, many innovative applications are yet to be realized due to our poor understanding of how robust, reliable, and predictable artificial gene circuits are built. In this work, we demonstrate that robust complex cellular behaviors (e.g., bistability and gene expression dynamics) can be achieved by engineering gene regulatory architecture and increasing the complexity of genetic networks. We further demonstrate that increasing demand for cellular resources causes resource-associated interference among noninteracting genetic devices of various complexities. Importantly, we show that feedback systems can be engineered to enhance the robustness and reliability of genetic circuits by reducing such resource-associated interference among independent circuits. Taken together, this work contributes to understanding the design principles that govern biological robustness and represents an important step towards construction of robust, tunable, reliable, and predictable complex artificial genetic circuits for a wide range of biotechnological applications.
","abstract_html":"<p>The ability to engineer programmable biological systems using complex artificial gene networks has great potential to unlock important innovative solutions to many biotechnological challenges. While cells have been engineered to implement complex information processing algorithms and to produce food, materials, and pharmaceuticals, many innovative applications are yet to be realized due to our poor understanding of how robust, reliable, and predictable artificial gene circuits are built. In this work, we demonstrate that robust complex cellular behaviors (e.g., bistability and gene expression dynamics) can be achieved by engineering gene regulatory architecture and increasing the complexity of genetic networks. We further demonstrate that increasing demand for cellular resources causes resource-associated interference among noninteracting genetic devices of various complexities. Importantly, we show that feedback systems can be engineered to enhance the robustness and reliability of genetic circuits by reducing such resource-associated interference among independent circuits. Taken together, this work contributes to understanding the design principles that govern biological robustness and represents an important step towards construction of robust, tunable, reliable, and predictable complex artificial genetic circuits for a wide range of biotechnological applications.</p>","abstract_has_math":false,"creators":["Shopera, Tatenda"],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Dissertation","degree_discipline":"Energy, Environmental & Chemical Engineering","degree_department":null,"school":null,"contributors":["Tae Seok Moon","Michael Brent, Himadri Pakrasi, Yinjie Tang, Fuzhong Zhang,"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-08-15T07:00:00Z","date_published":"2018-08-15T07:00:00Z","updated_at":"2026-07-24T06:13:31Z","subjects":["Biological robustness","Gene expression dynamics","Negative feedback","Protein sequestration","Regulatory architecture","Resource competition","Biomedical Engineering and Bioengineering","Chemical Engineering"],"languages":["English (en)"],"rights":["I have not registered my thesis with the U.S. Copyright Office, and do not intend to."],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["https://openscholarship.wustl.edu/eng_etds/378"],"render_values":[{"text":"https://openscholarship.wustl.edu/eng_etds/378","href":"https://openscholarship.wustl.edu/eng_etds/378","code":true}]}]},"links":{"outbound_url":"https://doi.org/10.7936/zasx-vf36","outbound_label":"DOI","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Tae Seok Moon","Michael Brent, Himadri Pakrasi, Yinjie Tang, Fuzhong Zhang,"]},{"key":"dc:creator","label":"Author","values":["Shopera, Tatenda"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2018-08-15T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Energy, Environmental & Chemical Engineering","McKelvey School of Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Biological robustness","Gene expression dynamics","Negative feedback","Protein sequestration","Regulatory architecture","Resource competition","Biomedical Engineering and Bioengineering","Chemical Engineering"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English (en)"]},{"key":"dc:rights","label":"Dc Rights","values":["I have not registered my thesis with the U.S. Copyright Office, and do not intend to."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://doi.org/10.7936/zasx-vf36","https://openscholarship.wustl.edu/eng_etds/378"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Permanent URL: https://doi.org/10.7936/zasx-vf36"]},{"key":"dc:description.abstract","label":"Abstract","values":["The ability to engineer programmable biological systems using complex artificial gene networks has great potential to unlock important innovative solutions to many biotechnological challenges. While cells have been engineered to implement complex information processing algorithms and to produce food, materials, and pharmaceuticals, many innovative applications are yet to be realized due to our poor understanding of how robust, reliable, and predictable artificial gene circuits are built. In this work, we demonstrate that robust complex cellular behaviors (e.g., bistability and gene expression dynamics) can be achieved by engineering gene regulatory architecture and increasing the complexity of genetic networks. We further demonstrate that increasing demand for cellular resources causes resource-associated interference among noninteracting genetic devices of various complexities. Importantly, we show that feedback systems can be engineered to enhance the robustness and reliability of genetic circuits by reducing such resource-associated interference among independent circuits. Taken together, this work contributes to understanding the design principles that govern biological robustness and represents an important step towards construction of robust, tunable, reliable, and predictable complex artificial genetic circuits for a wide range of biotechnological applications.
"]},{"key":"dc:title","label":"Title","values":["Engineering Robust and Programmable Biological Systems"]}]}],"canonical_facts":{"dc:contributor":["Tae Seok Moon","Michael Brent, Himadri Pakrasi, Yinjie Tang, Fuzhong Zhang,"],"dc:creator":["Shopera, Tatenda"],"dc:date.available":["2018-08-15T07:00:00Z"],"dc:description":["Permanent URL: https://doi.org/10.7936/zasx-vf36"],"dc:description.abstract":["The ability to engineer programmable biological systems using complex artificial gene networks has great potential to unlock important innovative solutions to many biotechnological challenges. While cells have been engineered to implement complex information processing algorithms and to produce food, materials, and pharmaceuticals, many innovative applications are yet to be realized due to our poor understanding of how robust, reliable, and predictable artificial gene circuits are built. In this work, we demonstrate that robust complex cellular behaviors (e.g., bistability and gene expression dynamics) can be achieved by engineering gene regulatory architecture and increasing the complexity of genetic networks. We further demonstrate that increasing demand for cellular resources causes resource-associated interference among noninteracting genetic devices of various complexities. Importantly, we show that feedback systems can be engineered to enhance the robustness and reliability of genetic circuits by reducing such resource-associated interference among independent circuits. Taken together, this work contributes to understanding the design principles that govern biological robustness and represents an important step towards construction of robust, tunable, reliable, and predictable complex artificial genetic circuits for a wide range of biotechnological applications.
"],"dc:identifier":["https://doi.org/10.7936/zasx-vf36","https://openscholarship.wustl.edu/eng_etds/378"],"dc:language":["English (en)"],"dc:rights":["I have not registered my thesis with the U.S. Copyright Office, and do not intend to."],"dc:subject":["Biological robustness","Gene expression dynamics","Negative feedback","Protein sequestration","Regulatory architecture","Resource competition","Biomedical Engineering and Bioengineering","Chemical Engineering"],"dc:title":["Engineering Robust and Programmable Biological Systems"],"thesis:degree_discipline":["Energy, Environmental & Chemical Engineering","McKelvey School of Engineering"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T06:13:31Z"}