{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/109418"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/109418","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Influenza a virus gene expression heterogeneity regulates viral superinfection potential and host innate antiviral response","abstract":"Influenza A virus (IAV) is an infectious respiratory pathogen that causes seasonal epidemics and sporadic pandemics in human, resulting in tens of thousands of deaths and tens of billions of dollars in economic costs every year in the U.S. alone. Its genome consists of eight gene segments each encoding one or more viral proteins. The expression of all eight genes is required to initiate productive infection. Interestingly, under the single particle infection condition, most IAV particles are semi-infectious particles (SIPs) that express an incomplete subset of the eight viral genes. The production and gene expression pattern of SIPs can vary hugely between IAV strains. However, the biological significance of this intrinsic gene expression heterogeneity at single particle level remains poorly understood. Here, I aim to investigate that whether and how this heterogeneity influences viral superinfection and host innate antiviral response. To initiate productive infection, multiple SIPs must co-infect one cell to achieve complementation. Within a certain MOI range, increasing the abundance of SIPs in a viral population increases the percentage of productively infected cells that result from co-infection. One of the primary ways by which co-infection can occur is superinfection, the sequential infection of one cell by multiple viral particles. However, how SIPs affect IAV superinfection remain largely unknown. By combining single particle infection and multi-color flow cytometry, I directly assessed the effects of individual IAV genes on superinfection efficiency and revealed that superinfection susceptibility is negatively correlated with the quantity of viral gene segments expressed within an infected cell, regardless of their identity. As a result, cells infected with SIPs are more susceptible to superinfection compared to cells infected with particles that express a complete set of viral genes, and viral populations that contain more SIPs undergo more-frequent superinfection. Further, I found that viral replicase activity in infected cells is responsible for inhibiting the subsequent infection. These findings identify viral gene expression heterogeneity as a major determinant of IAV superinfection potential. Viral infection outcomes are governed by the complex interactions between infecting virus population and host response. Although viral gene expression within IAV population is extremely heterogeneous, little is known about how this heterogeneity influences host response to infection. By pairing Fluorescence-Activated Cell Sorting (FACS) with single cell RNA-seq (scRNAseq), I examined the combined host and viral transcriptomes of thousands of individual cells, each infected with a single IAV particle. I observed complex patterns of viral gene expression and the existence of multiple distinct host transcriptional responses to infection at single cell level. In addition, SIPs that fail to express the NS gene can play a dominant role in triggering innate anti-viral response to infection. Finally, human H1N1 and H3N2 virus infections differ significantly in patterns of host anti-viral gene transcriptional at single cell level. These results revealed that how patterns of viral gene expression heterogeneity can serve as a major determinant of host antiviral gene activation. Altogether, these studies demonstrate that IAV gene expression heterogeneity has clear functional consequences on both viral superinfection potential and host innate response to infection. More broadly, my works help establish the importance of understanding the effects of population heterogeneity on viral collective interactions and pathogenesis.","abstract_html":"Influenza A virus (IAV) is an infectious respiratory pathogen that causes seasonal epidemics and sporadic pandemics in human, resulting in tens of thousands of deaths and tens of billions of dollars in economic costs every year in the U.S. alone. Its genome consists of eight gene segments each encoding one or more viral proteins. The expression of all eight genes is required to initiate productive infection. Interestingly, under the single particle infection condition, most IAV particles are semi-infectious particles (SIPs) that express an incomplete subset of the eight viral genes. The production and gene expression pattern of SIPs can vary hugely between IAV strains. However, the biological significance of this intrinsic gene expression heterogeneity at single particle level remains poorly understood. Here, I aim to investigate that whether and how this heterogeneity influences viral superinfection and host innate antiviral response. To initiate productive infection, multiple SIPs must co-infect one cell to achieve complementation. Within a certain MOI range, increasing the abundance of SIPs in a viral population increases the percentage of productively infected cells that result from co-infection. One of the primary ways by which co-infection can occur is superinfection, the sequential infection of one cell by multiple viral particles. However, how SIPs affect IAV superinfection remain largely unknown. By combining single particle infection and multi-color flow cytometry, I directly assessed the effects of individual IAV genes on superinfection efficiency and revealed that superinfection susceptibility is negatively correlated with the quantity of viral gene segments expressed within an infected cell, regardless of their identity. As a result, cells infected with SIPs are more susceptible to superinfection compared to cells infected with particles that express a complete set of viral genes, and viral populations that contain more SIPs undergo more-frequent superinfection. Further, I found that viral replicase activity in infected cells is responsible for inhibiting the subsequent infection. These findings identify viral gene expression heterogeneity as a major determinant of IAV superinfection potential. Viral infection outcomes are governed by the complex interactions between infecting virus population and host response. Although viral gene expression within IAV population is extremely heterogeneous, little is known about how this heterogeneity influences host response to infection. By pairing Fluorescence-Activated Cell Sorting (FACS) with single cell RNA-seq (scRNAseq), I examined the combined host and viral transcriptomes of thousands of individual cells, each infected with a single IAV particle. I observed complex patterns of viral gene expression and the existence of multiple distinct host transcriptional responses to infection at single cell level. In addition, SIPs that fail to express the NS gene can play a dominant role in triggering innate anti-viral response to infection. Finally, human H1N1 and H3N2 virus infections differ significantly in patterns of host anti-viral gene transcriptional at single cell level. These results revealed that how patterns of viral gene expression heterogeneity can serve as a major determinant of host antiviral gene activation. Altogether, these studies demonstrate that IAV gene expression heterogeneity has clear functional consequences on both viral superinfection potential and host innate response to infection. More broadly, my works help establish the importance of understanding the effects of population heterogeneity on viral collective interactions and pathogenesis.","abstract_has_math":false,"creators":["Sun, Jiayi"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Microbiology","degree_department":null,"school":null,"contributors":["Brooke, Christopher Byron","Kehl-Fie, Thomas Everett","Whitaker, Rachel","Blanke, Steven Robert"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-03-05T21:38:16Z","date_published":"2021-03-05T21:38:16Z","updated_at":"2026-07-22T22:24:50Z","subjects":["Influenza A virus","Semi-infectious particles","Gene expression heterogeneity","Superinfection","Innate antiviral response"],"languages":["en"],"rights":["Copyright 2020 Jiayi Sun"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/109418","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Brooke, Christopher Byron","Kehl-Fie, Thomas Everett","Whitaker, Rachel","Blanke, Steven Robert"]},{"key":"dc:creator","label":"Author","values":["Sun, Jiayi"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2021-03-05T21:38:16Z","2020-12-02","2020-12"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"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":["Influenza A virus","Semi-infectious particles","Gene expression heterogeneity","Superinfection","Innate antiviral response"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2020 Jiayi Sun"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/109418"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Influenza A virus (IAV) is an infectious respiratory pathogen that causes seasonal epidemics and sporadic pandemics in human, resulting in tens of thousands of deaths and tens of billions of dollars in economic costs every year in the U.S. alone. Its genome consists of eight gene segments each encoding one or more viral proteins. The expression of all eight genes is required to initiate productive infection. Interestingly, under the single particle infection condition, most IAV particles are semi-infectious particles (SIPs) that express an incomplete subset of the eight viral genes. The production and gene expression pattern of SIPs can vary hugely between IAV strains. However, the biological significance of this intrinsic gene expression heterogeneity at single particle level remains poorly understood. Here, I aim to investigate that whether and how this heterogeneity influences viral superinfection and host innate antiviral response. To initiate productive infection, multiple SIPs must co-infect one cell to achieve complementation. Within a certain MOI range, increasing the abundance of SIPs in a viral population increases the percentage of productively infected cells that result from co-infection. One of the primary ways by which co-infection can occur is superinfection, the sequential infection of one cell by multiple viral particles. However, how SIPs affect IAV superinfection remain largely unknown. By combining single particle infection and multi-color flow cytometry, I directly assessed the effects of individual IAV genes on superinfection efficiency and revealed that superinfection susceptibility is negatively correlated with the quantity of viral gene segments expressed within an infected cell, regardless of their identity. As a result, cells infected with SIPs are more susceptible to superinfection compared to cells infected with particles that express a complete set of viral genes, and viral populations that contain more SIPs undergo more-frequent superinfection. Further, I found that viral replicase activity in infected cells is responsible for inhibiting the subsequent infection. These findings identify viral gene expression heterogeneity as a major determinant of IAV superinfection potential. Viral infection outcomes are governed by the complex interactions between infecting virus population and host response. Although viral gene expression within IAV population is extremely heterogeneous, little is known about how this heterogeneity influences host response to infection. By pairing Fluorescence-Activated Cell Sorting (FACS) with single cell RNA-seq (scRNAseq), I examined the combined host and viral transcriptomes of thousands of individual cells, each infected with a single IAV particle. I observed complex patterns of viral gene expression and the existence of multiple distinct host transcriptional responses to infection at single cell level. In addition, SIPs that fail to express the NS gene can play a dominant role in triggering innate anti-viral response to infection. Finally, human H1N1 and H3N2 virus infections differ significantly in patterns of host anti-viral gene transcriptional at single cell level. These results revealed that how patterns of viral gene expression heterogeneity can serve as a major determinant of host antiviral gene activation. Altogether, these studies demonstrate that IAV gene expression heterogeneity has clear functional consequences on both viral superinfection potential and host innate response to infection. More broadly, my works help establish the importance of understanding the effects of population heterogeneity on viral collective interactions and pathogenesis.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2021-03-04 without embargo terms","The student, Jiayi Sun, accepted the attached license on 2020-12-01 at 20:26.","The student, Jiayi Sun, submitted this Dissertation for approval on 2020-12-01 at 21:30.","This Dissertation was approved for publication on 2020-12-02 at 09:44.","DSpace SAF Submission Ingestion Package generated from Vireo submission #16023 on 2021-03-04 at 15:35:48","Made available in DSpace on 2021-03-05T21:38:16Z (GMT). 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Its genome consists of eight gene segments each encoding one or more viral proteins. The expression of all eight genes is required to initiate productive infection. Interestingly, under the single particle infection condition, most IAV particles are semi-infectious particles (SIPs) that express an incomplete subset of the eight viral genes. The production and gene expression pattern of SIPs can vary hugely between IAV strains. However, the biological significance of this intrinsic gene expression heterogeneity at single particle level remains poorly understood. Here, I aim to investigate that whether and how this heterogeneity influences viral superinfection and host innate antiviral response. To initiate productive infection, multiple SIPs must co-infect one cell to achieve complementation. Within a certain MOI range, increasing the abundance of SIPs in a viral population increases the percentage of productively infected cells that result from co-infection. One of the primary ways by which co-infection can occur is superinfection, the sequential infection of one cell by multiple viral particles. However, how SIPs affect IAV superinfection remain largely unknown. By combining single particle infection and multi-color flow cytometry, I directly assessed the effects of individual IAV genes on superinfection efficiency and revealed that superinfection susceptibility is negatively correlated with the quantity of viral gene segments expressed within an infected cell, regardless of their identity. As a result, cells infected with SIPs are more susceptible to superinfection compared to cells infected with particles that express a complete set of viral genes, and viral populations that contain more SIPs undergo more-frequent superinfection. Further, I found that viral replicase activity in infected cells is responsible for inhibiting the subsequent infection. These findings identify viral gene expression heterogeneity as a major determinant of IAV superinfection potential. Viral infection outcomes are governed by the complex interactions between infecting virus population and host response. Although viral gene expression within IAV population is extremely heterogeneous, little is known about how this heterogeneity influences host response to infection. By pairing Fluorescence-Activated Cell Sorting (FACS) with single cell RNA-seq (scRNAseq), I examined the combined host and viral transcriptomes of thousands of individual cells, each infected with a single IAV particle. I observed complex patterns of viral gene expression and the existence of multiple distinct host transcriptional responses to infection at single cell level. In addition, SIPs that fail to express the NS gene can play a dominant role in triggering innate anti-viral response to infection. Finally, human H1N1 and H3N2 virus infections differ significantly in patterns of host anti-viral gene transcriptional at single cell level. These results revealed that how patterns of viral gene expression heterogeneity can serve as a major determinant of host antiviral gene activation. Altogether, these studies demonstrate that IAV gene expression heterogeneity has clear functional consequences on both viral superinfection potential and host innate response to infection. More broadly, my works help establish the importance of understanding the effects of population heterogeneity on viral collective interactions and pathogenesis.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2021-03-04 without embargo terms","The student, Jiayi Sun, accepted the attached license on 2020-12-01 at 20:26.","The student, Jiayi Sun, submitted this Dissertation for approval on 2020-12-01 at 21:30.","This Dissertation was approved for publication on 2020-12-02 at 09:44.","DSpace SAF Submission Ingestion Package generated from Vireo submission #16023 on 2021-03-04 at 15:35:48","Made available in DSpace on 2021-03-05T21:38:16Z (GMT). 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