Profiling Host Respiratory Responses to SARS-CoV-2 Infection
Single-cell genomics have revolutionized the granularity with which we can dissect cellular phenotypes in both health and disease. Global atlases of homeostatic tissues have revealed rare cell populations critical to organ function and provide comprehensive genomic reference maps for the scientific...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2023
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| Online Access: | https://hdl.handle.net/1721.1/152793 https://orcid.org/0000-0002-4040-5171 |
| _version_ | 1826212416768180224 |
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| author | Miao, Vincent N. |
| author2 | Shalek, Alex K. |
| author_facet | Shalek, Alex K. Miao, Vincent N. |
| author_sort | Miao, Vincent N. |
| collection | MIT |
| description | Single-cell genomics have revolutionized the granularity with which we can dissect cellular phenotypes in both health and disease. Global atlases of homeostatic tissues have revealed rare cell populations critical to organ function and provide comprehensive genomic reference maps for the scientific community, and profiling of non-homeostatic tissues—across oncology, inflammation, autoimmunity, infectious disease and beyond—have revealed insights into the drivers of disease pathogenesis and potential avenues for prophylactic or therapeutic intervention. Over the past three years, we have studied SARS-CoV-2 infection through the lens of single-cell genomics, querying pre-existing single-cell datasets, developing in vitro models of disease, validating animal models of infection, and profiling human samples with our clinical collaborators, all the while adding to the vast trove of COVID-19 knowledge generated amidst a global pandemic. In the early days of the pandemic, we identify putative targets of SARS-CoV-2 infection in human and non-human primate tissues and discover that the SARS-CoV-2 entry receptor ACE2/Ace2 is an interferon-stimulated gene in human but not murine nasal epithelia. We then profile nasopharyngeal swabs taken from individuals upon hospital admission, stratifying epithelial responses to infection based on ensuing peak disease severity. We identify a muted anti-viral response to infection within the nasal epithelia as a correlate of severe but not mild or moderate disease progression. Finally, we turn to non-human models of SARS-CoV-2 infection to profile the lower respiratory response to viral perturbation across multiple acute time points, pinpointing cellular populations and attributes that are associated with enhanced protection in the lower respiratory tract. Together, our work highlights the use of single-cell genomics in uncovering tissue-based host-pathogen interactions and provides a framework for rapidly and systematically assessing the immune response to emerging pathogenic threats. |
| first_indexed | 2024-09-23T15:21:19Z |
| format | Thesis |
| id | mit-1721.1/152793 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T15:21:19Z |
| publishDate | 2023 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1527932023-11-03T03:10:47Z Profiling Host Respiratory Responses to SARS-CoV-2 Infection Miao, Vincent N. Shalek, Alex K. Harvard-MIT Program in Health Sciences and Technology Single-cell genomics have revolutionized the granularity with which we can dissect cellular phenotypes in both health and disease. Global atlases of homeostatic tissues have revealed rare cell populations critical to organ function and provide comprehensive genomic reference maps for the scientific community, and profiling of non-homeostatic tissues—across oncology, inflammation, autoimmunity, infectious disease and beyond—have revealed insights into the drivers of disease pathogenesis and potential avenues for prophylactic or therapeutic intervention. Over the past three years, we have studied SARS-CoV-2 infection through the lens of single-cell genomics, querying pre-existing single-cell datasets, developing in vitro models of disease, validating animal models of infection, and profiling human samples with our clinical collaborators, all the while adding to the vast trove of COVID-19 knowledge generated amidst a global pandemic. In the early days of the pandemic, we identify putative targets of SARS-CoV-2 infection in human and non-human primate tissues and discover that the SARS-CoV-2 entry receptor ACE2/Ace2 is an interferon-stimulated gene in human but not murine nasal epithelia. We then profile nasopharyngeal swabs taken from individuals upon hospital admission, stratifying epithelial responses to infection based on ensuing peak disease severity. We identify a muted anti-viral response to infection within the nasal epithelia as a correlate of severe but not mild or moderate disease progression. Finally, we turn to non-human models of SARS-CoV-2 infection to profile the lower respiratory response to viral perturbation across multiple acute time points, pinpointing cellular populations and attributes that are associated with enhanced protection in the lower respiratory tract. Together, our work highlights the use of single-cell genomics in uncovering tissue-based host-pathogen interactions and provides a framework for rapidly and systematically assessing the immune response to emerging pathogenic threats. Ph.D. 2023-11-02T20:16:39Z 2023-11-02T20:16:39Z 2023-09 2023-09-07T20:20:05.131Z Thesis https://hdl.handle.net/1721.1/152793 https://orcid.org/0000-0002-4040-5171 In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology |
| spellingShingle | Miao, Vincent N. Profiling Host Respiratory Responses to SARS-CoV-2 Infection |
| title | Profiling Host Respiratory Responses to SARS-CoV-2 Infection |
| title_full | Profiling Host Respiratory Responses to SARS-CoV-2 Infection |
| title_fullStr | Profiling Host Respiratory Responses to SARS-CoV-2 Infection |
| title_full_unstemmed | Profiling Host Respiratory Responses to SARS-CoV-2 Infection |
| title_short | Profiling Host Respiratory Responses to SARS-CoV-2 Infection |
| title_sort | profiling host respiratory responses to sars cov 2 infection |
| url | https://hdl.handle.net/1721.1/152793 https://orcid.org/0000-0002-4040-5171 |
| work_keys_str_mv | AT miaovincentn profilinghostrespiratoryresponsestosarscov2infection |