{"id":{"repo_id":"cambridge","oai_identifier":"oai:www.repository.cam.ac.uk:1810/358979"},"canonical_url":"https://search.dev.ndltd.org/etd/cambridge/oai:www.repository.cam.ac.uk:1810/358979","repository":{"repo_id":"cambridge","name":"Cambridge University","base_url":"https://api.repository.cam.ac.uk/server/oai/request"},"display":{"title":"Understanding Development of Human Immunity One Cell at a Time","abstract":"The emergence of single-cell and spatial multi-omic technologies has revolutionized our understanding of the immune cells. The international Human Cell Atlas consortium has spearheaded and coordinated a global effort to construct atlases of human tissues across multiple developmental stages. This is revealing the identity and function of cells at unprecedented resolution and depth, enhancing our understanding of the immune system in health and disease. The Human Cell Atlas data is also providing us with valuable prior knowledge to guide *in vitro* engineering of immune cells towards specific cell states. This thesis aims to study human immune cell development from both *in vivo* and *in vitro* angles, utilizing both experimental and newly developed computational approaches. Importantly, I focus on applying insights from single-cell genomics studies of human immune cell development to *in vitro* lymphocyte engineering. Chapter 1 introduces the recent advances in single-cell technologies in the context of previous methods used to study immune cells, summarizes human immune cell development with a focus on lymphocyte development, and presents published efforts in *in vitro* T cell engineering. Chapter 2 covers the assembly of a multi-organ single cell atlas of the developing human immune system and describes the insights derived from this comprehensive atlas. We uncovered system-wide blood and immune cell development in organs other than primary haematopoietic organs, and characterized prenatal innate-like B and T cells, namely B1 cells and unconventional T cells in humans for the first time. Chapter 3 is dedicated to a new computational tool, Dandelion, that we developed for single cell antigen receptor sequencing (scVDJ-seq) data analysis. We also devised a novel strategy to leverage scVDJ-seq data in pseudotime trajectory inference. The application of Dandelion improved the alignment of human thymic development trajectories of double positive T cells to mature single-positive CD4/CD8 T cells, and provided novel insights into the origins of human B1 cells and ILC/NK cell development. Chapter 4 introduces another computational tool, Genes2Genes, for aligning two single-cell trajectories. By applying Genes2Genes to *in vivo* and *in vitro* T cell development, we found that *in vitro* single positive (SP) T cells were matched to an immature state of the *in vivo* SP T cells while lacking the final TNFα signaling. Chapter 5 summarizes the insights gained from my work on human immune cell development and highlights potential future directions of research in this area.","abstract_html":"The emergence of single-cell and spatial multi-omic technologies has revolutionized our understanding of the immune cells. The international Human Cell Atlas consortium has spearheaded and coordinated a global effort to construct atlases of human tissues across multiple developmental stages. This is revealing the identity and function of cells at unprecedented resolution and depth, enhancing our understanding of the immune system in health and disease. The Human Cell Atlas data is also providing us with valuable prior knowledge to guide *in vitro* engineering of immune cells towards specific cell states. This thesis aims to study human immune cell development from both *in vivo* and *in vitro* angles, utilizing both experimental and newly developed computational approaches. Importantly, I focus on applying insights from single-cell genomics studies of human immune cell development to *in vitro* lymphocyte engineering. Chapter 1 introduces the recent advances in single-cell technologies in the context of previous methods used to study immune cells, summarizes human immune cell development with a focus on lymphocyte development, and presents published efforts in *in vitro* T cell engineering. Chapter 2 covers the assembly of a multi-organ single cell atlas of the developing human immune system and describes the insights derived from this comprehensive atlas. We uncovered system-wide blood and immune cell development in organs other than primary haematopoietic organs, and characterized prenatal innate-like B and T cells, namely B1 cells and unconventional T cells in humans for the first time. Chapter 3 is dedicated to a new computational tool, Dandelion, that we developed for single cell antigen receptor sequencing (scVDJ-seq) data analysis. We also devised a novel strategy to leverage scVDJ-seq data in pseudotime trajectory inference. The application of Dandelion improved the alignment of human thymic development trajectories of double positive T cells to mature single-positive CD4/CD8 T cells, and provided novel insights into the origins of human B1 cells and ILC/NK cell development. Chapter 4 introduces another computational tool, Genes2Genes, for aligning two single-cell trajectories. By applying Genes2Genes to *in vivo* and *in vitro* T cell development, we found that *in vitro* single positive (SP) T cells were matched to an immature state of the *in vivo* SP T cells while lacking the final TNFα signaling. Chapter 5 summarizes the insights gained from my work on human immune cell development and highlights potential future directions of research in this area.","abstract_has_math":false,"creators":["Suo, Chenqu"],"institution":"University of Cambridge","degree_name":"Doctor of Philosophy (PhD)","degree_level":"Doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Teichmann, Sarah"],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-03-11","date_published":"2023-03-11","updated_at":"2026-07-22T22:24:07Z","subjects":["antigen receptor sequencing","atlas","B cell","cell engineering","genomics","immune","single cell","T cell"],"languages":["eng"],"rights":[],"rights_urls":["https://apollo8-f-pro.lib.cam.ac.uk/bitstreams/29b47e99-74ee-4c2d-a85b-c88a699fae3d/download","https://creativecommons.org/licenses/by-nc-nd/4.0/"],"identifier_entries":[{"key":"dc:creator.authoridentifier","label":"Author Identifier","values":["0000000288130875"],"render_values":[{"text":"0000-0002-8813-0875","href":"https://orcid.org/0000-0002-8813-0875","code":true}]}]},"links":{"outbound_url":"https://doi.org/10.17863/CAM.102304","outbound_label":"DOI","outbound_source":"dc:identifier.doi"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Teichmann, Sarah"]},{"key":"dc:contributor.sponsor","label":"Sponsor","values":["This work was supported by the Wellcome Human Cell Atlas Strategic Science Support (grant WT211276/Z/18/Z), CZI Seed Networks for the Human Cell Atlas (Thymus award CZF2019-002445), a MRC Human Cell Atlas award, the Wellcome Human Developmental Biology Initiative, and a grant from the Wellcome Sanger Institute’s Translation Committee Fund. 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Importantly, I focus on applying insights from single-cell genomics studies of human immune cell development to *in vitro* lymphocyte engineering. Chapter 1 introduces the recent advances in single-cell technologies in the context of previous methods used to study immune cells, summarizes human immune cell development with a focus on lymphocyte development, and presents published efforts in *in vitro* T cell engineering. Chapter 2 covers the assembly of a multi-organ single cell atlas of the developing human immune system and describes the insights derived from this comprehensive atlas. We uncovered system-wide blood and immune cell development in organs other than primary haematopoietic organs, and characterized prenatal innate-like B and T cells, namely B1 cells and unconventional T cells in humans for the first time. Chapter 3 is dedicated to a new computational tool, Dandelion, that we developed for single cell antigen receptor sequencing (scVDJ-seq) data analysis. 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