2026-09-19T15:39:21Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1278882026-06-17T14:44:48Zcom_1721.1_7582com_1721.1_7581col_1721.1_131022
J. Christopher Love.
Tu, Ang A.(Ang Andy)
Massachusetts Institute of Technology. Department of Biological Engineering.
Massachusetts Institute of Technology. Department of Biological Engineering
2020-10-08T21:28:56Z
2020-10-08T21:28:56Z
2020
2020
https://hdl.handle.net/1721.1/127888
1197072592
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, May, 2020
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 107-112).
Heterogeneity of the immune system has increasingly necessitated the use of high-resolution techniques, including flow cytometry, RNA-seq, and mass spectrometry, to decipher the immune underpinnings of various diseases such as cancer and autoimmune disorders. In recent years, high-throughput single-cell RNA sequencing (scRNA-seq) has gained popularity among immunologists due to its ability to effectively characterize thousands of individual immune cells from tissues. Current techniques, however, are limited in their ability to elucidate essential immune cell features, including variable sequences of T cell antigen receptors (TCRs) that confer antigen specificity. Incorporation of TCR sequencing into scRNA-seq data could identify cells with shared antigen-recognition, further elucidating dynamics of antigen-specific immune responses in T cells.
In the first part of this thesis work, we develop a strategy that enables simultaneous analysis of TCR sequences and corresponding full transcriptomes from 32 barcoded scRNA-seq samples. This approach is compatible with common 32 scRNA-seq methods, and adaptable to processed samples post hoc. We applied the technique to identify transcriptional signatures associated with clonal T cells from murine and human samples. In both cases, we observed preferential phenotypes among subsets of expanded T cell clones, including cytotoxic T cell states associated with immunization against viral peptides. In the second part of the thesis, we apply the strategy to a 12-patient study of peanut food allergy to characterize T helper cell responses to oral immunotherapy (OIT). We identified clonal T cells associated with distinct subsets of T helper cells, including Teff, Treg, and Tfh, as well as Th1, Th2, and Th17 signatures.
We found that though the TCR repertoires of the patients were remarkably stable, regardless of their clinical outcomes, Th1 and Th2 clonotypes were phenotypically suppressed while Tfh clonotypes were not affected by therapy. Furthermore, we observed that highly activated clones were less likely to be suppressed by OIT than less activated clones. Our work represents one of the most detailed transcriptomic profiles of T helper cells in food allergy. In the last part of the thesis, we leverage the simplicity and adaptability of the method to recover TCR sequences from previously processed scRNA-seq samples derived from HIV patients and a nonhuman primate model of TB. In the HIV study, we recovered expanded clonotypes associated with activated T cells from longitudinal samples from patients with acute HIV infections. In the TB study, we modified the primers used in the method to T cells from TB granulomas of cynomolgus macaques.
We identified not only expanded clonotypes associated with cytotoxic functions, but also clonotypes shared by clusters of activated T cells. In total, these results demonstrate the utility of our method when studying diseases in which clonotype-driven responses are critical to understanding the underlying biology.
by Ang A. Tu.
Ph.D.
Ph.D. Massachusetts Institute of Technology, Department of Biological Engineering
126 pages
eng
Massachusetts Institute of Technology
MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.
http://dspace.mit.edu/handle/1721.1/7582
Biological Engineering.
Recovery of T cell receptor variable sequences from 3' barcoded single-cell RNA sequencing libraries
Thesis
application/pdf
2020-10-08T21:28:55Z
Publication
Doctoral
BioEng
unknown
unknown
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<Abstract>Heterogeneity of the immune system has increasingly necessitated the use of high-resolution techniques, including flow cytometry, RNA-seq, and mass spectrometry, to decipher the immune underpinnings of various diseases such as cancer and autoimmune disorders. In recent years, high-throughput single-cell RNA sequencing (scRNA-seq) has gained popularity among immunologists due to its ability to effectively characterize thousands of individual immune cells from tissues. Current techniques, however, are limited in their ability to elucidate essential immune cell features, including variable sequences of T cell antigen receptors (TCRs) that confer antigen specificity. Incorporation of TCR sequencing into scRNA-seq data could identify cells with shared antigen-recognition, further elucidating dynamics of antigen-specific immune responses in T cells.</Abstract>
<Abstract>In the first part of this thesis work, we develop a strategy that enables simultaneous analysis of TCR sequences and corresponding full transcriptomes from 32 barcoded scRNA-seq samples. This approach is compatible with common 32 scRNA-seq methods, and adaptable to processed samples post hoc. We applied the technique to identify transcriptional signatures associated with clonal T cells from murine and human samples. In both cases, we observed preferential phenotypes among subsets of expanded T cell clones, including cytotoxic T cell states associated with immunization against viral peptides. In the second part of the thesis, we apply the strategy to a 12-patient study of peanut food allergy to characterize T helper cell responses to oral immunotherapy (OIT). We identified clonal T cells associated with distinct subsets of T helper cells, including Teff, Treg, and Tfh, as well as Th1, Th2, and Th17 signatures.</Abstract>
<Abstract>We found that though the TCR repertoires of the patients were remarkably stable, regardless of their clinical outcomes, Th1 and Th2 clonotypes were phenotypically suppressed while Tfh clonotypes were not affected by therapy. Furthermore, we observed that highly activated clones were less likely to be suppressed by OIT than less activated clones. Our work represents one of the most detailed transcriptomic profiles of T helper cells in food allergy. In the last part of the thesis, we leverage the simplicity and adaptability of the method to recover TCR sequences from previously processed scRNA-seq samples derived from HIV patients and a nonhuman primate model of TB. In the HIV study, we recovered expanded clonotypes associated with activated T cells from longitudinal samples from patients with acute HIV infections. In the TB study, we modified the primers used in the method to T cells from TB granulomas of cynomolgus macaques.</Abstract>
<Abstract>We identified not only expanded clonotypes associated with cytotoxic functions, but also clonotypes shared by clusters of activated T cells. In total, these results demonstrate the utility of our method when studying diseases in which clonotype-driven responses are critical to understanding the underlying biology.</Abstract>
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