Understanding adaptive immunity using immune receptor repertoire sequencing
dc.contributor.advisor
Cowan, Graeme
dc.contributor.advisor
Gray, Mohini
dc.contributor.advisor
Simpson, Ian
dc.contributor.author
Sutherland, Catherine
dc.date.accessioned
2023-12-21T14:28:08Z
dc.date.available
2023-12-21T14:28:08Z
dc.date.issued
2023-12-21
dc.description.abstract
Adaptive Immune Receptor Repertoire Sequencing (AIRR-seq) uses high
throughput sequencing to characterise the state and dynamics of B and T cell
receptor (BCR and TCR) repertoires. In this thesis, I utilise this technique both
in bulk and at the single cell level to explore adaptive immune cell populations.
I also document development of a simulation tool that facilitates
benchmarking of AIRR-seq analysis pipelines.
Firstly, TCR repertoire sequencing was used to characterise Epstein-Barr
Virus (EBV)-specific T cell products from the Scottish National Blood
Transfusion Service. These cells are used to treat reactivation of latent EBV in
immunosuppressed individuals, and a new manufacturing method is under
development. Both next generation and current products were sequenced
and found to be oligoclonal. There was substantial variation across all
samples, with some being highly enriched for TCR sequences previously
determined to be EBV-specific. No significant effect of manufacturing
technique was found. Products targeted against SARS-CoV2, generated in
the same manner, showed less restricted diversity and less enrichment for
previously identified virus-specific sequences than the EBV samples. This
work provides detail on these clinically important T cells, indicates that the
repertoires of cells in the next generation EBV bank are not dissimilar to those
currently used in treatment, and shows that virus specific products targeting
different viruses have altered repertoire characteristics.
In the second chapter, I establish the source of a previously identified
“hypomutated” IgG signature in rheumatoid arthritis (RA) by integrating single
cell whole transcriptome and BCR sequencing. I found that no individual
blood B cell population was enriched for sequences with few mutations in RA.
However, differential gene expression analysis revealed altered expression of
a small number of genes in cells with hypomutated BCR sequences. A similar
gene expression signature was observed in the RA synovium, where BCRs
with low levels of mutation were also found across all identified B cell subsets.
This suggests a widespread phenomenon of reduced somatic hypermutation
in B cells from RA patients, rather than the presence of a single pathogenic
hypomutated population that could be targeted for treatment.
Finally, I developed AIRRSHIP, a flexible and fast Python package that
produces synthetic human B cell receptor sequences. Work to assess the
reliability of the numerous tools developed to analyse the complex data
produced by AIRR-seq experiments is sorely needed. Benchmarking of this
kind is dependent on the ability to produce high quality simulated datasets
with known ground truth. AIRRSHIP produces such datasets by using a
comprehensive set of reference data to replicate key mechanisms in the
immunoglobulin recombination process. The resulting repertoires are highly
similar to experimental data and can be used to determine the accuracy of
tools that process BCR sequences. By enabling thorough, systematic
assessment of their performance, AIRRSHIP will allow more informed
decisions on tool use to be made, and for error rates to be accounted for in
analysis.
Overall, this thesis uses AIRR-seq to aid understanding of the adaptive immune
response in differing situations and illustrates its potential to inform treatment
of human disease. It also details a simulation tool that can be used to improve
and advance methodologies for AIRR-seq analyses.
en
dc.identifier.uri
https://hdl.handle.net/1842/41308
dc.identifier.uri
http://dx.doi.org/10.7488/era/4043
dc.language.iso
en
en
dc.publisher
The University of Edinburgh
en
dc.relation.hasversion
Bioinformatics: Catherine Sutherland and Graeme J M Cowan, AIRRSHIP: simulating human B cell receptor repertoire sequences, Bioinformatics, Volume 39, Issue 6, June 2023, btad365, https://doi.org/10.1093/bioinformatics/btad365
en
dc.rights.embargodate
2027-01-14
en
dc.subject
AIRR-seq
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dc.subject
Repertoire sequencing
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dc.subject
Epstein-Barr virus
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dc.subject
T cells
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dc.subject
clonotypes
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dc.subject
B cells
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dc.subject
rheumatoid arthritis
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dc.subject
synovium
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dc.subject
AIRRSHIP
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dc.subject
synthetic human BCR sequences
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dc.title
Understanding adaptive immunity using immune receptor repertoire sequencing
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dc.type
Thesis or Dissertation
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dc.type.qualificationlevel
Doctoral
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dc.type.qualificationname
PhD Doctor of Philosophy
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dcterms.accessRights
RESTRICTED ACCESS
en
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