Antibodies are essential molecules that help to provide immunity against a vast
population of environmental pathogens. This antibody conferred protection is dependent
upon genetic diversification mechanisms that produce an impressive repertoire of
lymphocytes expressing unique B-cell receptors. The advent of high throughput
sequencing has enabled researchers to sequence populations of B-cell receptors at an
unprecedented depth. Such investigations can be used to expand our understanding of
mechanistic processes governing adaptive immunity, characterization of immunity related
disorders, and the discovery of antibodies specific to antigens of interest. However, next
generation sequencing of immunological repertoires is not without its challenges. For
example, it is especially difficult to identify biologically relevant features within large
datasets. Additionally, within the immunology community, there is a severe lack of
standardized and easily accessible bioinformatics analysis pipelines. In this work, we
present methods which address many of these concerns. First, we present robust statistical
methods for the comparison of immunoglobulin repertoires. Specifically, we quantified
the overlap between the antibody heavy chain variable domain (V H ) repertoire of antibody
secreting plasma cells isolated from the bone marrow, lymph nodes, and spleen lymphoid
tissues of immunized mice. Statistical analysis showed significantly more overlap between
the bone marrow and spleen VH repertoires as compared to the lymph node repertoires.
Moreover, we identified and synthesized antigen-specific antibodies from the repertoire of
a mouse that showed a convergence of highly frequent VH sequences in all three tissues.
Second, we introduce a novel algorithm for the rapid and accurate alignment of VH
sequences to their respective germline genes. Our tests show that gene assignments
reported from this algorithm were more than 99% identical to assignments determined
using the well-validated IMGT software, and yet the algorithm is five times faster than an
IgBlast based analysis. Finally, in an effort to introduce methods for the standardization,
transparency, and replication of future repertoire studies, we have built a cloud-based
pipeline of bioinformatics tools specific to immunoglobulin repertoire studies. These tools
provide solutions for data curation and long-term storage of immunological sequencing
data in a database, annotation of sequences with biologically relevant features, and analysis
of repertoire experiments. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/30450 |
| Date | 26 August 2015 |
| Creators | Chrysostomou, Constantine |
| Contributors | Georgiou, George |
| Source Sets | University of Texas |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
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