THESIS
2021
1 online resource (xvii, 223 pages) : illustrations (some color)
Abstract
Vaccination is arguably the most successful medical intervention against infectious diseases,
yet some infectious viruses remain elusive. Rapid advancement in genetic sequencing
technologies and immunological experiments are enabling rational designs of
vaccines. Such next-generation vaccines can train the immune system to target specific
fragments of the virus while avoiding others.
This thesis leverages data science approaches to guide the design of vaccines by identifying
those specific fragments that the immune system of a diverse population can effectively
target for three infectious viruses: human immunodeficiency virus (HIV), dengue
virus, and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2, which is the
cause of COVID-19). Due to the underlying biology, these viruse...[
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Vaccination is arguably the most successful medical intervention against infectious diseases,
yet some infectious viruses remain elusive. Rapid advancement in genetic sequencing
technologies and immunological experiments are enabling rational designs of
vaccines. Such next-generation vaccines can train the immune system to target specific
fragments of the virus while avoiding others.
This thesis leverages data science approaches to guide the design of vaccines by identifying
those specific fragments that the immune system of a diverse population can effectively
target for three infectious viruses: human immunodeficiency virus (HIV), dengue
virus, and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2, which is the
cause of COVID-19). Due to the underlying biology, these viruses pose unique challenges
to identifying the effective immune targets, therefore, by aggregating various
types of data and developing and adapting different computational methods, we attempted
to mitigate these challenges.
First, we improved the identification of an evolutionarily constrained region within an
immunogenic protein of HIV, by principally modifying a spectral decomposition-based
sectoring method that has been used to reveal mutational patterns in HIV. This work
informs effective immunogen design for use in HIV vaccines. Second, we identified a
set of vaccine targets that are potentially robust against multiple circulating subtypes of the dengue virus by performing a comprehensive conservation analysis. Third, for
SARS-CoV-2, we leveraged available data for the genetically similar SARS coronavirus
to provide specific recommendations for immunological experiments and vaccine design.
We developed a web-based platform that regularly monitors new data as the COVID-19 pandemic progresses and updates these recommendations. Moreover, we described
the emerging landscape of T cell immune targets by compiling and analyzing SARS-CoV-2-specific data from multiple immunological studies and complemented this with
an online platform. Lastly, we reviewed and compared the performance of computational
methods that predict T cell targets and have assisted experimental studies on
SARS-CoV-2.
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