Single-Cell Analysis of Dynamic Cell Transitions in Atherosclerosis

Cellular transitions play crucial roles in the development of numerous diseases,
including the top two leading causes of death: heart disease and cancer. Here, I present
work to advance understanding of cellular transitions: FLOW-MAP, a computational
analysis tool for single-cell data tailored to time course data; high-resolution mass
cytometry studies of atherosclerosis at multiple stages of disease progression; and a
multiplexed lineage tracing tool to study complex molecular histories of cells.
FLOW-MAP is a graph-building tool that is unique in using time point information
to constrain graph building and limit spurious graph connections. In chapter 2, I present
validation of this tool using synthetic and biological datasets, including a single-cell RNA
sequencing dataset. FLOW-MAP’s inclusion of time point information improves
resolution of cells in 2D.
In chapters 3-5, I present mass cytometry studies of blood vessels with varying
degrees of disease progression towards atherosclerosis. I developed and applied
high-resolution mass cytometry panels, capturing cellular transitions at each timepoint
to understand the critical cell changes at each disease stage.
Lastly, I present progress towards a multiplexed lineage tracing tool in chapter 6.
Our understanding of cellular transitions is usually limited to inference from snapshot
data or from in vitro data subject to limitations of context dependence. With a
multiplexed lineage tracing tool, complex, multi-gene intermediates will be able to be
studied with greater confidence.
Together this work advances the ability of researchers to study cellular
transitions, and each study also provides biological insight into its specific application.