Decoding cellular diversity in complex biological systems

Biological processes are inherently dynamic, complex and exhibit cell-to-cell variation. It is this variation, in multiple levels of cellular information that arises in either or both regulated and stochastic manners that allows multi-cellular organisms like us to function as a system. However, the philosophy of science historically has applied reductionist frames of thinking and therefore experimentation to model an organism as the sum of its parts. With modern develop- ments to scientific technologies and techniques, we now have the ability to ask broad as well as deep questions about biological processes. This systems biology approach pays homage to the fact that multiple levels of control exist and are interconnected and interacting simultaneously. We have barely scratched the surface of capturing the true variation present in nature, but perhaps this is an optimistic direction to discover more fascinating biological complexities and adaptations at play. At the heart of understanding cell-to-cell variation are technologies that capture information at single cell resolution. With the emergence of multiplexed, single cell technologies such as mass cytometry (CyTOF) and multiplexed ion beam imaging (MIBI-TOF), one can identify high- dimensional cell states at high throughput in both single cell suspensions and in solid tissue. This allows us to study complex biological processes at high resolution and with a systems biology approach. This thesis chronicles a journey in novel applications of these technologies to capture different levels of cellular information to better understand biological phenomenon such as drug resistance and hematopoiesis. The first part of the thesis examines cell-to-cell variation in apoptotic induction and non-canonical signaling response to recombinant TRAIL (TNF-related apoptosis-inducing ligand) protein as a cancer therapeutic. Historically drug resistance is thought to have arisen from a pre-existing subset of cells harboring genetic aberrations that confer resistance. But work in the past decade has shown that drug resistance is much more complex and involves non-genetic traits which are induced rather than selected for. We explore this key intersectionality between non-genetic mechanisms of resistance and response to recombinant TRAIL ligand to deduce conserved mechanisms across cancer types -- by capturing high-dimensional signaling states, apoptotic, cell cycle states as well as translation rates of single cells across 10 cell lines. We show that different cancers respond differently to TRAIL treatment, however the variation in signaling response to TRAIL corresponds to level of resistance to apoptotic induction. Cellular variation is a biological adaptation to TRAIL that is likely hijacked in cancer, yet variation alone does not explain this non-genetic TRAIL resistance phenomenon. We hypothesize that epigenetic mechanisms are also likely playing a role in driving resistance that is sustained through cell division -- where heritable traits are conferred through chemical modifications of DNA and associated histone proteins, and sustained chromatin structure. However, a large gap in knowledge is how these epigenetic factors, taken together drive a chromatin structure that interplays with various facets of cellular signaling to influence development, adult cellular differentiation, homeostasis, and the loss of it in disease. Unfortunately, we currently lack the single cell tools to link key phenotypic readouts that are encoded by proteomic levels such as signaling proteins in the case of response to TRAIL, to epigenetic states. The second part of this thesis introduces our novel functional epigenetics toolkit that comprises of Chromotyping (single cell chromatin content capture) on CyTOF and MIBI-TOF as well as a modified ATAC sequencing technique, InTAC seq that captures chromatin accessibility pro- files of fixed, permeabilized and intracellular factor-sorted cells at live-cell ATAC data quality. This toolkit allows us to capture multiplexed epigenetic states of single cells along with information on cell identity and function simultaneously in complex, dynamic biological processes. We are able to, for the first time, create detailed epigenetic trajectories that align with known phenotypic trajectories to identify key epigenetic transitions. We are then able to link our identified epigenetic transitions to its chromatin accessibility landscape and deduce the major DNA- binding factors at play using InTAC seq. We apply our functional epigenetic toolkit to biological processes such as the cell cycle and hematopoiesis in order to delineate novel epigenetic transitions and their associated regulome. The final section looks to better understand the specific link between protein level abundance and the associated regulome of DNA-binding factors. We use our InTAC seq technique to examine populations of cells with varying levels of key transcription factor, GATA1. In both the K562 cell line and in bone marrow, we see a distinct dose-dependent relationship between factor abundance and chromatin occupancy. This work sets the stage to better understand the important link between the epigenetic and phenotypic states of a cell. Cell-to-cell variation exists at multiple levels of cellular functioning, including at the chromatin structure level and we need to study it as a system in order to better understand what drives key phenotypic states and transitions in development and disease. This thesis details novel experimental and computational techniques to capture and understand variation in the epigenome, signaling landscape, and phenotype of single cells

Advisor: Bendall Sean
Greenleaf William James
Mallick Parag
Nolan Garry P.