From the Cover: Arsenite Uncouples Mitochondrial Respiration and Induces a Warburg-like Effect in Caenorhabditis elegans.

Millions of people worldwide are chronically exposed to arsenic through contaminated drinking water. Despite decades of research studying the carcinogenic potential of arsenic, the mechanisms by which arsenic causes cancer and other diseases remain poorly understood. Mitochondria appear to be an important target of arsenic toxicity. The trivalent arsenical, arsenite, can induce mitochondrial reactive oxygen species production, inhibit enzymes involved in energy metabolism, and induce aerobic glycolysis in vitro, suggesting that metabolic dysfunction may be important in arsenic-induced disease. Here, using the model organism Caenorhabditis elegans and a novel metabolic inhibition assay, we report an in vivo induction of aerobic glycolysis following arsenite exposure. Furthermore, arsenite exposure induced severe mitochondrial dysfunction, including altered pyruvate metabolism; reduced steady-state ATP levels, ATP-linked respiration and spare respiratory capacity; and increased proton leak. We also found evidence that induction of autophagy is an important protective response to arsenite exposure. Because these results demonstrate that mitochondria are an important in vivo target of arsenite toxicity, we hypothesized that deficiencies in mitochondrial electron transport chain genes, which cause mitochondrial disease in humans, would sensitize nematodes to arsenite. In agreement with this, nematodes deficient in electron transport chain complexes I, II, and III, but not ATP synthase, were sensitive to arsenite exposure, thus identifying a novel class of gene-environment interactions that warrant further investigation in the human populace.

Characterizing Genetic Drivers of Lymphoma through High-Throughput Sequencing

The advent of next-generation sequencing, now nearing a decade in age, has enabled, among other capabilities, measurement of genome-wide sequence features at unprecedented scale and resolution.

In this dissertation, I describe work to understand the genetic underpinnings of non-Hodgkin’s lymphoma through exploration of the epigenetics of its cell of origin, initial characterization and interpretation of driver mutations, and finally, a larger-scale, population-level study that incorporates mutation interpretation with clinical outcome.

In the first research chapter, I describe genomic characteristics of lymphomas through the lens of their cells of origin. Just as many other cancers, such as breast cancer or lung cancer, are categorized based on their cell of origin, lymphoma subtypes can be examined through the context of their normal B Cells of origin, Naïve, Germinal Center, and post-Germinal Center. By applying integrative analysis of the epigenetics of normal B Cells of origin through chromatin-immunoprecipitation sequencing, we find that differences in normal B Cell subtypes are reflected in the mutational landscapes of the cancers that arise from them, namely Mantle Cell, Burkitt, and Diffuse Large B-Cell Lymphoma.

In the next research chapter, I describe our first endeavor into understanding the genetic heterogeneity of Diffuse Large B Cell Lymphoma, the most common form of non-Hodgkin’s lymphoma, which affects 100,000 patients in the world. Through whole-genome sequencing of 1 case as well as whole-exome sequencing of 94 cases, we characterize the most recurrent genetic features of DLBCL and lay the groundwork for a larger study.

In the last research chapter, I describe work to characterize and interpret the whole exomes of 1001 cases of DLBCL in the largest single-cancer study to date. This highly-powered study enabled sub-gene, gene-level, and gene-network level understanding of driver mutations within DLBCL. Moreover, matched genomic and clinical data enabled the connection of these driver mutations to clinical features such as treatment response or overall survival. As sequencing costs continue to drop, whole-exome sequencing will become a routine clinical assay, and another diagnostic dimension in addition to existing methods such as histology. However, to unlock the full utility of sequencing data, we must be able to interpret it. This study undertakes a first step in developing the understanding necessary to uncover the genomic signals of DLBCL hidden within its exomes. However, beyond the scope of this one disease, the experimental and analytical methods can be readily applied to other cancer sequencing studies.

Thus, this dissertation leverages next-generation sequencing analysis to understand the genetic underpinnings of lymphoma, both by examining its normal cells of origin as well as through a large-scale study to sensitively identify recurrently mutated genes and their relationship to clinical outcome.

Roles of CTCF and YY1 in T Cell Receptor Gene Rearrangement And T Cell Development

Diversity of T cell receptors (TCR) and immunoglobulins (Ig) is generated by V(D)J recombination of antigen receptor (AgR) loci. The Tcra-Tcrd locus is of particular interest because it displays a nested organization of Tcrd and Tcra gene segments and V(D)J recombination follows an intricate developmental program to assemble both TCRδ and TCRα repertoires. However, the mechanisms that dictate the developmental regulation of V(D)J recombination of the Tcra-Tcrd locus remain unclear.

We have previously shown that CCCTC-binding factor (CTCF) regulates Tcra gene transcription and rearrangement through organizing chromatin looping between CTCF- binding elements (CBEs). This study is one of many showing that CTCF functions as a chromatin organizer and transcriptional regulator genome-wide. However, detailed understanding of the impact of specific CBEs is needed to fully comprehend the biological function of CTCF and how CTCF influences the generation of the TCR repertoire during thymocyte development. Thus, we generated several mouse models with genetically modified CBEs to gain insight into the CTCF-dependent regulation of the Tcra-Tcrd locus. We revealed a CTCF-dependent chromatin interaction network at the Tcra-Tcrd locus in double-negative thymocytes. Disruption of a discrete chromatin loop encompassing Dδ, Jδ and Cδ gene segments allowed a single Vδ segment to frequently contact and rearrange to diversity and joining gene segments and dominate the adult TCRδ repertoire. Disruption of this loop also narrowed the TCRα repertoire, which, we believe, followed as a consequence of the restricted TCRδ repertoire. Hence, a single CTCF-mediated chromatin loop directly regulates TCRδ diversity and indirectly regulates TCRα diversity. In addition, we showed that insertion of an ectopic CBE can modify chromatin interactions and disrupt the rearrangement of particular Vδ gene segments. Finally, we investigated the role of YY1 in early T cell development by conditionally deleting YY1 in developing thymocytes. We found that early ablation of YY1 caused severe developmental defects in the DN compartment due to a dramatic increase in DN thymocyte apoptosis. Furthermore, late ablation of YY1 resulted in increased apoptosis of DP thymocytes and a restricted TCRα repertoire. Mechanistically, we showed that p53 was upregulated in both DN and DP YY1-deficient thymocytes. Eliminating p53 in YY1-deficient thymocytes rescued the survival and developmental defects, indicating that these YY1-dependent defects were p53-mediated. We conclude that YY1 is required to maintain cell viability during thymocyte development by thwarting the accumulation of p53.

Overall, this thesis work has shown that CTCF-dependent looping provides a central framework for lineage- and developmental stage-specific regulation of Tcra-Tcrd gene expression and rearrangements. In addition, we identified YY1 as a novel regulator of thymocyte viability.

Punctuated evolution and transitional hybrid network in an ancestral cell cycle of fungi

© Medina et al.Although cell cycle control is an ancient, conserved, and essential process, some core animal and fungal cell cycle regulators share no more sequence identity than non-homologous proteins. Here, we show that evolution along the fungal lineage was punctuated by the early acquisition and entrainment of the SBF transcription factor through horizontal gene transfer. Cell cycle evolution in the fungal ancestor then proceeded through a hybrid network containing both SBF and its ancestral animal counterpart E2F, which is still maintained in many basal fungi. We hypothesize that a virally-derived SBF may have initially hijacked cell cycle control by activating transcription via the cis-regulatory elements targeted by the ancestral cell cycle regulator E2F, much like extant viral oncogenes. Consistent with this hypothesis, we show that SBF can regulate promoters with E2F binding sites in budding yeast.

Quantifying Eukaryotic Gene Regulation in Hormone Response and Disease.

Quantifying the function of mammalian enhancers at the genome or population scale has been longstanding challenge in the field of gene regulation. Studies of individual enhancers have provided anecdotal evidence on which many foundational assumptions in the field are based. Genome-scale studies have revealed that the number of sites bound by a given transcription factor far outnumber the genes that the factor regulates. In this dissertation we describe a new method, chromatin immune-enriched reporter assays (ChIP-reporters), and use that approach to comprehensively test the enhancer activity of genomic loci bound by the glucocorticoid receptor (GR). Integrative genomics analyses of our ChIP-reporter data revealed an unexpected mechanism of glucocorticoid (GC)-induced gene regulation. In that mechanism, only the minority of GR bound sites acts as GC-inducible enhancers. Many non-GC-inducible GR binding sites interact with GC-induced sites via chromatin looping. These interactions can increase the activity of GC-induced enhancers. Finally, we describe a method that enables the detection and characterization of the functional effects of non-coding genetic variation on enhancer activity at the population scale. Taken together, these studies yield both mechanistic and genetic evidence that provides context that informs the understanding of the effects of multiple enhancer variants on gene expression.

A Molecular-scale Programmable Stochastic Process Based On Resonance Energy Transfer Networks: Modeling And Applications

While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.

In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.

By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.

Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.

Biochemical Characterization of Human Exonuclease 1 Protein-protein Interactions

Human Exonuclease 1 (Exo1) plays important roles in numerous DNA metabolic/repair pathways including DNA mismatch repair, DNA double strand break repair, Okazaki fragment maturation etc. The nuclease activity of Exo1 is tightly regulated in vivo. The regulation of Exo1 in different pathways is achieved by interactions with different protein partners. The focus of this dissertation will be on characterization of Exo1 interactions with traditional protein partners and providing experimental evidences for new Exo1 interactions.

Molecular cloning, biochemical assays, collaborative nuclear magnetic resonance and X-ray crystallography have been employed to study Exo1 interactions with protein partners. This work contains: (i) the experimental evidence for new Exo1 interactions, and (ii) the detailed characterization of Exo1 interactions with PCNA, MLH1 and MutSα/β.

Taken together, the research progress presented in this dissertation further advances our understanding of traditional Exo1 interaction network and probably provides new insights to new functions and new regulations of Exo1.