Epigenetic regulation in neural crest development : role of DNA methyltransferases 3A and 3B

The neural crest is a group of migratory, multipotent stem cells that play a crucial role in many aspects of embryonic development. This uniquely vertebrate cell population forms within the dorsal neural tube but then emigrates out and migrates long distances to different regions of the body. These cells contribute to formation of many structures such as the peripheral nervous system, craniofacial skeleton, and pigmentation of the skin. Why some neural tube cells undergo a change from neural to neural crest cell fate is unknown as is the timing of both onset and cessation of their emigration from the neural tube. In recent years, growing evidence supports an important role for epigenetic regulation as a new mechanism for controlling aspects of neural crest development. In this thesis, I dissect the roles of the de novo DNA methyltransferases (DNMTs) 3A and 3B in neural crest specification, migration and differentiation. First, I show that DNMT3A limits the spatial boundary between neural crest versus neural tube progenitors within the neuroepithelium. DNMT3A promotes neural crest specification by directly mediating repression of neural genes, like Sox2 and Sox3. Its knockdown causes ectopic Sox2 and Sox3 expression at the expense of neural crest territory. Thus, DNMT3A functions as a molecular switch, repressing neural to favor neural crest cell fate. Second, I find that DNMT3B restricts the temporal window during which the neural crest cells emigrate from the dorsal neural tube. Knockdown of DNMT3B causes an excess of neural crest emigration, by extending the time that the neural tube is competent to generate emigrating neural crest cells. In older embryos, this resulted in premature neuronal differentiation. Thus, DNMT3B regulates the duration of neural crest production by the neural tube and the timing of their differentiation. My results in avian embryos suggest that de novo DNA methylation, exerted by both DNMT3A and DNMT3B, plays a dual role in neural crest development, with each individual paralogue apparently functioning during a distinct temporal window. The results suggest that de novo DNA methylation is a critical epigenetic mark used for cell fate restriction of progenitor cells during neural crest cell fate specification. Our discovery provides important insights into the mechanisms that determine whether a cell becomes part of the central nervous system or peripheral cell lineages.

Targeting DNA repeat sequences with Py-Im polyamides

Hairpin pyrrole-imdazole polyamides are cell-permeable, sequence-programmable oligomers that bind in the minor groove of DNA. This thesis describes studies of Py-Im polyamides targeted to biologically important DNA repeat sequences for the purpose of modulating disease states. Design of a hairpin polyamide that binds the CG dyad, a site of DNA methylation that can become dysregulated in cancer, is described. We report the synthesis of a DNA methylation antagonist, its sequence specificity and affinity informed by Bind-n-Seq and iteratively designed, which improves inhibitory activity in a cell-free assay by 1000-fold to low nanomolar IC50. Additionally, a hairpin polyamide targeted to the telomeric sequence is found to trigger a slow necrotic-type cell death with the release of inflammatory molecules in a model of B cell lymphoma. The effects of the polyamide are unique in this class of oligomers; its effects are characterized and a functional assay of phagocytosis by macrophages is described. Additionally, hairpin polyamides targeted to pathologically expanded CTG•CAG triplet repeat DNA sequences, the molecular cause of myotonic dystrophy type 1, are synthesized and assessed for toxicity. Lastly, ChIP-seq of Hypoxia-Inducible Factor is performed under hypoxia-induced conditions. The study results show that ChIP-seq can be employed to understand the genome-wide perturbation of Hypoxia-Inducible Factor occupancy by a Py-Im polyamide.

Metastability and dynamics of stem cells: from direct observations to inference at the single cell level

Organismal development, homeostasis, and pathology are rooted in inherently probabilistic events. From gene expression to cellular differentiation, rates and likelihoods shape the form and function of biology. Processes ranging from growth to cancer homeostasis to reprogramming of stem cells all require transitions between distinct phenotypic states, and these occur at defined rates. Therefore, measuring the fidelity and dynamics with which such transitions occur is central to understanding natural biological phenomena and is critical for therapeutic interventions.

While these processes may produce robust population-level behaviors, decisions are made by individual cells. In certain circumstances, these minuscule computing units effectively roll dice to determine their fate. And while the 'omics' era has provided vast amounts of data on what these populations are doing en masse, the behaviors of the underlying units of these processes get washed out in averages.

Therefore, in order to understand the behavior of a sample of cells, it is critical to reveal how its underlying components, or mixture of cells in distinct states, each contribute to the overall phenotype. As such, we must first define what states exist in the population, determine what controls the stability of these states, and measure in high dimensionality the dynamics with which these cells transition between states.

To address a specific example of this general problem, we investigate the heterogeneity and dynamics of mouse embryonic stem cells (mESCs). While a number of reports have identified particular genes in ES cells that switch between 'high' and 'low' metastable expression states in culture, it remains unclear how levels of many of these regulators combine to form states in transcriptional space. Using a method called single molecule mRNA fluorescent in situ hybridization (smFISH), we quantitatively measure and fit distributions of core pluripotency regulators in single cells, identifying a wide range of variabilities between genes, but each explained by a simple model of bursty transcription. From this data, we also observed that strongly bimodal genes appear to be co-expressed, effectively limiting the occupancy of transcriptional space to two primary states across genes studied here. However, these states also appear punctuated by the conditional expression of the most highly variable genes, potentially defining smaller substates of pluripotency.

Having defined the transcriptional states, we next asked what might control their stability or persistence. Surprisingly, we found that DNA methylation, a mark normally associated with irreversible developmental progression, was itself differentially regulated between these two primary states. Furthermore, both acute or chronic inhibition of DNA methyltransferase activity led to reduced heterogeneity among the population, suggesting that metastability can be modulated by this strong epigenetic mark.

Finally, because understanding the dynamics of state transitions is fundamental to a variety of biological problems, we sought to develop a high-throughput method for the identification of cellular trajectories without the need for cell-line engineering. We achieved this by combining cell-lineage information gathered from time-lapse microscopy with endpoint smFISH for measurements of final expression states. Applying a simple mathematical framework to these lineage-tree associated expression states enables the inference of dynamic transitions. We apply our novel approach in order to infer temporal sequences of events, quantitative switching rates, and network topology among a set of ESC states.

Taken together, we identify distinct expression states in ES cells, gain fundamental insight into how a strong epigenetic modifier enforces the stability of these states, and develop and apply a new method for the identification of cellular trajectories using scalable in situ readouts of cellular state.

DNA-Mediated Charge Transport Devices for Protein Detection

Detection of biologically relevant targets, including small molecules, proteins, DNA, and RNA, is vital for fundamental research as well as clinical diagnostics. Sensors with biological elements provide a natural foundation for such devices because of the inherent recognition capabilities of biomolecules. Electrochemical DNA platforms are simple, sensitive, and do not require complex target labeling or expensive instrumentation. Sensitivity and specificity are added to DNA electrochemical platforms when the physical properties of DNA are harnessed. The inherent structure of DNA, with its stacked core of aromatic bases, enables DNA to act as a wire via DNA-mediated charge transport (DNA CT). DNA CT is not only robust over long molecular distances of at least 34 nm, but is also especially sensitive to anything that perturbs proper base stacking, including DNA mismatches, lesions, or DNA-binding proteins that distort the π-stack. Electrochemical sensors based on DNA CT have previously been used for single-nucleotide polymorphism detection, hybridization assays, and DNA-binding protein detection. Here, improvements to (i) the structure of DNA monolayers and (ii) the signal amplification with DNA CT platforms for improved sensitivity and detection are described.

First, improvements to the control over DNA monolayer formation are reported through the incorporation of copper-free click chemistry into DNA monolayer assembly. As opposed to conventional film formation involving the self-assembly of thiolated DNA, copper-free click chemistry enables DNA to be tethered to a pre-formed mixed alkylthiol monolayer. The total amount of DNA in the final film is directly related to the amount of azide in the underlying alkylthiol monolayer. DNA monolayers formed with this technique are significantly more homogeneous and lower density, with a larger amount of individual helices exposed to the analyte solution. With these improved monolayers, significantly more sensitive detection of the transcription factor TATA binding protein (TBP) is achieved.

Using low-density DNA monolayers, two-electrode DNA arrays were designed and fabricated to enable the placement of multiple DNA sequences onto a single underlying electrode. To pattern DNA onto the primary electrode surface of these arrays, a copper precatalyst for click chemistry was electrochemically activated at the secondary electrode. The location of the secondary electrode relative to the primary electrode enabled the patterning of up to four sequences of DNA onto a single electrode surface. As opposed to conventional electrochemical readout from the primary, DNA-modified electrode, a secondary microelectrode, coupled with electrocatalytic signal amplification, enables more sensitive detection with spatial resolution on the DNA array electrode surface. Using this two-electrode platform, arrays have been formed that facilitate differentiation between well-matched and mismatched sequences, detection of transcription factors, and sequence-selective DNA hybridization, all with the incorporation of internal controls.

For effective clinical detection, the two working electrode platform was multiplexed to contain two complementary arrays, each with fifteen electrodes. This platform, coupled with low density DNA monolayers and electrocatalysis with readout from a secondary electrode, enabled even more sensitive detection from especially small volumes (4 μL per well). This multiplexed platform has enabled the simultaneous detection of two transcription factors, TBP and CopG, with surface dissociation constants comparable to their solution dissociation constants.

With the sensitivity and selectivity obtained from the multiplexed, two working electrode array, an electrochemical signal-on assay for activity of the human methyltransferase DNMT1 was incorporated. DNMT1 is the most abundant human methyltransferase, and its aberrant methylation has been linked to the development of cancer. However, current methods to monitor methyltransferase activity are either ineffective with crude samples or are impractical to develop for clinical applications due to a reliance on radioactivity. Electrochemical detection of methyltransferase activity, in contrast, circumvents these issues. The signal-on detection assay translates methylation events into electrochemical signals via a methylation-specific restriction enzyme. Using the two working electrode platform combined with this assay, DNMT1 activity from tumor and healthy adjacent tissue lysate were evaluated. Our electrochemical measurements revealed significant differences in methyltransferase activity between tumor tissue and healthy adjacent tissue.

As differential activity was observed between colorectal tumor tissue and healthy adjacent tissue, ten tumor sets were subsequently analyzed for DNMT1 activity both electrochemically and by tritium incorporation. These results were compared to expression levels of DNMT1, measured by qPCR, and total DNMT1 protein content, measured by Western blot. The only trend detected was that hyperactivity was observed in the tumor samples as compared to the healthy adjacent tissue when measured electrochemically. These advances in DNA CT-based platforms have propelled this class of sensors from the purely academic realm into the realm of clinically relevant detection.