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The Role of Stellar Feedback in Star Cluster Formation
Get PDFA methodology for numerical magnetohydrodynamics simulations of star cluster formation, accounting for all mechanisms of stellar feedback from massive stars, is developed and used to address a range of problems regarding the formation of stars and star clusters in giant molecular clouds (GMCs). These studies culminate in a new theoretical framework that connects properties of GMCs to those of the star clusters that form in them.
The simulation methodology is established and tested, and the problem of the star formation efficiency (SFE) of molecular clouds is addressed. It is found that SFE is set by the balance of feedback and gravity, with very weak dependence upon other factors. A simple dimensional scaling law with cloud surface density emerges from the complex interplay of different feedback physics. Parameter space is found where feedback must fail, and the SFE is high, and the implications of this prediction are explored.
The star clusters formed in the simulations are found to resemble observed young, massive star clusters in the form of their surface brightness profiles, leading to the hypothesis that this structure is a result of the star formation process. It is shown that the shallow, power-law density profiles characteristic of young clusters is predicted by the hierarchical star formation scenario. It is shown that the SFE law, when coupled to an analytic cloud collapse model, predicts that gas should be exhausted by highly-efficient star formation at a stellar surface density of ∼ 105 − 106 Msun pc-2, consistent with the maximum observed.
A new suite of simulations is developed to specifically model GMCs in the Milky Way. It is found that the picture of feedback-disrupted star formation is able to account for both the normalization and the scatter in the measured SFE of GMCs in the Milky Way, the first theory to do so.
The uncertainty in the simulated SFE due to the choice of feedback prescription is quantified, by running a controlled methods study of several different prescriptions in the literature. In the cloud model simulated, the choice of prescription affects the simulated SFE at the factor of ∼ 3 level, explaining discrepancies in the literature and identifying the small-scale details of massive star formation as the main uncertainty in cluster formation simulations.
Finally, the simulation suite is extended to model massive GMCs in local spiral galaxies, and to simulate 10 random realizations at each point in parameter space, mapping out the stochastic nature of star cluster formation in GMCs. A model is calibrated to the simulation results, taking the cloud bulk properties as input parameters, and predicting the detailed properties of the star clusters formed in it. A star cluster catalogue is synthesized from observed GMCs in M83, and good agreement is found with observed star cluster properties, including the fraction of stars in bound clusters, the maximum cluster mass, and the distribution of cluster sizes.</p
Highly Multiplexed Imaging of E. Coli Chromosome and Sensitive Detection of Single-Cell Protein
Get PDFThe driving force for biology research is the development of new techniques which allow high-sensitivity, high-throughput measurement in various contexts. Over the past decade, the emerging of a variety of single-cell techniques have greatly transformed our understanding of biological system. My thesis work was therefore focused on development of new single- cell techniques and use the techniques to generate new insights into biological system. Specifically, in the first part of my thesis work, we developed DNA seqFISH, a technique that allows us to image more than 100 different loci on the chromosome in single cells. We applied this technique to image E. coli chromosome with 50kb genomic resolution and 50nm spatial precision. Our data allows us to parse the E. coli chromosome structure according to their different spatial conformations and different cell-cycle stages. We identified two chromosome conformations with distinct domain structures, which is obscured from previous population-average research. We further characterized the domain structure dynamics during daughter chromosome segregation. Therefore, our data provides a high- resolution, dynamic view of E. coli chromosome structure.
In the second part, we developed a novel method for sensitive detection of targeted protein and its post-translational modification (PTM) isoform in single cells. Instead of depending on antibodies to distinguish targeted protein and its PTM isoform, we developed an efficient covalent barcoding strategy to barcode targeted protein inside the cells. Thereafter, targeted protein and its PTM isoform are separated by conventional gel electrophoresis, while their single-cell identity is preserved in the covalently attached oligo. By counting the attached DNA oligos using next-generation sequencing, targeted protein, and its PTM isoform can be accurately measured. We demonstrated the utility of the technology by quantification of histone protein, H2B and its mono-ubiquitination isoform, H2Bub at single-cell level. Our method revealed the single-cell heterogeneities of H2Bub/H2B ratio and its cell-cycle dynamics. Our method therefore provides an antibody-free method for sensitive detection of proteins and its isoforms in single cells.</p
Control of Aggregated Bacterial Communities through Engineered Surface Displayed Proteins
Get PDFBacterial aggregation through surface display of cross-associating proteins has previously been demonstrated, but the formation of these aggregates is only controllable and reversible through the addition of chemical inducers or soluble proteins. Here, we present a design for a photoswitchable surface-display system that causes bacterial aggregation. This system should reversibly disaggregate under exposure to blue light. We created our mutant by modifying Photoactive Yellow Protein (PYP), a fluorescent protein that undergoes a large reversible conformational change when exposed to blue light. We computationally designed this mutant to drive photoswitchable sequestration of a cap domain that is designed to selectively aggregate with SynZip18. Characterization of this designed protein's photoactivity was inconclusive due to its limited solubility though the synthesized chormophore, a p-coumaric acid derivative, was capable of reconstituting native photoactive PYP. While we did not show that the designed mutant could cause disaggregation under exposure to blue light, it was capable of selectively aggregating with surface displayed SynZip18 as desired.</p
Town Meeting: A Representative but Non-Sovereign Institution
Get PDFQuestions of democracy are fundamental for modern society. One of the main distinctions made in the study of democracy is between direct and representative democracy. While most democratic institutions today are representative, the roots of democracy lie in direct democracy, a system in which citizens vote directly on the issues rather than on candidates who will then make the decisions. One of the most historically significant institutions in the area of direct democracy, especially in the American tradition, is the town meeting. Unfortunately, most of the discussion on the town meeting has focused on the question of representation (for example attendance rates at meetings) resulting in a substitution of a broad discussion on democracy with a narrow discussion on representation. The aim of this thesis is not only to illustrate this issue, but also to indicate how the addition of another axis of analysis, power-external/sovereignty, can untangle some of the confusing aspects of the existing narratives regarding the town meeting. The thesis draws upon a variety of documents, such as 17th century town meeting records, the writings of Thomas Jefferson, a 20th century radio show, and present day news articles, in order to aid in the reconceptualization of core issues such as power and representation, as well as to provide new insights in topics such as the use of direct democracy for purposes of political education. The hope is to inspire more advances in our understanding of the limitations and shortcomings of our current framework of analysis for the town meeting, as well as to introduce different perspectives of analysis which, in combination with representation and power, can provide a more holistic understanding of the town meeting institution.</p
Landau Damping Induced Limits in Nanogap Metal-Insulator-Metal Plasmonic Waveguides and Cavities
Get PDFPlasmonic structures permit the focusing of light into volumes far below the diffraction limit. In particular Metal-Insulator-Metal (MIM) gap plasmonic structures can reach nanoscale energy confinement if the gap is sufficiently miniaturized. Under classical models, gap plasmonics can achieve indefinite confinement, down to the single atom level. However, these classical models fail to consider quantum effects that occur as the confinement approaches the single nanometer level. Recently, it has been demonstrated that Landau Damping, the absorption of highly confined plasmonic energy, is the dominant effect in highly confined MIM devices until the tunneling regime is reached. However, the effects of Landau Damping on MIM gap devices are poorly understood. In this work, we analyze the effects of Landau Damping on MIM gap devices, specifically MIM waveguides and cavities. It is found that in waveguides, Landau Damping does not limit the confinement but does limit the maximum propagation length achievable. Moreover, in cavity structures, Landau Damping causes the Quality Factor to drop significantly as the gap is further miniaturized. In terms of quantum optics applications, this causes the radiative spontaneous emission enhancement to actually decrease as the gap is miniaturized sufficiently and a saturation of the coupling-loss ratio limiting the achievement of strong coupling. These effects will limit the possibilities for high performance nanogap plasmonic devices.</p
Conformations and Charge Fluctuations in Polyelectrolyte Solutions
Get PDFFrom DNA and RNA encoding life to flocculation agents used in water remediation, charged polymers (polyelectrolytes) are prevalent in nearly all facets of our lives. The charged nature of polyelectrolytes has rendered them useful in many applications, from the stabilization of colloids to the formation of nanoparticles for drug or gene delivery. There are open questions regarding the factors that dictate polyelectrolyte stability, and electrostatic fluctuations, first elucidated by Debye and Hückel for simple electrolytes, are key to the thermodynamic description of such charged systems. Electrostatic fluctuations lead to ionic clouds around charges, leading to favorable energy decreases. While charge-fluctuations are well-described for simple electrolytes, the impact of polyelectrolyte (PE) charge connectivity on charge fluctuations is much less well understood: a huge number of degrees of freedom must be considered in order to describe the multicomponent nature of polyelectrolyte solutions and the large number of conformations the polyelectrolytes themselves can assume. Past theories have both under- and over-estimated the connectivity effects on electrostatic fluctuations, and do not give a clear picture of the transition from weak to strong electrostatic fluctuations.
My work has focused on coming up with a theory that self-consistently accounts for the coupling of chain connectivity and electrostatic fluctuations, thus spanning electrostatic fluctuations from weak to intermediate fluctuation strengths. In particular, I present a novel renormalized Gaussian fluctuation (RGF) theory that identifies the renormalization of chain structure as a key physical consequence of intermediate-strength electrostatic fluctuations. The theory self-consistently couples chain structure with the thermodynamics, and mediates the transition from weak, linearized fluctuations to the onset of stronger fluctuation effects like ion pairing. While the onset of these different fluctuation effects has a clear sequence, they are all coupled and must be determined self-consistently. A key concept introduced by the theory is the notion of the polyelectrolyte self energy, which describes the electrostatic work required to charge the molecule in solution, and provides a useful perspective from which to understand and rationalize the effects of chain conformation on thermodynamic behavior. We use the theory to study the phase behavior of polyelectrolyte solutions and connect theory to experimental results.</p
Microbial Modulation of Host Locomotion
Get PDFCoordinated locomotor behavior is critical for the survival and propagation of an individual and is modulated by internal and external sensory inputs. The microbiota regulates host metabolism, which is closely intertwined with motor behavior. However, little is known regarding influences by the gut microbiome on host locomotion, or the pathways involved. The work presented in this thesis examines microbial regulation of locomotor behavior from both bacterial and host perspectives. Removal of the microbiota results in hyperactivity in female D. melanogaster, which is reversible through colonization with specific bacteria or administration of bacterial-derived products, including xylose isomerase (Xi) from Lactobacillus brevis. We found that Xi modulates host speed via sugar metabolism and octopamine signaling in flies. Additionally, aspects of microbial regulation of host locomotion appear to be conserved in mice. This work suggests that microbial modulation of host physiology extends beyond local intestinal effects to locomotor behavior through alterations in energy-related pathways
Synthetic Strategies for the Total Synthesis of the Ryanoid and Isoryanoid Diterpenes
Get PDFHighly oxygenated, polycyclic terpenoids provide a rich source of biologically active natural products, yet the translation of their activity to lead candidate analogs and useful biological probes requires concise solutions to address, at once, accessibility and diversification. This dissertation will disclose our efforts to bridge that gap through the development of synthetic strategies for the total synthesis of the ryanoid and isoryanoid diterpenes. The studies herein will address the strategy and logic that rendered the success of a challenging C3 acylation to directly incorporate a pyrrole-2-carboxylate ester, ultimately resulting in an 18-step total synthesis of (+)-ryanodine. The versatility of the route was demonstrated by the preparation of the related ryanoid diterpene (+)-20-deoxyspiganthine. Enabling the success of both syntheses was the development of robust conditions to induce late-stage reductive ring closure and forge the C1–C15 bond.
The lessons learned from these synthetic efforts drew us thereafter to the complex, polycyclic structure of the isoryanoid diterpene (+)-perseanol. The evaluation of several different approaches culminated in the discovery of a successful fragment coupling approach, hinging on a 2-step sequence involving (1) 1,2-addition to induce convergent union of two fragments of equal complexity and (2) Heck-Stille cyclization/cross-coupling cascade to complete the preparation of the ABC tricyclic core. Emphasis will be placed on the strategic use of our fragment coupling approach to overcome the inherent stereochemical bias presented by late-stage intermediates, thereby enabling an 18-step total synthesis. The oxidation tactics developed herein should find broad utility in the preparation of other ryanoid, isoryanoid, and highly oxidized diterpenoids.</p
A Theory of Genetic Analysis Using Transcriptomic Phenotypes
Get PDFThis thesis deals with the conceptual and computational framework required to use transcriptomes as effective phenotypes for genetic analysis. I demonstrate that there are powerful theoretical reasons why Batesonian epistasis should feature prominently in transcriptional phenotypes. I also show how to compute and interpret the aggregate statistics for transcriptome-wide epistasis and transcriptome-wide dominance using whole-organism transcriptomic profiles of C. elegans mutants. Finally, I developed the WormBase Enrichment Suite for enrichment analysis of genomic data.
RNA-seq as a tool has enormous potential because it relies on protocols that are fast, simple and increasingly cheap. In spite of their potential, transcriptomes have seen their use largely limited to single-factor experiments. Even when many transcriptomes are collected, the main analytic approach is to apply clustering algorithms that correlate responses but do not have any power to identify causal mechanisms.
I demonstrate that if a complete genetic experimental design is used (in the form of a full two-factor matrix), transcriptomes can establish genetic interactions between a pair of genes without the need for clustering algorithms. Surprisingly, when we performed epistasis analyses of hypoxia pathway mutants in C. elegans we did not simply observe a generalized epistatic interaction between the mutants. In fact, the transcriptomes recapitulated the same Batesonian epistatic relationship that had been observed using classical phenotypes. In other words, we observed that the transcriptomic phenotype of one gene can be masked by the transcriptomic phenotype of a second gene, such that a double mutant of these two genes has exactly the same phenotype as a single mutant of the epistatic gene. Motivated by this observation, we developed methods to recognize and interpret Batesonian epistasis at the transcriptomic level. This method relies on the calculation of a single aggregate coefficient that we named the transcriptome-wide epistasis coefficient.
The observation that Batesonian epistasis could be reproduced on a transcriptomic level was surprising. To explain how transcriptome-wide epistasis can arise, I studied a simplified model of transcriptional regulation using statistical mechanics. These studies demonstrate that epistatic analysis is equivalent to a perturbative analysis of the partition function of a promoter. Moreover, these studies revealed that a sufficient condition for Batesonian epistasis to occur is if the two genes encode variables that are transformed and multiplied together to form an effective single compound variable. Finally, these studies clearly demonstrate the connection between statistical (or generalized) epistasis and Batesonian epistasis and establish a physical basis for genetic logic.
Genetic analyses of gene functional units can also be carried out using allelic series in tandem with complementation (also known as dominance) tests. I developed a statistical coefficient known as transcriptome-wide dominance to enable analyses of allelic series using expression profiles. A crucial aspect of allelic series is the ability to enumerate the independent phenotypes associated with an arbitrary set of alleles. I developed the concept of phenotypic classes as a transcriptomic analogue of classical phenotypes for this purpose. Briefly, a phenotypic class is a set of transcripts that are differentially expressed in a specific set of genotypes. Thus, an allelic series consisting of two mutant alleles (and a wild-type) can at most result in 7 phenotypic classes. However, some of these phenotypic classes may be artifactual as a result of the significant false positive and false negative rates that are associated with RNA-seq. I developed a simple algorithm that tries to identify phenotypic classes that are artifactual, though often these classes may also be identified through a critical evaluation of their biological implications. I applied these concepts to a small allelic series of the dpy-22 gene, which encodes a Mediator subunit in C. elegans, and identified 3–4 functional units along with their sequence requirements.
Finally, I developed the WormBase Enrichment Suite by implementing a hypergeometric test on the tissue, gene and phenotype ontology for C. elegans. The importance of this tool derives mainly from its integration to WormBase, the repository of all C. elegans knowledge, which means that the databases that are tested will undergo continuous improvement and curation, and thus will yield the most accurate results.</p
Computational Heterogeneous Electrochemistry – From Quantum Mechanics to Machine Learning
Get PDFBecause of coulomb interactions and complex surface morphologies, rigorous methods for heterogeneous electrochemical catalysis were not well-established. Thus, for different types of electrochemical systems, a specific strategy must be adapted. In this thesis, we first used the cluster model to study the chemistry on a 1D chain of MoS2 edges. Then, a rigorous grand canonical potential kinetics (GCP-K) method was developed for general crystalline systems. Starting from quantum mechanical calculations, the method gave rise to a different picture from the traditional description given by the Butler-Volmer kinetics. Next, we studied the chemical selectivity of CO2 reduction on polycrystalline copper nanoparticles. Because of the complexity of the reaction sites, we combined the reactive force field, density functional theory, and machine learning method to predict the reactive sites on 20,000 sites on a roughly 200,000-atom nanoparticle. Such a strategy opens up new way to understand chemistries on a much wider range of complex structures that were impossible to study theoretically. Lastly, we formulated a machine learning force field strategy using atomic energies for amorphous systems. We have shown that such a method can be used to reproduce quantum mechanical accuracies for molecular dynamics. This method will enable the accurate study of the dynamics of heterogeneous systems during electrochemical reactions. In summary, we have developed quantum chemical methods and machine learning strategies to reformulate rigorous ways to study a wide range of heterogeneous electrochemical catalysts.</p