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Development of Single-Cell SPRITE: a Tool for Measuring Heterogeneity of 3D DNA Organization
Get PDFAcross eukaryotic cells, DNA from each nucleus is organized in three dimensions in order to help regulate transcriptional activity. Decades of chromosome capture technologies have revealed fundamental chromatin structures, providing information about how DNA is assembled genome-wide. The majority of these methods utilize direct physical ligation of DNA molecules to generate pairwise interactions, which have provided information about short-range interactions and intra-chromosomal structures. Recent technologies have moved toward identifying multiple DNA interactions simultaneously without physical ligation of DNA molecules, revealing information about long-range interactions and inter-chromosomal structures. One of the biggest limitations of these methods is that they only study DNA organization in bulk, which misses the heterogeneity of chromosomal structures at the single-cell level. As a result, single-cell chromosome capture methods have been developed to begin probing into the cell-to-cell variability of DNA organization and answer long-standing questions regarding single-cell structure. However, single-cell methods are currently limited to identifying low-resolution, intra-chromosomal DNA interactions with few numbers of cells. This creates a need for an improved, high-throughput single-cell method that can capture high-resolution structures and simultaneous mapping of both intra- and inter-chromosomal interactions to better elucidate single-cell DNA organization. In this thesis, we describe the development of 'single-cell split-pool recognition of interactions by tag extension' (scSPRITE), a single-cell chromosome capture method that allows for mapping of high-resolution, intra- and inter-chromosomal structures across thousands of cells. Through scSPRITE, we were not only able to reveal fundamental information about single-cell DNA organizations, but we can also quantitatively measure the variability of DNA interactions from cell to cell.</p
Studies in Physical Biology: Exploring Allosteric Regulation, Enzymatic Error Correction, and Cytoskeletal Self-Organization Using Theory and Modeling
Get PDFPhysical biology offers powerful tools for quantitatively dissecting the various aspects of cellular life that one cannot attribute to inanimate matter. Signature examples of living matter include adaptation, self-organization, and division. In this thesis, we explore different interconnected facets of these processes using statistical mechanics, nonequilibrium thermodynamics, and biophysical modeling.
One of the key mechanisms underlying physiological and evolutionary adaptation is allosteric regulation. It allows cells to dynamically respond to changes in the state of the environment often expressed through altered levels of different environmental cues. The first thread of our work is dedicated to exploring the combinatorial diversity of responses available to allosteric proteins that are subject to multi-ligand regulation. We demonstrate that proteins characterized through the Monod-Wyman-Changeux model of allostery and operating at thermodynamic equilibrium are capable of eliciting a wide range of response behaviors which include the kinds known from the field of digital circuits (e.g., NAND logic response), as well as more sophisticated computations such as ratiometric sensing.
Despite the fact that biomolecules at thermodynamic equilibrium are able to orchestrate a variety of fascinating behaviors, the cell is ultimately 'alive' because it constantly metabolizes nutrients and generates energy to drive functions that cannot be sustained in the absence of energy consumption. One prominent example of such a function is nonequilibrium error correction present in high-fidelity processes such as protein synthesis, DNA replication, or pathogen recognition. We begin the second thread of our work by providing a conceptual understanding of the prevailing mechanism used in explaining this high-fidelity behavior, namely that of kinetic proofreading. Specifically, we develop an allostery-based mechanochemical model of a kinetic proofreader where chemical driving is replaced with a mechanical engine with tunable knobs which allow modulating the amount of dissipation in a transparent way. We demonstrate how varying levels of error correction can be attained at different regimes of dissipation and offer intuitive interpretations for the conditions required for efficient biological proofreading.
We then extend the notion of error correction to equilibrium enzymes not endowed with structural features typically required for proofreading. We show that, under physiological conditions, purely diffusing enzymes can take advantage of the existing nonequilibrium organization of their substrates in space and enhance the fidelity of catalysis. Our proposed mechanism called spatial proofreading offers a novel perspective on spatial structures and compartmentalization in cells as a route to specificity.
In the last thread of the thesis, we make a transition from molecular-scale studies to the mesoscopic scale, and explore the principles of self-organization in nonequilibrium structures formed in reconstituted microtubule-motor mixtures. In particular, we develop a theoretical framework that predicts the spatial distribution of kinesin motors in radially symmetric microtubule asters formed under various conditions using optogenetic control. The model manages to accurately recapitulate the experimentally measured motor profiles through effective parameters that are specific for each kind of kinesin motor used. Our theoretical work of rigorously assessing the motor distribution therefore offers an avenue for understanding the link between the microscopic motor properties (e.g., processivity or binding affinity) and the large-scale structures they create.
In all, the thesis encompasses a series of case studies with shared themes of allostery and nonequilibrium, highlighting the capacity of living matter to perform remarkable tasks inaccessible to nonliving materials.</p
Multifunctional Volumetric Metaoptics
Get PDFOptical systems are often comprised of modular arrangements of components, and the improvement of these systems has historically leaned on the precise manufacturing and alignment of the comprising elements. This provides an intuitive pathway to optical design, but ultimately yields systems that are far bulkier than required by the laws of physics. It is often the case that the required degrees of freedom to achieve complex tasks is present within dielectric volumes that are only several wavelengths per side, and these degrees of freedom can be accessed by patterning the dielectric volume with subwavelength resolution. Even in such small volumes, all of the fundamental properties of light (wavelength, polarization, k-vector) can be controlled which opens the possibility for extremely multifunctional, compact image sensor elements. The determination of the refractive index distribution of these devices has historically been a challenging inverse-design problem, and the fabrication of 3D dielectric devices is a challenge unique to different regimes of the electromagnetic spectrum. This thesis utilizes current state-of-the-art optimization techniques to design multifunctional volumetric devices, and theoretically expands upon the techniques to facilitate the optimization of high index contrast structures. Multiple microwave prototypes are measured, devices operating at terahertz frequencies are fabricated using silicon micromachining, and optical devices with resolutions achievable with CMOS processing techniques are studied for next-generation camera sensors.</p
Josephson Inductance Thermometry in Resonantly-Coupled Van-der-Waals Heterostructures
Get PDFA promising strategy for pushing single-shot energy-resolving detection to the level of individual microwave photons, thermal phonons, and single kBT heat pulses is the development of thermal detectors with miniscule heat capacities. Graphene, with its vanishing heat capacity and diminished electron-phonon coupling at cryogenic temperatures, is an enticing material platform for achieving heat capacities at the level of single-kB in solid-state systems at dilution refrigerator temperatures. Key to the design and operation of a thermal detector is the readout method employed to monitor the temperature of the thermal element. However, to date, existing thermometry methods for Van-der-Waals materials have typically been slow and ill-suited for single-shot calorimetry, limited either by long averaging times, sweep repetition rates, or resetting times of switched Josephson junctions.
This dissertation presents Josephson inductance thermometry, a method we have demonstrated for probing the electron temperature of Van-der-Waals materials at milli-Kelvin temperatures. The technique relies upon the inductive loading of a superconducting resonator by a graphene-based Josephson junction, in which increases in electron temperature of the graphene flake are transduced to shifts of the resonant frequency. This technique brings with it many of the benefits of resonant readout, such as fast response times, ease of frequency-division multiplexing, and operation at the lowest temperatures available to a dilution refrigerator where the device parameter regime yields the greatest detector sensitivities. Such a device design is well-suited, for example, to the serving as the fundamental pixel architecture of next-generation dark matter searches.
This thesis derives all thermal detector performance metrics and fundamental noise sources from first principles and provides a pedagogical introduction to the superconducting phenomena and low-temperature physics exploited by the detector. Subsequently, a thorough discussion is presented of the device architecture, fabrication procedures, measurement chain, physical characterization via carrier density sweeps, physical characterization via Joule heat sweeps, and noise measurement characterization. It is our hope that researchers interested in pushing the limits of ultrasensitive thermal detectors and calorimetry can use this thesis to delve into details of Josephson inductance thermometry as well as the field of cryogenic thermal detection broadly.</p
Probing the Corona in Active Galactic Nuclei Using Broadband X-Ray Spectroscopy
Get PDFActive Galactic Nuclei (AGN) are some of the most luminous sources in our known universe, powered by large-scale accretion onto a supermassive black hole. Supermassive black holes are known to co-evolve with their host galaxies, with AGN playing an important role in regulating feedback in galaxies by depositing large amounts of energy through outflows and jets. While studies of AGN have dated back to the 1960's when the first quasar was discovered, much is still unknown about the key source powering the X-ray emission in AGN, i.e. the corona. In my thesis, I present detailed investigations of the properties of AGN coronae using broadband X-ray spectroscopic techniques. This work utilizes spectroscopic data taken with the NuSTAR telescope, which has revolutionized studies of the corona. Being the first focusing high energy X-ray telescope in orbit, NuSTAR's high sensitivity at hard X-ray energies (> 10 keV) has enabled robust measurements of fundamental properties of the corona, such as its temperature, from single epoch observations of AGN for the first time. In the first study presented in this thesis, I performed measurements of coronal temperature in a sample of 46 NuSTAR-observed AGN through fitting X-ray spectral models for each object. My analysis showed the temperature of the corona to be regulated by electron-positron pair production and annihilation processes. From this sample, I identified an AGN with an unusually low coronal temperature, 2MASX J19301380+3410495. I modeled the broadband X-ray spectrum of this object in detail using multi-epoch X-ray observations taken with the Swift, XMM-Newton, and NuSTAR telescopes, and found the object to also belong to a rare class of X-ray obscured but optically unobscured AGN. Using multi-wavelength information, I elucidated the nature of the complex obscuration present in 2MASX J19301380+3410495. In recent work presented in this thesis, I compiled one of the largest samples of unobscured AGN with high quality NuSTAR X-ray spectra in order to characterize how the physical properties of the corona relate to fundamental accretion parameters in AGN, such as the Eddington ratio and mass of the supermassive black hole. Finally, I discuss possible future work directed at investigating other enigmatic AGN similar to 2MASX J19301380+3410495 that have conflicting optical and X-ray classifications. Using techniques such as multi-wavelength spectropolarimetry in addition to X-ray spectroscopy, it may be possible to unveil the mechanisms of obscuration within these exotic sources that challenge classical pictures of AGN structure.</p
Machine Learning Methods Inspired by Challenges in Total Synthesis
No full textSynthetic organic chemists face a dearth of challenges in the efficient construction of functional molecules, particularly bioactive compounds. Predictive approaches offer reductions to research timelines and resource costs and allow chemists to devote their expertise where it is most valuable. Promising machine learning (ML) methods have evolved for uncovering patterns in chemical data that are beyond the grasp of expert humans, but a number of grand challenges in molecular ML remain. First, the learning of chemical structure representations rooted in physical first principles has yet to be robustly demonstrated. Second, the practical task of predicting successful "over-the-arrow" reaction conditions remains elusive. Finally, the demonstration of such solutions in the context of complex synthesis has yet to be realized.
Herein, approaches to these grand challenges are developed and described. Inspiration is derived from the successful synthesis of the anticancer marine natural product ritterazine B. Reaction condition prediction is approached first, where a novel graph neural network architecture is developed under a multilabel classification framework. The resulting model is successfully demonstrated on datasets of four high-value reaction types in modern synthesis. Next, 3D-to-1D representation learning is approached by development of a volumetric neural architecture based on inception networks. Such voxel models are demonstrated for the prediction of expensive quantum mechanical properties from space-filled data alone.
The merging of these approaches for reaction condition optimization and utility in complex settings is discussed and forecasted for future works, which are currently underway.</p
Single Neuron Correlates of Learning, Value, and Decision in the Human Brain
Get PDFIn this thesis, I present several new results on how the human brain performs value-based learning and decision-making, leveraging rare single neuron recordings from epilepsy patients in vmPFC, preSMA, dACC, amygdala, and hippocampus, as well as reinforcement learning models of behavior. With a probabilistic gambling task we determined that human preSMA neurons integrate computational components of stimulus value such as expected values, uncertainty, and novelty, to encode an utility value and, subsequently, decisions themselves. Additionally, we found that post-decision related encoding of variables for the chosen option was more widely distributed and especially prominent in vmPFC. Additionally, with a Pavlovian conditioning task we found evidence of stimulus-stimulus associations in vmPFC, while both vmPFC and amygdala performed predictive value coding, establishing direct evidence for model-based Pavlovian conditioning in human vmPFC neurons. Finally, in a Pavlovian observational learning paradigm, we found a significant proportion of amygdala neurons whose activity correlated with both expected rewards for oneself and others, and in tracking outcome values received by oneself or other agents, further establishing amygdala as an important center in social cognition. Taken together, our findings expand our understanding of the role of several human cortical brain regions in creating and updating value representations which are leveraged during decision-making.</p
Capturing Nuclear Quantum Effects at Classical Efficiency: a Path-Integral Approach
Get PDFQuantum mechanical effects of nuclei are ubiquitous in chemistry. For a typical example, zero-point energies and tunneling effects of the nuclei shift the chemical equilibrium and manipulate the reaction rate. However, theoretical investigation of such nuclear quantum effects in chemical reactions remains a challenge due to the heavy computation cost. To this end, imaginary-time path-integral based approximate methods have been previously introduced, which allows the inclusion of nuclear quantization in real-time chemical dynamics simulations at the efficiency of classical Newtonian dynamics. In the dissertation, we further extend the applicability of those path-integral methods and exploit the methods for practical chemical investigations. Specifically, we introduce novel dynamics approaches based on ring-polymer molecular dynamics methodology to incorporate nuclear quantum effects in the simulations of excited state dynamics and microcanonical scattering processes, and to examine the nuclear quantum effects in Hydrogen/Deuterium sticking to the graphene surface.</p
A Multi-Disciplinary Approach: How Aqueous Minerals Hold the Key to Understanding the Climate and Habitability of Terrestrial Planets
Get PDFUnderstanding the interplay between geological processes and the climate within the ancient pasts of terrestrial planets holds the key to deciphering what makes terrestrial planets habitable. The climates of both Mars and Earth were drastically different in their ancient pasts. Liquid water once flowed on Mars ~3-4 Ga, creating fluvial valleys and aqueous minerals, until Mars dried out to the desert planet we know today. During the Pleistocene (~ 2.6 Ma – 11.7 ka) and Neoproterozoic (640-710 Ma), Earth experienced widespread glaciations and even a global glaciated state, respectively. Aqueous minerals, such as clays and carbonates, record the history of their aqueous environments and can be used to track these dramatic changes in climate and environment. In Chapter 2, I use hyperspectral infrared imagery and high resolution images retrieved by the Mars Reconnaissance Orbiter to characterize the lithology of some of the oldest Noachian ~3.8-4.1 Ga crust exposed on Mars. I document eight geological units and features that will be studied with the Perseverance rover and record the presence of pyroxene-bearing igneous crustal materials, aqueous environments that led to widespread clay formation, and basin-forming impact processes that brecciated the crust. Associated younger Noachian-aged magnesium carbonate-bearing geological units will also be studied and sampled with the Perseverance rover. In Chapter 3, I review magnesium carbonate formation on Earth and Mars and find that textures of nodules, crusts, veins, sparry crystals, and thrombolites/stromatolites, their associated host lithologies and related secondary mineralogy can be used to distinguish between formation within weathering, lacustrine, hydrothermal, diagenetic, or microbially influenced aqueous environments, respectively, with rover analyses. Laboratory analysis of stable and radiogenic isotopes of returned samples will allow us to analyze the surface temperature and atmospheric isotopic composition of ancient Mars. In Chapter 4, I characterize the paragenesis of hydrated carbonates. In frigid environments, carbonates form in hydrated species known as monohydrocalcite (MHC) and ikaite that transform to calcite upon heating. Through petrographic analysis of Pleistocene ikaite pseudomorphs and a review of more ancient examples, I define a new carbonate microtexture, guttulatic calcite, which is diagnostic for carbonate dehydration and can be used to document frigid temperature conditions. In Chapter 5, I characterize the stable carbon, oxygen (δ¹⁸OCARB), and clumped (Δ₄₇) isotope systematics of hydrated carbonates. Through heating experiments of modern MHC, I measure and model change in δ¹⁸OCARB and Δ₄₇ signatures facilitated by equilibrium exchange as MHC is dehydrated. Using the determined correction for dehydration overprint allows reconstruction of precursor ikaite formation temperatures and isotopic signatures. The textural and isotopic proxies can now be used for reconstructing temperatures and isotopic signatures within Pleistocene and Neoproterozoic sedimentary deposits. In Chapter 6, I use the Perseverance rover’s SHERLOC instrument’s deep-UV Raman and fluorescence spectroscopy to discover evidence for two potentially habitable ancient aqueous environments that contain aromatic organic compounds. Spectral and textural observations of the olivinecarbonate assemblage within Jezero crater, Mars reveal carbonation of ultramafic protolith. A separate, later brine formed sulfate-perchlorate mixtures in void spaces. Fluorescence signatures consistent with multiple types of aromatic organic compounds occur throughout these samples, preserved in minerals related to both aqueous processes. These organic-mineral associations indicate that aqueous alteration processes led to the preservation and possibly formation of organic compounds on Mars. In Chapter 7, I model the global water budget and hydrogen isotopic composition (D/H) of Mars, using measured constraints from geomorphology, atmospheric escape rates, volcanic degassing processes, crust volatile content, and D/H. In my simulations, I find that chemical weathering sequestered a 0.1-1 km global equivalent layer of water, decreasing the volume of water participating in the hydrological cycle by 40 to 95% over the Noachian (~3.7-4 Ga) period, reaching present-day values by ~3 Ga. Between 30 and 99% of Martian water was sequestered through crustal hydration, demonstrating that irreversible chemical weathering can increase the aridity of terrestrial planets. In summary, this PhD thesis demonstrates that the formation of aqueous minerals is a major control on terrestrial planet climates and that aqueous minerals can be used to track the conditions of their formation environments.</p
Dynamics of Ultralight Flexible Spacecraft During Slew Maneuvers
Get PDFTraditional spacecraft design paradigms rely on stiff structures with comparatively flexible appendages. More recent trends, however, trade deployed stiffness for packaging efficiency to stow increasingly large-area apertures inside existing launch vehicles. By leveraging recent advances in materials and structures, these ultralight, packageable, and deployable spacecraft, hereafter referred to as ultralight flexible spacecraft, are up to several orders of magnitude lighter and more flexible than the current state-of-the-art. They promise to deliver higher performance for a wide range of applications, but this comes at a cost, in this case, due to their very low-frequency structural dynamics. Structural dynamics can negatively interact with spacecraft attitude control systems and degrade pointing performance.
These developments motivate the main objective of this thesis: to demonstrate the feasibility and limitations of maneuvering next-generation ultralight flexible spacecraft. To that end, the thesis proposes a quantitative method for determining structure-based performance limits for flexible spacecraft slew maneuvers using reduced-order modal models. It then develops a geometrically nonlinear flexible multibody dynamics finite element model of a representative ultralight flexible spacecraft based on the Caltech Space Solar Power Project architecture to validate this method. The results demonstrate that contrary to common assumptions, other constraints impose more restrictive limits on slew maneuver performance than the dynamics of the structure. In particular, they show that the available attitude control system momentum and torque are often significantly more limiting than the structure. Consequently, these results suggest that spacecraft structures can either be (i) maneuvered significantly faster, assuming suitable actuators are available, or (ii) built using lighter-weight, less-stiff, and lower-cost construction that moves the structure-based performance limits closer to those of the rest of the system. Thus, there is a significant opportunity to design less-conservative, higher-performance space systems.</p