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Co-Translational Protein Targeting and Insertion by SecA
Get PDFCo-translational protein targeting is a conserved process for the biogenesis of membrane proteins. This pathway was generally thought to depend on signal-recognition particle (SRP) for recognition of nascent protein and delivery to the membrane. Recently, SecA was found to also bind ribosomes near the nascent polypeptide exit tunnel, but the function of SecA’s ribosome interaction remains unclear.
A combination of in vitro reconstitution and in vivo targeting assays show that SecA is necessary and sufficient to direct the targeting and translocation of RodZ to the bacterial plasma membrane in an obligatorily co-translational mechanism. The N-terminal extension preceding the transmembrane domain and periplasmic domain sequences immediately downstream of the transmembrane domain of RodZ provide distinguishing features that allow RodZ to engage SecA instead of the SRP machinery. Biochemical and cryoEM analyses further show that the N- terminal amphipathic helix on SecA and the ribosomal protein uL23 together form a composite binding site for the transmembrane domain (TMD) on the nascent chain. This interaction positions additional sites on the ribosome and SecA for recognition of the charged residues on both sides of the TMD, explaining the substrate specificity of SecA recognition. Quantitative kinetic analyses demonstrate that membrane-embedded SecYEG can associate with and remodel the SecA-bound ribosome-nascent chain complex, which together with elongation of the nascent polypeptide facilitates handover of the translating ribosome to the translocase.</p
Theoretical Characterization of Aromatic Exciplex Fluorescence
Get PDFThe negative effects of soot on the environment and human health are well known, but efforts to decrease soot production in combustion processes are hampered by the absence of accurate, transferable models for soot formation. Uncertainties about the soot nucleation mechanism, including the size and properties of the molecules involved and the relative importance of chemical and physical stabilization, have made model development difficult. Electronic spectroscopy methods such as laser-induced fluorescence (LIF) have the potential to characterize transient soot nuclei, but interpreting spectra requires a comprehensive understanding of the photoresponse of likely soot precursors, namely polycyclic aromatic hydrocarbon (PAH) dimers and clusters. To build up a picture of this photoresponse using theory, it is necessary to evaluate which methods are capable of treating the relevant molecules at reasonable cost while capturing the excited-state and noncovalent interactions involved in excimer and exciplex formation, a key excited-state process for aromatic clusters. In this work, we describe extensive benchmarking of basis set error in highly-accurate perturbatively-corrected multireference calculations of exciplex interaction strength and use the best possible multireference approach to evaluate the performance of less-expensive time-dependent density functional theory (TDDFT) results. Using the most accurate TDDFT methods, we explore how the geometric and electronic properties of the monomers influence excited-state interactions in complexes, considering a large database of complexes. A predictive model for exciplex fluorescence emissions of complexes containing six-membered ring PAHs based on monomer HOMO-LUMO gaps is proposed. We describe the contrasting photoresponse of PAHs containing five-membered rings, where nonaromatic groups produce conformational flexibility that has a strong impact on absorption and emission behavior.</p
Application of Path-Independent Integrals to Soil-Structure Interaction
Get PDFAssessing seismic pressure increment on buried structures is a critical step in the design of infrastructure in earthquake-prone areas. Due to intrinsic complexities derived from the need to match the solution in the far-field to the localized solution around the structure, the near-field, researchers have aimed at finding simplified models focused on engineering variables as the seismic earth thrust. One such model is the so-called Younan-Veletsos model, which pivots on a stringent assumption on the stress tensor.
At the same time, the might of the path-independent integrals of solid mechanics to deal with problems in Geotechnical Engineering at large, and Soil-Structure Interaction in particular, has remained unexplored, despite of a rich landscape of potential applications. The unbridled success of these path-independent integrals in Fracture Mechanics, a discipline which cannot be understood without them currently, may be mirrored in problems in Geotechnical Engineering, since the two fields, despite appearing very detached from each other at first glance, share deep traits: in both cases, the system under consideration can be conceptualized as a domain with simple, easy-to-assess regions (the areas where remote loading is applied and the far-field, respectively) and also with other complex, hard-to-understand regions (the crack tip, the near-field).
We present the first derivation of the exact solution of the Younan-Veletsos problem, which is later analyzed to reveal phenomena not captured by previous approximate solutions. Then, we introduce a novel model which relies on the path-independent Rice’s J-integral, a customary tool in Fracture Mechanics, which is applied here in the Soil-structure Interaction context for the first time. This novel model captures those features of the exact solution that were missed by prior approximations. The capabilities of the J-integral to, first, find an upper bound of the force induced by earthquakes over the walls of underground structures, under some conditions, and, second, to understand the soil-structure kinematic interaction phenomenon are also assessed.
Additionally, the intermediate step of analyzing of the far-field yielded some results concerning Site Response Analysis which are also included in the text.</p
Development of a Modular Strategy Towards the Total Synthesis of (+)-Pleuromutilin and Progress Towards the Synthesis of (–)-Merrilactone A
Get PDFNatural products have long stood as a rich source of biologically relevant molecules bearing highly functionalized and complex architectures. On one hand, they are a focal point for the development of new therapeutic agents owing to their inherent biological activities. On the other, they serve as an exciting testing ground for existing synthetic methodologies and provide opportunities for the development of new reactions.
Herein, we describe a modular strategy that was employed for the total synthesis of the antibiotic (+)-pleuromutilin. Key features of our synthesis include (1) the development of a highly stereoselective SmI₂-mediated ketyl radical cyclization to establish the central eight-membered ring and (2) a modular crotylation reaction to install the eight-membered ring’s backbone that permits full control over the stereochemistry at C12 as desired. During our synthetic studies, a transannular [1,5]-hydrogen atom transfer reaction that affects a stereospecific redox relay to set the C10 stereocenter was serendipitously uncovered. This strategy enabled the completion of a concise total synthesis of (+)-pleuromutilin, proceeding in 18 steps. To demonstrate the modularity of our synthetic approach, the same strategy was readily applied to the synthesis of (+)-12-epi-pleuromutilin with no reoptimization, providing a new platform for the preparation of fully synthetic derivatives that may hold promise as broad-spectrum antibiotics.
This report also highlights the work we have conducted in the development of a synthetic strategy towards (–)-merrilactone A. We detail our investigation of a Pd-catalyzed asymmetric allylic alkylation reaction that rapidly constructs the D-ring bearing the C5 and C6 vicinal quaternary centers. Potential paths forward to complete the synthesis of this neurotropic natural product leveraging this advanced intermediate will also be discussed.</p
Deep Learning in Unconventional Domains
Get PDFMachine learning methods have dramatically improved in recent years thanks to advances in deep learning (LeCun et al., 2015), a set of methods for training high-dimensional, highly-parameterized, nonlinear functions. Yet deep learning progress has been concentrated in the domains of computer vision, vision-based reinforcement learning, and natural language processing. This dissertation is an attempt to extend deep learning into domains where it has thus far had little impact or has never been applied. It presents new deep learning algorithms and state-of-the-art results on tasks in the domains of source-code analysis, relational databases, and tabular data.</p
A Novel Digital Holographic Microscope (DHM) to Investigate and Characterize Microbial Motility in Extreme Aquatic Environments
Get PDFRecent shifts in the astrobiological community have prompted the development of methods for the direct search for extant life within our solar system. In order to look for life elsewhere in our solar system, it is important to also investigate the broad spectrum of extant life on Earth. Over millions of years of evolution, life has continually adapted such that an 'extreme' environment has become a relative term. What is considered extreme for one type of organism is home to another and vice versa. Furthermore, very little is known about the organisms that inhabit these extreme environments, and even less in known about their in situ behavior. Investigating various extreme environments around Earth in order to understand the in situ behavior of organisms that inhabit it will better inform the astrobiological community when planning future space missions for the direct search for extant life within our solar system. However, no suitable instrument exists to conduct these in situ field campaigns, while also being physically robust enough to withstand the rugged terrains that can be expected from extreme environments.
This thesis describes the development of a novel off-axis digital holographic microscope (DHM) for the direct in situ observation of microscale organisms in extreme aquatic environments. The hardware developments of this instrument are introduced and validated experimentally as well as software developments including autonomous particle detection and tracking algorithms. This instrument is then used in novel laboratory experiments involving the development of optical phase contrast agents, as well as deployed to multiple field campaigns where off-axis DHM is used to observe the in situ behavior of microorgansisms in various extreme aquatic environments around North America.</p
Three Essays in the Dynamics of Political Behavior
Get PDFIn this thesis, I empirically assess the dynamics of political behavior. More specifically, I analyze what creates — or does not create — change in political participation, such as voting in elections and contributing to campaigns. Through this, I intend to show that paying close attention to dynamics can help answer fundamental questions of political behavior and offer important insights for real-life policies.
In Chapter 1, I focus on how non-political life events and election administration policy impact voter turnout. I analyze (1) the effect of moving on turnout over time and (2) how an election administration policy helps with the recovery of lowered turnout by lowering the re-registration burden of movers.
Moving depresses turnout by imposing various costs on voters. However, movers eventually settle down, and such detrimental effects can disappear over time. I analyze these dynamics using United States Postal Services (USPS) data and detailed voter panel data from Orange County, California. Using a generalized additive model, I show that previously registered voters who move close to the election are significantly less likely to vote (at most -16.2 percentage points), and it takes at least six months on average for turnout to recover. This dip-and-recovery is not observed for within-precinct moves, suggesting that costs of moving matter only when the voter's environment has changed much. I then evaluate an election administration policy that resolves their re-registration burden. This policy proactively tracks movers, updates their registration records for them, and notifies them by mailings. Using a natural experiment, I find that this policy is effective in boosting turnout (+5.9 percentage points). This success of a simple, pre-existing, and non-partisan safety net is promising, and I conclude by discussing policy implications.
Chapter 2 (published at Election Law Journal, doi: 10.1089/elj.2019.0593, coauthored with R. Michael Alvarez and Jonathan N. Katz) shows how the participation dynamics of political participation differ between two distinct classes of donors---hidden and visible (from data), based on their amount contributed. In campaign finance we find that there is something about the data generating process that is often overlooked, but which affects the interpretation of data greatly. This precedes Chapter 3 as it provides some important intuitions as to how the data should be filtered, wrangled, and interpreted for usage.
More specifically, inferences about individual campaign contributors are limited by how the Federal Election Commission (FEC) collects and reports data. Only transactions that exceed a cycle-to-date total of \$200 are individually disclosed, so that contribution histories of many donors are unobserved. We contrast visible donors and "hidden donors," or small donors who are invisible due to censoring and routinely ignored in existing research. I use the Sanders presidential campaign in 2016, whose unique campaign structure received money only through an intermediary (or conduit) committee. These are governed by stricter disclosure statutes, allowing us to study donors who are normally hidden. For the Sanders campaign, there were seven hidden donors for every visible donor, and altogether, hidden donors were responsible for 33.8\% of Sanders' campaign funds. We show that hidden donors start giving relatively later, with contributions concentrated around early primaries. We suggest that as presidential campaign strategies change towards wooing smaller donors, more research on what motivates them is necessary.
In Chapter 3, I focus on how events in the election cycle affect political behavior — this time, campaign contributions. I show how the aggregate behavior of campaign contributors is not affected as a function of election cycle dynamics and events.
Using the 2016 campaign finance data from the FEC as a daily time-series, I test the hypothesis that if presidential donors are either instrumental or momentum-driven, they will be responsive to events that reveal new information about candidate viability, such as early victories or unexpected upsets in primaries. I employ the sequential segmentation spline method to detect structural breaks while providing smooth estimates between the jumps. I find that on the national level, daily aggregates for any candidate is a slow-moving, smooth process, without any particular critical events. Even when data is disaggregated by state, events expected to create shocks hardly ever do, such as the Iowa caucus or the New Hampshire primary. This is also observed for a preliminary analysis of the 2020 contribution data. I conclude that campaign contributing is, in aggregate, a smooth process, and that donors are neither uniformly instrumental nor momentum-driven.
In all these chapters, my methodological contribution is in taking advantage of extremely large administrative datasets and harnessing the power of the large sample size with nonparametric and semiparametric methods. The rich world of nonparametric and semiparametric methods remains largely untapped by political science studies. I hope to show through this thesis that they can answer new questions, answer old questions in new ways, and provide strong insight that the default linearity model cannot provide.</p
Protein-Mediated Colloidal Assembly
Get PDFThe assembly of colloidal-sized particles into larger structures by the manipulation of inter-particle forces has been a subject of significant research towards applications in materials science, soft matter physics, and synthetic biology. To date, much of this work has utilized manipulation of electrostatic or depletion interactions to drive the aggregation of the particles. More recently, specific (bio)-chemical interactions have been harnessed, particularly the use of deoxyribonucleic acid (DNA) linkers to program particle interactions by Watson-Crick base-pairing. In this thesis, we will demonstrate the use of an alternative set of biochemical interactions, protein-protein interactions, which have useful properties (in particular, their ability to be completely genetically-programmable).
In Chapter 2, we discuss the development of a model system for the protein-mediated assembly of colloidal micro-particles. Associative proteins are grafted onto the surface of polystyrene micro-particles, enabling their assembly into aggregates either through reversible coiled-coil interactions or by irreversible isopeptide linkages. The sizes of the resulting aggregates are tunable and can be controlled by the concentration of the immobilized associative proteins on their surface. Further, we show that particles grafted with different protein pairs show excellent self-sorting into separate aggregates. Finally, we demonstrate that these protein-protein interactions can be used to assemble complex core-shell aggregates. The principles of protein-mediated colloidal assembly learned in this chapter will be instructive as we attempt the more complex assembly of living microbial cells.
In Chapter 3, we discuss the implementation of a protein-driven aggregation system in living bacterial cells. Similarly to Chapter 2, we demonstrate that we can drive the aggregation of bacteria by the surface display of proteins enabling reversible coiled-coil interactions or irreversible isopeptide bonds. The sizes of these aggregates are tunable by titration of surface expression levels by standard synthetic biology techniques. Finally, we show that this programmable aggregation of bacteria may have physiological consequences for the cells, in particular, the activation of a quorum sensing circuit due to a higher local concentration of bacteria.
In Chapter 4, we further investigate how the properties of the aggregates described in Chapter 3 can be controlled and how these relate to the underlying properties of the associative proteins and shear field. we demonstrate control of the assembly kinetics and equilibrium sizes of the resulting flocs over several orders of magnitude using different associating proteins and expression levels. Finally, we show that a single point mutation in the associative protein leads to an unexpected ultra-sensitive pH-responsive coil, demonstrating the importance of molecular-scale interactions on the macro-scale properties of the aggregates.
In Chapter 5, we discuss the ability of the bacterial aggregates described in Chapters 3 and 4 to enable substrate channeling between bacterial strains, leading to enhancement of titers in multi-step biosynthetic pathways. When biosynthetic pathways are split into separate bacterial strains, dilution of the intermediate compound into the bulk media may decrease reaction flux. By aggregating the bacteria, the intermediate compound is able to rapidly diffuse into the downstream cell without being diluted, enabling higher reaction fluxes. we demonstrate through the model flavonoid synthesis pathway that aggregation can lead to substantially higher titers of the desired compound without pathway re-engineering, and develop a mathematical model by which this result can be understood.</p
Engineering Vectors for Non-Invasive Gene Delivery to the Central Nervous System using Multiplexed-CREATE
Get PDFViruses are widely modified and used as gene delivery vectors for various applications in science and therapeutics. To this end, my thesis focuses on modifying the recombinant adeno-associated viral (rAAV) vectors that are identified as a safer choice for cargo delivery compared to other known viral vectors. They are widely used in the scientific communities, have seen promising outcomes in gene therapy clinical trials, and as of today have three products approved to use in humans. However, the natural repertoire of rAAVs have broad tropism when delivered systemically, and there is room for further improvement on the efficiency and specificity, especially for gene delivery in the central nervous system (CNS). The prior work done in Dr. Gradinaru lab addresses the issue by using a directed evolution approach called CREATE, Cre recombination-based AAV targeted evolution, to identify AAV-PHP.B and AAV-PHP.eB capsids, which broadly transduce the CNS (Deverman et al, 2016; Chan et al, 2017). CREATE selects for functional lox-flipped viral DNA that crosses the blood-brain barrier (BBB) and successfully transduces a specific nerve cell-type expressing Cre, thereby applying a strong selection pressure. However, the method is limited by its ability to identify a handful of enriched variants, and may also be prone to false positives resulting from experimental biases. The effort to fully understand the selection landscape, and to select for capsids that are not just efficient towards a cell-type but also specific towards it, led to the development of Multiplexed-CREATE (M-CREATE). M-CREATE allows parallel positive selections across different cell-types of interest, enables post-hoc negative selections across off-targets using a next-generation sequencing (NGS) based capsid recovery, and retains the principles of Cre-dependent functional recovery from CREATE. The method has a synthetic library generation approach to minimize biases within selection rounds, a variant replicate feature to identify the signal versus noise within a biological system, and an analysis pipeline to group families of enriched variants based on amino acid motifs, all of which together increases the confidence in the outcome and the throughput from a single experiment. Selections across brain endothelial cells, neurons, and astrocytes yielded several AAV-PHP.B-like variants that broadly transduce the CNS, AAV-PHP.V variants that can efficiently transduce the vascular cells forming the BBB, a AAV-PHP.N variant that transduces neurons with greater specificity, and AAV-PHP.C variants that cross the BBB without murine strain specificity across tested strains. The AAV-PHP.C variants have different amino acid motifs compared to the AAV-PHP.Bs that have been previously shown to have limited CNS transduction across some mouse strains due to its interaction with the strain specific host cell surface receptor, ly6a, a homolog of which is not found in humans. (Hordeaux et al, 2018, Hordeaux et al, 2019; Huang et al, 2019; Batista et al, 2019) Therefore AAV-PHP.Cs offer some hope towards translation across other species. In summary, the M-CREATE methodology turns out to be a high-confidence, robust selection platform to yield several novel viral capsids for use in neuroscience and potential gene therapy related applications.</p
Development of Tools for Probing Order in Single Crystals Using Electron and Photon Spectroscopy
Get PDFDiscovering novel quantum phases of matter–from emergent behavior of strongly-correlated electrons in solid-state systems to superfluidity in quantum degenerate liquids–has been a cornerstone of condensed matter physics for many decades. In the most recent decades, however, the discovery of topological phases has emphasized the importance of symmetry, in addition to the conventional paradigm of symmetry breaking, in the definition of the order parameter, Ψ, and hence the quantum phase it represents. Naturally, novel experimental tools, capable of coupling to said order parameter, directly or indirectly, are required to discover conventionally elusive quantum phases. In this thesis, I will discuss experimental techniques, using both photon and electron spectroscopy, to study exotic electronic phases in single crystals. The thesis will be divided into two unequal parts: (a) the development of a high-energy-resolution sub-Kelvin angle-resolved photoemission spectroscopy apparatus to study 3D time-reversal invariant topological superconductors, and (b) the experiments exploiting the non-linear and time-resolved aspects of femtosecond lasers to study a broad class of many-body systems.</p