VictorJuiz/thesis huggingface dataset:
Virally-mediated disruption of cellular homeostasis: regulation of pH and HDAC function

Viruses have evolved to manipulate the cellular environment to promote their replication and spread. They do so by encoding viral effectors that co-opt or disrupt cellular processes to create an environment suitable for infection. This dissertation will discuss two viral proteins that disrupt cellular homeostasis. First, I will present work demonstrating that the SARS-CoV-2 Envelope (E) protein interferes with retention of the endoplasmic reticulum (ER) aminopeptidase associated with antigen processing (ERAAP) in cells. To protect the SARS-CoV-2 fusion protein Spike from improper cleavage by Golgi resident proteases, E protein increases the pH of this compartment. The change in pH delays trafficking and likely impairs the function of these proteases. We show that E-mediated Golgi pH neutralization impedes ERAAP retention likely by disrupting the interaction between ERAAP and ERp44, a chaperone we and others have shown to control ERAAP localization. Specifically, we demonstrate that the expression of SARS-CoV-2 E results in decreased ERAAP intracellular levels and ERAAP secretion into the extracellular environment. ERAAP’s reliance on ERp44 and a functioning ER/Golgi pH gradient for proper localization and function led us to propose that ERAAP serves as a sensor of disturbances in the secretory pathway during infection and disease./nThe second viral protein that will be discussed is the M18 protein from murine cytomegalovirus (MCMV). Previous work found that M18 disrupts the function of histone deacetylases (HDACs). HDACs are epigenetic modulators capable of controlling gene expression by removing acetyl modifications on histones and non-histone proteins. Importantly, HDACs have been shown to regulate herpesvirus replication and latency. Moreover, herpesviruses encode proteins that antagonize or harness the action of these enzymes. I aimed to elucidate the cellular functions of M18 and the contribution of this protein to viral pathogenesis. Here, we demonstrate that M18 is produced as two isoforms, M18L and M18S, during infection. These isoforms likely possess different functions, as suggested by their differential localization. Furthermore, using RNAseq, we found that M18 regulates the expression of a subset of immune-related genes, including various members of the chemokine family. We hypothesize that induction of these factors by M18 could promote viral dissemination by recruiting monocytes, which are known MCMV reservoirs./nAltogether, this dissertation presents work that expands our understanding of viral effectors and their cellular functions. These contributions further illuminate the complex interactions between viruses and their hosts.

Advisor: Coscoy, Laurent
Scalable Supervision for Safe and Efficient Online Robot Learning

Robotics has seen increasing success in automating a wide variety of tasks in structured settings, such as factories and assembly lines. However, using robots for reliable automation in less structured, open-world environments remains a critical challenge. Recent advances in machine learning have played a critical role in the development of agents which can bridge this gap by exploring the environment online and leveraging collected experiences to modify their behavior. For these algorithms to be broadly applicable in practice, they must be both efficient enough to direct exploration towards regions that are relevant for learning new tasks while being safe and reliable enough to deploy in the physical world. However, this is exceedingly challenging if these algorithms must discover information about promising and unpromising behaviors entirely from their own online experience, and are not provided with any additional supervision indicating promising behaviors to emulate and unpromising behaviors to avoid./nThis dissertation introduces a number of online learning algorithms for learning from demonstrations, reinforcement learning, and bandit exploration which use scalable sources of super- vision, both from sparing human queries and offline datasets, to structure online exploration to facilitate safe and efficient robot learning. I will discuss both theoretical properties of these algorithms and their evaluation in a number of environments with uncertain dynamics both in simulation and on robotic manipulation tasks in the physical world. I will end by talking about opportunities for future work in improving the scalability and applicability of online learning algorithms for robot learning in practice.

Advisor: Goldberg, Kenneth Y.
The regulation of gene expression and genetic exchange between Vibrio cholerae, bacteriophage ICP1, and their mobile genetic elements

Organisms of all domains of life face a multitude of physiological stresses, ranging from metabolic stresses, such as limited nutrient availability, to predation by viruses. Bacteriophages (phages), the viruses of bacteria, are suspected to be the most abundant entity on the planet. As such, bacteria are faced with omnipresent predation by their phages and have evolved numerous distinct mechanisms to overcome phage infection. The identification and characterization of these bacterial immune systems has rapidly increased. It has become increasing appreciated that mobile genetic elements of bacteria, genomic loci capable of inter- and intra-genome transfer, are hotspots of these immune systems that inhibit bacteriophage infection. The relationship between the host bacterium, mobile genetic element, and infecting phage is highly convoluted, as each entity must sense and properly respond to another, tipping the complicated symbioses at play in their favor. In this work, we probed the interactions between Vibrio cholerae, its selfish mobile genetic elements, and the bacteriophage that prey upon V. cholerae at three distinct magnitudes: local transcriptional regulation, global transcriptional regulation, and cross-genome exchange between entities. First, we define a novel role for mobile genetic element encoded small RNAs in regulating the bacterial response to infection by phage. Prokaryotic small RNAs act as post-transcriptional regulators, altering the expression of a set of target transcripts by direct base pairing. Second, we investigated the regulation of mobile genetic element gene expression at the genomic scale, identifying global regulators involved in the regulation of V. cholerae mobile genetic elements. These global regulators act to control the activation of many mobile genetic elements simultaneously. We then leveraged our collection of co-isolated bacteria and phages to undertake a primarily bioinformatic analysis of the role that mobile selfish nuclease genes play in the conflict between phages, mobile genetic elements, and their hosts. The genetic exchange of these mobile nuclease genes is suggested to be a driving force of evolution between the entities. Broadly, this work investigates the local and global transcriptomic and genomic interactions between bacteria, their selfish mobile elements, and phages.

Advisor: Seed, Kimberley D
From Raw Material Extraction to Waste Generation - Environmental Footprint Analysis of Energy Sources from Mining and Transportation

Fossil fuels like coal, gas, and oil have been the main source of energy in the U.S. and many other countries for decades. By the mid-century, the United States will have rapidly adopted renewable energy sources, resulting in waste from mining, the construction of these systems, and the decommissioning of fossil fuel-based plants. Decommissioning existing fossil fuel combustion power plants and adopting less energy-dense renewable energy sources will increase raw material demand for the construction of these systems and waste generation from the decommissioning of the former. So, the fast adoption of renewable energy sources will affect the demand for raw materials, the transportation of these materials due to a complicated supply chain, and the need to adopt appropriate waste management strategies because the federal government has not yet adopted recycling solar panels or wind turbine blades, and it is not yet financially viable in the United States. At the same time, there are practices that can be adopted from the nuclear energy sector that have a rigorous end-of-life strategy to protect the environment from the impact of spent nuclear fuel. Wind, solar, and coal are all industries that could use some of these practices. More raw materials will be taken out of the ground, creating a lot of mining waste. At the same time, coal and nuclear power plants will be shut down, which will add to the total amount of decommissioning waste produced over the next few decades. To make informed decisions about the environmental impact of different energy sources, one must examine the life cycle of each fuel or technology, from the extraction of the materials to the disposal of residuals (which is called a life-cycle assessment), and calculate the impact of complex logistical systems to build these power systems. In this study, we examine the main ways waste is handled in the energy industry with a focus on mining activities and the amount of waste produced per MWh of electricity generated and per MW of the installed capacity of a project, as well as the amount of carbon dioxide emissions caused by shipping raw materials from all over the world to meet the needs predicted for the next 30 years. The main focus here is on the mining impact: (1) raw material supply is a critical component for any technology; (2) mining waste was not accounted for in previous studies; (3) the mining waste will depend on the raw material list; (4) the mining sector is the area where most of the waste is generated; 5) raw materials make their way through a complex supply chain, adding to the overall carbon emissions. This research demonstrates which systems generate the most waste by mass and require the largest amount of materials required to build such a system and assesses the expected carbon footprint if the U.S. does not adopt localized raw material production practices.

Advisor: Vujic, Jasmina
Wainwright, Haruko
Towards clinical immuno-MPI: Optimizing magnetic particle imaging of superferromagnetic iron oxide nanoparticles and developing MPI leukocyte tracking

Magnetic particle imaging (MPI) is a sensitive, high contrast tracer modality that directly images superparamagnetic iron oxide nanoparticles (SPIOs), enabling radiation-free theranostic imaging. With zero tissue signal, persistent biosafe tracers, and no ionizing radiation, MPI has shown great promise for cell tracking, vascular imaging, and imaging applications. Indeed, its capability for multi-month studies and exquisite contrast position itself uniquely for immune-cell based diagnoses and extended monitoring of immunotherapies. However, MPI resolution is currently limited by scanner and particle constraints. Recent tracers have experimentally shown 10x resolution and signal improvements, with dramatically sharper M-H curves. Experiments suggest that this results from interparticle interactions, conforming to literature definitions of superferromagnetism. We thus call our tracers superferromagnetic iron oxide nanoparticles (SFMIOs). While SFMIOs provide excellent signal and resolution, they exhibit hysteresis, with non-negligible remanence and coercivity. In my dissertation I provide the first report on MPI scanning with remanence and coercivity, including the first quantitative measurements of SFMIO remanence decay and reformation using a novel multi-echo pulse sequence. We also describe an SNR-optimized pulse sequence for SFMIOs under human electromagnetic safety limitations. I separately investigate ex vivo and in situ labeling neutrophils and macrophages and tracking to inflammation and immune activity with XY Zhou and P Chandrasekharan. I demonstrate the first antibody MPI (Ab-MPI) images using antibody-conjugated SPIOs (Ab-SPIOs), showing bone marrow and sites of lipopolysaccharide-induced myositis. Through bioluminescent imaging, electron microscopy, flow cytometry and histopathology, I confirm labeling and tracking of neutrophils and macrophages. Excitingly, our images are able to differentiate between the acute inflammation response from neutrophils, and the chronic response from macrophages. With the resolution improvements from SFMIOs, which could be used to reduce hardware costs by 100x, and the demonstrated applications of Ab-SPIOs, MPI demonstrates incredible potential for clinical diagnosis and immunotherapy monitoring.

Advisor: Conolly, Steven M
Browsing in the Library of Babel: Leveraging Evolutionary Information to Improve Protein Modeling

Proteins are the molecular machines that perform the vast majority of natural biological functions. Discovering proteins to perform novel functions or optimizing them for an existing function are central goals of synthetic biology. Doing so is challenging primarily because for most proteins there is limited understanding of how they function, let alone how to modify them; experimental characterization and crystal structures are expensive and time-consuming to collect. For a given protein, however, genes performing related functions can be found in the the genomes of diverse organisms -- the natural result of the process of evolution. With improved techniques for genetic sequencing, an abundance of data deposited in protein sequence databases has become available. This presents a tantalizing modeling opportunity: models that can understand protein function through the observation of related sequences can reduce the reliance on experimental characterization and unlock new possibilities for protein discovery and optimization. Building such models has been a goal of bioinformatics research, and has more recently emerged as a goal of machine learning research. In particular, ``protein language models,'' models trained to learn a distribution over sequence data, have shown promise in predicting functional properties of proteins./nThis work leverages the information in protein sequence databases to the following ends. First, it presents a benchmark for the effectiveness of protein language models using a suite of protein prediction tasks. Second, it draws a connection between a well-established graphical model of protein families and the neural network architecture of protein language models. Third, it presents a framework for deriving synthetic protein fitness landscapes from evolutionary data that can be used to evaluate strategies for model-guided protein design in silico.

Advisor: Song, Yun S
High-Latitude Carbon Cycling: Improving Mechanistic Understanding of Heterogeneity and Change in Complex Ecosystems

High-latitude ecosystems play a key role in the global carbon cycle. There are large stocks of carbon stored in permafrost soils, protected by freezing temperatures and saturated soil conditions. However, the arctic is the fastest warming region on the planet, and as permafrost thaws much of the carbon will become vulnerable to microbial decomposition. At the same time, warming air temperatures, changing precipitation patterns, increasing nutrient availability, and rising CO2 concentrations will lead to dramatic changes in vegetation dynamics and ecosystem carbon uptake. Because of strong feedbacks and system complexity, current estimates of the impact of climate change on regional net carbon balance are highly uncertain. Indeed, high-latitude carbon cycling was identified in the IPCC AR6 report as one of the largest sources of uncertainty in the global carbon cycle./nThis thesis explores large- and fine-scale controls on high-latitude carbon cycling and examines uncertainties associated with regional estimates of carbon fluxes. This work relies heavily on ecosys, a process-rich mechanistic ecosystem model that has been extensively tested at high-latitudes. After a brief introduction, background on ecosystem ecology and the structure and process representation of ecosys is given. Then, an analysis on the large-scale controls on high-latitude carbon cycling, and how those controls will change with climate change, is presented through the lens of seasonality using ecosys simulations of Alaskan ecosystems. Next, key drivers of fine-scale variability of permafrost distribution, vegetation dynamics, and carbon cycling in a discontinuous permafrost watershed are identified using a sensitivity analysis of ecosys. Finally, machine learning models trained on ecosys outputs are shown to inaccurately predict both current and future high-latitude carbon balances.

Advisor: Riley, William J
Knobloch, Edgar
Mechanisms of the type V CRISPR-Cas12c system

CRISPR (clustered regularly interspaced short palindromic repeats)-Cas (CRISPR-associated) systems are a form of prokaryotic adaptive immunity against invading viruses or plasmids. In these systems, Cas nuclease effectors recognize and cleave foreign nucleic acids containing sequences that are complementary to their associated CRISPR RNA (crRNA) to trigger degradation of targeted sequences. For successful CRISPR interference to occur, the sequences encoding crRNAs must be first acquired from foreign genetic material. These acquired DNA sequences are then transcribed into pre-crRNAs and processed into mature crRNAs that can guide interference against the specific invaders. The type V CRISPR-Cas12c (V-C) system is a compact system that has unique 3’ pre-crRNA processing activity and lacks a cas2 gene that was previously thought to be essential during the acquisition stage for all CRISPR systems. Although the initial activities of this system have been analyzed, the mechanisms by which this system acquires functional spacer, produces its guide RNA, and restricts viral infection are not fully defined. For my graduate work, I addressed the fundamental mechanisms of the type V-C system by determining the mechanisms of Cas12c-mediated pre-crRNA processing and interference. My work has revealed that Cas12c is an RNA-guided DNA binder that does not cleave target DNA. The repurposed RuvC domain of Cas12c exclusively processes pre-crRNA, and maturation of crRNA is essential for efficient Cas12c DNA targeting. Importantly, targeted Cas12c DNA binding can repress transcription and restrict phage infection, accomplishing antiviral interference without chemical attack on the invader. Additionally, I attempted to reconstitute type V-C adaptation in vivo in a heterologous host Escherichia coli with the goal of eventually identifying determinants for adaptational protospacer adjacent motif (PAM) selectivity and looking for evidence of primed type V-C adaptation. Together the investigation described here in this dissertation sheds light on the mechanisms of the compact V-C CRISPR system, allowing for comparison with more complex systems and provides insight into the evolutionary history of CRISPR systems and functions.

Advisor: Doudna, Jennifer
Effects of extreme weather, water treatment, and COVID-19 on water quality and child health in rural Kenya

In 2019, approximately 5 million children died before reaching age five, largely due to preventable or treatable causes. Water treatment could interrupt diarrheal disease transmission, and reduce child mortality, but 2 billion people still lack access to safe water at home. Both climate change and the COVID-19 pandemic may affect the ways in which infectious disease are transmitted. This dissertation examines water treatment and child health in rural Kenya and provides evidence of how climate change and the COVID-19 pandemic have affected infectious disease transmission./nChapter 1 presents background information on the global burden of diarrheal diseases and other diseases associated with poverty, discusses evidence for water treatment as an intervention strategy, outlines the potential implications of climate change and the COVID-19 pandemic, and describes the study areas in rural western Kenya. Chapter 2 provides evidence for the effects of climate change on diarrheal disease transmission by quantifying the effects of extreme weather (heavy precipitation and high temperature) on bacteria levels in two key transmission pathways: drinking water and hands. We find that heavy precipitation and high temperature increase bacteria levels in drinking water but decreases bacteria levels on child hands. The relationship between heavy precipitation and bacteria in stored water holds only when households have not treated their water, suggesting that water treatment is an appropriate mitigation strategy and may be particularly important after periods of heavy precipitation or high temperature. Chapter 3 evaluates one such water treatment intervention at drinking water kiosks in Kisumu, Kenya. The Venturi chlorine doser can be attached to any pipe outflow. We evaluate the technical feasibility and kiosk and customer demand for the device. We find that the device reliably doses water with liquid chlorine. We also find that kiosks were willing to pay to lease or lease-to-own the device, and that customers reported buying chlorinated water. The COVID-19 pandemic has disrupted daily activities world-wide and may have affected infectious disease transmission. Chapter 4 examines the effects of the COVID-19 pandemic on child mortality and respiratory illness in the study area in rural Kenya. Finally, Chapter 5 concludes the dissertation by summarizing my research findings and discussing overarching themes.

Advisor: Pickering, Amy J
Controlling Devices to Achieve Stability Guarantees on Electric Distribution Grids

Due to the massive increase in renewable energy deployment around the world, the distribution level of electric power grids has more active devices than ever before. Many distributed energy resources (DERs) were installed to output the maximum amount of power available without consideration of the grid's status or the presence of other devices. As a result, grid operators can encounter power quality issues, especially voltage volatility, which can stall the adoption of more renewable energy devices. Traditional grid devices that are intended to maintain distribution grid power quality may be insufficient to address today's challenges. While academic literature has proposed many types of approaches to device control, it can favor approaches that are optimization-based at the expense of being impractical for deployment on real distribution grids./nThis thesis argues for the analysis of simple, flexible device controls to improve power quality and power delivery. We take a dynamical systems perspective, which provides transparency into the underlying device interactions. This perspective allows us to develop intuition for device interactions and develop safety guarantees that prevent dangerous behavior. For the important problem of computing DER power injections, we take a holistic approach to controller design, where control parameters and DER siting are analyzed to achieve improved voltage stability. Furthermore, this design is achieved without imposing restrictions on the DER communication network. Next, we consider device design under two important modeling scenarios. First, we consider the case of abnormal voltage events, in which there is a strict time limit during which DERs must recover the voltage before devices must disconnect. Then we model the interaction between inverter-based DERs and load-tap changer devices, to determine parameter relationships that guarantee against voltage oscillations. We conclude with a discussion of future work and as synthesize important principles for device control in power systems.

Advisor: Sanders, Seth
von Meier, Alexandra