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UC Santa Cruz Electronic Theses and Dissertations

Cover page of Responding to an emergent plant pest-pathogen complex across social-ecological scales

Responding to an emergent plant pest-pathogen complex across social-ecological scales

(2021)

Responding effectively to accidental introductions of plant pests (e.g., fungi, bacteria, viruses, animals, plants) is complicated because timely and costly decisions must be made across social and ecological scales with limited information. In this dissertation, I provide an interdisciplinary framework that allows responsible institutions to respond quickly and effectively to an emerging, introduced, multi-host pest-pathogen complex using even minimal knowledge available about pest attributes. First, I take an evolutionary ecology approach and examine how the phylogenetic structure of host ranges of different pest-pathogen combinations can be used to predict likelihoods of establishment, spread, and impacts of Fusarium dieback - invasive shot hole borers (FD–ISHB) in the urban-wildland forests and avocado growing regions of Southern California, where the pest-pathogen complex has established after its introduction from Southeast Asia. Phylogenetic dispersion analysis on a comprehensive FD–ISHB host-range data set shows that the strength of the phylogenetic signal is progressively more pronounced for more severely affected host species. As a basis for risk analysis, this understanding helps plant health first responders assess how any polyphagous pest complex might behave when introduced to novel environments with a new set of possible hosts, which in turn informs more efficient and cost-effective phytosanitary surveillance priorities. Second, I conduct a multivariate analysis of fungi and bacteria cultured from wood in a phylogenetically diverse set of live tree hosts to determine if the structure and composition of tree microbiomes is predictive of the likelihood or outcome of attack by FD–ISHB. I further explore interactions within the microbiome between endophytic microbes and the pathogen to identify potential opportunities and mechanisms to shape disease establishment and spread, and evaluate whether endogenous microbes could be manipulated for sustainable integrated pest management. I found consistent differences in wood-inhabiting microbial communities between avocado, which grows in an agricultural setting, and three wildland tree species (willow, sycamore, and oak), but there were no strong, consistent differences among microbial communities based on host attack status. However, enough differences were detected to suggest that inconsistencies most likely reflect undersampling in the community – a common problem with culture-based studies – which sets the stage for future culture-independent studies that integrate a richer data set into the analysis. Furthermore, 15 fungal species and 11 species of bacteria exhibited clear in vitro antagonism against the pathogen, indicating their potential to confer a protective benefit to tree hosts as biological control agents. Finally, I analyze participant-observation and public-document data to assess the effectiveness of governance processes that influence management decisions in a statewide deliberative and consensus-directed process to control FD–ISHB spread and impacts. I found that the comprehensive set of collaborative actions that emerged from this process were due to conditions identified in theoretical frameworks for collaborative governance and could not have been attained by any organization acting alone. These actions were enhanced by the structure and quality of principled-engagement process elements, which benefited from prior histories of cooperation and conflict. Collectively, this dissertation provides valuable technical and collaborative tools to improve integrated pest management and respond to the large-scale socio-ecological disturbances that accompany invasive, introduced pests.

Novel Gene Expression Analyses to Accelerate Precision Pediatric Oncology Research

(2020)

Cancer is the second leading cause of death in the United States. While there have been medical advances in treating cancer, the standard of care has not changed significantly in recent decades. Chemotherapy, radiation, and surgery are the clinician’s first line of defense against cancer progression, but new therapeutic strategies such as precision oncology are being developed that personalize cancer therapy to individuals. Precision oncology has primarily relied on coding mutations as biomarkers of response to therapies. Numerous challenges have arisen in the incorporation of transcriptome analysis into precision oncology workflows. One such challenge is in the necessary consideration of relative rather than absolute gene expression level, requiring differential expression analysis across samples. However, expression programs related to the cell-of-origin and tumor microenvironment effects confound the search for cancer-specific expression changes. To address these challenges, we developed an unsupervised clustering approach for discovering differential pathway expression within cancer cohorts using gene expression measurements. The hydra approach uses a Dirichlet process mixture model to automatically detect multimodally distributed genes and expression signatures. This led to the identification of recurrent tumor microenvironment signatures across pediatric cancers as well as a relationship between transposable element expression and immune infiltration.

I then developed the vaccinaTE software toolkit to further characterize transposable elements as potential immunotherapy targets. Using RNA-seq and mass spectrometry analysis, I found expression and MHC-bound peptides uniquely mapping to transposable element loci. This led to the creation of a novel process for prioritizing TE vaccine targets as well as a microarray technology for personalizing TE vaccine therapy. To address the need for accurate preclinical models to accelerate drug development for pediatric cancers, I then created a Bayesian hierarchical modeling framework for evaluating patient-derived xenografts. I generated a database of PDX-specific pathway expression to facilitate validation studies that attempt to target differentially expressed pathways. This thesis has sought to improve the treatment of pediatric cancers through the identification of tumor subtypes that respond to specific therapies, identify novel immunotherapy targets based on tumor microenvironment states, and use gene expression analysis to optimize preclinical validation experiments. These methods have been developed for pediatric cancers but can be modified for adult cancers as well as other diseases

for which gene expression data is available.

Plant Response to Land Use Change in Two Iconically Stressful Habitats: California’s Desert Solar Fields and Restored Coastal Salt Marshes

(2020)

This work examines plant response to human alteration in deserts and coastal salt marshes, two systems in which abiotic stress is assumed to limit plants more strongly than biotic factors.

In the desert, I used experimental panels to simulate the effect of solar energy infrastructure on two habitat types. I measured plant diversity and abundance, finding that panels interacted with rainfall and physical features of each habitat type to drive different outcomes. Under panels, diversity and abundance tended to be higher in one habitat type, but lower in the other. I also examined panel effects on the demography of a closely related rare-common species pair. Panel effects on individual demographic rates were rarely strong, but matrix models integrating these effects across the life cycle revealed a negative impact on the rare species, mediated by increased competition under panels. This result highlights the risk of using a common relative to predict impacts on a rare species.

In the coastal salt marsh, I tested whether the Stress Gradient Hypothesis (SGH) can be applied to improve restoration outcomes. The SGH framework predicts that interactions between plants should shift from competition to facilitation as stress increases. I found that soil conditions were more stressful (more negative water potential) at higher marsh elevations, so I expected clustered plantings to do better upslope. I planted two natives in loose and clustered patterns and tracked their performance across elevation for two years. Surprisingly, performance did not vary with elevation during the first year, while clustering had a negative effect on growth. After two years both species showed clear but inverse patterns of cover across elevation – yet across the entire elevation gradient, clustering strongly inhibited cover in both species.

My work demonstrates that even in “stressful” systems, abiotic stress is not always the dominant constraint on plants. To develop effective conservation and restoration strategies in these systems will require a deep understanding of how human disturbance interacts with the biotic and abiotic drivers that govern plant performance.

Specificity in Transcriptional Regulation

(2020)

Gene-specific regulation of transcription is achieved through the binding of transcription factors to DNA sequences. Many Eukaryotic transcription factors maintain affinity differences between target and non-target sequences that appear too small to explain the specificity observed for the genes they regulate. How is specificity achieved in Eukaryotic gene expression? In eukaryotes, DNA is spooled around histone protein octamers to form nucleosomes. The nucleosome represses transcription by acting as a barrier to the binding of transcription factors. Thus, gene activation requires the recruitment of ATP-dependent chromatin remodelers which remove nucleosomes covering important regulatory sequences. However, promoter nucleosome structure is heterogeneous even under activating conditions. Why does the cell expend energy to maintain heterogenous promoter chromatin in the promoters of actively transcribing genes?

In Chapter 1, I present a model of gene transcription which represents a unified solution to these questions, among others. I show that activator mediated ATP dependent stochastic removal and reformation of nucleosomes on promoter DNA may be used for the kinetic proofreading of activator-DNA interactions. The specificity enhancement due to kinetic proofreading is an archetype that, in part, can be used to explain the observed specificity in Eukaryotic gene expression. I show that contrary to expectation, heterogeneity in promoter chromatin structure reduces the variation observed in gene expression. Additionally, I provide insight into the necessity of transcriptional bursting for regulated, highly expressed genes.

In Chapter 2, I present a number of experimental tests of the proofreading model. We observe transcriptional bursting, chromatin remodeling and activator binding at a classic model gene, PHO5, in Saccharomyces cerevisiae. I show that transcriptional bursting of PHO5 occurs in at least two distinct timescales, an expectation of the proofreading model. In addition, I show that mutation of a single chromatin remodeler, Isw2, is sufficient to disrupt correlation at the longer timescale. I present a model of kinetic proofreading of activator specificity by Isw2 and test conjectures such a model purports.

In chapter 3, I present a technique for studying eukaryotic gene expression by generating and testing the expression of >400,000 permuted synthetic cassettes generated from 26 genes from Saccharomyces cerevisiae.

Cover page of Data-Efficient Surrogate Models for High-Throughput Density Functional Theory

Data-Efficient Surrogate Models for High-Throughput Density Functional Theory

(2020)

High-throughput screening of compounds for desirable electronic properties can allow for accelerated discovery and design of materials. Density functional theory (DFT) is the popular approach used for these quantum chemical calculations, but it can be computationally expensive on a large scale. Recently, machine learning methods have gained traction as a supplementation to DFT, with well-trained models achieving similar accuracy as DFT itself. However, training a machine learning model to be accurate and generalizable to unseen materials requires a large amount of training data. This work proposes a method to minimize the need for novel data creation for training by using transfer learning and publicly-available databases, allowing for both data-efficient and accurate machine learning to mitigate the computational cost of DFT.

Cover page of Bridging Intermediate Representations to Achieve Hardware Design Language Translation

Bridging Intermediate Representations to Achieve Hardware Design Language Translation

(2020)

The hardware industry is currently beginning a trend towards a more productive hardware design flow. Many designers have been noticing for years a lack of efficiency when it comes to the design process. In response, research groups have been proposing tools and languages to improve productivity in this domain. Two such examples are LiveHD and Chisel. LiveHD is a framework that seeks to perform live synthesis and simulation, where live means that results for these tasks are achieved in seconds or minutes rather than hours. Chisel is a new hardware description language that focuses on using software abstractions to improve design reuse. The compilers for both works rely upon intermediate representations to model a design for their compiler. Having LiveHD and Chisel interact is currently impossible since the way in which they model hardware designs is different. This paper proposes an implementation of a translator that would bridge the gap between these two research efforts, allowing designers to reap the benefits of both and thus greatly improve their productivity during the design process.

"Water is Sacred! Womxn are Sacred!": Indigenous Womxn's Embodied Knowledge on the Frontlines

(2020)

“Water is Sacred! Women are Sacred!”: Indigenous Womxn’s Embodied Knowledge on the Frontlines engages with the issues of gendered environmental violence by exploring the ways Indigenous peoples, especially Indigenous womxn, continue to fight for sovereignty and environmental wellbeing of the Fourth World. The issue of U.S. colonial state attacks against Indigenous Nations and lands have made it mainstream, and the politics of Indigenous Knowledge begs the question of how to best support activists’ work to transmit environmental knowledge while not erasing the connected issue of localized colonial violence that affects, though differently, every major region in the world. To help make sense of the intersections of gendered violence and environmental degradation, “Water is Sacred! Women are Sacred!” explains why and how IK is mobilized, both as an enactment of anticolonial relations and an identity-knowledge-object, in different forms across the frontlines.

I supplemented participatory observations in Indigenous lead activists’ spaces with archival research and over 30 in-depth interviews with Indigenous activists, mostly womxn. The in-depth interviews, ranging from 1 to over 2 hours each, include mothers supporting the movement through digital activism to internationally known leaders in the United States and Canada. I gathered supplementary materials from Indigenous lead conference proceedings, online archives, and the Freedom Archives in San Francisco.

Water is Sacred! Womxn are Sacred! proposes that to reinvigorate knowledge production as an anticolonial process and strengthen our abilities as radical environmental justice pedagogues, scholars must reimagine Indigenous ways of knowing as more significant than and beyond an intervention to sustainability. In documenting Indigenous womxn’s embodied critiques embedded within their analysis of environmental degradation, the dissertation recasts the seemingly new narratives about recognition and decolonization in mainstream sustainability as modes of extraction. The foundational claim is that U.S. American research bent toward the arch of radical transformation must consider settler colonialism as an ongoing process, especially with understandings of knowledge, law, and power.

Cover page of Measuring the electron and positron primary cosmic ray spectra between 20 MeV and 1 GeV with the AESOP-Lite balloon-borne spectrometer

Measuring the electron and positron primary cosmic ray spectra between 20 MeV and 1 GeV with the AESOP-Lite balloon-borne spectrometer

(2020)

We report a new measurement of the cosmic ray electron and positron spectra in the energy range of 20 MeV and 1 GeV. The data were taken during the first flight of the balloon-borne spectrometer AESOP-Lite (Anti Electron Sub Orbital Payload), which was flown from Esrange, Sweden, to Ellesmere Island, Canada, in May 2018. The instrument accumulated over 130 hours of exposure at an average altitude of \SI{3}{\gram.cm^{-2}} of residual atmosphere. The experiment uses a gas Cherenkov detector and a magnetic spectrometer, consisting of permanent dipole magnet and silicon strip detectors, to identify particle type and determine the rigidity. Electrons and positrons were detected against a background of protons and atmospheric secondary particles. The primary cosmic ray spectra of electrons and positrons, as well as the re-entrant albedo fluxes, were extracted between 30 MeV and 1 GeV during a positive solar epoch. The positron fraction below 100 MeV appears flat, suggesting diffusion-dominated solar modulation at low rigidity. The all-electron spectrum is presented and compared with models from a heliospheric numerical transport code.

Cover page of Santa Cruz Routing Information Protocol

Santa Cruz Routing Information Protocol

(2020)

The Santa Cruz Routing Information Protocol (SCRIP) is a new routing protocol designed to solve performance problems present in current routing protocols used in the Internet. The routing protocols used in the Internet today were created over twenty five years ago and were created with strict limitations of storage and bandwidth in mind. SCRIP builds on the foundation of the RIP to provide shortest path routing for networks within autonomous systems. The problems that SCRIP solves include routing loops, high storage and signaling overhead, and convergence times that may become too long. These problems are solved by maintaining reference distances, supporting both on-demand and proactive routing, and implementing other techniques for the efficient exchange of distance-vector information. The main idea that allows SCRIP to be loop free and therefore more efficient, was introduced in Ordered Distance Vector Routing (ODVR). ODVR is a routing protocol used in wireless ad-hoc networks that showed that it was possible to maintain loop freedom through distance values alone. A formal proof of correctness and completeness shows that SCRIP is able to exhibit loop freedom at every point in its operation. Simulation experiments using ns-3 show that SCRIP performs better than RIP and OSPF in terms of convergence and signaling overhead in a variety of scenarios.

Cover page of Rational Design of High-Performance Electrocatalysts for Electrochemical Energy Technologies: From Structural Engineering of Nanocomposite Catalysts to Mechanistic Understanding of Electrocatalytic Activity

Rational Design of High-Performance Electrocatalysts for Electrochemical Energy Technologies: From Structural Engineering of Nanocomposite Catalysts to Mechanistic Understanding of Electrocatalytic Activity

(2020)

Developing sustainable, high efficiency and clean energy technologies is one of the urgent missions for modern chemistry. Fuel cells with their high energy conversion efficiency, high reliability, low CO2 emission and extensive applications, show promising outlook among all new energy devices. However, the expensive electrocatalyst and their sluggish electrode reaction kinetics greatly hamper the commercialization of fuel cells. Thus, the advanced electrocatalyst should be designed and synthesized, meanwhile, the reaction mechanism should be better understood for material structural modification and activity enhancement. My thesis focused on design, synthesis of nano materials for advanced electrocatalysts and understanding and exploring the catalytic mechanism. Based on series of research projects, a systemic strategy framework for electrocatalyst preparation and understanding is established by combination of experimental and theory method. This framework contains a wide range of aspect of electrocatalyst studies. Specifically, Chapter 1 introduces the background of fuel cell, water electrolyzer and their related critical electrochemistry reactions. A systematic overview of electrocatalyst design, modification and reaction mechanism understanding is illustrated. Based on the current and previous results, the strategy loop and the central dogma of electrocatalyst design is proposed. Each of the work introduced in other chapters was carried out based on one or several aspects of the strategy loop, which including material synthesis, activity measurement, active site revealing, electronic structure understanding, modification of electronic structure. Chapter 2, chapter 3, chapter 4 introduces series work of carbon nanowires for electrocatalyst. These works include the aspects of material synthesis, activity understanding, active site identifying or understanding the source of activity. Specifically, chapter 2 introduces the design and synthesis of a novel nitrogen and iron-doped carbon nanowires material for great activity for alkaline oxygen reduction reaction, with the performance even surpass the commercial platinum carbon. Moreover, the active site was identified, and their activity was compared as the order of Stone-Wales FeN4 sites> Normal FeN4 sites> neighboring carbon atom of nitrogen atom in the carbon matrix. In addition, the source of activity of each important activity site were also revealed. The great activity of FeN4 comes from the d-orbital of Fe atom provide great chance for oxygenous intermediate species to absorb and detach. While, the neighboring carbon to nitrogen atom have much better ability for adsorption than normal carbon, due to the charge transfer from themselves to the nearby nitrogen atoms. Chapter 3 introduces the design and synthesis of novel ruthenium and nitrogen doped carbon nanowires for excellent activity for hydrogen evolution reaction in alkaline electrolyte, with the performance better than commercial platinum carbon and other noble metal-based material as reported previously. Moreover, it was identified that the activity is coming from a novel single atom ruthenium site, RuC2N2 structure embedded in the carbon, other than ruthenium nanoparticle or normal RuN4 sites as assumed previously. The ruthenium and its neighboring carbon atoms of RuC2N2 can provide efficient water dissociation process which is critical for overall reaction. Chapter 4 introduces a typical work for adopting theoretical calculation to reveal active sties and for guiding experimental electrocatalyst synthesis. In this work, a high throughput first principle calculation was first carried out and find that the platinum needs a minimum domain size (about 0.9 nm of diameter) to maintain activity for catalyzing oxygen reduction reaction. Any platinum species smaller than that limit will suffer great difficulty of adsorbing oxygen molecules due to the lack of states and electron near Fermi level. Moreover, it was further revealed cobalt atom doping can greatly assist in oxygen adsorption when the domain size of platinum is too small. The following experimental work confirmed the theoretical finding and successfully synthesized PtCo few atom clusters as high efficiency electrocatalyst for oxygen reduction reaction, which can have an ultrahigh mass activity as much as 48 times better than commercial platinum carbon. Chapter 5 and chapter 6 mainly focus on several individual works about interfacial charge transfer of nanomaterial and its induced electrocatalytic activity enhancement. For instance, Chapter 5 introduce several works about charge transfer induced electrochemical activity enhancement. In one work, it was observed oxygen vacancy doped TiO2 can transfer electrons to the palladium nanoparticles loaded on them. This charge transfer can significantly enhance the activity of ethanol oxidation reaction catalyzed by palladium nanoparticles. In another work, it was found that black phosphorus can donate significant number of electrons to the platinum, gold and silver nanoparticle load on it. This charge transfer can induce the activity decrease for platinum nanoparticles and increase for gold and silver nanoparticles towards oxygen reduction reaction. Chapter 6 introduces developing new methods for charge transfer. Specifically, TiO2 nanoparticles functionalizing with alkyne ligand can induce significant one-way charge transfer from ligand to surface of metal oxide through M-O-C≡C- core-ligand linkages. This linkage can also induce novel states inside of band gap. Moreover, this unique charge transfer can be universally observed on other metal oxide, exhibiting a powerful ability for increasing the charge density of metal oxide catalyst. Finally, all of finding are systemically summarized in chapter 7. In addition, a perspective of future works was put forward based on the previous works.