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Genomic resources for the study of anisogramma anomala and the Eastern filbert blight pathosystem
No full textCommercial production of European hazelnut (Corylus avellana) in the United States is severely limited by Anisogramma anomala, the causal agent of Eastern Filbert Blight (EFB). Research efforts have identified a resistance gene from ‘Gasaway’ that confers complete resistance to EFB. Hazelnut breeding programs have since integrated the so-called ‘Gasaway’ R gene into a range of EFB resistant C. avellana cultivars despite concerns over single gene resistance. In the years since, these ‘Gasaway’ protected hazelnut trees have held up poorly in New Jersey and succumbed to EFB. Despite the economic importance of A. anomala, little is known about this pathogen, largely due to methodological difficulties associated with laboratory-based experimentation on biotrophic pathogens. The purpose of the following works is to apply genomics to elucidate the biological properties of A. anomala and the EFB pathosystem and determine the cause of ‘Gasaway’ resistance breakdown in New Jersey. The genome of a strain of A. anomala isolated from Oregon was sequenced and annotated to provide a reference genome for future study of EFB. The massive 350 Mb genome reveals features that are consistent with other biotrophic plant pathogens, including the proliferation of transposable elements, species-specific gene families with functions related to pathogenesis, and a large cache of putative effector genes. A. anomala also exhibits a genome with bipartite architecture, fitting the “two-speed” genome model, providing a mechanism by which genome evolution occurs. Simple sequence repeat (SSR) markers derived from the genome sequence were used for genetic fingerprinting of a controlled inoculation evaluating the breakdown of ‘Gasaway’ resistance in New Jersey. The results indicate a genetic shift in the population of A. anomala, suggesting the emergence of a novel pathotype of the fungus that is responsible for the compatible plant pathogen interaction and the incidence of EFB observed in New Jersey. Finally, the genome of the ‘Gasaway breaker’ pathotype was sequenced and utilized in a comparative genomics approach with other pathotypes, including the reference strain. The results of the comparative genomics study reveal the expansion of gene families that encode putative effectors with novel functions in the ‘Gasaway breaker’. Evidence of transposable element insertion into genomic regions corresponding to genes encoding effectors suggests that transposon activity may contribute to the mechanisms by which A. anomala is evolving to overcome ‘Gasaway’ mediated resistance. Taken together, these works provide a genetic basis for the breakdown of ‘Gasaway’ resistance in New Jersey and the biological features of A. anomala that enable the pathogen to evolve and adapt to a resistant host population.Ph.D.Includes bibliographical reference
Dual functions of a biosynthetic enzyme, QueE in cell division and translation in E. coli
No full textBacteria have evolved a complex array of mechanisms that allow them to sense and respond effectively to various challenging environmental conditions. These signaling pathways lead to the activation of specific genes tailored to mitigate the detected stress. This stress response can trigger secondary roles of proteins, but the mechanisms by which this occurs are not always clear. In this thesis, I investigate the non-canonical roles of an epitranscriptomic enzyme QueE in Escherichia coli outside of its function in queuosine (Q) tRNA modification. Under stress conditions induced by exposure to cationic antimicrobial peptides such as C18G, E. coli strongly activates the well-studied PhoQ/PhoP two-component signaling system, leading to the upregulation of QueE. Elevated levels of QueE protein result in its co-localization with the cell division protein FtsZ at the septum, inhibiting division and causing filamentous growth. However, whether the dual roles of QueE are functionally linked, the precise mechanism of inhibition of septation by QueE, and other roles of QueE outside translation and septation inhibition were unclear.In my research, I show that QueE affects cell size in a dose-dependent manner and use alanine scanning mutagenesis to identify residues that distinctly contribute to either Q biosynthesis or cell division regulation, revealing QueE as a moonlighting protein. Further, this work demonstrates that QueE orthologs from enterobacteria like Salmonella enterica and Klebsiella pneumoniae also cause filamentation, whereas orthologs from more distantly related bacteria such as Pseudomonas aeruginosa and Bacillus subtilis do not. Our comparative analyses pinpoint a unique region responsible for QueE’s regulatory function in cell division. To examine the mechanism of QueE-mediated cell division inhibition, I performed mechanistic studies using fluorescently tagged divisome proteins under PhoQP activation. These experiments reveal that QueE does not affect the early steps of cell division but instead blocks septation by interfering with the recruitment of late-stage divisome proteins. Further, I identify cell division proteins that genetically suppress PhoQP-dependent QueE-mediated filamentation.
Additionally, I explore the activation of the PhoQP system and related phenotypes using engineered derivatives of the antimicrobial peptide LL37, which is found as part of human innate immunity. Using single-cell fluorescence reporter and phenotypic assays, this work demonstrates that these peptides, like other cationic antimicrobial peptides, trigger PhoQP activation, leading to QueE-dependent filamentous growth. Additionally, I probed the role of MgrB, a negative inhibitor of the PhoQ sensor kinase in responding to the antimicrobial peptides. The findings provide new insights into the interaction of PhoQ with antimicrobial peptides, MgrB, and magnesium ions.
Finally, to investigate how QueE affects global gene expression in E. coli, we performed RNA-seq and ribosome profiling analysis using wild-type and queE deletion strains. The data reveal that QueE influences metal homeostasis (especially copper) and other metabolic pathways, suggesting roles beyond Q-biosynthesis and cell division inhibition. Overall, my work establishes QueE as a dual-function protein, with pleiotropic effects across diverse cellular processes, from RNA modification and cell division to stress response and metabolism. Moonlighting proteins like QueE challenge the conventional "one gene, one enzyme, one function" model and highlight their importance to bacterial stress response.Ph.D.Includes bibliographical reference
Graph generation motion planning
No full textMotion planning is a critical and foundational task in robotic systems. It aims to find high-quality, collision-free paths within the configuration space. While learning-based GNN planners have nearly reached their performance limits and demonstrating significant advantages over traditional non-learning-based planners, they still rely on RGGs generated by KNN. Although this approach enhances planning speed, additional techniques, such as path smoothers, are often required to improve path quality. Moreover, these planners are not adapted to dynamic environments. To address these limitations, this thesis introduces GGMP, a Graph Generation Motion Planning network, which directly operates on sampled points in the workspace without relying on RGGs. By employing a customized model architecture and a novel training mechanism, GGMP generates graph representing potential paths and identifies the optimal path in the graph. Experimental results on 2D mazes validate GGMP's feasibility as an innovative direction for GNN-based motion planning and highlight its potential for further development in dynamic environment planning.M.S.Includes bibliographical reference
The role of fibroblast growth factor 15/19 (fgf15/19) in regulating circadian energy metabolism and liver tumorigenesis
No full textEndocrine fibroblast growth factor 15/19 (mouse FGF15, human FGF19) functions as a crucial regulator of bile acid (BA) synthesis, lipid and glucose metabolism, and hepatocellular proliferation. Ileum-derived FGF15/19 is induced by the nuclear receptor Farnesoid X receptor (FXR) that is activated by increased BAs postprandially. Released FGF15/19 travels to the liver via portal venous circulation and binds to FGF receptor 4 (FGFR4) and co-receptor β-Klotho in hepatocytes to mediate relevant intracellular pathways, leading to the suppression of BA synthesis and gluconeogenesis, and enhancement of protein and glycogen synthesis in the liver. Recent investigations have shown that various mutations including missense mutation, gain-of-function, and loss-of-function mutations in Fgf15/FGF19 gene are associated with the onset, development and progression of hepatic metabolic diseases including metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH). These findings suggest that enhancement of endocrine FGF15/19 signaling may potentially provide therapeutic strategies for MASLD and MASH prevention and/or treatment. Accumulating evidence indicates that chronic disruption of circadian rhythms caused by shift work, jet lag, or light--at-night (LAN) is associated with an increased risk of metabolic diseases and cancers in animal models and humans. Restoring and enhancing circadian homeostasis can help regulate metabolic processes such as glucose, BA and lipid metabolism, thereby preventing against metabolic disease development. Therefore, it is important to investigate the potential signaling pathways that connect circadian rhythms with energy metabolism, which may influence the disease onset and development. Hepatocellular carcinoma (HCC) is a primary malignancy of the liver and is one of the most common causes of cancer death worldwide. The most important and severe liver-related complication in MASH is the development of HCC. It is well established that FXR deficiency leads to spontaneous HCC in Fxr knockout (KO) mice. FXR can prevent HCC development in both BA-dependent and -independent pathways, and FGF15 is also involved in regulating a variety of liver functions. Thus, it is important to investigate the role of FGF15 in HCC initiation and promotion induced by FXR deficiency. The present studies demonstrated the disruption of central (melatonin and cortisol) and peripheral (clock genes (CGs) and clock-controlled genes (CCGs), nicotinamide adenine dinucleotide (NAD+)-dependent sirtuin 1 (SIRT1) signaling, and FGF15-BA signaling) clock markers in night shift (NS) versus day shift (DS) nurses. The results findings indicate that desynchrony of circadian internal network and misalignment with external lighting and behavioral activity (rest/active and fasting/eating) schedules among shift workers contributes to metabolic dysregulation and increases the risk for metabolic diseases and cancers. In addition, FGF15/19 may be able to restore circadian expressions of genes involved in circadian rhythms and BA and lipid metabolism through the increase of NAD+-dependent SIRT1 signaling, leading to prevention against liver metabolic diseases associated with circadian disruption of energy metabolism. Lastly, our studies found that FGF15 overexpression prevented spontanoues HCC development caused by FXR deficiency. Both lower BA levels and reduced growth signaling pathways that are consequences of FGF15 overexpression maybe responsible for the reduced HCC carcinogenesis.Ph.D.Includes bibliographical reference
Curve neighborhoods and gromov–witten invariants of Pieri type
No full textIn this thesis we present two independent results related to the Quantum Cohomology and the Quantum K-theory rings of flag varieties.In the first part, we prove an explicit description of a two-pointed curve neighborhood Γd (Xw0 w , X u ) as a Schubert variety, where w ∈ W comin and X is a flag variety of type A. We also prove a reduction result that works in all types, that the description holds in if it holds for a flag variety defined by a maximal parabolic.
In the second part, we consider a maximal orthogonal grassmannian X = OG(n; 2n), and compute its K-theoretic Gromov–Witten invariants Id (XP , X Q , X p ) where XP, XQ are Schubert and opposite Schubert varieties, and X p is an opposite Schubert variety of Pieri type. Along the way we prove a parametrization conjecture for Richardson varieties in submaximal orthogonal grassmannians Y = OG(m; 2n) stated by Ravikumar.
The first result confirms a conjecture of Buch–Chaput–Perrin in type A, while the second result extends the results of Buch–Chaput–Perrin and Ravikumar in type D.Ph.D.Includes bibliographical reference
Analysis of genomic differences in SARS-CoV-2 variants, and its Impacts on transmissibility and virulence: Washington and Florida states
No full textThis purpose of this study was to analyze genetic differences between SARS-CoV-2 and its variants, examine how these genetic differences relate to SARS-CoV-2 transmissibility and virulence, and determine the impact of SARS-CoV-2 transmission and virulence for different regions – Washington and Florida – in the United States. Methods: Genetic sequences of SARS-CoV-2 variants were obtained from the National Institutes of Health/National Center for Biotechnology Information and analyzed for genetic variations by the NIH/NCBI Sequence Alignment Tool and the Coronavirus Typing Tool. Data collected by the Center for Disease Control and Prevention, US Department of Health and Human Services, Global Initiative on Sharing All Influenza Data, CoVariants, and Washington State Department of Health was compiled to analyze SARS-CoV-2 health statistics and circulating variants between June 2021 and June 2022. Pearson correlations, unpaired t-tests, and linear regressions were conducted to assess the relationships between health statistics, variants, and region. Results: Alpha, Delta, and Omicron variants had acquired genetic mutations from the original SARS-CoV-2 strain, with Delta obtaining the most. Washington and Florida saw significant relationships between Delta and Omicron and transmissibility; however, no variant had a significant relationship with virulence in either state. similarly, experienced transmission similarly but had significant differences for SARS-CoV-2 virulence. Conclusion: This study shows that Sars CoV-2 Delta and Omicron had significant genetic mutations than Alpha. Omicron being the most significant in both states for transmissibility – cases and hospitalization. The virulence (death) was significantly different between both states.Ph.D.Includes bibliographical reference
An examination of the social and economic factors contributing to HIV prevalence among Black women in Texas
No full textThe social determinants of health (SDoH) are defined as the daily settings where people live their lives. They include community / social context, income, education, food security, healthcare systems, and neighborhood /physical environment. Exposure to violence, which for the purposes of this study is a proxy for neighborhood /physical environment, is known to be associated with an increased risk for HIV infection and has been demonstrated in the literature for many decades. Community and interpersonal violence (CIPV) is defined as the ratio of property and violent crime per capita, and a higher level of CIPV has been shown to be a significant indicator of the inability to maintain optimal health for people living with HIV, especially for poor minority women. Past studies, including a 2017 unpublished manuscript and a 2018 study, highlighted significant relationships between high CIPV levels and adverse health outcomes. METHOD: This current study builds upon previous research by examining the impact of CIPV and other SDoH indicators on HIV prevalence and viral suppression among BWLH in Texas. The analysis included various factors, such as food insecurity, income, and social/environmental context, focusing on the top five cities/counties in Texas with the highest HIV prevalence. Multiple logistic regression and statistical correlations were calculated to understand the strength of associations between these indicators, HIV prevalence among Black women, and health outcomes.
RESULTS: Strong correlations (ranging from 0.80 to 0.91) were found between multiple SDoH indicators and HIV prevalence among BWLH. Violence-related factors showed very strong associations, with a negative correlation of 0.88 with viral suppression. Conversely, higher income levels were positively correlated (0.91) with improved viral suppression. These findings underscore the significant impact of violence and other SDoH factors on HIV prevalence and health outcomes. CONCLUSIONS: This research highlights the overwhelming influence of social determinants of health, especially violence-related factors, on HIV prevalence and health outcomes among Black women living with HIV in Texas. These findings emphasize the critical relationship between social determinants of health (SDoH) and HIV prevalence, as well as the impact on health outcomes, such as viral suppression, among Black women living with HIV in Texas.Ph.D.Includes bibliographical reference
Examining Romina’s Growth in Reasoning and Collaboration in 10th & 12th Grades
No full textThis is Analytic 2 (of 3) of "Tracing Romina’s Growth In Reasoning And Sense-Making about Math Problems and Development of Beliefs about Math Teaching/Learning"This analytic examines the development of Romina’s problem-solving heuristics and examples of her behaviors in collaborative settings in tenth and twelfth grades. We watch Romina argue, make meaning, and generalize as she revisits the Tower Problem through an extension known as “Ankur’s Challenge.” Two years later, we witness her engagement with the Taxicab Geometry task as a senior in high school and ultimate connection to the isomorphism of this task with Pascal’s Triangle and Towers Problem. As examined by Steffero (2010), Romina’s mathematical behaviors in these high school episodes include a variety of questioning in collaborative settings that seek information, make suggestions, ask for explanation, or reiterate others’ ideas. We also watch Romina’s justification and generalization develop as she incorporates other’s ideas through collaboration to refine her problem-solving strategies and representations as well as ultimately make convincing arguments for her peers.References Steffero, M. (2010). Tracing beliefs and behaviors of a participant in a longitudinal study for the development of mathematical ideas and reasoning: A case study. Rutgers The State University of New Jersey, School of Graduate Studies
Towards socially aware visual navigation with hierarchical learning
No full textReinforcement learning (RL) has made significant strides in the last few years by proposing increasingly more complex networks that use larger and larger amounts of data to solve a vast host of problems, from playing games to autonomous navigation. Continuing along this trajectory is infeasible for those who do not have access to the large amounts of computing power, data storage, or time required to perpetuate this trend. Additionally, these networks suffer from low sample efficiency and struggle to generalize to out of distribution data. This thesis proposes that leveraging the hierarchical structure inherent in many real world problems, specifically navigation, while efficiently incorporating socially cognizant design into model training and ideation can provide an alternative to this data- and compute-hungry approach. We start with the hypothesis that using networks that mirror the hierarchical structure inherent in many tasks will allow for better overall task performance using simpler networks. We take inspiration from the temporal abstraction of human cognitive processes and compare the performance of several flat neural network architectures and hierarchical paradigms in the maze traversal task. The temporally abstracted actions, also called subroutines, of hierarchical networks happen over multiple time steps and allow agents to reason over complex skills and actions (like leaving a room or going around a corner) instead of low level motor commands. We find that learning a policy over these temporally abstracted actions leads to faster training times, more training stability, and increased accuracy over standard RL or supervised learning with LSTMs. Using this insight, we next explore whether a predefined set of subroutines used by hierarchical networks provides better performance than a learned set. We create a hierarchical framework, comprised of a manager network that passes information to a worker network via a goal vector, for autonomous vehicle steering angle prediction from egocentric videos. The manager network learns an embedding space of subroutines from historical vehicle information. This learned subroutine embedding from the manager allows the worker network to more accurately predict the next steering angle than when using predefined subroutines. Additionally, this hierarchical framework shows improvements over state of the art steering angle prediction methods. In the real world, it is uncommon for the full set of subroutines needed to accomplish a task to be known a priori. Additionally, in order to have a complete autonomous navigation agent, it is imperative that the agent has a model of pedestrian behavior. In the next set of experiments, we aim to address these concerns by building a network to learn a dictionary of pedestrian social behaviors in a self-supervised manner. We use this dictionary to analyze the relationship between pedestrian behavior and the spaces they inhabit as well as the relationships between subroutines themselves. We also use this behavior embedding network in a hierarchical framework to constrain the state space for a worker network, allowing for future pedestrian trajectories to be predicted using a very simple architecture. Finally, we combine our findings into a hierarchical, socially cognizant, visual navigation agent. Instead of formalizing navigation into a traditional reinforcement learning framework, we implicitly learn to mimic optimal human navigation policies from collected demonstrations for the image-goal task in a simulated environment. We build a hierarchical framework with three levels. The first network builds a latent space that acts as a memory module for the navigation agent. The second network predicts waypoints in the current observation space indicating which area of the environment to move towards. The third network predicts which action to execute in the environment with a simple classifier network. The key to this method's success is that each of these networks operates at a different temporal or spatial scale, thus allowing them to bootstrap off of each other to incrementally solve a much larger navigational task and achieve SOTA results without the use of RL, grpahs, odometry, metric maps, or other computationally complex and memory intensive methods.Ph.D.Includes bibliographical reference
A combinatorial topological method for the global dynamics of parameterized ODEs
No full textWe introduce a combinatorial topological framework for characterizing the global dynamics of ordinary differential equations (ODEs). The approach is motivated by the study of gene regulatory networks, which are often modeled by ODEs that are not explicitly derived from first principles. The proposed method involves constructing a combinatorial model from a set of parameters and then embedding the model into a continuous setting in such a way that the algebraic topological invariants are preserved. In this manuscript, we build upon the software Dynamic Signatures Generated by Regulatory Networks (DSGRN), a software package that is used to explore the dynamics generated by a regulatory network. By extending its functionalities, we deduce the global dynamical information of the ODE and extract information regarding equilibria, periodic orbits, connecting orbits and bifurcations. We validate our results through algebraic topological tools and analytical bounds, and the effectiveness of this framework is demonstrated through several examples and possible future directions.Ph.D.Includes bibliographical reference