UC Riverside

Oscillations in protein levels or activation state are ubiquitous in eukaryotic signaling pathways, but the function of these oscillations remains unclear. We find that p38α MAPK activation state oscillates at multiple frequencies in response to stress rather than at a singular frequency. Fourier analysis of p38α activation state measured with a novel FRET sensor shows that unique stressors including IL-1β, SARS-CoV-2 Spike protein, and sorbitol induce unique response patterns in the frequency domain. Analysis of statistically over represented frequencies suggests that frequency bins are fixed and organized as harmonics with a fundamental frequency of 0.09 hr−1(p=0.04). Cross spectral dynamics between p38α and a substrate indicate that substrate activation behaves similarly to a forced oscillator system being driven at resonance. We have developed a model that characterizes the MAPK phosphorylation cascade as a chemical resonator that impart multiple frequencies on p38α, allowing the kinase to regulate its substrates through resonance selectivity. Stochastic simulations of substrates being driven on and off-resonance produce spectra comparable to experimental data.

Experiments on E. coli expressing a transposon of the IS200/IS5605 family reveal that expression of transposon protein TnpB leads to a higher excision rate. Furthermore, cells that excise possess TnpB at a significantly higher expression level than cells that don’t, with TnpA expression levels making no discernible difference in excision dynamics.

We present a protocol for purification of SARS-CoV-2 structural proteins using a bacterial expression system, SUMO tags, and affinity purification methods. We further report a method to insert synthesized dimers into a suspended lipid membrane in a homogeneous orientation. AFM and Cryo-EM in tandem with molecular dynamics simulations show membrane thinning around the M protein and a propensity to induce local membrane curvature.

Urban systems, or socio-ecological systems, are complex on fine and coarse scales, and are important to humans through the effects of ecological processes. Nitrogen pollution is uniquely altered by humans and variable on fine spatial scales with understudied potential sources and sinks. We found local atmospheric nitrogen pollution concertation in Riverside correlated with traffic as a pollution source, but plant canopy did not act as a significant source. Atmospheric pollution does not remain within city limits, and effects in natural systems can be observed in the air, canopy, and soil. We observed a deposition gradient, with decreased atmospheric nitrogen further from urbanization. However the pattern was not consistent for nitrogen in the canopy and the soil, highlighting a disconnect in the gradient and the complexity of teleconnections. Urban ecology affects humans in socioecological systems and plays an important role in science policy. The Salton Sea is a hyper-resilient ecological crisis that fits within the framework of wicked problems. Through research on existing government policy and interviews with key stakeholders, we identified issues that potentially keep the sea in a degraded state and recommendation via resilience theory to address the wicked problem. The dissertation as a whole seeks to improve understanding of socio-ecological systems across scales, and quantify variation in ecosystem processes and nitrogen patterns within and beyond urban areas.

Species extinction is increasing due to anthropogenic threats such as climate change and land-use change. Thus, there is increasing interest in predicting the future fate of species and implementing effective management strategies. In this study, we used spatially-explicit stochastic population models to simulate future projections of three Monkeyflower species, Erythranthe cardinalis, Erythranthe lewisii, and Erythranthe guttata, under climate and land-use change in their regional habitat range in the California Floristic Province. We compared future population projections of two of the three Monkeyflower species, sub-divided into lower and higher elevation ranges, to examine the role of elevational differences in life history parameters in the persistence of the species under projected habitat changes. Lastly, due to the appearance of oscillations and declines in population trajectories of one Monkeyflower species, we explored the role of small, colonized patches on population trajectories. The modeling framework linked species distribution models (SDMs) with population models and dispersal modes parametrized with a combination of multi-year population census data, information from the literature, and publicly available environmental data, including temperature and precipitation projections under two climate scenarios and two climate models. Due to high population growth rates, all three species were limited by changes in habitat due to climate and land-use change. However, subpopulations of E. cardinalis had a low population growth rate at lower elevational ranges leading to extirpation in that region. Conversely, E. lewisii had a high population growth rate but experienced substantial declines in suitable habitat. In the population trajectories of E. lewisii, damped oscillations were observed stemming from a combination of high growth rates and colonization of new small patches which paradoxically reduced the overall population size across the metapopulation. This study highlights the importance of examining small-scale local spatial and demographic characteristics and dynamics, as opposed to large-scale regional habitat and population projections, in understanding the drivers of declines and extinction.

Annotinolides A and B are 7,8-seco¬-lycopodane-derived 8,5-lactones isolated from the club moss Lycopodium annotinum. Preliminary investigations revealed amyloid-beta (Aβ) anti-aggregation properties that are not commonly observed in Lycopodium alkaloids, demonstrating potential as a therapeutic agent for Alzheimer’s disease (AD). AD is characterized by progressive cognitive decline and memory loss that remains a significant challenge in modern medicine. These derivatives show promise in mitigating AD pathology by modulating neurotransmitter levels, reducing oxidative stress, and inhibiting Aβ aggregation, a hallmark of AD progression. Given the history and knowledge of Lycopodium alkaloids in promoting healthier connections between nerve cells in the brain, a streamlined and targeted synthesis was conceived towards annotinolides A and B. Our synthesis design features an inverse electron-demand Diels–Alder reaction to access the tricyclic lycopodine-type skeleton, bioinspired radical cyclopropanation, and photochemical [2+2] cycloaddition. Efforts towards the synthesis of the key tricyclic intermediate will be described.Tetrahydroisoquinoline (THIQ) alkaloids belong to another class of natural products that are ubiquitous in nature, exhibiting multifaceted pharmacological properties, including anti-inflammatory, antioxidant, and anti-apoptotic activities. More specifically, numerous studies have identified protoberberine natural products as potent modulators of AMP-activated protein kinase (AMPK), a key enzyme involved in energy metabolism regulation. Although AMPK activation is widely recognized, its counterpart remains underexplored, demanding the use of powerful synthetic tools to access novel AMPK inhibitors. To this end, a concise synthetic strategy was developed that showcases novel oxidative C–H functionalization and anionic aza-6π electrocyclization methodologies. Heteroatom-substituted alkynes, categorized as subgroups of alkynes, have recently found extensive use in the development of synthetic methods. Ynamides in particular, characterized by their polarized triple bonds directly linked to a nitrogen atom, have recently emerged in C–H functionalization processes. The challenge of effectively and selectively transforming C−H bonds stems from their high bond dissociation enthalpy and widespread occurrence throughout organic molecules. To overcome this challenge, a common strategy involves utilizing a weakly coordinating Lewis-basic directing group. Building on the oxidative rhodium-catalyzed C−H functionalization of electron-rich alkenes (Chapter 2), the combination of N-methoxybenzamides with underexplored electron-rich ynamides is examined, unveiling unique regioselectivity that features cobalt-catalyzed C–H activation.

Since the discovery of graphene in 2004 a host of materials has been growing inthe 2D limit including semiconductors, superconductors, and topological insulators, all of which exhibit a range of unique properties. These crystals are defined by consisting of few- atom-thick sheets which can be stacked upon one another into a myriad of combinations of heterostructures with atomically sharp interfaces that effectively become fundamentally new quantum materials. But it wasn’t until 2017 that long-range magnetic ordering was observed in such systems. Bringing magnetism to the 2D regime similarly opens many doors. For example, magnetic anisotropy introduces novel interactions, and topological phenomena are more easily observed. In this thesis, I present experiments on magnetic van der Waals (vdW) materials that share similar properties such as perpendicular magnetic anisotropy (PMA) and the presence of topological spin textures. My main method of probing these phenomena is a scanning probe technique known as magnetic force microscopy (MFM), a 2D imaging technique which is sensitive to the stray fields of the spins within a magnetic sample. I also employ a relatively new approach to probe the interlayer exchange coupling of such magnetism using a quartz tuning fork (QTF) as a strong oscillator rotated within an external magnetic field to perform Differential Torque measurements. The results show incredible promise for a family of materials that can exhibit similar behaviors with their own unique flavors under varying circumstances. As the synthesis of vdW magnets becomes more routine, the techniques utilized in these studies help to establish a workflow for characterizing and probing the many unreal- ized magnetic materials on the horizon. Additionally, the skyrmions observed in Fe3GeTe2 pave the way for spintronic techniques and applications. Finally, the topological magnetic textures imaged from Fe-doped TaS2 provide insight and additional contribution to a rel- atively young and every growing body of knowledge in the facet of magnetically doped transition metal dichalcogenide (TMD) systems.

A fundamental aspect of goal-directed behavior involves the capacity to selectively respond to specific stimuli during the decision-making process. My dissertation project is dedicated to uncovering the associations between changes in behavioral outcomes and the broader patterns of cortical activity as mice acquire proficiency in the selective detection task. In our research, we aim to delve into the neural mechanisms that underlie sensory selection (sensory detection and impulse control), employing the Widefield Calcium imaging technique. To achieve this, we conducted a training regimen with mice, employing a whisker-based selective detection paradigm where they learned to respond to preferred target stimuli while disregarding non-preferred distractor stimuli throughout the learning process. Notably, mice that achieved expertise in the task demonstrated a clear attenuation of sensory-to-motor signal propagation in distractor-aligned cortical regions. Additionally, we explored the impact of prestimulus activity in the neocortex on stimulus detection. We observed that reduced prestimulus activity in the dorsal cortex correlated with improved stimulus detection, predicting whether a response would occur or not, and resulting in faster reaction times. Finally, we investigated whether learning the selective detection task induces widespread changes across the cortex, examining whether alterations in specific behavioral measures can be linked to distinct cortical modulations. Our results showed that the learning process entails extensive neocortical adaptations as mice advance to expert-level performance in the task. This research offers valuable insights into the learning mechanisms involved in the selection process, with potential applications for understanding impairments in learning trajectories observed in certain mental health disorders.

The two-dimensional Euler equations describe the velocity of an inviscid incompressible fluid. A classical vortex patch is a solution to the two-dimensional Euler equations whose initial vorticity is the indicator function of a bounded simply connected open region in the plane. Properties of the flow maps and vorticity transport in two dimensions ensure that the vorticity at any time will be the indicator function of the the image of the region, which remains simply connected and bounded. In 1991, Chemin proved in [Che91] that, in the whole plane, a vortex patch with an initially Holder continuous boundary maintains that boundary regularity for all time. A few years later, Serfati published an alternate strategy in [Ser94b] that simplifies certain aspects of Chemin's argument. Here, we prove that, for 0 < α < 1, C^{1,α} regularity of a vortex patch boundary persists for all time for fluids in a simply connected bounded domain that itself has a smooth boundary, as long as the patch is initially not touching the boundary. The proof reproduces a 1998 result of Depauw ([Dep98]) using simpler methods inspired by Serfati's approach, which is more easily adaptable to a bounded domain than the methods of Chemin and Depauw.

Anthropogenic global climate change can disrupt plant-pollinator interactions by altering the traits, phenologies, and distributions of interacting species, exacerbating insect declines and compromising ecosystem function. However, most research has focused on diurnal pollinators, and little is known about the prevalence, importance, and vulnerability of nocturnal moth pollination. This knowledge gap limits our ability to predict and mitigate the effects of climate change and other stressors on moths and their pollination services. In this dissertation, I investigate the ecology of moth pollination interactions, how moths and their host and nectar plants will be impacted by climate change, and how to apply this knowledge in conservation strategies. I focus on native plants and moths in California, a biodiversity hotspot that is particularly impacted by climate change. I employ techniques ranging from greenhouse experiments to DNA metabarcoding to explore impacts spanning the levels of functional traits to ecological networks. In Chapter 1, I document hundreds of previously undescribed moth pollen-transport interactions along an elevational gradient spanning desert to conifer forest. I also find that moths are smaller, less diverse, and more sensitive to the simulated loss of their nectar plants in hotter and drier conditions. In Chapter 2, I reveal that experimental warming and drought alter diel patterns of floral nectar quantity and quality in a generalist plant. This may differentially affect interactions with diurnal and nocturnal pollinators, scaling up to alter the structure and stability of plant-pollinator interaction networks. In Chapter 3, I analyze and compare Lepidoptera-host and -nectar plant interaction networks across California, revealing structural differences and spatial patterns that inform management priorities. I also analyze species roles in networks to identify spatially-explicit keystone plant species to be used in butterfly and moth conservation efforts. Together, my results reveal that moth pollination interactions are diverse, complex, and vulnerable to climate change, and that data-driven conservation strategies can help protect them. Ultimately, this dissertation highlights the importance of considering the nocturnal components of plant-pollinator networks in research and management.

This thesis consists of two parts.

In the first part, we develop a model that will be used to investigate pavement cell morphogenesis. Pavement cells, the leaf epidermal cells in the Arabidopsis thaliana plant, have complex jigsaw puzzle piece shapes. The formation of these interlocking shapes relies on mechanical, chemical, and cell to cell signals at different scales. Because of this, pavement cells are an interesting model system used to study the mechanisms involved in cell morphogenesis in plant tissue. Utilizing the local level set method, biochemical dynamics on moving cell boundaries are captured. By incorporating cell-cell adhesion, the model is expanded to a multicellular framework that can be used to investigate the components involved in establishing these intricate cell shapes.

In the second part, we use a combination of experimental and modeling techniques to study new and existing regulations in the Dpp-Rho1-Cdc42 network in the Drosophila wing disc. During organogenesis in the wing disc, the regulation of epithelial cell height and curvature is crucial in developing correct tissue shapes. This requires the interplay between mechanical forces and morphogen-mechanogen pathways, at both the cell and tissue levels. Morphogens, such as Decapentaplegic (Dpp), regulate cell growth and division, as well as mechanogen activity. Mechanogens, such as RhoGTPases, are small diffusible molecules that regulate mechanical components, such as actin and myosin, to coordinate cell shape and tissue geometry. Even though the effect of morphogens in regulating mechanogens is critical for proper tissue formation, insufficient work has been done to understand this in the context of epithelial organogenesis. In this study, a combination of experimental and mathematical modeling approaches are used to study the linkage between Dpp, Rho1, and Cdc42 in the wing disc. By using experiments, new regulations between Dpp and Cdc42 have been identified, as well as the interaction between Cdc42 and Rho1. A mathematical model is developed by using a system of reaction-diffusion equations to model Dpp, Rho1, and Cdc42 dynamics, as well as the newly identified regulations. We utilize Bayesian optimization to explore this model and to investigate the robustness of the proposed networks.

The use of e-cigarettes for the inhalation of nicotine and cannabis products has become popular in the United States across many demographics. Their rise in popularity is largely attributed to their ease of access, customization options, and perception as safer alternatives to traditional methods. However, despite their perceived safety, inhalation of vaping emissions has great potential to cause adverse health outcomes in users, as evidenced by events such as the outbreak of e-cigarette- or vaping-associated lung injuries (EVALI) in the U.S. in 2019. While many e-liquid ingredients are considered safe for dermal or oral exposure, the vaping process has been found to result in the thermal degradation of e-liquid ingredients. As a result, the emitted aerosols are complex mixtures of chemicals formed during vaping that may have different chemical and toxicological properties than their parent compounds. However, characterization of these compounds remains challenging due to the wide range of customizable options – such as temperature, use patterns, device construction, and more – that may influence the resulting chemical composition of e-cigarette emissions.This dissertation aims to address the knowledge gaps in the relationship between user- and device-driven parameters on the thermal degradation behavior of e-liquids and the chemical and toxicological properties of e-cigarette aerosol emissions, using VEA as a model e-liquid. First, this work identifies novel VEA vaping products and their potential mixture effects on toxicity upon exposure to human lung cells using a combination of chemical and cellular-based analyses. Second, the change in VEA vaping emission product distribution as a function of variable voltage/temperature settings was characterized using non-target gas chromatography/mass spectrometry (GC/MS) analysis. Finally, a tube furnace reactor system was used to investigate the role of oxygen (O2) and transition metals in the thermal degradation behavior and emission product distribution of VEA. Results from this dissertation contribute to an improved understanding of the thermal degradation behavior and chemistry of e-liquids, and how varying user- and device-driven parameters can alter the chemical and toxicological properties of vaping emissions. Detailed compositional and mechanistic information on e-cigarette emissions will be helpful for future hazard identification and the public health risks associated with e-cigarettes.