University Of California Riverside

NSF Awards · FY 2024 · 2024-09

This award supports research in relativity and relativistic astrophysics, and it addresses the priority areas of NSF's "Windows on the Universe" Big Idea. In the last decade, gravitational wave astronomy has opened a new window into the Universe. A century after Einstein predicted gravitational waves, NSF's Laser Interferometer Gravitational-wave Observatory (LIGO) rewarded decades of investment with the first direct observations of gravitational waves from merging black holes and neutron stars. With improvements in sensitivity, gravitational-wave detectors will drive transformative discoveries across physics, astronomy, and cosmology in the coming decade, observing millions of black holes and neutron stars across cosmic time, probing the nature of the most extreme matter in the universe, and exploring open questions in gravity and fundamental physics. This award supports research to develop new adaptive optical technology critical to extending the astrophysical reach of gravitational-wave detectors and enabling future facilities. By clearing a key technological hurdle toward a next-generation gravitational-wave observatory, this award will ensure that gravitational-wave science continues inspiring young scientists across the country to fulfill their potential as the world-leading researchers of the future. The award will support the training of students in STEM areas. The main goal of this project is to develop and deploy new adaptive optical technology to improve the sensitivity of gravitational-wave detectors by a significant factor, expanding their detection horizon past a redshift of 5 and enabling new tests of strong-field gravity, cosmology, and dense nuclear matter. The project is integral to realizing a planned upgrade of the LIGO, known as A#, and will also help lay the foundation for a next-generation U.S.-based gravitational-wave observatory, Cosmic Explorer. These improvements primarily target LIGO's quantum-noise-limited detection band above 200 Hz, where some of the most impactful observations—black hole ringdowns and binary neutron star mergers (with potential particle or electromagnetic counterparts)—stand to be made. They will be achieved through improved control of thermal distortions of the optics, enabling a fourfold increase of the laser power, to 1.5 MW, and higher levels of squeezed light enhancement. Modeling indicates this will require a qualitatively new form of active wavefront correction in the test masses, targeting finer spatial scales. The proposed work will deliver these critical new corrective capabilities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY Approximately 40% of Alzheimer’s Disease (AD) cases in the U.S. (and 56% in Latin America) are due to modifiable lifestyle factors such as hypertension, obesity, physical inactivity, heavy alcohol use, and smoking. People who engage in more physical activity, eat healthier meals, avoid substance use, and get preventative check-ups, tend to have better cognitive health, slower cognitive decline, and are at lower risk for late detection of disease and AD diagnosis. Yet, comprehensive theories of self-regulation and healthy aging suggest that engaging in healthy behaviors is promoted by environmental opportunities (or hindered by constraints). This potential discrepancy between health behaviors and environmental opportunities is referred to as a behavior- opportunity gap, which can be characterized as matched (level of health behavior and opportunity match), vulnerable (less health behavior than expected given opportunities), and resilient (more health behavior than expected given opportunities). Identifying the direction of behavior-opportunity gaps is critical because it impacts potential targets for effectively preventing AD: increasing health behavior uptake vs. policy changes to increase accessibility to healthy amenities. Despite recognized importance, the present proposal is among the first to identify associations between behavior-opportunity gaps and cognitive health, due to a dearth of longitudinal data containing both individual-level health behaviors and geographical-level environmental opportunities. This is a particularly pressing need for minoritized populations, who face disproportionate barriers in accessing environmental resources, stronger associations between modifiable lifestyle factors and AD risk, and spend more living years cognitively impaired. The long-term goal of this research is to identify how to effectively promote healthy cognitive aging in place for diverse older adults. The objectives for this application are to conduct geographical linkages to maximize the scientific value of an existing NIA-funded longitudinal family study of Mexican-origin immigrants living in the U.S. (Aim 1) and to identify associations between behavior-opportunity gaps and midlife cognitive health (Aim 2). Aim 1 will geocode 17 years of annual address data for 1,784 individuals and link to publicly-available geographical data containing indicators of environmental opportunities. Aim 2 will combine geographical data with extant health behavior and cognitive function data to identify associations among behavior-opportunity gaps and midlife cognitive health among Mexican-origin immigrants. The central hypothesis is that larger behavior-opportunity gaps will be associated with worse cognitive health over and above main effects of the behavior and environmental characteristic, such that vulnerable individuals will have worse cognitive function compared to matched and resilient individuals. This work will lead to new knowledge about the intersection of health behaviors and environmental opportunities as prevention and intervention targets for promoting healthy cognitive aging in place among minoritized adults.

NSF Awards · FY 2024 · 2024-09

Ultrafaint dwarf galaxies are the faintest galaxies known. They typically contain only 100 to 100,000 stars. Ultrafaint dwarfs are excellent probes for cosmology and the nature of dark matter. They also offer a new regime to understand processes like star-formation and stellar feedback. Currently, only about 100 of these faint galaxies are known, all within the volume of the Local Group. Surveys from telescopes like the Vera Rubin Observatory and the Nancy Grace Roman Space Telescope will allow the discovery of ultrafaint dwarfs within a 100-1000 times larger volume. However, theoretical predictions from numerical simulations are unable to reach the necessary resolution to model such small galaxies, limiting the reach of observational efforts. This investigator will combine a set of analytical methods and idealized numerical simulations to effectively extend the range of predictions of current cosmological hydrodynamical simulations to the regime of faint and ultra-faint dwarfs. Through the Cal-Bridge program, undergraduate students from underrepresented groups will participate fully in this research, receiving training in computer programming along with presentation and writing skills. She will also develop workshops to train middle and high-school teachers with hands-on activities based on topics related to this proposal. The PI and her research team will use tidal tracks describing the tidal evolution of satellites to supplement the cosmological simulations of groups and clusters from the TNG project in regimes where the simulations are under-resolved. This will enable their model to make predictions for the satellite population in groups and clusters, including faint and ultrafaint dwarfs. With their simulated catalogs they will address three fundamental topics. (1) Predictions for the number, stellar/luminosity function, sizes and radial distribution of satellite galaxies within groups and clusters. (2) Study the impact of tidal stripping in the formation of compact objects such as compact ellipticals (cE) dwarfs. (3) Quantify the number and properties of stellar streams expected in groups and clusters in Lambda-CDM. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Meiotic recombination is a fundamental aspect of reproduction in most eukaryotes. Recombination rate, i.e. the number of crossovers per generation, is also a key modulator of genetic and evolutionary processes, having profound effects on basic patterns of genetic inheritance, as well as high-level phenomena like adaptation and speciation. Errors in recombination (e.g., nondisjunction) also contribute to a variety of human chromosomal disorders, including trisomy 21 and Klinefelter syndrome. Despite its wide-ranging importance across many domains of biology, we have a poor understanding of how and why recombination rate varies across biological scales. Over the next five years, my lab will shed light on the genetic and evolutionary causes and consequences of recombination rate variation by testing long-standing hypotheses using modern genomic tools. This work will leverage empirical tools from two model systems, threespine sticklebacks and Drosophila, and several new key genomic technologies. We will undertake four lines of research to test hypotheses regarding the evolutionary drivers of recombination rate variation in natural populations. First, we will explore the evolutionary drivers of recombination rate variation in a model vertebrate, threespine sticklebacks, using gamete sequencing. Second, we will perform the first experimental test for the role of structural variants in determining genome-wide recombination rate variation in vertebrates. Third, we will perform a novel experimental test of the role of chromosomal inversions in adaptation using recent advancements in CRISPR-mediated chromosomal engineering to create and “undo” chromosomal arrangements in a Drosophila model species. Finally, we will develop modern and user-friendly statistical methods for comparing recombination maps within and between species and populations. This research program will greatly advance our understanding of the fundamental biology of meiotic recombination, create myriad new resources and tools, and train personnel in cutting-edge techniques that span genomics, computational biology, and evolutionary biology. These advances will be applicable across all domains of biology, from understanding the evolution of diseases like SARS-CoV-2, to understanding the fundamental mechanics of evolution in natural populations.

NIH Research Projects · FY 2025 · 2024-09

Summary Project Clinical and preclinical studies have demonstrated perturbations to the cerebrovascular network in Alzheimer’s Disease (AD) in sex-specific manner. Altered blood flow, cerebrovascular reactivity, and vessel topologies are all hallmarks of progressing AD in animal models and in human subjects. Blood-borne protein biomarkers have reported altered profiles in humans and mouse models of AD. AD research has predominately focused on neuronal, inflammatory and glial markers of disease progression. At the present time there are no studies that directly relate AD-induced changes in angioarchitecture to blood-borne protein biomarkers of endothelial stress and vascular dysfunction. Similarly, there are no studies linking blood borne protein biomarkers to vessel genomics, specifically targeting endothelial cell genes. This is a critical gap with significant clinical value because several studies suggest that vascular abnormalities precede AD onset. Therefore, blood-borne protein biomarkers could be used to predict likelihood of vulnerability to AD, disease onset and progression. This gap in knowledge will be addressed by this proposal, with the goal of describing the temporal evolution and relationships between damaged vascular networks and blood-based protein biomarkers and vascular genes. We have previously reported in AD mouse models there is an altered vascular density and complexity with increasing age. Sex differences have also been poorly studied within the context of vascular biomarkers, a gap we will also directly address in this proposal. Four interrelated but not interdependent Aims will elucidate the relationship between vessel genomics, cerebrovascular structure and function modifications and blood-borne protein biomarkers of endothelial and vascular functions. Aim 1 will examine in fine detail the timeline of vascular function structural changes over the lifetime (4, 12, >18mo) in 5xFAD mice of both sexes. Known risk variants will be added to clarify the effects of amyloid β seeding. The blood-based biomarkers will focus on proteins of endothelial stress, vascular damage and recovery (VEGF, vWF, Claudin-5, etc), glial (GFAP), inflammation (IL-1b, TNFa, HMGB1, IL6, MMP9) and neuronal damage and neurodegeneration (NF-L, Tau and its various phosphorylated forms and Abeta40 and 42). We believe that a panel of blood-borne biomarkers will accurately reflect the underlying cerebrovascular abnormalities with increasing age. Aim 2 will utilize the 3xTg AD mouse that has early amyloid β followed by tau deposition and 3xTg mice with the addition of risk variants. Aims 1-3 will utilize the identical methods biomarkers, genomes and structure/function assessments. Aim 4 will model all the findings to identify a unique biomarker set that has predictive capabilities for AD onset. The proposed project will provide technical and conceptual innovations through using a unique combinatory approach to establish direct relationships between blood-borne biomarkers and vascular function and topology, as well as genomic markers from the same animals of both sexes using PWI MRI, 2-photon microscopy, vessel painting, state-of-the-art spatial transcriptomics and single-nucleus RNA-seq and blood-borne protein biomarkers. Such innovative biomarkers would enable early identification of patients with elevated risk for AD, prediction of AD onset and severity, and objective monitoring treatment efficacy, our long-term research objectives.

NSF Awards · FY 2024 · 2024-08

Forecasting how our environment will change into the future requires the scientific community to understand the processes that shape Earth's surface environments through time. To do this, geoscientists collect images of Earth with satellites, run simulations, and test hypotheses with laboratory experiments. All of these methods improve our understanding of landscape change, but scientists using each of these tools struggle to bring their research together to make new insights. This project establishes a framework of interoperable hardware and software tools, called sandpiper, that enables research products from different teams and approaches to integrate with one another more easily than ever before. Major efforts of the project team include (1) designing and implementing an affordable open-source hardware-firmware system for data acquisition, (2) forging a community-backed data standard, (3) developing a flexible and interoperable data-analysis software library, and (4) establishing a sustainable community of practice. The project team is also advancing science and technology education by creating science museum exhibits that demonstrate fundamental principles in geomorphology and reach a wide audience through an interactive web interface. Recent strides in geomorphology have been fueled by widely available satellite imagery, powerful numerical modeling toolkits, and decades of physical laboratory experiments. Customized algorithms lie at the heart of the discipline because raster data—e.g., photographs, topography—form a fundamental bridge between these complementary modes of inquiry. Transformative insights can arise when researchers apply tools from one mode of inquiry to data from another. However, most innovation at the forefront of geomorphology currently proceeds in silos via ad-hoc algorithms that accumulate “mutations” as they traverse laboratories and graduate-student generations. The problem is particularly acute for experimental geomorphology, where technological barriers have prevented FAIR (Findable, Accessible, Interoperable, Reusable) and OS (open-source) principles from integration into the research process. At present, there is no unifying framework to support collaboration between modelers, observationalists, and experimentalists. The team for this project is creating such a cyberinfrastructure framework and solving these problems at every level. (1) To break down experimental silos, the project team is designing and implementing a modular and extensible open-source hardware–firmware system to affordably and uniformly make measurements and generate reproducible data products in labs across the world. (2) To promote and simplify data sharing, the project team is organizing a community effort to forge a data standard. (3) To mitigate algorithm drift, the project team is developing a flexible analysis library that integrates with this data standard. (4) To establish a community of practice, the project leaders are engaging researchers in their own laboratories and computing environments to facilitate reusing and contributing algorithms to the library. This acquisition-to-analysis toolchain, called sandpiper, will enable the next generation of collaborative research in geomorphology, sedimentology, and stratigraphy; advances could also influence seemingly unrelated fields like dendrochronology, hydrology, and seismology. This award by the Office of Advanced Cyberinfrastructure is jointly supported by the National Discovery Cloud for Climate initiative within the Directorate for Computer and Information Science and Engineering and by the Geosciences Directorate’s Research, Innovation, Synergies, and Education and Earth Sciences divisions. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

With support from the Improving Undergraduate STEM Education: Hispanic-Serving Institutions (HSI Program), this Track 2 project looks to impact student outcomes in general chemistry courses at the University of California-Riverside (UCR), Mount San Antonio College and Mount San Jacinto College. Significant effort has been made nationwide over the past several decades to address equity gaps in higher education STEM outcomes to support the development of scientists for 21st century STEM workforce. One reason that these equity gaps have persisted has been co-curricular programs that continue to funnel students into introductory STEM courses designed to filter out less prepared students. Thus, this project will focus on developing a mastery outcomes assessment strategy in the year-long general chemistry program. This approach will give students opportunities to demonstrate growth in learning rather than using a small number of high-stakes exams. Major project components include: 1) training workshops for faculty instructors; 2) a phased implementation of a mastery outcomes assessment structure in the UCR general chemistry program and at two partner community colleges; 3) implementation of a parallel metacognitive learning intervention for students; and 4) assessment of the mastery outcomes framework and self-regulated learning strategies on student outcomes and attitudes. This project is expected to reduce equity gaps and improve retention of historically underserved students in this critical gateway course sequence, and ultimately it will act as model for improving student outcomes in other introductory STEM gateway courses. The primary objective of project research and evaluation efforts is to measure the reduction in equity gaps and retention of the Hispanic student populations in the general chemistry sequence. This project will not only improve the success and retention of historically underrepresented students at the collaborating institutions, but will also provide a template for improving these outcomes in other higher education STEM gateway courses at institutions across the nation. The following research questions will be addressed: 1) how does a mastery outcomes assessment approach impact chemistry mindset for historically underserved students; and 2) how does a mastery outcomes assessment approach impact faculty instructors' view on how introductory STEM courses should foster a growth mindset vs. a fixed mindset? This project will employ a mixed methods research approach to evaluate the efficacy of the mastery outcomes assessment structure. Performance equity gaps will be measured using final exam data and final course grades, and affective learning outcomes will be assessed using surveys and individual interviews with selected students. Additionally, the impact on faculty instructors' approach to fostering a growth mindset and pedagogical content knowledge with respect to assessment will be evaluated in pre/post surveys. Broader dissemination of the project implementation and associated research results will be carried out through university public relations announcements, presentations at national STEM education conferences, and scholarly research publications. This project is funded by the HSI Program, which aims to enhance undergraduate STEM education, broaden participation in STEM, and build capacity at HSIs. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

Plants use internal and external chemical signals to shape their development and interactions with the environment. Understanding how these chemicals are formed, perceived, and responded to can lead to improvements in crop yields that are important for food security in the face of continued population growth and environmental stresses. This project will investigate how karrikins, a class of chemicals found in smoke that act as plant growth regulators, and internal karrikin-like chemicals are converted into active signals by plants. A family of proteins that putatively regulate metabolism of these chemicals will be studied through genetic and biochemical approaches to understand how they work and how they potentially integrate the status of nitrogen availability into this process. The project will help to build and diversify the U.S. scientific workforce capacity in genetics and biotechnology through training of two graduate student researchers and approximately one hundred undergraduates, many of whom are first-generation college students or from low-income households, participating in an introductory biology lab that contributes to the research objectives. Karrikins are butenolide compounds found in smoke that can promote seed germination, light-responsive seedling development, root hair growth, and stress tolerance of many plants. Karrikin (KAR) responses are mediated by an enzyme-receptor, KARRIKIN INSENSITIVE2 (KAI2), which putatively recognizes an unknown, endogenous signal, KAI2 ligand (KL), as well as a plant-derived KAR metabolite(s). The identity of KL and genes that carry out KL and KAR metabolism remain undiscovered. KARRIKIN UPREGULATED F-BOX1 (KUF1) participates in negative feedback regulation of KAR/KL signaling, likely by attenuating KL biosynthesis and metabolic activation of KAR1. As an F-box protein, KUF1 putatively targets specific protein substrates for polyubiquitination and proteasomal degradation. Several ACT-domain repeat (ACR) proteins have been found to be likely substrates of KUF1 in Arabidopsis thaliana. The overarching goals of this project are to complete an in-depth reverse genetic and biochemical validation of ACR proteins as KUF1 targets, and to determine how ACR proteins work at a molecular level. The project will reveal the physiological functions and regulation of ACR proteins in plants. Links have been made between the ACR family and nitrogen assimilation, primarily through the characterization of one plastidic protein, but it is unclear whether this role is conserved in the non-plastidic proteins that make up the majority of the family. This project will also reveal whether ACR proteins facilitate allosteric control of nitrogen assimilation or integrate nitrogen status into KAR/KL metabolism. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2024 · 2024-08

ABSTRACT Mosquitoes use their olfactory and gustatory systems to find and land on a human host’s skin for a blood meal, and in the process transmit diseases like Dengue to hundreds of millions of people worldwide. Therefore, the two chemosensory systems are excellent targets for behavior disruption strategies. The gustatory system, in particular, plays the most critical role in avoidance of the synthetic topical insect repellent DEET, however it has not been leveraged for discovery of improved repellents. There is a huge need for better topical repellents; the poor cosmetic properties and high cost for frequent application on the skin preclude the use of DEET by high- risk populations in tropical countries. We reasoned that new behavioral actives could be identified from human skin-associated compounds, the rationale being that anthropophilic mosquitoes, such as Aedes aegypti, exhibit different preferences for individual humans based on differences in skin chemistry. In a recent breakthrough we developed a Machine Learning cheminformatic method to predict odorant and tastant repellents from in silico screening of skin-associated compounds. In preliminary testing using behavior assays, we found powerful repellent effects from components of skin volatiles, sweat and even microbiome metabolites. The overarching goal of this proposal is to identify skin compounds that affect close-range mosquito landing behavior and perform an analysis of the cellular and receptor pathways (Or, Ir, Gr or TrpA1) that are required to sense these compounds in olfactory and gustatory neurons of Ae. aegypti. The objective will be achieved via three specific aims. First, we will validate the computationally-predicted skin repellents in mosquito behavioral assays designed to evaluate close-range (olfactory) and contact-dependent (gustatory) effects, which will create priority lists for the following aims. Second, compounds that act upon contact or are non-volatile will be prioritized for surveying gustatory responses with single sensillum electrophysiology and in assays to examine residency and probing behaviors, which occur after landing in preparation for blood feeding. Testing Gr and Ir co-receptor mutants will identify chemoreceptor pathways involved in sensing any taste-active repellents. Third, compounds that are low- volatility and act at close range (like DEET) will be prioritized for surveying olfactory responses with electrophysiology. Contributions of chemoreceptor pathways involved in sensing the olfaction-active repellents will be identified by testing Orco and Ir co-receptor mutants. Finally, we will test if blends of predicted skin repellents that act on both olfactory and gustatory pathways can alter host attractiveness. Successful completion of this proposal will provide a foundation for understanding how aversive components of complex skin-associated cues can alter mosquito-host interactions at close range.

NSF Awards · FY 2024 · 2024-08

This project explores how a unique fly species, Drosophila sechellia, has adapted to eat a fruit that is toxic to most other flies. Found in the Seychelles islands, D. sechellia feeds exclusively on the noni fruit, which contains chemicals that repel or harm other fly species. The researchers want to understand how D. sechellia's sense of taste has changed to allow it to eat noni fruit and previously discovered that D. sechellia is less sensitive to the bitter taste of noni and more able to detect its sweetness compared to other fly species. Now, they aim to identify the specific genes responsible for these differences. The team will focus on genes involved in taste detection, looking for changes that might explain D. sechellia's unique ability to eat noni compared to its close relatives that cannot. This research could help us understand how animals adapt to new food sources over time. It may also provide insights into how insects choose their host plants, which could have implications for pest control and agriculture. The project will train students in cutting-edge research techniques in the laboratory, generate valuable genetic tools for the scientific community, and include public outreach activities to share the excitement of scientific discovery with the local community. D. sechellia's unique adaptation to the Morinda citrifolia (noni) fruit, which contains fatty acids that are toxic to other drosophilids, presents an excellent model for studying behavioral diversification and host shifts in insects. Building on preliminary studies, the researchers will employ a candidate gene approach to identify genes underlying differences in noni fatty acid taste responses between D. sechellia and its generalist sibling species. The study will focus on two key aspects of D. sechellia's taste system: 1) reduced responses to noni fatty acids in deterrent bitter taste neurons, and 2) reduced inhibition of appetitive sweet taste neurons by noni fatty acids. The research team will leverage genetic tools developed for D. melanogaster and apply state-of-the-art transgenic, CRISPR/Cas9 genome-editing and sequencing strategies to both D. melanogaster and D. sechellia. The complementary functional neurogenetics approaches with the two species will allow for a systematic investigation of the roles of candidate Gustatory receptors (Grs), Odorant-binding proteins (Obps), and Ionotropic receptors (Irs) in evolutionary variation in cellular and behavioral responses to noni fatty acids. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-08

RNA modification serves as a major posttranscriptional mechanism to regulate gene expression. Recent advances in high-throughput sequencing have exponentially expanded the breadth and depth of RNA modification types, substrate varieties and biological significance in normal developmental processes and the genesis/progression of human diseases, including cancers, virus infections, and many neurodegenerative diseases. In eukaryotic cells, all nascent mRNAs are born with a 5' triphosphate group (ppp) and then immediately modified with an m7G cap in the nucleus. tRNAs and rRNAs also initially bear a 5' ppp group but lose it during maturation via RNA cleavage events. Eukaryotic cells stringently regulate the 5' ppp group to generate a cytoplasm free of ppp-RNAs, allowing them to easily detect viral RNAs, some of which bear a 5' ppp group. Whether the ppp group is subject to alternative modifications to alter RNA fates remains to be a knowledge gap in the RNA field. Recent studies by the PI and others have demonstrated that RNA polyphosphatases, which remove two phosphates from the 5' ppp group, play important roles in regulating nuclear small RNAs and viruses. The PI is also studying another modification on the ppp group, the m2,2,7G cap on ncRNAs including U1 and U2 snRNAs. The PI found that influenza A virus (IAV) prefers to snatch the caps of ncRNAs and utilize them to generate viral RNAs with these caps in canonical and non-canonical cap- snatching processes, the latter of which was discovered by the PI recently. The PI is studying a third nuclear RNA modification, the m5C on piRNAs, a relatively unexplored but important research area, since piRNAs usually serve as the sensors in innate immune responses. In all, the PI proposes to investigate these three types of nuclear RNA modifications. Unlike the PI's previous study focusing on small RNA pathways, this proposal primarily focuses on how proteins in this RNA polyphosphatase family, especially PIR-2, regulate mRNA and lincRNA, as the PI discovered that these proteins play non-small RNA mediated essential roles in C. elegans. The PI will identify the substrates and systematically examine if and how this polyphosphatase family regulates DNA replication, RNA transcription and chromatin modification in a variety of cells including germline cells and neurons. This study will discover a new mode of gene regulation, which utilizes nuclear RNA polyphosphatases to alter nascent ppp-RNA fate. The PI will also study how m5C on piRNA modulates RNA stability and functions in target binding and processing, as m5C on other RNAs. Moreover, the PI will examine if IAV preferentially utilizes the m7G caps derived from nascent U1 and U2 snRNAs or the m2,2,7G caps derived from mature U1 and U2 in the nucleus, and if RNA splicing mediated by U1/U2 snRNA is compromised by IAV. The proposed research is original and innovative, and bears direct relevance with human health and disease. Not only will this study generate new gene regulation tools for research and disease treatment, but it also promotes next generation researchers, especially those underrepresented /underserved.

NSF Awards · FY 2024 · 2024-08

This research seeks to understand the mechanisms that regulate plant cell division positioning, which is required for plant growth and development. Critically, plants are essential for life, as they feed people and form the majority of biomass on the planet. Despite their critical roles, how plants position division planes is still mostly unknown. This project will investigate how functionally redundant proteins control division plane orientation in the dicot Arabidopsis thaliana by determining whether two unrelated division site-localized proteins interact with each other and how yet unknown proteins mediate the localization of these division site proteins and contribute to division plane positioning. The Broader Impacts include the intrinsic merit of the project as the results are likely to be generalizable to all flowering plants, including those of agronomic importance. Additional activities will involve the training of graduate and undergraduate students, and a postdoctoral researcher who will gain valuable soft and hard skills including experimental design, communication with other scientists, project management, and a deeper understanding of scientific ethics. Outreach activities are planned for elementary school students. Two unrelated microtubule binding proteins, TANGLED1 (TAN1) and AUXIN INDUCED IN ROOT CULTURES9 (AIR9), are together essential for division plane positioning. The current hypothesis is that TAN1 and AIR9 mediate division plane positioning by forming two distinct but equivalent hubs that localize independently to the Arabidopsis division site. To test this hypothesis, the investigator will assess whether these proteins interact with each other using a variety of biochemical and in vivo assays. In addition to assessing potential physical interactions, genetic interactions have also been tested by identifying enhancer mutants that alter division plane positioning in combination with air9 mutants. Several air9 enhancer mutants will be characterized via quantitative analysis of the mutant phenotype, localization of the affected protein and identification of protein interactions that mediate division plane positioning. Finally, structure and function analysis will be used to characterize domains of the division-site localized protein AIR9 that are essential for division plane positioning in plant cells as well as the protein(s) that recruit AIR9 to the division site. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2024 · 2024-08

Project Summary Growing clinical evidence suggests that traumatic brain injury (TBI) is a major risk-factor over an individual’s lifetime, and results in symptoms and pathophysiology consistent with Alzheimer’s disease (AD) and related dementias (ADRD). Rodent models recapitulate early pathological clinical features of TBI, but it is unknown if these models manifest long-term ADRD features such as cognitive decline, neurodegenerative brain atrophy, chronic inflammation, vascular disturbances, and accumulation of amyloid-β (Aβ) and altered fluid biomarker levels. Well-known risk factors for TBI-induced ADRD (i.e. APOE, sex etc.) influence susceptibility for lifespan progression, but the role of TBI pathophysiology has not been well characterized. This proposal will fill these knowledge gaps using a closed head injury (CHI) TBI model over the animal’s lifespan that exhibits ADRD-like features. Using the CHI TBI model, we will examine how AD risk alleles (i.e. humanized amyloid-β (hAβ), APOEε4, and hAβ.APOEε4) accelerate ADRD progression. Importantly, cognitive behavioral outcomes, clinically relevant neuroimaging (PET, MRI) using established protocols (ADNI3) combined with fluid biomarkers will be used to assess disease advancement. Construct and face validity measures (within and between performance sites will be demonstrated using multi-modal data modeling to confirm replicability and to differentiate between TBI+ADRD from TBI or ADRD trajectories alone. Using our CHI TBI mouse model, which replicates human mild/moderate TBI, and exhibits altered blood brain barrier (BBB), progressive cognitive decline, late Aβ deposition, chronic neuroinflammation, and progressive vascular perturbations, we will establish in sex and age-specific manner the conditions for TBI evolution to ADRD. We also will leverage NIA-funded MODEL-AD platform mice expressing hAβ and APOEε4 on a C57BL/6J (B6) background, as significant risk factors for ADRD progression. Using these models exposed to TBI, we will investigate how injury exposure at 3 epochs (juvenile 17D; middle 8M, old 12M) across lifespan (24M of age) influences progression to ADRD (Aim 1). A repeated CHI TBI will be identically tested to demonstrate a further increased vulnerability to ADRD (Aim 2). Finally, we will leverage these multi-modal data in an unbiased manner to establish internal/external consistency and reproducibility (construct validity) as well as modeling how this maps to human progressive trajectories to dissociate TBI+ADRD from TBI or ADRD alone (Aim 3). These Aims will demonstrate, validate, and replicate our hypothesis that TBI throughout the lifespan continuum leads to age-specific trajectories towards ADRD symptomology. The proposed research will result in a deeply phenotyped TBI model as it progresses to ADRD, and the role of sex and age of injury. The derived data will serve as a significant resource to accelerate future research into the mechanisms of TBI ADRD.

NIH Research Projects · FY 2025 · 2024-08

PROJECT SUMMARY The long-term objective of this project is to determine the general principles and causal mechanisms underlying subcellular RNA localization, and the physiological implications during development and disease. In particular, the subcellular localization of messenger RNA (mRNA) to cell protrusions is known to be required for cell migration, but the mechanisms by which mRNA localization regulates protein function in this setting are unclear. Many genes implicated in mRNA localization are expressed in neural crest cells, which are a particularly migratory cell type that gives rise to much of the vertebrate head, as well as neurons, melanocytes, and aggressive cancers including melanoma. As such, neural crest cells provide a rich environment to uncover molecular mechanisms of mRNA localization in cell migration as well as the relevance there of to mammalian physiology. In this project, I will use cultured melanoma cells to identify and characterize trans-acting regulators of mRNA localization and elucidate the role of mRNA localization on protein function. I will also use in vivo mouse models to catalog mRNA localization that occurs during neural crest cell development and directly test the role of a well characterized localized mRNA, Kif1c, during development and cancer onset and progression. As neural crest and cancer genetics fields rely heavily on transcriptional studies, the mechanistic understanding of a post-transcriptional process as described here may provide unique insight into the cause, diagnosis and treatment of craniofacial birth defects and melanoma onset and progression. My career goal is to run an academic research program analyzing the role and regulation of subcellular RNA localization during embryogenesis, with special attention to neural crest cells and their derivatives. My ambition is to have a lab that can determine molecular mechanisms at the single-molecule level and causally link those processes to physiological outcomes in vivo. To this end, the proposed experiments and training plan are designed to develop expertise in cutting-edge technologies such as TIRF microscopy, computational image analysis, genetic engineering and in vivo disease assays. Training in these advanced techniques will be directly supported by the resource-rich and collaborative environment at UT Southwestern, and especially mentorship from Dr. Gaudenz Danuser, Dr. Ondine Cleaver, Dr. Khuloud Jaqaman, Dr. Lu Le and Dr. Sean Morrison, who make up my advisory committee. The Pathway to Independence Award will provide the time, resources and autonomy to fully develop and initiate this ambitious research program and accrue the resources, expertise and experience necessary to launch an impactful, thriving research lab in Fall 2024.

NIH Research Projects · FY 2026 · 2024-07

PROJECT SUMMARY The proposed research aims to unravel fundamental mechanisms behind neuronal survival across an organism's lifespan, shedding light on specialized RNA regulation pivotal for prolonged neuronal resilience. Essential for learning, memory, and environmental adaptation, mature neurons must persist throughout an organism's life, yet our understanding of the intricate genetic regulations enabling this endurance remains incomplete. Prior studies predominantly emphasized competition for external cues and growth factors in establishing neural circuits and preventing cell death. Our research uncovers intrinsic genetic mechanisms facilitating continuous neuronal survival. Notably, during differentiation, neurons alter their apoptosis regulation, becoming more resistant to cell death triggers. This transformation coincides with global reprogramming of apoptosis-related genes at both transcriptional and post-transcriptional levels, resulting in the generation of neural-specific alternative isoforms. A significant focus lies on understanding the role of specific gene elements which exhibit crucial regulatory functions. We have determined a dozen of these splicing controls with implicated functions in controlling neuronal survival and cell death. Our preliminary data show that splicing alternation significantly impairs neuronal health. We propose three independent and interrelated overarching aims for systematic exploration of these elements in influencing neuronal apoptosis. Additionally, by investigating the impact of exon deletions and genetic manipulations, we seek to determine their continuous necessity for long-term neuronal survival. Our interdisciplinary team, adept in genetics, neurobiology, molecular cellular biochemistry, and computational biology, uniquely positions us to tackle these critical questions. Through innovative methodologies and rigorous investigations, we endeavor to unveil neuron- specific regulatory mechanisms governing apoptosis competence. Such discoveries may not only reshape our comprehension of intrinsic neuronal survival strategies but also pave the way for novel strategies to enhance neuronal resilience and combat neurological disorders affecting brain tissue equilibrium and circuitry formation.

NSF Awards · FY 2024 · 2024-07

This project focuses on enhancing the safety and reliability of autonomous driving systems, making them more trustworthy in a variety of environments, including potentially hostile ones. The research will develop advanced detection and countermeasure techniques at the application, system, and hardware layers to help ensure that self-driving cars can make safe driving decisions even when faced with deliberate attempts to disrupt their operation. This involves creating robust deep-learning modules for driving decisions, enhancing the safety and security of automotive processors, and developing tools to detect and fix hardware issues in mission mode. By conducting extensive real-world testing with popular automotive benchmarks, the project aims to validate these innovations, ensuring they can be confidently adopted in everyday use. This comprehensive approach addresses current and future challenges in autonomous driving technology, paving the way for safer and more efficient transportation systems that the public can trust. The broader impact of this research extends beyond automotive technology to other critical systems such as space exploration, smart medical devices, and various Internet of Things (IoT) applications. With the deep learning market expected to grow to $24.5 billion by 2025, advancements from this project will play a crucial role in ensuring the safety and security of numerous technologies that impact daily life. The project’s findings will be widely disseminated through publications, software releases, and educational courses, contributing to the development of a skilled workforce in this rapidly evolving field. Further, the researchers will engage in educational outreach, including workshops and summer camps for students from diverse backgrounds, promoting inclusivity and inspiring future scientists and engineers. The researchers’ ongoing collaboration with leading semiconductor companies will also support translation into practice. The project not only advances technology, but contributes to societal well-being by making autonomous systems safer and more reliable, ensuring that the benefits of these innovations are widely accessible. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2024-07

Abstract: This proposal describes the development of sustainable methodologies using Earth-abundant Ni-based catalysts to synthesize nitrogen-containing molecules. The proposed projects target improving the synthesis of amines, amides, and nitriles by overcome pervasive challenges in the field, like the limited scalability of current state-of- the-art photocatalytic methods and the need for toxic reagents for nitrile synthesis. These functional groups are both commonly relied upon as readily manipulated synthetic intermediates and are also ever-present in biologically active molecules, commercial drugs, and polymers. The first project describes the design of Ni catalysts to mediate C−N bond-forming reactions. The objective is to enable reaction mechanisms similar to those observed under light irradiation with Ir cocatalysts, but while bypassing the limitations of those systems. Specifically, we aim to enable processes that do not require Ir or light to proceed. This is because photochemical reactions are difficult to perform at industrially relevant scales and avoiding the use of Ir will reduce the reaction cost. If successful, the new systems will enable the coupling of amines and amides at ambient temperatures. This contrasts with other non-photochemical approaches that require high temperatures and strong bases to promote these reactions. It is expected that the milder conditions will allow for a wider functional group tolerance and thus increase the scope of molecules that will be directly accessible by these methodologies. The second project describes the use of aryl nitriles as cyanide sources. Aryl nitriles are ideal CN precursors because, unlike most cyanide sources, they are non-toxic. Consequently, the development of synthetic methods relying upon them would be highly advantageous. In this context, preliminary data is presented for two different transformations: (i) the carbocyanation of alkenes and (ii) the addition of electrophiles and cyanides to cyclopropyl ketones to yield open-chain ketones. Both these transformations facilitate the introduction of two different groups in a single step. As a result, these protocols enable direct access to a broad range of nitrile- containing products in an efficient and sustainable manner.

NSF Awards · FY 2024 · 2024-07

Mean field games is the study of strategic decision making in large populations where individual players interact through a certain quantity in the mean field. Mean field games have strong descriptive power in socioeconomics and biology, e.g. in the understanding of social cooperation, stock markets, trading and economics, biological systems, election dynamics, population games, robotic control, machine learning, dynamics of multiple populations, pandemic modeling and control as well as vaccination distribution. It is therefore essential to develop accurate numerical methods for large-scale mean field games and their model recovery. However, current computational approaches for the recovery problem are impractical in high dimensions. This project will comprehensively study new computational methods for both large-scale mean field games and their model recovery. The comprehensive plans will cover algorithmic development, theoretical analysis, numerical implementation and practical applications. The project will also involve research on speeding up the forward and inverse problem computations to speed up the computation for mean field game modeling and turn real life mean field game model recovery problems from computationally unaffordable to affordable. The research team will disseminate results through publications, professional presentations, the training of graduate students at the University of California, Riverside as well as through public outreach events that involve public talks and engagement with high school math fairs. The goals of these outreach events are to increase public literacy and public engagement in mathematics, improve STEM education and educator development, and broaden participation of women and underrepresented minorities. The project will provide novel computational methods for both forward and inverse problems of mean field games. The team will (1) develop two new numerical methods for forward problems in mean field games, namely monotone inclusion with Benamou-Brenier's formulation and extragradient algorithm with moving anchoring; (2) develop three new numerical methods for inverse problems in mean field games with only boundary measurements, namely a three-operator splitting scheme, a semi-smooth Newton acceleration method, and a direct sampling method. Both theoretical analysis and practical implementations will be emphasized. In particular, numerical methods for inverse problems for mean field games, which is a main target of the project, will be designed to work with only boundary measurements. This represents a brand new field in inverse problems and optimization. The project will also seek the simultaneous reconstruction of coefficients in the severely ill-posed case when only noisy boundary measurements from one or two measurement events are available. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2024-06

PROJECT SUMMARY Posttraumatic epilepsy (PTE) refers to chronic unprovoked seizures following traumatic brain injury (TBI), and is a major clinical problem in both the military and civilian populations. Despite the importance of PTE, the locus of where PTE develops relative to the site of head injury and thus the anatomy of development of PTE in distributed brain networks is not well understood. Consequently, the physiological changes occurring specifically in the PTE seizure focus underlying epilepsy have not been determined. Our long-term goal is to identify mechanisms of PTE. The objective here is to determine the anatomic locus of PTE in the controlled cortical impact (CCI) model of TBI and to determine underlying cellular, molecular, and physiological alterations accompanying PTE. Our central hypothesis is that following CCI, localized molecular changes that impair astrocytic function and divergent injury-induced microcircuit reorganization of intratelencepalic (IT) and extratelencepalic (ET) Layer 5 pyramidal cells (L5PCs) and hippocampal CA1 pyramidal cells (HPCs) underlie emergence of seizure foci. By using multielectrode array (MEA) electroencephalography (EEG) to define the seizure focus at various time points after CCI and comparing the molecular, cellular and circuit alterations in electrographically defined seizure foci in PTE mice with corresponding loci in seizure-free injured mice, we will identify the cellular and circuit changes and electrographic markers that predict transition to PTE. First, we will define the anatomic locus and electrographic biomarkers of PTE onset in the animal model of controlled cortical impact (CCI) using multielectrode array (MEA) electroencephalography (EEG). Second, we will determine which cellular and molecular changes in the seizure focus underlie the onset of PTE. Third, we will identify cell-type specific changes in L5PC (IT and ET) and HPC physiology and compromises in astrocytic transporter function that underlie emergence of seizure foci. These experiments are anticipated to have a positive impact by elucidating the necessary and sufficient changes in the brain underlying PTE and identifying new cellular and molecular targets for treatment.

NIH Research Projects · FY 2025 · 2024-06

Project Summary/Abstract Focal disease processes affect a specific organ, or part of an organ. Examples include primary tumors, inflammatory bowel disease, focal epilepsy, post-surgical pain, embolisms. The mainstay of medical management of these disease processes is drug treatment. However, the vast majority of our drug treatments of focal disease processes lack spatial targeting. For example, oral or intravenous drug treatments will deliver drug to the affected region; however, they will also expose all other organs to therapeutic drug levels. This systemic, off-target drug exposure causes severe, lethal side effects which limits our use of these medications in treating disease. To limit off-target side effects, there is significant interest in developing spatially targeted, focal drug delivery technologies. While some technologies have had important clinical impact, focal drug delivery has not yet achieved widespread success. We have developed intra- arterial drug-eluting bioresorbable composite implants that can reduce off-target drug exposure by 40-fold. For many drug treatments, this would effectively eliminate off-target side effects. Our implants are designed according to the four following criteria: (1) maximize drug storage and elution, (2) minimize disruptions to blood flow, (3) biocompatible for clinical use, and (4) biodegradable with tunable absorption rate when no longer needed. Moreover, this is a platform technology for delivery of a wide range of drugs, which can be used to treat an array of disease processes. Through this award, we intend to demonstrate the platform potential of our technology, by focally delivering two different drugs to two different organs. Additional analyses will assess for safety and efficacy of our intervention. If successful, the data obtained from this award would strongly motivate the next steps of product development for pre-clinical trials.

NIH Research Projects · FY 2025 · 2024-05

PROJECT SUMMARY AND ABSTRACT Cancer nanomedicine is a rapidly growing area of medical research which may overcome the intrinsic limits of convention cancer therapies for more effective and safer cancer treatment. Yet, the challenge remains in the development of cancer nanomedicine owing to the inability for nanoparticles (NPs) to efficiently deliver therapeutic agents into solid tumors. It has been well documented that delivering NPs into biological fluids results in the formation of NP-protein corona which endows NPs a biological identify by unpredictably altering the uptake, biodistribution and toxicity of NPs, thus hindering the therapeutic potential of nanomedicines. Therefore, the objective of this proposal is to use artificial intelligence (AI) algorithms to take into account NPs-interactions protein corona fingerprints into the prediction model to improve the delivery efficiency of NPs to tumor. Our hypothesis is that the proposed AI-based computational model will be capable of precisely predicting the pharmacokinetic profiles of NPs and NPs libraries with desired optimal targeting efficiency by considering the distinct protein corona fingerprints. Our methodology proposed herein can find a general use for reducing the number of nanomedicines that need to be tested at the early-stage preclinical trials and could identify a targeted library of novel NPs with desired delivery efficiency to tumor. Two Specific Aims of this proposal were formulated to test the hypothesis. Aim 1: To establish a generative adversarial network (GAN) model for the predictions of a protein corona fingerprint corresponding to physicochemical properties of distinct NPs. Aim 2: A neural ordinary differential equation (NODE)-driven pharmacokinetic model will be developed to predict the temporal biodistribution and tumor delivery efficiency of the protein corona-NPs complex. This design is necessary because the protein corona patterns, which are dependent on the physiochemical properties of NPs, can significantly change the in vivo fate of NPs. Experimental data for the AI model training are from our recently published Nano-Tumor Database, in which tumor delivery efficiency and time-course pharmacokinetic profiles in different tissues were evaluated. The models will be made available as a user-friendly interface, through AI- guided design, to assist the discovery of the novel nanomedicine libraries with desired tumor delivery efficiency. The proposed research is significant as this study addresses possible solutions to the unmet need for understanding the interaction between protein corona and NPs that impacts their targeting to tumor. This project has broad impacts because, upon successful completion, the AI-based system can provide proof-of-art technology for the design of smart nanomedicines to select an optimized nanomedicine library displaying maximum efficacy at tumor sites. Additionally, since our computational approach can be extended to different NPs and species, this work points towards a novel way of designing and optimizing nanomedicines for a wide variety of applications.

NIH Research Projects · FY 2026 · 2024-04

SUMMARY The goal of this proposal is to investigate the dynamic changes in cerebrovascular morphology after acute ischemic stroke and reperfusion therapy and also use cerebrovascular morphological features to improve stroke outcome predictions. Stroke is among the leading causes of death and disability worldwide. Acute Ischemic stroke (AIS) constitutes approximately 90% of all strokes and is caused by a blockage or significant narrowing of the brain vessels. The resultant disruption in the blood flow patterns downstream of the occlusion could place the under-perfused regions of the brain at risk. Acute reperfusion therapies can restore the blood flow but vessel recanalization and improve outcomes when performed early after AIS. A well-connected collateral supply system, a redundant network of bypass vessels existing in the brain, is correlated with smaller final infarct size and more favorable outcomes. However, a detailed evaluation of the collateral supply remains challenging due to the small vessel size and network complexity. Timely diagnosis and treatment of AIS, as well as an accurate prediction of response to reperfusion therapies, risk of major complications, and long-term outcomes, are pivotal to patients, families, and providers to guide treatment pathways. However, accurate predictive models are lacking despite efforts to use a large number of clinical and imaging biomarkers. Brain vascular morphology and geometrical features have been shown to correlate with the development of cerebrovascular disorders. We recently developed an automatic algorithm that can extract the brain’s vascular morphologic and geometric features from the commonly used MR and CT angiograms in healthy subjects and AIS patients. We propose developing further and validating this algorithm to automatically extract complex cerebrovascular morphology in real-time. We also propose developing predictor models to accurately use the cerebrovascular morphologic features, collateral index, and other clinical and imaging information collected at admission to predict major complications and long-term outcomes after AIS.

NIH Research Projects · FY 2026 · 2024-04

PROJECT SUMMARY/ABSTRACT Signaling lipids, such as steroids, terpenoids, and eicosanoids, regulate diverse physiological processes in animals, including development, reproduction, and immune responses. Understanding modes of action of such lipid-derived signaling molecules, therefore, is critical for ensuring and promoting healthy development and well-being in humans. However, in contrast to proteinaceous signaling molecules such as peptide hormones and cytokines, the power of modern molecular genetics has not been fully utilized for signaling lipid research, as they are not directly encoded by genes. In the past several years, it has been demonstrated that the insect steroid hormone ecdysone requires membrane transporters for its entry into target cells, challenging the prevailing dogma in endocrinology that lipophilic hormones can simply diffuse across the plasma membrane. As exemplified by this study, there are huge knowledge gaps regarding how signaling lipids function in vivo, particularly concerning their transmembrane transport machineries. This project will utilize fruit fly genetics to reveal uncharacterized aspects of signaling pathways mediated by lipid-derived molecules. The project will focus on three major signaling lipids in insects, namely ecdysone, juvenile hormone, and eicosanoids, to better understand their modes of action. Successful completion of this project is expected not just to broaden our understanding of the functions of signaling lipids in this important model insect species, but also to provide an unprecedented example of a novel type of signaling lipid research and may inspire many researchers in the relevant field.

NIH Research Projects · FY 2026 · 2024-03

Project Summary Single nucleotide polymorphisms (SNPs) in the protein tyrosine phosphatase N2 (PTPN2) gene are confirmed risk markers in both forms of inflammatory bowel disease (IBD), Crohn’s disease (CD) and ulcerative colitis (UC). PTPN2 loss-of-function variants reduce PTPN2 activity and are associated with more severe disease in IBD patients. While we and others have utilized PTPN2 knockdown and knockout models to generate preliminary insights into the potential contributions of PTPN2 loss-of- function in IBD development, there is very little information as to how PTPN2 clinical variants compromise intestinal homeostasis. A major contributor to this knowledge gap lies in the lack of suitable model systems to study PTPN2 variants in intestinal epithelial cells, the critical cell type that comprises the gut barrier. To address this, we propose to utilize IBDGC resources to 1) identify gene clustering, expression, and biological pathways altered in IBD patients carrying the PTPN2 rs1893217 loss-of- function variant; 2) generate novel in vitro models that will allow us to mechanistically probe key targets, perform challenge and rescue (using pharmacologic and genetic approaches) experiments; and 3) generate novel gut-on-chip models to integrate these findings into a more physiologically relevant experimental system. Outcomes & Impact: This proposal will capitalize on our expertise in studying roles of PTPN2 in multiple facets of IBD pathophysiology by utilizing the unique resources of IBDGC to develop cutting- edge models for a greater translational understanding of how PTPN2 variants contribute to IBD. These models will also represent a significant advance to the field for discovery biology and for future ‘personalized’ drug development studies.

NIH Research Projects · FY 2026 · 2024-03

PROJECT SUMMARY Toxoplasma gondii is a common protozoan parasite that forms a lifelong infection in the brain. Despite chronic infection, Toxoplasma only causes clinical pathology in the immune compromised and therefore triggers an effective and well-balanced immune response in the brain. T. gondii replication and innate immunity are strongly regulated by CNS resident astrocytes. Astrocytes ordinarily execute vital processes for proper brain function and reprogram into reactive astrocytes (RAs) during brain inflammation. The beneficial or detrimental roles of RAs in brain inflammation and neurotoxicity has remained debated and largely unknown. During Toxoplasma infection, astrocytes limit parasite proliferation in a STAT1-depend- ent manner, produce multiple cytokines and chemokines to attract immune cells to the brain, and modify extracellular concentrations of neurotransmitters to regulate the inflammatory environment of the tissue Like many immune cells, astrocytes are increasingly recognized as falling into distinct functional subsets but unlike immune cells our ability to manipulate RAs or study their function in a disease- or infection- specific manner has been limited. Here we propose to characterize, track and selectively manipulate RAs to determine their diversity and functional roles in the immune response during chronic Toxoplasma in- fection. We have generated a novel tamoxifen-inducible Cre knock-in mouse line driven by the lipocalin 2 (Lcn2) promoter (Lcn2CreERT2). By crossing to the Ai9 TdTomato reporter line, we have visualized RAs in various pathological states including systemic inflammation and T. gondii infection. Traditional astro- cyte promoters will be used in combination with Lcn2CreERT2 to selectively target RAs for genetic manipu- lation at any point during progression of infection, while leaving healthy astrocytes, neurons, and other glial cell types intact, transforming our understanding of astrocyte function and underlying inflammatory mechanisms during Toxoplasma infection. Three aims are proposed: In Aim1 infection-induced astrocyte subsets will be identified and characterized over the course of infection using flow cytometry and scRNAseq analysis. In Aim2 we will track the resolution of RAs in the context of high and low inflammatory environments following infection and in Aim3 we will manipulate RA gene expression to determine the beneficial and detrimental roles of RAs during chronic Toxoplasma infection. The rationale for the pro- posed research is that determining the development, function and responsiveness of astrocyte subsets during chronic infection will provide new knowledge on the long-term consequences of Toxoplasma in- fection and the basis of a working inflammatory response in the brain.