Vanderbilt University

NSF Awards · FY 2025 · 2025-08

Solutions to real-world problems, such as scientific document question-answering, cybersecurity diagnosis, and e-commerce personalization, can often be improved by augmenting the underlying generative artificial intelligence-based (Gen-AI) systems with retrieved external knowledge. Much of this external knowledge is organized in graph-structured formats that encode unique relational signals. For example, citation links among scientific papers reveal their deep intellectual dependencies across different fields. Recurring co-occurrences among software components and vulnerability reports can reveal latent causal chains triggering security flaws. Online human interactions, such as liking, commenting, or reposting, reflect individual traits and preferences. This project pioneers retrieval techniques that locate the appropriate graph-structured knowledge and infuse it to assist Gen-AI systems with solving downstream problems, closing critical knowledge gaps, and enabling more useful, trustworthy, and diverse predictions, discovery, and decision-making. In personalization, the proposed retrieval techniques could give a social e-commerce platform a holistic view of each customer and support highly personalized recommendations. In cybersecurity, hidden dependencies among vulnerabilities and defenses could be exploited, allowing security operators to trace multi-step attack chains and harden critical systems against emerging threats. In scientific discovery and innovation, the relational knowledge in our proposed graph-level retrieval could facilitate exploration of multifaceted content and provide diverse insights that push existing knowledge boundaries. To meet these goals, this project pioneers a transformative roadmap to build well-rounded graph retrieval techniques for retrieval-augmented generation (RAG) systems that advance three dimensions: (1) Improving utility by harmonizing knowledge between structured knowledge in graphs and neural knowledge in large language models via structured knowledge checking, aligning retrieval emphasis with user interests by estimating continuously evolving trends, and incorporating agentic planning and reasoning capabilities for intelligent multi-round graph-structured traversal; (2) Safeguarding trustworthiness by reliably retrieving error-controlled graph-structured knowledge, disclosing vulnerability by designing structure-informed threat models and improving safety with data-centric textual subgraph anomaly detection and model-centric neighborhood trend filtering; (3) Promoting knowledge diversity through multi-agent collaborative exploration at both the conceptual subgraph and individual entity level. Together, these innovations will yield theoretical advances in graph algorithms, retrieval modeling, and graph-structured knowledge representations, ultimately transforming how graph-structured knowledge is discovered, integrated, and applied in RAG and Gen-AI systems across impactful domains, such as healthcare, scientific innovation, personalization, cyber defense, and targeting. 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 · 2025-08

PROJECT SUMMARY/ABSTRACT Despite important advances in the treatment of learning disabilities (LDs), the dominant approach to intervention—direct skills instruction—fails to meet the needs of 25-45% of LD students. This indicates the need to expand the framework for LD intervention science with innovative approaches. This clinical trial (CT) assesses the effects and mechanistic processes of an innovative approach to intervention guided by cognitive-academic mutualism theory, in which cognitive resources support development of academic competencies while academic tasks in turn exercise & strengthen cognitive abilities. The CT’s innovative intervention provides coordinated cognitive training & direct skills instruction with supports for transfer across domains. The academic focus is math: word-problem solving & arithmetic, both critical foundational skills. The cognitive focus is working memory (WM) because WM plays a central role in early math development. Participants are 6–8 years old, a critical age when WM malleability & beneficial effects between emerging skills are rich in opportunity and when school instruction on the targeted math competencies intensifies. Also, delays that remain at the end of 1st grade forecast math LDs. First-grade children selected for math delays and low WM are randomly assigned to: (1) standard-of-care direct skills math treatment + coordinated computerized WM training (the innovation; CO-Tx); (2) the same standard-of- care direct skills math treatment + the same amount of computer game-like instructional activities not involving WM or math (the contrast standard-of-care condition); & (3) control group (the conventional school program & maturation; CON). Treatment occurs 3 times per week for 15 weeks. The primary outcomes are word-problem solving, arithmetic, & WM. Innovative intervention’s added value over standard-of-care direct skills math treatment (without WM training) is tested at posttest & delayed posttest, with 1-year follow-up effects explored. Mechanistic processes are assessed by testing whether bidirectional relations between WM & math are involved in the mediation pathway linking CO-Tx’s effects on delayed posttest math & WM and whether CO-Tx’s bidirectional relations are stronger in CO-Tx than in other conditions. Exploratory subgroup analyses are conducted to provide insight into the robustness of effects. This CT impacts science by deepening understanding about the potential for treatments based on cognitive-academic mutualism theory to enhance learning more than conventional direct skills instruction and deepening understanding about bidirectional relations between WM and early math development. Results may impact clinical practice by providing an innovative approach for treating math difficulties and other forms of LD. This CT is highly relevant & significant because math LDs are associated with long-term debilitating difficulty in school, the workplace, and everyday life and because pressing need exists to expand the framework for treating LDs with innovative approaches.

NIH Research Projects · FY 2025 · 2025-08

My group studies the genomics, enzymology, structure-function, and engineering of ribosomally synthesized and post-translationally modified peptides (RiPPs). Roughly 50 molecular classes of RiPPs have been described, defined primarily by the type of modification(s) installed. RiPPs are biosynthesized from a bipartite precursor peptide with distinct regions for enzymatic recognition and modification. The physical separation of the substrate specificity and enzymatic modification sites renders RiPPs attractive for the facile evolution of new functions, a strategy already seized by Nature. In learning how to leverage RiPP biosynthesis for various biomedical applications, we discovered a widespread protein domain used by most prokaryotic RiPP pathways to engage the substrate peptide. Coupled with our AI-based tool RODEO, which identifies the often short, hypervariable, and unannotated precursor peptides, we have redefined RiPP genome-mining, illuminated tens of thousands of biosynthetic gene clusters hiding in plain sight, accessed the mature products from scores of pathways, identified robust enzymes for pathway engineering, discovered new enzymatic reactions, and in some instances, predicted enzymatic function. This MIRA application builds on these past achievements and proposes several new innovative directions for our research program. While the pace of genome sequencing accelerates, much of the data remains inaccessible to experimentalists with limited bioinformatics knowledge. Undoubtedly locked away in the Whole- Genome Shotgun database with little/no gene annotation are sequences from metagenomic and microbiome studies that encode countless undiscovered RiPPs formed via entirely new enzymatic transformations. To mine this vast, untapped resource, we are developing MetaRODEO. From the resulting datasets, we will validate the algorithm by experimentally characterizing new classes of RiPPs that are formed via unprecedented enzyme chemistry. As per our past practices, the tool and all datasets will be publicly available. Additionally, this project will elucidate the mechanistic enzymology that guides known and newly discovered RiPP biosynthetic pathways. Lasso peptides, for instance, are RiPPs distinguished by a knotted architecture and remarkable heat and protease stability. We wish to understand the molecular gymnastics performed by lasso cyclases that kinetically trap lasso peptides in their threaded rotaxane conformation. Inspired by their natural diversity and disparate functions, we will exploit our knowledge of lasso peptide biosynthesis to perform structure-guided and directed-evolution studies to engage desired biological targets with high affinity and specificity.

NSF Awards · FY 2025 · 2025-08

Gun violence and the reckless use of firearms have become a pervasive and growing problem in the United States that has only been exacerbated by easy access to firearms, and an increasing mistrust of law enforcement that often inhibits reporting by the community. This project seeks to build a community-based acoustic gunshot alert system for detecting and localizing gunshots using a distributed network of inexpensive acoustic sensors and pilot it in a community in Austin, Texas. Shots are reported directly to residents who may use this information to engage with local law enforcement or solely for peace of mind. Successful implementation of the system would represent the first time that a technology-based gunshot alert system would be commercially available to the general public, both in terms of affordability and scalability. It could open the door for entirely new ways of dealing with illegal gunfire and change the way that members of the community interact with local law enforcement agencies. The primary goal of this project is to assess the system’s impact on resident incident reporting behavior, law enforcement call response, and downstream impacts on public safety and community attitudes. It will also provide a model for other communities affected by gunfire to adopt and adapt to their unique needs and circumstances. The technology behind this project builds off the pioneering work by Vanderbilt University in wireless sensor network-based gunshot localization. Inexpensive acoustic sensors continuously listen for gunshots in the surrounding environment using a combination of traditional signal processing algorithms and neural network-based AI models. Upon detection of a shot, the sensor will communicate critical details to a cloud server, including the precise time of the shot, a confidence estimate, the sensor location, and a 3-second audio clip. The server will aggregate incoming shot alerts from nearby sensors to localize the source of the gunfire using a novel search algorithm. Shots will be reported directly to individuals in the community via a phone app, while a role-based access system will provide law enforcement with more granular data and the ability to aggregate disparate calls into a single incident report for faster response times and improved triaging. The research conducted under this project will advance the state of knowledge in low-cost gunshot localization technology, especially in situations in which acoustic sensors are placed irregularly and arbitrarily. 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 2025 · 2025-08

Coastal regions are vulnerable to flooding from rivers and rising seas, increasing storm strength, and destruction of ecologically-fragile areas. River deltas are especially impacted by the balance between increasing water levels from sea-level rise and tides, and land surface elevation changes. Bangladesh’s Ganges-Brahmaputra Delta (GBD), the world’s largest delta, is a particularly excellent place to investigate this problem. The land is sinking (subsiding), worsening the impact of sea-level rise, but the rivers supply ample sediment to elevate the land. However, there is a mismatch in the distribution of sediment and land subsidence; some areas are maintained by sediments, while others are at serious risk of land loss. This project will combine local, on-the-ground measurements of elevation change with broad satellite observations, and develop a comprehensive numerical model of elevation change. The numerical model will enable synthesis of all measurements and incorporate shallow processes that are missing from most models. Results will contribute to Bangladesh’s coastal planning through established collaboration with government agencies, academic institutions, and non-governmental organizations. This project will support 2 postdocs and 3 graduate students in the U.S. as well as build capacity for students and faculty in Bangladesh. U.S. undergraduate students will participate in the proposed research through internship programs and a capstone course that includes a Spring Break field trip to Bangladesh. The model will have great applicability for use in coastal areas prone to flood risk, especially lowland deltas worldwide including the Mississippi Delta. Unraveling the intersecting processes that contribute to vertical land-surface dynamics is critical for forecasting sustainability of lowland deltas into the future. This project will employ multidisciplinary research that integrates an existing delta-wide network of sediment cores and geospatial instruments with broad-scale, multi-sensor satellite remote-sensing analyses, producing novel high-resolution maps of decadal surface-elevation change, topography, and land-use across the coastal zone. A state-of-the-art poroelastic model will be developed, validated, and applied to coastal Bangladesh. The team hypothesizes that at any given site on the delta, surface-elevation change reflects the vertical integration of sedimentation, near-surface soil consolidation, subsurface compaction of Holocene sediment, and deep tectonic/isostatic response of the lithosphere. Across the delta, surface-elevation change reflects how modern land use restricts surface sedimentation and accelerates consolidation, and how ancient river dynamics constructed the alluvial architecture of compacting Holocene sediments. These hypotheses will be tested with a process-based, holistic understanding of vertical land-surface dynamics, and will guide coastal hazard mitigation and sustainability efforts on the GBD and other deltas that face similar environmental and anthropogenic stressors (e.g., Mississippi and Sacramento-San Joaquin river deltas). 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 · 2025-08

Project Summary Alcohol Use Disorder (AUD) is a learning disorder in which alcohol alters neural circuits, causing a maladaptive desire to seek and take alcohol. AUD can develop following repeated exposure, initiating a cycle of excessive alcohol consumption, periods of abstinence, and relapse. Despite the prevalence and cost of this disorder, treatment strategies are ineffective, especially in preventing relapse. It is well-known that cues associated with the availability of alcohol can trigger seeking, increase drinking behavior, and contribute to relapse. Thus, understanding the neural mechanisms encoding information about alcohol and associated cues is critical for understanding how these associations develop and change with long-term drinking to contribute to seeking behavior. The major goal of this proposal is to elucidate the neural mechanisms underlying cue-alcohol associations and how they are changed by chronic alcohol exposure and abstinence. Previous in vivo work from our lab has shown that D2-receptor-containing medium spiny neurons (MSNs) in the nucleus accumbens (NAc) are critical for encoding associations between cues and outcomes and causally control cue-associations at the population level. Importantly, our preliminary data indicates that D2 MSN activity is dynamically modulated over time with alcohol drinking, specifically, in response to alcohol-associated cues. However, the precise information encoded within the temporal activity of these D2 MSNs in vivo has not been clearly defined – especially at the single-cell level. Additionally, D2 MSNs in the NAc receive direct projections from multiple brain areas that are key to alcohol related behavioral dysfunction and these glutamatergic inputs have been shown to be altered with alcohol exposure. However, whether these alterations occur globally or at specific synapses has yet to be investigated. This proposal will utilize microendoscopes to visualize single cell activity dynamics of D2 MSNs in the NAc during operant alcohol self-administration to 1) define how D2 MSNs are engaged over the course of operant alcohol drinking and 2) assess changes in D2 MSN activity associated with abstinence from chronic intermittent ethanol (CIE) exposure and alcohol seeking. Next, using electrophysiology to measure functional circuit adaptations, we will 3) assess the effects of chronic alcohol use and forced abstinence on physiology and circuit connectivity of D2 MSNs in the NAc. I hypothesize that D2 MSN activity evoked by alcohol- associated cues is increased over alcohol exposure and abstinence and that chronic alcohol exposure and abstinence enhances circuit-specific glutamatergic drive onto D2 MSNs, affecting their physiological properties. This proposal encompasses technical and theoretical training that will provide the foundational expertise and conceptual thinking needed to address larger questions regarding how long-term exposure to alcohol changes the brain and drives continued alcohol use. Additionally, these findings can ultimately inform our understanding of underlying reward and learning processes and lead to more efficacious treatment interventions for AUD.

NIH Research Projects · FY 2025 · 2025-08

Summary Foundational to any actualized behavior are the processes of synapse formation and synaptic specificity that facilitates neural circuit wiring. These concerted efforts begin embryonically and are continuously refined throughout life. Therefore, any disruption in this system of actions can result in neurological disorders, which remain largely untreated due to the lack of knowledge of essential molecules and how they can respond to extracellular stimuli to promote intracellular bidirectional synaptic signaling. Adhesion class GPCRs have emerged as candidates for this role as they have been shown to be capable of extracellular adhesion and intracellular GPCR- mediated signal transduction. Latrophilin 2 and 3 are adhesion GPCRs that can mediate synapse formation as well as precise wiring of the hippocampus by activating a classical GPCR- signaling pathway. Interestingly, the only other adhesion GPCR, along with Latrophilin, to be conserved from vertebrates to invertebrates, is the Cadherin EGF Laminin-g Seven-pass G-type Receptor (CELSR) 1-3. Invertebrate models of CELSRs have been shown to mediate planar cell polarity, neuronal migration, dendritic growth, and axon guidance in the brain. However, CELSRs in this capacity have been critically understudied in the mammalian brain. Our lab has found that CELSRs are expressed in pyramidal cells of the hippocampus. CELSR2 and CELSR3 are the highest expressed and each possess unique cleavage properties. Consequently, my project strives to elucidate the role of CELSR2 and CELSR3 at mammalian hippocampal synapses by employing the use of novel epitope-tagged floxed conditional knockout mice. Aim #1 will characterize CELSR2 and CELSR3 function in knockout and control mice by employing electrophysiological assays and staining to assess synaptic neurotransmission and localization. Aim #2 will uncover the signaling mechanisms in which CELSR2 and CELSR3 mediate function via rescue electrophysiology experiments using previously found mutants of CELSR2 that prevent GαS coupling and CELSR3 seizure mutations located in the transmembrane region.

NIH Research Projects · FY 2025 · 2025-08

Project Summary Nucleotide excision repair (NER) is the primary pathway used to repair bulky DNA adducts, which are caused by diverse exposures ranging from UV light to certain chemotherapeutic agents. Although NER is necessary for protecting human cells from DNA damage, the pathway can significantly reduce the efficacy of cancer therapeutics that damage DNA, such as cisplatin. Cisplatin is a front-line treatment for a variety of cancer types; however, many patients develop resistance to the drug. Our long-range goal is to develop strategies to improve treatment response. This proposal investigates the hypothesis that small molecules inhibiting the interaction between two critical NER proteins, Xeroderma Pigmentosum Complementation Group A (XPA) and Replication Protein A (RPA), will lead to reduced NER capacity and increased Pt-agent sensitivity. The Chazin lab has previously (i) mapped the interaction between XPA and RPA, (ii) determined that XPA mutations known to disrupt binding with RPA decrease NER activity, and (iii) shown that disruption of the NER pathway seems to correlate with increased Pt-agent response. The objectives of this proposal are to generate small molecule inhibitors of the XPA-RPA interaction (Aim 1) and test their ability to diminish NER efficacy and sensitize cells to Pt-agents. Aim 1 will utilize a fragment-based discovery approach, screening a highly curated library of small molecular fragments. NMR will be used to identify fragment hits that bind within the XPA-RPA interface. These will be elaborated and optimized, and hits occupying different sites in the interaction interface will be linked to generate higher affinity compounds. Fragments and linked compounds will undergo multiple rounds of optimization so that the most promising inhibitor candidates will be developed. Aim 2 will determine the effect of candidate inhibitors on physical interaction of XPA and RPA, NER activity and Pt-agent sensitivity. The mode of action and binding affinity of the inhibitors will be characterized with techniques including NMR and fluorescence-based competition assays to confirm their ability to inhibit the interaction. Select inhibitors will then be tested in a variety of cell- based assays to determine if they diminish NER efficiency and increase sensitivity to Pt-agents. These aims will generate valuable tool compounds that provide detailed insight into the correlation between NER activity and response to Pt-based agents and serve as a foundation for testing the potential therapeutic value of inhibiting NER to improve the response to Pt-based anticancer therapies.

NIH Research Projects · FY 2025 · 2025-07

SUMMARY We request funds to purchase an ONI Nanoimager super-resolution microscope to support cutting-edge NIH- funded extracellular vesicle (EV) and nanoparticle research at Vanderbilt University (VU) and Vanderbilt University Medical Center (VUMC). The ONI Nanoimager is a class 1 laser, four-color fluorescence super- resolution microscope that provides a user-friendly solution for resolving nanoscale structures at 20 nm resolution. Its patented vibration-dampening microscope body can be placed on a standard lab desktop and yet generate single molecule localization data. The Nanoimager was developed with state-of-the-art characterization of EVs, nanoparticles, and other nanoscale structures in mind. It performs single-molecule localization microscopy (SMLM) modalities, including dSTORM, PALM, and PAINT, and is uniquely capable of super-resolution single-molecule FRET and single particle tracking. It further surpasses the function of other shared super-resolution microscopes at Vanderbilt by performing simultaneous two channel imaging and has a superior 100X magnification,1.45 numerical aperture objective. The light engine is equipped with 405 nm, 488 nm, 560 nm, and 640 nm high-powered lasers and a dichroic mirror split at 640 nm. Users can adjust the illumination angle in 0.5 degree increments for imaging in epifluorescence, HILO, and TIRF modes. The accessory environmental chamber allows extended live cell imaging under physiologically supportive conditions, while the APLO Flow microfluidic device provides our EV research users with end-to-end automation, from EV capture to labeling to imaging, and the capacity to perform microfluidics-based experiments. Operation of the Nanoimager is remarkably simple, with many customizable pre-built imaging protocols and powerful data analysis tools available. These attributes are quite unusual for a super-resolution microscope, making it ideally suited as a Core instrument. Our Major and Minor Users will use the Nanoimager’s super-resolution imaging capabilities to study diverse biological processes in cell and cancer biology, including immunology, neurobiology, drug delivery design, and biomarker studies. Major users' projects focus on EV and nanoparticle biogenesis and composition (Pua, Weaver, Coffey, Wilson), disease biomarkers (DelGiorno), EV functions in extracellular matrix organization (Weaver), and EV and nanoparticle immunopotentiation and suppression (Coffey, Wilson). The Vanderbilt Cell Imaging Shared Resource (CISR) and the Vanderbilt Center for EV Research will promote the utility of the Nanoimager to VU and VUMC researchers through seminars, workshops, and website content. CISR will administrate scheduling, train users in the operation of the instrument, manage use, and apply an established business model to support the long- term maintenance of the system. In summary, the ONI Nanoimager will permit multiple modes of high-speed super-resolution imaging and single particle analysis designed to support cutting-edge EV and nanoparticle research not currently available to the Vanderbilt community in a compact and user-friendly format.

NSF Awards · FY 2025 · 2025-07

This instrument development project will construct a next-generation molecular imaging instrument to visualize biological tissues and engineered materials that mimic biological systems. By integrating advanced laser optics, custom ion source design, gas-phase separation strategies, and high-resolution mass spectrometric analysis, this instrument will provide revolutionary capabilities for visualizing biological molecules. The new instrument will help expand the understanding of cellular systems. The project will be conducted in close partnership with leading investigators who are working to solve emerging challenges in biotechnology and human health. These collaborations are intentionally selected to drive iterative co-development and maximize real-world impact. The resulting platform will broaden the availability of high-performance imaging capabilities to researchers in academia, federal laboratories, and private industry. The instrument will be housed within the Vanderbilt University Mass Spectrometry Research Center, a nationally recognized hub for molecular imaging and mass spectrometry, and it will serve to train new generations or researchers. This project will strengthen national infrastructure, expand access to advanced technologies, and provide advanced capabilities for molecular discovery and biological research. The instrument to be developed is a state-of-the-art matrix-assisted laser desorption/ionization imaging mass spectrometry platform that integrates trapped ion mobility spectrometry with Fourier transform ion cyclotron resonance for high-specificity molecular imaging at cellular spatial resolution. Leveraging the high-field 15 Tesla magnet from a decommissioned instrument, the project will combine ion mobility gas-phase ion separation with a custom Omnitrap collision cell for multi-mode fragmentation and the ultra-high mass resolving power of Fourier transform ion cyclotron resonance mass spectrometry. This unique platform will enable deep analysis of isobaric and isomeric chemical species, high spatial resolution molecular imaging (<5 micron pixel sizes), ultra-high mass resolving power (>1,000,000), and comprehensive structural characterization of a wide range of biomolecules. Housed at the Vanderbilt Mass Spectrometry Research Center, the platform will serve as a cornerstone for interdisciplinary research across biology, engineering, and medicine, and will support extensive training activities through established workshops and collaborative activities. The system represents a major advance in molecular imaging capabilities, providing the scientific community with a powerful tool for answering complex biological questions, accelerating discovery, and advancing the frontiers of spatial omics. 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 · 2025-07

Computational evolutionary principles and methods are fundamental to understanding, preventing, and treating genetic and infectious diseases, but formal graduate training is lacking in many institutions, including Vanderbilt University (VU). This proposal seeks to establish a new training program on Computational Evolutionary Approaches to Disease (CoEvoD) at VU. The goal of our program will be to train students to employ or develop computational and bioinformatic-based evolutionary approaches to understand disease biology. Compared to typical domain-specific programs, the CoEvoD will occupy a unique niche, providing a deeper grounding in evolutionary and computational principles than typically received by trainees from life sciences backgrounds, and a more thorough exposure to biomedicine than is usual for students from computational or quantitative backgrounds. VU is uniquely suited to hosting a long-term program on CoEvoD. Both VU and VU Medical Center (VUMC) are on the same campus and are home to a stellar set of preceptors that use and develop computational evolutionary approaches in both basic and clinical settings; most preceptors hold appointments in multiple departments and schools. Our program will draw its training faculty from 10 different departments in the School of Medicine, the College of Arts & Science, and the School of Engineering, and will be rooted in an already established network of collaborative research and training activities. Our program is new, but we have a great track record of highly productive past VU trainees that have landed outstanding positions in leading universities and companies. Training on CoEvoD is not part of existing VU/VUMC training programs and will be highly complementary to existing ones. We will train students to employ or develop a wide range of computational approaches (e.g., phylogenetics, evolutionary epidemiology, disease ecology, evolutionary genomics, population genetics, and evolutionary biochemistry), often in combination with the use of state-of-the-art core facilities (e.g., for computing, genomics, proteomics) and resources (e.g., the large-scale biobank BioVU). We expect that trainees will engage with many of these approaches, facilities, and resources in their research. Trainees will join CoEvoD at the end of their first year of graduate training and will typically be supported for two years. T32 support will cover specialized didactic training, graduate research initiation, and professional development for 6 trainees. Whether T32-funded or not, all trainees (and their preceptors) will be active in CoEvoD program activities throughout their graduate training. Overall, the CoEvoD will enrich each student’s research and training experience and foster the development of the future of US biomedical science.

NIH Research Projects · FY 2025 · 2025-07

PROJECT SUMMARY/ABSTRACT Biliary tract cancers (BTC) include cancers of the bile ducts and gallbladder and they claim approximately 170,000 lives each year globally. BTC has a median overall survival of 4.5 months, increasing incidence, and is estimated to be the sixth leading cause of cancer death in 2024. Due to its aggressive nature and lack of efficacious treatments, prevention is of the utmost importance in preventing lives lost to this disease. Currently, BTC etiology is poorly understood. Major lifestyle risk factors include obesity, diabetes, gallstones, smoking tobacco, and alcohol intake, but it remains unclear if their associations with BTC risk are causal. Previous genome-wide association studies (GWAS) suggested markedly high heritability, but these studies were small, with <2,500 cases. We propose to significantly expand an ongoing GWAS of BTC by leveraging data and biologic samples from 21 studies and biobanks throughout the world including, conservatively,12,000 BTC cases and >700,000 controls. In Aim 1, we will assemble and harmonize data from 21 studies. In Aim 2, we will perform GWAS for BTC and its subtypes within studies and ancestral groups and combine the results with meta-analysis as appropriate to identify genetic variants associated with BTC risk. In Aim 3 we will delineate potential causal associations of BTC risk with the aforementioned BTC risk factors using two-sample Mendelian randomization methods. Study instruments will be derived from existing GWAS conducted for these risk factors. These analyses will allow us to identify genetic risk factors for BTC and provide the most robust evaluation of potential causal associations of lifestyle risk factors with BTC risk to date, directly supporting BTC primary and secondary prevention. 1

NIH Research Projects · FY 2025 · 2025-07

ABSTRACT Inflammation of the bone or bone marrow, known as osteomyelitis, is most frequently caused by Staphylococcus aureus infection, with the prevalence of this pathogen making osteomyelitis a critical disease state to study. Bone possesses a unique cellular environment and serves a critical role in producing immune cells, including the differentiation of hematopoietic stem cells into monocyte precursors. S. aureus is capable of surviving via various mechanisms, such as the formation of abscesses in the bone marrow. These characteristic tissue lesions contain a central staphylococcal abscess community surrounded by both viable and necrotic neutrophils and are encapsulated by fibrin deposits. Previous work in our laboratory suggested the presence of a unique set of macrophages with a lipid-laden phenotype localized to the outer border of the abscess. Macrophages are innate immune cells recruited to the site of infection to phagocytose invading pathogens and recruit additional immune cells. Heterogeneous macrophage phenotypes have previously been described using techniques like flow cytometry, but spatial interrogation of heterogeneous macrophage populations and physiology has been difficult. Given the presence of lipid-laden macrophages around the abscess border and previous studies indicating the necessity of macrophage-derived factors for adequate abscess formation, I hypothesize that lipid-laden macrophages mediate abscess formation in the context of S. aureus-induced osteomyelitis, exhibiting anti-inflammatory molecular profiles and facilitating a protective niche for the SAC. Understanding the overall tissue architecture and localization of these cells in relation to the abscess is crucial, prompting the use of a multimodal imaging approach to assess this hypothesis. Matrix- assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) is a label-free analytical tool capable of detecting hundreds of analytes within a tissue section with high specificity and sensitivity. My research group has pioneered new approaches for IMS of bone that will provide an unprecedented view of the lipid landscape in the context of osteomyelitis. Furthermore, spatial transcriptomics is a powerful, untargeted technique for identifying gene transcripts present within specific tissue regions. The novel integration of MALDI IMS and spatial transcriptomics in bone tissue, as proposed in Aim 1, will provide a comprehensive view of the impact of S. aureus on the bone and how macrophages impact the infection response. To further interrogate the role of macrophages in staphylococcal abscess formation, I will use multiple approaches to deplete these cells in our murine osteomyelitis model followed by the integrated multimodal imaging workflow. Additionally, I will establish a lipid-laden macrophage cell culture model, as described in Aim 2, to resemble the molecular profile observed in vivo and to characterize their interactions with S. aureus. These data will provide insight into the pathological progression of S. aureus infections and lipid-laden macrophage-induced inflammatory responses employed to fight off infection in the unique bone marrow microenvironment.

NIH Research Projects · FY 2025 · 2025-07

PROJECT ABSTRACT Non-small cell lung cancer (NSCLC), colorectal cancer (CRC), head and neck squamous cell carcinomas (HNSCC), and glioblasomas are leading causes of death in the United States. These cancers are often driven by mutations in and dysregulation of the epidermal growth factor (EGF) receptor (EGFR), a receptor tyrosine kinase (RTK) critical for epithelial and epidermal tissue development and homeostasis. For cancers such as RAS/RAF wild-type metastatic colorectal cancer, treatment with anti-EGFR antibodies improves survival; how- ever, overall survival (OS) only increases by two to four months for combined antibody and chemotherapy treat- ment compared to chemotherapy alone. The OS increase is hindered by EGFR ectodomain mutations that cause antibody resistance. Development of anti-EGFR peptides is an attractive strategy as an antibody alternative for treatment of EGFR-driven cancers such as CRC due to their favorable peptide properties, including low immu- nogenicy, better tumor penetrance, and cheaper production. Further, peptides have high specificity and affinity for their targets and incorporation of non-canonical amino acids can tune their properties and increase their half- life. Altogether, these properties make development of peptides to target EGFR and emerging EGFR ectodomain resistance mutations highly attractive. To design and screen novel anti-EGFR peptides, the laboratory of Allison Walker (sponsor of this application) is partnering with the laboratory of Jens Meiler (co-sponsor of this ap- plication) and leveraging extant collaborations with peptide phage display expert Dr. Christina Lamers and col- orectal cancer expert Dr. Bhuminder Singh. The Meiler laboratory will integrate state-of-the-art protein modeling and peptide design methods to generate lead anti-EGFR peptide candidates. The Walker laboratory will collab- orate with the Lamers laboratory to screen lanthipeptides, peptides with post-translationally added lanthionine ring sidechain conjugations, using phage display to identify EGFR binding peptides. Lanthipeptides have fos- tered interset due to their frequently observed antibiotic, antitumor, and antifungal activity. All generated peptides will be tested for activity in the Singh laboratory. The central objectives of this proposal are to produce novel anti- EGFR peptides with therapeutic applications and to develop new algorithms to increase the scope of currently designable peptides. In Specific Aim I, I use existing protein design and screening techniques including com- putational peptide macrocycle design and phage display with lanthipeptides to design and screen anti-EGFR peptides. In Specific Aim II, I develop methodology for modeling and engineering RiPPs to ensure accurate modeling of sidechain conjugations and to enable incorporation of multiple post-translational modifications into a single peptide. As the methods in Aim II become available, they will be integrated into Aim I to model and optimize identified anti-EGFR lanthipeptides. Hence, these aims are designed to be highly complementary, yet independent, and will facilitate the rapid development of therapeutic peptides.

NIH Research Projects · FY 2025 · 2025-07

PROJECT SUMMARY This project aims to define the role of cancer-associated U2AF mutations in immune dysregulation. Splicing, the process by which intronic sequences are removed from mRNA precursors, is coordinated by machinery called the spliceosome. Mutations in components of the spliceosome and associated proteins have been linked to a wide range of pathologies, but are particularly prevalent in myeloid neoplasms, where they have been identified as drivers of abnormal hematopoiesis and of cancer progression. Several of these mutations occur in U2 Small Nuclear RNA Auxiliary Factor 1 and 2 (U2AF1 and U2AF2), which together play a key role in intron recognition. U2AF1 is one of the most commonly mutated splicing factors in the context of cancer, whereas mutations in U2AF2 are less common, but have been associated with more aggressive disease. Hyperinflammation and susceptibility to infection are also hallmarks of blood cancers. Notably, the risk of severe sepsis among those with hematological malignancies is 15 times higher than the general population. Under the current paradigm, dysregulated inflammatory immune pathways are linked to pathogenesis of hematological malignancies, but the mechanistic connection between mutations in splicing factors and dysregulated immune responses is poorly understood. Based on my preliminary data, I hypothesize that mutations in the U2AF heterodimer contribute to hyperinflammation through changes in splicing of immune transcripts. My proposal will characterize how cancer-associated mutations in U2AF1 and 2 lead to dysregulation of the innate immune response in ex vivo and in vivo models of sepsis. In Aim 1, I will identify and compare the consequences of disease-relevant mutations in U2AF1 and U2AF2 on the macrophage inflammatory response to lipopolysaccharide. In Aim 2, I will define how U2AF mutations impact inflammatory outcomes to sepsis in a mouse model. Training in long-read RNA-seq, CLIP-seq, and a variety of other molecular biology techniques will not only ensure the success of this proposal, but will also provide me with the skills necessary to one day lead a research program focused on understanding how the dysregulation of RNA processing contributes to human disease.

NIH Research Projects · FY 2026 · 2025-07

ABSTRACT While a large amount of work has focused on how stimuli are encoded in the transcriptional and physiological activity patterns within genetically defined neuronal populations, emerging evidence has clearly shown that stimuli activate only a small percentage of neurons in any given brain region. Therefore, understanding how specific functionally defined subsets of neurons within reward-related brain regions – such as the nucleus accumbens (NAc) - contribute to the progression of addiction will be important in finding more specific treatment strategies. We focus on how cocaine-activated ensembles are recruited initially and how these ensembles undergo changes over time to drive behaviors associated with cocaine use disorder. Epigenetic mechanisms - in which stimuli trigger long-lasting changes in transcription - have emerged as a mediator of drug-induced adaptation within the brain. Epigenetic regulation occurs at the nucleosome: DNA wrapped around an octamer of histone proteins, which constitutes a platform for epigenetic marks that dynamically regulate chromatin architecture and transcription. We identified a cocaine-induced epigenetic regulator in the NAc: lysine acetyltransferase 2a (KAT2a/Gcn5), showing that KAT2a is a critical regulator of cocaine reinforcement, cocaine-induced plasticity, and is expressed within cocaine-activated ensembles in the NAc. Building upon our strong preliminary data, we will probe how KAT2a regulates cocaine ensemble recruitment and maintenance by asking the following questions: 1. Does KAT2a expression dictate initial recruitment into cocaine-activated ensembles 2. Does KAT2a within recruited ensembles determine the cocaine-induced plasticity that occurs over time? Using single nucleus RNA sequencing (snRNAseq), ensemble-specific epigenetic profiling, and cellular resolution imaging in awake and behaving animals we will track the same cells over time to understand how KAT2a is involved in ensemble selection and maintenance and whether it is the initial cocaine ensemble that undergoes plasticity following cocaine self-administration or whether an entirely new ensemble is recruited by repeated drug exposure. Critically, this proposal goes beyond simply generating large quantities of multidimensional data – of which there are already many in the context of drug exposure. The next frontier of using these high-density approaches will be using them to ask targeted questions that were intractable before the advent of this technology.

NIH Research Projects · FY 2025 · 2025-07

PROJECT SUMMARY In Type 1 Diabetes (T1D), B lymphocytes present islet autoantigens to T cells, driving autoimmune destruction of pancreatic beta cells. Clinical trials targeting these T cell-B cell interactions have shown relative success, highlighting the importance of understanding pathogenic T-B interactions more precisely. The immediate challenges of these immunotherapies include a delay of T1D rather than durable protection, heterogeneity in individual responses, and undesirably broad immunosuppression. A major gap in knowledge of T1D pathogenesis is how T cells interact with B lymphocytes to expand and acquire pathologic functional potential. T follicular helper (Tfh)-like populations are increased in the peripheral blood of T1D individuals and high- affinity islet autoantibodies predict disease, pointing to a key role for germinal center (GC) Tfh cell/GC B cell responses in T1D. In non-obese diabetic (NOD) mice, Tfh cells can transfer diabetes. Work from our lab and others show that anti-insulin B cells can spontaneously adopt a GC phenotype, and that they can drive anti- insulin T cells to differentiate into Tfh cells. Conversely, pathogenic anti-insulin T cell clones drive anti-insulin B cells to become GC B cells and produce insulin autoantibodies. Our recently published work demonstrated that CD4-driven expression of Bcl6, which controls GC B cell and GC Tfh differentiation, is required for T1D. Therefore, I hypothesize that T1D anti-insulin B cells depend on interactions with GC Tfh cells to license the proinflammatory subsets of T cells that drives T1D pathogenesis. To test this hypothesis, we developed several new NOD models that allow dissection of the Tfh/GC B cell axis. These include 1) a model in which genetic deletion of SLAM-associated Protein (SAP) enables contrast between benign (SAP-/-) vs. pathogenic (SAP+) Tfh cells, 2) Bcl6fl/fl models, and 3) anti-insulin BCR and TCR transgenic mice with which we can separate autoreactive B and T cell expansion from their acquisition of effector functions, and how this process is impacted by loss of the key GC proteins, BCL6 and SAP. In Aim 1, I will determine the need for anti-insulin B cell engagement with Tfh cells in supporting lymphocytic invasion of islets and diabetes development. In Aim 2, I will dissect the pathogenic vs. benign Tfh phenotypic, metabolic, and transcriptomic changes in driving T cell functional changes in T1D. In Aim 3, I will characterize known and novel subsets of circulating Tfh-like cells elevated in PBMCs isolated from pre-symptomatic T1D individuals as they progress to diabetes onset. These experiments will identify key features of pathogenic Tfh cells in both mouse and human cells and will provide insight into the molecular control of pathogenic T/B lymphocyte interactions. Studies using mouse models will link pathogenic immune infiltration of beta cells with changes that are observable in the peripheral blood, as this is a practical biospecimen for clinical evaluation of progression in pre-symptomatic T1D individuals, and immunotherapy response. This work thus holds potential to uncover novel immunologic biomarkers and immunotherapeutic targets to delay or prevent beta cell destruction in T1D.

NSF Awards · FY 2025 · 2025-07

This grant provides support for the 2025 “Cyber Physical Systems (CPS) Rising Stars” workshop, held in conjunction with the 2025 Annual CPS Principal Investigators’ Meeting at Vanderbilt University in Nashville, Tennessee, March 2025. This workshop seeks to mentor promising PhD students and recent PhD graduates interested in pursuing academic careers in cyber-physical systems and help build that next-generation of outstanding researchers. Cyber-physical systems are engineered systems that deeply integrate computational elements with physical processes and are increasingly essential to the advanced technologies in scientific research and society. This workshop is modeled on prior successful CPS Rising Star workshops. It offers mentoring by leading experts in cyber-physical systems on navigating the early stages of a career in CPS, discussions about the CPS academic job market, guidance on applying for research grants, building research groups and collaborations, and extensive opportunities to network with the broad NSF CPS research communities at both the CPS Rising Stars workshop and the CPS PI Meeting. Based on applications to the workshop, participants are selected by the workshop program committee of CPS researchers and are provided support for the workshop. 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 2025 · 2025-07

This project will show how fire spreads on a global scale and link that behavior to the local scale. Wildfire damage to infrastructure and ecosystems is rising. It is possible to coexist with wildfires if decision makers consider fire behavior and take adaptive approaches, such as wildland fuel reductions and community home hardening. Knowledge of where and when adaptive approaches are needed requires a clear understanding of how wildfire propagates at multiple scales under different weather scenarios. Although researchers have made a substantial effort to model wildfire behavior at different scales, until recently, they knew little about how fires behave once they enter communities. Wildfire propagation models offer a unique opportunity to link fire behaviors on the global scale all the way to the individual-building level in communities. Making this link will allow for more effective wildfire management that couples fuel reduction and home hardening strategies tailored to account for the physical, social, ecological, and economic characteristics of each community. This project will establish a framework to merge characteristics of the built environment with those of wildlands to improve models of fire risk in fire-prone communities. The research will start by linking wildfire models to simulate the behavior of fire at different scales - from a global domain to the community level. In addition, the approach to wildfire risk modeling will consider houses as drivers of fire, rather than simply recipients of fire. This will be achieved using a new community wildfire propagation model, AGNI-NAR – Asynchronous Graph Nexus Infrastructure for Network Assessment of Wildland-Urban Interface Risk. AGNI-NAR is as a decision-making tool that captures fire interaction between vegetation and structures to allow stakeholders to make informed wildfire fuel and home hardening decisions at the wildland, individual property, and community landscape levels. Recognizing that every community is unique, the project will seek to co-produce actionable solutions using the wildfire models through iterative engagement with key stakeholders in the study areas to identify socially acceptable mitigation scenarios. 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 · 2025-07

Project Summary/Abstract Diabetes is characterized by a reduction in functional insulin-producing β cells within the pancreatic islet, leading to the onset of hyperglycemia. Establishment of adult -cell mass occurs during gestation and is highly variable across the human population. Individuals that are born with less -cell mass may have increased risk of developing Type 2 Diabetes (T2D) later in life. Current studies aim to create therapies by generating new replacement  cells in vitro or expanding existing  cells in vivo, raising the relevance for understanding the molecular mechanisms controlling both differentiation and proliferation of β cells. Known transcriptional networks regulate pancreas organogenesis. One key member of this network is the homeobox transcription factor, pancreatic and duodenal homeobox 1 (Pdx1) which is essential for -cell differentiation and proliferation. Our published data revealed that  cells lacking Pdx1 or with ectopically high Pdx1 levels fail to progress through the cell cycle.  cells with elevated Pdx1 are also more likely to undergo apoptosis. Taken together, these data suggest that dynamic regulation of Pdx1 levels is required for β-cell proliferation and maintenance of functional β-cell mass. Many transcription factors, including Pdx1, contain domains that mediate physical interactions with other transcriptional regulators, that directly affect target gene selection, protein stability, or function. Our group identified a motif located within the Pdx1 C-terminus, between amino acids (aa) 210-238, through which Pdx1 interacts with either Oc1/Hnf6 (aa210-238) or the E3 ubiquitin ligase substrate adapter protein, SPOP (aa224- 238). Our collaborators have shown that these interactions overlap and are mutually exclusive. Interaction of Pdx1 with SPOP results in Pdx1 degradation, while interaction with Oc1 stabilizes Pdx1 and promotes endocrine cell differentiation. Here I propose that the balance between SPOP and Oc1 interactions with the Pdx1 C- terminus directly influences the choice between proliferation or differentiation. Ultimately, the proposed studies will examine the novel role of these Pdx1 C-terminal interacting domains in vivo and will provide insight into the mechanism by which these interacting partners influence endocrine differentiation and proliferation during development. Results of the proposed studies will inform efforts to optimize directed differentiation of β cells ex vivo for cell-based therapies and in vivo to expand β-cell mass in individuals with diabetes.

NSF Awards · FY 2025 · 2025-07

Tennessee Technological University, the University of Tennessee Knoxville, Meharry Medical College, and Vanderbilt University have joined in this project to address health challenges via Artificial Intelligence (AI) and Machine Learning (ML) infused workshops and training. At present, Tennessee ranks 44th among the 50 states in national health outcomes. This project will advance the use of modern, AI/ML-enabled computer technology in medical research and healthcare delivery. At the heart of the project is a three-part workshop series, powered by National AI Research Resource (NAIRR) Pilot resources aimed at accelerating interdisciplinary research at the intersection of advanced cyberinfrastructure, AI/ML, and health outcomes. These workshops train participants in high-performance computing, cloud-based AI applications, and open data tools, while fostering sustained collaboration among medical professionals, engineers, scientists, and students who participate. Workshop course content and outcomes will be shared with the NSF NAIRR program and broadly with the public. This project brings together leaders in medical AI/ML research at Vanderbilt University and the University of Tennessee, along with emerging research cyberinfrastructure centers such as Meharry Medical College. It builds upon collaborative frameworks previously advanced by the AI Tennessee Initiative, a statewide initiative led by UT Knoxville and TN Tech's AI Center---structures that have demonstrated success in enabling cross-institutional efforts. The workshops are linked to the usage of NAIRR Pilot AI resources, and will train participants to use NAIRR resources through hands-on training. Significant training on NAIRR resources---both HPC and Cloud---for AI applications, methods, and practice is included in all three workshops. Relevant methods, applications, and techniques working on open data will provide participants with significant training and scaffolding to engage in further AI/ML use-inspired research and to use NSF NAIRR resources in the future. Overall, this workshop series will engage and train a significant group of medical professionals, scientists, engineers, and pre-professional students on NAIRR Pilot resources and AI/ML concepts, advancing the careers of medical professionals, scientists, and engineers. 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 2025 · 2025-07

The Sub-national Nonstate Actor Governance (SNAG) project introduces a new measurement strategy and public dataset to measure territorial control at the local level within conflict zones, tracked over time. Understanding how groups gain or lose territorial control, and thus how conflicts begin, evolve, and end, is essential to national security and preparedness. Yet scholars, policymakers, and military strategists lack reliable and accessible techniques to measure and monitor territorial control within conflict zones. Existing empirical research is focused on a limited number of conflicts for which there happen to exist reliable measures of local-level territorial control over time. This limits ability to understand conflict more generally, and to apply knowledge to new threat environments. This research draws upon open-source information to ensure a transparent process that is easily replicated across contexts and adapted to new measurement challenges. The project uses machine learning and natural language processing (NLP) tools to automatically detect mentions of belligerent activity and control in a corpus of open-source texts, which are then used to produce spatially and temporally disaggregated estimates of rebel and government territorial control. The Subnational Nonstate Actor Governance (SNAG) project measures nonstate actors’ territorial control and governance at the local level, capturing temporal variation throughout conflict, comparable across contexts. This project makes both substantive and methodological contributions, generates new publicly available data capturing nonstate actors’ territorial control, uses an approach that translates across contexts to facilitate comparative analyses. The PIs annotate text from a corpus of news reports from conflict zones, identifying indicators of rebel and government territorial control with location and time information. These annotations are then used to train a new natural language processing pipeline, which is applied to the remainder of the corpus to automate the process of extracting relevant information from the full corpus. The information produced by this process is incorporated into a measurement model to produce fine-grained spatio-temporal data on conflict belligerents’ territorial control within conflict zones, facilitating systematic comparison of these phenomena within and across conflicts. The subnational territorial control data are used to investigate basic research questions related to the causes and consequences of territorial control and governance, fundamental to understanding the security risks in “differently governed” spaces, the efficacy of counterinsurgency aid, and the consequences for state-building after conflict. Methodologically, SNAG contributes new tools for generating geospatial data from text and for developing spatial latent variable models adaptable for additional social science applications. 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 · 2025-07

PROJECT SUMMARY (ABSTRACT) Helicobacter pylori is a Gram-negative bacterium that colonizes the stomachs of about half the world’s human population. Although most infected individuals remain asymptomatic, H. pylori infection can lead to adverse health outcomes, including peptic ulcer disease, gastric adenocarcinoma, or gastric lymphoma. H. pylori infection is the primary risk factor for the development of gastric cancer, a leading cause of cancer-related deaths, and has been designated a Group I Carcinogen by the World Health Organization. Differences in health outcomes among H. pylori-infected individuals can be partially attributed to the genetic diversity of H. pylori: certain strains produce virulence factors that are associated with a higher risk of disease development. One of these virulence factors is Vacuolating Cytotoxin A (VacA), a secreted pore-forming toxin. The vacA gene contains highly polymorphic regions that vary among strains. Certain forms of VacA display more activity in cell culture, and H. pylori strains producing these active forms are associated with a higher risk of gastric cancer than strains producing less active forms. Active variants of VacA form channels in cell membranes and induce a range of alterations within cells, including the swelling of late endosomes (vacuolation), mitochondrial dysfunction, and even cell death in certain cell lines. However, the mechanisms by which VacA promotes H. pylori fitness and modulates host cell function remain incompletely understood. My preliminary studies indicate that VacA influences host cell cholesterol metabolism by significantly increasing the transcript abundances of genes involved in cholesterol biosynthesis and altering cellular cholesterol levels. VacA-induced alterations in cellular cholesterol biosynthesis are likely to be relevant in multiple contexts: (i) VacA binds to cholesterol-rich regions of host cell membranes, (ii) H. pylori is a cholesterol auxotroph that can acquire cholesterol from host cells, (iii) dysregulated cholesterol biosynthesis contributes to malignant transformation and gastric cancer risk, and (iv) statin therapy for high cholesterol has been associated with a lower incidence of stomach cancer in humans. I hypothesize that VacA disrupts cholesterol host cell cholesterol homeostasis, and that this process influences H. pylori cholesterol acquisition. The proposed research will address these hypotheses through three specific aims. In Specific Aim 1, I will further define the specific alterations in gastric cell sterol biosynthesis triggered by different forms of VacA using enzymatic assays, liquid-chromatography tandem mass spectrometry (LC-MS/MS), and RT-qPCR. In Specific Aim 2, I will assess the effects of VacA on cholesterol efflux, uptake, and trafficking using LC-MS/MS and confocal imaging assays. In Specific Aim 3, I will determine whether VacA influences H. pylori cholesterol acquisition by comparing the cholesterol uptake of VacA-producing strains and various VacA mutant strains. Taken together, these aims will lead to a better understanding of cellular responses to VacA and will define the consequences of VacA-induced cholesterol dysregulation for the host and bacteria.

NIH Research Projects · FY 2025 · 2025-06

PROJECT SUMMARY AND ABSTRACT. A key feature of cocaine use disorder is an increase in drug taking and seeking that develops over an individual’s drug-use history. To this end, a large amount of work has been focused on understanding how plasticity in reward-related brain regions strengthens circuits that drive motivation. However, in humans and animal models, while chronic drug use increases drug seeking, it simultaneously reduces motivation for alternative reinforcers such as sucrose. The goal of this proposal is to understand the neural mechanism by which cocaine self-administration differentially alters the neural encoding drug and non-drug reinforcers. The nucleus accumbens (NAc) is a key region that causally mediates reward encoding for both drug and non-drug rewards. This region is comprised of medium spiny neurons (MSNs) that are largely segregated into two non-overlapping populations based on their expressions of D1 and D2 type dopamine receptors. D1 MSNs, which specifically drive drug seeking, are activated at the population level by both drugs and sucrose and undergo robust drug-induced plasticity following repeated cocaine use. Two questions guide our research in this area: 1. Do cocaine and sucrose activate different populations of D1 MSNs? And 2. Does repeated cocaine use differentially affect the ability of cocaine or sucrose to increase D1 MSN activity in the NAc? Using cellular resolution imaging in awake and behaving animals with microendoscopes, we will record single-cell neural activity in the same animals in response to sucrose and cocaine and determine how cocaine self-administration alters the dynamics of each ensemble over time. We hypothesize that 1. Cocaine and sucrose recruit non-overlapping neuronal populations, and 2. Cocaine self-administration increases the ability of cocaine and decreases the ability of sucrose to increase D1 MSN activity. The training plan includes a mentoring team led by Erin Calipari, PhD (sponsor) with collaborators Brad Grueter, PhD, Thilo Womelsdorf, PhD, and Edward Nieh, PhD. This team will provide strong training in the use of cellular resolution imaging in awake and behaving animals and computational analyses to understand the relation of complex activity dynamics in the brain and in behavior. The training plan was specifically crafted to build upon Dr. Bradley Barth’s strong foundation of computational modeling in peripheral tissues to bring his training into the addiction field. Together this project will answer a fundamental question in the addiction field, while also providing training to help Dr. Barth become an expert in the neural dysfunction that occurs as a result of chronic drug use.

NIH Research Projects · FY 2026 · 2025-06

PROJECT SUMMARY The reversible phosphorylation of proteins is an essential process controlling cellular homeostasis. Protein kinases catalyze the transfer of phosphate from ATP to tyrosine (Tyr), serine (Ser), and threonine (Thr) residues in target proteins; protein phosphatases are responsible for removal of the phosphate group. Although Tyr phosphorylation is far less abundant than Ser and Thr phosphorylation (<0.1% of the total cellular phospho- amino acid content), it plays essential roles in many cellular signaling events. But Tyr phosphorylation is especially difficult to study, because it is low abundance and functions in rapid signaling events with a lifetime that is usually transient, increasing and then disappearing within minutes. Among the most useful tools for examining protein phosphorylation are phospho-specific antibodies (Abs), which can be used to readily quantify changes at phosphorylation sites and changes in their localization under various cell conditions. However, reliable phospho-specific Abs are difficult to obtain, due to poor specificity, limited availability of large-scale homogeneous preparations, and their inability to monitor protein phosphorylation in living cells. An attractive alternative to Abs is nanobodies (Nbs) – small (15 kDa), single domain, antigen binding fragments derived from camelid heavy chain-only Abs. Nbs targeting PTMs such as pTyr would be extremely valuable for the scientific community but reports describing such are very scant or non-existent. Although it has proven to be difficult developing Nbs targeting PTMs, our recent findings demonstrate remarkable success in developing Nbs targeting specific pTyr epitopes in two important families of signaling proteins – protein phosphatase 2A (PP2A) and the mitogen-activated protein kinase (MAPK) family member, ERK1/2. This proposal focuses on the development, characterization, and application of Nbs recognizing specific phosphosites in different subunits of PP2A, as well as the major MAPK family members, ERK1/2, JNK, and p38. We also will develop pan Nbs as probes for total protein abundances. Our approach will characterize the binding specificity, recognition, and affinity of each Nb for their targeted epitopes. We will determine the precise binding determinants by solving atomic resolution structures of Nb-peptide and Nb-protein complexes. We will systematically test our Nbs for their ability to recognize their respective phosphosite or protein target by Western analysis, immunoprecipitation, and immunohistochemistry, and determine effects of Nbs on MAPK and PP2A activity. Finally, we will develop Nb-based biosensors and PROTACs to respectively visualize phospho-epitope localization in cells and target them for degradation in living cells. The proposed work is responsive to PA-22-127, a technology development FOA requesting hypothesis-independent, broadly useful reagent and technology development. Completion of the proposed studies will not only yield novel tools for investigating signaling enzymes, but it will also open the door to a new technology that can be broadly applied to defining the phosphotyrosine proteome and expanding knowledge about the functions of this essential protein signaling event.