Vanderbilt University

NIH Research Projects · FY 2025 · 2022-09

Project summary Alzheimer’s disease (AD) and related dementias (ADRD) are exacerbated by neurovascular dysfunction. Astrocytes are key contributors to neurovascular health and blood-brain barrier (BBB) function. In response to pathogenic stimuli, astrocytes adopt a “reactive” phenotype generally characterized by morphological changes. Recent research has shown that reactive astrocytes can adopt a diverse spectrum of molecular identities, but the interplay between these different subtypes of reactive astrocytes and the brain vasculature remains unclear. Indeed, some studies have shown that reactive astrocytes negatively influence BBB function, while others have shown that reactive astrocytes are vital to neurovascular repair after injury. Most of these studies have been performed in the context of stroke or physical trauma, and while there are some emerging studies at single-cell resolution on reactive astrocyte states in ADRDs, there is little to no information on how these different states may directly contribute to neurovascular dysfunction. Herein, we propose to investigate how STAT3 activation in astrocytes drives neurovascular dysfunction in ADRDs. In preliminary work, using thin sections from postmortem human brain tissue, we have shown that AD patients have significantly increased numbers of STAT3-activated astrocytes and inflamed blood vessels. In a human in vitro model of astrocytes cocultured with brain endothelial cells, we have shown that inflammatory stimuli activate STAT3 signaling in astrocytes, which leads to BBB disruption, and inhibition of STAT3 activation in astrocytes mitigates these outcomes. Further, using combinations of the human in vitro model, ex vivo mouse cortical slice cultures, and in vivo manipulations, we have shown that alpha 1-antichymotrypsin (ACT)—a STAT3-regulated serine protease inhibitor—contributes directly to neurovascular dysfunction. Moving forward, we will build on these promising results in the following manner. In Aim 1, we will expand our human tissue studies into larger ADRD cohorts and employ advanced imaging techniques to quantify three-dimensional spatial relationships between STAT3-activated astrocytes and sites of vascular damage. In Aim 2, we will inhibit STAT3 signaling in astrocytes within transgenic mouse models of ADRD and evaluate longitudinal alterations to neurovascular dysfunction; these assessments will include single-cell RNA sequencing to characterize molecular changes to endothelial cells along the entire vascular tree. In Aim 3, we will causally link astrocyte-derived ACT to neurovascular dysfunction in transgenic mouse models of ADRD, as well as characterize prospectively synergy between ACT and APOE, which have known connections in AD and dementia risk. Collectively, outcomes from this work will define the mechanistic roles of STAT3-activated astrocytes in neurovascular dysfunction associated with ADRD and identify potential avenues for targeting astrocytes as an ADRD treatment strategy.

NIH Research Projects · FY 2025 · 2022-09

Project summary Cerebral amyloid angiopathy (CAA) is a disease that occurs when amyloid beta (Aβ) forms deposits on brain blood vessels. CAA frequently co-occurs with Alzheimer’s disease (AD) and is a significant risk factor for intracranial hemorrhage and dementia. There are no approved treatments for CAA, and the molecular etiology of the disease remains unclear, which has prevented the development of effective therapeutic interventions. Here, we propose to study cerebral perivascular fibroblasts and vascular fibrosis signaling pathways as potential contributors to CAA pathology. More than 20 years ago, pioneering work showed that astrocyte-specific upregulation of transforming growth factor beta 1 (TGFβ1), a master regulator of tissue fibrosis, could specifically induce Aβ pathology in the cerebrovasculature that was reminiscent of CAA. However, the mechanistic actions of TGFβ1 that could drive such a response were never elucidated. In studying postmortem human brain tissue from CAA patients, we have found that cerebral perivascular fibroblasts acquire myofibroblast markers around vessels with Aβ deposition and fibrotic signatures—this phenotype is observed specifically in CAA but not AD or age-matched controls. Further, this phenotype is replicated in 5xFAD mice after intracerebroventricular injections of human vascular-derived human Aβ seeds, which yields CAA-like pathology. Hence, we hypothesize that activation of perivascular fibroblasts and fibrotic signaling pathways in the perivascular niche leads to Aβ deposition, vascular fibrosis, and acquisition of the CAA phenotype. In Aim 1, we will explore this hypothesis within two complementary mouse models using three-dimensional tissue imaging techniques, single-cell RNA sequencing, and blood flow measurements. In Aim 2, we will leverage a novel bioengineered model of human cerebral arterioles to understand how TGFβ1 shapes the fibrotic microenvironment through multicellular crosstalk. In Aim 3, again in mouse models, we will target cerebral perivascular fibroblasts and fibrotic signaling pathways using gene silencing techniques and small molecule treatments and determine if CAA pathology is lessened. Collectively, these studies will unveil and characterize how perivascular fibroblasts and vascular fibrosis contribute to CAA pathology. Moreover, these investigations will identify potential preclinical drug development strategies focused on targeting fibroblast activation and signaling pathways that contribute to a pro- fibrotic microenvironment in CAA.

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY: The mission of the proposed Kidney Precision Medicine Project Tissue Interrogation Site (TIS) is to apply a platform of integrated multiomic imaging and spatially resolved molecular technologies to biopsies from patients with acute kidney injury (AKI) and chronic kidney disease (CKD) to define key pathways and understand the molecular drivers of disease heterogeneity. This TIS will leverage the unique resources of the Mass Spectrometry Research Center and VU Biomolecular Imaging Center, as well as the world-class clinical environment of the Vanderbilt University Medical Center, the valuable input of our patient partner, and the advanced biocomputational infrastructure available through the data analysis laboratories at Vanderbilt University and the Delft University of Technology. The main objectives of our TIS are to: (1) generate high quality images of kidney biopsies using an innovative state-of-the-art multimodal imaging pipeline that includes matrix- assisted laser desorption/ionization imaging mass spectrometry (IMS), autofluorescence, and stained microscopy; (2) acquire spatially resolved proteomics and transcriptomics data using microLESA, laser capture microdissection, and the GeoMx Digital Spatial Profiler as well as perform network and enrichment analysis to validate and enhance biological interpretation of the imaging data; and (3) implement advanced data analysis strategies to identify potential biomarkers and optimal points of therapeutic intervention. With this suite of technologies, data analysis capabilities, and previous experience developing atlases of healthy-for-age human kidney tissue, we will create kidney tissue atlases to define the molecular landscape of biopsies from various patient populations (e.g., age, race, sex) as well as of AKI and CKD clinical phenotypes, disease states, and transitions; with an eye toward determining potential disease subclasses. To accomplish these aims, we assembled a highly interactive and established team of investigators consisting of complementary expertise in nephrology, cell biology, analytical chemistry, and data science.

NIH Research Projects · FY 2025 · 2022-09

Project Summary The a priori prediction and design of efficient mutant enzymes are broadly recognized as a “Holy Grail” in chemistry and biology because it will allow researchers to find effective enzyme variants to degrade environ- mental pollutants, conduct late-stage functionalization of fine chemicals, and treat diseases. Directed evolution has been widely applied to identify optimal enzyme variants for chemical reactions, but how to accelerate the screening cycles remains a critical roadblock due to the unknown relationship between sequence, structure, and kinetics for enzyme catalysis. To overcome this challenge, the PI has been developing three computational in- frastructures: 1) an integrated enzyme structure-function database, IntEnzyDB, that provides clean and tabulated data for data-driven modeling; 2) a new software module, RosettaQM, for evaluating enzyme-reacting species interactions using quantum mechanical methods; and 3) a high-throughput workflow, EnzyHTP, that allows com- putational screening of enzyme variants. Enabled by these tools, in this MIRA proposal, the PI emphasizes advancing new computational tools to predict and design new enzyme catalysts. First, the PI will develop a multistate kinetic scoring function to predict the influence of mutation on apparent enzyme kinetics by leveraging the enzymology data stored in IntEnzyDB and the QM-based enzyme-reacting species interaction scoring in RosettaQM (Project-1). The PI plans to develop a kinetic scoring function that accounts for contributions of mul- tiple reactive states along a reaction pathway and is distinct from existing computational rational engineering strategies that emphasize the stabilization of one hypothetical transition state. The multistate kinetic scoring will be experimentally validated to predict efficiency-enhancing mutations for FR29 esterase for a proof of concept and fluoroacetate dehalogenase FAcD for environmental pollutant degradation. Second, the PI will develop an integrated enzyme predicting protocol that augments molecular simulations and machine-learning models to design enzyme variants to accommodate non-native substrates for late-stage functionalization of drug-like mol- ecules (Project-2). EnzyHTP will be further developed to incorporate machine learning models to achieve multi- objective prediction of beneficial mutations, evaluating the impact of mutations on enzyme electrostatic environ- ment, substrate positioning, substrate-enzyme interactions, and enzyme stability, solubility, and promiscuity. En- zyHTP will be experimentally examined in the design of new group-transferases to accommodate S-adenosyl methionine analogues for late-stage functionalization of everninomicin, a promising drug for treating a broad spectrum of antibiotic-resistant bacterial infections. In summary, the proposed research will deliver enabling computational tools for virtual prediction and design of function-enhancing enzyme variants for biomedical and biocatalytic uses.

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY – Overall This application proposes the continuation of a Tissue Mapping Center (TMC) for the human kidney within the Human BioMolecular Atlas Program (HuBMAP). The mission of the proposed TMC is to build a platform of integrated technologies for imaging and molecular analysis that enables the construction of comprehensive 3- dimensional molecular atlases of the human kidney. This TMC will leverage the unique resources of the Mass Spectrometry Research Center and the National Research Resource for Imaging Mass Spectrometry at Vanderbilt University, the world-class clinical environment of the Vanderbilt University Medical Center, and the advanced biocomputational infrastructure available to the TMC through the Data Analysis Core laboratories at Vanderbilt University and the Delft University of Technology, Netherlands to create a capability to molecularly characterize human tissues in 3-dimensions at a level of understanding unrivaled by current technologies. The innovative aspect of the proposed TMC is the integration of imaging mass spectrometry, highly multiplexed immunofluorescence microscopy, autofluorescence microscopy, stained microscopy, spatial transcriptomics, spatial proteomics, and single-cell RNA-seq to create comprehensive 2-D and 3-D molecular and cellular atlases of the human kidney. Through segmentation and cell type analysis determined by classical markers, we will correlate our molecular and clinical information to the existing knowledge of the kidney to better define the normal phenotypes across a range of diverse samples. The application of this multimodal pipeline to the kidney will provide a new paradigm of understanding the normal state of this organ across multiple dimensions, both molecular (e.g., lipids, metabolites, proteins, and transcripts) and spatial (e.g., whole organs to single cells). As a HuBMAP participant, the molecular atlases produced by this TMC will be disseminated to the community and to collaborators to generate new hypotheses regarding the function of this important organ system, enabling new insight into human health and disease. This multidisciplinary effort requires the creation and integration of three capabilities to 1) procure and manage human tissue specimens, 2) determine and mitigate non-biological pre- analytical factors, and 3) acquire, process, and disseminate multimodal 3-dimensional imaging and large-scale omics data. The goal of the proposed kidney TMC is to create atlases for community users, physicians, and researchers to navigate across the anatomical and molecular landscape of the kidney, generate novel hypotheses, and tackle meaningful biomedical research questions.

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY/ABSTRACT Fetal growth restriction is associated with a profound increase in perinatal and even long-term health risk. Antenatal care is key to optimizing outcomes and preventing stillbirth, yet up to half of growth-restricted infants are not identified during pregnancy. The placenta serves a central in maintaining a healthy pregnancy and supporting fetal growth; yet, direct assessment of placental development is glaringly absent from clinical care as there are no practical tools that enable providers to monitor placental development. In recent years, 3D ultrasound (3DUS) has allowed investigators to identify important associations between placental morphology and clinical outcomes using a variety of offline medical image analysis techniques. However, these techniques typically require extensive manual input. Moreover, we have recently developed an innovative tool based on a dynamic model of fetal-placental growth that considers placental growth in the evaluation of fetal growth and can help identify pregnancies at increased risk of growth restriction. However, this tool requires placental volume assessment, which, as mentioned above, remains impractical for clinical use. In this proposal, we will expand and enhance our automated segmentation tools to enable bedside volumetric assessment of the placenta throughout pregnancy. In addition, we will develop novel tools and parameters for assessing placental shape, gross morphology, and vascularity in an effort to identify additional features of placental development that can augment our understanding of placental development and create additional markers of placental health. Taken together, the current proposal leverages an ongoing collaboration between computer scientists and physician-scientists to utilize modern fully automated image analysis methodology to create clinically impactful placental assessment tools that can be integrated into the clinical workflow. The proposed research will allow bedside assessment of placental morphology and vascularity, which can be leveraged into precision medicine approaches and allow for more accurate and reliable surveillance of fetal growth and well-being. Specifically, we will build: 1) Refine and validate a fetal-placental growth model using automated early placental volume and placental histopathology, 2) Extend to include later gestational ages and expand the toolkit to include novel measures of placental shape and vascularity, and 3) create an augmented version of the dynamic model that incorporates the added functionality of our segmentation pipeline, as well as serum biomarkers, to result in a clinically useful tool for monitoring fetal growth. We anticipate that this proposal will significantly change clinical care and create a new, placenta-based paradigm for understanding and managing fetal growth disorders.

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY/ABSTRACT: For many psychiatric disorders, such as substance use disorder, sex is a critical biological variable and women represent a particularly vulnerable population. For cocaine use disorder women transition to addiction faster, take more cocaine, experience more adverse consequences, and have more difficulty remaining abstinent. Previous research has exposed significant sex differences in the mesolimbic dopamine system, a neural circuit critical in reward learning and motivation, and identified the gonadal hormone 17b-estradiol as a significant contributor to this vulnerability. The mesolimbic dopamine system - which originates in the ventral tegmental area and projects to the striatum - has been shown to be involved in the expression of sex-specific behavior especially as it relates to cocaine reward and motivation. To understand cocaine use disorder in females we need to understand the fundamental mechanisms by which drug responses are mediated and how this influences the systems these drugs act on – I focus here on the dopamine system. While substantial work has focused on sex differences in the anatomy of dopamine neurons and relative dopamine levels between males and females, an important characteristic of dopamine release from axon terminals in the striatum is that it is rapidly modulated by local regulatory mechanisms independent of somatic activity. The dopamine system contains a high density of estrogen receptors (ERa, ERb, and GPER-1 subtypes) that likely serve as important substrates through which ovarian hormones exert their influence on dopaminergic function. Indeed, there is robust dopamine system regulation by ovarian hormones where 17β-estradiol (E2) increases dopamine cell activity and release from dopamine terminals in the striatum. In Aim 1, I will combine analytical chemistry and optical imaging techniques with pharmacology to isolate dopamine terminals in the nucleus accumbens core and characterize the role of specific estrogen receptor subtypes in the modulation of presynaptic dopamine release. Further, previous work from our lab has shown selective increases in cocaine-evoked dopamine release, cocaine potency, and cocaine affinity for the dopamine transporter in estrus females (with high levels of circulating E2). In Aim 2, I will define how direct manipulation of estrogen receptors affects dopamine transporter-mediated clearance and potency of cocaine at terminals in the nucleus accumbens core. This work builds on the foundation set by innovators in the field to examine the role of estrogen receptors in presynaptic dopamine dynamics, and further proposes to investigate how these mechanisms modulate cocaine effects at the dopamine transporter. Importantly, this work provides me with an exceptional training opportunity while simultaneously providing answers to fundamental questions in the field, which are imperative in developing effective pharmacotherapies for cocaine use disorder. Together, understanding the mechanisms governing dopamine regulation and drug effects on the dopamine system is vital to our understanding of the basic mechanisms that govern neurotransmission in both sexes, as well as evidence-based interventions for diseases that are characterized by dysregulation of this system.

NIH Research Projects · FY 2025 · 2022-09

Numerous challenges may impede the research success and productivity of early and mid-career faculty. Faculty research productivity is closely intertwined with psychological stability. Factors such as support, mentoring, professional networking to forge collaborations, and a satisfactory work-life balance are associated with improving faculty stability. There are several programs largely focused on increasing the pipeline from undergraduate to graduate and post-doctoral scholars, leaving a gap in the training and mentoring needs of new and mid-career tenure-track faculty that require training and mentorship to enhance scholarly productivity and achieve success in grant writing in biomedical research. The overarching goal of the Faculty ACCESS Program is to provide early and mid-career faculty with tools and resources necessary to be successful biomedical scientific leaders. The objectives are 1) To provide programming and mentoring for early and mid-career faculty that focuses on skill building to increase rigorous research productivity, 2) To provide targeted training in grant-writing to increase NIH grant submissions, 3) To provide a network of funded senior faculty mentors to enhance social and tangible support for trainee participants. Expected outcomes of the Faculty ACCESS Program are to facilitate skill development in rigorous research to increase publication outputs, increase NIH grant submissions and resubmissions, better prepared faculty for promotion and tenure processes. The overarching goal is to facilitate success of faculty and increase retention in the biomedical research field.

NIH Research Projects · FY 2024 · 2022-09

Basement membranes are the oldest, most conserved forms of extracellular matrix and serve to separate tissue layers, direct signals to neighboring cells, insulate tissues from signals, and provide mechanical support. Further, basement membranes are subject to mechanical damage and require repair. Faulty basement membrane repair can aid in the progression of diseases such as asthma and diabetes, and diseases of the basement membrane itself, including Alport syndrome and Goodpasture syndrome. Therefore, understanding how basement membranes repair will be vital to treating these conditions. My work utilizes the Drosophila midgut basement membrane to probe repair dynamics. In Drosophila, all major basement membrane components have been conserved but with less redundancy than mammals. Our lab has developed an assay to reproducibly damage the basement membrane and study the repair process. Following damage, the basement membrane becomes less stiff and less dense, indicated by a mechanical stress/strain assay and electron microscopy, respectively. Previously it was reported that processes required for basement membrane repair are also required to maintain basement membranes that have not been damaged; these processes include continuous matrix synthesis and regulation of enzymes (matrix metalloproteinases and peroxidasin). Thus, it is unclear whether basement membrane damage is actively detected, or instead, passively repaired by homeostatic mechanisms. My preliminary data suggest basement membrane damage is actively detected. Following damage, the synthesis of matrix components is upregulated in a specific subset of gut epithelial cells we call matrix-makers, and these may be the same cells that express a mechanosensory stretch-activated ion channel, Piezo. This raises the possibility that a change in stiffness of damaged basement membranes signals the initiation of repair. Piezo knockout flies are able to assemble and maintain basement membranes in the adult fly, but, excitingly, Piezo knockouts cannot repair basement membranes after damage. This is evidence of a unique mechanism that detects basement membrane damage and initiates repair. I hypothesize that a loss in matrix stiffness triggers basement membrane repair mechanisms. In Aim 1, I propose to characterize a transient cell population responsible for synthesizing new matrix components following basement membrane damage. In Aim 2, I propose to identify the role of Piezo and its response following basement membrane damage. I expect to identify the first mechanism for detecting and repairing basement membranes. Understanding this mechanism will provide fundamental insights into epithelial biology and will be critical to treating and understanding diseases of the basement membrane.

NIH Research Projects · FY 2024 · 2022-09

PROJECT SUMMARY/ABSTRACT An aging human population has revealed the burden of chronic illness and age-related disease, and by understanding the genetic and environmental factors that drive aging, we will be better suited to develop and test therapeutics that slow age-related disease. As biological aging is influenced by both genetics and the environment, our laboratory studies the cellular and molecular drivers of aging, with a particular focus on inter- organelle communication in disease. Here, we newly describe a dramatic reorganization of endoplasmic reticulum (ER) subdomains in aging C. elegans. The ER mediates inter- and intracellular signaling through these sheet and tubule domains, and sheet:tubule balance is critical for cell function. ER tubules store calcium and lipids, and at specialized membrane contact sites, they regulate mitochondrial dynamics. We find that the aging ER undergoes a loss of rough ER sheets and expansion of smooth ER tubules, and our data suggest that modifying ER structure is sufficient to preserve mitochondrial morphology in age, making the ER a potential target in preventing age-related mitochondrial fragmentation. Though autophagy is seen as cytoprotective in aging, we show that autophagy is necessary for age-related ER remodeling. This may be explained by ER- phagy, a form of ER-selective autophagy that has not been studied in the context of aging, as ER-phagy shares common recycling processes. Finally, we demonstrate that caloric restriction, which extends lifespan, prevents this age-related loss of ER morphology. Therefore, we hypothesize that dysregulated ER-phagy drives age- related ER remodeling and that dietary restriction promotes longevity by mitigating this loss of ER form and function. To discern whether these changes are attributable to selective ER-phagy, rather than general autophagy, I will use a combination of in vivo imaging, fluorescent reporters, and RNAi to investigate the molecular mechanisms leading to a change in ER subdomains with age (Aim 1). In Aim 2, I will use dietary restriction, a robust longevity paradigm, to investigate the cause(s) and consequence(s) of ER remodeling in healthspan and lifespan regulation. This work will be conducted at Vanderbilt University under the supervision of Dr. Kristopher Burkewitz, Assistant Professor of Cell & Developmental Biology, who discovered roles for ER function in lifespan regulation through ER-mitochondrial crosstalk. I will additionally be supported by Dr. David Miller, Professor of Cell & Developmental Biology, whose lab is experienced in electron microscopy and pioneered many genetic engineering techniques I will perform in C. elegans. In these studies, I will receive feedback from a strong advisory committee with expertise including interorganelle signaling, membrane dynamics, and aging physiology. Successful completion of this project will not only advance our understanding of cell biology and the role of the ER in aging but also establish ER structure and function as therapeutic targets in the treatment of age-related disease.

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY: The overarching goal of the proposed work is to apply a platform of integrated multiomic imaging modalities and spatially resolved molecular characterization technologies to normal aging and Alzheimer’s disease brain tissues in order to discover and define key molecules and pathways that drive the underlying heterogeneity of the disease. This work will leverage the unique resources of the Mass Spectrometry Research Center and VU Biomolecular Imaging Center, as well as the world-class clinical environment of the Vanderbilt University Medical Center, and the advanced biocomputational infrastructure available through the data analysis laboratories at Vanderbilt University and the Delft University of Technology. The main objectives of our proposed work, which we believe will move the field forward, are to: (1) engage the molecular complexities of Alzheimer’s disease in a new and robust way to create molecular atlases of the heterogenous neuropathologies observed in human brain tissue, (2) define how the molecular underpinnings of neuritic plaques and neurofibrillary tangles overlap with pathways implicated in contributory neuropathologies to inform more precise development of experimental therapies; and (3) deploy multiomic tools to document cell-type specific molecular changes between normal aging and Alzheimer’s disease in well-defined microanatomical regions so changes in the metabolome, lipidome, proteome, and transcriptome can be attributed to the correct cell types and microenvironment. With this suite of technologies, advanced data analysis capabilities, and prior experience in developing atlases of healthy-for-age human tissues, this team will generate datasets with unprecedented detail and the potential to drive molecular discovery. To accomplish these aims, we assembled an interactive and established team of investigators, covering complementary expertise in Alzheimer’s disease, cell biology, analytical chemistry, and data science; and with direct in-house access to advanced instrumentation and facilities. We believe that our spatially resolved and molecularly comprehensive approach will lead to improved mechanistic understanding of Alzheimer’s disease and that these insights could inform better treatment options.

NIH Research Projects · FY 2025 · 2022-09

ABSTRACT Hearing loss is a major cause of disability that affects over 48 million Americans. Cochlear implants (CIs) are neuroprosthetic devices that allow people with profound hearing loss to recover hearing and speech comprehension. However, CI surgery outcomes are highly variable and difficult to predict, which creates a challenge for clinicians to guide patient decisions and expectations. Speech recognition is a multisensory process. Although it is known that visual speech cues can improve auditory speech recognition, the visual and audiovisual abilities of CI users have not been well characterized before and after cochlear implantation. In my preliminary data, I show that pre-implantation visual and audiovisual speech recognition predicts post- implantation auditory speech recognition, suggesting that multisensory integration may play an underappreciated role in CI outcomes. In the proposed experiments, I will explore changes in visual and audiovisual performance following CI surgery through a battery of sensory experiments (Aim 1). I will also assess the neural correlates of any behavioral changes using an innovative approach by simultaneously recording electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) responses over time (Aim 2). Finally, I will identify pre-implantation factors that predict post-implantation speech recognition and synthesize these data into a prediction model using machine learning (Aim 3). Through the experiments proposed in this fellowship application, I will comprehensively characterize the longitudinal changes in sensory perception and cortical organization following cochlear implantation. I will also use these findings to develop a novel clinical tool for predicting CI outcomes. The proposed plan integrates my research interests in auditory neuroscience with my clinical interests in otolaryngology, and it will set me up for success as a future physician-scientist.

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY About 60% of children can’t read proficiently, which is concerning as reading comprehension (RC) is linked to educational, vocational, and health outcomes. While a robust neurocognitive literature exists on word-level processes, a necessary but not sufficient skill for RC, similar studies at the discourse level (i.e., while reading passages/connected text) are largely absent in developing readers. This proposal tackles this needed research by systematically interrogating how adolescents’ neural variations during situation model formation (or building mental models while reading) results in RC success/failure. A critical consideration for such research is that texts are not monolithic, even though they are often treated as such: they vary by granular text features (e.g., word frequency) and by their superstructures, or whether a text is narrative (NarrT, stories) or expository (ExpT, informational text such as science passages). This is important, as ExpT is central for learning new material, while NarrT for socio-emotional growth. Notably, NarrT RC is easier than ExpT RC, a phenomenon which is poorly understood and not explained by granular text feature differences. Building upon our initial neurocognitive findings, along with existing theoretical and empirical work, we use neuroimaging coupled with behavioral methods to garner insights as to where (in the brain), when (at which text junctures), and thus how NarrT vs ExpT RC breaks down. Initial findings suggest that while both NarrT and ExpT rely on shared neurocognitive processes, they have distinctions that may be key for enhancing RC. NarrT uniquely relies on regions in a neural network linked to socio-emotional processes (e.g., dorsomedial prefrontal cortex), while ExpT uniquely relies on regions in a neural network that supports executive function/cognitive control (e.g., left dorsolateral prefrontal cortex). Our overarching hypothesis is that readers’ use of SocEMDMN vs FPN is a critical determinant of proficient situation model formation, and, thus, RC. We also posit that the enhanced socio- emotional NarrT context provokes greater connectivity between DisPDMN and SocEMDMN at key junctures in text, resulting in enriched intrinsic access to readers’ internal states, and thus a neurocognitive benefit for RC. Critically, pilot findings suggest that this enhanced socioemotional context can also be achieved in ExpT by embedding high emotion words [words with high arousal ratings] in ExpT, perhaps paving the way to bolster ExpT RC. Given that RC is a central avenue for learning new information after ~3rd grade, we are addressing a highly significant public health issue. To systematically test our hypotheses, we target 10-12 yo (N=220) who have crossed into the “reading to learn” stage to examine dynamic neural processes of ExpT vs NarrT online reading (situation model building; Aim 1); how readers’ individual differences (e.g., executive function, socio- emotional) modulate Aim 1’s findings (Aim 2); how Aims 1 & 2’s neural findings predict RC (Aim 3a); and, if enhancing the socioemotional context helps RC (Aim 3b). Our ultimate goal is to identify the best ways adolescents learn new information while reading so as to maximize academic success and prevent RC failure.

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY Monogenic kidney diseases such as cystinuria are well characterized genetically, but lack safe and effective clinical treatments. Patients with cystinuria form numerous cystine-based stones in their urinary tract due to failure to reabsorb cystine in renal proximal tubule cells, leading to chronic kidney disease in up to 70% of cases. The most common subclass of cystinuria, type A, is a result of a homozygous deficiency of SLC3A1, which encodes an amino acid transporter (rBAT) that reabsorbs cystine in proximal tubules. Recent advances in the genome engineering field have allowed for potentially curative therapy for monogenic diseases including cystinuria. Current barriers to renal genome engineering include delivery and sustained expression of transgenes. However, cystinuria is an ideal model disease to investigate and potentially overcome these barriers as the proximal tubule is targetable within the kidney, a low level of rBAT is estimated to prevent stone formation, and cystinuria could be targeted at any stage of life. When designing renal gene therapy for cystinuria, previous work has shown advantageous integration efficiency of transgenes using the piggyBac transposon system. Kidney-targeted genome engineering using piggyBac transposons for in vivo models can be accomplished with a novel proximal tubule-targeted adeno-associated virus (AAV). I hypothesize that the combination of a renal specific AAV with piggyBac transposon integration of SLC3A1 will lead to stable, kidney- targeted phenotypic correction in models of cystinuria. To test this hypothesis, I will engineer renal-specific AAV vectors to contain piggyBac-SLC3A1 in AIM 1. Self-complementary AAV has shown improved kidney specificity, but its’ compact size necessitates the splitting of SLC3A1 into two AAVs. Therefore, I will design a dual AAV system that recombines in vivo to express full length SLC3A1 using homologous recombination and mRNA splicing. I will also test the recombination and functionality of the dual AAV-piggyBac-SLC3A1 system in vitro. In AIM 2, I will generate SLC3A1-/- kidney organoids derived from human inducible pluripotent stem cells (iPSCs). I will then quantify expression of rBAT and cystine transport after delivery of the proposed system. Finally, I will assess the potential of AAV-piggyBac-SLC3A1 to phenotypically correct cystinuria through prevention of cystine stone formation in a mouse model of type A cystinuria in AIM 3.

NIH Research Projects · FY 2025 · 2022-09

Project Summary/Abstract Although males and females both suffer from cocaine use disorder (CUD), females represent a particularly vulnerable population and the neural mechanisms underlying this sex difference remain poorly understood. CUD is characterized by cocaine-induced alterations in dopamine release in the nucleus accumbens (NAc). Sex differences in dopamine release and its regulation in the NAc has also been linked to sex-specific behaviors in CUD. The goal of this proposal is to define sex differences in dopamine release regulation in the NAc and determine how this process is dysregulated following cocaine self-administration. GABA-A and GABA-B receptors in the NAc have been linked to the reinforcing properties of cocaine. Further, GABA is a key regulator of dopamine release through direct actions of GABA receptors on dopamine terminals in the NAc. However, long-term plasticity in GABAergic regulation of terminal dopamine release is unknown, and sex-differences in this process have been virtually unstudied. The goal of this proposal is to define sex differences in GABAergic regulation of dopamine release, determine if cocaine self-administration alters this regulation in a sex-specific fashion, and examine the causal role of GABA-A and GABA-B receptors in cocaine-induced plasticity in the NAc. In Aim 1, I will use ex vivo optical recordings in the NAc with a genetically encoded dopamine sensor (dLight1.2) to record evoked dopamine release in males and females. Using pharmacology, I will investigate GABA-A and B receptor regulation of dopamine release and determine if sex differences exist. Based on my preliminary data, I hypothesize that GABA-A-mediated inhibition of evoked dopamine release will be sex-dependent, with greater effects in males. In Aim 2, I will investigate cocaine-induced plasticity in this regulation following cocaine self- administration in mice. In Aim 3, I will knock out GABA-A and GABA-B receptors in dopaminergic neurons and determine if these receptors are necessary for cocaine-induced plasticity in dopamine release in the NAc. Taken together, the experiments in this proposal will be the first to define sex-differences in GABAergic regulation of dopamine release in the NAc, determine how these processes are altered by cocaine self-administration, and investigate the roles of GABA receptors in cocaine-induced plasticity in NAc dopamine release. This proposal encompasses technical and theoretical training that will provide the foundational expertise and conceptual thinking needed to address larger questions regarding how drug-induced and sex-specific changes in the brain support the development and sustainment of CUD. Additionally, these findings can ultimately inform our understanding of sex-specific mechanisms underlying reward and learning process and lead to more efficacious treatment interventions for males and females.

NIH Research Projects · FY 2026 · 2022-09

Project Summary Natural products from bacteria, fungi, and plants have long been a rich source of useful molecules. However, due to their complex structures, it is difficult to screen many analogs of natural products to truly understand the rules governing the relationship between their structure and activity. We will address this challenge by developing machine learning methods that can functionally model the structure-activity relationships (SAR) of natural products and aid in the design of biosynthetic pathways that can synthesize natural product analogs. Therefore, we will develop methods both for prioritizing natural products that are most likely to be useful as therapeutics for activity screens and for biosynthesizing natural products of interest. Machine learning is a powerful computational technique that enables computers to make inferences from data. There is a wealth of sequence, structure, and activity data available for biological molecules that we can use to build machine learning models to make predictions about the behavior of biochemical systems. Even machine learning algorithms that are not perfectly accurate can be extremely useful for drug discovery efforts. It is possible to screen orders of magnitude more compounds using machine learning than in high-throughput screens. Machine learning can therefore be used as an initial filter to increase hit rates in screens. Our first project will apply machine learning to study natural product SARs. We will take two approaches, a genetic and chemical structure approach. In the genetic approach we will validate correlations between biosynthetic genes and natural product activity that we have previously observed and confirm that the correlation extends to chemical substructures installed by the biosynthetic genes. In the chemical structure approach, we will investigate the ability of graph neural networks to predict natural product properties. Our second project will focus on developing machine learning and other computational tools for designing biosynthetic gene clusters (BGCs) to biosynthesize novel natural product-like molecules. We will first focus on Ribosomally Synthesized and Posttranslationally modified Peptides (RiPPs) and develop methods to predict compatible modifying enzyme-leader peptide pairs. To do this we will use molecular modeling, Statistical Coupling Analysis (SCA), and machine learning. After validating our methods on RiPPs, we will turn our attention to more difficult classes of BGCs, such as nonribosomal peptide synthetases (NRPS) and polyketide synthases (PKS). Our third project is the development of methods for designing RiPP-based protein-protein interaction (PPI) inhibitors. We will develop both molecular modeling and machine learning methods for predicting optimal RiPP sequences for inhibiting a PPI of interest. We will then validate and collect additional training data for these predictions using directed evolution experiments.

NIH Research Projects · FY 2025 · 2022-08

PROJECT SUMMARY/ABSTRACT Osteoarthritis (OA) results from a combination of natural wear and tear associated with aging and/or unnatural mechanical loading on the joint. Patients who suffer a joint injury (e.g., ligament damage) have increased risk for early development of OA. Injury-related post-traumatic osteoarthritis (PTOA) often occurs in younger patients. PTOA and OA are both associated with articular cartilage erosion and other joint changes that cause pain and loss in quality of life. The available treatments only provide temporary pain relief. However, alleviation of pain only briefly masks the disease and does not halt or slow its progression. Progression of PTOA/OA to the point where joint replacement becomes necessary is almost inevitable for large joints because there are currently no disease-modifying osteoarthritis drugs (DMOADs) that can stop progression of or cure the disease. Loss of cartilage associated with OA and PTOA is driven by local upregulation of matrix metalloproteinases (MMPs). We propose that blocking the cartilage-degrading MMPs could stop the progression of PTOA/OA, improve quality of life, and reduce the need for joint replacement in afflicted patients. Pharmaceutical companies have previously tested drugs that can block the activity of MMPs, but these treatments have failed, primarily because their lack of specificity and lack of delivery approaches that localize the drug to the affected joint. We propose to develop intra-articularly injected bioadhesive nanoparticles for locally-retained delivery of short interfering RNA (bioad-si-NPs). The bioad-si-NPs will potently and specifically “knock down” specific MMPs to halt cartilage degradation in joints with OA or at risk of OA development (following injury). The mechanism of siRNA enables these molecules to be selective for specific MMPs, and the bioad-si-NPs are designed to be retained locally at the site of intra-articular delivery; both of these features contribute to our approach having reduced risk of off target side effects. We will test bioad-si-NPs in animal models of both PTOA and spontaneous OA and for inhibition of single or combinations of MMPs. In the setting of spontaneous OA, we will also test the value of initiating treatment at early versus more advanced stages of disease. This project is uniquely accessible through the interdisciplinary team with bioengineering expertise in intracellular biologic drug delivery nanotechnologies and RNA chemistry (Duvall), OA biology and animals models (Hasty), analysis of PTOA/OA animal model joint function/pain (Krug), and clinical care of OA patients (Crofford).

NIH Research Projects · FY 2025 · 2022-08

PROJECT SUMMARY Limited approaches exist to examine longitudinal changes in the structural and biochemical properties of tissues under various physiological conditions such as pregnancy. Light and light based technologies offer the potential for non-invasive, real-time, in vivo monitoring of longitudinal shifts in tissue physiology in response to developmental, hormonal, or environmental influences. The objective of the proposed research is to pursue a multi-pronged platform with complementary Raman scattering approaches to study longitudinal changes in tissue physiology in vivo as well as ex vivo and compare the results with conventional assays to validate our approach. In addition, we will combine various forms of in vivo Raman imaging, including (i) dual wavelength, dual region Raman (ii) polarization-sensitive Raman, and (iii) resonance Raman spectroscopy to quantitatively analyze changes in tissue physiology. In response to a lack of detailed understanding of preterm birth and its tissue biochemistry, our group has reported the utility of in vivo RS to detect and extract longitudinal biochemical changes in the mouse as well as human cervix, a tissue that undergoes extensive remodeling over the course of pregnancy. We established the ability of a conventional in vivo RS probe to identify significant spectral changes in collagen, elastin, water, and blood. Moreover, we can correlate these Raman spectra with changes in biomechanical properties of the mouse cervix, including stiffness and distensibility, as the cervical tissue undergoes normal remodeling/maturation in preparation for labor. Building on our prior research, the present proposal will focus multimodal ex vivo and in vivo Raman approaches to gain in-depth, quantitative information during physiologic cervical maturation and in mouse models of premature remodeling. We hypothesize that multimodal Raman approaches will enable detection of key biochemical changes, such as extracellular matrix (ECM) organization, tissue hydration, lipid and protein influx and vascularity that will allow molecular and structural phenotyping of the cervix as a prototype of physiologic tissue remodeling. Results will be correlated with spatial information obtained via ex vivo imaging and biomechanical testing. Our Aims are to: 1) Implement multimodal non-linear imaging to characterize changes in structural proteins in the mouse cervix, 2) Use dual wavelength, dual region Raman Spectroscopy to track changes in tissue hydration and lipid dynamics, and 3) Evaluate spatial and temporal changes in blood and vascularization in the mouse cervix over the course of pregnancy. Ultimately, this project will integrate the results of these aims to provide a more complete picture of the molecular and structural changes that can be used to understand normal as well as compromised pregnancies. The resultant in-depth biomolecular profiles and spatial tissue maps obtained for normal term and preterm pregnancies with the innovative Raman approaches will provide vital information about the mechanism of premature cervical remodeling and for monitoring longitudinal changes in the structural and biochemical properties of other tissues with RS.

NIH Research Projects · FY 2025 · 2022-08

Newborns have immature liver function that is inefficient at metabolizing bilirubin. Consequently, nearly 80% of preterm and 60% of term babies develop hyperbilirubinemia resulting in neonatal jaundice within a week of birth. Severe hyperbilirubinemia can be fatal, making early, frequent, and accurate monitoring of bilirubin vital to avoid severe health issues and determine appropriate treatment. The gold standard for detecting hyperbilirubinemia is an invasive blood test to measure total serum bilirubin (TSB); however, frequent blood sampling in neonates is costly, painful, and increases the risk of infection. Existing non-invasive methods to monitor hyperbilirubinemia lack sufficient accuracy to replace blood tests. Commercial transcutaneous bilirubinometry (TcB), although clinically accepted for screening, has low correlation with TSB for clinical decision-making in dark-skinned neonates and in neonates undergoing phototherapy. A main reason for TcB limitations is spectral cross-talk: the inability to reliably distinguish contributions between skin analytes (e.g., melanin) and blood. Our central hypothesis is that a non-invasive mobile phone-based bilirubin detector can be developed that provides accurate, point-of-care blood bilirubin measurements in dark-skinned neonates and neonates where TcB underperforms. We propose to use spectroscopic optical coherence tomography (sOCT), an imaging technique with depth-resolved capabilities that can overcome spectral cross-talk. We will pursue three specific aims: (1) Develop a portable, mobile phone-integrated sOCT system for non-invasive, depth-resolved measurement of blood spectra. We will build and characterize a miniaturized sOCT device integrated with a smartphone application for data processing, analysis, display, and HIPAA-compliant transmission or storage. (2) Refine and test the sOCT algorithm in vivo. We will compare sOCT data to TSB blood tests and commercial TcB in 100 neonates, evaluating correlation, mean bias, and precision across a diverse range of skin tones. (3) Aim 3: Validate sOCT performance in neonates with poor TcB correlation. We will test sOCT in 78 neonates at Vanderbilt with darker skin tones to assess whether sOCT provides comparable results to lab-based TSB in populations where TcB underperforms. We will also perform usability and workflow assessments to optimize clinical integration.

NIH Research Projects · FY 2026 · 2022-08

PROJECT SUMMARY Schizophrenia is a severe and debilitating psychotic disorder, characterized by disturbances of the basic sense of self and social disconnection throughout the course of illness. The proposed project aims to elucidate the impact of self-disturbances in social impairments by focusing on one core aspect of the bodily self, the self-other boundary. An implicit awareness of clearly defined self-boundary is a prerequisite for adaptive interactions with the external world. In individuals with schizophrenia, however, a disrupted self-other boundary complicates the process of distinguishing one’s own behaviors from those of others, thereby undermining social interactions. Loss of social opportunities often leads to social isolation, which further erodes interpersonal relationships and exacerbates self-disturbances, setting up a destructive cycle. Despite the chronicity and prevalence of self-disturbances and social impairments in schizophrenia, common mechanisms underlying disrupted self-other distinction and social impairments have not been extensively investigated. One major hurdle has been a lack of methodological tools to quantify the subjective phenomenology of self-disturbances. We will utilize novel behavioral methods and leverage the technological advances in immersive virtual reality (VR) to investigate two core aspects of self-other interactions in space: (1) the implicit multisensory action space around the self that determines one’s self-other boundary (peripersonal space); (2) the social construct of the interpersonal comfort space (interpersonal distance). To estimate the implicit self- boundary in our participants, we will implement a basic visuo-tactile integration paradigm in VR adapted from neurophysiological studies of multisensory neurons in nonhuman primates. To assess the social comfort space that determines interpersonal distance, we will use the stop-distance paradigm in VR. This approach will allow us to quantify the self-other boundary in the context of social interactions and link to their neural correlates. We will specify mechanisms that connect these constructs to identify more precise targets for treatment. Systematic examination of the peripersonal space and its relation to interpersonal distance regulation may be a first step towards identifying the role of self-disturbances in components of disrupted social behavior. This project will utilize mechanisms underlying multisensory integration processes to understand complex social behavior. Self‐disturbances are common features of a wide range of neuropsychiatric conditions. Indeed, all forms of psychiatric disorders may be conceptualized as maladies of disrupted social homeostasis between the self and the social world. Thus, this approach may be broadly applicable across multiple neuropsychiatric conditions that intersect with self-disorders and social impairments and will contribute towards the goals of the NIMH Research Domain Criteria (RDoC) strategy.

NIH Research Projects · FY 2026 · 2022-08

PROJECT SUMMARY DNA methylation is an essential mediator of genome function. But considering the prevalence and distribution of sites of methylation across the genome, exactly how DNA methylation drives cellular phenotype is unclear. Although mammalian genomes are highly methylated, hypomethylated hotspots are scattered throughout non- coding regions and frequently coincide with open chromatin and other gene regulatory landmarks. DNA methylation is considered repressive to transcription, and gene regulatory elements are thought to require demethylation to promote transcription of lineage-specifying genes. Thus, hypomethylated regions (HMRs) of differentiated cells spotlight regions of past or present transcription factor occupancy, flagging key gene regulatory elements involved in lineage specification (cell history) or cell-type specific gene regulation. Recent work from our lab comparing methylation profiles across diverse cell-types demonstrates that HMR patterns are highly predictive of cellular phenotypes. Moreover, we have discovered that cell-type specific HMRs are enriched for genetic variants linked to specific clinical phenotypes. Together these data suggest HMRs provide important contextual information for genome function, and when combined with human trait data, HMRs provide a powerful means to connect genotypes to phenotypes. The objective of this proposal is to understand the functional significance of cell-type and lineage specific HMRs and their causal relationship with genes and cellular phenotypes. We propose that cell-type essential HMRs harbor genetic variants linked to cell-type-related phenotypes. We further propose that, by understanding this relationship, we will uncover new hypomethylation- dependent gene regulatory relationships that are critical for normal cell identity and function. We will perform comparative DNA methylation profiling of diverse cell types to identify cell specific HMRs. To elucidate HMR function, we will apply an unbiased, cutting-edge genetic approach that uses human population genetics to link HMR genotypes to human traits recorded in the electronic health record (EHR), the most extensive repository of phenotypic conditions of any model organism. In parallel we will probe the functional activities of HMR-defined genomic sequences using a powerful, multi-omic approach developed by our lab to isolate “driver” HMRs in specific cell contexts. Finally, we will use epigenome editing to understand the importance of hypomethylation on local genome regulation. This multi-level approach will test the hypothesis that cell-type and lineage specific HMRs are critical elements bridging genomes to phenomes. Ultimately, these studies will establish a fundamentally new way to understand how DNA methylation bridges the connection between genomes and phenomes, revealing important gene regulatory principles that are essential to understanding why epigenetic instability leads to specific disease outcomes.

NIH Research Projects · FY 2025 · 2022-08

Abstract Oxidative transformation of arachidonic acid by cyclooxygenases, lipoxygenases, and cytochromes P450 gives rise to endogenous lipid mediators that regulate cellular processes in homeostasis and disease. These lipid mediators form an evolving and expanding family referred to as eicosanoids. This application comprises two projects that both are concerned with novel transformations in eicosanoid biochemistry and present important ramifications for the use of non-steroidal anti-inflammatory drugs (NSAIDs) that inhibit their biosynthesis. The first project is centered around the 5-LOX/COX-2 cross-over biosynthetic pathway while the second project is concerned with novel metabolic transformations of eicosanoids, and what these mean for the use of plasma and urinary prostanoid metabolites as markers of drug response. Today, novel members of the eicosanoid family are often discovered in lipidomics approaches by their similarity with known eicosanoids. We have employed an approach based on understanding the structure-function of the biosynthetic pathways, enzymes, and substrates that allowed us to make predictions of novel transformations. This has led to the discovery of the 5-LOX/COX-2 cross-over biosynthetic pathway forming hemiketal eicosanoids (HKE2 and HKD2) and 5- hydroxy-prostaglandins, the identification of 15R-prostaglandins formed by aspirin-acetylated COX-2, and the identification of the Baeyer-Villiger oxidative pathway underlying the metabolism of PGD2 to 11-dehydro- thromboxanes. Underscoring the relevance of our approach is the fact that the novel eicosanoids we have shown to be formed in vitro and in vivo have not been identified in lipidomics analyses, likely due to their unusual properties that make them difficult to detect in standard analyses. We have designed analytical procedures that allow to detect and quantify the novel eicosanoids in vitro and in vivo. We plan to continue the identification of novel eicosanoids and to establish their cellular targets and biological role in homeostasis and in models of inflammatory disease. Our ongoing investigation into the biological effects of the cross-over eicosanoids has identified the receptor tyrosine kinase (RTK) VEGFR2 as a target for the pro-angiogenic activity of HKE2, as well as other RTK and an unknown target that mediates inhibition of platelet activation that are to be further analyzed. For the 5-hydroxy-prostaglandins we plan to employ screening approaches as well as targeted testing of prostanoid receptors in order to identify their cellular targets and determine biological effects. We aim to identify compounds that can be used to manipulate biosynthesis of 5-LOX/COX-2 cross- over eicosanoids independent from the formation of prostaglandins and leukotrienes. We will continue to characterize novel metabolic pathways of prostanoids and establish the relevance of these pathways in vivo. Identification and characterization of novel eicosanoids, their biological effects, and novel prostanoid metabolic pathways will result in a refined understanding of the pathophysiologic conditions for which NSAIDs may be used and effect of aspirin and other NSAIDs on prostanoid biosynthesis in vivo.

NIH Research Projects · FY 2025 · 2022-07

PROJECT SUMMARY This proposal addresses the significant, unmet need to develop and translate new therapies for children with advanced, high-risk neuroblastoma. Neuroblastoma (NB) is the third most common pediatric cancer and the most common extracranial solid tumor of childhood, accounting for 15% of all pediatric cancer deaths each year despite an intensive, multimodal, and toxic treatment regimen. Immunotherapy offers the potential for selective targeting and killing of cancer cells and represents an appealing alternative for eradicating recurrent, metastatic disease and achieving durable cures with minimal toxicity. However, NB has proven poorly responsive to most immunotherapeutic modalities, notably including immune checkpoint blockade and CAR T cell therapy. Therefore, novel immunotherapies for NB must be developed. The objective of this proposal is to advance and mature STING-activating nanoparticles (STANs), a promising experimental immunotherapeutic nanomedicine for enhancing immunotherapy responses in NB, towards clinical translation. To accomplish this, we will directly address potential barriers to the clinical advancement of STANs by further optimizing their physiochemical and biological properties via a scalable manufacturing process, elucidating key immunopharmacological parameters in rigorous NB mouse models, and establishing rationally-designed immunotherapy regimens that generate robust and durable responses. We will accomplish this through the following Specific Aims. First, we will employ an integrated polymer and materials science approach to reproducibility fabricate STANs with optimized properties via a facile and scalable flash nanoprecipitation nanofabrication strategy. Second, we will evaluate the pharmacokinetics, biodistribution, pharmacodynamics, safety, and therapeutic efficacy of STANs in a rigorous immunocompetent NB that mimic human disease. Third, we will evaluate and optimize rationally-designed immunotherapy regimens combining STANs with immune checkpoint blockade and NB-targeted CAR T cells. We expect the proposed work to address several critical preclinical gaps that, when filled, will accelerate STANs toward clinical translation. Therefore, this research addresses a problem of high clinical urgency by advancing a next-generation nanotechnology for enhancing immunotherapy responses in NB.

NIH Research Projects · FY 2026 · 2022-07

Project Summary The goal of our proposed research program is the design of new catalytic methodology for the synthesis of complex organic building blocks via site-selective activation of carbon-hydrogen bonds in simple organic molecules. Our approach makes use of a class of dipyridylarylmethanes as supporting ligands in iridium-catalyzed sp3 C-H borylation catalysis. This family of ligands was recently identified in our laboratory and is designed to borrow features of previous diimine and pentamethylcyclopentadienyl ligands for the same transformation while offering the advantage of modular synthetic routes for their preparation. Our initial studies on this ligand class identified one of the best catalysts for sp3 C-H borylation yet known, which has led us to design a research program that takes advantage of the improved functional group tolerance of this system to expand the scope of suitable substrates. Our proposed work will address challenges presented by the need for selectivity in sp3 C-H borylation, and in so doing will provide access to functionalized alkylboronic ester products with functional groups that were previously inaccessible through C-H activation. Further applications to the synthesis of linker molecules and biologically relevant cyclic boronate esters are proposed. We will also explore applications of dipyridylarylmethane ligands to C-H silylation catalysis, a class of chemical reactions that is substantially underdeveloped by comparison to C-H borylation. In total this program provides enabling technologies in the form of chemical methodology for the synthesis of complex building blocks from simple precursors. These methods will empower synthetic chemists in the synthesis of drug candidates and biological probes by providing tools to address the necessary complexity of molecules that interface with biological systems.

NIH Research Projects · FY 2025 · 2022-07

PROJECT SUMMARY Immune checkpoint blockade (ICB) is an immunotherapy that is revolutionizing cancer treatment, but is effective in a minority of patients. Across many solid tumor types, this can largely be ascribed to an insufficient number, diversity, and/or function of endogenously generated, pre-existing T cells that recognize tumor neoantigens and infiltrate tumors. Therefore, there is a critical need for new strategies to bolster the magnitude, breadth, and quality of neoantigen-specific T cells, to recruit cytotoxic CD8+ T cells to tumors, and to amplify their expansion, effector function, and persistence. Towards this goal, we propose a new strategy for neoantigen-targeted cancer immunotherapy. Our approach leverages a STING-activating nanoparticle vaccine (STAN-V) that we have designed to overcome several critical immunopharmacological barriers that limit cancer vaccine efficacy. The STAN-V platform is based on polymer nanoparticles engineered to enhance intracellular co-delivery of peptide neoantigen and agonists of stimulator of interferon genes (STING), a design that we have demonstrated stimulates potent neoantigen-specific CD8+ T cells and increases response to ICB. Our objective in this R01 application is to advance and mature STAN-V as a universal platform for neoantigen- targeted cancer vaccines. We will accomplish this through the following Specific Aims. First, we will develop and optimize a facile strategy for rapid fabrication of STAN-Vs based on spontaneous and efficient loading of neoantigenic peptides designed with optimized lipophilic domains. We will evaluate the capacity of this approach to increase the magnitude and breadth of neoantigen-specific T cell responses to physicochemically diverse neoantigens. As such, we expect these studies to advance the translational-readiness of STAN-Vs as a personalized vaccine technology. Second, we will leverage the unique morphology and properties of STAN- Vs to develop and optimize a novel adjuvant combination based on coordinated co-packaging and co-delivery of STING and TLR agonists. We will systematically explore the effect of combinatorial adjuvant delivery on innate and adaptive immunity, studies that we expect will yield an optimized adjuvant combination for stimulating antitumor cellular immunity. Third, we will devise and test a new approach for enhancing tumor homing and infiltration of T cells elicited via vaccination. This strategy will leverage systemic administration of a nanoparticle STING agonist that reshapes the tumor milieu to enhance T cell infiltration, proliferation, and function. Overall, these studies will advance STAN-Vs as an enabling and versatile technology for stimulating robust neoantigen-specific T cell responses and improving outcomes of immunotherapy across many cancers.