Clemson University

NIH Research Projects · FY 2025 · 2023-09

PROJECT SUMMARY/ABSTRACT Given the importance of the gut microbiota to human health and disease, there is great interest in defining how the indigenous microbes in these communities assemble and function in health. Ecological succession of the microbes that compose the gut microbiome begins at birth, with diversification of the community throughout human life. A key role for the gut microbiota is to break down resources from our available diet, which provides us with necessary nutrition to live. This also sustains other surrounding microbes, increasing microbiota diversity and resilience to environmental perturbation. In conjunction with the rich nutrients provided by the gut environment, the ability of a bacterium to diversify its nutrient acquisition repertoire can allow for related strains to establish new niches and coexist in a community. As such, niche partitioning among individual species or strains likely to contributes to maintenance of a diverse microbiota. Niche partitioning of select model commensal microbes of the gut, such as Bacteroides species, has been demonstrated, providing critical knowledge about the cooperative and competitive interactions that contribute to their assembly in the gut. Yet, we still lack comprehensive information about the metabolic strategies for many prevalent species in the gut, let alone how these species interact together to maintain a particular community structure. Understanding how non-model microbes assemble in the gut is important, as successful implementation of many targeted bacterial functions still rely on their surrounding community members. In this proposal, we aim to characterize the metabolic role of commensal Clostridia, which represent prevalent members of the gut microbiota that are under-characterized. We hypothesize that similar to what is known about more well-defined gut commensal species, nutrient niche partitioning among Clostridial species is essential to sustaining their diversity in the gut. We will use bioinformatic and in vitro methods to 1) characterize the fundamental (genonme-encoded) and realized (expressed) metabolic strategies used by select Clostridial species and 2) identify how these contribute to their assembly in the gut. Results from these data provide critical information about core functions, strain heterogeneity, and microbial interactions that are relevant to understanding comprehensive assembly of the human gut microbiota. These data provide a foundation for mechanistic studies surrounding commensal Clostridia in the gut, such as developing rational bacterial consortia or dietary interventions based on these fundamental characteristics. Overall, this proposal provides a path forward for our independent research program focused on understanding the role of commensal Clostridia in health.

NIH Research Projects · FY 2024 · 2023-09

PROJECT SUMMARY Cocaine Use Disorder (CUD) represents a significant public health and socioeconomic concern. Cocaine is involved in 40% of drug-related emergency room visits, and rates of cocaine overdose in the United States are climbing steadily. Yet, the genetic underpinnings that predispose to CUD remain poorly understood. Twin studies on the genetics of CUD provide heritability estimates between 42-79%. However, significant heritability estimates do not indicate which genes are involved, and how they might be functionally relevant. Genome-wide association studies (GWAS) of CUD are limited by inability to control environmental factors; the haplotype structure of the human genome limiting mapping precision; and small sample sizes due to difficulty recruiting participants because of criminalization of cocaine use. Model organisms such as the fruit fly Drosophila melanogaster offer a cost-effective alternative where sample size, environment, and genetic background can be controlled. Cocaine binds to the dopamine transporter of Drosophila as it does in humans, eliciting cocaine-induced locomotor phenotypes. GWAS in Drosophila are facilitated by the Drosophila melanogaster Genetic Reference Panel (DGRP), an expanding collection of wild-derived, inbred, fully sequenced lines that provide a living library of natural variation. It is my goal to use the DGRP and a systems genetics approach to uncover the genetic underpinnings of cocaine-related phenotypes. In Specific Aim 1, I will investigate the impact of genetic background on cocaine preference by screening 600 DGRP lines for cocaine preference using the microplate feeder assay. I will then perform a GWAS, utilizing whole genome sequence data to identify genetic variants associated with cocaine preference. I will perform gene ontology and KEGG orthology pathway enrichment analyses, as well as construct genetic interaction networks to implicate genes and pathways involved in cocaine preference. In Specific Aim 2, I will quantify the behavioral and transcriptomic effects of cocaine exposure in DGRP lines with extreme cocaine preference. For 25 DGRP lines that exhibit cocaine preference and 25 lines near the population average, I will assess effects of cocaine on sensorimotor integration upon repeated exposures. In Specific Aim 3, I will functionally validate candidate genes and variants associated with cocaine preference using RNA interference and out-of-sample testing of DGRP lines, respectively. Completion of these aims will result in a systems genetics model of cocaine preference in Drosophila with translational potential for human cocaine use disorder. This project will train me in advanced systems genetics techniques and analyses and prepare me for a professional career in the study of the genetics of substance use disorders.

NIH Research Projects · FY 2024 · 2023-09

Project Summary Tracking living cells in video sequences is a fundamental task in many fields of science, including biochemistry, bioinformatics, cell biology, and genetics. Manually linking cells is extremely time-consuming and not feasible in large-scale analysis. Automatic approaches can compute cell links by measuring how close two instances of a cell are, or how similar they look. These techniques work well with video acquired at a relatively high frame rate, but, unfortunately, acquiring images at high frame rates affects cells negatively. Too frequent imaging not only causes phototoxicity, leading to experimental artifacts, but also photobleaching, leading to the inability to measure quantities of interest over time. In addition, during image acquisition, the environment temperature and air quality are typically less controlled, which could also contribute to cytotoxicity. Moreover, when performing high- throughput live-cell imaging, the lower the acquisition rate, the more cells/plates can be imaged, and, consequently, the more experimental treatments can be applied and studied. If reducing the acquisition rate is beneficial for all these reasons, it severely affects the accuracy of cell tracking algorithms. To this end, we propose a new class of cell tracking approaches based on cell movement predictions. Instead of comparing cells based on their similarity, we propose to predict where every cell will move in the next frame. This will allow for searching the occurrence of such cells, even if the next frame was acquired after an extended period. The new approach will be investigated using a newly generated dataset for low frame rate cell tracking (Aim 1). Cell displacement will be predicted by using a new Recurrent Neural Network designed for the task (Aim 2). Cell tracking algorithms will be defined re-evaluating existing approaches under low-frame rate constraints when using cell displacement information (Aim 3). While current approaches require image acquisition to occur at least every 5-15 minutes, we will investigate the feasibility of cell tracking on images acquired at intervals of up to 2 hours. If successful, our research will allow to accurately track cells in low frame rate video sequences without the need for specialized tools or equipment.

NIH Research Projects · FY 2024 · 2023-08

Project Summary: In the U.S., there are more than 735,000 myocardial infarctions (MI) each year. While percutaneous coronary intervention (PCI) has significantly reduced acute adverse repones, the long-term prognosis for post-ischemia/reperfusion (I/R) patients remains poor. Due to the limited regenerative capacity of human hearts, human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) have received significant attention due to their proven capacity to restore contractile function upon transplantation to injured hearts in various mammalian models, leading to multiple ongoing clinical trials. However, the current transplantation approach mainly relies on dissociated hPSC-CMs, leading to low cell survival, moderate functional improvement, arrhythmogenic risk, and poor scalability. To address these challenges, our lab developed nanowired, pre- vascularized human cardiac organoids composed of hPSC-CMs, human primary cardiac fibroblasts, endothelial cells, stromal cells, and electrically conductive silicon nanowires (e-SiNWs). Endothelial cells are used to induce vasculature formation within the organoids, and e-SiNWs are added to create an electrically conductive microenvironment to facilitate hPSC-CM contractile development and their electrical integration with the host myocardium. Our preliminary in vivo data showed that nanowired organoids illustrated robust hPSC- CM engraftment and superior functional recovery. The major barriers in their clinical translation include: 1) the use of animal proteins in the cell and organoid culture and 2) the lack of functional benefit demonstration in a large animal model. Replacing human primary cells with isogenic hPSC-derived cells for organoid fabrication would reduce batch-to-batch variations and enhance immune compatibility through Major Histocompatibility Complex (MHC) matching hPSC donors with human recipients. In addition, while the current hPSC-CM implantation strategy has been focused on intramyocardial injection, developing an effective approach for intracoronary delivery of the organoids will accelerate their clinical translation. The goal of this proposal is to develop clinical-grade hPSC cardiac organoids and demonstrate their functional benefits with a large animal model to generate enabling data for IND submission. The central hypothesis of this proposal is the nanowired isogenic hPSC cardiac organoids provide a scalable system to both efficiently and effectively implant hPSC-CMs for cardiac repair. The proposal is innovative in that we will 1) derive isogenic hPSC-derived cells in xeno-free, chemically defined conditions to develop clinical-grade cardiac organoids for implantation and 2) leverage the size and the endothelial lumen-like structures in the organoids to develop an effective intracoronary delivery strategy. Accordingly, we will pursue the following 2 aims: 1) Fabricate and characterize nanowired human cardiac organoids using isogenic cardiac cells derived from hPSCs in xeno-free, chemically defined conditions, and 2) Determine the therapeutic efficacy of the nanowired isogenic hPSC cardiac organoids with a porcine I/R (ischemia/reperfusion) model.

NIH Research Projects · FY 2024 · 2023-07

Project Summary: Acute Cardiac Injuries (ACIs) occur in up to 20-25% of hospitalized COVID-19 patients and are associated with increased risks of morbidity and mortality. COVID-19 has been shown to induce immune system “overfiring” and “misfiring”, resulting in supraphysiological inflammation. Such cytokine storms have been shown to lead to organ damage through both direct cytokine insults and indirect mechanisms (e.g., recruitment of proinflammatory immune cells into organs). Myocarditis (e.g., monocyte infiltration) is a common complication in COVID-19 ACI hearts. However, the impacts of the infiltrated monocytes on COVID-19 ACI hearts remain under-defined. As previous studies have been limited to either clinical samples (e.g., peripheral blood, autopsy/biopsy tissues) or in vitro 2D co-culture experiments, these studies yield limited functional insights. 3D organotypic models provide a powerful platform to study the functional interactions between hearts and immune cells in circulation. To develop an organotypic model of human hearts for disease modeling, we developed 3D human cardiac organoids composed of human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs), human cardiac fibroblasts, endothelial cells, and stromal cells. Our preliminary data showed the Interleukin (IL)-1b treated organoids recapitulated key features of transcriptome, structure, and function of COVID-19 ACI hearts. As IL-1b is not a COVID-19 specific stimulus, these results laid the foundation to use serum from COVID-19 ACI patients to recapitulate the COVID-19 cytokine insults to the hearts. In addition, the exclusion of immune cells in the organoids has limited the full recapitulation of hyperinflammation in COVID-19 ACI hearts. The goal of this proposal is to leverage the serum and peripheral blood mononuclear cells (PMBCs) harvested from COVID-19 ACI patients to 1) simulate the effects of COVID-19 cytokine insults on human hearts, 2) develop the first in vitro COVID-19 myocarditis organoid model to simulate immune cell infiltration to COVID-19 ACI hearts and assess the infiltrated COVID-19 monocytes. The central hypothesis of this proposal is that infiltrated COVID-19 immune cells (e.g., monocytes) exacerbate the hyperinflammation of COVID-19 ACI hearts. This proposal is innovative in that it will, for the first time, develop an organotypic model of myocarditis to simulate immune cell infiltration into myocardium. Accordingly, we will pursue the following 2 Aims: 1) Determine the effects of COVID-19 ACI serum on human cardiac organoids, and 2) Determine the ability of COVID-19 ACI serum treated organoids to recruit immune cells from COVID-19 ACI patients. The proposed studies will lead to follow-up R01 applications focusing on the effects and mechanisms of the infiltrated monocytes in COVID-19 ACI hearts. In addition, the 3D organotypic model of myocarditis can be used for mechanistic studies of the effects of immunomodulatory drugs on hearts.

NIH Research Projects · FY 2024 · 2023-07

PROJECT SUMMARY The inability of Entamoeba histolytica to form infectious cysts in the laboratory setting has greatly hindered investigation of this crucial stage in the infection and disease cycle of this human pathogen that causes amoebic dysentery in ~100 million people each year worldwide. Instead, scientists have been forced to rely on studies with the distantly related reptile pathogen Entamoeba invadens. The long-term goal of our research program is to determine how E. histolytica adapts to different environments it encounters during infection and the disease process. In particular, we are interested in how E. histolytica adapts to the environment of the large intestine in order to colonize there and spread disease by formation and dissemination of infectious cysts. We have now established a reproducible system for encystation and excystation of E. histolytica in culture. This major technological advance enables us to pursue an understanding of how E. histolytica senses and responds to environmental cues that signal conversion from motile trophozoite to infectious cyst and back. As part of our long-term goal, the overall objective of this proposal is to identify and characterize genes responsible for initiation of encystation. The rationale for the proposed project is that understanding how E. histolytica senses and responds to its environment through encystation will lead to a better understanding of how this pathogen can survive and thrive as it encounters very diverse environments during different stages of its infectious cycle. We will pursue two specific aims: (1) identify encystation initiation genes using RNAseq; and (2) screen an overexpression library for genes involved in initiation of encystation in E. histolytica. Candidate genes identified through these two approaches will be validated through analysis of gene silenced and gene overexpression strains. We will evaluate these strains for their ability to encyst, excyst, and establish standard trophozoite growth as well as their responses to other stresses such as heat, oxidative, and nitrosative stress to determine whether any of the candidate genes play a general stress response role. As part of the proposed research, we will optimize our encystation protocol and determine other environmental signals that trigger more rapid encystation. The complementary RNAseq and library screening approaches should allow us to identify genes required for the earliest stages of encystation prior to chitin cell wall formation as well as regulatory genes. The significance of this research is that we can now begin to understand the interplay of environmental signals that regulate encystation and how these signals are acted upon by E. histolytica. This research will have an important impact on the field in that for the first time the processes involved in stage conversion can be fully studied directly in the human pathogen to provide a better understanding of how E. histolytica can thrive during colonization and continue to propagate disease through spread of infectious cysts.

NIH Research Projects · FY 2026 · 2023-05

Effects of macromolecular crowding on DNA mechanics, topology, transcription, and condensation ABSTRACT Macromolecular crowding (MMC) changes the concentration and affinities of intracellular biomolecules and promotes liquid phase separation. MMC has been shown to change the melting temperature of DNA oligos, but broad characterization of how it affects the mechanical stability of DNA is incomplete. Crowded DNA condensates may generate sub-piconewton retractile tension on DNA, which can be conveniently explored using magnetic/optical tweezers. While many experiments on DNA motors employ tensions opposing or assisting translocation of several to tens of pN, our group showed that sub-piconewton tension affects DNA topology, from supercoiling to protein-mediated looping, as well as the probability that an elongating E. coli RNA polymerase (RNAP) surpasses a protein roadblock. Surprisingly, the effect of MMC on topologies such as supercoiling and protein-mediated loops, and processes such as transcription, protein spreading, and condensation has not been well characterized. This proposal aims to assess the effects of MMC on DNA configurations including unwinding and looping, protein spreading, and liquid phase separation to integrate these features into our understanding of intracellular molecular biology. To do so, we integrate single-molecule, in vitro experiments with in vivo measurements and computational/theoretical approaches Over the next five years, we will analyze both model and/or novel systems with single-molecule techniques to learn how MMC changes DNA structure, affects protein-mediated looping, and alters transcription. We will also investigate how MMC influences ParB-mediated spreading along DNA and liquid-liquid phase separation (LLPS) which requires crowding agents in vitro. Then we propose to build artificial LLPS systems with which to learn what components are required to localize a liquid-liquid phase separated droplet on a DNA segment. P-granules, Cajal bodies, segrosome, and the nucleolus are some examples of LLPS that include specific genomic regions and demonstrate the ubiquity and importance of this phenomenon. Macromolecular crowding generates forces that affect fundamental DNA mechanics and topology and in the last decade MMC has emerged as a driver of LLPS. We will integrate in vitro experiments with computational and theoretical approaches and compare with appropriate in vivo measurements performed by a collaborator. Discovering the mechanisms by which crowding modifies DNA configurations, transactions, and segregation will advance our understanding of genome biophysics and regulation and provide new tools for synthetic biology.

NIH Research Projects · FY 2026 · 2023-04

Project Summary: Exosome therapy holds remarkable promise to treat acute infarction, a major cause of heart failure that affects over 6 million people in the US. Exosomes are nanoparticles secreted by cells to facilitate intercellular signaling through their bioactive cargos such as microRNAs (miRNAs). Compared to cell-based therapies, exosomes have distinct advantages including low immunogenicity, absence of tumorigenic risk, and amenable for large scale production and off-of-shelf storage. Among various exosomes used for cardiac regenerative medicine, exosomes from human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) have received significant attention. While 2D culture has been considered as “gold standard” for exosome production, recent studies show 3D culture promote the production of pro-reparative exosomes. To this end, we developed nanowired human cardiac organoids, which are composed of hPSC-CMs, human primary cardiac fibroblasts, endothelial cells, stromal cells, and electrically conductive silicon nanowires (e-SiNWs). Compared to 2D hPSC- CM culture, organoids provide a myocardium mimetic microtissue platform, and the e-SiNWs creates a conductive microenvironment to enhance exosome biogenesis and secretion. Compared to the unwired organoids (without e-SiNWs), the nanowired organoids showed the significantly higher ability to improve vascularization, preserve myocardium, attenuate pathological hypertrophy of the infarcted hearts and recover their contractile function. To improve the reproducibility of exosomes, we developed isogenic hPSC cardiac organoids using hPSC-CMs, -cFBs (cardiac fibroblasts), and -ECs (endothelial cells) derived from a single hPSC line. The goal of this proposal is to determine the effects of key variables of the nanowired hPSC cardiac organoids (i.e., size, cell composition and e-SiNW structures) on their exosome production and functionality. The central hypothesis of the proposal is the nanowired hPSC cardiac organoids provide an electrically conductive, biomimetic environment for hPSC-CMs, -cFBs, and -ECs to produce therapeutically potent exosomes for cardiac repair. The proposal is innovative is that, for the first time, we will synergize electrical nanomaterials with human cardiac organoids to enhance exosome production and functionality. Accordingly, we will pursue 2 Aims: 1): Determine the effects of cell seeding ratio, size and e-SiNW structure of the nanowired isogenic hPSC cardiac organoids on exosome production and function, 2): Determine the therapeutic efficacy of the exosomes derived from the optimized nanowired organoids. The proposed studies are significant in that we aim to shift the current paradigm of exosome production to develop organ-specific therapeutic exosomes by leveraging the recent advances in nanofabrication and engineered human cardiac organoids. These studies will provide a guiding principle to design and develop next generation of tissue engineering constructs that can provide a source of sustained exosome production after implantation in addition to a cell replacement therapy.

NIH Research Projects · FY 2026 · 2023-04

Project Summary/Abstract Energy intake (EI) plays a critical role in the etiology and prevention of prevalent and debilitating chronic diseases such as overweight/obesity and type 2 diabetes. Self-monitoring is the cornerstone of the self- regulation approach for reducing EI, but prevailing methods are burdensome and inaccurate which limits our ability to understand eating patterns and intervene on them to improve health. There is a clear need for innovative solutions that can unobtrusively monitor and reliably estimate EI in the context of daily life. For 10+ years, our group has researched the utility of a wrist-watch device (e.g., smartwatch) to passively monitor eating behavior by measuring the acceleration and rotation of dominant-hand wrist motion of food being brought to the mouth. Through several studies we have refined our approach for using patterns of wrist motion to identify individual intake gestures ("bite" of food, "drink" of beverage) during meals/snacks. We have shown that we can use intake gesture count to estimate meal-level EI by using advanced modeling to estimate kilocalories per bite (KPB) and kilocalories per drink (KPD) (e.g., EI = #bites x KPB + #drinks x KPD). We are on the cusp of making this approach widely available for clinical application, but our latest advances in sensor- based EI estimation require validation before the method is truly viable in real-world settings. In this project we will definitively address 3 final barriers: 1) Our approach must be validated across settings and among a highly representative sample; 2) Our models that use intake gestures to estimate EI must account for varying contexts, such as different types of foods or food sources, that could influence EI; and 3) We must maximize acceptability of the measurement methods. The proposed study will validate our sensor-based EI estimation methods among a diverse sample, across three settings (cafeteria, home-based, and free-living), incorporating minimal user input on foods and beverages (e.g., high energy density foods, zero calorie beverages) and contexts (e.g., food source, time of day), and using two different sensors (commercial smartwatch and smart ring). We will conduct two controlled data collections in which a single meal is video recorded while participants wear the smartwatch and smart ring: N=300 in a cafeteria and N=240 in participant homes. All participants (N=540) will then wear both devices and complete remote food photography during 4 days of everyday life (free living). We will evaluate sensor-based estimates of EI against ground truth captured using video (cafeteria and home) and remote food photography method (free-living). We will use our findings to create a practical platform to guide researchers/clinicians implementing a sensor-based EI self-monitoring protocol that maximizes accuracy and acceptability (selecting wrist vs. ring sensor, type of user input, and length of self- monitoring). Our platform will ultimately support work in precision nutrition by transforming how we develop and evaluate health-related interventions, and ultimately improve the quality of interventions targeting EI.

NIH Research Projects · FY 2026 · 2023-01

Individuals in low-resource communities were twice as likely to die from Coronavirus Disease 2019 (Covid-19). These poor health outcomes were fueled by inadequate access to essential resources throughout the pandemic. Such outcomes are not unique to Covid-19. Over the past century, emerging infectious diseases have significantly perpetuated poor health outcomes in low-resource communities. The interconnected pathways leading to these outcomes, including heterogeneous disease epidemiology, sociodemographic characteristics, and treatment uptake, remain understudied. Mobile health clinics (MHC) are aneffective and versatile tool for improving health outcomes through timely delivery of interventions to populations with insufficient medical resources. However, the inability to effectively identify and prioritize communities with high disease burden has posed daunting challenges for MHC decision makers and has led to suboptimal allocation strategies. To help improve the efficiency of these field-level interventions and improve health outcomes during infectious disease outbreaks, our proposal seeks to develop a modeling toolkit to improve infectious disease surveillance and prediction in low-resource settings and prioritize the delivery of essential resources to high-burden communities in real time. Our innovative, multilevel modeling framework will utilize statistical models, geospatial models, machine learning, compartment-based and agent-based models to improve health outcomes through 1) establishing a real-time data system feed for infectious disease surveillance and estimation of disease epidemiology across communities 2) identifying high-burden populations for allocation of essential resources, 3) evaluating the complex interplay between sociodemographic and clinical characteristics, infectious disease epidemiology, healthcare availability, and intervention uptake in order to improve emergency planning and response during infectious disease outbreaks and future health emergencies, and 4) establishing a modeling toolkit to inform delivery of essential resources to communities in real-time. This will be accomplished through real-time integration of infectious disease outcome data, sociodemographic, clinical characteristics, and community-level healthcare availability and other contextual factors for estimation of key input parameters in the dynamic simulation modeling framework. The framework we propose will be generalizable to other infectious diseases, where model inputs will be disease and location dependent for swift translation to other public health problems. To demonstrate the utility of our toolkit, our modeling framework will focus on delivery of MHCs to South Carolina communities for Covid-19, influenza, RSV, HCV, and HIV screening and treatment. Our proposal will improve emergency planning by developing the modeling infrastructure for community-level disease surveillance and epidemiology, ultimately improving timely delivery of essential resources to those of greatest need. Covid-19 alone had claimed nearly 1 million American lives and hospitalized over 4 million individuals through February 2022. Utilization of this toolkit by public health decision makers can prevent thousands of future infectious disease-related deaths. Our modeling framework is translatable to all infectious diseases and geographic regions and has potential to save many more lives during infectious disease outbreaks and future health emergencies.

NIH Research Projects · FY 2024 · 2022-09

PROJECT SUMMARY Most emergency departments (ED) in the United States are poorly designed, organized and equipped to provide safe and effective care for children with mental and behavioral health (MBH) conditions. Safety concerns for children with MBH conditions in the ED include delays in care, lack of appropriate psychiatric consults during visits, patient self-harm, harm against others or the environment, and involuntary restraint use resulting in patient and staff injury. A systems approach is needed to address the many latent conditions in the ED that impact MBH patient and provider safety. The purpose of the proposed ‘Realizing Improved Patient Care through Human- centered Design for Pediatric mental and behavioral health in the Emergency Department (RIPCHD.PED)’ patient safety learning lab (PSLL) is to develop and implement pediatric MBH health work systems in the ED that promote safe, efficient and effective care by minimizing unnecessary stressors for patients while also improving provider well-being. This PSLL will include a focus on the needs of children and their caregivers from minority communities in order to address disparities in MBH care in the ED. Further, the PSLL will focus on rural and urban EDs to ensure that proposed solutions address a range of resource constraints typically found in EDs across the US. A multidisciplinary team from Clemson University, Prisma Health and University of South Carolina School of Medicine will collaborate using a systems engineering approach involving in-depth problem analysis, design, development, implementation and evaluation. The specific aims of this project include, Aim 1: Use systems engineering methods to develop a shared in-depth understanding of the work system facilitators and barriers involved in the pediatric MBH ED caregiving workflow, Aim 2: Design and develop human-centered work systems for pediatric MBH patients in the ED that will improve access to timely MBH care, reduce adverse events and improve efficiency for ED healthcare providers and Aim 3: Integrate, implement and evaluate innovative interventions within pediatric MBH work systems in the ED that will improve outcomes for ED patients and healthcare providers. The team will use a range of methods including workflow analysis, journey mapping and space syntax analysis to understand barriers and facilitators and identify opportunities for improvement. An iterative design process will be used to design and develop solutions related to the physical environment, tools and technology and tasks and workflow. This PSLL strongly aligns with AHRQs mission by focusing on safety, quality, equity and access to appropriate mental health care for children with mental and behavioral health conditions. The project will support AHRQ’s strategic focus on children as a priority population by contributing to all 6 goals outlined in AHRQ’s strategic plan. Further, the PSLL will include a focus on underserved rural populations as well as children from Black and Latino communities. RIPCHD.PED PSLL will be the most comprehensive effort ever undertaken to improve work systems for pediatric MBH in the emergency department.

NIH Research Projects · FY 2025 · 2022-09

PROJECT SUMMARY The long-term goal of this proposal is to uncover mechanisms of pathogenicity of Cryptococcus neoformans (Cn) focusing on how Cn adapts to host temperature. Cn is a fungal pathogen that, upon entering the lung and disseminating through the bloodstream, causes a life-threatening meningo-encephalitis primarily in HIV/AIDS patients. Current anti-cryptococcal therapies can have devastating side effects. Thus, new treatment strategies are warranted to eliminate mortality associated with cryptococcosis. The objective of this proposal is to determine how the temperature is sensed by Cn and transmitted to downstream effector pathways critical for pathogenicity. The central hypothesis is that filament-forming GTP-ases called septins provide an essential hub protein complex which links temperature sensing to a compensatory signaling response and plasma membrane (PM) homeostasis. It is proposed that exposure to host temperature results in increased fluidity and curvature within the PM and the elevation of PM-associated phosphatidylinositol 4,5-bisphosphate (PIP2) leading to enrichment of septins at the PM based on PIP2 binding, which has two-fold role in Cn adaptation to host temperature: it maintains PM homeostasis and facilitates stress signaling via phospholipase C (PLC), and protein kinase C (PKC) pathways. In support of this hypothesis, experiments with recombinant septins or studies employing model organisms suggest that septins recognize membrane curvature via their propensity to bind PIP2. Importantly, recombinant septins prevent temperature-induced changes in lipid bilayer composition. Preliminary data supporting this application are: 1) Cn PIP2 levels increase at 37°C. 2) Septins associate with the PM when Cn is shifted to 37°C. 3) Septin-deficient mutants exhibit increased PM permeability and sensitivity to drugs that perturb PM. Published and preliminary data also demonstrate phenotypic similarity between septin-deficient and PLC signaling-defective mutants. The central hypothesis will be tested by pursuing two aims. Aim1: Dynamics of septin assembly at the PM will be defined with TIRF microscopy. Genetic and pharmacological approaches will determine whether septin complexes are enriched at the PM based on increased levels of PIP2. An innovative light switchable allele of Cdc42 (GTPase involved in septin assembly) will help to establish effectors down-stream of Cdc42 acting in septin complex formation. A septin mutant lacking the amphiphatic helix (AH) will be utilized to test the role of AH in recruiting septin complex to the PM. Aim2: An impact of septin complexes on PM lipid composition, PM biophysical properties, stress response signaling dependent on PIP2, and pathogenesis in animal infection model will be determined. The proposed research is significant because it will elucidate a novel mechanism through which septins contribute to sensing high temperature and regulating PM-dependent stress response signaling pathways crucial for the pathogenesis of Cn. Outcomes will be better understanding of how Cn adapts to host temperature and a new foundation upon which to develop improved anti-cryptococcal therapies in HIV/AIDS patients.

NIH Research Projects · FY 2025 · 2022-09

Project Summary/Abstract The desire to tie aspects of fundamental cell biology, the mechanisms of disease propagation, and clinical diagnostics is a major driver for the development of new technologies. Among the biological species that may be exploited along these lines, exosomes are particularly promising. Exosomes are small (30–130 nm) extracellular vesicles (EVs) derived from all cell types within the body, which are now realized as key agents in intracellular communication. They exhibit protein biomarkers from their cells of origin, making them promising candidates for use in disease diagnostics. Likewise, much interest lies in the potential use of exosomes as drug delivery vehicles (i.e., vectors). However, a great deal of fundamental research is necessary before the utility of exosomes is fully realized. A crucial challenge in the application of exosome-based research and application lies in the lack of robust and versatile methods for vesicle isolation from diverse biological media. While isolation and quantification methods have evolved, none have overcome the key issues associated with rigor and reproducibility to cleanly, quickly, and cost-effectively isolate exosomes. To address this void, an extremely efficient platform technology for exosome capture and isolation, based on novel poly(ethylene- terephthalate) (PET) capillary-channeled polymer (C-CP) fibers and films, is being developed for applications across the scales of relevance for basic research, clinical diagnostics, and preparative recovery. Initial results show that the fibers can effectively isolate extracellular vesicles, enriched in exosomes, with size distributions and yields comparable to traditional isolation methods, in much shorter times, smaller volume scales, and higher purity. Proposed here is the further development and validation of this exosome isolation methodology for fundamental research and clinical laboratories, with extension to the preparative-scale for vector applications. As dictated by the objectives of this program, and as demanded by the collective “exosome community”, the ultimate objective of the effort is the delivery of working prototypes for evaluation by scientific peers and potential commercial providers. The Research and Development program is pursued across three Specific Aims. In the first, highly permeable chromatography columns created from unique-shaped fibers provide a platform for isolation and purification of exosomes amenable to applications on the clinical, research, and preparative scales, superior to current exosome isolation methodologies. In the second, implementation of the fibers in spin-down tip format provides greater versatility towards generic- and targeted-exosome harvesting using common, bench-top centrifuges. In the third, C-CP fiber films can be configured to affect a high-efficiency, multiplexed lateral flow immunoassay for clinical diagnostics. It is fully believed that the results of this program will demonstrate that novel C-CP fiber/film isolation platforms will prove to be an efficient, cost- effective means to isolate exosomes for use in fundamental biochemistry research, clinical diagnostics, and preparative applications, and that those characteristics will lead to commercial availability of the platfroms.

NIH Research Projects · FY 2025 · 2022-09

Abstract Amyloid aggregation of islet amyloid polypeptide (IAPP) is associated with β-cell death in type-2 diabetes (T2D). IAPP, a peptide hormone co-secreted with insulin by β-cells, is one of the most amyloidogenic proteins and readily forms amyloid fibrils in vitro. Mounting evidence suggests that inhibition of IAPP aggregation and aggregation-mediated cytotoxicity, our long-term goal, is an attractive therapeutic strategy to prevent β-cell death and stop the progression of diabetic conditions in T2D. With the recent advances of Cryo-EM in Structural Biology, atomic structures of IAPP fibrils have been solved, comprised of parallel in-register β-sheets as the cross-β core. However, due to heterogeneous and transient nature of oligomer intermediates populated during aggregation, many details of the process from isolated monomers to final fibrils are still unknown. With amyloid toxicity likely mediated by direct or indirect interactions with the cell membrane, it is increasingly important to study the aggregation of IAPP in the membrane environment. Increasing evidence also suggests pathological correlations between different amyloid diseases – e.g., T2D is the risk factor of neurodegenerative diseases, including Alzheimer’s and Parkinson’s diseases; and bacterial amyloids may contribute to the onset of neurodegenerative diseases and diabetes. Cross-interactions between different amyloid proteins at the molecular level might contribute to the pathological correlation between corresponding diseases. We have demonstrated that novel nanoparticles can be engineered to mitigate hIAPP aggregation and cytotoxicity. Despite many advantages including the ability to cross biological barriers, major concerns for nanomedicine development include potential toxicity associated with immune responses and the lack of specificity. In this MIRA renewal application, the PI proposes to continuously uncover molecular mechanisms of IAPP aggregation and to explore novel nanoparticle approaches to inhibit IAPP aggregation and toxicity in the following directions: 1) IAPP aggregation and interactions with the membrane; 2) cross-interactions between hIAPP and other amyloidogenic proteins; and 3) mitigation of IAPP amyloidosis with nanoparticles functionalized by endogenous inhibitors. The PI lab will combine computational modeling with experimental characterization and validation. Computational modeling can help bridge the time and length scale gaps between experimental observations and the underlying molecular systems, providing not only molecular insights to experimental observations but also offering experimentally-testable hypotheses. Such a combined computational and experimental approach can improve research efficiency and shorten discovery cycle. The outcome of the proposed studies will help understand disease mechanisms and discover novel therapeutic targets (Project 1); provide molecular bases for pathological correlations between T2D and other amyloid diseases, and the contribution of bacterial infections and dysbiosis to the onset of T2D (Project 2); and offer new approaches to design anti-amyloid nanoparticles with high specificity and reduced nanotoxicity (Project 3). 1

NIH Research Projects · FY 2025 · 2022-09

Understanding the genetic architecture of complex traits is critical for personalized medicine, as knowledge of underlying risk loci is required for treatment and prediction of disease state. Genome wide association studies (GWAS) have identified hundreds of thousands of genotype-phenotype associations. This information – incorporated in Polygenic Risk Scores (PRS) – has provided levels of prediction accuracy for some complex diseases and health-related traits comparable to those obtained for monogenic diseases. While this is an important advance, significant problems still need to be overcome to achieve the ultimate goal of precision medicine. First, prediction accuracy is low for most complex traits. Possible reasons for this observation are the higher polygenicity of these traits, requiring larger sample sizes to discover associated loci and estimate their effect; and gene-by-context interactions that are usually ignored in prediction models. Second, results obtained in a population usually transfer poorly to a different population and are therefore not generalizable. This is due to differences in effect sizes across populations because of different patterns of linkage disequilibrium (LD) and allele frequencies and/or gene-by-context interactions. My research program will focus on investigating the role of gene-by-context interactions on the genetic architecture and polygenic prediction of complex traits. My first goal is to elucidate the importance of gene-by-context interactions for complex traits. To do so, I will develop a new analytical strategy using a combination of methods that will increase the power for discoveries. This will result in a comprehensive assessment of the contribution of gene-by-context interactions to complex trait variation. My second goal is to evaluate the utility of accounting for gene-by-context interactions to improve phenotypic prediction. To do so, I will use statistical methods developed for agricultural breeding that have been successful at increasing complex trait prediction accuracy in that field. I will also develop a prediction method that models gene-by-context interactions explicitly, while simultaneously accounting for other sources of effect heterogeneity. The long-term goal of my laboratory is to increase prediction accuracy for medically relevant traits in the general population.

NIH Research Projects · FY 2026 · 2022-08

PROJECT SUMMARY Studies across a broad range of species have established a common set of evolutionarily conserved hallmarks of aging, including age-related decline in mobility and mitochondrial failure. This evidence points to the potential for pharmacological intervention to improve healthy aging and extend longevity. Pharmacological blockade of the Renin Angiotensin System (RAS) by inhibition of the angiotensin-converting enzyme (ACE) is an effective therapy in improving age-related impairment of physical function and is a potential strategy to slow human aging. The beneficial effect of ACE ihibition in reducing age-associated damage of tissues, such as the skeletal muscle, may be attributed in part by the drug’s capacity to preserve mitochondrial function. However, improvement in physical performance in response to RAS blockade varies widely in human studies, potentially due to genetic variation among individuals. Research in this area has been slowed by lack of understanding of the biology that connects aging, genetics, and response to drug treatment and because of the shortage of appropriate animal models for biological and intervention studies. To tackle this issue, we propose to leverage the evolutionary conservation of ACE across species to determine the genetic basis for the anti-aging effect of the ACEi Lisinopril in the invertebrate model D. melanogaster. The proposed research builds on a powerful genomics resource, the Drosophila Genetic Reference Panel (DGRP), which consists of genetically distinct lines of flies derived from a natural population. Our preliminary studies using three genetically diverse DGRP lines revealed that treatment with Lisinopril extends lifespan and improves age-specific walking in D. melanogaster, but it does so in a genotype-specific manner. Our data also suggest that genotype-specific responses to Lisinopril may act, in part, through variation in the degree to which mitochondrial function is affected by the drug treatment. To address this hypothesis, we propose to use genome-wide association mapping in 400 new DGRP lines to first identify variants, genes and genetic pathways that respond to ACEi to ameliorate age-related decline in locomotor activity and extend lifespan (Aim 1). Functional genetic studies using RNA interference (RNAi) of candidate genes are then proposed to validate the effects of ACEi on lifespan and healthspan and to test whether these effects are mediated via changes in mitochondrial function in skeletal muscle (Aim 2). Finally, we propose to evaluate the genome wide effects of ACEi on gene expression and the metabolome for genes for which RNAi in thoracic muscle extends lifespan and/or healthspan in order to gain insight into the mechanism(s) by which ACEi modulates lifespan and healthspan (Aim 3). Completion of the proposed studies will identify genetic and metabolic pathways that regulate the ACEi-mediated improvement in physical performance in older individuals.

NIH Research Projects · FY 2026 · 2022-07

Project Summary/Abstract Immune responses are the result of a combined effort of multiple cell types. In innate immune responses the activity of both macrophages and neutrophils is important in targeting pathogens, resolving tissue damage, and maintaining homeostasis. My laboratory uses the larval zebrafish model to determine the differential role and functions of these two innate cell types in inflammatory responses. The overarching goal of my research program is to identify specific signaling pathways, including signals, receptors, and effector mechanisms, that are required for the function of macrophages versus neutrophils. During human disease, the function of just a subset of these cells may go awry, yet common treatments target broad pathways that inhibit multiple cell types and therefore cause harmful side effects. Identification of discrete mechanisms used by single cell types in inflammatory disease will provide targets for future precision therapies. We have developed an experimental system in larval zebrafish using the fungal pathogen A. fumigatus that separates the function of macrophages and neutrophils. Over the next five years, we propose to combine this system with genetic targeting tools and chemical inhibitors to interrogate the requirement of intracellular killing mechanisms, cell death pathways, Toll-like receptors, and C-type lectin receptors in macrophage versus neutrophil functions against A. fumigatus and in response to PAMPs and DAMPs. In future research, we will expand our experimental model to interrogate the role of these genes and pathways in other inflammatory scenarios, such as sterile inflammation during auto-inflammatory disease. Altogether, this research will delineate complete pathways differentially required for innate immune cell function.

NIH Research Projects · FY 2024 · 2022-07

ABSTRACT/SUMMARY To address the shortage of underrepresented STEM professionals, The Call Me Doctor® ESTEEMED Scholars Program will serve as the undergrad arm of Clemson’s existing Call Me Doctor® Graduate Fellowship Program, establishing a pipeline for underrepresented undergraduates in bioengineering and bioengineering-related fields. The program integrates sustainable strategies through a combination of existing and innovative programming to offer academic, mentoring, and research support to increase participation of underrepresented students in PhD and MD/PhD careers in biomedical research. The program objectives will be achieved through the following aims: AIM 1 - Create communities of support through formal and informal mentoring networks, AIM 2 - Support early development of research skills and scientific communication, and AIM 3 - Facilitate exploration of advanced careers related to biomedical engineering through professional and career development workshops with subsequent self-reflection to create a Program Portfolio. The key elements of the Call Me Doctor® ESTEEMED Scholars Program are 1) EUREKA!, a Summer Bridge program that provides early immersion in research experiences for incoming freshmen that will be combined with coursework in computing and introductory biomedical science concepts, 2) Academic year activities including laboratory rotations for lab selection; laboratory research; mentoring by Call Me Doctor® graduate fellows, peers, faculty, and staff; lunch-and-learn career panels; visits to biomedical and clinical research labs, and presentation of research at the annual Call Me Doctor® Symposium; 3) Development of a program portfolio including self-reflections of research and career exposures; 4) Sophomore summer research experience; and 5) Junior year transition to the bioengineering department’s advanced thesis-based honors program, a program with an over 75% success rate of enrollment in advanced degree programs. The diverse team of five Clemson University investigators is led by an African- American female (Alexander-Bryant), recipient of a 2021 NSF Early CAREER Award, and an African-American male (Gilmore), director of the existing Call Me Doctor® Graduate Fellowship Program. All team members are members of the bioengineering department’s Diversity and Inclusion Committee, which the PI directs. Outcomes of the program include 1) development of research and scientific communication skills, 2) presentation of research at local and national conferences, 3) publication of research in scientific journals, 4) participation in sophomore summer research, 5) transition upon junior year into the bioengineering department’s honors program, and 6) 75% matriculation into graduate school.

NIH Research Projects · FY 2025 · 2022-07

PROJECT SUMMARY/ABSTRACT Eukaryotic pathogens are the causative agents of some of the most devastating and intractable diseases of humans, including malaria, amebic dysentery, African sleeping sickness, Chagas disease, trichomoniasis, aspergillosis, cryptococcal fungal meningitis, toxoplasmosis and primary amebic meningoencephalitis (PAM). The global impact of these diseases is immense. It is noteworthy that many of these pathogens are the causative agents of neglected tropical diseases (NTDs), neglected diseases of poverty (NDPs) and/or are classified as bioterrorism agents. Importantly, infections caused by eukaryotic pathogens are increasing in the US due to globalization. The primary goal of this COBRE proposal is to increase the number of NIH-funded scientists in the state of South Carolina by supporting a world-class research center, the Eukaryotic Pathogens Innovation Center (EPIC), at Clemson University (CU). The scientific focus of EPIC is a multidisciplinary study of important global eukaryotic pathogens. EPIC is the first-and-only in the state with a focus on infectious diseases, and the first- and-only in the country with a focus on eukaryotic pathogens. Four projects from target junior investigators will be supported. Their projects are 1) Regulation mechanisms of Trypanosome brucei axonemal dynein, 2) Functional roles of ncRNA, afu-182, in azole response and pathobiology of Aspergillus fumigatus, 3) Investigating the function of macrophages in the efficacy of anti-fungal drugs in larval zebrafish, and 4) Evaluating anti-parasitic diazacyclobutenes. These investigators will be matched with external and internal mentors who are established NIH-funded researchers. The projects will be supported by a well-organized Administrative Core and two state-of-the-art Scientific Cores in Genomics, and Imaging/Cell Sorting. The center also has a substantial infrastructure base and significant institutional support. For example, CU will recruit two additional faculty members and two post-doctoral fellows to expand activities of this center over the course of the project period. Pledges of graduate assistantships, equipment, and space further exemplify the institutional commitment. The continuation of this COBRE-funded center will significantly expand research in South Carolina and will facilitate recruitment, training, and retention of a critical mass of investigators with cross-disciplinary skills in this important research area.

NIH Research Projects · FY 2026 · 2022-01

Project Summary Craniofacial skeletal deformities include mandibular retrognathism (MR), which is Class II skeletal deformity occurring in ~5% of individuals, and mandibular prognathism (MP), which is Class III skeletal deformity occurring in ~1% of individuals. There is an association between craniofacial skeletal deformity and TMJ disorders, with degenerative changes in 43% of Class II and 20% of Class III deformities, but only in 3% of Class I (i.e., no skeletal deformity). Moreover, Class II females which typically have smaller condyles, have a much higher risk to develop TMJ dysfunction. Even though there is increasing evidence that craniofacial skeletal deformity may be an important risk factor for the development of TMJ disorders, only studying morphological parameters has not given any insight into a biological mechanism or a cause-effect relationship. Additionally, orthognathic surgery can be beneficial by adjusting skeletal morphology, but its efficacy on TMJ function is poorly understood. Joint morphology drives biomechanics, which in turn regulates mechanobiology in joint tissue remodeling. Identifying the mechanistic relationships between craniofacial morphology, TMJ biomechanics, and joint mechanobiology, has led to a better understanding of the etiology and sex disparity of TMJ disorders. Specifically, smaller condyles and shorter mandibles increase female TMJ loads, contact stresses and energy density, while decreasing both tissue nutrient availability and cell viability, leading to pathological TMJ remodeling. The objective of this application is to take this same integrated approach of TMJ morphology, mechanics, and mechanobiology but in the context of Class II and III phenotypes. Our over-arching hypothesis is that mechanical loading magnitude, as well as tissue nutrient availability and cell viability, of the TMJ are significantly different between skeletally mature individuals with Class I, II, and III phenotypes. More specifically we hypothesize that the TMJ in Class II females has the highest mechanical loading, lowest tissue nutrient availability, and lowest cell viability due to disproportionally small condyle and short mandible, and that orthognathic surgery can improve both TMJ biomechanics and mechanobiology, thus giving mechanistic insight. We propose three specific aims (1) Determine differences in craniofacial morphology and TMJ biomechanics between individuals with Class I, II, and III phenotypes. (2) Determine differences in TMJ mechanobiological indicators between individuals with Class I, II, and III phenotypes. (3) Determine differences in TMJ morphology, mechanics, mechanobiology before and after orthognathic surgery in individuals with Class II and III phenotypes. This project combines expertise in morphologic characterization and treatment of craniofacial deformities of NIDCR Clinical Center intramural investigators, with the TMJ biomechanics and mechanobiology measurement and modeling expertise of the extramural applicants. The outcomes will (i) identify clinically measurable risk factors for TMJ disorders in skeletal deformity patients, (ii) justify the benefit of orthognathic surgery for restoring TMJ health, and (iii) guide future patient-specific surgical planning to optimize post-op TMJ function.

NIH Research Projects · FY 2025 · 2021-08

AA-White differences have been observed in cognitive performance and risk for cognitive impairment, particularly Alzheimer’s disease and related dementias (ADRD). Few studies have examined how sleep may further explain these disparities, especially considering that sleep disturbances are common in AA adults. Since disparities in cognition and sleep have been observed in middle-aged adults, this portion of the lifespan is ideal to investigate the association between sleep and cognitive decline as well as the underlying psychosocial, contextual, and biomarker factors that influence sleep and/or cognitive AA-White disparities. Every year for 4 years, the proposed study will collect measures of sleep duration and quality, cognitive functioning, inflammatory biomarkers (e.g., CRP, IL-6), life stressors, and resilience factors (e.g., spirituality, coping) in a sample of middle- aged participants from the HANDLS study. The overall objective of this study is to identify mechanisms of AA-White sleep disparities and the mechanisms that account for AA- White differences in ADRD risk. The central hypothesis is that disparities in sleep will be associated with disparities in cognitive decline. Guided by the investigators’ previous research, three specific aims will be tested: 1) To determine if there are differences in the daily coupling of sleep and mobile cognitive performance and whether differences in this coupling are moderated by life stressors (e.g., financial strain and neighborhood disorder); 2) To test longitudinal associations among sleep and performance on mobile cognitive assessments and explore the role of life stressors, protective factors (e.g., spirituality and neighborhood cohesion) and inflammation; 3) To determine whether changes in the strength of the daily coupling of sleep and performance on mobile cognitive assessments relate to differences in traditional clinical measures of cognitive decline over 4 years, and to elucidate the potential mediational role of inflammation. This approach is innovative because it will not only examine the association between sleep and cognitive functioning over time, but will also examine the relationship of life stressors, sleep, inflammatory biomarkers, and/or resilient factors on disparities in cognitive decline. The proposed research is significant because of its potential to identify psychosocial and contextual factors related to impaired sleep and cognition that could serve as the basis for evidence-based behavioral or policy interventions.

NIH Research Projects · FY 2025 · 2021-08

Project Summary Splicing is the process of removing intronic regions from a precursor messenger RNA (mRNA) and combining exons into a mature transcript. Alternative splicing results in differential intron removal, producing multiple alternatively spliced isoforms arising from a common precursor mRNA. The dysregulation of splicing is estimated to underlie at least 15% of human diseases, and is likely to contribute to many more. Splice reactions are performed by the spliceosome, an RNA protein complex that is assembled onto precursor mRNA in stages. The final activity of the spliceosome is influenced by a combination of trans-acting spliceosome factors and cis elements within the precursor mRNA. However, factors involved in cis element function, like sequence motifs and RNA structure folds, are not fully understood, and a majority of such elements remain unidentified. This is particularly true for branchpoint selection, an essential early stage of spliceosome assembly within the intron around the catalytic adenosine. Although the branchpoint is loosely recognized as a highly degenerate sequence motif, it influences downstream splice site selection. My first goal is to elucidate the impact of RNA structure on branchpoint selection by focusing on RNA structure-mediated binding by the spliceosome associated SF3B complex. To do so, I will develop RNA secondary structure models for SF3B-dependent precursor RNAs to identify enriched structural motifs. My work will entail the first large-scale derivation of intronic secondary structures, including branchpoint regions, which will aid in better understanding of how RNA structures around cis regulatory elements influence splicing. My second goal is to develop a system to identify cis splicing regulatory elements and rapidly test their functional significance. To identify regulatory elements, I will identify cis features on mRNAs, including protein binding sites, conservation and RNA secondary structure, and use machine learning to discover novel signatures of functionally relevant cis regulatory regions. The functional impact of such sites on alternative splicing will be experimentally tested through use of antisense oligonucleotide (ASO) that can block or inhibit the regulatory region. I will set up a positive feedback loop where I can predict cis splice regulatory elements and immediately test their impact on splicing with ASOs, incorporating the test results back into the model to improve predictions. This system will lead to accurate prediction of cis regulatory splicing elements within any gene of interest. Accurate identification of cis elements will improve our ability to understand co-regulation of alternative splicing. The long-term vision of my research is to demystify the splicing code by clarifying the role of RNA structure in splicing and developing a powerful system to identify functional cis regulatory splicing elements and test their activity.

NIH Research Projects · FY 2025 · 2021-08

PROJECT SUMMARY/ABSTRACT Precise replication of DNA is required to maintain genome stability. Replication forks face many obstacles from both endogenous and exogenous sources that result in fork stalling or breakage threatening genome integrity. The double strand break repair pathway, homologous recombination, has critical roles at stalled replication forks independent of double strand break repair. The importance of this pathway is highlighted by patients with inherited chromosomal instability orders and cancer predisposition syndromes. Although an intense area of study, the mechanistic role of recombination proteins at replication forks is still poorly understood. A comprehensive understanding of the replication response is critical for the understanding the molecular mechanisms of human disease and to lead to development of novel therapeutics for patients harboring defects in replication response genes. The long-term goal of the PI to elucidate the roles of recombination proteins in the replication stress response. Here we will elucidate the role of recombination proteins at hydroxyurea-stalled replication forks in two distinct projects. In Project 1, we use a powerful separation-of-function allele of the central recombination enzyme, RAD51, to determine how RAD51 protects the integrity of the replication fork during unchallenged and stressed conditions using a combination of genetic, molecular biology and proteomic approaches. In Project 2, we propose a series of experiments to investigate the role of additional recombination accessory factors in the replication response. Preliminary data from our lab has uncovered a novel role for recombination proteins in protecting the integrity of stalled replication forks. We will test our current models through mechanistic dissection of the replication stress response pathway using genetic and molecular approaches. The work presented here will lay the foundation for future studies involving the elucidation of molecular mechanisms of recombination proteins involved in the replication stress response. The completion of this work will lead to not only a better of understanding of the role recombination proteins play at stalled replication forks, but will also provide molecular insight into how disruption of this pathway results in human disease. A complete understanding of this pathway is essential for development of therapeutics for patients with inherited genome instability disorders and cancer that target the cellular replication response.

NIH Research Projects · FY 2025 · 2021-05

ABSTRACT – MECHANISTIC PHARMACODYNAMIC MODELING FOR DRUG COMBINATIONS Most industries simulate design options before implementation, but this is rarely possible in the pharmaceutical and medical industries. An important gap is unbiased drug combination response predictions, which is experimentally impractical. A long-term vision of our lab is improving drug development and precision medicine by building “mechanistic pharmacodynamic models” that can simulate drug combination responses. Such models infuse pharmacology concepts with physics and engineering approaches to describe causal, quantitative, and dynamic mechanisms underlying drug response. A foundational premise is that capturing (i) mechanistic, causal network structure, (ii) dose-response, (iii) dynamics, and (iv) cell-cell variability is necessary to improve many combination response predictions. Here, we study how drug combinations affect single-cell proliferation and death fates by merging theoretical and experimental innovation. The first project builds on our recent and one of the most comprehensive mechanistic models for regulation of single-cell proliferation and death dynamics. We will leverage our involvement with a recent LINCS consortium effort that generated a deep molecular characterization of perturbation response dynamics, including dose responses to 8 drugs. We will integrate network biology with mechanistic models using new approaches to obtain candidate models that are consistent with this dataset, and experimentally test drug combination predictions for the 8 drugs. This will for the first time address the prediction of a comprehensive set of drug combination responses across varied mechanisms of action relying on causal biochemical reasoning and also identify novel mechanisms of signaling and drug response through iterative model refinement and experimental validation. The second project builds on our recently developed experimental approach for fluorescence multiplexing called MuSIC. We propose that MuSIC can enable high-dimensional genetic interaction screening in single mammalian cells, which is not yet possible but would be transformative. We will test the approach by evaluating genetic interactions between a recently curated set of 667 gene targets of 1,578 FDA-approved drugs. This work will nominate new network structures not only for use in the first project, but also more generally. The third project also leverages the above mechanistic model but pivots across cell lines with Cancer Cell Line Encyclopedia data for 1,132 cell lines and 24 drugs. An innovative and foundational feature of our model is that it ingests multi-omic data to create a cell line-specific context through “initialization”. We will generate 1,132 model variants with cell line-specific profiles and evaluate predictive capacity for single and prioritized drug combination responses. This project will establish performance of the current models, identify critical modeling gaps for improving predictions, suggest new potentially effective drug combinations, and elucidate mechanisms underlying synergy. Overall, these projects will produce next-generation pharmacodynamic models that move towards filling the drug combination prediction gap that hinders drug development and precision medicine.

NIH Research Projects · FY 2025 · 2021-03

Project Summary/Abstract Human arginine vasopressin receptor 2 (AVPR2) is an -helical membrane protein expressed in the collecting ducts of the kidneys involved in regulating urine volume. Mutations of AVPR2 at some 96 sites are known to cause nephrogenic diabetes insipidus (NDI), likely by promoting misfolding. The vasopressin antagonist drugs (“vaptans”) have been shown to rescue cell-surface expression, putatively by acting as chaperones stabilizing the native folded state. Thus, understanding the relative energetics of the folded and misfolded states in the presence and absence of ligands would shed light on the native structural dynamics of AVPR2 and how those dynamics are changed by disease-causing mutations. Such results would be relevant to NDI, and also more generally to diseases arising from G-protein coupled receptors (GPCRs). However, the established biochemical technique of chemical denaturation in detergent micelles that is used to measure membrane-protein thermodynamic stability (G) and its change upon mutation or ligand binding (G) suffers from several limitations that make it unsuitable for studies of AVPR2. In particular, the non-native detergent environment, the poorly defined denatured state with significant residual secondary structure, and the need to extrapolate from high denaturant concentration cause the measured energetics to poorly reflect the underlying, biologically relevant molecular values. Most significantly, chemical-denaturation-based techniques have never been successfully applied to GPCRs because GPCRs do not globally refold when the denaturant is removed. These shortcomings motivate the overall aim of this proposal: to develop alternate techniques for measuring membrane-protein energetics, based on force-induced unfolding rather than chemical denaturation. Such techniques, implemented on an atomic force microscope (AFM), can study membrane proteins in the native lipid bilayer and obviate the problem of globally reversible unfolding by probing a small portion of the protein at a time. Work during the postdoctoral K99 phase will use the model membrane protein bacteriorhodopsin (bR) to further develop these force-based techniques. Two particular aims will be achieved: (1) measurement of point-mutant free energy changes of bR in its native bilayer and without confounding chemical denaturant and (2) quantification of the energetics of a photo-activated ligand isomerization in bR. Completing this work during the K99 phase will establish the basis for the aim of the independent R00 phase: to elucidate the folding and ligand-interaction energetics of AVPR2 using these new techniques. In addition to providing specific insight into AVPR2 folding and misfolding, this work will establish a new paradigm in which energetic measurements can be made directly in biomedically relevant systems like AVPR2, rather than just in model systems. The transition to independence will also be facilitated by training during the K99 phase, most notably in the expression and purification of GPCR samples. The University of Colorado provides world-class facilities for carrying out this work, and co-mentors will offer expertise in both single-molecule AFM experiments and membrane-protein biochemistry.