Cornell University

NIH Research Projects · FY 2025 · 2023-09

Project Summary: The structure, dynamics and function of a biomolecule play a key role in determining disease mechanisms, knowledge of which is essential for early diagnosis, drug development and effective treatment. Many biological studies focus on structure determination of biomolecules but the study of dynamics is vital to understand disease mechanisms, including their function and interaction with their environment. Compared to other biophysical methods, multi-frequency 2D Electron Spin Resonance (ESR) spectroscopy are powerful methods for studying structural dynamics of proteins at physiological temperatures for a wide range of time scales (sub-𝑛𝑠 to tens of 𝜇𝑠) and can provide a detailed description of motion that includes both dynamics as well as local structural ordering. Despite major advances, multi-frequency 2D-ESR lack sufficient sensitivity and resolution needed to study biological systems at 𝜇𝑠 timescales, because the signals are heavily dominated by noise with Signal-to-Noise Ratios (SNRs) of unity and so are hardly visible. To address this problem, the proposed research will develop computational methods based on wavelet transforms to remove noise for accurate signal recovery. The proposed research is aimed at developing multidimensional wavelet denoising for multi-frequency 2D-ESR signals at SNR ~ 1, extending the 1D wavelet denoising approach. Wavelet transforms provide a powerful approach to remove noise as they focus on separating noise from the signal, an active subject in the field of signal processing. The methods will include multi-dimensional representation of signals, development of new wavelets, enhancement in signal resolution in the wavelet domain, and development of noise thresholds based on well-defined statistical theorems, all of which will contribute to separate noise from signals. A new criterion will also be developed and adopted to quantify noise and uncertainty. The new denoising methods will be applied to reveal conformational dynamics of a well-characterized T4 Lysozyme protein and to understand lipid-transmembrane interactions ranging from 𝑛𝑠 to tens of 𝜇𝑠 time scales at physiological temperatures and concentrations for understanding signaling pathways related to diseases. This will lead to a detailed understanding of protein dynamics at the time scale of exchange between conformational substates and will create a platform for which motions of biological complexes can be studied, which currently remains elusive and are of key functional importance. Measurement of exchange rates under physiological conditions is a new experimental frontier and lifetimes in the range of 𝜇𝑠 are anticipated. It will also lay the foundation for using data processing methods to remove noise from experimental signals and permit their application during data acquisition for real-time processing. Data processing methods are inexpensive, easy-to-implement, and easily scalable to existing instruments.

NIH Research Projects · FY 2026 · 2023-09

ABSTRACT Low-income rural youth face economic and social factors that may negatively impact health, and challenges in accessing health care. School-Based Health Centers (SBHCs) are an innovative response to increase access, but their impact in rural communities is not well documented. This project proposes a multilevel mixed-methods evaluation of an SBHC network operating in 4 low-income rural counties in New York state. Run by the Bassett Healthcare Network, these SBHCs are permanent, on-site, year-round and attend to the full range of healthcare needs (physical, dental, mental, chronic and acute) at no out-of-pocket cost to patients. The setting permits a quasi-experimental design to assess SBHC impact by comparing 16 school districts with SBHCs and 22 school districts without. The project involves a multi-disciplinary team of Cornell University and Bassett researchers and community partners. The project will use both qualitative data (from semi-structured interviews and focus groups) and quantitative data (administrative data, survey, and patient healthcare visit data) and multilevel analytical methods to address three aims: Aim 1. Assess the impact of SBHCs on healthcare utilization. We will assemble a panel dataset of all patient visits to Bassett healthcare facilities over 12 years (2011-2022) to measure healthcare utilization (frequency, location, services) for preventive care (well-care, vaccinations) and care for acute and chronic conditions ( asthma, mental health) among children in school districts with and without SBHCs. Aim 2. Assess the impact of SBHCs on cross-agency collaboration. We will assess provision of social services in the 4-county study area through document research, focus groups, interviews with school and community leaders, and a survey of agency leaders. We will identify and measure factors that differentiate the level of cross agency collaboration among healthcare providers, community agencies, and local governments for each school district. Aim 3. Assess the impact of SBHCs and cross-agency collaboration on school performance and on community healthcare utilization. Combining data from multiple levels (patient, school district, and county) will enable us to assess the different roles SBHCs play in improving health. Community outcome measures include school attendance and broader community healthcare utilization. Study results will enhance understanding of how SBHCs may shape health outcomes and contribute to individual and community wellbeing to inform rural health policy.

NIH Research Projects · FY 2025 · 2023-09

Osteoarthritis (OA) is a joint disease and the major cause of disability in the adult population. Joint pathology includes disruption of normal cartilage morphology, changes in the underlying subchondral bone properties, and induction of osteophyte formation at the joint margins. Traumatic joint injuries such as meniscus and ligament tears or articular cartilage damage increase the susceptibility of developing a specific type of OA, post-traumatic arthritis (PTOA). The association of PTOA with a joint injury provides a well-defined event after which to intervene and attenuate or inhibit subsequent OA initiation and development. In addition to cartilage damage with PTOA, progressive changes to subchondral bone develop that initiate with bone resorption and loss, suggesting that targeting bone could prevent early-stage PTOA. We have developed a non-invasive model that induces OA with repetitive loading and PTOA with a single dose of loading applied to the mouse knee. In our preliminary data with this OA model, intermittent parathyroid hormone (iPTH) was beneficial to joint tissue health in adult male mice, even when iPTH treatment was followed by 6 weeks of damaging daily loading. Using the PTOA model, we found that load-induced joint damage was attenuated when bone remodeling was inhibited immediately after traumatic loading. Based on these intriguing results, we hypothesize that intermittent PTH treatment will inhibit the development of PTOA pathology in the joint. We propose to test this hypothesis using our load-induced PTOA model in three specific aims: (Aim 1) To attenuate load-induced tissue morphological damage and cellular responses after a single bout of damaging in vivo loading with delayed iPTH treatment in adult male and female mice; (Aim 2) To demonstrate that pain is reduced, joint function maintained and neuroimmune mechanisms modulated with iPTH treatment immediately or delayed 2 wks after a single bout of damaging in vivo loading to initiate PTOA in adult male and female mice (Aim 3) To identify altered neuroimmune gene expression is correlated with reduced tissue damage in cartilage, synovium and bone from adult male and female mice treated with iPTH immediately after a single bout of in vivo loading to initiate PTOA We expect that the beneficial effects of iPTH will be able to overcome existing tissue damage and modify PTOA disease progression with delayed treatment through bone anabolism and chondrogenesis. Our preliminary data demonstrate a role for specifically targeting the subchondral bone and cartilage using FDA- approved osteoporosis treatments in slowing OA progression. iPTH inhibition of cartilage and bone pathology following joint trauma will transform clinical practice.

NIH Research Projects · FY 2025 · 2023-09

1.0 Overall Abstract We propose the establishment of PORTENT – “Point-of-Care Technologies for Nutrition, Infection and Cancer for Global Health” centered at Cornell University in partnership with Columbia and McGill Universities. The recent Lancet Diagnostic Commission report states that the “diagnostic gap is most severe at the level of primary health care, in which only about 19% of populations in low-income and lower-middle-income countries have access to the simplest of diagnostic tests … People who are poor, marginalized, young, or less educated have the least access to diagnostics.” Developing PoC devices for these populations is challenging. The needs are unique, the users have disparate qualifications, the path to commercialization is different, the settings have variable infrastructure, the regulatory agencies have distinctive requirements, and the stakeholders are diverse. The PORTENT Center is unique as it (1) focuses on primary health care globally; (2) addresses the needs of the most vulnerable in the US and internationally; and (3) enables a broad range of diagnostic technologies to be validated on a global scale while simultaneously developing expertise and building capacity internationally to have the most impact even beyond the center. The center builds on our decades of international experience in validation, deployment, and commercialization of POC systems and incorporates clinical validation and satellite technology sites across four continents enabling testing on diverse populations and with a unique set of users. Our approach is fundamentally enabled by 5 key differentiable elements: (1) A rigorous approach to Needs Assessment through the establishment of an annual Global PoC Needs Assessment Consensus developed by a Needs Assessment Advisory Board; (2) The ability to validate PoC technologies on an exceptionally broad range of established populations and biospecimens in New York City, Ecuador, India, and Uganda; (3) The establishment of a “Lab-to-Market accelerator for Global Health Point of Care Technologies” to provide commercialization and tech-to-market support for PORTENT projects; (4) Unique training opportunities and knowledge transfer workshops for healthcare workers in LMICs on the use of PoC devices and clinical rotations at our international sites for PoC developers; (5) Access to the team’s network of industrial partners, diagnostics companies, regulatory experts, venture capital groups, and domestic & international non-governmental organizations. Illustrative of what we will fund through PORTENT, we describe four “Year 1” projects that (1) enable early screening of cervical cancer, (2) determination of iron status enabling anemia screening, (3) combined HIV and multiplexed detection of sexually transmitted diseases, and (4) broader, cheaper, and more accurate malaria testing. By the end of year 5, PORTENT will: initiate 20 independent PoC technology projects (with 30% from outside US), engage ~ 15 teams in the Global Health Lab-to-Market accelerator program, train 30 health care workers from LMICs on use of PoC technologies, and provide >20 clinical rotations for technology developers.

NIH Research Projects · FY 2025 · 2023-09

PROJECT SUMMARY We recently discovered an unexpected and intriguing role for white adipose tissue (WAT) in breast cancer. Our past studies identified that the mechanical properties of WAT extracellular matrix (ECM) regulate tumor cell invasion, a key rate-limiting step of metastasis, and that these properties are altered in obesity, contributing to the increased prevalence and worse prognosis of breast cancer in obese patients. Now, recent preliminary data from our labs additionally suggest that adipocyte mechanical properties may be similarly important. However, how adipocyte mechanics change with obesity and which effect these changes have on ECM remodeling and tumor invasion remains largely unclear. Understanding these connections is important for several reasons: First, while the biochemical functions of WAT are widely known to contribute to the pathogenesis of breast cancer, the influence of WAT mechanical properties on breast cancer invasion is largely unexplored. Second, our preliminary data suggest that aberrant remodeling of WAT in obese individuals promotes breast cancer invasion due to adipocyte lipid loss, transdifferentiation into myofibroblasts, and consequential changes in ECM deposition all of which affect WAT mechanics. Last, our preliminary results also indicate that tumor-induced lipid loss may synergistically promote invasion by changing WAT mechanical properties and tumor cell metabolism. Elucidating how these parameters are interconnected will be critical to decrease breast cancer burden and requires computational methods to uncover how single-cell properties of adipocytes and tumor cells affect WAT mechanics and tumor cell invasion. Through three focused and complementary Specific Aims, the proposed work iteratively couples computational models of tumor cell invasion into WAT, materials characterization of adipocytes and ECM, engineered cell culture models, and transgenic mouse models that allow visualization and manipulation of WAT in the mammary gland. Furthermore, single cell and spatial RNA transcriptomics, coupled with advanced bioinformatics approaches and human specimens, will determine the associated molecular mechanisms and potential value to patient prognosis. In particular, we will (1) define WAT physical properties in the breast as a function of obesity and determine their effect on tumor invasion, (2) determine the synergistic effect of tumor-induced lipid loss on WAT physical properties and tumor cell metabolism, and (3) establish the molecular basis of tumor-induced lipid loss in lean versus obese adipocytes and determine their effect on WAT physical properties and tumor invasion. These studies will identify specific obesity-dependent changes in WAT mechanical properties and their associated molecular mechanisms that will help predict the risk of breast cancer invasion for a given patient based on histological analysis.

NIH Research Projects · FY 2024 · 2023-09

PROJECT SUMMARY/ABSTRACT The DNA damage sensor kinase ATR is essential for human cell viability and plays a crucial role in cell tolerance to DNA replication stress1–3. Cancer cells often feature elevated levels of replication stress due to oncogene action and are therefore susceptible to inhibitors of ATR, making ATR a prime target in anti-cancer therapies4–7. While ATR inhibitors have been shown to be particularly effective in combination with replication stress-inducing agents, the molecular mechanisms behind these drug synergies remain poorly understood, primarily due to the sheer complexity of the ATR signaling network5,8–11. To uncover the signaling events that underlie these therapeutic synergies, I will utilize mass spectrometry to perform both unbiased and targeted phosphoproteomic screens in cancer cells lines treated with different chemotherapeutic agents shown to synergize with ATR inhibitors. Pilot unbiased screens I conducted in HCT116 cancer cells have begun to identify and quantify ATR signaling in response to chemotherapies CPT and Olaparib, allowing each response to be barcoded for direct comparison. Comparing pilot barcodes revealed dramatic differences in ATR signaling induced by each drug, also raising questions regarding whether such ATR signaling varies further between cancers resistant to these chemotherapies8,12. Moreover, when investigating CPT-induced ATR signaling, we uncovered a set of non- canonical signaling events that are independent of DNA resection, a process required for the activation of canonical ATR signaling1,13. These non-canonical signaling substrates include proteins involved in the dissolution of R-loops: DNA:RNA hybrids that increase in abundance upon CPT treatment and contribute to genome instability14–16. Faced with these data, I hypothesize that ATR signaling varies between drug treatments and cancer cell types, and that non-canonical ATR signaling contributes to CPT resistance via regulation of DNA:RNA hybrid processing. I aim to expand signaling barcodes for CPT and Olaparib-induced ATR responses several fold via scaled up phosphoproteomic screens, curating a synthetic peptide library from events uncovered. This library will enable high-throughput targeted barcoding of ATR signaling responses across cancers differentially resistant to CPT, Olaparib, and ATR inhibitor combination therapy, allowing for correlation of chemotherapy resistance with cancer-specific ATR signaling. I also aim to investigate the role of novel resection-independent ATR signaling events in cancer resistance to CPT by using genetic, biochemical, and cell biological techniques. Overall, results will delineate drug- and cancer-specific ATR responses and establish the contribution of a new mode of ATR signaling to chemotherapy outcomes. Generated knowledge will serve as a framework for systems-wide dissection of the mechanisms underlying ATR inhibitor chemotherapeutic synergies and resistances, potentially revealing drug targets and opportunities for more selective combination therapies.

NIH Research Projects · FY 2025 · 2023-09

Project Summary With increasing age comes age-associated declines in cognitive and everyday functioning, a greater propensity for illness, and the onset of disorders such as mild cognitive impairment (MCI) and Alzheimer’s Disease Related Dementias (ADRD). People with MCI are at a high risk for developing dementia and thus interventions are needed to improve or maintain current levels of function or delay further cognitive decline, as well as to improve the quality of life among those with MCI. VR-based approaches are portable, adaptable, and cost-effective, which offers enhanced access compared to outpatient treatments. In addition to demonstrating efficacy, another crucial goal of intervention research is developing an understanding of “how and why” interventions work. Insufficient understanding of the underlying principles or the mechanisms of action of interventions impedes implementation. As such, the goal of the proposed work is to generate and test a VR- based intervention to improve the wellbeing and quality of life of older adults with MCI while simultaneously untangling the intervention’s hypothesized mechanisms of action and moderators of intervention success. This project is highly innovative as it is using a VR-based delivery method and harnesses the human capital of older individuals seeking volunteer experiences to engage in meaningful social and cognitive engagement with other older adults with MCI as intervention partners. The inclusion of volunteers will also provide meaningful experiences for the volunteers and enhance the scalability of the intervention. The activities of this Stage I behavioral intervention project will include the generation of a new VR intervention (through the refinement of VR modules that we have already developed along with the creation of new modules), the development of instructional materials to train community interventionists (older adult volunteers), and the preliminary testing of intervention efficacy. The intervention development will apply a user-centered iterative design approach to generate and evaluate the Social Engaging Restorative Virtual Environment (SERVE), which will provide older adults with MCI an opportunity for social interaction through a variety of social and cognitively engaging collaborative activities within their own homes. The intervention will pair MCI individuals with non-impaired older adult volunteers. MCI participants and volunteers will interact remotely within a shared virtual space and productively engage and collaborate in shared activities. We hypothesize, based on empirical research and theoretical models of aging, that SERVE will increase perceived social support among the older adult participants with MCI, and that increases in perceived social support will reduce loneliness, improve wellbeing, and enhance quality of life. Our pilot data and a growing body of research literature suggest that perceived spatial presence within the VR environment will be an important moderator of intervention success.

NIH Research Projects · FY 2025 · 2023-09

PROJECT SUMMARY/ABSTRACT Advances in technology are enabling the collection of massive datasets of millions of human genomes. The long-term vision underlying this proposal is to leverage modern datasets and machine learning (ML) to under- stand how genetics and the environment determine traits and outcomes important to improving human health. Modern ML thrives on vast datasets of millions of unstructured datapoints (genomes, clinical notes, images), and stands to greatly impact statistical genetics, the field which studies the genotype-phenotype link. Improve- ments in statistical genetics have in turn the potential to elucidate the genetic basis of disease and support per- sonalized medical therapies. This proposal advances the above vision via two thrusts: (1) developing novel machine learning (ML) algo- rithms motivated by problems in statistical genetics; (2) creating open-source software systems for scientists and clinicians based on the above algorithms. Specifically, we describe a plan for the development of computa- tional methods in three broad areas in statistical genetics: modeling linkage disequilibrium and the structure of genetic variation, analyzing genome-wide association study data, and predicting risk from genetic and environ- mental factors. Within in each area, we aim to develop open-source software for key applied problems includ- ing genetic imputation, haplotyping, low-pass sequencing, causal variant identification, and risk scoring. Our research seeks to establish a foundation for statistical genetics based on modern ML and also advance ML in directions that may not be pursued in other application domains. Our methods will support technologies that have immediate applications in healthcare and that help reveal novel genetic factors that influence dis- ease; improve the accuracy of genomic prediction in domains from preventive medicine to pharmacogenomics; significantly reduce the cost of genomic sequencing assays, and ultimately improve human health.

NIH Research Projects · FY 2024 · 2023-09

Abstract The goal of this project is to develop a novel bifocal catadioptric objective that will allow large-scale recording of neural circuits in vivo. The objective will enable faster volumetric imaging of large brain regions by simultaneous two-photon (2P) imaging of shallow layers and three-photon (3P) imaging of deep layers of brain tissues with improved collection efficiency. Although three-photon microscopy (3PM) allows imaging at depths inaccessible by two photon microscopy (2PM), 2P excitation generates larger fluorescence signal with lower excitation pulse energy when imaging at shallow tissue layers. Therefore, for fast imaging across a large depth, the optimum approach is to use 2PM for the superficial layers and 3PM for the deeper regions simultaneously. Implementation of this approach inevitably requires the objective lens to generate two focal planes that are separated by a large axial distance while still maintaining high spatial resolution and large field of view. Simultaneous 2PM and 3PM will not only allow for utilization of the advantages of both modalities but also for faster volumetric imaging of large brain columns. We will develop a bifocal catadioptric (i.e., both refractive and reflective) lens based on the idea of separation the optical paths of the excitation light with different wavelengths. The lens will feature two focal planes separated axially by ~ 600 µm for the 2P (< 1100 nm) and 3P (>1200 nm) excitation wavelengths. The design approach also separates the excitation path and the collection path and allows independent optimization for efficient collection of the emitted fluorescence. The bifocal objective will collect fluorescence back through non-imaging pathways, which enables the proposed catadioptric objective to have a large collection numerical aperture and a large collection field of view. The collection efficiency is approximately 5x higher than the commercially available objective lenses when imaging deep (>1 mm) into the mouse brain. Improving the signal collection efficiency will immediately increase the frame rate without increasing the excitation power, enabling high-resolution, high-speed imaging at these depths. We will design, fabricate and validate the novel objective lens and will combine it with focus-tunable lenses to enable faster volumetric imaging of mouse brains. The successful completion of this program will immediately enable simultaneous 2P and 3P imaging across a large range of depth (~ 1.2 mm), such as recording population of neurons across different layers of mouse brains. The technology developed within this program will have potential impacts in a large number of biomedical fields such as neuroscience, immunology, and cancer biology.

NIH Research Projects · FY 2026 · 2023-08

ABSTRACT Racial/ethnic minority populations in the United States face pervasive disparities in health care access, utilization, and outcomes. Access to transportation is an important factor that has the potential to affect access to care. Past work has found that improved transportation has significant impacts on both health care utilization and outcomes. Little is known, however, about the extent to which the Medicaid non-emergency medical transportation (NEMT) benefit is associated with racial/ethnic disparities in health care access and outcomes. The long-term goal of the proposed research is to determine how transportation services and related policy are related to health care disparities in the United States and can be used to improve access to care. The overall objective of this project is to provide evidence for state and federal policymakers on who uses the NEMT benefit, how use and disparities in use correlate with state-level NEMT program design, how eligibility and use correlate with patient outcomes, and how to ensure meaningful transportation to access care. The central hypothesis is that use of the NEMT benefit, and the association between use and health care access and outcomes, vary substantially by race/ethnicity and across beneficiary populations, as a function of discrete features of states’ NEMT policies and administrative requirements. These hypotheses will be tested by pursuing three specific aims: (1) examine racial/ethnic disparities in beneficiary-level NEMT utilization across states and assess the correlation between observed disparities and state-level NEMT policies; (2) estimate the association between use of and eligibility for the NEMT benefit and health care access and outcomes, as well as heterogeneity in this association by race/ethnicity; and (3) investigate the process of NEMT benefit administration and use of NEMT to identify potential ways to improve the program. Methodologically, the project will employ rigorous quasi-experimental approaches, including difference-in-differences analyses, as well as semi-structured interviews with Medicaid beneficiaries, health care providers, and transportation providers. The proposed research is innovative, in the applicants’ opinion, because it fills critical gaps on the potential for the NEMT benefit to reduce health care disparities in the United States using quantitative findings from a large, multi-state data source paired with in-depth, qualitative research. It also relies on a multi-stakeholder advisory board composed of Medicaid beneficiaries, policymakers, clinicians, and transportation providers to inform the research design and maximize translation to policy. The project is significant because it will provide actionable guidance for state and federal policymakers on how to optimize the design of the NEMT benefit to improve access to medical care in the United States.

NIH Research Projects · FY 2024 · 2023-08

PROJECT SUMMARY Over 40% of adult women in the U.S. are obese and obesity will soon overtake smoking as the leading risk factor for cancer. For breast cancer, obese women demonstrate both a higher incidence and higher rate of cancer- related mortality compared to normal weight women. While many studies focus on potential systemic connections behind this observation, the breast is rich in white adipose tissue (WAT), which is highly remodeled in the context of obesity, and thus local tissue-resident cues must also be considered. At the cellular level, white adipocytes are the functional units of WAT and secrete extracellular vesicles (EVs) that promote tumor progression. Recent studies indicate that adipocyte-derived EVs contain lipids and other metabolites for fatty acid oxidation that modulate tumor cell metabolism to increase migration, proliferation, and chemoresistance. In obese individuals, adipocytes become hypertrophic with known consequences for metabolic disease. Whether adipocyte hypertrophy similarly impacts breast cancer risk and prognosis is less clear. Preliminary data in this proposal indicate that hypertrophic adipocytes promote the proliferation and migration of co-cultured tumor cells to a greater extent than donor-matched, non-hypertrophic control adipocytes. Moreover, I found that hypertrophic adipocytes secrete more EVs and exhibit remodeled cortical actin. Given that the actin cytoskeleton mediates the biogenesis of EVs by other cell types, this proposal aims to investigate if hypertrophy, remodeled cortical actin, and increased EV secretion are interconnected. Moreover, the proposed research also aims to discern if these differences impact breast cancer progression by altering tumor cell metabolism. In Specific Aim 1, I will characterize the concentration, size distribution, and cargo of EVs released by hypertrophic vs. control adipocytes via nanoparticle tracking analysis and mass spectrometry. In Specific Aim 2, I will expose breast cancer cells to EVs secreted by hypertrophic vs. control adipocytes to assess how treatment impacts tumor cell behavior in vitro and in vivo. Moreover, I will perform pharmacological and genetic inhibitor studies to determine if altered fatty acid oxidation underpins any observed differences in tumor cell phenotypes. Collectively, this work will help discern if hypertrophic adipocytes constitute a distinct subpopulation of cells conducive to tumor progression and thus contribute to the poor prognosis of obesity-associated breast cancer. In the clinic, identified molecular mechanisms between adipocytes and tumor cells could be targeted therapeutically and the degree of mammary adipocyte hypertrophy could serve as a prognostic biomarker for patient outcomes. Beyond research, I will develop skills around experimental design, data analysis, mentorship, and science communication through my training goals and team of mentors outlined in this proposal. These skills will be essential to achieve my long- term professional goal of becoming an independent investigator at a research-focused institution.

NIH Research Projects · FY 2026 · 2023-08

Project Summary/Abstract Phosphatidic acid (PA) is a multifunctional signaling lipid and central biosynthetic intermediate that is subject to strong homeostatic regulation, with its levels tightly controlled in space and time. Though many PA- metabolizing enzymes and PA transporters are characterized, it is not well understood how cells sense changes in PA levels and how homeostasis is achieved. To both elucidate mechanisms underlying the spatiotemporal regulation of PA metabolism and reveal a broader spectrum of effector proteins that propagate PA signaling, we posit that new strategies to rapidly perturb PA levels with organelle-level precision are required. We have begun to develop precision “membrane editing” tools for the rapid installation of physiologically active pools of PA on target organelles. An optogenetic phospholipase D (optoPLD) uses blue light to recruit a bacterial PLD to desired organelle membranes, where it generates transient pools of PA via phosphatidylcholine hydrolysis, and recent directed evolution efforts have yielded second-generation, super-active optoPLDs (superPLDs). The combination of superPLD-mediated membrane editing and organelle membrane proteomics via proximity biotinylation using a membrane-tethered TurboID, which we term a “feeding and fishing” (F+F) strategy, has afforded us a global view of rapid changes to the integral and peripheral membrane proteomes of the plasma membrane during conditions when its lipidome is edited using superPLD to transiently elevate PA levels. Beyond detecting known regulators of PA metabolism, we identified and validated new candidate proteins for sensing, transporting, and signaling the presence of PA in these membranes. Yet, several critical issues remain unaddressed, related to both method development and mechanistic understanding of hits from our screens. The overall objective of this proposal is to deploy new optogenetic and proteomics tools to understand how cells establish and maintain functionally distinct PA pools in different locations to balance biosynthetic and signaling needs. First, we will develop ultralow-background, next-generation optogenetic PLDs and apply them to elucidate roles for PA in mediating crosstalk between two major cell signaling pathways and discover new regulators of PA homeostasis. Second, we will elucidate roles for a new player implicated in the interorganelle transport of PA using a combination of cellular and in vitro studies. Third, we will elucidate the molecular details and functional importance of the interaction of PA with a newly discovered PA-binding protein whose mutation causes a heritable musculoskeletal disease. Collectively, our studies will yield widely useful tools for membrane editing and deciphering PA signaling and establish a mechanistic framework for understanding how cells exert spatiotemporal control over the levels and bioactivity of a pleiotropic lipid to maintain homeostasis and direct specific physiological and signaling events.

NIH Research Projects · FY 2025 · 2023-08

SUMMARY Across the biomedical sciences there has been an increased recognition that many key questions in these fields require phylogenetic thinking and approaches. My group has a very strong track record of making fundamental methodological contributions that have changed how biologists think about and analyze phylogenetically structured data and of finding new applications for these methods. My group’s current research is focused on two main themes, both related to the evolution of genomic function. First, we will use phylogenetic comparative approaches to investigate the dynamics of gene expression evolution across species. We will first assess the appropriateness of adopting phylogenetic models of phenotypic evolution for describing changes in gene expression using an approach we have previously developed. This will enable us to assess the robustness of findings regarding the relative importance of different evolutionary processes in generating interspecific diversity and help us develop the next-generation of models, specifically tailored to functional genomic data. We will then build a mechanistic model that will allow us and other researchers to test for associations between gene expression evolution and sequence evolution in the promoter regions. Second, we will study the evolution of Immunoglobulin genes, which encode the unique antigen recognition sequences of B cells, which produce antibodies. We will investigate this at two nested levels: the evolution of the B cell repertoire over time and in response to pathogens and the evolution of the germline Immunoglobulin genes. To examine changes in the B cell repertoire, we will adopt approaches that our research group has pioneered in the context of macroevolution, to characterize the dynamics of the system. We are specifically interested in estimating the rate of somatic mutation and the number of distinct clonal lineages that are expanding in response to an infectious disease. There is accumulating evidence that variation in the evolved response of B cells is associated with inter-individual variation in the germline Immunoglobulin genes. However, the underpinning mechanism remains unclear as do the reasons there appears to be so much diversity at these loci across individuals. We will derive an evolutionary model, and parameterize it using comparative genomic data, to evaluate the plausibility of alternative hypotheses for explaining both of these observations.

NIH Research Projects · FY 2024 · 2023-08

Project Summary/Abstract Arterial blood pressure (BP) and pulmonary arterial pressure (PAP) are fundamental for diagnosis and management of both systemic and pulmonary hypertension and for monitoring of surgical and critically ill patients. Systemic hypertension is the most common modifiable risk factor for cardiovascular disease and the leading contributor to mortality and disability in the world. Pulmonary hypertension is a group of pulmonary vascular disorders leading to increased PAP, right ventricular failure, and death. It is also common in the intensive care unit. Diagnosis of pulmonary hypertension remains challenging. Arterial BP is most commonly monitored with the non-invasive cuff-based sphygmomanometer, which only outputs brachial systolic and diastolic BP, differs from the critical central BP, and is prone to errors in the presence of arrhythmias. Instead of providing a continuous measurement, its BP values are averaged over many pulses. Invasive catheterization allows for direct arterial BP monitoring, but the technique is not risk-free. Noninvasive estimates of PAP from echocardiography, computed tomography (CT) scan and magnetic resonance imaging (MRI), although useful, remain variable and operator-dependent. Therefore, right heart catheterization is still the gold-standard diagnosis for PAP and pulmonary hypertension, despite being highly invasive. Monitoring of PAP at home or primary care is currently unfeasible. The overarching aim of this proposal is to evaluate whether a non-invasive radio-frequency (RF) sensor can retrieve central BP and PAP transients accurately and non-invasively. We hypothesize that the near-field coherent sensing (NCS) by RF carriers, which has been benchmarked on heartbeat and respiration waveforms with the gold-standard devices, can also be applied to derive central BP from the vibration characteristics of the aorta and pulmonary arteries in the entire cardiac cycle. The principle of operation is similar to that of the ground penetrating radar and air-puff tonometry, where Hilbert-Huang Transforms and machine learning can be adapted for BP signal processing. Our effort will start from building a phantom heart model, which will allow direct pumping control and host the NCS and catheter-based pressure sensors. We will also explore the multiple-input-multiple-output (MIMO) NCS to improve the local mapping of vibration characteristics. We will use anesthetized pigs as animal models for aortic BP and PAP studies, where similar sensors from the phantom will be deployed. The accuracy of the sensors and their ability to track changes in relation to the gold-standard pressure catheters will be benchmarked. Aortic BP studies will be modified by infusion of inotropes and vasopressors, while PAP by acutely changing the fraction of inspired oxygen (FiO2) and by inducing surfactant depletion followed by lung recruitment. Additionally, electrocardiogram (ECG) and photo-plethysmography (PPG) will be synchronized on the animals to investigate whether noninvasive calibration of the NCS BP readout can be realized.

NIH Research Projects · FY 2025 · 2023-08

Summary Phages are the natural viral predators of bacteria and are harmless to humans. The phages’ ability to recognize, bind, infect, and lyse host bacteria has led to their use as sensors for their hosts. Phages can be genetically engineered to express reporter proteins during the infection of their host, resulting in the release of the reporters following the lysis stage of infection. Our central hypothesis is that advanced methods in synthetic biology and genetic engineering will allow phages to be genetically optimized to perform as a dedicated nanobiosensor, and that phage-based assays can deliver genetic-level specificity of their host through reporter selection and optimization. The objective of this proposal is to use synthetic biology to abate current weaknesses identified for phage-based biosensing. The rationale for the proposed research is that while several weaknesses have been proposed for phage biosensors, advances in bioengineering and synthetic biology can provide solutions to address them. These issues include a lack of specificity within a species and a need for increased sensitivity. By mitigating these issues, phage-based sensors can be used to sensitively detect bacterial genetic sequences (e.g., pathogenicity and antibiotic resistance genes) with rapid results, low-cost, and minimal reagent storage conditions. Aim 1: Bioengineering phage infections for maximal reporter protein expression. Our working hypothesis is that the T4 infection conditions can be engineered to maximize the expression of reporter protein by optimizing lysis time and deleting genes non-essential for reporter expression on the phage genome. We will test the working hypothesis by engineering T4 phages with nonessential and structural protein genes deleted/silenced and complemented on a plasmid for propagation. Our expectation is a significant improvement in the limit of detection when used to detect wild type E. coli. Aim 2: Phage-enabled Recombinase Polymerase Amplification (RPA). Our working hypothesis, based on preliminary work, is that T4 phages bioengineered to have genes for RPA proteins can enable the genetic amplification of their host bacteria DNA following phage- induced lysis. To test the working hypothesis, we will genetically engineer the phage T4 with the genes for RPA- required proteins which will be expressed during infection of the bacterial host. Our expectation is that the post- infection lysate mixed with specific primers will allow detection of E. coli with genetic specificity. Following successful completion of the specific aims, the expected outcome is development of a suite of technologies which can bring phage-based biosensing across the technological “valley of death” and towards further application and commercialization. Phages, which allow rapid and low-cost detection of bacteria, suffer from a lack of specificity within a species. We will have demonstrated a method to significantly improve the expression of reporter proteins and a method to provide genetic level specificity while maintaining the overall benefits of phage-based detection (e.g., low-cost, rapid analysis, minimal reagent storage, bacterial lysis).

NIH Research Projects · FY 2024 · 2023-08

PROJECT SUMMARY Surface-associated microbial populations are ubiquitous in nature and display evolutionary dynamics that are not yet well characterized, despite their importance to human health and technology. Genetic drift, the change in allele abundances due to chance alone, is known to be much more important in the surface-associated scenario than for microbes in well-mixed liquid media, but it is unknown which properties of cells and populations modulate this effect. I performed an evolutionary range expansion experiment with the budding yeast, Saccharomyces cerevisiae, to investigate how cells evolve when selected for more efficient surface-associated growth. We found that cells selected for faster expansion on surfaces evolved an elongated cell shape and a bipolar budding pattern, in which daughter cells bud at the pole opposite to the birth scar. Additionally, preliminary results suggest that evolved colonies display increased genetic drift compared to the ancestor. This proposal aims to understand the genetic changes that caused these phenotypes, and how these phenotypes modify the physical parameters of the system to enable faster expansion. Further, I will use this information to understand how properties of single cells affect the relative strength of natural selection and genetic drift in dense cellular aggregates. I hypothesize that the faster expansion is the result of evolved changes in physical properties of the colony that modify the way cells interact with each other and the agar surface. Additionally, I hypothesize that an elongated cell shape contributes to an increased strength of genetic drift in surface-associated growth. I will address this hypothesis by identifying the genes that cause each evolved phenotype, characterizing the physical properties of colonies and cells that affect expansion dynamics and three-dimensional colony structure, and finally use this information to assess the effect of each phenotypic change on the relative strength of genetic drift in expanding colonies. Completion of these goals will ensure I have developed expertise in both theoretical and experimental approaches pivotal to independent biophysical research with health-related applications, a major goal of my fellowship training plan. My training plan also includes training in scientific communication and inclusive teaching and mentorship. I will benefit from the significant resources granted to me by Cornell in the way of on-site, state-of-the-art research facilities, collaboration with experts specific to all fields represented in my research, and a wonderfully supportive research advisor, the sponsor of this work.

NIH Research Projects · FY 2025 · 2023-08

ABSTRACT (30 lines) It is well established that the increasing lifespan in the US is leading to increased prevalence of brain diseases and mental illnesses, with dementia and Alzheimer’s posing significant challenges to the healthcare system. Because brain Positron Emission Tomography (PET) is a powerful noninvasive tool for clinical studies and research on fundamental mechanisms of brain maladies and metal disorders, it is expected to play an important role in addressing this challenge. However, current brain PET technologies are limited with relatively low sensitivity and low spatial resolution, constraining its usefulness in this context. Consequently, there is a critical need to improve quantitative imaging performance of brain PET. To address this need, we propose to develop advanced detector modules and associated algorithms, leveraging in particular recent progress in time-of-flight (TOF) detector technologies. These modules will lay the foundation for a follow-on project to develop an ultra-high-performance dedicated whole-brain TOF-PET camera (BRAIN PET EXPLORER) for research and clinical work. This device will overcome the current technology shortcomings by providing substantial gain in effective sensitivity and much higher spatial resolution imaging over the most current advanced brain PET system (NeuroEXPLORER commissioned in 2022). The crucial factor for improved performance of TOF-PET is better coincidence time resolution (CTR - time difference between arrival of the two annihilation photons) enabling accurate localization of the annihilation event a line-of-response. Our research is innovative because the goal of this proof-of-concept proposal is to build and demonstrate these novel and advanced thin-slab TOF-PET detector modules, and establish their suitability for scale up in a full BRAIN PET EXPLORER (future work). These detector modules will establish CTR <100 ps FWHM performance, enabling an 8× gain in effective sensitivity and outstanding 3D event localization (compared to the current state-of-art scanners) at reduced cost. An additional factor of up to 2× boost in effective sensitivity is expected to be achieved by accurate determination of the point-of-first-interaction for annihilation photons that undergo Compton scatter between detector blocks. The overall > 8× increase in the effective sensitivity can be used to reduce the activity of radiotracer administered to the patient, reduce the examination duration, increase spatial resolution, or increase the temporal resolution in dynamic brain-PET imaging. All these factors will make the brain-PET a more useful, cost-effective and affordable research and clinical tool. The advent of such innovative brain PET technology will help address growing prevalence of brain diseases and mental illnesses facing the aging population of the US. 2

NIH Research Projects · FY 2026 · 2023-07

PROJECT SUMMARY Eukaryotes have evolved complex signaling networks that assess internal energy and nutrient stores and respond to the available nutrients. In humans, inaccurate nutrient sensing can result in type II diabetes and obesity. Unfortunately, the therapeutic targets available to treat these diseases are limited. Cancer progression is promoted by changes in metabolism, since rapid growth of tumors is mediated by dysregulation of carbon, nitrogen, and phosphate utilization. A key knowledge gap is understanding how eukaryotic cells distinguish between available nutrients and integrate signals from diverse nutrient sensing pathways. Filling this gap may identify targets for future diabetes, obesity, or cancer therapeutics. Many nutrient sensing pathways used as therapeutic targets in humans were originally identified in eukaryotic microbes. However, much of this work focused on the model yeast Saccharomyces cerevisiae, which has a limited nutrient utilization repertoire. Eukaryotic microbes that utilize a more diverse set of nutrients employ additional mechanisms of nutrient sensing conserved in humans. To characterize novel conserved nutrient sensing regulatory mechanisms, this project focuses on defining the nutrient sensing network by investigating genes that integrate signaling pathways and distinguish between nutrient sources in eukaryotic microbes with unique phenotypic outputs. In response to available nutrients, the filamentous fungus Neurospora crassa exquisitely tailors the regulation of secreted enzymes with easily measurable activity. The oleaginous yeast Rhodosporidium toruloides accumulates lipids when carbon is abundant and nitrogen or phosphate limiting. To investigate how signaling networks are integrated, this project will use the easily scorable phenotypes of these two atypical model fungi to focus on two questions: (1) the mechanism by which signals are integrated between nutrient sensing pathways and the p38 mitogen activated protein kinase pathway, which regulates both nutrient utilization and stress, to achieve downstream responses specific to differing stimuli; and (2) the genetic mechanisms that integrate signals from carbon, nitrogen, and phosphate pathways. Many conserved pathways that regulate nutrient utilization in humans play an important role in fungi, especially when cells must distinguish between preferred and nonpreferred nutrients. This project will characterize conserved genes, including three highly conserved kinases, that play a role in distinguishing between available nutrients in eukaryotic microbes. An innovative aspect of this project is using powerful genomic tools, including high-throughput functional genomics and multi-omics, in understudied eukaryotic microbe model organisms with substantial nutrient utilization repertoires. Working in these two distantly related organisms will identify conserved genes that may be important for nutrient sensing throughout eukaryotic species and serve as novel targets to treat metabolic diseases in humans. Conversely, regulatory mechanisms specific to one species may serve as therapeutic targets to mitigate deaths from fungal disease.

NIH Research Projects · FY 2024 · 2023-07

Meiotic recombination results in the formation of DNA crossovers (CO) that are critical for ensuring the correct segregation of homologous (maternal and paternal) chromosomes at the first meiotic division. Chromosome segregation errors show striking sexual dimorphism: In humans, 20-80% of eggs versus 2.5-7% of sperm are aneuploid, likely due in large part to errors in CO formation. Meiotic recombination is initiated by the formation of DNA double strand breaks (DSB) that are then repaired via various pathways to achieve a tightly regulated frequency and distribution of COs across the genome. These DSB repair events occur in the context of the synaptonemal complex (SC), a proteinaceous structure that forms along the chromosome axes, tethering homolog pairs together. SC length correlates strongly with CO number, and most studies in human and mouse report females have higher CO rates due to their longer SC length. Paradoxically, meiotic recombination in females is highly error-prone, implying critical sex differences in CO formation cannot be explained by a correlation with SC length. I hypothesize that sexual dimorphism in CO rates is the product of key differences in molecular features of meiotic prophase I, namely the factors that orchestrate meiotic recombination and chromosome axis assembly. Unlike common laboratory mice (e.g., B6) and humans, wild-derived PWD male mice have higher CO number despite their shorter SCs, challenging the dogma that CO rates are inextricably linked to SC length. Thus, I propose to address my hypothesis using mice from diverse genetic backgrounds to dissect the molecular and genetic factors underlying sexually dimorphic CO rates. In Aim 1, I will examine dynamic localization of meiotic recombination proteins in male and female PWD and B6 mice to elucidate how sexually dimorphic CO rates progressively manifest through prophase I. Using high resolution imaging methods, I will characterize the accumulation of critical DSB repair factors (including RAD51, RPA2, MSH4, RNF212, and MLH1) to pinpoint sexually dimorphic differences in CO regulation. In Aim 2, I will evaluate cohesin-mediated chromatin organization in male and female B6 and PWD mice. Using CUT&Tag to profile REC8 and RAD21L cohesin distributions, I will identify sex differences in cohesin axis assembly and how they correlate with early DSB repair intermediates. In Aim 3, I will use the recombinant mouse lines of the Collaborative Cross to map genetic loci associated with sex differences in CO number and SC length. Collectively, these studies will be the first to examine the molecular and genetic factors that influence sexually dimorphic CO rate and SC length in diverse mouse genetic backgrounds. Insights gained from this project will provide critical understanding of why recombination errors are more common in females. Over the course of this project, I will receive invaluable training in the use of super-resolution microscopy, computational analysis of genomics data, and quantitative genetics of complex traits. Along with career development mentoring, these skills will be critical to the development of my independent research program.

NIH Research Projects · FY 2026 · 2023-07

Project Summary The Wei Lab develops accurate and scalable inference methods in population genetics and statistical genetics. In the next few years, we will focus on understanding the evolution and genetic basis of complex traits. Large biobank datasets with hundreds of thousands of human genomes and tens of thousands of phenotypic measurements provide unprecedented opportunities to understand complex phenotypes. At the same time, these massive data sets demand more scalable and unbiased computational methods. My lab recently developed new algorithms and data structures to improve the scalability of standard computations involving genotype matrices, including the calculation of heritability components and linkage disequilibrium scores. Our RSHE method runs 10-100x faster than the current state-of-the-art method to allow heritability analysis on biobank-size whole-genome sequencing data. Further methodological improvements will require new conceptualizations of the genotype-phenotype relationships. Conventional statistical genetics uses genotype matrices directly, ignoring that genetic polymorphisms are organized by gene genealogy into an interpretable graph structure. Whole-genome genealogies can now be readily inferred using ancestral recombination graph (ARG) inference software. Studying genealogy-phenotype relationships on ARGs could pinpoint causal mutations, reduce multiple testing, promote algorithm efficiency, and integrate evolutionarily meaningful models. We are developing a scalable algorithm for ARG-wide association studies and will demonstrate its advantages even in the face of uncertainty in ARG reconstruction. We will also develop fine-mapping methods on ARGs to study homogeneous and admixed populations. Leveraging our RSHE code, we will implement a scalable method for estimating heritability from ARGs and will apply this new method to the UK biobank to understand why heritability estimated in unrelated individuals is lower than that from pedigree analyses. Building upon this, we will implement a novel model parameterization to study complex trait evolution using ARGs. Current polygenic adaptation papers all inevitably assume that GWAS significant SNPs can be treated as causal variants and that different polygenicity levels across phenotypes can be ignored. Our proposed method will provide the first rigorous framework that takes these factors into account. In summary, this proposal will develop methods to fully integrate ARGs into statistical genetics to better understand and conceptualize phenotype-genealogy relationships. It will provide more scalable computational tools for the field in response to the rapidly growing biomedical data and enable novel and more calibrated discoveries for human disease genetics and phenotypic evolution.

NIH Research Projects · FY 2025 · 2023-07

Project Summary Precision nutrition approaches aim to move away from a one-size fits all approach to identify individual-level dietary and nutritional intake for optimal health by accounting for individual variability in genes, phenotype, environment, and lifestyle for each person (NIH) – i.e., tailoring nutrition interventions and/or recommendations to individuals by accounting for the complex nutritional ecology reflecting the interaction of a complex system. The components of precision nutrition include assessments of a number of biological, clinical, social, and environmental parameters including the multi-omics, genomics, proteomics, and metabolomics, as well as account for sustainability. Approaches relying on Artificial Intelligence (AI) and machine learning (ML) are increasingly being used across the research realm including in nutrition to analyze and interpret such complex data. The 2020-30 Strategic Plan for NIH Nutrition Research, developed by the NIH Nutrition Research Task Force, identifies a key need to produce a nutrition workforce that is trained to solve the most pressing problems in nutrition and health, by applying novel methods and working in multidisciplinary teams. We propose to leverage our existing strengths and initiatives at Cornell to implement a novel program to train the next generation of scientists in the domains of AI and precision nutrition to address the future needs for the nutrition workforce. The training program, with positions for 4 predoctoral and 1 postdoctoral trainees per year, is built on the outstanding doctoral programs in the multiple departments at Cornell University participating in this application, which emphasize multidisciplinary and integrative scholarship across the biological, physical, behavioral, data, and social sciences. The 23 trainers represent the broad range of disciplines necessary to achieve the goals of the training program and include renowned scientists with expertise spanning from nutrition, medicine, health, computing and information sciences, bioinformatics, population genetics, and computational biology. The trainers have active research programs and excellent training records. The proposed training program includes a core curriculum tailored for students starting in nutrition and minoring in computer science and for those starting in computer sciences and minoring in nutrition. We have also included plans for a new AI and Precision Nutrition course with hands on analyses that is already being put in place and will be ready for roll out in the next academic year. The infrastructure to support the proposed training program is outstanding, with added strengths from faculty members across the campus. Further, the new AI innovation hub at the Cornell Center for Precision Nutrition and Health will provide a unique opportunity for diverse trainees to come together and prepare the next generation of the nutrition scientific workforce.

NIH Research Projects · FY 2026 · 2023-07

Project summary/Abstract The Golgi complex plays a prominent role in secretory and endocytic trafficking in eukaryotic cells and is key to the biosynthesis of glycoconjugates (glycoproteins and glycolipids) that are essential for life. Golgi resident proteins, such as glycosyltransferases and sugar nucleotide transporters, are precisely distributed across the Golgi stacks by recycling mechanisms that counteract the flow of ongoing vesicular transport. Dysfunction in these mechanisms, or their hijacking by viruses and toxins, is known to have serious consequences for human health, leading to congenital disorders of glycosylation, cancers, and immune dysfunction. Membrane proteins residing in various Golgi compartments are well annotated; however, the mecha- nistic basis of how most Golgi proteins are selected for recycling, or how these processes are regulated are poorly understood. My lab is interested in uncovering these fundamental mechanisms governing Golgi homeostasis using a multifaceted approach combining genetics, flow-cytometry, imaging, in vitro reconstitution, and proteomics. In preliminary results, we have identified novel transmembrane compo- nents orchestrating recycling of specific subsets of Golgi enzymes. Our findings have opened doors for interrogating new players and dissecting the mechanisms critical to maintain Golgi identity and function. Over the next five years, our goals are to (1) identify novel recycling receptors required at different Golgi compartments and establish a systematic map of the intra-Golgi recycling network, (2) determine how the transmembrane receptors engage with their cargos, and (3) define the novel functions of a disease- associated membrane transporter in solute transport and protein recycling in the Golgi. The combined results of our experiments will elucidate how multiple recycling pathways sustain normal Golgi function, and how this homeostasis is disrupted in human disease.

NIH Research Projects · FY 2025 · 2023-07

The mission of this MSTP at Cornell’s College of Veterinary Medicine (CVM) is (i) to create a comprehensive veterinary clinician and scientist community to support and mentor Combined DVM-PhD Degree (CD) trainees along the axes of their personal interests, clinical discipline, and research domain; (ii) to provide integrated training in clinical veterinary medicine and biomedical research that prepares trainees to perform at the highest standards as rigorous clinician-scientists; (iii) to develop biomedical science leaders exhibiting creativity, curiosity, compassion, and service; and (iv) to develop skills for success in a broad range of veterinary clinician-scientist research careers through experiential learning. Towards this mission, we have established a flexible and vibrant CD training plan that strategically and uniquely pairs Cornell’s Doctor of Veterinary Medicine (DVM) curriculum with the graduate (PhD) program in Biomedical and Biological Sciences (BBS). The current Cornell CD program has a strong track record of ongoing success since its creation in 2002. Approximately 71% of our 24 CD graduates are in research careers (33% in academia, 17% in government, and 21% in industry). Incoming CD students will choose their PhD mentor, after their laboratory rotations, from a pool of 40 trainers (including 4 affiliate trainers) representing 8 research specialties with an average of $900,000 of research grant funding. Cornell is committed to providing all CD students, including MSTP trainees, full financial support (tuition, stipend, and health insurance) for all years during their CD programming. The training of CD students at Cornell is flexible. It typically starts with 1.5 years in the DVM curriculum, then switching to a 3- or 4-year long Ph.D., and finally returning to the remaining 2.5 years of DVM training. Of the current cohort of 15 CD students, including 2 newly admitted trainees, 6 (40%) hold prestigious predoctoral fellowships, including 5 NIH F30s. Key objectives for our MSTP are to: (1) Recruit and retain students, and grow an outstanding CD student cohort; (2) Develop biomedical science leaders with skills in major competency domains required for clinician-scientists, namely disciplinary knowledge combined with clinical, technical, operational, professional, and self-development skills; (3) Optimize DVM and PhD training integration and the combined time-to-degree through the temporal intermingling of DVM and PhD training, research during the DVM curriculum, and clinical training during the PhD curriculum; and (4) Expand opportunities for career development, both in academia and beyond academia, and enhance skills in communication, team-science, and entrepreneurship. Our overarching objective is to develop a comprehensive pool of well-trained veterinary clinician-scientists who have the disciplinary knowledge and skills that will uniquely prepare them for leadership roles in biomedical research to advance human health at the individual and population levels.

NIH Research Projects · FY 2026 · 2023-07

PROJECT SUMMARY/ABSTRACT Human genome is peppered with an estimated one million enhancers that can regulate their specific target gene(s) from a distance up to megabases away, and in an orientation-independent manner. The broad goal of this project is to define the fundamental architecture and function of human enhancers in a in-depth manner and to better understand the specificity of their interplay with different classes of promoters that use different transcription factors and/or are regulated at distinct steps in transcription. We have shown that enhancers can be identified and precisely mapped using our GRO/PRO-cap assay that map transcription start sites of nascent RNA with highest sensitivity of all available methods. This assay has shown that both enhancers and promoters share a common architecture whereby both are delimited by two divergent core promoters (CPs) and a central cluster of transcription factor (TF) binding motifs. The roles and required organization of the multiple sequence motifs that constitute enhancers and the two CPs need to be fully dissected to understand how active enhancers function. Additionally, enhancers can interact productively with specific promoters, and the basis of this specificity especially at long range remains ill-defined. Finally, we know that promoter and enhancer elements have sequence motifs that can act at distinct regulatory steps of the transcription cycle, but how these activities coordinate gene regulation has yet to be examined. In Aim 1, we will test the activity of all PRO-cap identified enhancer candidates in K562 from representative human Chromosomes 8 and 11 with a carefully chosen set of promoters harboring distinct regulatory features. A set of active enhancer-promoter combinations will then be subjected to a comprehensive motif mutagenesis of the central clusters of TF binding motifs and each of the two core promoters. These studies test our fundamental enhancer unit hypothesis and assess the relationships of enhancers to targeted promoters, and the role of specific motifs and sequence features in enhancer function. In Aim 2, we examine quantitatively enhancers and key mutants identified in Aim 1 by barcoding and integrating WT and mutant enhancers 5 kb upstream of their normally responsive promoter in a chromosomal context at the AAVS1 safe harbor locus. These assays will rigorously test function of enhancer motifs, core promoters, and the overall architecture of enhancers in a constant chromosomal background. In addition, we will also test the regulatory code underlying enhancer specificity for promoters and evaluate effects of mutant TF motifs on TF binding and on nascent transcription using targeted genomic assays. Finally, in Aim 3, we explore the ability of enhancers to act over long distances, using the NMU enhancer (eNMU), which resides 94 kb upstream of the NMU promoter and stimulates its transcription by 10,000-fold. We will utilize this robust model enhancer, which is not confounded by redundant/shadow enhancers at the native locus, to establish a novel long-range, chromosomal, massively-parallel reporter system using a landing pad at the eNMU locus and characterize functional motifs of eNMU by mutagenesis.

NIH Research Projects · FY 2025 · 2023-06

PROJECT SUMMARY Breast cancer is a second leading cause of cancer death in women, exceeded only by lung cancer. Among the different subtypes, triple-negative breast cancer (TNBC) that does not express the estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2, is characterized by poor prognostic outcomes. TNBC forms solid tumors with high interstitial fluid pressure (IFP). High IFP promotes tumor progression several ways and cancer immunotherapies are also compromised in TNBC tumors with high IFP since the interstitial pressure keeps immune cells from infiltrating into tumors. While solid stress formed by fibrotic tumor extracellular matrix contributes to tumor IFP formation, hyperpermeable blood vessels, combined with compromised lymphatic drainage, lead to high IFP. To decrease tumor IFP, researchers have tried to reduce solid stress and normalize leaky blood vessels in tumors. However, how lymphatic drainage is impaired in tumor microenvironment and how the impaired lymphatic function affects tumor IFP, immune cell interactions, and anti- tumor immunity are still ambiguous. Several studies have reported that lymphatic vessels (LVs) are structurally and functionally impaired in tumors, and lymphangiogenic vascular endothelial growth factor C (VEGFC) treatment inhibited tumor growth by promoting lymphangiogenesis and boosting T cell recruitment to the tumors. However, VEGFC has also been recognized to promote lymph node metastasis. Given the conflicting effects of VEGFC, the main goals of this project are to normalize lymphatic drainage in TNBC without using VEGFC or without promoting lymphangiogensis, by deciphering the mechanisms of lymphatic endothelial cell (LEC) junction remodeling in TNBC. In this proposal, we will use physiologically responsive in vitro 3D systems of lymphatic vessels co-cultured with breast cancer cells, which can recapitulate lymphatic structure, lymphatic drainage, and immune cell interactions in breast cancer. With these organotypic 3D model systems, we will examine lymphatic junction morphogenesis and drainage in TNBC in the context of a tissue-like and in vivo environment, examine LEC junction zippering in TNBC-associated LECs, evaluate the roles of lymphatic function in dendritic cell trafficking to lymphatics, T cell activation, and T cell infiltration in tumors; and assess the roles of LEC junction zippering for anti-tumor immunity. If successful, our studies will not only identify new targets to treat breast cancer, but also provide a new tool for mechanism studies and fast screening of potential drug candidates to treat cancer and lymphatic disease.