Grants

NICHD - Eunice Kennedy Shriver National Institute of Child Health and Human Development

Recruitment, adherence, and retention are critical challenges in medical rehabilitation and health promotion research for people with physical disabilities. These challenges often result in small sample sizes, poor adherence, and high dropout rates, which limit the generalizability of research findings. In addition, combining data from existing and new datasets to develop research questions and analyze data across studies is a complex task. The Deep South, particularly Alabama, Mississippi, and Louisiana, has some of the highest disability rates in the nation. Chronic conditions like diabetes and obesity are significantly more prevalent in people with physical disabilities in this region, exacerbated by environmental barriers and an unsupportive environment that hinder healthy behaviors. The primary goal of this research project, supported by the Administrative, Resource, and Community Engagement and Outreach (CEO) Cores, is to apply AI and behavioral economics-based approaches to develop tools and strategies to optimize data utilization and improve retention and adherence to health promotion and secondary condition prevention (HP/SCP) interventions for PWD. These resources will be promoted to medical rehabilitation and health promotion researchers to facilitate more robust research in HP/SCP for people with physical disabilities. Aim 1 will develop AI-enabled tools to conduct data harmonization, leveraging existing data to support medical rehabilitation and health promotion researchers. Aim 2 will utilize behavioral economics–based approaches to learn participant preferences toward HP/SCP interventions. Aim 3 will develop and test the usability of an AI-enabled multichannel digital HP/SCP platform to improve adherence and retention in trial studies. Aim 4 will conduct factorial experimentation to pilot three behavioral economics–related design features in gamification and financial incentives to determine which optimizes adherence and engagement. Leveraging our ongoing digital health promotion tools at the National Center on Health, Physical Activity and Disability (NCHPAD) Data Coordinating Center, we aim to develop resources that will allow researchers to systematically address these barriers and develop their own digital HP/SCP interventions. Our research project is innovative through its use of behavioral economics and AI-enabled tools to improve intervention adherence and retention in HP/SCP trials. The resources developed will be invaluable for investigators in digital medical rehabilitation and health promotion research. They will facilitate data harmonization and analysis, incorporate user preferences to enhance intervention delivery, and ensure high usability through inclusive design and gamification. Ultimately, they will enable precision-based recruitment and adherence recommendations and support future optimization trials for digital HP/SCP interventions for people with physical disabilities. This research project aligns with the NCMRR/NICHD RFA-HD-25-001 to promote healthy behaviors and preventative medicine for secondary conditions, ultimately improving health and function for people with physical disabilities.

Alliance of People with disAbilities

Augment the instruction and hardware at the Independence Technology & Employment Computer Lab to better serve individuals with mental health and other non-visible disabilities.

NHGRI - National Human Genome Research Institute

Translational genomic research (TGxR) holds promise for reducing the burden of common chronic diseases in the US and relies on cohort diversity for impartial implementation. Participation of people with disabilities in TGxR studies is necessary for achieving these goals. This large population (27% of US adults) experiences difficulties accessing routine care and disproportionately high prevalence of chronic diseases. Yet, research shows that people with disabilities are only limitedly participating in general (not disability specific) TGxR. This finding is disconcerting, as people with disabilities could greatly benefit from research advances and their absence from such research cohorts contribute to persisting health disparities. Two key obstacles are likely to hinder the long-term participation of people with disabilities in TGxR: 1) disability-related enrollment and retention challenges; and 2) unique concerns about data sharing, including future data uses that may cause individual and group-level harms. Despite growing recognition of the importance of participation across demographic groups in TGxR and community-driven approaches for data stewardship, as well as researchers’ expressed interest in assuring data sharing practices that are socially responsible towards the participants they enroll, no study has examined disability-related practices “on the ground” that foster participation or considered the unique concerns of people with disabilities about data sharing, including how to mitigate potential harms and what disability-specific practices might promote access to benefits for everyone. The proposed study employs a disability community-engaged model and leverages large cohorts of the eMERGE4 Network, which includes disability status data on identifiable participants, to close these gaps. We will 1) identify disability-specific challenges to participation and strategies used to address them via interviews with eMERGE4 participants with disabilities and research staff involved in recruitment and participant-facing study implementation; 2) examine and compare views on data sharing and data uses via a survey of three key cohorts: eMERGE4 participants with and without disabilities, and non-eMERGE4 participants with disabilities from the general public; and 3) develop evidence-based guidelines to promote fair data sharing practices using an iterative process, community forums and expert workshops to ensure responsiveness to both disability and scientific communities. The study is led by researchers across career stages and academic disciplines; it has representation from five adult-focused eMERGE4 sites. This project can transform TGxR—by fostering actionable, all embracing, and disability-informed practices—and the trajectory for improved health outcomes for everyone.

Mayor's Office For People With Disabilities

DISABLED SURVIVORS OF GUN & COMMUNITY VIOLENCE

Disabled Veterans National Foundation

Disabled Veterans National Foundation is an active grantmaking foundation based in Lanham, MD. Focus: general. Contact the foundation directly for current funding opportunities.

HOMELAND SECURITY, DEPARTMENT OF.FEDERAL EMERGENCY MANAGEMENT AGENCY.INCIDENT SUPPORT SECTION(ISS70)

Disaster Overseas Transportation (DOTS) US Virgin Islands & Puerto Rico (VIPR)

Western NY Assoc-Hist Agencies

Disaster Planning Workshop and Extensions

Family Bike Seattle

The Disaster Relief Trials is an event that mobilizes bicyclists and emergency hubs to work together as bicyclists carry emergency relief supplies to community and communication hubs, as well as participate in public emergency preparedness activities.

NIDA - National Institute on Drug Abuse

ABSTRACT The ongoing opioid crisis in the United States, with over 80,000 overdose deaths in 2023, disproportionately affects rural communities where access to medications for opioid use disorder (MOUD) remains limited. Natural disasters, such as hurricanes, further disrupt healthcare infrastructure, treatment continuity, and medication supply chains—exacerbating barriers to care in these underserved regions. Yet, little is known about how such disasters impact MOUD systems, especially in rural areas. This 12-month R36 study will investigate how hurricanes affect MOUD access through two complementary aims. First, a triple-difference analysis will quantify changes in buprenorphine and methadone distribution to pharmacies and treatment centers across rural and urban counties using ARCOS (Automation of Reports and Consolidated Orders System) data—a national DEA-managed database that tracks controlled substance shipments at the transaction level. Second, in-depth interviews with MOUD providers in Western North Carolina, a rural region severely affected by Hurricane Helene, will explore how providers adapted to treatment disruptions. Guided by the Healthcare Resilience Model, this multi-methods approach will assess system absorptive, adaptive, and transformative capacities in disaster contexts. Findings will provide actionable insights to strengthen rural health system resilience, inform disaster preparedness policy, and improve continuity of MOUD care during future emergencies—supporting NIDA’s priority to overcome barriers to addiction treatment.

NYC Department of Cultural Affairs

Discalced, Inc.

NCI - National Cancer Institute

PROJECT SUMMARY Triple Negative Breast Cancer (TNBC) is the most aggressive form of breast cancer. It disproportionately impacts young and African American/Black women, who are 23% more likely to die from TNBC than their European American/White counterparts. Due to its lack of estrogen (ER) and progesterone receptors as well as HER2, TNBC is primarily treated with cytotoxic chemotherapy along with immunotherapy or antibody-drug conjugates. While effective, patients frequently experience relapse. Hence it is imperative to discover new therapies that are effective, and have limited toxicity to improve patient outcomes. This project focuses on this unmet need by discovering a new driver of TNBC that could be therapeutically targeted. By evaluating a large, publicly available dataset, we discovered that CDK10 (cyclin dependent kinase 10) is more highly expressed in TNBCs from Black compared to White patients. Elevated CDK10 is also associated with worse patient outcomes from this disease, suggesting that it may fuel disease aggressiveness. We further found that targeted disruption of CDK10 decreases TNBC cell growth and increases the incidence of aberrant mitoses and chromosomal instability. Unlike many other CDKs, loss of CDK10 in non-transformed cells has no impact on growth. This suggests that it has a high degree of selectivity for controlling tumor versus normal cells. Together, these data suggest that CDK10 may be an innovative target for therapeutic development that would result in limited toxicity. CDK10 is a “dark” kinase, meaning it is understudied with unclear functions. As a member of the cyclin dependent kinase family, it controls cell cycle progression. Inhibitors of other CDKs have been previously developed, with the most notable being those that target CDK4/6. These drugs have been practice-changing for another type of breast cancer but are generally ineffective in TNBC. This proposal will test the overarching hypothesis that suppressing CDK10 will provide a novel avenue for blocking the cell cycle and treating TNBC, using a robust set of in vitro and in vivo models. Moreover, it will discover mechanisms that control CDK10 as well as reveal how it stimulates mitosis and TNBC cell growth. This work will provide fundamental insights regarding a potential architect of TNBC aggressiveness that may serve as an effective target for treating this disease and reducing disparities in breast cancer outcomes.

NSF

Accurate interpretation of hyperspectral data depends on the availability of reference spectra: measurements of known materials compiled into spectral libraries. Such libraries support both direct classification and machine learning applications. When combined with on-site hyperspectral imaging, they have proven effective across a variety of domains including heritage conservation, homeland security, hydrology, and geology. Urban conditions, however, present unique challenges to spectral data collection. In this context, urban materials refer to the components of the built condition, including both manufactured materials (e.g., asphalt, concrete, paint) and naturally occurring materials that have been anthropogenically modified for urban use (e.g., cut stone). Although hyperspectral data have been utilized in select urban planning tasks, the broader potential of hyperspectral imaging for material identification remains underutilized. This project will develop and extend community involvement in hyperspectral remote sensing technology to analyze and study urban landscapes. This will be paired with open metadata standards, modular processing toolkits, and automated archival workflows that prioritize FAIR principles. HS-SPECTRA (Hyperspectral Standardizing and Sharing Possibilities for Urban Conditions through Toolkits, Resources, and Archiving) addresses fundamental challenges in hyperspectral library design by: 1) Developing a metadata architecture tailored to longitudinal urban field campaigns; 2) Incorporating auxiliary sensors to contextualize spectral variability; 3) Implementing a flexible versioning and querying model that reflects the dynamic nature of repeated, real-world observations; and 4) Enabling interoperability across platforms through spectral resampling and standardization pipelines. By embracing the temporal complexity of real urban conditions and focusing on reproducible, extensible data infrastructures, HS-SPECTRA will generate a uniquely valuable dataset for cross-instrument, cross-temporal analysis. The resulting protocols and open-source tools will significantly advance methodological rigor and accessibility in urban planning, Earth system science, computer vision, and urban monitoring fields. This award by the Office of Advanced Cyberinfrastructure within the Directorate for Computer and Information Science and Engineering is jointly supported by the Directorate for Engineering. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF

Today's frontier Heliophysics research topics require fusing data from multiple distinct sources in order to advance community knowledge. However, creating analysis-ready data from multiple data sources remains burdensome. A more uniform way to discover measurements ripe for synthesis, as well as a consistent and efficient method to subsequently obtain the data in a common analysis environment for the study in question, is urgently needed to produce future discoveries while following interoperable, reusable principles and open science practices. This project provides concrete, usable, and valuable progress by linking the NSF-sponsored Madrigal Database, responsible for storing and providing access to a vast variety of ground-based geoscience data, with two emerging tools for standardizing data access, organization, and metadata: (1) the Heliophysics Application Programming Interface (HAPI), a time series download service and a tool bundle; and (2) the Space Physics Archive Search and Extract (SPASE) data model. This project will integrate the NSF-funded Madrigal, the database for upper atmosphere science, with the Heliophysics Application Program Interface (HAPI) and Space Physics Archive Search and Extract (SPASE) model. The project will increase the Findable, Accessible, Interoperable, and Reusable (FAIR) of the data and enable scientific discovery across a wide range of heliophysics with five major activities: 1) development of a Madrigal-HAPI server to serve Madrigal data via HAPI infrastructure, 2) development of a metadata converter between HAPI and SPASE, 3) development of a Madrigal-specific plugin to populate SPASE metadata, 4) research community engagement and training, and 5) quantitative assessment of the efficacy of newly developed tools. This award by the Office of Advanced Cyberinfrastructure in the Directorate for Computer and Information Science and Engineering is jointly supported by the Directorate for Geosciences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF

The Dark Matter Data Commons project addresses a pressing need in experimental astrophysics by creating an open, reusable, and accessible data infrastructure to support discovery in dark matter research. There has been an important investment in dark matter detection experiments, but the field still lacks standardized mechanisms for sharing data and analysis workflows. This gap hinders transparency, reproducibility, and innovation in science. By aligning with FAIR principles (i.e., Findable, Accessible, Interoperable, and Reusable), the project builds a data platform that broadens access to high-value experimental datasets, enabling participation of students, early career researchers, and institutions with limited infrastructure. The project advances scientific progress and national research capacity through this data infrastructure while supporting educational development and the research community. It contributes to national interest by accelerating discovery in a federally prioritized scientific area and fostering access to cyberinfrastructure for data-intensive science. The project establishes an end-to-end infrastructure for curating, storing, accessing, and analyzing dark matter experiment data. It delivers a FAIR-compliant repository enriched with standardized metadata, integrated with scalable AI and machine learning (AI/ML) workflows, and accessible through user-friendly command-line and Python interfaces. Built atop NSF-funded resources, the commons begins with time-series data from the Cryogenic Dark Matter Search and DELight experiments. It also includes tutorials, training materials, and an affinity group to foster community engagement and reproducibility. This work is a template for similar data infrastructure across rare-event physics, providing a foundation for long-term open science and AI-enabled discovery. This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Physics at the Information Frontier (PIF) Program within the Division of Physics in the Directorate for Mathematical and Physical Sciences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF

The project aims to advance the Findable Accessible Interoperable Reusable (FAIR) principles within the Earth and Space Science sample data ecosystem by promoting the adoption of persistent identifiers infrastructure (PID) across the geoscience community. The project plans to achieve the goal by engaging with four types of key stakeholders: researchers, sample repositories, data repositories, and scholarly publishers, through community engagement, education, training, and coordination. Scientific research across many disciplines relies on material samples as a basic element for reference, study, and experimentation. Given the high cost of collecting and curating these samples, it is essential to maximize research investments by ensuring samples and related data are open and FAIR. This can be done by a) assigning persistent identifiers to samples; b) persistently associating samples with their resulting research products; and c) citing samples in research literature. The infrastructure to support these actions is fragmented and incomplete, but uptake of best practices is growing. To advance adoption of open science practices in sample-based research, the project will engage four key stakeholders in the sample data ecosystem: (1) researchers, (2) sample repositories, (3) data repositories, and (4) scholarly publishers. For each community, the team will conduct an analysis of the current adoption of relevant open science practices such as usage of sample persistent identifiers (PIDs) and sample citation. Informed by this work, the group will organize these communities to begin realizing the vision of a functioning sample data ecosystem, where samples and their research products are fully described, persistently linked, and FAIR. This award by the Office of Advanced Cyberinfrastructure in the Directorate for Computer and Information Science and Engineering is jointly supported by the Directorate for Geosciences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

National Park Service

United State Department of the Interior, National Park Service (NPS) Notice of Intent to Award. This is not a request for applications. This funding opportunity is to provide public notice of NPS's intention to fund the following project activities without full and open competition. Task Agreement # P14AC01750 under Cooperative Agreement P14AC01749 with the Washington Trust for Historic Preservation, for project titled "Discover Washington Youth Summit"

Seaport Museum New York

Discover Your City's History

NIAMS - National Institute of Arthritis and Musculoskeletal and Skin Diseases

Project Summary Immune checkpoint inhibitors (ICIs) have revolutionized advanced cancer care, with up to 44% of all cancer patients eligible for ICI therapy as of 2019, representing 230,000 patients annually in the US alone. However, ICIs are associated with morbid and potentially fatal toxicities, known as immune-related adverse events (irAEs). In this work, we propose to study the genetic landscape of cutaneous irAEs (cirAEs) by analyzing germline data from thousands of ICI recipients and integrating with carefully collected spatial and longitudinal molecular data across multiple scales. No germline association studies of cirAEs have been performed to date, with an urgent need for discovery and functional follow-up. First, we will identify germline variants associated with cirAEs across >10,000 immunotherapy patients. We will investigate the genetic mechanisms of common germline variants; common and rare HLA alleles; as well as germline interactions with tumor and/or environmental features. Second, we will characterize the causal genes and phenotypic consequence of cirAE-associated variants. We will integrate population-scale RNA-seq data to identify the causal genes mediating cirAE events; we will investigate the downstream effects on anti-tumor response and overall survival; and we will identify associations with extremely severe cirAEs. Third, we will carry out prospective molecular phenotyping to map the precise mechanisms of cirAE risk in time and space for genotyped patients with skin cancer. For patients on ICIs, we will prospectively collect tissue for spatial profiling, TCR sequencing, and proteomics to comprehensively assay the precursors and consequences of cirAEs. If successful, our proposal will increase our understanding of the genetic architecture of cirAEs, identify avenues for therapeutic intervention and patient stratification to mitigate irAEs across organ systems, and potentially identify new ways of heightening the broader anti-tumor effect of ICIs.

NSF

This project will enable high efficiency conversion of fuels to electricity using a conversion device called a fuel cell. The key components of the fuel cell are the proton conducting electrolyte and the catalysts that facilitate the reaction of oxygen with protons to generate electricity. The project will create advanced electrocatalysts that operate at ~500 degrees Fahrenheit. This temperature is hot enough to accelerate the desired fuel conversion reaction, yet cool enough to slow unwanted material degradation. The research team has previously identified catalyst materials with high activity, but they degrade because they react with the electrolyte in the fuel cell. To address this challenge, the team will utilize ultra-thin barrier layers that are permeable to protons but block the reaction of the catalyst material with the electrolyte. In parallel, they will utilize advanced characterization techniques to reveal the pathway for the reaction of oxygen with protons. This will allow rational design and selection of high activity catalysts. The project will include researchers at various academic levels, and it will support training through internships for high school and undergraduate students, as well as postdoctoral research opportunities for early career professionals. This research aims to design oxygen reduction catalysts suitable for use in solid acid fuel cells. These fuel cells operate at ~ 250 degrees C and incorporate a superprotonic solid acid, cesium dihydrogen phosphate (CsH2PO4) with a proton conductivity of ~ 10-2 S/cm, as the electrolyte. Despite operating at temperatures higher than polymer electrolyte membrane fuel cells, oxygen reduction rates on the Pt catalysts of solid acid fuel cells are relatively low, necessitating the development of alternative catalyst materials. Possible candidates, including Pd and Ag, which show evidence of higher activity than Pt, react with the electrolyte and their activity quickly degrades. The PI proposes multi-layered structures in which proton-permeable barrier layers prevent these detrimental interactions. These structures and the reaction pathways facilitating oxygen reduction will be studied using a suite of tools including X-ray diffraction, X-ray photoelectron spectroscopy, scanning electron microscopy, transmission electron microscopy, Raman spectroscopy, and mass spectroscopy of evolved gases, in addition to electrochemical characterization by voltammetry and impedance spectroscopy. These studies are aimed at uncovering the reason for the poor activity of Pt in solid acid fuel cells and enabling rational design and selection of high activity alternatives. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NCI - National Cancer Institute

PROJECT SUMMARY Breast cancer (BC) is a complex and heterogeneous disease, further complicated by the discovery of tumor- specific microbiota, including Fusobacterium nucleatum (F. nucleatum), which has been detected in 30% of BC cases and is associated with increased malignancy. While F. nucleatum has been correlated with worse clinical outcomes in BC patients, the mechanisms underlying its effects remain unclear, partly due to limited research on how this bacterium alters tumor biology and immune responses in immunocompetent, clinically relevant BC models. Our preliminary studies reveal that F. nucleatum infection accelerates triple-negative BC (TNBC) growth. This raises the critical question of whether F. nucleatum fosters a pro-tumorigenic, immunosuppressive tumor microenvironment (TME) that diminishes the efficacy of chemotherapy in BC. We hypothesize that F. nucleatum and its metabolites drive an immunosuppressive TME, decreasing immune surveillance of the cancer by T-cells and impairing the response to chemotherapy. Targeting the infection will restore efficacy by increasing immune surveillance, transforming infected tumors into ‘hot’ tumors that are more responsive to treatment. In Aim 1, we will characterize the relationship between F. nucleatum infection and changes in the TME, and their collective role in promoting disease progression in BC. We will use two immunocompetent models of TNBC, 4T1 and T11-APOBEC (T11-AB), which have been comprehensively profiled and demonstrate strong genomic and genetic similarities to human TNBC. We will quantify the TME metabolome, transcriptome, and immune cell populations, alongside primary tumor growth, metastatic spread, and lifespan. We will perform the most extensive immunophenotyping of F. nucleatum-infected BC to date using spectral flow cytometry. Given the limited research on F. nucleatum’s role in BC, our study will address a critical gap by generating a detailed profile of the functional and immune alterations caused by this infection and its relation to disease outcomes. In Aim 2, we will tackle the challenge of eradicating F. nucleatum without disrupting the gut microbiota, which is crucial for maintaining immune function and overall health. Conventional antibiotic treatment can lead to dysbiosis, impair immune responses, and potentially promote tumor progression. To avoid this, we will use a novel combination therapy involving multi-drug polymeric micelles (MDPMs) to co-deliver anticancer drug, paclitaxel and the antibacterial antibiotic metronidazole directly to the tumors via intravenous administration. This approach aims to bypass the gastrointestinal tract, targeting both cancer and bacteria in the TMBC tumor while minimizing off- target antibiotic effects and preserving beneficial gut microbiota. By integrating these strategies, our study will provide critical insights into how F. nucleatum contributes to BC progression and offer a promising, microbiome- sparing therapeutic strategy for treating bacteria-infected tumors.

NIAID - National Institute of Allergy and Infectious Diseases

PROJECT SUMMARY: Mycobacterium tuberculosis (Mtb) is the leading cause of death worldwide due to a single pathogen. Mtb is exceptionally reliant on specialized lipids, yet little is known about how lipids and lipid- linked glycans transit across the membranes and aqueous periplasm of mycobacteria. My objective is to reveal how Mtb controls the localization and effects of important lipidic antigens, virulence factors, and cell envelope components. I found that one of the primary mycobacterial lipid transport systems, Mce4, is not restricted to exogenous lipid import as previously thought, but maintains steady-state levels of hundreds of native mycobacterial lipids. I will define how periplasm-spanning Mce channels mediate directional lipid transport in Mtb, using unbiased lipidomic methods, a new reverse micelle separation technique, and collisional mass spectrometry. This will push the field beyond previous studies of selected exogenous lipids, and will identify the roles that Mce channels play in native lipid transport within laboratory and clinical strains of Mtb. I also found that the putative transport lipid mannosyl phosphomycoketide (MPM) is covalently linked to one or more Mtb glycans, and that the gene pks12—which is required for the synthesis of MPM—is important for glycan localization. This suggests that MPM is at the center of an undiscovered lipoglycan transport mechanism. I will uncover this mechanism through chromatography and mass spectrometry-based identification of MPM-linked glycans. Through the same methods along with electron microscopy and glycan labeling, I will determine the effects of pks12 on exported Mtb glycans. I will finish by determining the role that pks12 and glycans play in a growth defect I discovered, thereby providing a mechanistic basis for the likely in vivo essentiality of pks12 in human disease. This proposed investigation of understudied Mtb lipid and lipoglycan transport will address a critical knowledge gap that hinders development of tuberculosis drugs, vaccines, and diagnostics. I will conduct the K99 phase of this award as a postdoctoral research fellow in Dr. D. Branch Moody’s group at Brigham and Women’s Hospital. The Moody lab is exceptionally well equipped for mass spectrometry analysis of Mtb lipids and cell envelope components. I will rely on advisors including Dr. Laura Kiessling to support my studies of glycan and lipoglycan transport, and will leverage the scientific networks of Harvard Medical School, its teaching hospitals, the Harvard T.H. Chan School of Public Health, and the broader Boston research community. In my mentored training I will gain expertise in analytical chemistry, manage large collaborations from inception to publication, and enhance my mentoring and teaching skills. These training objectives are in service of my long-term career goal of leading an independent research team focused on the synthesis, localization, and essential roles that Mtb cell envelope lipids and glycans play in bacterial survival and human disease. In my R00 phase I will apply for independent R01 and other funding, beginning a career with meaningful impact on the treatment, prevention, and diagnosis of human tuberculosis.

NIDDK - National Institute of Diabetes and Digestive and Kidney Diseases

Subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and the liver are the key metabolic tissues involved in maintaining homeostasis and cardiometabolic health. In individuals with metabolic dysfunction- associated steatotic liver disease (MASLD), the liver is inundated with fat and unable to perform optimally. MASLD may further progress to its pro-inflammatory stage, metabolic dysfunction-associated steatohepatitis (MASH), which is often coupled with cardiovascular disease (CVD), including coronary artery disease (CAD). Both MASLD/MASH and CAD are associated with obesity and related cardiometabolic disease (CMD) and CVD traits. In line with this, recent studies have identified two types of MASLD: one that manifests into more severe liver disease (“liver MASLD”) and another that is primarily associated with CVD (“systemic MASLD”). This suggests that there are multiple distinct mechanisms and pathways in the pathogenesis of MASLD, making prevention and treatment of MASLD challenging. This is of clinical significance because MASLD is growing globally, and CVD is the leading cause of death in individuals with MASLD. Therefore, it is important to improve understanding of the multisystem mechanisms underlying MASLD. Single nucleus RNA-sequencing (snRNA- seq) provides a granular view of gene expression by cell-type and cellular subtypes. Coupled with genotype data it allows the investigation of genetic regulation of cell-type and cellular subtype level gene expression and how that relates to MASLD susceptibility. We hypothesize that there are cell-type and cellular subtype level regulomes and susceptibility genes associated with development of MASLD and its two types. Leveraging cohorts with matched tissue samples, we will 1) discover master transcription factors (TFs) trans regulating cell-type or cellular subtype level expression of genes associated with MASLD and 2) elucidate cis variants regulating cell- type or cellular subtype level gene expression of genes differentially expressed (DE) by MASLD across the SAT, VAT, and the liver. In Specific Aim 1, we will use co-expression network methods to find the TFs regulating gene expression in cell-type level networks that we hypothesize to reflect cellular subtypes. We will then assess the DE genes by MASLD regulated by TFs in the networks and functionally validate TF target genes with existing functional data and knockdown experiments to improve understanding of complex cell-type and subtype level trans regulation of tightly coordinated co-expressed genes involved in MASLD in SAT, VAT, and the liver. In Specific Aim 2, we will first identify cell-type and cellular subtype level cis-expression quantitative trait locus (eQTL) variants and genes DE by MASLD in the three key metabolic tissue. Following this, we will colocalize these cis regulatory variants with GWAS variants of the two MASLD types to discover cell-type and cellular subtype level genes involved in the two types of MASLD, “liver MASLD” versus “systemic MASLD”. Accomplishing Specific aims 1-2 will improve understanding of 1) cell-type level key trans regulators of MASLD genes and 2) cis regulatory variants and their genes underlying the two types of MASLD.

NSF

Lithium is a critical component of batteries that power everything from smartphones to electric vehicles. Current methods for extracting lithium are often inefficient, costly, and harmful to the environment. This project will design new molecular binders that selectively capture lithium ions from natural sources such as salt lakes and geothermal brines. It will result in materials that capture and release lithium more efficiently and sustainably. This work will strengthen the U.S. supply chain for critical materials, promote energy security, and reduce environmental impact. In addition to its scientific contributions, the project will train students in advanced chemical research, support workforce development in science and technology, and inspire the next generation of STEM leaders through educational activities and outreach initiatives. The key challenge in this field is how to selectively extract lithium ions from an aqueous solution containing many other ions. Existing processes often use crown ethers and other macrocyclic receptors with cavities that trap lithium, but exclude larger metal ions. These receptors typically show weak lithium binding, low selectivity over competing ions, and costly syntheses. This project introduces a new approach to designing acyclic molecular receptors that exploit strong noncovalent forces, particularly ion-dipole and electrostatic interactions, to achieve selective lithium binding. The project team will design and synthesize a series of acyclic molecular receptors and systematically evaluate their lithium binding in solution. Promising candidates will then be immobilized onto solid supports, and their separation performance will be assessed under conditions typical of industrial practice. The results will advance fundamental understanding of how noncovalent interactions can be exploited for selective ion binding. Overall, the project will establish the molecular-level principles needed to develop sorbents with improved efficiency, selectivity, and sustainability for lithium extraction. This project will promote national self-reliance for critical minerals. Additional benefits will derive from extensive outreach activities at pre-college level, and incorporating virtual reality experiences for chemistry education. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIGMS - National Institute of General Medical Sciences

Project Summary Halogen atoms (F–, Cl–, Br–, and I–) are incredibly versatile components of both naturally produced and synthetic compounds. Over half of the pharmaceuticals on the market in the United States contain at least one halogen atom, and likely many more compounds involve halogen atoms in their synthesis. Chemical methods for installing halogen atoms typically generate one or more undesired side products and require reagents that have adverse effects for human and environmental health. Methods improving both halogenation selectivity and sustainability are therefore highly desired. My lab approaches these general needs by studying enzymes to complement synthetic chemical methods. Specifically, we focus on halogenases capable of installing halogen atoms onto organic compounds with precise selectivity in an environmentally-benign manner. In the area of medicinal chemistry, halogenases have the potential to transform the landscape of environmentally-conscious catalysis, but shortcomings related to enzyme stability, scope of substrate preference, and reaction kinetics have limited their broad application thus far. To combat these known limitations, my group combines bioinformatics, natural product biosynthetic logic, and enzymology to identify novel enzymes in publicly available genomic data with biocatalytic potential. Using these techniques, we have identified a new family of halogenases that is phylogenetically unrelated to known halogenases and possesses superior kinetic properties, enhanced stability, and broad substrate scope. Within this family exist two distinct chemoselectivity preferences where one subsection of the family targets indole-containing molecules such as the amino acid L-tryptophan and the other selectively installs halogen atoms onto terminal alkynes to generate haloalkynes, a reaction that was previously unknown in enzyme chemistry. The initial discovery of these powerful biocatalysts inspires the focus of this proposal, which places emphasis on expanding our fundamental understanding of the biochemistry of this new halogenase family and developing both scalable and high throughput biocatalytic platforms to leverage the potential of these enzymes in medicinal chemistry. In the period of the next five years, we aim to break new ground in halogenation chemistry and biocatalysis, develop robust and generalizable methodologies to apply to other enzyme systems in our lab, and identify the next phase of biocatalytic innovation in our program through natural product discovery. Through the highly interdisciplinary research described in this proposal, members of the Lukowski lab are trained in enzymology, natural products chemistry, biosynthesis, analytical chemistry, biocatalysis, organic chemistry, microbiology, synthetic biology, marine science, and bioinformatics, enabling challenging problems to be tackled and preparing the next generation of researchers for careers in industry, academia, government, and the private sector.