# data[].attributes.title
Regulation of the Inflammasome by Gasdermin D mRNA Chimerism

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National Institute of Allergy and Infectious Diseases (NIAID)

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Appreciation for the complexity of RNA processing is essential for understanding regulatory mechanisms of innate immunity. We uncovered novel splice variants that occur through the fusion of two distinct RNA transcripts (chimeric mRNA) in murine macrophages, including a fusion transcript containing Gsdmd and Tmem106a (Gsdmd:Tmem106a), two genes situated on separate chromosomes. Following inflammasome assembly, triggered by microbial signals and cellular damage, gasdermin D (GSDMD) is cleaved into its active form by inflammatory caspases. GSDMD N-terminal (GSDMD-NT) fragments oligomerize and create pores in the plasma membrane allowing for the release of IL-1β. This often triggers inflammatory cell death but occasionally allows for longer lasting states of pro-inflammatory cytokine release. GSDMD is essential for host defense against a variety of bacterial pathogens but excessive inflammasome activation and GSDMD pore formation is linked to autoinflammatory diseases, sepsis, and cytokine release syndrome. Regulatory mechanisms of pore formation, acting downstream of GSDMD cleavage, are a topic of intensive investigation. To functionally assess the role of Gsdmd:Tmem106a downstream of inflammasome activation, we selectively knocked-down this chimeric mRNA using RNA interference and discovered that it is required for optimal IL-1β release. Based on our preliminary results, this proposal will test the hypothesis that Gsdmd:Tmem106a facilitates GSDMD pore formation and contributes to physiological inflammation. To robustly investigate the function of this chimeric mRNA and protein, we generated two mouse models: endogenous GSDMD:TMEM106A protein tag mice (GTMyc) and GSDMD:TMEM106A-deficient mice (GTstop). Aim 1 of this proposal will mechanistically interrogate Gsdmd:Tmem106a function by first characterizing chimeric protein localization and interacting partners during inflammasome activation using GTMyc mice (Aim 1.1) and secondly, by assessing GSDMD-NT oligomerization and pore formation in GTstop bone marrow derived macrophages, as well as by using in vitro systems of GSDMD- NT pore formation that function independently of the upstream inflammasome (Aim 1.2). As Gsdmd:Tmem106a encodes a novel protein with a truncated GSDMD-NT, we hypothesize that it promotes native GSDMD pore formation through direct interaction. Aim 2 of this proposal will evaluate the in vivo expression landscape of Gsdmd:Tmem106a following systemic LPS exposure (Aim 2.1), as well as use GTstop mice to assess its physiological role in LPS sepsis induced inflammation and death (Aim 2.2). We hypothesize that Gsdmd:Tmem106a will be robustly expressed following LPS treatment, and that this chimeric mRNA plays a role in exacerbating inflammation and LPS sepsis lethality, as native GSDMD has been reported to. Taken together, this work will uncover a novel mechanism of GSDMD pore formation, and demonstrate that chimeric mRNA are present and functional during inflammation, highlighting an entirely new class of mRNA for further exploration in the immune system.

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Mechanisms of Thrombosis in SARS CoV-2 Infection

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National Heart Lung and Blood Institute (NHLBI)

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More than 100 million individuals in the United States have experienced Coronavirus Disease 2019 (COVID- 19), caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). Life-threatening thrombotic events are well-described in these patients and occur in 2-3% of hospitalized patients. However, it is clear that a much greater number of patients experience microclots, small thrombotic events capable of causing localized tissue damage, and that microclots associate with the development of long-term complications from COVID-19. We hypothesize that these microclots result from a combined procoagulant and antifibrinolytic state. Through our preliminary studies we have identified two novel regulatory mechanisms that lead to the hemostatic and fibrinolytic dysfunction and microclot formation: (1) Activated endothelial cells secrete von Willebrand Factor (VWF), which binds and sequesters and inhibits protein S (PS), a critical plasma anticoagulant; and (2) dyslipidemia and elevated plasminogen activator inhibitor-1 result in sequestration and inhibition of the fibrinolytic protein tissue plasminogen activator (tPA). This combination of impaired anticoagulant and impaired fibrinolytic activity results in the formation of stable microclots, capable of blocking blood flow in microvascular beds, and causing localized hypoxia and tissue damage. We hypothesize that these dysfunctions occur during the acute phase of COVID-19 infection and persist in a sub-population of patients post-infection. As such, these mechanisms contribute to both acute and post-acute COVID- 19-associated coagulopathy. In the present study, we will test these hypotheses and extend our previous findings by following patients longitudinally from first diagnosis through 6-months post-infection, to identify the changes in the hemostatic and fibrinolytic systems, directly assess the contributions of PS and tPA to this process and their regulatory mechanisms, and determine the correlation of dysfunctions in these systems with microclot formation and recovery post-infection. Finally, we will perform similar analyses using samples from a cohort of patients with post-acute sequelae of COVID-19 (PASC), long-term complications from their initial infection. We hypothesize that these patients are individuals whose systems did not fully recover from the initial infection, and the proposed studies will allow us to compare the hemostatic and fibrinolytic systems between acute and PASC patients to evaluate this hypothesis, with particular focus on PS and tPA. The results from this study will inform on the mechanism(s) leading to COVID-19-associated coagulopathy and may determine biomarkers that can be used to identify those patients at greatest risk.

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Centers for Disease Control and Prevention (U.S.)

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Post-Acute Sequelae of SARS-CoV-2 Infection

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Aerocyte-mediated Alveolar Epithelial Regeneration following Lung Injury

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National Heart Lung and Blood Institute (NHLBI)

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/ ABSTRACT  Acute Respiratory Distress Syndrome (ARDS) is a life-threatening lung injury caused by various factors such as infection and trauma, currently lacking a cure. Annually, approximately 190,000 Americans are diagnosed with ARDS, a number further amplified by the COVID-19 pandemic. The primary pathology involves damage to the alveolar epithelium, necessitating innovative approaches to accelerate alveolar epithelial regeneration for treating ARDS.  Alveoli, surrounded by abundant capillaries for gas exchange, remain poorly understood in their regulatory role within this intensive capillary niche. Our focus is on aerocytes, a recently identified capillary endothelial population specialized in the lungs and positioned on the outer surface of the alveolar epithelium. Given this unique location, we propose that aerocytes play a pivotal role in alveolar epithelial regeneration. Preliminary data indicate that aerocytes express the angiocrine factor R-spondin3, a Wnt signaling activator, and stem cell factor. Loss of angiocrine R-spondin3 impedes regenerative epithelial remodeling and lung repair following injury, suggesting a crucial role for aerocyte-derived signaling in lung alveolar regeneration.  Our research proposal aims to establish the central role of aerocytes in regulating alveolar regeneration post lung injury, with a specific focus on the signaling molecule R-spondin3. We hypothesize that aerocytes guide regenerative alveolar remodeling through R-spondin3, enhancing Wnt signaling in alveolar epithelium, and orchestrating interstitial macrophage plasticity for the necessary regenerative niche. To rigorously test this hypothesis, we outline the following specific aims: Aim 1: Investigate the role of aerocyte-derived R-spondin3 in lung growth and recovery using loss-of- function and gain-of-function animal studies within disease-related lung injury models. Aim 2: Define the mechanisms of regenerative alveolar remodeling guided by aerocyte-derived signaling, focusing on AT2 cell renewal, transition into TSCs, and differentiation into AT1 cells using advanced techniques such as alveolar organoids. Aim 3: Examine the impact of aerocytes on interstitial macrophage plasticity in establishing a regenerative alveolar niche.  By unveiling the role and mechanisms of aerocytes in alveolar epithelial regeneration, this research potentially leads to innovative therapeutic strategies for treating ARDS by targeting aerocyte-derived signaling to regenerate the alveoli, ultimately improving the health and quality of life for individuals affected by severe respiratory complications associated with COVID-19 and ARDS.

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CAREER: Mechanism-Informed AI for Biological Systems-of-Systems to Accelerate Biomanufacturing Systems Integration and Innovations

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Unlike traditional pharmaceuticals, biopharmaceuticals use living organisms, e.g., cells, as factories to provide essential life-saving treatments for severe and chronic diseases (including cancers, metabolic diseases, and infectious diseases such as COVID-19) often with advantages such as increased efficacy and reduced side effects. However, current manufacturing systems lack the flexibility to produce existing and new biopharmaceuticals on demand. This is mainly because biomanufacturing processes are highly complex and variable, with hundreds of biological, physical, and chemical factors dynamically interacting at molecular, cellular, and macroscopic scales.  Further, bioprocessing mechanisms are not systematically understood, and data are often very limited, sparse, and heterogeneous. To address these challenges, this Faculty Early Career Development (CAREER) project aims to optimize biomanufacturing processes via a bioprocess-specific AI that integrates uncertainty, intelligence, and science (i.e., systems and synthetic biology). Leveraging emerging sensing technologies that can monitor bioprocesses at molecular and cellular scales, this AI can also efficiently decode fundamental mechanisms. Moreover, by transferring this AI to industry practice, it is hoped this research will help make life-saving biopharmaceuticals rapidly available by accelerating biomanufacturing systems integration and automation with dramatically improved capabilities. The project will in parallel create a world-leading workforce pipeline from training the current workforce to educating (under)graduate and K-12 students.     This project will create a mechanism-informed AI platform on Biological Systems-of-Systems to enable the quick assembly of flexible and robust biomanufacturing systems. To support biomanufacturing systems integration and accelerate the development of flexible optimal robust manufacturing systems, this research will answer two fundamental questions: (1) how to create a unified knowledge representation that enables integration of heterogeneous data collected at molecular, cellular, and macroscopic scales in different production processes; and (2) how to enable sample-efficient and interpretable learning for fundamental mechanisms and optimal control strategies within and across different scales. These questions will be addressed through three integrated research efforts: (i) creating a multi-scale probabilistic knowledge graph (pKG) hybrid (mechanistic + statistical) model with a modular design capable of representing spatial-temporal causal interdependencies from molecular- to cellular- to macroscopic scales for different biomanufacturing processes; (ii) developing interpretable federated learning to quickly fuse sparse and heterogeneous data collected from different production processes to advance scientific understanding and track critical latent states through sequential Bayesian inference on the pKG; and (iii) constructing new provably efficient model-based reinforcement learning schemes on Bayesian pKG, accounting for model uncertainty, informing design of experiments for digital twin calibration, and streamlining the policy search on optimal robust biomanufacturing systems.    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.

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EAGER: LGBTQI+ DCL:Exploring the influence of community cultural wealth on nonbinary engineering students professional formation

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Current and future US engineering workforce demands require research to better understand how to support the professional formation of all engineering students. The number of enrolled engineering students nation-wide had the sharpest decline in a generation. Further complicating the problem is the decreased math and reading scores across the US since the pandemic, adding an additional filter of who can enter into engineering. Projected national shortages of engineers are in the tens and hundreds of thousands of workers in some sectors. Simultaneously, fewer young people are entering into four-year degrees. Once a student has enrolled in an undergraduate engineering program, they become a valuable asset for meeting the workforce demands and need support to continue in their professional formation. However, researchers have found that some subgroups of students are at a particularly high-risk of leaving engineering. Among those subgroups of at-risk learners are nonbinary engineering students. Researchers know very little about factors supporting or hindering nonbinary students engineering professional formation. This project serves to help understand how these students leverage identity-specific strengths from their communities, known as community cultural wealth, to succeed in their academic careers. This novel, transformational EAGER proposal will explore their community cultural wealth—that is, for example, how these students sustain hopes and goals, successfully navigate their majors, receive support from family-style relationships, leverage their social network, transgress expectations and resist negative stereotypes and microaggressions—as a means to thrive in engineering. We will interview twenty nonbinary engineering students at various stages of their academic careers using narrative inquiry. Through this project, we aim to raise awareness of the unique assets of the nonbinary engineering community so that engineering students feel affirmed and heard, and engineering educators may design inclusive education practices and advocate on behalf of the nonbinary community in engineering. This project outcomes will result in the development of resources that can be shared to support the professional formation of nonbinary students, as well as the broader engineering student population.     The purpose of this asset-based qualitative study is to investigate how nonbinary engineering students leverage their community cultural wealth to support their wellbeing, belonging, and persistence during their professional formation. We are guided by two research questions: 1) How do nonbinary engineering students access community cultural wealth within engineering and queer communities, and 2) how do nonbinary engineering students mobilize their cultural capital to support their wellbeing, sense of belonging and persistence? We will interview 20 engineering students at various stages of their professional formation using composite narrative inquiry and critical incident technique. By interviewing students at various stages of professional formation, we will explore how capital is accrued and how different forms of capital impact students’ persistence at differing stages of their identity development. Our findings will generate new knowledge about how nonbinary students draw upon their personal assets and those of the LGBTQ+ and ally communities during their professional formation. Nonbinary participants will benefit from being heard, affirmed, and seen throughout the interview process, and from reading the narratives of other nonbinary engineering students leveraging their assets to persist, belong and thrive in engineering. To reach students outside of the study, we will disseminate the composite narratives to LGBTQ+ STEM focused social media and professional organizations.    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.

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I-Corps: Translation Potential of a Handheld Standoff Photothermal Spectroscopy System for Real-time Indication of Viral Epidemics

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Technology, Innovation and Partnerships (TIP)

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This I-Corps project is focused on the development of an innovative. non-invasive, diagnostic tool for viral infections. The technology is able to provide rapid, accurate, and real-time detection of influenza, respiratory syncytial virus, and COVID-19. The tool's portability ensures that it can be widely distributed, making it accessible in a variety of healthcare settings, including clinics, hospitals, and in remote areas with limited medical infrastructure. By enabling early and precise diagnosis, this tool can improve patient outcomes, reduce the spread of infectious diseases, and alleviate the burden on healthcare systems. Furthermore, its scalability and low manufacturing costs position it as a viable option for mass production and global distribution, addressing urgent public health needs.    This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of a method to determine multiple pathological conditions simultaneously. The solution detects the infrared signatures produced by the resonant excitation of certain molecules using a tunable source. This approach achieves a limit of detection that is orders of magnitude higher than available nanosensors. By applying machine learning techniques to analyze the nanomechanical infrared response profile, multiple pathological conditions can be identified simultaneously. This device is capable of continuous miniaturization, making it portable and affordable for widespread deployment.    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.

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PFI (MCA): Integration of Protein Engineering and Electrochemical Biosensors for Virus Detection

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The University of Central Florida Board of Trustees

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This Partnerships for Innovation – Mid Career Advancement (PFI-MCA) project is focused on the development of a new, affordable technology to test for viruses with high accuracy. The project innovation is in the use of stable enzymes that can be stored at room temperature without requiring cold environments. The enzymes, combined with an electrochemical biosensor and microfluidics technology, will create a portable, affordable platform for virus detection in resource-limited environments. This technology can impact areas like health diagnostics, national security, and food safety. The research is multidisciplinary as it integrates chemistry, biology, and engineering. The project will give students hands-on experience in research scientific fields. The commercial impact of this technology will be important since it has potential to develop technology for virus detection that will be low cost and portable so it can be used anywhere and can supplement virus outbreak surveillance. This project will also translate the technology to manufacturing and commercialization.    This project employs protein engineering to make stable enzymes that can be stored at room temperature without requiring cold environments. These enzymes are used to perform isothermal amplification of a virus fragment for posterior detection with electrochemical biosensors. By combining these two technologies, the project will develop a virus detection platform that works even in areas with limited resources, making it more accessible and cost-effective. The recent pandemic has shown the urgent need for affordable and quick virus detection methods. Currently, the most common virus detection method, Reverse Transcriptase Polymerase Chain Reaction, is expensive, requires special equipment and trained staff, and is mostly available in large labs, which makes it hard to use in areas with limit resources. This project aims to develop a more affordable and practical solution by using protein engineering to create stable, cost-effective enzymes that can be used with Nucleic Acid Sequence-Based Amplification technique at a single temperature. The enzymes, combined with an electrochemical biosensor and microfluidics technology, will create a portable, affordable platform for virus detection in resource-limited environments.    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.

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Conference: International Symposium on the Infectious Diseases of Bats:Fourth International Symposium on the Infectious Diseases of Bats (BatID 2025), Chicago, IL

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This award supports the Fourth International Symposium on the Infectious Diseases of Bats (‘BatID 2025’), an international conference which brings together researchers from the disparate fields of virology, immunology, biochemistry, ecology, physiology, and genetics to investigate the role of bats as unique pathogen hosts. Bats are natural reservoir hosts for several high profile emerging human pathogens—including SARS-related coronaviruses, the likely precursors to the COVID-19 pandemic—yet they demonstrate limited pathology upon infection with viruses that cause extreme disease in non-bat (including human) hosts. Studying the mechanisms by which bats avoid disease from infection offers opportunities to translate bat-inspired immunological approaches into human disease therapeutics. This meeting offers opportunities for early career trainees, particularly graduate students and postdoctoral scholars, to share ideas and research findings with experts across this wide-ranging and interdisciplinary field. The meeting also aims to facilitate conversation between bat ecologists and conservationists with those engaged in more molecular approaches to understanding bat infectious disease to reconcile bats’ roles as major pathogen reservoirs.    BatID 2025 is organized around three major conference objectives: (1) to disseminate research on the unique role of bats as pathogen hosts, (2) to foster collaborations and expand the field of bat infectious disease research, and (3) to identify a priority future research agenda in the study of bat infectious diseases. The first objective highlights this meeting’s utility as a research-sharing forum that welcomes representatives from disparate disciplines, who may not closely follow research outputs from other fields. The second objective seeks to turn this idea exchange into action by fostering collaborations among attendees, this year with a particular emphasis on recruiting participants and speakers who have not previously attended this meeting. Finally, the third objective seeks to organize the community around future research goals through an open discussion at the end of the two-day program. As an output, the Conference Organizing Committee will produce a peer-reviewed ‘Conference Proceedings’ article (to be led by junior researcher attendees) that shares these goals with the broader scientific community.    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.

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CAREER: Intelligent Biomarker Analysis based on Wearable Distributed Computing

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Some of the challenges associated with wearable technologies are the limitation on computational power, battery capacity, data privacy, user interface design, and the need for seamless integration into user lifestyles without causing discomfort. These challenges limit the on-device implementation of machine learning methods, which are suitable for classifying and estimating medical conditions based on the biomarkers sensed by the wearable devices. This research addresses these problems by developing a scheme that distributes the computational load of machine-learning models across wearable devices. Results from this research contribute to deploying advanced health monitoring tools for in-home care of frail populations, such as post-COVID patients. This is aligned with the NSF mission to promote the progress of science and advance national health. The development of this project involves multidisciplinary efforts from computer science, bioengineering, and electrical engineering, as well as educational activities with the participation of students from underrepresented groups.    This project focuses on developing a wearable sensor network scheme with distributed and interconnected computing capabilities. As an application case, the wearable computing sensor network is aimed at biomechanics analysis for frail populations. The research plan is geared toward creating an advanced scheme of wearable devices to improve power consumption, data privacy, and computational performance for advanced health monitoring and analysis. To fulfill the strict requirements of size, computational load, and energy consumption, a novel distributed machine learning architecture is designed and deployed on each wearable sensor using field programmable gate arrays. The deployed architecture is a simplified version of the parallel-computing architecture found in commercial graphics processing units, which have been demonstrated to be suitable for machine-learning applications. In addition, this architecture contains additional hardware components for estimating missing data, synchronization, and addressing communication errors between the devices. This project addresses realistic challenges in biomedical and wearable technologies research, including (i) segmenting and training machine learning models considering the nature of biomechanical data and wearable inertial sensors without affecting accuracy, (ii) modeling a lightweight computer architecture for performing distributed machine learning inference in real time, (iii) estimating detailed body motion dynamics using a reduced amount of inertial sensors, and (iv) integrating reliable and state-of-the-art data analytics environments for efficient real-time analysis and visualization. The education plan tackles three major areas: (i) research training and competitive experiences for graduate and undergraduate students in the areas of computer science, computer architecture, and health-related areas, (ii) course development in topics related to edge computing, real-time systems, and machine learning applications to healthcare, and (iii) outreach to K-12 students and professionals by the introduction of competitive activities. Most of the students and contributors for this project are Hispanic, and this project supports broader access to and training in cutting-edge research in computational applications.    This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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SBIR Phase I: Novel Peptide Immunomodulators for Treatment of Autoimmune and Inflammatory Disorders

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Technology, Innovation and Partnerships (TIP)

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The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is in developing a novel class of compounds capable of treating autoimmune and inflammatory conditions safely and effectively. With the constant threat of new COVID variants, influenza, and RSV, there is an unmet medical need for therapeutics that can effectively treat autoimmune diseases especially in pediatric patients without compromising the immune system to respond to infections. This problem has been overcome with the discovery of novel compositions that demonstrate efficacy equal or superior to many of the first line therapies used to treat immune diseases. The improved safety, efficacy and lower cost of these therapeutics should provide a significant benefit to patients by overall contributing to their quality of life as compared to current medications, as well as marketing and partnering advantage in its commercialization efforts, which will focus on rare diseases, such as juvenile idiopathic arthritis-associated uveitis and pediatric Crohn’s disease among others. In the era of socio-economic disparities, these affordable drugs will become available to the historically neglected low-income communities. If executed successfully, this proposal would validate the platform technology and demonstrate the feasibility of identifying candidates for further development into life-changing treatments.    This Small Business Innovation Research (SBIR) Phase I project will demonstrate the unique design of novel compounds to augment and re-program the immune responses from pro- to anti-inflammatory, based on the binding to MHC class II molecules that leads to immunomodulation. The technical complexities of understanding the effects of peptide sequences on the outcomes of cellular interactions present challenges related to selecting the appropriate amino acids both for the random and specific components of these compositions. These hurdles will be addressed by design of several candidate compounds for each target condition, juvenile idiopathic arthritis-associated uveitis and pediatric Crohn’s disease, that will take into account the structure of autoantigenic peptides known to interact with both the MHC class II and T cell receptor (TCR). These candidate compounds will be initially tested in vitro in human macrophages to assess their potential to inhibit secretion of pro-inflammatory cytokines. Of these compounds, the most efficient ones will be tested for activity in relevant animal models. This approach will allow identifying and selecting the best drug candidates for further development into therapies for pediatric conditions as outlined above.    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.