# data[].attributes.title
Durable and broad airway immunity through next-generation intranasal boosters

# data[].attributes.funder_divisions[]
National Institute of Allergy and Infectious Diseases (NIAID)

# data[].attributes.abstract
Intramuscular SARS-CoV-2 mRNA-LNP do not reliably nor durably elicit respiratory mucosal IgA. Moreover, vaccinated individuals who become infected are more durably protected and this is thought to be mediated by respiratory mucosal IgA. Currently, there are no mucosal respiratory vaccines for human use. We identified a mucosal booster vaccine admixed with a mast cell agonist adjuvant, mastoparan-7, and a toll-like receptor 9 agonist adjuvant, CpG, that elicits durable mucosal IgA. Importantly, mice intranasally boosted with a multivalent nanoparticle vaccine adjuvanted with mastoparan-7 and CpG are protected from bat SARS-like virus challenge. We propose to study the mechanism of mast cell and antigen-presenting cell signaling modulated by this novel mucosal adjuvant combination. We will pursue our central objective which is to understand how mucosal IgA is elicited and maintained following respiratory mucosal vaccination with our exciting universal vaccines to ultimately achieve durable and broadly protective immunity against zoonotic coronaviruses. To achieve this objective, we will complete these aims: Aim 1: Test the hypothesis that mast cells and antigen-presenting cells elicit specific cytokines and chemokines that modulate durable IgA. We propose to study the impact of intranasal boost dose and interval on IgA kinetics and durability. We will also define if the mastoparan-7 and CpG adjuvant combination requires mast cell and antigen presenting cells that signal through CpG via the TLR-9 pathway. We will then define gene expression profiles from respiratory tract mast cells and antigen presenting cells that are activated by mastoparan-7 and CpG and modulate durable mucosal IgA responses. Aim 2: Test the hypothesis that M7/CpG nanoparticle vaccine elicits durable IgA secreting cells and IgA memory B cells in the respiratory tract using lineage-tracing, fluorescent reporter mice pre- immune with common-cold CoV. We will determine how intranasal boosting modulates IgA-secreting plasma cells and IgA memory B cells that home back to the respiratory mucosa in SARS-CoV-2 immune mice and in mice immune against common-cold coronaviruses. We will use cre-lox inducible, IgA-secreting cell and IgA memory B cell fluorescent reporter mice to define how intranasal boosting modulates mucosal IgA immunity. We will also test adjuvant and intranasal safety using a human lymph node organoid model from upper- respiratory tract draining lymph tissue from humans. Aim 3: Test the hypothesis that durable mucosal IgA can protect against transmissible SARS-CoV-2 variants in hamster transmission models and protect against SARS-related coronaviruses. We will determine if the mastoparan-7 and CpG adjuvanted nanoparticle intranasal booster reduces transmission of SARS-CoV-2 variants in hamster models. We will also use IgA knockout mice to determine if IgA is required for protection against SARS-like viruses.

# data[].attributes.keywords[]
Middle East Respiratory Syndrome Coronavirus

# data[].attributes.title
Detection of Shigella Species in Wastewater - A Pilot Study for Community and Building Scale Wastewater-Based Surveillance of Bacterial Pathogens

# data[].attributes.funder_divisions[]
National Institute of Allergy and Infectious Diseases (NIAID)

# data[].attributes.abstract
/ Abstract  Bacillary dysentery or shigellosis is caused by bacteria of the Shigella species: S. dysenteriae, S. flexneri, S boydii, and S. sonnei. Infections range from mild or asymptomatic to severe bloody diarrhea, so reported prevalence grossly underestimates actual prevalence. Shigellosis is a global public health concern and antimicrobial resistance has compounded the problem. Moreover, shigellosis is also sexually transmitted in the United States, Europe, and other developed countries. Such outbreaks are driven by the emergence of antibiotic resistant strains of S. flexneri infecting men who have sex with men.  The objective of this proof-of-concept study is to demonstrate that wastewater-based epidemiology (WBE) using digital PCR to detect pathogen molecular markers can provide a more accurate picture of community prevalence of bacterial pathogens than traditional case reporting. Wastewater surveillance for viral pathogens has been in use for decades and its use to monitor SARS-CoV-2 is now widely applied globally. Analogous methods for wastewater surveillance of bacterial pathogens by digital PCR has lagged. We will develop and validate methods to detect Shigella, an important bacterial agent of diarrheal disease, in wastewater. We will also field test the methods to assess shigellosis prevalence at community and building scale and link the data to the actual population residing in the wastewater collection area. We will provide actionable data to the local health department which can then develop targeted public health interventions. The independent but complementary aims in demonstrating the proof-of-concept are: 1. Develop and validate sensitive, specific, and reproducible WBE methods for detection of Shigella  species in wastewater using digital PCR. Three subaims will: 1.1) optimize methods for extraction and  detection of Shigella in wastewater using laboratory-grown strains of Shigella species to “spike” authentic  wastewater and laboratory prepared “synthetic” wastewater; 1.2) validate molecular targets for  differentiation of S. flexneri from S. sonnei in wastewater; and 1.3) culture of Shigella from wastewater to  assess antibiotic resistance genotypes and phenotypes. 2. Assess proof-of-concept of WBE as a public health tool for Shigella at community and building  scale with emphasis on high risk congregate populations, i.e., day care centers. Two subaims will:  2.1) measure the prevalence of Shigella species at community scale by sampling at the wastewater  treatment plant intake and using wastewater flow rate as a population normalization marker; and 2.2)  extend shigellosis surveillance to building scale targeting high risk congregate pediatric populations. Strengths of this proposal are the innovative application of WBE to a bacterial pathogen, our method for population normalization, differentiation of Shigella species, prevalence measurement of Shigella species at community and building scale, and the expertise of our multidisciplinary team.

# data[].attributes.keywords[]
Centers for Disease Control and Prevention (U.S.)

# data[].attributes.title
Biophysical constraints on antibody affinity maturation to SARS-CoV-2

# data[].attributes.funder_divisions[]
National Institute of Allergy and Infectious Diseases (NIAID)

# data[].attributes.abstract
The objective of this proposal is to develop a quantitative understanding of how the biophysical properties of antibodies impact their capacity to evolve affinity to divergent SARS-CoV-2 spike variants. Though there is substantial evidence that mutations acquired during affinity maturation impact antibody expression, affinity for distinct viral variants, and self-reactivity, we lack a quantitative understanding of (1) how mutations impact these biophysical properties and (2) how these properties, and trade-offs between them, collectively determine the fate of the corresponding B-cell lineage. Here, we propose three Aims to test our hypothesis that mutations differentially impact antibody expression, affinity, and self-reactivity, resulting in biophysical trade-offs that constrain the evolution of antibodies that bind divergent SARS-CoV-2 spike variants. In Aim 1, we quantitate the biophysical effects of mutations in anti-SARS-CoV-2 spike antibodies, using high-throughput mammalian cell- display methods we recently developed. By measuring the expression, affinity, and self-reactivity for millions of anti-spike antibodies, including broadly neutralizing antibodies (bnAbs) that bind divergent spike variants, their evolutionary predecessors, and systematically mutagenized antibody sequences, we will unveil biophysical constraints that shape affinity maturation to rapidly evolving viral antigens. In Aim 2, we evaluate the contributions of antibody biophysical properties to B-cell fitness, or proliferation, using longitudinally-sampled patient B-cells following exposure to divergent strains of SARS-CoV-2. This approach will reveal the relative importance of distinct antibody biophysical properties in driving B-cell evolutionary dynamics in human repertoires and enable development of quantitative models for predicting the outcomes of affinity maturation. In Aim 3, we define the impact of selection pressure during affinity maturation on the biophysical properties of the resulting antibodies, focusing on selection regimes known to favor the maturation of bnAbs that bind distinct spike variants. To this end, we leverage a B-cell directed evolution platform that mimics the mutagenic load of somatic hypermutation, enables fine-tuning of the antibody selection conditions, and supports longitudinal B-cell sampling to profile the evolutionary dynamics of the B-cell response and the biophysical properties of the corresponding antibody lineages. The resulting data will be used to define the impact of the selection regime on the biophysical determinants of B-cell fitness. Successful completion of these Aims will yield quantitative insight into (1) how antibody biophysical properties change during affinity maturation, (2) how they collectively determine B-cell fate in human repertoires, and (3) how their relative importance varies across distinct selection regimes. Thus, this work will advance our fundamental understanding of the biophysical mechanisms that shape antibody affinity maturation to rapidly evolving pathogens like SARS-CoV-2, supporting efforts to design and elicit antibodies that bind existing and novel viral variants.

# data[].attributes.title
Molecular Mechanisms of Antimicrobial Resistance from Machine Learning Augmented Enhanced Sampling

# data[].attributes.funder_divisions[]
National Institute of General Medical Sciences (NIGMS)

# data[].attributes.abstract
ABSTRACT: Antimicrobial resistance threatens our ability to treat previously curable infectious diseases and may soon become a global public health crisis. The Ray group aims to understand and characterize the molecular mechanisms of antibiotic and antiviral resistance to identify potential avenues to target resistant pathogens. This R35 MIRA pro- gram involves two distinct research projects that utilize advanced machine learning (ML) and enhanced sampling algorithms for molecular dynamics (MD) simulations to gain mechanistic insights into antimicrobial resistance and facilitate the development of future therapeutic applications. In the first project, we will study the process of ligand binding to riboswitches, a class of regulatory RNA segments that are potential targets for next-generation antibi- otics. Our goal is to identify the role of conformational dynamics and distant nucleotide mutations in modulating the binding mechanism of the small molecule inhibitors (e.g., Ribocil) to RNA targets (e.g., Flavin-mononucleotide (FMN) riboswitch). We will design neural network (NN) and explainable artificial intelligence (XAI) based collec- tive variables from system agnostic descriptor space and perform enhanced sampling simulations to compute the free energy landscape of riboswitch conformational transition and ligand binding. This work will provide key mechanistic insights into RNA-small-molecule interactions and pave the way for designing more resilient antibi- otics. In the second project, we will study how resistant mutations in the viral antigens, e.g., SARS-CoV-2 spike protein, affect the binding mechanism of neutralizing antibodies. Previous research in this area primarily focused on the antigen-antibody interface but often overlooked the long-range allosteric effect of antigen mutations on the antibody binding process. We will perform NN and XAI-guided enhanced sampling simulations to elucidate the mechanistic details of antigen-antibody recognition. In addition, we will trace the allosteric communication path- ways using mutual-information-based protein graph connectivity networks constructed for various intermediate configurations sampled from the association pathway. This work will open new avenues for the rational design of broad-spectrum monoclonal antibodies through the judicious strengthening of distant regions of the antibody structure that are less susceptible to epitope mutations.

# data[].attributes.title
Molecular evolution of entry receptor usage underlying zoonotic human betacoronaviruses

# data[].attributes.funder_divisions[]
National Institute of Allergy and Infectious Diseases (NIAID)

# data[].attributes.awardee_organization.name
UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH

# data[].attributes.abstract
Most human viruses originate from recent zoonotic spillover, but the upstream evolutionary processes in animal reservoirs that drive zoonosis-promoting traits remain poorly understood. Our long-term goal is to elucidate the evolutionary forces enabling animal viruses to acquire traits facilitating human spillover and adaptation, with a focus on viral entry receptor usage as a critical determinant of cross-species transmission. Toward this end, this proposal investigates the evolutionary dynamics underlying changes in receptor-binding specificity in beta-coronaviruses (CoVs) linked to past and potential future zoonoses: SARS-CoV-2, MERS- CoV, and HKU1 alongside their bat, rodent, and other animal relatives. Our central model is that long-term evolutionary arms races between viruses and wildlife hosts drive evolvable mechanisms of receptor- engagement promoting subsequent human spillover and adaptation. This model will be examined through three specific aims: (1) Identify mechanisms driving human receptor binding in bat SARS-related CoVs; (2) Dissect the origins and consequences of receptor-switching in bat MERS-related CoVs; and (3) Identify evolutionary origins of and functional constraints imposed by a newly discovered HKU1 CoV receptor. In each aim, we combine phylogenetic surveys across diverse animal CoVs with high-throughput mutagenesis screens to map the evolutionary, genetic, and structural mechanisms driving receptor-use transitions and their downstream evolutionary consequences. These studies will illuminate how host-virus dynamics shape receptor-binding architectures to enable zoonotic potential and post-spillover antigenic evolution. The resulting large-scale genotype-phenotype maps will inform computational models for assessing viral zoonotic risk and guide the design of broad-spectrum antibody and vaccine therapeutics for pandemic preparedness. Taken together, this work advances understanding of mechanisms of viral evolution while providing actionable insights for proactive ecological, diagnostic, and therapeutic interventions.

# data[].attributes.keywords[]
Middle East Respiratory Syndrome Coronavirus

# data[].attributes.funder_divisions[]
National Institute of Allergy and Infectious Diseases (NIAID)

# data[].attributes.abstract
Type I interferon (IFN) is the first line of defense in innate antiviral immunity, orchestrating transcriptional and metabolic responses that restrict viral replication. While IFN signaling is known to modulate sterol and glycerolipid pathways, its impact on sphingolipids (SPLs)—a class of bioactive lipids involved in immune signaling and cell stress responses—remains poorly understood. Mounting evidence suggests that infections by RNA viruses, including flaviviruses and coronaviruses, induce the accumulation of ceramide (Cer), but whether this promotes viral replication or enhances antiviral defenses is unclear. Our preliminary studies show that Zika virus (ZIKV) triggers overall changes in SPL composition and relies on Cer biosynthesis for successful infection. However, other studies implicate Cer in restricting viral replication and promoting cell survival, raising the possibility that these lipids are upregulated by the host response rather than the virus. The central goal of this proposal is to uncover how type I IFN affects SPL metabolism and to determine whether these lipids, in turn, control the IFN response and infection outcomes. We hypothesize that SPLs, particularly Cer, play a dual role in infection and immunity. Viruses may induce Cer to suppress innate immune responses, including IFN production, as suggested by the known roles of Cer in modulating host signaling pathways. However, we also propose that IFN itself alters SPL metabolism, as it does with other lipid classes, and that these IFN-induced lipid changes may contribute to antiviral defense. To disentangle these possibilities, we will use a combination of untargeted lipidomics, innovative SPL probes, CRISPR gene editing, and organelle-targeted lipid perturbation to systematically determine the causes and consequences of SPL dysregulation in infection. Aim 1 will define how IFN-β alters SPL content and distribution in infected and uninfected cells. In doing so, we will generate the first comprehensive map of IFN-driven changes in the cellular lipidome—including SPLs—across multiple cell types, providing a foundational resource for the broader virology and immunometabolism communities. Aim 2 will determine whether Cer regulates IFN-β signaling and antiviral defense, and whether the subcellular location of Cer influences its role as a pro- or anti-viral signal. Together, these studies will determine how IFN shapes and is shaped by SPLs, providing fundamental insight into the role of these lipids in the earliest steps of antiviral innate immunity.

# data[].attributes.keywords[]
Clustered Regularly Interspaced Short Palindromic Repeats

# data[].attributes.title
Lymphotoxin-dependent control of long COVID

# data[].attributes.funder_divisions[]
National Institute of Allergy and Infectious Diseases (NIAID)

# data[].attributes.abstract
SARS-CoV-2 infection causes acute lung pathology and can lead to long-term complications, collectively known as long COVID. These complications include persistent pain, headaches, myalgia, and post-exertional malaise. However, the mechanisms behind these neurological symptoms remain poorly understood. In particular, the role of sensory neurons in the pathogenesis of long COVID is largely unexplored. This knowledge gap hinders the development of novel therapeutic strategies for managing neurological complications associated with long COVID. Animal models are essential for investigating the role of sensory neurons in SARS-CoV-2 infection and testing preclinical interventions. Unfortunately, existing mouse models that allow for the study of SARS-CoV-2 specific effects on sensory neurons in vivo are lacking. In our research, we found that wild-type mice infected with a mouse- adapted SARS-CoV-2 strain develop long-term pain. To further explore the role of sensory neurons in long COVID, we developed a mouse model with selective SARS-CoV-2 infection of sensory neurons through hACE2 expression in Nav1.8+ neurons. Additionally, we identified lymphotoxin beta receptor (LTβR) as a novel immune regulator of chronic pain following SARS-CoV-2 infection. The objective of this proposal is to investigate the role of LTβR signaling in sensory neurons in the pathogenesis of long COVID and to test the potential of LTβR antagonist to mitigate neurological complications of long COVID. Our central hypothesis is that LTβR signaling in sensory neurons promotes long COVID neurological symptoms which can be ameliorated by administration of LTβR antagonist. This hypothesis will be tested through two specific aims. In Aim 1, we will define the impact of LTβR signaling in sensory neurons on long COVID neurological symptoms, viral replication, and immune cell changes in sensory ganglia, using mice with selective LTβR inactivation in Nav1.8+ sensory neurons. In Aim 2, we will assess the therapeutic effects of LTβR antagonist in alleviating long COVID neurological symptoms and identify critical LTβR-dependent pathways in sensory ganglia using single-cell RNA sequencing. This proposal is innovative, significant and impactful, as it will elucidate the role of sensory neurons in long COVID pain, establish new animal models for studying long COVID, and evaluate the therapeutic potential of LTβR antagonists for treating SARS-CoV-2-induced neurological complications.

# data[].attributes.title
Identification of Novel Targets for Enhancing Targeted RNA Degradation in Antiviral Discovery

# data[].attributes.funder_divisions[]
National Institute of Allergy and Infectious Diseases (NIAID)

# data[].attributes.abstract
/ ABSTRACT  The development of targeted RNA degradation (TRD) technologies, such as RNA-degrading chimeras, holds significant promise for antiviral therapies by reducing viral RNA levels to prevent viral replication. Despite their potential, current TRD mechanisms exhibit limited potency. In various literature reports, ribonuclease- targeting chimeras (RIBOTACs) exemplify this problem, achieving only ~75% maximum degradation of distinct RNA targets in cells. For example, our preliminary work optimized a synthetic RNA ligand, C34, which binds robustly to an RNA G bulge in the 5’ untranslated region of SARS-CoV-2’s RNA genome with a low nanomolar dissociation constant. However, the minimum inhibitory concentration (MIC) of the C34-based RIBOTAC remained moderately high at 20 μM in SARS-CoV-2-infected cells, indicating insufficient cellular potency. RIBOTAC is a drug-induced TRD modality utilizing an endogenous ribonuclease, RNase L. Interestingly, this RIBOTAC potency cap in cells was not observed in cell-free assays using purified recombinant RNase L, indicating the possible presence of cellular factors that inhibit the RNase L degradation complex. To address this potency limitation, the proposed project aims to discover novel cellular targets to significantly enhance RNase L activity and brand-new TRD mechanisms for future drug development through two specific aims. Aim 1 focuses on identifying cellular determinants that inhibit RNase L-dependent RIBOTAC activity using a genome-wide CRISPR knockout screen. By targeting these inhibitory genes, we aim to significantly boost the efficacy of existing RIBOTACs. Aim 2 focuses on discovering novel cellular targets for TRD by performing genome-wide screenings in three screening platforms. We will utilize a plasmid library comprising ~14,000 open reading frames from the human genome to identify candidate genes that can effectively induce TRD through drug-induced proximity. Both aims will leverage a SARS-CoV-2 cellular model and our optimized RNA ligand C34 to validate these new mechanisms in antiviral research. Ultimately, this project seeks to expand our chemical genetics toolbox by unveiling new mechanisms and targets for RNA degradation. These advancements will be pivotal in developing new chimeric molecules designed to combat a variety of infectious diseases, significantly enhancing our capacity to address global health challenges. 1

# data[].attributes.keywords[]
Clustered Regularly Interspaced Short Palindromic Repeats

# data[].attributes.title
Mechanisms of simian arterivirus entry, immune evasion, and zoonotic potential

# data[].attributes.funder_divisions[]
National Institute of Allergy and Infectious Diseases (NIAID)

# data[].attributes.abstract
Many emerging zoonotic viruses (animal viruses that transmit to humans) are highly pathogenic, having the potential to cause deadly epidemics or even global pandemics. The risks zoonotic viruses pose are highlighted by the emergence of the SARS/MERS coronaviruses, Ebola virus, and HIV-1, all of which are related to animal viruses that were unknown before they caused substantial cases of disease in humans. Given the risk animal viruses pose to humans, many researchers have turned to viral discovery—using genome sequencing tools and metagenomic analyses, researchers hope to identify novel animal viruses before they emerge in humans. We've developed a pipeline that integrates viral surveillance with molecular investigations in the laboratory to identify pre-emergent viruses with epidemic potential. Using this approach, we've provided compelling evidence suggesting that simian arteriviruses (SAVs)—understudied and neglected pathogens of African monkeys—are poised for spillover, posing a threat to human health. We demonstrate key biological features that poise SAVs for zoonosis, including: (1) compatibility with human receptors; (2) high titer propagation in human cells; and (3) potential for evasion of human innate immunity. Further interrogation of the biology of SAV infection is crucial for future epidemic preparedness efforts.  The objective of this proposal is to uncover mechanisms of cell entry, immune evasion, and zoonotic potential for these highly concerning viral pathogens. In Aim 1, we employ a series of molecular, biochemical, structural, and functional approaches to define SAV-receptor interactions and establish proof-of-concept strategies for future therapeutics—an essential step in outbreak preparedness. In Aim 2, we will identify SAV proteins that antagonize the human innate immune response, with the goal of revealing vulnerabilities that may help develop safe and effective antiviral approaches. In Aim 3, we will thoroughly evaluate the zoonotic potential of diverse SAVs. This includes: (1) identifying novel SAVs through whole virome sequencing of wild African primate biomaterials; (2) the development and application of non-human primate induced-pluripotent stem cell (iPSC)-derived macrophages to isolate novel SAVs in cell targets from natural host species; and (3) detailed infection studies in human cells to evaluate human compatibility. Further, we will perform the first in-depth serosurvey for SAV exposure history using banked sera from a Ugandan case-control cohort. When taken together, this proposal will lead to a deeper understanding of the molecular biology and pathogenesis of these understudied viruses, as well as a greater appreciation for the zoonotic risk that they pose. It is imperative that we invest in characterizing the biology and pathogenesis of SAVs now so that we may begin to develop platform technologies (i.e., diagnostics, vaccines, therapeutics) in case they do emerge in the future.

# data[].attributes.keywords[]
Middle East Respiratory Syndrome Coronavirus

# data[].attributes.title
Intelligent biosensing system for automated real-time monitoring of airborne pathogens for safe indoor environments

# data[].attributes.funder_divisions[]
National Institute of Allergy and Infectious Diseases (NIAID)

# data[].attributes.awardee_organization.name
UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN

# data[].attributes.abstract
The increasing frequency of respiratory infectious diseases, such as influenza and COVID-19, which can spread rapidly and lead to severe outbreaks, necessitates that we re-envision our approaches to monitor pathogen exposures in the indoor environments. Current surveillance methods mostly depend on syndromic data from hospital admissions, clinic visits, and school absenteeism rates. However, these approaches can lead to underestimation and delay in disease surveillance due to no reporting of mild or asymptomatic cases, lack of access to healthcare, and time-consuming lab and diagnostic processes. A proactive approach in combating airborne diseases requires early detection of target pathogens. Here, we propose to innovate an intelligent system capable of real-time, efficient, and cost-effective monitoring of airborne pathogens in the environment. We will build upon our preliminary success in automated bioaerosol sampling and pathogen detection, to create an Airborne Pathogen Sensing (APS) system. This goal will be achieved by focusing on two specific aims. First, we will create a novel class of modular whole-cell biosensors for sensitive, rapid, and robust detection of multiple critical airborne pathogens. The pathogen detection will be achieved by creating quenchbody (Q-body) display biosensors, where target specific quenchbody is expressed and displayed on the surface of microbial host cells. When the Q-body binds to its antigen (target pathogen), the fluorescence intensity substantially increases via the antigen-dependent removal of the quenching effect on the fluorophore. Second, we will design and build a portable and automated bioaerosol sampling device that can be coupled to the biosensing and signal detection systems. To this end, we will evaluate and optimize two sampling devices: mist chamber and biosampler, and choose the device with the highest bioaerosol capture efficiency. Finally, we will integrate the biosensing component with the bioaerosol sampling device and an automated flow-through fluorescence detection system to achieve automated real-time monitoring of airborne pathogens.