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Postdoctoral Fellowship: PRFB: How host immunity drives the evolution of pathogen virulence

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This action funds an NSF Postdoctoral Research Fellowship in Biology for FY 2025. The fellowship supports research and training of the fellow that will contribute to biology in innovative ways. This research will improve our understanding of how pathogens evolve. More clearly than ever following the COVID-19 pandemic, pathogens can evolve extremely rapidly with global impacts. One of the most important ways that pathogens evolve is in their virulence, the harm they inflict upon their hosts. Understanding and predicting how pathogen virulence will evolve is paramount for fields from vaccine design to epidemiology, agriculture, and healthcare. The evolution of virulence can be shaped by numerous factors, but one of the most important factors that every pathogen interacts with is the host’s immune system. This project will test how immunity influences pathogen evolution, using experimental and simulation methodologies to build a predictive understanding of how pathogen virulence is shaped by the host immune system. The results of this research have broad implications, including for public health. This fellowship will also support mentorship, training, and education for undergraduate and graduate students.    To test how immunity influences pathogen evolution, this project will use mathematical models and laboratory experiments. It aims to answer two questions: 1) how do different parts of the immune system individually shape pathogen virulence evolution, and 2) how does variation in immunity between hosts in a population shape pathogen virulence evolution. To answer these questions, this project leverages an extremely powerful laboratory model system: Caenorhabditis elegans nematodes. These nematodes are easy to experiment with, and their innate immune system shares many similarities with mammals. In this research, C. elegans will be experimentally infected with a widespread bacterial pathogen, Pseudomonas aeruginosa, to directly observe how Pseudomonas evolves depending on the immune state of C. elegans. Experimental measurements will be integrated with mathematical models to directly test how well model predictions match experimental outcomes. Through the course of this fellowship training, the fellow will develop expertise with C. elegans-bacteria systems, build essential bioinformatic skills, and gain experience with evolutionary modeling. The broader impacts of this project include potential applications in public health policy and vaccine design, mentorship and hands-on research training for undergraduate students, development of a peer mentorship program for graduate students, and instructional modules that integrate research into undergraduate 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.

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I-Corps: Translation Potential of Voice Analysis to Pre-screen Airborne Diseases

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Technology, Innovation and Partnerships (TIP)

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This I-Corps project focuses on the development of a non-invasive digital health solution that uses voice and biometric signals collected from smart devices to pre-screen for respiratory illnesses such as respiratory syncytial virus (RSV), influenza, and COVID-19. The technology addresses a growing national health concern: the delayed detection and spread of airborne diseases, which strain healthcare systems, reduce workplace productivity, and threaten public health—particularly in crowded or high-risk environments like schools, airports, and hospitals. The solution aims to empower individuals with early warning tools, allowing them to take preventative action before symptoms worsen or spread to others. By minimizing unnecessary clinic visits, enabling quicker triage, and supporting population-level monitoring, this technology promotes national health and welfare while contributing to more resilient and responsive healthcare infrastructures.    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 voice-enabled biometric monitoring system powered by machine learning algorithms that analyze deviations from a user's baseline in real time. The system integrates voice modulations, heart rate, and temperature data, and correlates them with clinically observed patterns of respiratory illness. Recent advances in mobile computing, edge artificial intelligence (AI), and signal processing enable the secure and scalable deployment of this solution across smartphones, wearables, and smart speakers. Unlike traditional diagnostics, this technology offers a passive and continuous approach to health surveillance, benefiting users through earlier detection, reduced costs, and improved public health coordination.    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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Collaborative Research: Optimized Testing Strategies for Fighting Pandemics:  Fundamental Limits and Efficient Algorithms

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Large-scale high-throughput prevalence and diagnostic testing is essential for the containment and mitigation of pandemics. The testing bottleneck in the COVID-19 pandemic has led to a resurgence of interest in group testing, where several people's biological samples are mixed together and examined in a single test. When the rate of infection in the population is low, this method can significantly reduce the total number of tests per subject and increase the throughput of the existing testing infrastructure. However, traditional group testing has the following limitations: First, efficient group testing based methods for the estimation of prevalence have been largely overlooked in the literature. Second, traditional group testing usually assumes that the testing results are qualitative (positive versus negative), not quantitative (providing viral load information). Third, the theoretical study of group testing rarely takes practical constraints, such as the sensitivity of the pooled tests and the dilution effect, into consideration, which hinders the applicability of the testing schemes in practice. The goal of this project is to overcome these limitations of traditional group testing and design advanced pooled testing strategies for efficient prevalence tracking and accurate infection diagnosis. It will develop optimized pooled testing strategies with strong theoretical performance guarantees yet feasible and cost-effective in practice.    The proposed research is organized in three research thrusts as follows. Thrust 1 aims to design effective sampling and testing algorithms to estimate the prevalence in communities and track its evolution, under scarce testing resource constraints. Thrust 2 focuses on the design of optimized pooling and decoding algorithms for compressed sensing based (COVID-19) virus diagnostic testing. Thrust 3 validates the accuracy and efficiency of the proposed pooled testing through experiments on anonymized COVID-19 samples. This project bridges group testing and online learning, the two largely disconnected areas, with the objective to effectively allocate limited testing resources for efficient prevalence tracking. Such integration leads to novel sampling strategies, broadens the paradigm of group testing, and advances the state of the art of online learning. Moreover, the proposed compressed sensing based diagnostic testing leverages quantitative measurements provided by advanced testing technologies, which can significantly increase test throughput, reduce the number of needed tests, decrease the consumption of scarce reagents, and provide results robust against observation noises and outliers. The rich compressed sensing theory provides possible approaches to the rigorous mathematical certification of the correctness of the decoded results. Besides, the clinical constraints on pooled testing also lead to novel problem formulation and theoretical characterization, enriching the study of compressed sensing.    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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Increasing naloxone availability and use in high-risk settings: public libraries as partners for reducing opioid overdose mortality

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Opioid overdose mortality has increased substantially since the start of the COVID-19 pandemic. Opioid overdose deaths are preventable and can be reversed with the timely receipt of naloxone. To date, naloxone distribution and implementation programs have targeted traditional first responders (e.g., EMS) as well as people with opioid use disorder and their social networks. While these initiatives have resulted in measurable reductions in opioid overdose mortality, major gaps in naloxone availability and use persist. The overarching goal of this work is to save lives by advancing evidence regarding place-based naloxone implementation and overdose reversal readiness in high-risk settings, using public libraries as a test case. More than one in ten public libraries experienced an on-site overdose in 2022. In addition, public libraries—which host 1.2 billion in-person visits annually and are within 2 miles of most Americans’ homes—are an important safety net for vulnerable populations, including those with substance use disorders. For these reasons, libraries represent a novel setting to promote naloxone uptake. There have been nascent efforts to equip libraries with naloxone, however, uptake remains low. Thus, we aim to understand institutional barriers to and facilitators of naloxone uptake (Aim 1). Then, we will establish a Public Libraries Cohort (PLC) to monitor and identify drivers of naloxone uptake and incidence and outcomes of overdose among public libraries (Aim 2). Aim 3 will compare the efficacy of two web-based interventions (facilitator-guided and self-guided training), each vs. the other and vs. usual care, on increasing both overdose reversal readiness and naloxone uptake in libraries. This work will advance the evidence for place-based naloxone implementation and overdose prevention.

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Molecular and Functional Characterization of Transcriptionally Defined Subpopulations of VTA Dopamine Neurons

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Substance use disorder is a complex neurobiological disease characterized by a loss of control over drug-taking and drug-seeking behaviors. Further exacerbated by the COVID-19 pandemic, the rate of drug-related overdoses and subsequent deaths has increased dramatically over the past decade, surpassing 107,000 in 2022. All drugs of abuse increase dopamine (DA) transmission within the nucleus accumbens (NAc) from DA projections from the ventral tegmental area (VTA). While the presence of tyrosine hydroxylase (Th) has long been used to identify DA neurons, more recent studies have revealed remarkable heterogeneity among VTA DA neurons, with some neurons co-expressing markers for both DA and glutamate (Glut) transmission that are similarly Th+. However, the role of DA-only compared to combinatorial cells in substance use disorder is currently unknown. Using single nucleus RNA sequencing to comprehensively profile the VTA, we previously identified unique markers for these two subpopulations of DA neurons. Slc26a7, a gene that encodes an anion transporter, serves as a selective marker for combinatorial neurons that harbor expression of genes implicated in both Glut and DA synthesis and neurotransmission. Likewise, the GTP cyclohydrolase Gch1 was identified as a marker for DA-only neurons. Using a fluorescent in situ hybridization protocol, I validated these findings showing the Slc26a7 marks DA+/Glut+ cells while Gch1 marks DA+/Glut- cells. I have shown unique induction of the neuronal activity marker Fos in Slc26a7+ cells in the VTA 1 hour following cocaine, but not fentanyl, experience; this same response was not observed in Gch1+ cells, suggesting a difference in response to cocaine between these two distinct DA neuron populations. These results suggest that two subpopulations of DAergic cells in the VTA respond to cocaine in unique ways and may in turn drive distinct downstream effects and behavioral responses to cocaine. Following these findings, I hypothesize that differences in cellular targets and neurophysiology confer distinct behavioral roles of DA subpopulations. Using these selective markers, I have designed and generated novel adeno-associated viruses (AAVs) to both express distinct fluorophores and manipulate the neurons in a cell-type specific way. Using these AAVs, this project aims to take a multidisciplinary approach to rigourously investigate and determine any differences in cell types through the following aims: (1) Characterize anatomical and cellular localization of projections, (2) Determine neurophysiological differences, and (3) Determine the role of combinatorial cells in behavior. The proposed studies will deepen our understanding of the role of these combinatorial cells in SUD, providing avenues for therapeutic exploration for a disease largely lacking treatment options. Under this award, I will master behavioral paradigms and electrophysiology, techniques that will aid my success as a physician-scientist.

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Multi-scale characterization of antigen-polymerized immune complexes underlying thrombotic pathologies triggered by adenoviral-vectored vaccines

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National Heart Lung and Blood Institute (NHLBI)

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Immunothrombosis is a critical element of intravascular immunity, but its dysregulation or malfunction leads to a range of thrombotic disorders including stroke and disseminated intravascular coagulation. The massive vaccination campaign during the recent COVID-19 pandemic brought to light a novel immunothrombotic pathology, a relatively rare but extremely dangerous side effect of adenoviral (Ad) vectored vaccines, which is now known as vaccine-induced immune thrombotic thrombocytopenia (VITT). Although COVID-19 is no longer a global health threat, the close association of VITT with a specific delivery vector raises the specter of other Ad- vectored vaccines also eliciting this deadly side effect, a grave prospect given the popularity of this platform. VITT has been linked to the emergence of autoantibodies recognizing a cognate chemokine, platelet factor 4 (PF4), but the specific mechanism underlying this pathology remains elusive. Understanding its molecular mechanism and etiology is critical for addressing the currently unmet need to design rational therapeutic and prophylactic strategies targeting VITT. It will also go a long way towards filling the gaps in understanding the delicate interplay between the beneficial and deleterious effects of immunothrombosis and provide the urgently needed ammunition to suppress the latter without sacrificing the former. We will use a combination of experimental and modeling tools to study VITT emergence and progression on different scales, ranging from micro- (formation of platelet-activating immune complexes) to macroscale (thrombi formation). We have already obtained a complete amino acid sequence of the pathogenic VITT antibody and produced its recombinant copy (RVT1) in quantities sufficient for both biophysical and biological investigations. On the microscale, we will use mass spectrometry and other biophysical tools to study the architecture and biological properties of the immune complexes composed of PF4 and RVT1. On the macro-scale, we will use these complexes to study thrombi initiation and formation using in vitro models based on microfluidic devices mimicking vascular environments relevant for VITT pathogenesis (e.g., cerebral venous vasculature). Bridging the micro- and macro-scales will allow us to elucidate the detailed mechanism of VITT progression by understanding how the disease outcome is modulated by the physical and biochemical properties of its molecular triggers. It will also provide a unique opportunity to address another enigmatic feature of VITT - its frequent localization within the cerebral venous sinuses. Lastly, correlating the amino acid sequences of the pathogenic antibodies and the germline sequences for a set of VITT patients will reveal the etiology of this disease, enabling the design of effective prophylactic and monitoring strategies. The proposed research will be carried out by an interdisciplinary team comprising chemists and biophysicists (Dr. Kaltashov's lab at UMass-Amherst), hematologists and molecular biologists (Dr. Nazy's lab at McMaster University School of Medicine) and biomedical engineers (Dr. Jiménez' lab at UMass-Amherst).

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Platelet-MLKL role in S100 Release with Age and Infection

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Advanced age is a single risk factor for developing serious complications from infections with respiratory viruses such as influenza, SARS-CoV-2 or RSV. These complications are reflected in thrombotic outcomes including microthrombosis, myocardial infarction and pulmonary embolism. The actual cause and mechanisms of these thrombotic outcomes remains elusive. Pathogen spreading and crossover of these viruses into the circulation is regulated by various mechanisms, some of which involve lytic programmed cell death pathways such as necroptosis executed by membrane channels formed by oligomerized phosho-Mixed Lineage Kinase Domain Like Pseudokinase (MLKL). Platelets express MLKL, have a plethora of immune-sensing viral receptors and are the major blood component responsible for thrombotic outcomes. We have shown that respiratory viral RNA can be found in circulating platelets from influenza patients and preliminary result support channel formation. In this proposal, we hypothesize that platelet-pMLKL channel formation, mediated by influenza, leads to cytoplasmic S100 content release and contributes to immunothrombosis with age. We propose to test this hypothesis with the following aims: 1. Determine the MLKL-specific platelet content release and whether platelets undergo necroptosis as a result of influenza and (or) age, and 2. Determine the contribution of age to MLKL-activation and immunothrombotic aggregates during infection. The proposed studies are central to elucidating mechanisms that may increase immunothrombotic risk and adverse cardiovascular outcomes beyond classical platelet activation, with advanced age, and provide a basis for novel and targeted treatments for prevention.

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Multidisciplinary studies on overcoming SARS-CoV-2 main protease drug resistance and on fitness costs

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National Institute of Allergy and Infectious Diseases (NIAID)

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The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused a global pandemic since first emerging in 2019. Since, Pfizer, Inc. (USA) developed Paxlovid™, an FDA-approved antiviral containing the protease inhibitor nirmatrelvir (NIR) that has seen moderate success in treating SARS-CoV-2 infections. The main protease (Mpro) of SARS-CoV-2 cleaves the viral polyproteins to release proteins essential for replication. NIR mimics the Mpro consensus sequence, thus covalently blocking Mpro activity and viral replication. However, resistance mutations to NIR have started to develop as its use increases globally. Understanding how such substitutions confer resistance and balance the impacts on fitness will enable the strategic design of the next generation of Mpro inhibitors. My preliminary data and published experiments have identified drug resistance mutations (DRMs) in Mpro that confer significant resistance to NIR including E166V. Further, I have demonstrated that the E166V substitution remains susceptible to GC376, a feline coronavirus protease inhibitor, and PF-00835231, developed during the SARS-CoV-1 epidemic. E166V also severely decreases viral fitness and requires compensatory mutations such as L50F to rescue fitness. Despite this fitness cost, E166V and L50F/E166V were both observed in patients treated with Paxlovid™ during the clinical trial, and recent case studies also identified the L50V/E166V combination. It is unclear how E166V decreases fitness and why mutations at Leu50 restore fitness. Structural work from other labs and my preliminary data indicate Mpro forms an active homodimer with the N-terminus from the opposite protomer interacting with Glu166. Loss of these interactions due to the E166V mutation are likely to disrupt Mpro dimerization and, consequently, activity. Of note, dimerization has not been studied in the context of drug resistance, and the role of Leu50 mutations in restoring fitness is poorly understood. Building upon my previous work, I will analyze E166V and L50V/E166V using virological, biophysical, and structural techniques. The goal of my project is to characterize mechanisms of NIR resistance, determine how DRMs impact Mpro activity and fitness, and investigate strategies for overcoming NIR resistance. I hypothesize that DRMs alter the intermolecular interactions in the active site resulting in decreased binding of inhibitors and Mpro dimer formation. Aim 1 will characterize the effect of the selected substitutions on Mpro resistance to NIR, GC376, PF-00835231, and a novel inhibitor shown to inhibit E166V Mpro (NIP-22c) using a virus-like particle (VLP) assay (Aim 1.1) and elucidate the mechanism of and strategies for overcoming NIR resistance using biochemical (Aim 1.2) and crystallographic studies (Aim 1.3). Aim 2 will investigate the effect of E166V and L50V on viral replication efficiency in cells (Aim 2.1) and on Mpro dimerization in vitro using biochemical methods (Aim 2.2). This project will provide valuable insights into mechanisms of drug resistance, impacts on viral fitness, and strategies for overcoming NIR-resistant SARS-CoV-2 Mpro informing the design of next-generation antivirals targeting Mpro and future development of pan-coronavirus antivirals. Completing this project will train me in techniques and skills essential for my future career as an independent scientist.

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From humans and eukaryotes to viruses and pathogens; how transition metals shape catalysis and allostery

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National Institute of General Medical Sciences (NIGMS)

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Metalloproteins play a crucial but poorly understood role in how viruses manipulate their hosts and how key cellular processes are regulated in eukaryotes, parasites, and viruses. Our proposed research program for the next five years aims to bridge the existing knowledge gap about how metal ions affect the function of enzymes that are at the nexus of host-pathogen interface, immune response, and dNTP homeostasis. Our strategy is a conceptualization of our ideas about how metal ions tune activity and regulation of two important enzyme super- families: viral proteases and SAMHD1 dNTPases.  Viral proteases. Viral polyprotein complexes enclose proteases that not only release the non-structural proteins required for replication of the viral genome but also harbor moonlighting activities that intercept host protein function, ultimately derailing immune defense. A number of viral proteases coordinate an essential for function metallocofactor in a putative Zinc-finger motif that is located far from the proteolytic active site. We propose that this metallocofactor is an Fe-S cluster and that this center is a common but unrecognized element in viral proteases. We aim to dissect the metal-dependent activities of four proteases from viruses for which efficient treatments are lacking: the PLpro from Sars-Cov(2), the Nsp1α from the Porcine Reproductive and Respiratory Syndrome Virus, the putative cysteine protease (PCP) from the Hepatitis E Virus, and the 2Apro from Enterovirus 71 (hand-foot-mouth disease). Based on our results that these proteases interchangeably coordinate [4Fe-4S] clusters or Zn2+, we propose a revision of the well-accepted paradigm of Zn utilization in this class of enzymes. Our studies promise to resolve the apparent Fe-S cluster/Zn dilemma in viral proteases by establishing: i) the in vivo physiological cofactor and ii) the biological relevance of this metal binding promiscuity.  SAMHD1 dNTPases. Sterile Alpha Motif and HD-domain containing protein 1 (SAMHD1) is the only hydrolase in humans that catalyzes the breakdown of cellular deoxynucleotides (dNTPs). SAMHD1 also occurs in phylogenetically diverse organisms, such as viruses, plants, and human pathogens. This proposal exposes significant conceptual and methodological gaps about how SAMHD1 dNTPases have evolved to regulate dNTP levels essential for organism fitness. In this respect our studies promise to delineate, for the first time, molecular and chemical details that govern SAMHD1 catalysis in the human enzyme as well as the untapped pool of eukaryotic and viral orthologs. In this proposal we will: i) establish the role of Fe and Mn in activation and catalysis of human SAMHD1, ii) map the functional repertoire of newly identified SAMHD1 orthologs, and iii) shed light into the evolutionary and functional diversification of SAMHD1 dNTPases. The projected outcome will broadly provide a molecular paradigm for dNTP regulation in plants, fungi and parasites that remains entirely unexplored.

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Porcine respiratory and reproductive syndrome virus

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Examining the Relevance of Social Network Characteristics and Cognitive Aging: A Causal Inference Study

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The study embarks on an exploration of the influence of Social Network Cognitive Buffers (SNCBs), comprising both quantifiable and subjective facets of social interaction, on cognitive aging and their potential link to Alzheimer's Disease and Related Dementias (AD/ADRD). Leveraging the unique context of the COVID-19 pandemic, the research aims to assess the cognitive effects of increased social isolation in older adults and the possible recuperative outcomes of restoring social ties post-pandemic. Guided by two primary objectives, the analysis utilizes longitudinal data from the Health and Retirement Study to distinguish between objective social isolation and subjective feelings of loneliness. First, the study examines changes in cognitive aging due to the fluctuation of SNCBs among individuals aged 65 and above, shedding light on the role of social networks in cognitive health. Secondly, it delves into the diverse impacts of reduced social contact and loneliness on cognitive outcomes, probing into the protective potential of varied social connections. In particular, the research focuses on uncovering the mechanisms most responsible for acting as cognitive buffers, exploring the long-term cognitive effects of the pandemic on older adults, and investigating universal mechanisms, such as the value of social network diversity in reducing cognitive decline. By employing causal inference methodologies and panel models, the study aims to pinpoint the specific SNCBs that significantly affect cognitive health. The anticipated findings could highlight the potential benefits of reestablishing social ties in later life stages, contributing not only to the understanding of conditions like AD/ADRD but also to the broader field of aging research. The study's multifaceted approach represents a vital step in advancing the knowledge of social network effects on cognitive health and has the potential to guide public health strategies for older adults. Additionally, it serves as a significant milestone in the development of the candidate, furthering a promising career in aging research.