University Of Chicago

NIH Research Projects · FY 2025 · 2021-09

PROJECT SUMMARY Health disparities in the burden of multiple chronic conditions for low-income and racial/ethnic minority groups are pervasive and have their roots in social determinants of health and unequal access to evidence-based health care services during critical periods of life. A long history of racial segregation in the Chicago region has resulted in neighborhoods that are disproportionately burdened by poverty and related social determinants of health as well as poor access to high quality health resources. Unequal distribution of resources across the Chicago region results in geographic “hotspots” where high numbers of residents suffer from multiple cardiometabolic conditions. Innovative local solutions are necessary to bridge gaps in the healthcare system, gaps in the traditional approach to delivering preventive and management services, and gaps generated by the traditional siloed approach to science. The Chicago Chronic Condition Equity Network (C3EN) will address these gaps by strengthening collaborations across community-based organizations, practice networks, and academic researchers, by promoting a comprehensive approach to the prevention and management of multiple chronic conditions that accounts for mental health, functional health and social life, and by supporting interventions that actively seek to cross boundaries of disease-specific management, professional training, community and practice. This network will be the communication channel for multi-directional exchange of ideas regarding how to address disparities in communities, the community-based research network where both pilot studies and larger regional studies of scalable interventions will take place, and the training ground for new investigators. Our research projects have been selected to demonstrate our scientific thematic interest in promoting a comprehensive view of health that acknowledges the importance of physical, psychological, and social functioning as outcomes as well as potential avenues for health improvement. The C3EN will benefit from a foundation of multiple institutes and centers at the University of Chicago and Rush that set the stage for conducting interdisciplinary research aligned with public health goals of the Chicago region, inter-institutional collaboration, and models for training programs. Our Center’s Specific Aims are: 1) To build a Chicago regional community-based research network based on collaborations with key stakeholder groups including community-based organizations, networks of ambulatory practices, and academic institutions, to identify innovative, effective, and scalable interventions that reduce disparities for multiple chronic conditions; 2) To provide cutting edge research support and expertise (intersectoral health, informatics, implementation science, community-resource referral software systems, remote sensor technology) to facilitate chronic condition health disparities research conducted across practice networks, in community settings, and in the home; and 3) To attract and support diverse new investigators by providing education, training, mentoring, support for community and stakeholder engagement, pilot grant funding, and access to research support.

NIH Research Projects · FY 2024 · 2021-09

Project Summary Interpreting individual genome sequence and the consequence of any sequence variation is critical for the study of the genetic basis of diseases and the path toward precision medicine. Genomic sequence is at the basis of multiple levels of genome regulation which are highly intertwined, including chromatin protein binding, 3D genome architecture, and gene transcription. Decoding these regulatory functions directly from the sequence will provide a computational platform for scalable prediction of variant effects and interrogation of base pair-level sequence functions with “in silico mutagenesis”. Progress has been made in decoding regulatory genomic sequence, including with the development of deep learning sequence models. However, the sequence-basis of complex phenomena such as transcriptional regulation will not be fully resolved without accounting for genome structure and long-range 3D sequence context. Genome structures at multiple spatial scales, including promoter- enhancer interactions, transcriptional condensates, topologically associating domains, chromatin compartments, and nuclear bodies can have strong impacts on transcriptional regulation. With data and techniques that have only now become sufficient to tackle this challenge, we will study these phenomena and trace complex regulatory output back to the basis of sequence dependencies by developing sequence models of 3D genome regulatory architecture. We will develop a computational framework of deep learning sequence models with the capability of modeling multiscale 3D genome interactions and integrating long-range sequence information, for comprehensively interpreting the regulatory functions of genome sequence. The proposed work will open up new possibilities for interpreting and applying structural and transcriptional impacts of sequence variations, including asking how genetic factors, such as large structural variants, affect gene expression through remodeling of genome structural organization in healthy and disease states.

NIH Research Projects · FY 2025 · 2021-09

Project Summary/Abstract Adaptive immune response, brain development, and tumor progression all display physiology that depends on somatic mutations and genomic rearrangements among interacting cells. There is currently no widely-available tool to capture nucleotide-level variation in a tissue’s three- dimensional context. In my lab, we are developing spatial-genetic technologies to bridge this major technological gap. DNA microscopy, an imaging modality that I developed for generating spatial-genetic maps of tissue de novo (Weinstein, Regev, Zhang, Cell 2019) provides a critical foundation for this work. DNA microscopy encodes the spatial positions and nucleotide-level differences of cells into the DNA products of a stand-alone chemical reaction. The technology operates by first tagging individual DNA and RNA molecules with unique DNA barcodes, and then turning these barcoded molecules into an intercommunicating network: linking barcodes to one another at rates that depend on the distance between the original molecules. In doing so, DNA microscopy uses DNA as an imaging medium, effectively imaging a specimen from the “inside-out”. My lab’s research has two thrusts. The first of these is aimed at exploiting the fact that DNA microscopy image-capture is intrinsically volumetric, and applying it to deep-tissue three- dimensional spatial-genetic imaging. The second thrust of our research is aimed at using the phylogenetic relationships encoded into the DNA of proliferating cells, via genomic mutations and other forms of stochastic genomic reorganization, in order to ultimately decode from their genomes information about cellular dynamics through time. Our goal is to use DNA microscopy’s capability to jointly resolve cellular positions and cell clonal relationships to reconstruct their spatial and temporal dynamics in model organism development. We further aim to apply this framework to deepen our understanding of genomic variability in tumors and immune cells in mammalian tissue. In this proposal, I describe our plan to achieve both of these goals, and to establish a foundation for DNA microscopy to be deployed as a critical tool for spatial-genetic imaging in both basic biology and pathology.

NIH Research Projects · FY 2025 · 2021-09

PROJECT SUMMARY The human genome encodes information that specifies the development of an entire organism comprising at least 10 trillion cells and more than 200 different cell types. The genome also contains the information to direct appropriate responses to a host of environmental stimuli to maintain homeostasis and respond to challenges, e.g. from microbial pathogens. Changes to this code or dysregulation of its interpretation underlie almost all human diseases, including chronic inflammatory diseases, metabolic disorders, and cancer. Obtaining mechanistic and quantitative understanding of gene regulation in individual cells is a crucial prerequisite for a better understanding, and ultimately treatment, of diseases. Studying gene regulatory processes in human tissues has been challenging because of their cellular heterogeneity and because most human samples are not accessible to longitudinal observations and direct perturbations. However, the advent of single cell genomic technologies, the development of human iPSC and organoid-based in vitro model systems, and the availability of powerful tools for genetic perturbations have the potential to overcome these challenges and to revolutionize biomedical research. In this proposal we combine the development of single- cell multiomic tools that accurately profile multiple regulatory features within single cells or molecules with mechanistic and disease-focused studies to understand how genetic and environmental perturbations of gene regulatory processes disrupt cellular differentiation and underlie pathologies.

NIH Research Projects · FY 2025 · 2021-09

PROJECT SUMMARY/ABSTRACT Celiac disease (CeD) is a complex intestinal inflammatory disorder that is triggered by dietary gluten and develops in genetically susceptible individuals expressing HLA-DQ2 or HLA-DQ8 molecules. 1% of the worldwide population is affected by this disease for which the only effective treatment is a lifelong and restrictive gluten-free diet (GFD). Yet, persistent symptoms and enteropathy remain commonplace even among CeD patients that adhere to a GFD. This stresses the need to develop non-dietary interventions for CeD. The development of new therapies has however proven challenging because of our incomplete understanding of the immune mechanisms underlying CeD pathogenesis and the lack of a suitable mouse model. CeD is characterized by the loss of oral tolerance to gluten manifested by HLA-DQ2 or HLA-DQ8- restricted anti-gluten inflammatory CD4 T cells in the small intestinal mucosa and by a massive expansion of cytotoxic intraepithelial CD8+ lymphocytes (IE-CTLs) that are involved in the killing of intestinal epithelial cells. These observations have led to the general idea that CeD is primarily a T cell-mediated immune disorder. We hypothesize, however, that B cells also play a critical role. This hypothesis stems from several observations. First, CeD is characterized by a considerable expansion of plasma cells in the mucosa of CeD patients as well as the development of anti-deamidated gluten peptides (DGP) antibodies and autoantibodies against the enzyme tissue transglutaminase 2 (TG2). Second, the main model to explain the production of anti-DGP and anti-TG2 antibodies is that gluten-specific CD4+ T cells provide help to B cells suggesting that B cells could act as antigen-presenting cells for T cells and promote the amplification of the anti-gluten CD4 T cell response. Finally, several case reports on patients having CeD associated with another autoimmune disease suggest that B cell depletion therapy can provide clinical benefit in CeD, and we have demonstrated that B cell depletion significantly reduces intestinal tissue damage in our mouse model of CeD. The objective of this application is to characterize in vivo the role of B cells in amplifying the anti-gluten T cell response and allow it to reach a sufficient magnitude to promote tissue destruction. This project is innovative as it employs unique mouse models of CeD allowing to manipulate B lymphocytes, gluten-specific T cells, the gluten antigen, and the CeD predisposing HLA molecule to 1) assess the contribution of B cells as antigen-presenting to the activation and amplification of the anti-gluten CD4+ T cell response, and 2) assess the role of B cells and antibodies in the activation of IE-CTLs and tissue destruction. The knowledge gained from this study will provide unprecedented insights into the mechanisms by which B cell-mediated immunity contribute to the pathogenesis of CeD and will assess for the first time the therapeutic potential of B cell depletion therapy in an experimental mouse model of CeD.

NIH Research Projects · FY 2025 · 2021-09

Ingested food affects the composition of intestinal microbes, whereas microbes can affect the development of autoimmunity, including Type 1 diabetes (T1D). Many experiments conducted in animals and observations made in humans were suggestive of the importance of diet. Those dietary interventions that changed the development of T1D attracted our attention because they can be applied to large and diverse groups of people. We are interested in understanding how strongly dietary interventions depend on the microbiota and how they influence the immune system and disease development. The results of our preliminary experiments revealed that Hydrolyzed Casein (HC)-based diet was a microbiota-independent protector, whereas addition of gluten to HC diet caused a microbiota-dependent loss of protection. We hypothesized that protection works be relieving beta cells from stress minimizing activation of autoimmunity. Gluten’s mode of action is facilitation of both adaptive and innate immune mechanisms. To further uncover the mechanisms behind exacerbating properties of gluten, we will pursue the following aims: Specific Aim 1. Investigate the immune mechanisms involved in dietary protection from T1D and its reversal by gluten. · Analyze gene and protein marker expression at the single cell level in islets and pancreatic lymph nodes (PLN) of mice on different diets using single cell sequencing and multiparameter flowcytometry. · Perform functional testing of antigen presentation in animals fed different diets. · Perform functional comparisons of effector and regulatory T cell in these animals. · Perform analysis of other cell types in the islets and PLN. Specific Aim 2. Understand the autoimmune consequences of gluten and microbiota interactions. · Analyze the role of bacterial proteolysis in generation of the TCR agonists - peptides recognized by mouse T cells in the context of H-2g7. · To test the hypothesis that bacterial digest of gluten produces cross-reactive agonists that can cross- stimulate anti-islet responses. · Address the role of biologically active proteolytic products of gluten in innate immune system activation in vitro and, more importantly, in vivo.

NIH Research Projects · FY 2024 · 2021-09

Project Summary Spatial transcriptomics is a groundbreaking new technology that allows measurement of gene ac- tivity in a tissue sample while mapping where the activity is occurring. It holds the promise to facilitate our understanding of spatial heterogeneity underlying essential phenotypes and diseases, such as neurodegenerative diseases and cancer. However, the development of bioinformatics infrastructures and computational tools has fallen seriously behind the technological advances. The lack of proper computational approaches presents current data analysis barriers that significantly hinder biological investigations. The overarching goal of this proposal is to address some of the most pressing ana- lytic challenges facing profiling and interpreting spatial transcriptomics data, including 1) lack of robust identification of genes with spatial expression patterns across a variety of technical platforms, 2) lack of tools to identify structures, microenvironments as well as developmental trajectory on the tissue, and 3) lack of tools that can jointly analyze spatial transcriptomic data across multiple samples and multiple data sources. In the proposal, we will work on the following aims: Aim 1. Develop nonpara- metric tools for identifying genes with spatial expression patterns. Aim 2. Develop spatially aware dimension reduction tools for detecting structures and developmental trajectories on the tissue. Aim 3. Develop integrative association tools for spatial transcriptomic analysis across multiple samples and datasets. All the methods will be implemented in user-friendly software and disseminated to the sci- entific community. Successful achievement of all aims will dramatically increase the power of spatial transcriptomics analysis, and facilitate the application of these cutting-edge technologies to transla- tional and clinical studies.

NIH Research Projects · FY 2025 · 2021-09

PROJECT SUMMARY / ABSTRACT Our lab focuses on structural and functional studies of molecular machines involved in chemical modifications of macromolecules. Naturally occurring chemical modifications of macromolecules play essential roles in all aspects of molecular biology, from transcriptional and translational regulation to functional modulation of various proteins. Misregulation of the chemical modifications is involved in many human diseases such as cancers and neurodegenerative diseases. Although many have been described and characterized, there are still significant amounts of chemical modification systems that are poorly understood. Our long term goal is to elucidate the structure and function of molecular machines involved in various chemical modification systems and develop new tools and strategies to modulate their activity against the relevant diseases based on what we have learned. In the next five years, we will be focusing on two systems, the p97 related ubiquitination system and the Vault related ADP-ribosylation system. More than thirty mutations of human p97 have been identified, which are associated with a number of neurodegenerative diseases. The molecular mechanism, however, remains elusive. Through structural biology approaches and protein engineering, we will address 1) how p97 processes ubiquitin chains of different topologies through the cofactors; 2) the structural and functional consequences of disease mutations; 3) the mechanism of inhibitors of p97 and its cofactors. Our efforts promise unprecedented insights into the function of p97, a central hub of cellular protein homeostasis. Vault is the largest ribonucleoprotein in eukaryotic cells with a unique structure. The function of Vault has been linked to drug resistance in cancer and innate immune response. Recently, major vault protein (MVP) was identified as one of the 9 marker genes that can predict influenza vaccination responses. Given the importance of vaccine development during this COVID-19 pandemic, a deep understanding of Vault’s molecular mechanism is critical. We are going to focus on PARP4, the only enzyme in the Vault complex catalyzing ADP-ribosylation. Elucidating the function of PARP4 and how it interacts with Vault particle is the key to understand the molecular function of Vault.

NIH Research Projects · FY 2024 · 2021-09

Summary of the Request. We are requesting funds for the purchase of an Agilent 1260 Infinity II LC System to support our ongoing NIH project R01GM144663-03, “New Methods and Strategies for the Concise Synthesis of Complex Indole Alkaloids.” This advanced HPLC system, capable of solvent flow rates between 1-10 mL/min, is essential for both our primary analytical needs and semi-preparative applications. A reliable HPLC is critical for quantifying product ratios from various reactions, including diastereomers and distinct products, as well as determining enantiomeric ratios using chiral columns. Our current HPLC, an Agilent 1100 system purchased in 2005, has become increasingly unreliable, experiencing frequent leaks and severe pressure spikes that disrupt our research. The acquisition of the Agilent 1260 Infinity II LC System will ensure the accuracy and reliability of our analytical processes, thereby enhancing the quality and efficiency of our research. We respectfully request this supplement to maintain the high standards of our ongoing work and achieve the objectives outlined in our funded project.

NIH Research Projects · FY 2025 · 2021-09

PROJECT ABSTRACT Transitions of Care (TOC) for high-risk, frequently hospitalized adults with chronic diseases are complex, costly, and vulnerable to safety threats and poor health outcomes. Communication breakdowns, information lapses, and IT-induced unintended consequences can result in poor follow-up and medication non-adherence, both of which contribute to preventable readmissions or emergency room (ER) visits. The Transitional Care Model (TCM) aims to reduce such risks through a holistic, collaborative, patient-centered approach with in-home interventions. Prior to the SARS-CoV-2 pandemic and resulting coronavirus disease 2019 (COVID-19), most in- home interventions relied on in-person visits, which can be cost-prohibitive and unsustainable. One potential sustainable and scalable solution is to use telehealth for in-home virtual visits; however, use of telehealth for post-discharge TOC interventions has not been routinely implemented. In the post-COVID-19 era, given the rapid expansion of telehealth, hospitals are well-positioned to initiate this virtual care. In-home virtual visits may be particularly promising for patients with chronic obstructive pulmonary disease (COPD), who are often hospitalized, have multiple comorbidities, and require intensive medication teaching due to rampant inhaler misuse. COPD affects more than 16 million US adults, many of whom are older, contribute ~$50 billion to healthcare costs annually, experience high rates of acute care revisits, often due to care coordination failures. For this reason, Medicare’s Hospital Readmission Reduction Program (HRRP) aims to incentivize hospitals to implement TOC programs for increased quality and value of care for COPD patients. However, currently, such programs fall short of aligning with the full TCM. In-home interventions may be particularly salient for improving medication skills and outcomes for patients with COPD given rampant inhaler misuses, the effectiveness of in- hospital inhaler education, and evidence showing the need for inhaler education reinforcement post discharge. Thus, our trans-disciplinary team proposes to implement and evaluate “TELE-TOC: Telehealth Education: Leveraging Electronic Transitions Of Care for COPD patients,” which seeks to integrate virtual, pharmacy-based, in-home visits for COPD patients within our hospital’s existing COPD HRRP. Our central hypotheses are that virtual visits with pharmacists will be feasible to implement and will result in improved medication use and outcomes among COPD patients at high risk for readmission. We aim to iteratively design TELE-TOC using participatory study design and stakeholder input. We will then test the effectiveness of adding TELE-TOC virtual visits in a randomized controlled trial among COPD patients enrolled in our HRRP program. Lastly, we will develop a plan for a dissemination strategy and roadmap with national stakeholders to facilitate widescale adoption of TELE-TOC nationwide.

NIH Research Projects · FY 2025 · 2021-09

Project Summary/Abstract Ovarian cancer (OvCa) has an overall poor prognosis due in part to high rates of metastasis at the time of diagnosis and few targeted therapeutic options. Microtubule targeted agents (MTAs), including the taxane paclitaxel (PTX), are some of the most effective agents used for the treatment of women’s cancers, including both breast and OvCas. Although PTX is often effective during the initial phase of treatment, the development of resistance is a significant limitation to long-term anticancer efficacy. MTAs are collectively classified as antimitotic agents; however, different drugs of this class have shown distinct effects on oncogenic signaling pathways with notable differences demonstrated particularly between microtubule stabilizers, like PTX, and microtubule destabilizers, such as the vinca alkaloids. Additionally, there is an opportunity to develop new classes of MTAs that can circumvent well-established mechanisms of taxane resistance, including the upregulation of drug efflux transporters. I hypothesize that the development of microtubule stabilizers that circumvent clinically relevant mechanisms of taxane resistance, as well as the identification of biomarkers that can be used to direct the more rational choice among different agents of this clinically validated and mechanistically diverse class of drugs, will provide improved options for patients with taxane-resistant OvCa. To complete my dissertation, I will use a combination of molecular and cellular biology, bioinformatics, and in vitro and in vivo cancer pharmacology to identify key determinants for the targeted use of distinct MTAs for the treatment of drug-resistant OvCa (F99 phase). I will test the hypothesis that the taccalonolide class of covalent microtubule stabilizers will retain efficacy in locally disseminated, taxane-resistant OvCa models. Additionally, I will follow up on findings that the Septin 9 isoform 1 (Sept9_i1) oncogene is differentially localized upon treatment with microtubule stabilizers and destabilizers to test the hypothesis that Sept9_i1 can serve as a biomarker for the differential response to these drugs, particularly in EGFR-driven breast and OvCas. In the K00 phase, I will expand my training into the area of metabolic disorders to elucidate the molecular mechanisms of adipocyte-mediated taxane resistance in OvCa. I will build on studies that demonstrate PTX promotes IL-8 production in adipocytes due to its ability to directly activate the inflammatory TLR4 signaling pathway and test the hypothesis that structurally distinct MTAs that do not activate TLR4 signaling will circumvent this resistance mechanism both in vitro and in vivo, which could be used to inform on more rational use of particular MTAs in subsets of women with OvCa. The proposed research will utilize an effective, but mechanistically underappreciated, class of drugs to determine mechanisms underlying taxane resistance that will guide future therapeutic choices. The research and career training provided by this F99/K00 mechanism will provide me an opportunity to smoothly transition from my predoctoral research to a postdoctoral fellowship and, ultimately, into an independent investigator with a focus on drug-resistance in women’s cancers.

NIH Research Projects · FY 2024 · 2021-09

Project Summary Cardiac outflow tract (OFT) defects have an estimated prevalence of 1-2 in 1,000 live births. The 22q11.2 deletion syndrome or 22q11.2DS is one of the most frequent genetic causes of cardiac OFT defects. A total of 60% of patients with 22q11.2DS have congenital heart disease that ranges from mild to severe including bicuspid aortic valve (BAV), isolated ventricular septal defects (VSDs) to tetralogy of Fallot (TOF) or persistent truncus arteriosus (PTA). These clinical findings suggest genetic modifiers may affect phenotypic expression . In this project, we propose to use the Lgdel/+ mouse model to understand the relationship between neural crest cells (NCCs) and adjacent endocardial cells (ECCs) in forming and remodeling of the cardiac OFT. Mesenchymal cells (MCs) derived from NCCs and ECCs occupy the distal and proximal OFT, respectively, and form a distinct OFT MC boundary during heart development. Proper deployment of MCs from the two lineages ensures correct position and formation of aorto-pulmonary-ventricular septum and semilunar valves to separate the heart outlet into the systemic and pulmonary circulation. The function of NCCs in OFT defects has been well studied with respect to 22q11.2DS, however, the role of ECCs in OFT malformations has not been investigated. We have begun to fill this knowledge gap by studying the Lgdel/+ mouse, which was generated by deleting one copy of the mouse syntenic region of human 22q11.2 containing 26 protein-coding genes (22q11.2DS genes). We found a spectrum of OFT defects ranging from isolated VSD to TOF. The structural defects are preceded by a disrupted OFT MC boundary, increased expression of Edn1 during endocardial-to-mesenchymal transformation (EMT), and decreased NOTCH1 signaling and Ctgf expression during post-EMT OFT remodeling. By single cell RNA sequencing (scRNA-seq), we identified Edn1 as part of a unique gene program operating in a subset of ECCs undergoing EMT. Based on these findings, we propose an overall hypothesis that 22q11.2DS genes control OFT development by regulating the function of ECCs and the cell-cell communications between MCs from ECC and NCC origins, via interacting with genes essential for OFT formation. We will test this hypothesis in three specific aims. Aim 1 will determine whether the 22q11.2DS genes regulate EMT through modulating the EMT gene program, and if Edn1 acts downstream of 22q11.2DS genes to regulate the process. Aim 2 will ascertain whether 22q11.2DS genes also regulate OFT remodeling through a cell-cell interaction network that patterns the OFT MC boundary, and if Ctgf functions as a hub gene required for the post-EMT OFT remodeling, downstream of 22q11.2DS genes. Aim 3 will define whether Notch1 haploinsufficiency can potentiate the 22q11.2DS OFT defects. At the completion of this study, we expect discoveries that will establish genetic, molecular, and cell crosstalk regulated by important syndromic and non-syndromic CHD genes essential for mouse OFT morphogenesis. The information will provide deeper understanding of heart developmental biology and inform the disease mechanism of OFT defects, with a broader implication in congenital heart disease.

NIH Research Projects · FY 2025 · 2021-09

Significant geographic differences in HIV incidence exist in the United States, with people in the Southern United States having disproportionately high rates of HIV infection yet low rates of PrEP utilization. Through preliminary work, we have identified successful strategies to increase PrEP uptake and support PrEP persistence among patients in community health clinic settings. Using the Exploration, Preparation, Implementation, and Sustainment (EPIS) implementation science framework, this proposal will adapt these strategies for implementation and scale up in the Southern United States to improve PrEP care continuum outcomes among patients.

NIH Research Projects · FY 2025 · 2021-08

PROJECT SUMMARY / ABSTRACT The objective of this new Immuno-Engineering Postdoctoral Training (ImEPosT) Program is to train a new generation of interdisciplinary scientists in the emerging field of immunoengineering, by taking advantage of the strengths of University of Chicago mentors in identifying the most pressing questions in immunology and combining that with a growing body of bioengineers who create new tools, technologies, and algorithms to push the technical boundaries to address those questions. Anchored by a collegial and cohesive body of 36 mentors across the Pritzker School of Molecular Engineering (PME) and the Biological Sciences Division (BSD), The ImEPosT program will select the most promising postdoctoral trainees from bioengineering and immunology backgrounds to participate on a two-year program of collaborative research across the immunology-bioengineering interface that includes a flexible didactic component to build important skills like project development and management, grant writing, teaching, science communication, outreach, and career planning. In the laboratory, the mentors have expertise in six major areas: (A) Allergy, Autoimmunity, & Transplantation; (B) Vaccines; (C) Immuno-oncology; (D) Cellular & Molecular Immunology; (E) Computational & Systems Immunology; and (F) Microbiome. These mutually-overlapping areas of expertise have created a portfolio of collaborative projects. These include improving vaccination outcomes through in silico modeling of the effects of adjuvants on the immune system; systems approaches to delineate the molecular mechanisms of communication between commensal microbes with the immune system and the digestive system that lead to homeostasis versus disease; organotypic devices to model neutrophil swarming and activation during early inflammatory activation; protein engineering and computational approaches to deliver cytokine receptor `superagonists' as adjuvants in vaccines or cancer immunotherapies. Ultimately, ongoing projects across the 36 participating PME and BSD laboratories seek to use unconventional approaches to deliver new insights to gaps in knowledge in immunology, therapies that correct immunologic dysfunction or loss-of-function, and also diagnostics to identify potential routes of intervention. Led by Profs. Melody A. Swartz and Maria-Luisa Alegre, with Dr. Shann S. Yu (Scientific Director of the Chicago Immunoengineering Innovation Center) as the program administrator, the ImEPosT program will build on an outstanding infrastructure for postdoctoral training at UChicago together with a history of success of its faculty in mentoring prior trainees into successful careers in academia, government, and industry to create a new program that addresses emerging engineering needs in the rapidly evolving fields of immunopathology and immunotherapy.

NIH Research Projects · FY 2025 · 2021-08

PROJECT SUMMARY/ABSTRACT Metastatic ovarian cancer (OvCa) is the leading cause of death from gynecologic cancer. Despite aggressive chemotherapy and surgery, most patients (80%) experience intraabdominal progression or recurrence to visceral adipose tissue in the abdominal cavity. For more than 15 years, my laboratory has concentrated on elucidating the biology of OvCa metastasis, focusing on understanding how deregulation of the tumor microenvironment (TME) promotes OvCa metastasis and chemotherapy resistance. We defined the contribution of multiple stromal cell types to metastasis, revealing a critical role for a methyltransferase (NNMT) in the reprogramming of normal fibroblasts into cancer-associated fibroblasts through metabolic remodeling. Additionally, we answered the decades-old question of why abdominally metastasizing tumors have a propensity to metastasize to the omentum, finding that adipokines attract cancer cells to adipose tissue, and that adipocytes provide long-chain fatty acids to cancer cells for energy production through β-oxidation. However, fundamental questions remain about metabolic processes in OvCa progression. How are OvCa metastases metabolically different from primary tumors? Which fuels/metabolites are altered after chemotherapy, and how do they contribute to chemotherapy resistance? Given that immunotherapies are effective in several epithelial tumors, one of the more puzzling and timely questions is why checkpoint inhibitors are ineffective in OvCa. My hypothesis is that cancer associated adipocytes contribute to therapy resistance and immune effector cell exhaustion through the lipid-driven metabolic reprogramming of the TME. We have adapted methods to perform in vivo metabolic flux analysis in OvCa patients, by infusing labeled metabolites (non-radioactive 13C-glucose, acetate) and are working on methods to optimize compartment resolved metabolomics on tumor tissue using imaging mass spectrometry. These data will allow us to define metabolic changes in cancer, immune, and stromal cells before and after neoadjuvant chemotherapy. The hypotheses generated by these studies will be tested with wide-ranging experimental approaches using primary organotypic 3D cultures and mouse models. Our experimental approach will span functional cellular assays (to study adhesion, migration, and invasion), confocal imaging, biochemical activity assays, and newly devised methods to test the functionality of natural killer cells, T-cells, and macrophages in vitro and in vivo. Compartment-specific insights into metabolic changes in the tumor organ will be employed to develop high-throughout screening campaigns. These should discover small molecule inhibitors that can be optimized through an established and structured process towards clinical testing. We believe that, by targeting metabolic processes identified in the tumor organ, we can greatly enhance anti-tumor therapy response in OvCa, potentially halting the inexorable progression characteristic of this deadly disease.

NIH Research Projects · FY 2025 · 2021-08

Project Summary/Abstract Movement is the primary way in which animals interact with the world. To produce the incredibly adaptable behavior of mammals the brain must continually choose actions, then flexibly generate control signals for the body. The main objective of this project is to understand how ensembles of neurons and brain areas work together to control movement and make simple decisions. To understand how behavior is generated, we must know: How is a high-level decision (e.g., reach left vs. right) transformed into a time-varying command signal? And, how does this transformation and the generation of complex outputs exploit the precise biology of neural tissue to function reliably, despite the inherent noisiness of neurons? This goal is critical not only to better understand how neural tissue implements challenging computations, but also because deeper knowledge of these processes is likely to improve treatments for motor disorders such as Parkinson’s and disorders heavily affecting neural connections such as stroke and traumatic brain injury. To achieve this aim, we pair the power of experimental tools in mice together with dynamical systems analysis, which provides mathematical tools for investigating the function of neural ensembles. In the monkey, the dynamical systems approach has led to many insights. For example, we have learned that activity in motor cortex unfolds over time according to oscillatory dynamical “rules”; that much of motor cortical activity exists to support these dynamical rules and does not influence movement directly; and that there is a separation between signals for what movement will be made and when it will be initiated. In the mouse, we propose taking this approach several steps further by mapping the dynamical rules to specific biological features, such as cortical layers and projection pathways. In Aim 1, we will use two-photon calcium imaging to record neural activity during a simple reaching task that elicits variable movements from the mouse. We will then exploit this variability with our dynamical systems tools to identify the rules that govern the M1 pattern generator, and uncover how these rules map to cortical layers. In Aim 2, we will determine how information processing is divided into stages as signals are passed from visual decision areas to motor areas. This second Aim will employ a more complex visually-guided joystick task, together with optogenetic inhibition of specific pathways, calcium imaging, and retrograde tracing. This will allow us to compare activity in the neurons that connect areas with those that are engaged only in local processing. Finally, in Aim 3, we will record from identified projection neurons and apply powerful new machine learning techniques to test two competing theories of how the brain produces consistent outputs: whether the brain suppresses neural “noise” in the output neurons themselves, or suppresses only task-relevant noise according to a more population- oriented approach. These findings will advance our understanding of sophisticated cortical processes including decision making and motor control by grounding theoretical ideas about neural computation in our biological understanding of the tissue that implements it.

NIH Research Projects · FY 2025 · 2021-08

South Asians account for nearly 25% of the global population, displaying unique and complex genetic and social structures. South Asians also exhibit a high burden of infectious and non-infectious diseases. Yet, the paucity of modern and ancient genomics data deriving from individuals of South Asian ancestry results in a fragmented picture of the genetic and socio-cultural origins and evolution of humans in this region. Over the next five years, one of primary research programs in the Raghavan lab will leverage our expertise in ancient and modern genomics to address three crucial themes to promote our understanding of the genetics of South Asians and their diseases: (i) the regional demographic history over the last ~8,000 years, (ii) the prehistoric occurrence of infectious diseases and the evolution of pathogens and infectious diseases in this region, and (iii) the impact of dietary transitions on the gut microbiome composition and health of Indian populations. Since present-day gene pools and disease landscapes are products of long-acting evolutionary processes, we will jointly generate and analyze ancient and modern human genomic datasets in order to achieve Themes 1 and 2 that focus on the evolution of modern human populations, including reconstructing past migrations and admixture events, and infectious diseases, including the detection and phylogenetic characterization of ancient pathogens in human skeletal materials, respectively. Theme 3 will additionally benefit from my group’s growing networks with Indigenous populations across India to study the impact of dietary and subsistence transitions – so-called ‘westernization’ of traditionalist diets - on the gut microbiome. Ultimately, through the implementation of these complementary themes set within the context of South Asian populations, this research program will contribute towards our overall understanding of the evolutionary mechanisms that underlie health and disease among human populations. Importantly, data and results from our research will address critical gaps in the genomics literature especially for a region that, in light of being one of the most populous regions with the largest diaspora, contributes substantially to the global disease burden.

NIH Research Projects · FY 2024 · 2021-08

Project Abstract/Summary Cells utilize an array of actin binding proteins with diverse and complementary properties to assemble, maintain and disassemble a range of distinct F-actin networks to facilitate different fundamental functions including motility, polarization and division. To serve its function, each of these networks has a unique architecture defined by the number, lengths and connectivity of its filaments, which is maintained by a continuous dynamical balance of actin filament assembly, remodeling and disassembly. A fundamental challenge is to understand how functional network architectures are formed and maintained by the continuous coupling of architecture and assembly dynamics. Here we are focusing on the cell cortex, a dynamic network of actin filaments, crosslinkers and myosin motors, lying just beneath the plasma membrane, that undergoes rapid deformation and flow to drive cell movement, polarization, division and tissue morphogenesis. How ensembles of actin regulatory factors work in concert to simultaneously regulate actin filament network architecture assembly and dynamics at the cortex of living cells is poorly understood. The one cell C. elegans embryo provides a uniquely powerful opportunity to address these questions in a single large cell, that is directly accessible to high resolution microscopy, with powerful genetics, transgenics, CRISPR and RNAi. The C. elegans cortex is primarily composed of an F-actin network of linear filaments and small filament bundles that are assembled by formin CYK-1-mediated polymerization of profilin-actin, and decorated by actin filament crosslinkers plastin PLST-1, anillin ANI-1, and by mini-filaments of non-muscle myosin II NMY-2. Conversely, cofilin UNC-60A and capping protein CAP-1/CAP-2 appear to be key regulators of filament disassembly and filament length, respectively. We are addressing how the C. elegans cortical F-actin network architecture is formed and maintained through the dynamic integration of formin-dependent filament assembly, filament crosslinking, filament capping, and cofilin-dependent filament disassembly, all while the network experiences continuous myosin- driven deformation and flow. We are combining the complementary state-of-the-art in vivo expertise (quantitative single molecule imaging and particle analysis) and in vitro expertise (reconstitution and biophysical analysis) of the Ed Munro and David Kovar lab’s to address two major questions concerning the architecture and dynamics of the C. elegans F-actin cortex. First, we will characterize the fundamental dynamics, regulation and feedback control of formin- mediated actin filament and bundle assembly (Aim 1). Second, we will investigate the fundamental dynamics, regulation and feedback control of cofilin-mediated actin filament disassembly of the formin actin filament networks (Aim 2).

NIH Research Projects · FY 2025 · 2021-08

PROJECT SUMMARY Acute kidney injury (AKI) occurs in up to 20% of hospitalized patients and is associated with increased risk of readmission, morbidity, and mortality. The estimated annual cost of AKI care in the US is over 10 billion dollars, and, with the incidence rising, these costs will continue to increase. The current gold standards for diagnosing AKI, creatinine and urine output, are often delayed in their recognition of tubular injury. Prior work on AKI has typically focused on patients who have already developed AKI based on these standards, and interventions at this late time point have had mixed success. In contrast, emerging data suggest that intervening earlier can improve outcomes. Therefore, it is critical to optimize the early detection of AKI in hospitalized patients. We have previously developed a machine learning tool to identify patients at high risk of severe (stage 2 or greater) AKI more than a day earlier than clinically apparent using structured electronic health record (EHR) data. Although more accurate than prior methods, it suffers from a high rate of false positives, which limits its value in clinical practice. There is a large amount of valuable information that is stored in unstructured free-text fields (e.g., clinical notes) that could be utilized using natural language processing (NLP) within advanced deep learning neural network models that could significantly improve the detection of early AKI. Furthermore, there are established and emerging kidney injury biomarkers that could be combined with EHR-based models to improve accuracy even further. Finally, it remains unclear what interventions will have the best chance of decreasing the risk for developing severe AKI in high-risk patients. A better understanding of which interventions are of greatest benefit to specific patients is critical for improving the outcomes of patients at risk of AKI. The objective of this project is to develop novel tools to improve the identification and treatment of patients at high risk of AKI using a large, multicenter cohort. In Aim 1, we will use NLP and deep learning algorithms to develop a model to predict severe AKI across four health systems. In Aim 2, we will silently run the best- performing model developed in Aim 1 in real-time to identify high-risk patients. Manual retrospective chart review will be performed on a cohort of the highest risk patients to determine both the proportion of patients who receive guideline-based care as well as the association between receipt of guideline-based care and outcomes. We will also identify novel phenotypes of patients who are particularly helped or harmed by specific guideline-based interventions. Finally, in Aim 3, we will collect kidney injury biomarkers in the highest-risk patients to determine the added value of biomarkers to EHR-based models alone. Our proposal will provide clinicians with new tools to identify patients at risk of AKI earlier and more accurately. It will also provide evidence for which interventions are most likely to improve patient outcomes. This will result in earlier, more personalized care for patients at high risk of AKI, which will lead to decreased costs, morbidity, and mortality.

NIH Research Projects · FY 2024 · 2021-08

Project Summary: Evolution builds proteins with a remarkable combination of characteristics. They can fold spontaneously and carry out difficult chemical reactions, but also are robust to perturbation and able to adapt as conditions of fitness fluctuate. In recent years, sequence-based statistical models have provided specific models for how all these properties are encoded in the amino acid sequence of proteins. Here, we propose a data-driven, evolution-based design (EBD) process that, with the developments outlined here, can address several basic problems in protein mechanism and evolution. We will unify and optimize approaches for EBD and then apply it (1) to quantify the functional sequence space of a protein family, (2) to parse the constraints on paralogs and orthologs of a protein family, and (3) to understand how substrate specificity in an enzyme can adapt through a process of stepwise variation and selection. The work is extensively supported by preliminary data, and is enabled by new technologies for statistical inference, gene synthesis, and high-throughput functional assays, both in vitro and in vivo. The outcomes will be a unified computational framework for sequence-based statistical inference, and an serious test of the power of emerging evolution-based protein design approaches to understand and engineer protein molecules.

NIH Research Projects · FY 2025 · 2021-08

PROJECT SUMMARY/ABSTRACT Immunotherapies hold immense promise to provide cures for many cancers and metastatic disease, but only benefit a fraction of patients. Tumors can still engage multiple mechanisms to avoid and escape anti-tumor immune responses, including suppression, inactivation, and exclusion of potential cytotoxic T cells, processes which collaborate with cells in the tumor microenvironment (TME). A better understanding of these barriers has led to a multitude of new immunomodulatory targets to be developed, some to be used in combination with e.g., checkpoint blockade or CAR T cells. On the other hand, dominant barriers to immunotherapy can be different among patients with the same cancer type, and thus there is a need for personalized approaches to immunotherapy, so that the appropriate targets are used. Here we develop a novel organotypic culture devices to maintain ex vivo cultures of primary tumors and an immune component (tumor-draining lymph nodes or circulating leukocytes), on a platform that enables precise control over spatial, molecular, cellular, and mechanical characteristics and that is relatively high-throughput to allow screening or large numbers of experimental variables. In preliminary data, we show that these devices mirror key features of in vivo responses to immunotherapy, such as improved tumor cell killing and increased markers of immunotoxicity (possible adverse events) in response to cytokine immunotherapy. We propose that these devices can be used both to screen for ideal immunotherapy combinations as well as to probe the basic mechanisms underlying the deficiencies in the anti-tumor immune response for tumors exhibiting varying levels of immune infiltration, neoantigen load, and baseline lymphatic densities. In this way, we can begin to build a stratification map that aligns key morphological features of individual tumors to treatment regimes that are most likely to lead to efficacy and tumor regression. Using a combination of both murine mouse models and primary patient-derived biospecimens, we will take advantage of the level of control afforded by our novel organotypic devices to mechanistically interrogate individual immune cell subsets and signaling axes, towards understanding their roles in influencing the course and outcomes of anti-tumor immune responses.

NIH Research Projects · FY 2025 · 2021-07

PROJECT SUMMARY/ABSTRACT The lack of effective vaccines against most infectious diseases is largely a result of our fundamental lack of understanding of mechanisms involved in protective immunity. Adjuvants incorporated into vaccine formulations have a major impact on vaccine efficacy via modulating and prolonging host immune responses; however, our understanding of their underlying mechanism(s) of action in driving specific immune parameters is incomplete. While vaccines are the most effective way to prevent and control infectious diseases, many pathogens that significantly impact human health remain without an effective vaccine. For example, one-fourth of the world's population is latently infected with Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB)1, the leading infectious disease killer in the world. It is likely that for TB, and other major infectious diseases (e.g. AIDS and malaria), new adjuvants or adjuvant combinations will be essential for instructing a protective immune response. We and others have shown that targeting both the type 1 T helper (Th1) cells and type 17 T helper (Th17) cells enhance vaccine-induced immunity for TB5-8. Additionally, we have recently demonstrated that live vaccines (e.g. BCG) and adjuvants (e.g. β-glucan) generate innate memory response, termed trained immunity, via epigenetic reprogramming of monocytes/macrophages, thereby conferring protection against Mtb infection9,10. These data together suggest that combination adjuvants targeting both innate trained immunity and adaptive Th1/Th17 cellular responses can enhance protective immunity against pathogens. Thus, defining the mechanisms of action of combination adjuvants that generate potent trained immunity and protective Th1/Th17 axis, are the overall goals of this proposal. In the current proposal, we hypothesize that combinations of adjuvants that drive Th1 responses (AS01 or UM-1007, a novel TLR7/8 agonist) and Th17 responses (β- glucan, nanoemulsion, or UM-1098, a novel Mincle agonist) will result in Th1/Th17 adaptive responses and/or enhance trained immunity. We will achieve these overall goals through the following four Specific Aims. Specific Aim 1: To determine the mechanisms by which combination adjuvants elicit Th1/Th17 immune responses. Specific Aim 2. To determine the impact of combination adjuvants on hematopoietic stem cells and trained immunity. Specific Aim 3. To determine whether use of combination adjuvants improves recall Th1/Th17 responses and trained immunity upon challenge. Specific Aim 4. Determine the mechanism of action of combination adjuvants in a pre-clinical human-like rhesus macaque model. Together, the aims of this study will map out the pathways induced by combination of adjuvants that effectively drive Th1/Th17 responses and trained immunity. Through Mtb challenge studies, we will demonstrate whether the mechanisms by which Th1/Th17 and trained immunity are elicited are involved in protection against pathogen challenge. While we will use TB as a model system, we envision that dissecting the mechanism of adjuvants-mediated immunity has broader impact on many other infectious diseases.

NIH Research Projects · FY 2025 · 2021-07

ABSTRACT Asthma and allergic diseases are among the most common chronic diseases in children and adults, costing our health care system over $80 billion per year. Rates have been increasing over the past 40 years and therapeutic advances have been incremental. Over 150 loci have been reported in large genome-wide association studies (GWAS) of asthma and allergic diseases, but their individual effects are small and these variants account a small fraction of the overall genetic risk. Moreover, remarkably few of the GWAS findings for asthma and allergic diseases have led to discoveries of causal variants or causal genes that contribute to asthma and allergic disease pathogenesis. The latter has been particularly challenging due in part to the significant clinical heterogeneity of these diseases, and in part to the lag in the development of powerful statistical, molecular, and immunologic tools for bridging the trajectory from GWAS to gene discovery to biology to translation. In this application, we propose a robust and comprehensive strategy for identifying candidate causal variants and their target genes at asthma and allergic disease-associated loci, and for characterizing (i) their functional effects in asthma and allergic disease-relevant cells types, including bronchial epithelial cells, airway smooth muscle and lung immune cells, as well as peripheral immune cells, all in resting and activated states; (ii) their downstream phenotypic effects on both broad categories of disease groups and traits in the UK Biobank resource and on specific asthma and allergic disease endotypes in deeply phenotyped ethnically-diverse subjects participating in asthma birth cohorts; and (iii) their immunologic effects in resting and activated lung lymphocytes and myeloid cells and in “humanized locus” BAC-engineered mouse models. These goals will be accomplished through a highly collaborative and synergistic program that includes two projects, a service core, and an administrative core that together will that bridge the trajectory from GWAS to translation through highly integrated studies by an exceptional team of investigators with expertise in genetics, (epi)genomics, statistical genetics, and immunology. Achieving these goals will ultimately identify novel drug targets and the individuals most likely to respond, providing a framework for precision medicine and personalized treatment of asthma and allergic diseases.

NIH Research Projects · FY 2025 · 2021-07

Recent technological advances have transformed genetics research, and best practices for graduate education and research training have also evolved. We propose an innovative interdisciplinary predoctoral T32 program, Genetic Mechanisms and Evolution (GME), which is specifically crafted to meet the challenges and opportunities presented by these changes. The GME program will train an outstanding group of Ph.D. scientists in molecular, statistical, and evolutionary genetics research who will serve as the next generation of innovative scientific leaders in genetics. Training will ensure development of multidisciplinary competence across these fields, with a strong foundation in quantitative and computational analysis for every student. The GME training program leverages the world-class strength of the University of Chicago in genetics. Mentors include 56 faculty with extraordinary records of research and graduate training, drawn from 14 departments across the fields of evolutionary, statistical, and molecular genetics. Further, the University’s unique organizational structure brings all areas of genetics into a single division and makes possible the interdisciplinary program we propose. Trainees for 18 funded positions will be selectively drawn from 9 graduate programs across disciplinary areas. The pool of potential trainees is extraordinarily well-qualified. Trainees will be funded in years 2-3 of their studies, but they will participate in training and advising activities from matriculation through graduation. A new interdisciplinary core course and breadth requirements will develop student foundations in molecular, statistical, and evolutionary genetics and build strong skills in programming and statistics. Specialized workshops and an annual hackathon will provide further rigorous training in computational and quantitative analysis of modern genetic data. Formal writing instruction along with workshops in grant-writing and oral presentation skills will train scientists for effective communication and help address any existing differences in educational preparation among students. Individual development plans, mentor-mentee contracts, faculty mentor training, and peer mentoring will facilitate trainee success and allow growth of an effective and mutually supportive community of faculty and students. Participation in a pioneering career development program will support trainees in finding and preparing for a variety of post-PhD career paths. All these activities -- building on the strengths of an exceptional cadre of trainees, trainers and institutional support – will allow us to recruit and train the future leaders of 21st century genetics research.

NIH Research Projects · FY 2025 · 2021-07

Project Summary The overall, long-term goal of this project is to understand the molecular mechanism of that define the cochlear amplifier in outer hair Cells (OHC). Specifically, we will focus on the voltage-driven motor Prestin, a unique member of the SCL26 family of transporters found in the basolateral membranes of OHCs. Although Prestin has been studied extensively though functional approaches, the basic mechanistic understanding of this fundamental component of the cochlear amplifier remain to be solved. In spite of the richness of the existing functional data, the lack of a high resolution structure is a key missing element in defining its mechanism at a molecular level. This is particularly so for the two fundamental aspects of Prestin’s mechanism of action: the process underlying voltage sensing and the molecular mechanism of electromotility. In light of exciting new preliminary data at the core of this proposal we will be able to study the functional behavior, high resolution structure and dynamics of Prestin as a biological piezoelectric device. To do so, we plan to experimentally address several fundamental questions: What is the physical basis of the energy transduction steps, starting with transmembrane voltage changes and culminating in protein (and ultimately OHC) motion? What are the structures of the key functional states in its native, bilayer-embedded form? Where in the molecule does mechanical transduction occur? And how? What are the physical basis of the Prestin-bilayer interaction? Functional studies will be designed to understand the physical basis of energy transduction. Information on the high resolution structure of functionally relevant conformations, conformational dynamics and energetic relationship of Prestin with its surrounding lipid bilayer will be obtained from cryo-EM, electrophysiology and Fluorescence microscopy experiments. The data will be interpreted to generate high resolution structures of the different stages of the electromechanical transduction. We suggest that the advent of new cryo-EM approaches to the analysis of structure and dynamics in membrane proteins in their native lipidic environment shall open an exciting new experimental avenue. This information will impact our understanding of physiologically important events such as hearing, high frequency amplification and signal transduction.