University Of California, San Diego

NSF Awards · FY 2024 · 2024-10

This project aims to serve the national interest by preparing computer science students for a career in software development. Decades of research has uncovered an “academia-industry gap” in which new graduates are under-prepared for the task of contributing to large, existing code bases in the software industry. To make graduates job ready, and to help fill the urgent need for qualified software developers, the tech industry has been recommending to universities that students be taught how to work on large code bases. The goal of this project is to develop a high-impact course that teaches students how to work on large code bases, that can be adopted by other institutions, and taught to a broad student population. Students’ comprehension of programming components in large code bases is not only under-researched but also overlooked in many upper-division computing courses. This project will be grounded in two relevant theories—the Block Model (a program comprehension theory) and Cognitive Apprenticeship (a teaching and learning theory)—to 1) advance our understanding of how students comprehend large code bases and 2) design a course that imparts program comprehension skills to students. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

Machine learning is deployed across various domains (e.g., finance, education, hiring) with the assumption that model outcomes are accurate and authoritative. But in reality, the specific model that is deployed is just one option of many: previous work has shown that multiplicity – the existence of multiple equally good models – arises at many stages of the machine learning pipeline. Formally reasoning about multiplicity is challenging due to the large (potentially infinite) set of models one has to take into account. As such, existing techniques are currently only able to reason about certain forms of model-based multiplicity, and generally only with empirical guarantees. This project’s novelties are a set of approaches that increase the auditability of machine learning pipelines. These techniques consist of frameworks and formal techniques to understand how multiplicity in the dataset creation and modeling processes impacts the final learned model that is deployed. The project’s impacts are especially prominent in domains where the decisions of machine learned models directly affect humans --- understanding multiplicity is vital for developing machine learning models that are fair and robust. The investigators are involved with organizing outreach programs to expose high schoolers and undergraduates to computer science and topics in machine learning. This project investigates multiplicity for diverse model architectures across the whole machine learning pipeline including training data, model predictions, and model explanations. The research integrates formal methods and robust machine learning techniques to provide techniques to help answer the question of whether machine learning outcomes are reliable, or whether they are just an artifact of multiplicity. For instance, the investigators study algorithms to certify (deterministically or probabilistically, depending on the model architecture) whether a model’s prediction is robust under various sources of multiplicity. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

This project is motivated by the increasing public concerns on privacy issues, new legislations and the high demand for privacy enhancing technologies such as differential privacy (DP) in applications from both private and public sectors. The overarching theme of the project is to address the pressing new challenges that arise as differential privacy transforms from a theoretical construct into a practical technology. The project advances the state-of-the-art of research in the area of DP, and contributes to privacy education. On the research front, the project develops new algorithms and analytical tools that enable more precise privacy accounting and higher utility in DP. On the education front, the project involves training future leaders in DP areas, creating educational materials and expanding an open-source software library called autodp that makes state-of-the-art differentially private computation more accessible. Collectively, the integrated research and educational activities contribute to ongoing collaborative efforts in building innovative applications of differential privacy. The project has three main components in use-inspired fundamental research. The first component unifies the recent breakthroughs in DP, such as, Renyi DP, moments accountant, f-DP and produce an intermediate functional representation that allows lossless conversions among these representations. The second component focuses on investigating the stronger privacy properties permitted by the structures of the actual data, and addressing the dilemma of interpreting worst-case privacy on average-case data. The third component focuses on using a public dataset to ``denoise'' the private data releases or to facilitate private machine learning. The outputs of the research will be broadly shared through integration in autodp library, and will be integrated in courses. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

Advanced manufacturing strategies for functional analytical biomaterials are needed immediately to help accelerate tissue model development and enable high-throughput screening platforms for biomedical and pharmaceutical technologies. For example, one of the primary factors that halts the advancement of new therapeutic drugs are their adverse reactions in organs such as the heart. To help accelerate drug development and de-risk the progression towards clinical studies, better cardiac tissue models are required that not only mimic mature human heart tissue but also have integrated analytical tools that can rapidly assess the mechanical behavior of the tissue with high spatial resolution and sensitivity in response to early developmental drugs. Because of the material tunability, speed of fabrication, and biocompatibility, three-dimensional (3D) optical bioprinting has become an ideal additive manufacturing strategy to achieve realistic tissue models; however, very little advancement has been made on the printing of high-resolution biomechanical sensors directly into fabricated tissue constructs. This Boosting Research Ideas for Transformative and Equitable Advances in Engineering (BRITE) project spearheads this advancement by supporting research that intends to develop additive manufacturing processes that can rapidly print, and/or erase, biomaterials capable of high density wireless mechanical sensing. Through a multi-faceted diversity, equity, and inclusion plan, this project will also boost underrepresented minority student retention and degree attainment in science, technology, engineering, and mathematics (STEM) fields by building a STEM awareness program at community colleges and identifying opportunity/equity gaps in rigorous STEM curricula. Technically, this project aims to conduct research focused on engineering photolabile ferroelectric bioinks that incorporate piezoelectric nanoparticles modified with electrochromic dyes within a hydrogel that can be used for additive and/or subtractive manufacturing in 3D stereolithography instruments. These bioinks will be used to 3D print nano-ferroelectric biomaterials with < 5 micro spatial resolution that have tunable mechanical properties, high piezoelectric coefficients, and can directly couple piezoelectric and optical signals. Through surface engineering and modeling, a strong understanding of how to control and optimize the polarization-strain relationship in optically printed ferroelectric nanocomposites will be generated. In addition, fundamental questions will be answered on how local piezoelectric strains fields can be engineered to induce molecular Stark effects and how cleavable chemical bonds can be leveraged to rapidly deconstruct and erase polymer nanocomposites using light. Lastly, this project will demonstrate that functional analytical biomaterials can be optically manufactured from the developed bioinks and 3D bioprinting instrumentation that are capable of high-density force read-outs and sensitivity via a piezoelectric-to-optical transduction mechanism. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

Traditional data centers are organized with a cluster of computer servers. Like a personal computer, each computer server in a data center includes a set of computing hardware resources such as CPU, memory, and disks. In recent years, a new data-center architecture called resource disaggregation has arisen. With resource disaggregation, different types of hardware resources are divided into separate pools (e.g., a CPU pool and a memory pool), and an application can run with any available resources in a pool, thereby improving the resource utilization of a data center. Prior resource-disaggregation research has taken two main approaches: (1) asking application developers to port their software to a resource-disaggregation-specific model and (2) changing the operating system to add support for resource disaggregation. The former requires manual work, while the latter incurs significant performance overhead because of its generality. To solve these shortcomings, this project proposes to leverage application features and behaviors in building resource-disaggregation solutions. The project's novelties are a new direction in resource-disaggregation research, new computing layers explored when building resource-disaggregation systems, and the study of data-center applications from the perspective of resource disaggregation. The project's broader significance and importance is to render resource disaggregation a cost-efficient and performance-efficient option for production data-center and cloud environments that often host a range of applications with diverse behaviors and performance requirements launched by multiple users. More specifically, the project aims to extract and leverage application-inherent semantics, including static and dynamic semantics such as memory access patterns, data object ownership, type-based data structures, execution profiles, and language runtime activities. This project lays the groundwork for constructing programming languages, compilers, and system support that can integrate a comprehensive range of program semantics into diverse disaggregation choices. This project aims to enable disaggregation systems to customize, without manual intervention, these multiple choices based on application-specific behaviors rather than relying on generic decisions. 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.

NIH Research Projects · FY 2025 · 2024-09

ABSTRACT Interstitial cystitis/bladder pain syndrome (IC) is characterized by pain related to the bladder, usually with frequency and urgency, in the absence of other diseases that could cause these symptoms. Given the difficulty in diagnosing IC, the US prevalence of IC was unknown until recently. With funding from the Centers for Disease Control and Prevention (CDC), we p r e v i o u s l y determined the national prevalence of IC by creating a nationwide cohort of IC patients using the largest integrated health system in the US: The Veterans Affairs (VA) Health system. After a detailed chart review of nearly 3,000 subjects, adjusting our findings based upon age and gender strata to the US general population, we found the national prevalence of IC to be 1.08% in women and 0.66% in men. However, key unanswered questions remain: What is the natural history of IC? Can we predict a diagnosis of IC with a urinary biomarker? What are typical IC treatment patterns? Is there variation in care and do these patterns of care affect IC progression and remission? What is the relationship between IC and other comorbidities such as depression and post-traumatic stress disorder? Do health disparities in IC outcomes exist by race/ethnicity, gender, geography (urban/rural), and socioeconomic status? Funded by our current CDC award, we aimed to address these questions by creating a prospective cohort of 378 subjects who have IC by ICD-9 codes, further confirmed by chart review, and followed subjects annually via validated questionnaires. By following our nationwide cohort of IC subjects and two additional clinical cohorts, we hypothesize we can gain greater understanding of IC treatment patterns, clinical outcomes, and the impact on quality of life (QoL). We propose to expand our prospective cohort of 378 VA patients to 500, adding additional cohorts at UCSD (200 patients) and Kansas University (100 patients). Patients will be contacted yearly to complete validated QoL surveys, 24-hr food recalls, and Fitbit activity trackers. We will also capture additional symptom flares and follow the cohort for the development or worsening of comorbid conditions (PTSD and depression). We will measure disparities in care and outcomes, and lastly, we will validate a set of previously tested urine biomarkers. Finally, we propose to continue the very productive partnership we’ve established with the IC Network (ICN). The ICN will continue to educate the larger IC community and provide a forum for disseminating our research findings. This study will make major strides in our understanding of IC and ultimately improve QoL for IC patients.

NIH Research Projects · FY 2025 · 2024-09

Project Summary Adenosine monophosphate-activated kinase (AMPK) is a master metabolic regulator critical for sensing low cellular energy states and initiating catabolic activities while also inhibiting anabolic activities.1 It has become increasingly clear that spatiotemporal regulation of AMPK is key to achieving specificity in AMPK signaling and fluorescent biosensors have served as powerful tools for monitoring spatiotemporal AMPK activity.2 AMPK helps maintain vascular homeostasis by phosphorylating different substrates such as angiotensin converting enzyme 2 (ACE2), a transmembrane receptor critical for maintaining blood pressure homeostasis, which is phosphorylated by AMPK to maintain stability, though where and how this AMPK/ACE2 interaction occurs is unclear.3 Due to the topology of ACE2 as a type I transmembrane protein, the AMPK/ACE2 interaction would require AMPK to enter the secretory pathway despite having no secretory signal peptides. In this proposal, we aim to (1) identify molecular mechanisms underlying the regulation of AMPK in ER lumen and (2) examine the functional role of ER lumen AMPK activity in ACE2 signaling. In preliminary studies, using an ER lumen-targeted single-fluorophore excitation ratiometric AMPK activity reporter (ExRai AMPKAR), I found AMPK is active within the ER lumen and that such activity is dependent upon the upstream kinase CAMKK2. I also showed that endogenous AMPK is associated with an ER lumen-specific protein, Grp94, using the proximity ligation assay (PLA). I hypothesize that AMPK is phosphorylated by CAMKK2 prior to its Grp94-mediated translocation into the ER lumen and will combine biochemical and live-cell assays to test this hypothesis. As part of our second aim, I found endogenous ACE2 is localized to the ER and that AMPK-phosphomimic ACE2 had enhanced presence at the plasma membrane versus nonphosphorylatable ACE2. I hypothesize that AMPK phosphorylates ACE2 in the ER lumen to facilitate its trafficking to the plasma membrane where it functions to maintain vascular homeostasis. We are now developing an ER lumen AMPK inhibitory peptide to use in ACE2 trafficking and endothelial function assays. The proposed studies will illuminate a novel AMPK activity site not mechanistically described and will fortify our understanding of spatial AMPK signaling to inform cardiovascular drug development and therapeutic strategies, especially for hypertension.

NIH Research Projects · FY 2025 · 2024-09

Summary/Abstract Late-onset idiopathic Alzheimer’s Disease (AD) is the most common cause of dementia and the sixth leading cause of death in the United States. While the pathology and disease progression of AD is well-documented, current effective therapies are limited. With the incidence of AD expected to climb over the next half century, it is critical to further investigate the molecular and cellular mechanisms underlying idiopathic AD. Genome-wide association studies have identified numerous noncoding genetic variants that are highly associated with AD, but the cell type specific function of these variants and how they confer AD risk remains unknown. The strongest noncoding risk loci associated with late-onset idiopathic AD is upstream of the gene Bridging Integrator 1 (BIN1). Despite its predicted importance, little is known about how BIN1 is regulated, its cell type specific function or its role in AD pathogenesis. We have previously published that the putative causal single nucleotide risk variant upstream of BIN1 lies within a microglia specific DNA regulatory region, or enhancer. The central hypothesis of this proposal is that BIN1 regulatory risk genetics confer AD risk through a cell type specific and environmental context dependent effect in microglia, with BIN1 expression being regulated by genetic variation within a microglial specific enhancer. We developed novel CRISPR/cas9 mediated enhancer deletions that have led to our strong preliminary data identifying neurodegenerative stimuli specific microglial dysfunction with reduced BIN1 expression secondary to the enhancer deletion. Here we apply innovative in vitro and in vivo methods to ascertain the contribution of human microglial BIN1 to tauopathy. The project goal is to identify the downstream pathways and mediators of microglial BIN1 and intersect with the potential contribution to neuropathology in neurodegeneration (Aim 1), together with the effect of reduced microglial BIN1 expression on the onset and progression of tauopathy in organoids and cocultures (Aim 2) and finally using a xenotransplantation model we developed to identify the role of microglial BIN1 in vivo in a murine model of tauopathy (Aim 3). Together these aims will integrate iPSC modeling, complex cocultures, tauopathy, and xenotransplantation as well as cutting- edge transcriptome and epigenetic methodologies to link human genetic variants in enhancers to microglia gene expression in a humanized mouse model of tauopathy. The long-term goal of this proposal is to elucidate the cells specific roles of non-coding variants in AD pathogenesis to identify novel therapeutic targets and pathways amenable to early intervention and AD prevention.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY In this project, we will engineer bright, small luciferases with bioavailable substrates orthogonal to NanoLuc/furimazine—the brightest and most widely employed bioluminescent system currently available to researchers. Bioluminescence is rapidly gaining traction as a general means to observe and control biochemical and electrophysiological signals in cells and is particularly advantageous for tracking and manipulating cells non- invasively in intact animal models of spinal cord injury, neurodevelopment, and neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and Amyotrophic Lateral Sclerosis (ALS). The addition of one or more small, bright, independently controllable luciferin-luciferase systems will enable far more informative studies of the complex dynamics of the brain and other tissues. Here, we will take inspiration from the naturally orthogonal luciferin, vargulin (derived from marine ostracods), which produces very bright bioluminescence in its native context. We will take advantage of the small and bright coelenterazine-consuming luciferase variant SSLuc (derived from Oplophorus shrimp), an enzyme engineered by the project team. By making stepwise changes to the side groups of the luciferin coupled with directed evolution of the luciferase to increase specific activity, we will evolve SSLuc into an enzyme that efficiently generates light from vargulin rather than coelenterazine. In parallel, we will generate membrane-permeant caged analogs of vargulin that enable it to be delivered efficiently into cells in the central nervous system, along with caged analogs tailored for delivery to cells expressing specific enzymes, extending the utility of the vargulin platform. Our work is highly innovative, as it combines a unique blend of chemical synthesis and protein engineering to fill a long-standing void in bioluminescence-based imaging and cell manipulation. The proposed research is significant, as the bioluminescent tools will enable the direct and independent interrogation of multiple cells and pathways using bioluminescence, which is not currently possible with existing toolsets. The luciferin substrates generated in this work will be highly bioavailable, stable, and genetically targetable. Additionally, like other imaging technologies, the bioluminescent probes developed in this project will likely catalyze new discoveries in a broad spectrum of fields.

NIH Research Projects · FY 2025 · 2024-09

ABSTRACT Auto brewery syndrome (ABS), also known as gut fermentation syndrome, is a rare condition in which a dysfunctional intestinal microbiome produces ethanol, which is absorbed and results in intoxication. ABS may result in behavioral, familial, social, and legal problems and is difficult to diagnose in part because of its rarity, and because alcohol use disorder is common. Patients typically have “flares” of the condition, with episodes of inebriation. ABS may be caused by yeast, sometimes brewer’s yeast or Saccharomyces cerevisiae, but it may also be associated with bacteria, such as Klebsiella species, E. coli or others, sometimes in combination. We recruited 38 ABS patients and their household partners (HHP). Preliminary data showed that anaerobic bioreactor cultures of ABS patient microbiota produced ex vivo significantly more ethanol than that of HHP. Ethanol production was abrogated by antibiotic treatment. Metagenomic analysis of fecal samples showed higher proportions of several bacterial species and of genomic DNA encoding alcohol dehydrogenase (ADH) in stool of patients with ABS as compared with HHP. These findings indicate that pathologic production of ethanol is driven by gut bacteria in most ABS patients. We have safely treated one ABS patient with an active flare using capsule fecal microbiota transplantation (FMT) under a single patient treatment IND. The patient achieved clinical remission. We hypothesize that FMT in ABS patients is safe, tolerable and may result in an eradication of alcohol producing microbes. We therefore propose a phase 1, open label safety and feasibility study of capsule-based FMT in subjects with ABS under FDA and IRB supervision. Primary clinical outcomes are safety and feasibility; secondary and exploratory endpoints include clinical outcomes and assessment of flares by blood and breathalyzer ethanol monitoring, dietary intake, and microbiome and bioreactor assessment of stool samples. These studies may reveal a new and safe therapeutic approach for patients with ABS, and will improve our understanding of how gut microbial ethanol production contributes to the disease. Results from this safety and tolerability study may lead to the conduct of a larger randomized controlled clinical trial for FMT use in patients with ABS. The study may also inform our understanding of the effect of the microbiome on other hepatic and metabolic disorders.

NIH Research Projects · FY 2024 · 2024-09

Advances in next-generation sequencing are enhancing the routine detection of human genetic variants, particularly in clinical settings. Yet, the ability to interpret the functional consequences of these variants has lagged far behind. While the identification of clinically actionable and pathogenic mutations has revolutionized the field of precision medicine, these unfortunately represent a small minority of reported human genetic variants. A large fraction of patients (~30-70%) who undergo diagnostic genome sequencing are found to have variants of unknown significance (VUS), for which a clinical impact cannot be assigned. Multiple computational methods have been designed to score the severity of a particular protein-coding mutation. While informative, predictions from these methods are imperfect and do not give mechanistic insights into a variant’s impact. On the other hand, laboratory-based functional genomics approaches have been used to characterize individual pathogenic variants in human cell lines or model organisms, but these methods are low-throughput and can only focus on a handful of mutations. Given the sheer volume of identified (and as-yet undiscovered) genetic variants in need of clinical interpretation, there is a pressing need for high-throughput technologies to address this challenge. Here, we describe complementary experimental and computational strategies for high-throughput characterization of the impact of genetic variants in key regulatory and DNA repair genes. We focus on mutations in "trans-acting factors” such as chromatin regulators, transcription factors and DNA repair genes, which are widely implicated in human disease. Mutations in these genes have the potential to induce widespread transcriptomic, chromatin or genomic changes, and thus are most amenable to the strategies described in our proposal. Notably, while these categories represent only a subset of clinically actionable genes, they nonetheless encompass thousands of potential gene targets. We interrogate two classes of phenotypes: global transcriptomic/chromatin changes induced by mutations to key transcription factors or other regulatory proteins, and mutator phenotypes induced by disrupting proteins involved in DNA repair processes. We first develop scBE-seq (single cell base editor sequencing), which combines pooled, high-precision genome editing with single-cell sequencing assays to interrogate effects of hundreds of variants simultaneously. scBE-seq leverages chemical base editing (BE) to introduce specific single nucleotide variants (SNVs). In parallel, we develop computational approaches leveraging genomics datasets from large biobanks to identify genes harboring high- impact variants which can be followed up using scBE-seq. Overall, our proposal brings together complementary expertise spanning computational human genomics, molecular biology, genome editing and development/implementation of genomic technologies. We envision the proposed experimental and computational strategies will make important advances in the ability to interpret the impact of individual variants in a variety of contexts and provide insights for predicting the effects of previously unobserved genetic variants.

NIH Research Projects · FY 2025 · 2024-09

PROJECT ABSTRACT Among the 20% of US adults experiencing laryngeal symptoms, 80% are diagnosed with laryngopharyngeal reflux (LPR) based on symptoms alone and empirically treated with proton pump inhibitors (PPIs). However, laryngeal symptoms respond poorly to PPIs, and patients often seek additional evaluation (on average 10 consultations & 6 diagnostic tests). Despite an arduous journey, patients rarely achieve clarity or relief. This usual care approach for laryngeal symptoms significantly impairs quality of life, leads to PPI overuse, and accounts for $50 billion in annual health care costs. The therapeutic dilemma is that varied mechanisms beyond gastric acid contribute to laryngeal symptoms and, thus, acid suppression with PPI is insufficient as a sole therapy. Through clinical trials and outcomes research, our team has identified novel mechanism targeted laryngeal recalibration therapy to address hyper-responsive laryngeal mechanical and cognitive behaviors. Another critical challenge is in the diagnosis of LPR. Our team has developed and validated an array of novel metrics with tremendous diagnostic potential including acid exposure time, a risk prediction score and salivary biomarkers (pepsin, bile acids). These cutting-edge discoveries in light of diagnostic and therapeutic gaps for LPR indicate that a trial of mechanism guided versus usual care PPI is an urgent, unmet need. We are uniquely positioned to address these critical gaps as we have assembled a multidisciplinary team with the requisite expertise in clinical trials, esophageal physiology, laryngology and laryngeal recalibration therapy to ensure successful design and high-quality execution of the MVP (Mechanism guided vs PPI) trial for LPR. This randomized controlled trial (n=160) will compare a mechanism guided strategy which will provide laryngeal recalibration therapy to all subjects as well as PPI to those with elevated esophageal acid versus the usual care empiric PPI strategy in order to address two overarching aims. Specific Aim #1 will determine efficacy of a mechanism guided strategy in patients undergoing evaluation for LPR; and, Specific Aim #2 will examine performance characteristics of esophageal acid exposure, risk prediction score, and salivary biomarkers in order to identify reliable diagnostic methods for the evaluation of LPR. The

NIH Research Projects · FY 2024 · 2024-09

Project summary The human reference pangenome, which represents a collection of genome sequences in a single data structure, has the potential to transform human genetics applications. Compared to a traditional linear reference genome, pangenomes enable analysis of megabases of genetic sequence that were previously ignored, reduce bias when analyzing diverse genomes, and provide dramatically improved genotyping of structurally complex regions of the genome. These complex regions likely harbor medically relevant variants contributing to a range of human traits. However, pangenomes have yet to be integrated into medical genetics and complex trait workflows due to a lack of analysis and visualization tools that are accessible to non-experts. Our central hypothesis is that pangenomes can be used to improve fine-mapping of trait associations and detection of pathogenic variants in complex regions by identifying particular paths enriched in individuals with a phenotype of interest. We focus on developing and applying tools that leverage pangenomes to identify, visualize, and fine-map genomic loci associated with complex traits. The tools proposed below are motivated by two major challenges identified by our own efforts to this end. First, visualization and browsing pangenome subgraphs for loci of interest, which is a critical step in exploring and understanding complex genomic regions, is currently a cumbersome and time-consuming process involving multiple command line tools geared at bioinformatics experts. Second, there is a lack of tools for integrating existing biobank datasets for which both genotype and phenotype data are available for complex traits analysis, with the reference pangenome. Our proposal integrates multiple large datasets encompassing a range of technologies and builds on existing pangenome resources and the computational infrastructure developed by the HPRC. In particular, we use genotype data and whole genome sequencing (WGS) datasets available for hundreds of thousands of individuals of a range of ancestries from the UKBiobank and All of Us as well as thousands of phenotypes available for these samples. A key goal is to enable backwards compatibility with existing biobank-scale datasets that have been mapped to linear reference genomes, which will facilitate more immediate use of the pangenome reference. We additionally use near complete long read assemblies and the reference pangenomes (primarily minigraph-cactus) released by HPRC. Further, our tools are designed to integrate with the current pangenome computational ecosystem by incorporating existing file formats (e.g. rGFA) and toolkits (e.g. vg). To this end we will develop a web-based pangenome browser that integrates with existing data based on linear genomes (Aim 1), develop metrics to quantify local graph complexity and use these metrics to characterize existing GWAS signals (Aim 2), and integrate pangenomes with existing biobank datasets to perform fine-mapping and visualization of individual trait-associated loci (Aim 3).

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY/ABSTRACT The Metabolomics Workbench (MW) – National Metabolomics Data Repository (NMDR) is a unique data resource that serves the biomedical research community. It was started through the NIH Common Fund Metabolomics Initiative over a decade ago and has developed into a one-of-its-kind metabolomics data repository and resource. Projects ranging from independent investigator studies involving metabolic measurements (funded through R21 or R01 mechanisms) to large national initiatives, including several Common Fund-driven metabolomics studies, find their home in the NMDR. The NMDR contains almost 3000 studies, some very large, containing more than 1000 human subjects. The metabolomics data generated by the researchers can be submitted through easy and facile mechanisms that have evolved over the years by the MW. The MW-NMDR is widely regarded as one of the most FAIR (findable, accessible, interoperable, usable) data resources of its kind. The sunset associated with the Common Fund Projects has mandated the need for mechanisms to sustain data, such as the NMDR, and the RFA offers the mechanism for this perpetuation for the community. This proposal will address two essential aspects needed for the metabolomics resource. The first and primary objective of the MW-NMDR proposal is the continuation of the repository and resource along with the evolution of all features currently present in the infrastructure. The MW-NMDR receives approximately 50 study submissions, some very large, each month and offers mechanisms for easy upload of the data followed by curation by the MW team. It is subsequently transferred into a relational database along with the metadata to make the data discoverable. These mechanisms require continuous maintenance and updating. The MW also houses a metabolite structure database and RefMet, the reference metabolite classification and annotation system, which facilitates data harmonization. The metabolite database and RefMet require continuous updating, an essential task for the MW. The outreach and engagement of the biomedical research community is another need of the MW-NMDR; continuing this effort with additional mechanisms is a key objective.The second objective of the MW-NMDR proposal is the enhancement of the infrastructure through multiple mechanisms. First, the dramatic growth in the data warrants easy discovery mechanisms. Towards this, we will develop a graph database and query system, which will enable researchers to pose complex queries/filters to discover data and access them. We will develop a Neo4j graph database along with an interactive graph visualization interface that will facilitate dynamical queries in a cascading manner. This will obviate the need for a researcher to learn sophisticated computer skills. Second, we will develop a simple and accessible human subjects’ clinical metadata model to help create specified cohorts and the associated metabolomics data. Third, we plan to provide data in multiple formats using tools and interfaces. Finally, we will develop further the cloud aspects of MW-NMDR and provide AI-ML-ready datasets.

NIH Research Projects · FY 2025 · 2024-09

SUMMARY Alcohol is the most commonly used licit substance in pregnancy, and cannabis is the most commonly used illicit substance in pregnancy. Approximately half of pregnant people who use cannabis also use alcohol, and one third of pregnant people who used alcohol also used cannabis. Both substances are associated with adverse outcomes among offspring, including preterm birth, small for gestational age offspring, and adverse neurodevelopmental outcomes, including fetal alcohol spectrum disorders in alcohol-exposed offspring. There is accumulating evidence that prenatal co-exposure to cannabis and alcohol confers greater risks to the developing fetus than either exposure alone, although data are primarily from animal models. Further, there is no evidence from pregnant populations of whether cannabis is used simultaneously with alcohol, and whether cannabis substitutes or complements alcohol use over the highly dynamic time of pregnancy. Of additional concern, there is accumulating evidence that paternal preconceptional exposure to cannabis and alcohol may directly and indirectly increase the risk of adverse offspring outcomes. The purpose of this developmental proposal is to gather information about alcohol and cannabis use before, during and after pregnancy, for both the pregnant individual and the biologic father, to support the feasibly of a larger cohort in the future. This proposal will elucidate distinct patterns of alcohol and cannabis use and co-use that are necessary to power future studies, and the feasibility of enrolling and interviewing biologic fathers about their own use. Our team includes a perinatal epidemiologist with research expertise in pregnancy cohort studies and prenatal alcohol and cannabis use, a Maternal-Fetal-Medicine specialist with research expertise in alcohol, cannabis and paternal exposures, and a psychiatrist who specializes in addiction during pregnancy. From San Diego County, we will recruit 100 pregnant individuals who used cannabis and alcohol in the three months prior to pregnancy, and their male partners. We will collect detailed information on alcohol and cannabis use and co- use over the course of the pregnancy, using methods shown to be reliable in other pregnancy cohort studies. The aims are to 1) Characterize the patterns of maternal alcohol and cannabis use before, during, and after pregnancy, 2) Characterize the patterns of paternal alcohol and cannabis use before, during, and after pregnancy, and 3). Model individual and joint trajectories of exposure for pregnant individuals and their partners. Success in this project will reveal the patterns of alcohol and cannabis use before, during and after pregnancy, by the pregnant person and the biologic father. These data are critical to inform future studies of the direct and indirect effects of parental use of alcohol and cannabis, and to inform intervention efforts and guide counseling.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY In most organs, the vasculature is permeable to many blood-borne molecules and cells, but the vessels of the nervous system tightly regulate the movement of ions, molecules and cells between the blood and the nervous tissue. In this way, the vasculature of the nervous system rigorously controls the neural environment to allow for proper neuronal function, and protect the neural tissue from toxins and pathogens. The blood nerve barrier (BNB) is the set of vascular characteristics that describes this strict regulation in the peripheral nervous system (PNS) and is analogous in function to the blood brain barrier (BBB) in the central nervous system (CNS). Dysfunction of either of these barrier properties has been associated with various pathologies including diabetic peripheral neuropathy in the PNS and multiple sclerosis in the CNS. Researchers have made great strides in answering many fundamental questions about BBB biology, especially by leveraging the use of RNA sequencing to identify genes of importance. In contrast, little is known about the cellular and molecular mechanisms responsible for BNB function in health and dysfunction in disease. Although the differences in cell types between the CNS and PNS are well known, no one has performed an in-depth molecular comparison of the BBB and BNB. Given the clinical relevance of BBB and BNB dysfunction in disease, a thorough comparison of both would be valuable to advance novel therapeutics for both PNS and CNS diseases, alike. As such, the principal goal of this proposal is to leverage the use of single cell RNA sequencing technology to compare the gene expression of the key cell types that form the BNB and BNB under physiological conditions, and characterize changes in the gene expression of the BNB during diabetic peripheral neuropathy. To accomplish this, we will first perform single cell RNA sequencing comparing adult mouse sciatic and optic nerves since these are analogous regions from the PNS and CNS and will have BNB and BBB vasculature, respectively. We will then perform single cell RNA sequencing on sciatic nerves from diabetic mice at early, mid, and late- stages of the disease, comparing them with healthy controls. Overall, this proposal will provide transcriptomic information on the differences between the BNB and BBB in health and BNB dysfunction in a diabetic model, providing a framework for a more complete understanding of the BNB in an aim to develop novel therapeutic strategies.

NIH Research Projects · FY 2024 · 2024-09

ABSTRACT Minimally invasive surgery (MIS) has gained popularity in recent years by offering increased manipulation dexter- ity in hard-to-reach areas through small incisions, thereby reducing patient pain, complication rate, and recovery time. However, MIS often involves a limited field of view, complex hand-eye coordination, and limited depth and tactile information. Without sufficient timely and context-aware feedback, these procedures are difficult to learn and, even then, still challenging and risky. Aiming to understand the activities and progress of the surgery to provide valuable feedback, artificial intelligence, and machine learning technologies have been proposed. How- ever, large-scale and high-quality data has been a consistent bottleneck to new developments and the inclusion of new surgical disciplines and procedures. In modern surgery, a dramatic amount of video data is captured at a high resolution and frame rate, so it is impractical to label the data densely, and until now, existing pub- licly available surgical datasets are still dismally small in size and representativeness compared to non-surgical datasets, attributing to the necessity of costly hand-labeling by clinical experts. This projoect proposes to develop autonomous algorithms for rapid, cost-effective surgical video frame annotation. Specifically, the approach ad- dresses methods to automatically compress lengthy surgical video data to only key informative time segments based on surgical context (Aim 1) and find within these segments the most informative video keyframes of specific anatomy/tissues to be used eventually for downstream tasks such as annotation and/or image-guidance (Aim 2). The expected outcome will be algorithms automatically identifying informative video segments and selecting the most information-rich keyframes to extract for hand-labeled annotations. These keyframes may then be used to learn neural network-based semantic segmentation models that can be trained to perform pixel-level recognition of anatomy in the scene. A colorectal robotic surgery dataset of low anterior resection will be built as part of the effort, where there is significant clinical importance in recognizing anatomy to avoid hitting nerves that could lead to erectile dysfunction. We will compare the performance of the segmentation algorithms trained with our proposed sparse annotations against algorithms trained with denser (but more costly) annotations. If success- ful, the project will generate a solution to address the lack of high-quality data. The obtained preliminary data with algorithms trained on it will provide rich semantic information to potentially enhance surgery safety, improve treatment outcomes, and reduce healthcare expenses in the future.

NIH Research Projects · FY 2025 · 2024-09

Microglial activation and neuro-inflammation regulate disease progression in diverse neurodegenerative di- seases (NDs), including but not limited to Alzheimer's Disease, Parkinson's Disease, and Tauopathies. Under- standing pathways that regulate neuro-inflammation in NDs is a significant goal. Cellular Prion Protein (PrPC) is best known as a GPI-anchored membrane protein that, in rare circumstances, undergoes conformational change to generate a derivative that aggregates in the brain, causing rapid ND and death. Pathogenic PrPC is trans- missible. Non-pathogenic PrPC is expressed widely, inside and outside the CNS. Numerous studies in diverse mouse model systems have shown that PrPC attenuates inflammatory responses, including neuro-inflammation. We contributed to this field by identifying a system of receptors that mediates the anti-inflammatory activity of PrPC in macrophages when PrPC is released from cells by ADAM family proteases (S-PrP) or in exosomes and other extracellular vesicles (EVs). This receptor system includes LDL Receptor-related Protein-1 (LRP1) and the NMDA Receptor (NMDA-R). Binding of PrPC derivatives to the LRP1/NMDA-R receptor assembly in mac- rophages blocks pro-inflammatory responses initiated by diverse Pattern Recognition Receptors. We now have data showing that the PrPC-LRP1/NMDA-R interaction initiates anti-inflammatory cell-signaling in microglia. We also have shown that the anti-inflammatory activity of S-PrP may be harnessed in small synthetic peptides (14- mers, 4-mer) corresponding to a putative LRP1-binding motif in PrPC that includes Lys100 and Lys103. The major goal of this research project is to characterize the activity of PrPC and the LRP1/NMDA-R receptor system in neuro-inflammation in NDs. A second goal is to test whether PrPC derivatives may be administered therapeu- tically to amplify the activity of the microglial LRP1/NMDA-R system and thereby attenuate neuro-inflammation. Three specific aims are proposed. In Specific Aim 1, we will test the ability of anti-inflammatory PrPC derivatives to regulate microglial activation and secretion of pro-inflammatory mediators by microglia and astrocytes in res- ponse to proteins that accumulate and aggregate in the extracellular spaces of the CNS in various NDs, including amyloid-β (Aβ), microtubule-associated protein Tau, and α-synuclein. In Specific Aim 2, the effects of PrPC gene (Prnp) deletion on biomarkers of microglial activation and neuro-inflammation will be studied in three distinct mouse models of ND, including AppNL-F mice, P301S-Tau transgenic mice, and mice that receive intracerebral injections of α-synuclein pre-formed fibrils. In Specific Aim 3, we will replicate the studies proposed in Specific Aim 2, studying tga20 mice, which express 3-4× more PrPC in the CNS compared with wild-type mice. Next, we will exploit the known ability of LRP1 to serve as a Blood-Brain Barrier Trojan Horse-receptor that transports proteins into the CNS and test whether systemically administered PrPC-derived proteins and peptides augment the anti-inflammatory activity of the microglial LRP1/NMDA-R receptor system in the CNS. Collectively, these studies will elucidate a novel anti-inflammatory system that may be highly significant in diverse NDs.

NIH Research Projects · FY 2024 · 2024-09

Project Summary In many mammalian species, infants rely on parental caregiving to survive the vulnerable phase of early development. Considerable evidence indicates that infants are not just passive recipients of parental care and maternal separation for even a few hours a day during early postnatal life can lead to profound social deficits in adult mice. Indeed, it is well established that early life adversity leads to long-lasting sociability deficits in humans, and developmental sensory processing deficits are closely associated with neurodevelopmental disorders such as Autism Spectrum Disorder (ASD). Moreover, ASD and other neuropsychiatric disorders are marked by sex bias in their manifestation, but the sources of this sexual dimorphism is not understood. Although recent work has revealed mechanistic insights into adult circuit dysfunction induced by early-life adversity, we know close to nothing about how the infant nervous system encodes parental cues. Investigations of infant neural processing have been held back by a lack of behavioral paradigms and technologies to capture and manipulate neural activity and gene expression during the first few days of life. In preliminary experiments, we have developed a monomolecular odorant induced olfactory imprinting paradigm which induces a long-lasting appetitive memory of maternal odors experienced during the first few days after birth. These results provide an opportunity to dissect neural mechanisms underlying valence attachment to maternal cues and its contributions to the development of social behaviors. Here, we propose to develop a modular genetic and viral toolkit for the rapid and reversible interrogation of neural activity and gene expression, allowing us to directly investigate the infant nervous system. We will use these tools to achieve the following goals: First, we will genetically identify sensory neurons that attach positive valence to neutral olfactory cues underlying olfactory imprinting. Next, we will use spatial transcriptomics to comprehensively map neuronal cell-types in the sensory periphery and forebrain of mouse pups and explore the origins of sexual dimorphisms in early-life social processing. In summary, by combining high resolution behavioral, molecular and genetic tools, our project will provide the first characterization of ethologically relevant sensory processing mechanisms in the infant brain and provide insights into the role of maternal cues in the ontogeny of social behavior.

NIH Research Projects · FY 2025 · 2024-09

Abstract Cardiovascular disease (CVD) is the leading cause of mortality in patients with Type 1 Diabetes (T1D), driven by complex pathophysiological dysfunctions that remain poorly understood at the cellular and molecular level. Epicardial fat accumulation and dysfunction have recently emerged as significant contributors to coronary artery disease (CAD) in T1D, potentially by inducing coronary artery endothelial dysfunction through pro-inflammatory adipocytokine secretion. This project utilizes the CARE-T1D consortium tissue bank to investigate the cellular and molecular dysfunctions in epicardial fat and coronary vasculature in T1D. Specifically, we hypothesize that T1D induces dysfunction in epicardial adipocytes, causing the release of inflammatory adipocytokines that traffic to coronary endothelial cells disrupting their function. We propose to: 1) Comprehensively identify T1D-specific cell states and regulators in epicardial fat and coronary arteries by performing single cell epigenetic and RNA profiling on CARE-T1D flash-frozen samples. 2) Genetically program “induced” T1D adipocytes in vitro to functionally characterize diabetes-specific adipocyte cellular responses and identify dysregulated adipocytokines. 3) Integrate CARE-T1D coronary vascular profiles with functional genomic perturbations in endothelial cells to define molecular mechanisms of T1D-specific endothelial dysfunction and test identified adipocytokines on endothelial functions such as angiogenesis, adhesion and migration. This research promises to elucidate the cellular mechanisms of CVD in T1D, offering insights into novel therapeutic targets and a genomic atlas of single cell resolution data for future investigation.

NIH Research Projects · FY 2024 · 2024-09

Climate change has multiple pathways to directly and indirectly impact human health. There is a strong connection between global warming and agricultural crops production through low precipitation, high temperatures, and drought. The lower crops production impacts quality and quantity of foods and their availability to low income communities. Our parent grant is leading the field of research in climate change and health through the Global Center for Climate Change and Water Energy Food and Health Systems (GC3WEFH) in rural Jordan. We are bringing together a large and diverse group of scientists to develop solutions and potential policies and interventions to help vulnerable populations cope with climate change health impacts. In this Administrative Supplement we will complement the existing focus of the parent grant on water quality and quantity with new data and focus on dietary quality and quantity. We established a robust team of scientists and community engagement of residents in the municipality of Alkhaldyia in Northern Jordan to address water access through an intervention of water desalination. This supplement will extend this effort to understand diet quality and food security within this same community and its relation to water and noncommunicable diseases in the context of climate change. We will recruit up to 100 homes from the target population and 1) measure nutrient adequacy, sources, and dietary quality of consumed food as risk factors for noncommunicable diseases; 2) determine if farming communities have adequate access to food and the level of food insecurity among these impoverished communities; and 3) include the collected dietary data into the WEFH modeling and tradeoff analysis that is being developed by the parent GC3WEFH project. We will expand our team to include expertise in clinical nutrition and train graduate students to apply methods of food assessment at the population level to be included in the parent grant’s Water-Energy-Food-Health nexus. The supplement will provide insight into the complex climate-agriculture-food-nutrition-health context and in relation to climate change impacts of low quality and quantity of drinking water. We have data collected on water use and access through the parent grant which this diet data will complement to help us understand the Water- Energy-Food-Heath Nexus within rural Jordan.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY/ABSTRACT Molecular Transducers of Physical Activity (MoTrPAC), Nutrition for Precision Health (NPH), and the Human Health Exposure Analysis Resource (HHEAR) are NIH-funded national projects (three originating from NIH Common Fund initiatives) that measure thousands of metabolites in large cohorts of human subjects under exercise, diet, environmental exposure conditions respectively. The Common Fund initiated Metabolomics Workbench, which serves as the data repository, the metabolomics harmonization center and the data analytics workbench for deep analyses of human metabolomics and provides the infrastructure to develop the concept of human metabotype. We characterize the metabolomic state of groups of individuals with common homeostatic points for a collection of metabolites as “human metabotypes”. More precisely, the metabotype defines a collection of metabolites or metabolite classes that is unique (in the metabolomic hyperspace) to a class of individuals – defined in this project through metabolomics measurements from humans subject to exercise and diet perturbations and humans subject to distinct environmental exposures. Human subjects can be classified as belonging to one of several distinct groups (e.g., clusters in a UMAP) defining the metabotype for a chosen set of metabolites in a class. At the quantitative level, the distinct groups are defined by distinct profiles of metabolites or metabolite classes. The major goal of this project is to use the three national projects to develop the “metabotype” concept into a concrete set of points in the metabolomics hyperspace that define the human physiological state. Towards this, we harmonize the metabolomics data across the national projects, identify the clusters of metabolites/metabolite classes that define a group of human subjects, and provide the biological context to the metabotype. The tools we will develop will enable an end user to analyze and decipher the physiological function that further defines the metabotype and explore perturbations such as exercise, diet, or changing environment to see how the homeostatic endotype points change into another possible homeostatic state. Most importantly, given that the definition of the endotypes in the MoTrPAC, NPH and HHEAR projects largely refer to healthy human subjects, we will develop the ability for any individual with their metabolomic measurements to map their data on the metabotype space. Using such a “Metabotype Calculator”, the most valuable product of this project, a human subject will be able to assess their “state of health” and assess how perturbations such as exercise or diet will alter their homeostatic metabotype states. We anticipate that the “Metabotype Calculator” will serve as a dynamic living counterpart to the genotype in defining the human subject’s state of physiology. All the resources developed in this project will be available on the Common Fund Data Ecosystem Data Repository Center (CFDE DRC). The Principal Investigator (PI) of this U24, also the CFDE DRC PI, will facilitate making this resource available to the user community.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY/ABSTRACT We are requesting funds for a NanoString CosMx Single Molecule Imager (SMI) to support spatial -omics in the Institute of Genomic Medicine (IGM) Genomics Center at the University of California, San Diego (UC San Diego). The CosMx SMI will be placed in the IGM Genomics Center, a campus-wide core facility managed by the IGM. The highly trained staff of the Genomics Center are experienced with cutting edge genomics technologies, skills which will translate well to spatial-omics. Since the IGM Genomics Center was established in 2013, we have provided access to genomics technologies to the UC San Diego community, consistently upgrading equipment and services to keep pace with the latest innovation in the field. Both our team and our users are excited about spatial -omics technologies, and we are committed to providing access to this cutting- edge workflow to campus. The IGM Genomics Center supports the genomics research of 290 NIH-supported investigators from UC San Diego, as well as neighboring institutions, in the areas of basic, translational, and clinical biomedical research. We have identified 10 Major and Minor Users across the UC San Diego research community, including investigators from nine different departments The projects of our Users encompass multiple areas of relevance to human health including retinal disease, inflammatory bowel disease, wound healing, neurobiology, immunology, neural degeneration and reproductive science. The data generated on the CosMx SMI has the potential to uncover novel disease mechanisms and potential new treatments for disease. UC San Diego has demonstrated a strong commitment to the advancement of genomics research and the IGM Genomics Center is determined to continue to provide cutting edge technologies and technical expertise to the local research community. With the support of our institution and our qualified staff, we will ensure that the CosMx SMI is properly maintained and used to its full potential.

NIH Research Projects · FY 2024 · 2024-09

Abstract The specific aim of this proposal is to obtain partial funding for the expenses (travel and lodging) for junior investigators, postdoctoral fellows and graduate students from the USA to attend the 11th International Meeting on Epithelial-Mesenchymal Transition. The meeting will be held November 12-15, 2024 at The Allen Institute for Cell Science in Seattle, WA, USA under the auspices of The Allen Institute for Cell Science and the Epithelial- Mesenchymal Transition International Association (TEMTIA). The objectives of the meeting are to 1. Bring together investigators in the separate disciplines of cancer, pathology and development to discuss their observations on EMT and explore whether there is a consensus on important components of the process. 2. Provide a forum where students and junior investigators can interact with senior investigators and display their own work and ideas in the field. 3. Expand a viable co-operative cross disciplinary forum of EMT-related researchers internationally. This will continue to provide a worldwide network for exchange of expertise, reagents and techniques across disciplines. 4. Publish a timely meeting update on cellular, molecular and genetic aspects of EMT in an appropriate cross-disciplinary international journal. Epithelial-mesenchymal transition (EMT) is a fundamental cellular process undertaken by cells in the embryo to form 3-dimensional structures from sheets of cells. During EMT, epithelial cells lose adherence to adjacent cells, degrade the local basement membrane and invade the underlying interstitial extracellular matrix. At the cellular level, this process requires specific signal transduction elements, new gene transcription, reorganization of the cytoskeleton, secretion of extracellular matrix molecules and growth factors. In the embryo, this process is reiterated at gastrulation, neural crest cell formation, somite breakdown, pancreatic islet formation, heart valve formation brain organization and in several other areas of organogenesis. In the adult, EMT occurs as a component of wound healing and in the pathologies of cancer metastasis and tissue fibrosis.

NIH Research Projects · FY 2025 · 2024-09

ABSTRACT/SUMMARY The maternal-fetal/infant axis of transport represents one of, if not the highest duration and intimacy of long-distance communication across multi-tissue barriers between two individuals. Transporters enable such communication by controlling the uptake and distribution of metabolites across membranes, tissues, organs, and even between the mother and the infant. Remarkably, only a few hundred human transporters control the exchange of tens of thousands of nutrients and metabolites between different tissue compartments. A comprehensive map of transporters to tissue barriers, and to the substrates (nutrients, metabolites, dietary supplement constituents, xenobiotics, and drugs) whose passage they facilitate along the maternal-fetal/infant axis, are yet to emerge because we simply do not know the identity of most transported metabolites, or how to prioritize candidate hits. We propose to create a Mother-infant Metabolite-transporter Atlas (MiMA) devoted to the deorphanization of transporters, while prioritizing our studies by considering their expression, abundance, localization and importance at tissue barriers of mother and developing infant, including the fetal blood-brain barrier (BBB) and infant gut in the context of the lactating mother and child. MiMA will leverage existing advanced infrastructures and apply process innovations/expertise to produce an atlas that can be used as a basis for system integration of metabolomics, proteomics, and transporter biology. MiMA seeks to answer the following questions: (1) How does a network of only a few hundred transporters control and optimize levels of perhaps thousands of small molecules along the mother-infant mammary gland-gut-brain axis? (2) Which endogenous small molecules and xenobiotics/drugs does each of these transporters recognize and permeate? (3) Are there rules that ensure a homeostatic system (patterns of metabolite:transporter specificity, tissue distribution, function), and can these rules inform precision nutrition and precision medicine? This project is expected to generate a comprehensive atlas populated with precise knowledge of what metabolites bind to which transporters to be able to move across organ/tissue compartments. MiMA will also create a novel workflow to empirically validate specificity among interacting metabolite-transporter pairs, combining metabolomics and molecular structural biology. The project will validate specificity among interacting metabolite-transporter pairs and create advanced nanobody reagents to interrogate localization as perturb function of transporters. MiMA will produce omics-validated model systems to have better contextual understanding of transporters in normal and diseased human physiology. Taken together, MiMA is expected to deliver an integrated map or mother-infant metabolite-transporter atlas to formulate the “rules” that govern tissue/body homeostasis and serve as resource for many exciting research questions to be asked and solved.