Genetic, Interventional, and Causal Inference Approaches to Understanding the Role of Life Purpose in Older Adults and Ovarian Cancer Survivorship
Aliya Alimujiang, Epidemiologic Science
Aim 1 will determine whether psychological well-being, lifestyle behaviors, and co-morbid conditions jointly mediate the relationship between life purpose and mortality in HRS. This study will enable us to comment on the direct effect of life purpose on mortality, which is critical when developing interventions. Aim 2 will take a two-pronged approach (GWAS and Mendelian randomization) to understand the association between life purpose and ovarian cancer survival and to provide some insight into the potential underlying biological mechanisms. Aim 3 will study whether an electronic health application designed to influence life purpose is effective among ovarian cancer patients. This app could provide ovarian cancer survivors with a self-directed means of influencing both their quality of life and potentially, their survival. Randomized clinical trials with the app or other interventions to improve life purpose would be a reasonable future direction of this work and could have a major public health impact.
Investigating Functional Amyloid Inhibition
Anthony Balistreri, Chemical Biology
Amyloids are a class of protein assembly that are known for their extreme stability and fibrous structure. Functional amyloids, a growing subclass of amyloids found in all domains of life, are protein fibers that fulfill key biological roles related to biofilm formation, structural scaffolds, storage, and much more. Control over functional amyloid formation is a topic of great research interest, given that unchecked aggregation of proteins is associated with the group of protein misfolding diseases called amyloidoses. We aim to elucidate the mechanism of action of a natural amyloid inhibitor protein called CsgC and enhance its activity against human pathogenic amyloids. Controlling amyloid formation in the laboratory is also a useful research endeavor. We have created a functional amyloid protein that responds to a chemical stimulus in order to start aggregating.
Investigating Novel Cell Intrinsic and Extrinsic Factors in X-chromosome Inactivation
Marissa Cloutier, Human Genetics
X-chromosome inactivation equalizes X-linked gene expression between female and male mammals via the silencing of genes on one of the two X-chromosomes in early female embryos. X-inactivation is a paradigm of epigenetic transcriptional regulation because two genetically identical chromosomes become transcriptionally differentiated and these transcriptional states are maintained through many rounds of cell division. Imprinted X-inactivation results in the silencing of genes on the paternal X-chromosome in the preimplantation mouse embryo. Notably, imprinted X-inactivation is a paradigm of transgenerational epigenetic regulation due to its stable parent-of-origin-specific inactivation pattern. Here, I identify a role for maternal Polycomb Group Repressive Complex 2 (PRC2) protein EED in initiating imprinted X-chromosome inactivation in mice. I have also discovered that loss of other PRC2 core proteins results in a milder defect in imprinted X-inactivation, suggesting a role for EED in gene silencing independent of the PRC2 complex. Additionally, I have helped identify lithium chloride and other GSK-3 inhibitors in culture media as a cause of X-inactivation erosion in human embryonic stem cells. Taken together, this work has identified key intra- and extracellular influences on X-inactivation in mice and humans.
Utilizing Cascade Biocatalysis for the Chemoenzymatic Synthesis of Unnatural Hapalindole-Type Metabolites
Robert Hohlman, Medicinal Chemistry
Hapalindole-type metabolites are a class of indole alkaloid natural products that have been isolated from the Stigonemataceae order of cyanobacteria. They possess a polycyclic ring system, unique functional groups and stereo- and regiochemical isomers. Since their initial isolation, they have been explored as potential therapeutics due to their wide range of biological activities. Isolation of the compounds from cyanobacteria remains low yielding and thus, numerous groups have devised synthetic methods to enable access for further studies. However, due to the complexity of the compounds, these methods suffer from low yields and/or high step counts. Recently, work to uncover how these compounds are made biosynthetically has revealed a wide variety of new prenyltransferases, cyclases, and oxygenases. This work focuses on using these new enzymes to biocatalytically produce novel hapalindole-type metabolites for biological testing. It also explores methods to produce the E-ring of the pentacyclic ambiguines through both biosynthetic and chemoenzymatic methods.
Deciphering Metabolic Alterations with Data-Driven Network Analysis
Gayatri Iyer, Bioinformatics
The metabolome provides a readout of the cellular and biochemical events that reflect the genetic and epigenetic makeup of an organism, as well as the microbiome and environmental exposures. In recent years, metabolomics has emerged as an integral part of biomarker discovery in a variety of diseases. It can also help understand the underlying disease mechanisms. However, the bioinformatics tools for extracting information from complex metabolomics data is still scarce. In my first project, we developed a novel data-driven network-based bioinformatics tool to identify biochemical disruptions leading to disease from metabolomics data. In my next project, we are developing methodologies for integration of metabolomics with gene expression and genotyping data to gain deeper understanding of the crosstalk between genes and metabolites and their role in pathological and physiological processes. My dissertation research will thus make a critical contribution to the rapidly developing field of metabolomics.
Mechanisms of Phenotypic Evolution at Different Levels of Biological Organization: From Molecules to Organisms
Daohan Jiang, Ecology and Evolutionary Biology
The relative role of various evolutionary processes in shaping phenotypic variation within and between species has been a central question in evolutionary biology. My thesis explores patterns and mechanisms of phenotypic evolution from three angles. First, I revisit studies of phenotypic evolution (of vertebrate gene expression levels, coleoid RNA editing, and fly wing morphologies) that all report or assume adaption but find that the observations are better explained by other factors/processes such as genetic drift, pleiotropy, and historical contingency. Second, in examining correlated traits, I identify differences between the correlation generated by mutation and that observed among divergent lineages, demonstrating a role of selection in shaping trait-trait coevolution. Finally, by comparing large sets of randomly chosen traits at molecular, cellular, and organismal levels, respectively, I assess the variation in the importance of adaptive selection in trait evolution across different phenotypic levels. These studies help us understand general principles of phenotypic evolution.
TorsinA and Neuronal Nuclear Pore Complex Biogenesis
Sumin Kim, Cellular and Molecular Biology
Nuclear pore complexes (NPCs) are large protein complexes that mediate nucleocytoplasmic transport. NPC abnormalities are implicated in several diseases including DYT1 dystonia, a neurodevelopmental movement disorder caused by a loss-of-function mutation in torsinA. Yet, NPC biogenesis in neurons remains poorly understood, and the biological function of torsinA and molecular defects underlying DYT1 remain unknown. Using a combination of new mouse genetic tools and super-resolution microscopy, I discovered a steady upregulation in NPC biogenesis during neuronal maturation. Contrary to wild-type neurons, torsinA-null neurons develop mislocalized clusters of NPCs that become increasingly severe during maturation. Despite the drastic difference in NPC distribution, NPC density is unaffected in torsinA-null neurons. These studies identify a novel and crucial function of torsinA in the localization and assembly of new NPCs during a key period of neuronal development, and highlight aberrant NPC biogenesis in the pathogenesis of DYT1 dystonia.
Targeting Nuclear Hormone Receptors as a Strategy for the Radiosensitization of Breast Cancer
Anna Michmerhuizen, Cellular and Molecular Biology
Nuclear hormone receptors including the androgen receptor (AR) and estrogen receptor (ER) have been identified as drivers of breast tumor growth. Recently AR has been identified as a mediator of resistance to radiation therapy in AR-positive (AR+) triple negative breast cancer. We have also identified a role for ER in the radiation response as inhibition of ER promotes radiosensitization. Radiosensitization with AR- or ER-inhibitors is due, at least in part, to the inhibition of non-homologous end joining-mediated repair of DNA double strand breaks. Ongoing work seeks to understand how the relationship between AR and ER may be impacting the radiation response and promoting cell survival following radiation in AR+/ER+ breast cancer models. In addition, a multi-omics approach will identify global changes due to hormone receptor signaling. This work will continue to inform the use and timing of radiotherapy in combination with AR- and/or ER-targeting therapies for breast cancer patients.
Causal Inference Methods and Intermediate Endpoints in Randomized Clinical Trials
Emily Roberts, Biostatistics
In essentially any randomized clinical trial, intermediate endpoints can serve several purposes. An intermediate marker may serve as a surrogate for a true clinical outcome of interest with the goal of making the trial run more efficiently or cost-effectively. Rigorous assessment as to whether a proposed surrogate endpoint is valid is challenging, however. This dissertation extends causal inference approaches to validate a candidate surrogate outcome using potential outcomes in a novel way. Using the principal surrogacy criteria, we first incorporate baseline covariates in the setting of normally-distributed endpoints and develop methods to incorporate conditional independence and other modeling assumptions. This method is broadly applicable, and we extend the methods for different types of outcomes such as longitudinal and time-to-event data with a model that incorporates the censoring and semi-competing risk nature of survival endpoints. We lastly consider intermediate markers to define a stopping rule for futility in a clinical trial.
Neural and Genetic Mechanisms of Cold Sensation in C. elegans
Elizabeth Ronan, Molecular and Integrative Physiology
Temperature has profound effects on all life forms ranging from bacteria to humans. In order to survive in their environments, animals and humans have evolved molecular thermal sensors and sensory neurons/circuits, to detect, respond, and adapt to temperature changes. The identities of the neurons and molecular sensors mediating cold sensation remain largely unknown. This knowledge gap partly results from technical challenges of administering cooling temperatures rapidly and precisely. Through pioneer microscale thermal measurement technologies, I have applied highly controllable and sensitive temperature devices on C. elegans, a powerful genetic model organism, and discovered that cold evokes profound behavioral responses mediated by cold-sensitive neurons. Genetic screens have identified novel molecular cold sensors that detect cold temperatures. These molecular cold sensors are evolutionarily conserved, suggesting that they may mediate cold sensation in humans. Together, this work sheds light on evolutionarily conserved mechanisms of thermosensation, advancing the contemporary view at the molecular, cellular, circuit, and behavioral levels.
Amplifying Immune Response with Nutritional Metal Ions for New Cancer Immunotherapy
Xiaoqi Sun, Pharmaceutical Science
Immunotherapy is advancing cancer treatment on multiple fronts. Accumulating evidence indicates stimulator of interferon genes (STING) pathway is the crucial immune pathway orchestrating antitumor immunity, and STING agonists are under development as new cancer immunotherapy. Nutritional metal ions play essential roles in the regulation of many important immune processes, which may be harnessed for disease treatment. However, it remains largely unknown how to utilize them for immunotherapeutic applications. I screened various nutritional metal ions and discovered that cobalt2+ and manganese2+ (Mn2+) potentiated type-I interferon response induced by STING agonists by up to 77- fold. Besides, I have discovered that Mn2+ and cyclic dinucleotide (CDN) STING agonists could self-assembled into nanoparticles (CDN-Mn Particle, CMP) that elicit strong immune cell activation. In preclinical studies, CMP eradicated 50% of established tumors after intravenous administration. Overall, my work suggests that nutritional metal ions may serve as a powerful pharmaceutical ingredient for improved cancer immunotherapy.
The Roles of SURF4 in Cholesterol Homeostasis and Protein Secretion
Vi Tang, Molecular and Integrative Physiology
Heart attack and stroke affect millions of people worldwide for which abnormally high blood cholesterol is a risk factor. We recently identified SURF4, a protein that influences cholesterol level in the blood. I found that deletion of SURF4 in mouse livers reduced their blood cholesterol by over 90% without adverse consequences. This is due to impaired secretion of APOB and PCSK9, two proteins involved in cholesterol transport and metabolism. I am working on determining whether these mice remain healthy long term following Surf4 deletion and if they are protected against elevation of blood cholesterol due to a high fat diet. Finally, I will identify additional proteins synthesized by the liver that also depend on SURF4 for secretion. Better understanding of SURF4 will allow development of drugs that lower blood cholesterol. This will reduce the risk of stroke and heart attack in people, allowing them to live a longer and healthier life.
Elucidating Routes of Community MRSA Transmission with Genomic Epidemiology
Stephanie Thiede, Microbiology and Immunology
Bacterial pathogens are becoming difficult or impossible to treat as they acquire resistance to antibiotics and spread globally. One such pathogen, methicillin-resistant Staphylococcus aureus (MRSA) causes invasive disease and has been labeled a serious threat by the CDC. MRSA was once confined to infecting those in the hospital setting, but began infecting otherwise healthy individuals in the community around 1999. While healthcare-associated MRSA has declined over the past decade, community-associated MRSA has remained persistent. This is in part due to a lack of understanding of the routes of transmission in the community and thus where to intervene. My dissertation focuses on the integration of large genomic and epidemiological data sets to elucidate pathways of MRSA transmission within high-risk urban communities. I believe this data-driven approach will help guide future infection prevention efforts to reduce community MRSA by revealing locations and behaviors associated with MRSA spread.
Investigating the Molecular Mechanisms That Persistently Reprogram Sensory Responses to Promote Obesity
Anoumid Vaziri, Molecular, Cellular, and Developmental Biology
Diets rich in sugar, salt, and fat alter taste perception and food preference, contributing to obesity and metabolic disorders, but the molecular mechanisms through which this occurs are unknown. My thesis work tests the hypothesis that diets high in sugar persistently reprogram sensory responses through the epigenetic regulator Polycomb Repressive Complex 2 (PRC2) to promote food intake and obesity. To test this hypothesis, we use recently-developed neurogenetic and molecular tools that target the activity of the PRC2 complex specifically to the sensory neurons, in vivo neural recordings of sensory neurons, and a combination of behavioral and biochemical assays to measure taste responses and obesity. In animals fed high sugar, the DNA binding of PRC2 in the sweet gustatory neurons is redistributed to repress a transcriptional network that modulates the responsiveness of these cells to sweet stimuli, reducing sweet sensation. Half of these transcriptional changes persist despite returning the animals to a control diet, causing a permanent decrease in sweet taste. Our results uncover a new epigenetic mechanism that, in response to the dietary environment, regulates neural plasticity and feeding behavior to promote obesity.
Single Cell Transcriptomic Analytics: Methods Development, Benchmarking, and Applications in Biological Research
Xianing Zheng, Human Genetics
Single-cell RNA sequencing (scRNA-seq) has recently emerged as a powerful tool for surveying cell types and state transitions over thousands of cells to answer long-standing questions in organ development, maintenance, and disorders such as infertility and cancer. My research centers on applying scRNA-seq and spatial transcriptomic technologies to understand functional heterogeneity of complex tissues, while addressing data science challenges in the reproducible analyses and integration of such data. My dissertation describes four major efforts: 1) applying scRNA-seq in comparative analyses of spermatogenesis in mammals (mouse, monkey, human), and in studying cell population shifts during AML relapse; 2) developing a new approach to use each cell’s gene expression diversity (Gini index) as a measure of its differentiation potency, i.e., stemness; 3) systematic benchmarking of scRNA-seq software tools using multi-parameter ensembles of simulated data and extendable workflows; 4) building a data processing pipeline for spatial transcriptomic analyses using highly multiplexed single-molecule imaging.
Some Statistical Learning Methods for Procuring Individualized Treatment Rules in Personalized Healthcare
Yiwang Zhou, Biostatistics
Precision health has gained increasing attention in recent years. One central task of precision health is to establish individualized treatment rules (ITRs) for patients to tailored interventions to maximize the therapeutic effects. Although various methods have been proposed to estimate the optimal ITR, specific methodological challenges still need to be addressed, such as validating an existing ITR, procuring ITR with multiple views and missing clinical data. In this dissertation, I develop new statistical learning methods to extend the techniques currently used to establish ITRs. In Project I, I propose a new statistical framework, called net benefit index, to quantify added values of candidate biomarkers when they are included in the existing ITR. In Project II, I propose a novel learning method, termed Synergistic Self-learning (SS-learning), to address two major methodological challenges, including heterogeneous multidimensional outcomes and complex missing data patterns, when deriving ITR in the presence of multiple clinical outcomes. In Project III, I further extend SS-learning to establish a multi-view ITR in longitudinal clinical studies with incomplete data. Simulation experiments and real clinical trial analysis have been carried out to illustrate the performance of the proposed methods in improving the establishment of ITRs.
Characterization of the Mechanism of Leucine Sensing and the Role of Leucine in Gene Regulation by the E. coli Leucine-Responsive Regulatory Protein (Lrp)
Christine Ziegler, Biological Chemistry
Bacterial genes are regulated hierarchically; global regulator proteins sense environmental signals and orchestrate timely cellular responses by altering the expression of hundreds of genes. One such global regulator in E. coli is the leucine-responsive regulatory protein (Lrp), which senses general nutrient availability, is highly conserved among bacteria and archaea, and plays a vital role in pathogenesis by sensing whether the cell is in a host environment (via leucine) and regulating genes involved in metabolism, nutrient transport, motility, and host infection. However, despite almost 50 years of research, little is known about the molecular mechanisms of Lrp. My thesis work sheds light on the mechanism by which Lrp senses leucine and how it uses this signal to regulate over one third of the genes in E. coli. These new findings are critical for understanding general gene regulation in bacteria and, more specifically, the regulation of bacterial virulence.