HIV/AIDS is one of the largest health problems the world is currently facing. Even with anti-retroviral therapies (ART), many resource-constrained countries are unable to meet the treatment needs of their infected populations. ART-distribution methods need to be created that prevent the largest number of future HIV infections. We have developed a compartment model that tracks the spread of HIV in multiple two-sex populations over time in the presence of limited treatment. The model has been fit to represent the HIV epidemic in rural and urban areas in Uganda. With the model we examine the spread of HIV among urban and rural regions and observe the effects of preferential treatment to rural areas on the spread of HIV in the country as a whole. We also investigate the effects of preferentially treating women on the spread of HIV. We find that preferentially treating urban women produces the most dramatic effect in reducing the number of infected male and females in rural and urban areas.

The most common causes of childhood interstitial lung disease (chILD) are autosomal recessive mutations in the gene encoding ATP Binding Cassette A3 (ABCA3) protein, a lamellar body (LB) associated lipid transporter exclusively expressed within the alveolar epithelial type II cells (AEC2s) in the lung. Instability of primary AEC2s in culture has prevented studies of ABCA3 mutations, resulting in limited understanding of disease pathogenesis. To overcome this challenge, we developed AEC2-like cells from human pluripotent stem cells (PSCs) in vitro, allowing study of normal ABCA3 function and perturbations that result from ABCA3 mutations. To develop an AEC2 model that would recapitulate ABCA3 biology, we targeted human PSC lines with a knock-in GFP fusion reporter (ABCA3:GFP). Differentiations of PSCs into AEC2s (iAEC2s) resulted in exclusive expression of ABCA3:GFP in iAEC2s and intracellular localization to LAMP3+ vesicles, reminiscent of endogenous ABCA3. Moreover, we find these ABCA3:GFP+ iAEC2s express LBs, process surfactant proteins, and secret surfactant lipids, indicative of preserved ABCA3 function. To study the effects of ABCA3 mutations using our model, we generated two sets of PSC reporter lines: 1) two patient-derived iPSC lines carrying rare homozygous E690K and W308R ABCA3 mutations predicted to affect ABCA3 function or trafficking, respectively, and their two syngeneic gene-corrected lines each targeted with the AEC2-specific knock-in fluorescent reporter SFTPCtdTomato; and 2) three syngeneic ABCA3:GFP knock-in iPSC lines encoding wildtype, E690K, or W308R proteins. Directed differentiation of patient iPSCs into iAEC2s revealed attenuated secretion of surfactant-specific lipids, recapitulating clinical findings of surfactant deficiency. Examination of ABCA3 protein trafficking using the ABCA3:GFP fusion reporter revealed retained E690K and W308R mutant ABCA3 protein processing and trafficking compared to the wildtype protein by confocal microscopy and western blot analyses, however mutant iAEC2s exhibited smaller LBs, indicative of defective ABCA3-dependent lipid transport. Bulk RNA sequencing of mutant and gene-corrected SFTPCtdTomato- or ABCA3:GFP-expressing iAEC2s revealed enrichment of the TNF𝛼-NF𝜅B pathway in both W308R and E690K mutant iAEC2s, validated by lentiviral reporter assays and secretion of NF𝜅B-driven cytokines. Thus, we provide insights into how ABCA3 mutations alter AEC2 physiology and developed a platform to study other genetic AEC2 diseases through our ABCA3:GFP reporter system. / 2021-05-26T00:00:00Z

Hereditary transthyretin amyloidosis (ATTR amyloidosis) is a multi-system protein folding disorder that results from >100 described mutations in the transthyretin (TTR) gene. In the disease, non-natively folded TTR, originally produced by the liver, travels throughout circulation and deposits extracellularly at downstream target organs. The multi-tissue etiology of the disease makes it difficult to study in vitro, while no mouse model accurately recapitulates disease pathology. Therefore, we utilized patient-specific induced pluripotent stem cells (iPSCs) to test the hypothesis that production of and exposure to destabilized TTRs results in distinct cellular and molecular changes. The liver’s contribution to the deposition of TTR at distal tissues is understudied. As a result, in Aim 1 we sought to assess the effects of destabilized TTR production on effector hepatic cells. To this end, we utilized gene editing to generate isogenic, patient iPSCs expressing either mutant or wild-type TTR. Combining this tool with single cell RNAseq, we identified hepatic proteostasis factors, including unfolded protein response (UPR) pathways, whose expression coincided with the production of destabilized TTR. Enhancing endoplasmic reticulum (ER) proteostasis within patient hepatic cells via exogenous activation of adaptive UPR signaling, we demonstrated preferential reduction in the secretion of pathogenic TTR. In turn, we demonstrated that production of disease-associated TTR correlates with expression of proteostasis factors capable of regulating TTR secretion and in turn downstream pathogenesis. ATTR amyloidosis patients exhibit extreme phenotypic variation (e.g. TTR fibril deposits at cardiac tissue and/or peripheral nerves). In Aim 2, we sought to define responses of target cell types to pathologically-diverse TTRs. To accomplish this, we profiled transcriptomic changes resulting from exposure to a variety of destabilized TTRs to determine 1) target cell response to TTR exposure and 2) how this response changes across diverse variants and cell types. In doing so, we found that TTR exposure elicits distinct variant- and cell type-specific transcriptional responses. Herein, we addressed our central hypothesis by profiling destabilized TTR production within hepatic cells and TTR exposure at target cell types. Collectively, these data may result in the discovery of unidentified and potentially druggable pathologically-associated pathways for ATTR amyloidosis and other systemic amyloid diseases.

Commonly used simulation models for predicting outbreaks of re-emerging infectious diseases (EIDs) take an individual-level or a population-level approach to modeling contact dynamics. These approaches are a trade-off between the ability to incorporate individual-level dynamics and computational efficiency. Agent-based network models (ABNM) use an individual-level approach by simulating the entire population and its contact structure, which increases the ability of adding detailed individual-level characteristics. However, as this method is computationally expensive, ABNMs use scaled-down versions of the full population, which are unsuitable for low prevalence diseases as the number of infected cases would become negligible during scaling-down. Compartmental models use differential equations to simulate population-level features, which is computationally inexpensive and can model full-scale populations. However, as the compartmental model framework assumes random mixing between people, it is not suitable for diseases where the underlying contact structures are a significant feature of disease epidemiology. Therefore, current methods are unsuitable for simulating diseases that have low prevalence and where the contact structures are significant. The conceptual framework for a new simulation method, Evolving Contact Network Algorithm (ECNA), was recently proposed to address the above gap. The ECNA combines the attributes of ABNM and compartmental modeling. It generates a contact network of only infected persons and their immediate contacts, and evolves the network as new persons become infected. The conceptual framework of the ECNA is promising for application to diseases with low prevalence and where contact structures are significant. This thesis develops and tests different algorithms to advance the computational capabilities of the ECNA and its flexibility to model different network settings. These features are key components that determine the feasibility of ECNA for application to disease prediction. Results indicate that the ECNA is nearly 20 times faster than ABNM when simulating a population of size 150,000 and flexible for modeling networks with two contact layers and communities. Considering uncertainties in epidemiological features and origin of future EIDs, there is a significant need for a computationally efficient method that is suitable for analyses of a range of potential EIDs at a global scale. This work holds promise towards the development of such a model.

Resistance to glucocorticoid (GC) therapy results in poor prognosis for acute lymphoblastic leukemia (ALL) patients. Utilizing a whole genome shRNA screen our lab identified several novel mechanisms of GC resistance. My thesis work established that an orphan nuclear receptor, the Estrogen Related Receptor Beta (ESRRB), is critical for induction of apoptotic genes following treatment with the GC dexamethasone. ESRRB has mostly been implicated in maintenance of pluripotency in mouse embryonic stem cells. We find that repression of ESRRB results in GC resistance in ALL and define ESRRB as a novel cooperating transcription factor in GC-induced gene expression. We also show that agonists to ESRRB synergize with dexamethasone and increase dexamethasone induced apoptosis in relapse ALL patient samples. Interestingly, our shRNA screen identified another factor important in stem cell maintenance: SOX2. While we originally hypothesized that ESRRB and SOX2 may cooperate in ALL, RNA-sequencing studies revealed that these factors mediate GC resistance by independent mechanisms. Our data define SOX2 as a repressor of key signaling pathways in ALL. Upon SOX2 knockdown, we observe activation of pro-survival gene expression including activation of the MAPK pathway, which has previously been implicated in GC resistance. MAPK activation may be explained by an increase in EGFR expression observed in Sox2 knockdown cells and GC resistant patients, suggesting EGFR inhibitors may re-sensitize patients to GCs. Overall my thesis work identifies mechanisms of GC resistance in ALL and utilizes these findings to define novel therapeutic strategies for GC resistant ALL patients.

The kinetics of tumor growth and progression are governed by the interaction between tumor cells, the non-malignant stroma and both innate and adaptive immune cell lineages. Innate immunity has a critical role in the control of tumor cell growth and metastasis. The microenvironment of many tumors is populated with innate immune cells, including regulatory natural killer (NK) cells and dendritic cells (DCs), tumor associated macrophages, and myeloid derived suppressor cells, that suppress normal immune function. Much of our understanding of interactions between tumors and the innate immune system is based on experimental studies performed in mouse “syngenic” models. However, there is clear need for a mechanistic understanding of the human innate immune system within the tumor microenvironment. The goal of my thesis is to characterize the interactions between human innate immune cells and tumors and to define specific pathways and cell lineages that are targets for immune modulation. A central focus of my thesis is the use of cutting-edge humanized mouse models based on the immunodeficient NOD-scid IL2Rgnull (NSG) mouse strain to study human immuno-oncology. In the first section of my thesis I describe studies that evaluate the influence of inflammatory stimuli on innate immune control of tumors. Agents that induce inflammation have been used since the 18th century for the treatment of cancer. The inflammation induced by agents such as toll-like receptor (TLR) agonists is thought to stimulate tumor-specific immunity in patients and augment control of tumor burden. While NSG mice lack murine adaptive immunity (T and B cells), these mice maintain a residual murine innate immune system that responds to TLR agonists. Here I describe a novel NSG mouse strain lacking TLR4 that fails to respond to lipopolysaccharide (LPS). NSG-Tlr4null mice support human immune system engraftment and enables the study of human specific responses to TLR4 agonists. My data demonstrate that specific stimulation of TLR4 activates human innate immune system and promotes regression of human patient derived xenograft (PDX) tumors. In the second section of my thesis I describe the development of an NSG mouse strain that constitutively expresses human Interleukin 15 (IL15) and supports the development of functional human NK cells. Using humanized NSG-IL15 transgenic mice (NSG-Tg(Hu-IL15), my data clearly demonstrate a critical role for human NK cells in limiting growth of a PDX melanoma. In the third section of my thesis I describe, the use of the bone marrow/liver/thymus (BLT) humanized mouse model to study the interactions between the human immune system and PDX melanoma and to evaluate the response of the melanoma to immunotherapy modalities. My results collectively suggest that mice engrafted with human immune systems and bearing human tumors can be harnessed as translational models, which are critically needed as tools to study tumor immunotherapy. These humanized mouse models are an ideal translational tool to advance our understanding of human immuno-oncology and for development and testing of novel immune therapies for the treatment of malignancies.

When attempting to mitigate the spread of an epidemic without the use of a vaccine, many measures may be made to dampen the spread of the disease such as physically distancing and wearing masks. The implementation of an effective test and quarantine strategy on a population has the potential to make a large impact on the spread of the disease as well. Testing and quarantining strategies become difficult when a portion of the population are asymptomatic spreaders of the disease. Additionally, a study has shown that randomly testing a portion of a population for asymptomatic individuals makes a small impact on the spread of a disease. This thesis simulates the transmission of the virus that causes COVID-19, SARSCoV- 2, in contact networks gathered from real world interactions in five different environments. In these simulations, several testing and quarantining strategies are implemented with a varying number of tests per day. These strategies include a random testing strategy and several uniform testing strategies, based on knowledge of the underlying network. By modeling the population interactions as a graph, we are able to extract properties of the graph and test based on those metrics, namely the degree of the network. This thesis found many of the strategies had a similar performance to randomly testing the population, save for testing by degree and testing the cliques of the graph, which was found to consistently outperform other strategies, especially on networks that are more dense. Additionally, we found that any testing and quarantining of a population could significantly reduce the peak number of infections in a community.

<p>Glaucoma is a leading cause of blindness characterized by the progressive loss of retinal ganglion cells (RGCs), essentially severing the connection between the eye and the brain. Among many underlying causes of the disease, mutations in the Optineurin (OPTN) gene result in severe RGC neurodegeneration in the absence of elevated intraocular pressure, providing a novel opportunity to study molecular mechanisms that lead to RGC neurodegeneration associated with glaucoma. Efforts of this study establishing a human pluripotent stem cell (hPSC)-derived in vitro disease model by inserting OPTN(E50K) mutation via CRISPR/Cas9 genome editing and investigate the cellular mechanisms of RGC neurodegeneration associated with glaucoma. OPTN(E50K) RGCs revealed neurodegeneration phenotypes, including downregulation of RGCs transcription factors, neurite retraction, and hyperexcitability, suggesting that OPTN(E50K) RGCs can serve as an appropriate disease model to study glaucoma-associated neurodegeneration. Since OPTN serves a primary role as an autophagy receptor, we further hypothesized that the OPTN(E50K) mutation disrupts autophagy in RGCs, and modulation of autophagy by mammalian target of rapamycin (mTOR)-independent pathways can preserve RGC phenotypes by maintaining mTOR signaling. OPTN(E50K) RGCs exhibited a higher number of OPTN puncta along with an overall reduced expression of OPTN protein, indicating a gain of toxic protein accumulation or loss of protein function. Furthermore, OPTN(E50K) RGCs revealed an accumulation of the autophagosome protein LC3 in a punctal manner as well as increased expression of lysosomal proteins, suggesting a disruption of degradation pathway in autophagosome and lysosome fusion. As mTOR complex 1 (mTORC1) signaling serves as a negative regulator of autophagy, a downregulation of mTORC1 signaling via activation of stress sensor adenosine monophosphate-activated protein kinase (AMPK) was observed as a possible compensatory mechanism for autophagy deficits in OPTN(E50K) RGCs. Pharmacological inhibition of mTOR in wild-type hRGCs resulted in similar disease-related phenotypes, while preservation of the mTOR pathway in OPTN(E50K) RGCs by treatment with the mTOR-independent autophagy modulator trehalose cleared OPTN accumulated puncta, preserving mTORC1 signaling, as well as rescuing neurodegenerative phenotypes. To further validate these associations in an animal model, the microbead occlusion mouse model was established by injection of magnetic microbeads in the anterior chamber to block aqueous outflow resulting ocular hypertension. In agreement with our findings in hRGCs, a decrease in mTOR signaling associated with an increase in the expression of autophagy-associated proteins was observed in RGCs in the microbead occlusion model. Additionally, these disease-related phenotypes were observed specifically within RGCs but not cortical neurons with an underlying OPTN(E50K) mutation, demonstrating that autophagy represents an essential pathway in RGCs to maintain homeostasis, and selective disrupt of autophagy in RGCs leads to neurodegeneration. Taken together, the results of this study highlight an essential balance between autophagy and mTORC1 signaling that is essential for the homeostasis of RGCs, while disruption to these signaling pathways contributes to neurodegenerative features in glaucoma. These results also demonstrated the ability to pharmacologically intervene to experimentally manipulate these pathways and rescue neurodegenerative phenotypes, providing a potential therapeutic target to prevent glaucoma-associated neurodegeneration. </p>

Acute Lymphoblastic Leukemia (ALL) is one of the most common type of hematologic malignancy in children, characterized by an excessive proliferation of unfunctional immature lymphoblasts in the blood and the bone marrow, which leads to a range of severe blood-related complications. Given the remarkable increase in the prevalence of leukemia in the past 20 years, there has been a particular interest in the development of in vitro experimental models for cancer research. Ultra-short self-assembling peptides have shown to be a promising class of synthetic biomaterials due to their biocompatibility, tunable mechanical properties, and the possibility of controlling the scaffold composition. The objective of this study was to create a bioactive but well-defined synthetic 3D model of the bone marrow (BM) microenvironment for the simulation of ALL using biofunctionalized ultrashort self-assembling peptide scaffolds. Different bioactive motifs derived from integral extracellular matrix (ECM) constituents that are known to enhance cell-matrix adhesion, including RGDS from fibronectin, YIGSR from laminin, and GFOGER from collagen, were incorporated into the parent peptide IIZK. These peptides demonstrated to be capable of generating stable hydrogel structures composed of fibrous porous networks, each with unique nanofiber morphology and mechanical properties. All the peptide scaffolds that were investigated in this study exhibited optimal characteristics concerning the cytocompatibility of multiple BM niche cells, including human bone marrow mesenchymal stem cells (MSCs), human umbilical vein endothelial cells (HUVECs), and patient derived ALL cells. The suitability of the scaffolds as drug screening platforms was evaluated, demonstrating their potential as versatile tools for the assessment of drug efficacy.

Background Dengue is a significant problem of international health concern. According to the World Health Organization in 2012, globally, dengue is “the most important mosquito borne viral disease” with incidence 30 higher than it had been 50 years ago. While most of the burden of disease associated with dengue is located in areas with a tropical and sub-tropical climate, increasing evidence suggests temperate areas are also at risk. Considering the recent introduction of relevant mosquito vectors into Southern Europe, and increasing numbers of imported dengue via travelers, Europe and other temperate areas may be increasingly at risk for dengue emergence, establishment and local transmission in the foreseeable future. Methods Recent dengue emergence in Madeira and reemergence in Tokyo underline the hypothesis that passenger air-travel can be an important conduit for the importation of vector-borne disease leading to emergence in naïve areas climatically suitable for dengue transmission, including parts of Europe. Combining information on travel with virus genetic similarity was useful in discerning likely pathways of for the importation of infections. Generalizing information learned from outbreaks in Tokyo and Madeira with global epidemic intelligence, global travel networks, and climate change projections, leads to more refined understanding of the magnitude of dengue infectious imported into temperate areas and these virus introduction events’ potential implications for seeding epidemics in the 21st century. Results While compared to total travel, imported dengue events and epidemics of dengue outside the tropics are rare, our combined evidence and modeled estimations suggest strongly that epidemic dengue emergence in temperate areas is possible and will continue to increase. We found that global change dynamics including warming temperatures in the much of the northern hemisphere and increasing passenger interconnectivity between areas endemic for dengue and dengue free areas are key mechanisms partly explaining these unprecedented epidemiological transitions. Conclusion While we calibrated our models on information known about dengue, many elements of the methods and conclusions may increase understanding of the potentially global implications for imported infections of other climate-sensitive infectious diseases’ that may have similar parameters. During 2016 and the years to come, techniques developed in this doctoral research will contribute to models used in risk analysis for vector-borne diseases of interest, including the increasing important potential for imported Chikungunya and Zika viruses into a variety of unexposed areas.