Molecular simulation studies of extrinsic and intrinsic mechanism of permeation block in eukaryotic potassium channels

Ion channels are an extremely important class of proteins. They are crucial to every aspect of life, including sensory perception, movement, thought and memory, and heartbeat. Potassium (K+) channels are the most abundant type of ion channel. Mutations in these proteins are linked to a wide array of neurological, cardiovascular, and metabolic diseases in humans. Research into the molecular mechanisms of these proteins is necessary to understand the origin of these diseases and to identify potential therapeutic strategies. This thesis is specifically focused on investigating intrinsic and extrinsic mechanisms of blocking ion permeation in three distinct K+ channels using Molecular dynamics simulations: human TMEM175, which is key in lysosomal homeostasis; Shaker from Drosophila melanogaster, a prototypical member of the family of eukaryotic voltage-gated K+ channels and important in neuronal function; and Kv2.1 from Rattus norvegicus, another member of the family of voltage-gated K+ channels and also crucial for neuronal function. Investigating the mechanism of inhibition for a known inhibitor, 4-aminopyridine (4-AP) of the non-canonical TMEM175, we learn that 4-AP is recognized by TMEM175 in both a dynamic and specific manner and inhibits permeation in an electrostatic as well as steric manner. We also investigate the recently solved structure of C-type inactivated Shaker and learn that dilation of the filter through repositioning of crucial neighboring residues causes inhibition of rapid ion permeation. Finally, we compare RY785, a potent and specific inhibitor of Kv2.1, to a well characterized inhibitor tetraethylammonium (TEA), and discover that while TEA occludes the pore, RY785 still allows for permeation indicating RY785 facilitates channel closing suggesting an allosteric mechanism of inhibition. The insights gained into mechanisms of intrinsic and extrinsic inhibition can not only aid in the development of more targeted therapeutic approaches and novel drugs for these specific K+ channels but can contribute to a broader understanding of the mechanisms of inhibition and inactivation in other K+ channels, as well as, ion channels in general

FDI Linkages: How Political Economy Influences the Materialization of Linkages between Foreign and Domestic Firms

Linkages between foreign direct investment (FDI) firms and their domestic suppliers can lead to positive impacts on these suppliers, such as productivity gains and skills and technology transfers. However, the materialization of these linkages is not automatic. Many factors can affect whether and the degree to which FDI linkages take place, which have been amply studied in existing literature. One aspect which has not received as much attention is the role of political economy factors in FDI linkages. This thesis seeks to study the impact of political economy, specifically the political influence of firms, on the materialization of linkages between FDI firms and domestic suppliers. The firm-level empirical analysis, based on the World Bank Enterprise Survey (WBES) and using the Political Influence Index (PII) for 41 economies, finds that the political influence of a foreign firm is negatively associated with the linkages it creates. Foreign firms may use their political influence to evade any obligations, commitments, or pressures to create linkages. The negative relationship between political influence and linkages is only significant for manufacturing firms, not for services firms. It is also only present in countries with lower levels of governance as measured by the World Bank’s Worldwide Governance Indicators. The country’s level of income has no bearing on results. The thesis also examines two case studies in the automotive sector, in Morocco and Tunisia. The automotive sector plays an important role in the economy of both countries; however, FDI linkages with domestic suppliers are limited. This is mainly due to the limited numbers and capabilities of domestic firms, the latter hindering the ability of existing would-be suppliers to offer products with the requisite quality and reliability standards. Economic policies in both countries were not highly successful in enabling domestic firm entry and upgrade to meet foreign firm standards. In Morocco, politically influential foreign automotive firms were able to shape policies to their benefit and evade excessive linkages obligations and pressures. In both countries, elite domestic firms influenced government policies to their advantage, gaining rents and protections and dominating joint ventures and supply contracts, thus limiting opportunities for non-elite firms in the automotive sector

Methods and applications for large-scale pangenomic analysis

Recent technological and algorithmic advances have propelled genome sequencing from a multi-billion dollar, decades long endeavor to common and available research practice. Thanks in large part to long-read, ultra-long-read, and high fidelity sequencing, assembling complex genomic regions from non-model organisms is now possible. While telomere-to-telomere assemblies are not yet common-place and perfect genome assemblies are not yet possible, there have been great strides on both fronts. However, it is increasingly apparent that in order to fully appreciate the rich genomic diversity of a population, and thus accurately map phenotypes to genotypes, a single reference genome assembly is insufficient. Too much genetic variation is lost with a single reference, and thus pangenomes, defined as the entire set of genetic information within a clade, are necessary to resolve complex genotype-to-phenotype relationships. This thesis presents several pieces of work related to the pangenome problem. First, we review and present a tutorial for k-mer based applications in genomics, specifically for efficiently modeling genomes from non-model species, a key first step in genome and pangenome assembly of these species. Next, we detail the construction and analysis of a genus-wide pangenome of Solanum (nightshades), with a focus on utilizing this pangenome for biological insights. We then detail a novel, alignment-free method for efficiently analyzing and visualizing large pangenomes. Finally, we discuss several applications of pangenomes, with a focus on the plant kingdom. Taken together, these chapters underscore the necessity of pangenomes to capture the full spectrum of genetic diversity and provide innovative methods and applications for their assembly and analysis, particularly within the plant kingdom

Understanding mammalian cell metabolism and developing cell culture strategies for enhanced manufacturing of biotherapeutics

Mammalian cells, like Chinese hamster ovary (CHO) and human embryonic kidney (HEK293), are used as workhorses for biotherapeutics production owing to their ability to grow in large scale suspension cultures and produce high product titers with desirable product quality attributes (PQAs). However, bioprocessing faces challenges due to inefficient cell metabolism resulting in accumulation of toxic by-products, hindering cell proliferation, and causing cell death. Sub-optimal formulations of cell culture media (CCM), an expensive raw material, further reduces process yields. In this thesis, we studied the synergistic relationship between cell metabolism and CCM by employing bioanalytical tools to develop cell culture strategies for enhanced biotherapeutic production. Firstly, we identified inhibitory metabolites (IMs) secreted by mammalian cells using LC-MS/MS based metabolomics pipeline. Eight IMs were found to accumulate in cell culture supernatants at levels detrimental to cell growth and protein synthesis. Pathway mapping of IMs revealed amino acids (AAs) as chief contributors toward IMs buildup. A design of experiment (DOE) guided statistical framework was developed to modify AA levels for bioprocess enhancements. Reduced AA levels in CCM lowered accumulation of IMs. Next, due to low solubility and stability of traditional AAs, dipeptides were tested as alternative nutrients to problematic AAs like tyrosine and cysteine. Supplementation of dipeptides in CHO cultures supported biomass synthesis and protein production. 13C-Labeling experiments and kinetic modeling were performed to elucidate the utilization kinetics of dipeptides. We determined that dipeptides are cleaved both intracellularly and extracellularly and the cleavage rate depends on the structure, composition, and concentration of supplementation. Furthermore, Ala-Cys-Cys-Ala (ACCA) dipeptide dimer boosted growth and improved efficiency of glucose metabolism of CHO cells. High solubility of ACCA in basal medium simplified fed-batch processes by eliminating cysteine requirements from feed medium. Lastly, induction of cytotoxicity in HEK293 cultures during transient recombinant adeno-associated virus (rAAV) production was characterized. Analysis of rAAV-producing cells revealed caspase-mediated apoptosis as a likely mechanism of cellular death. Inhibition of caspases using small molecule, Z-VAD.fmk, alleviated cell death and increased full to empty capsids ratio, a key PQA for rAAV vectors. To sum up, cellular metabolism was investigated for CCM development to achieve superior biomanufacturing

Integrative transcriptomic profiling of the hippocampus across species and activity states

Activity-regulated gene (ARG) expression patterns in the hippocampus (HPC) regulate synaptic plasticity, learning, and memory, and are linked to both risk and treatment responses for many neuropsychiatric disorders. Cell type-specific ARG programs in the HPC are not well characterized. We used single-nucleus RNA-sequencing (snRNA-seq) in a mouse model of acute electroconvulsive seizures (ECS) to identify cell type-specific molecular signatures associated with induced activity in HPC neurons. Induced ARG responses were divergent across neuron populations, with dentate granule cells being particularly responsive to activity. Differential expression analysis identified both upregulated and downregulated cell type-specific gene sets in neurons following ECS. Within these gene sets, we identified enrichment of pathways associated with various biological processes. Finally, we used non-negative matrix factorization to reveal gene expression patterns differentially associated with cell types and ECS. This work provides a rich resource for interrogating activity-regulated transcriptional responses in HPC neurons at single-nuclei resolution in the context of ECS. To promote further research on ARG expression in HPC neurons, we also make these data publicly available. HPC cells have distinct spatial topography, morphology, physiology, and connectivity, highlighting the need for transcriptome-wide profiling strategies that retain cytoarchitectural organization. We generated spatially-resolved transcriptomics (SRT) and snRNA-seq data from adjacent tissue sections of the anterior human HPC across ten adult neurotypical donors. We defined molecular profiles for HPC cell types and spatial domains. Using non-negative matrix factorization and transfer learning, we integrated these data to define gene expression patterns within the snRNA-seq data and infer the expression of these patterns in the SRT data. With this approach, we leveraged rodent datasets retaining information on circuit connectivity and neural activity induction to make predictions about axonal projection targets and likelihood of ensemble recruitment in spatially-defined cellular populations of the human hippocampus. Finally, we integrated genome-wide association studies with transcriptomic data to identify enrichment of genetic components for neurodevelopmental, neuropsychiatric, and neurodegenerative disorders across cell types, spatial domains, and gene expression patterns of the human hippocampus. To make this comprehensive molecular atlas accessible to the scientific community, both raw and processed data are freely available

GENOME-WIDE ANALYSES OF CELL-FREE DNA FOR THERAPEUTIC MONITORING OF PATIENTS WITH PANCREATIC CANCER

Determining response to therapy for patients with pancreatic cancer can be challenging using imaging alone, and there is an unmet need for noninvasive assessment of tumor burden. We evaluated two liquid biopsy methods for assessing response to therapy using circulating cell-free DNA (cfDNA) in patients with metastatic pancreatic cancer treated with immune checkpoint inhibition and radiation as part of the CheckPAC trial (NCT02866383). Samples were evaluated after initiation of therapy and mutant allele fractions in cfDNA were determined using tumor-informed plasma whole-genome sequencing (WGMAF) and a mutation- and tumor-independent approach (ARTEMIS-DELFI), combining genome-wide cfDNA fragmentation profiles and repeat landscapes. Of those assessed with WGMAF, molecular responders (n=10) had a median progression-free survival (PFS) of 157 days compared to 51 days for molecular non-responders (n=10), (HR=0.23, 95% CI=0.07–0.69, p=0.0053), and a median overall survival (OS) of 319 days compared to 126 days for molecular non-responders (HR=0.29, 95% CI=0.11–0.79, p=0.011). For the ARTEMIS-DELFI approach, patients with low scores after therapy initiation (n=16) had a longer median PFS and longer median OS than patients with high scores (n=17), (PFS: 153 days versus 50 days), (HR=0.26, 95% CI=0.11-0.64, p=0.0013), (OS: 375 days versus 121 days), (HR=0.12, 95% CI=0.045-0.30, p<0.0001). By contrast, imaging at the same evaluation time point as the molecular analyses did not stratify survival (p=0.10). We validated our methodologies in a separate cohort of patients with pancreatic cancer treated with first line chemotherapy, with and without IL-6 inhibition, as part of the PACTO trial (NCT02767557). These analyses suggest that non-invasive mutation-based and fragmentation cfDNA approaches can identify individuals with pancreatic cancer who respond to therapy. Incorporation of these molecular methods to evaluate tumor burden may provide information for patient-physician decision making to improve patient care

WHAT'S IN A MEASURE? THE ROLE OF MORTALITY ESTIMATION IN POPULATIONS IN DISTRESS: EVIDENCE FROM NEGLECTED CRISES IN CHAD AND THE CENTRAL AFRICAN REPUBLIC

Mortality rates are crucial indicators of a population’s health, especially in humanitarian crises, where accurate estimates can drive life-saving interventions. Despite the long-standing use of mortality thresholds to trigger responses, questions remain regarding the adequacy and relevance of these methods. This dissertation critically examines the application of mortality estimation methods in crisis settings, where the complexity of conflicts, displacements, and natural disasters complicates data collection and analysis. Through a series of studies, this dissertation assesses the reliability and validity of various methods—retrospective household surveys, community-based surveillance (CBS), key informant surveillance (KIS), and burial site surveillance (BSS)—in capturing mortality rates. The research reveals that retrospective surveys are not without limitations, including biases and delays, they remain an important tool in their ease of use and capacity to provide valid estimates. Conversely, CBS and KIS, though useful in capturing real-time data, face challenges related to bias, resource demands, and sustainability. The dissertation also explores an innovative approach by use of Multiple Systems Estimation (MSE) to evaluate the validity of outcomes estimated by each method. By comparing methods across two settings in neglected crises, this research underscores the need for actors to commit to regular mortality estimation in the areas they serve, rigorously evaluate the results, and invest in research to refine these methods. Accurate mortality estimation is crucial for ensuring that humanitarian aid is targeted where it is needed most, and that interventions are both timely and effective. The findings highlight the vital role of precise mortality data in guiding public health actions, advocating for affected populations, and ultimately reducing excess mortality in crisis settings

Horace Made Strange: Carpe Diem as Mood, Reception as Attunement

This study examines Horace’s carpe diem odes, noting how landscape, atmosphere, and mood participate in poetic production. Roughly eighteen poems are usually grouped together as Horace’s carpe diem odes, though how this designation came about—and how it affects our understanding of Horace—has not been adequately studied. I offer a history of how this happened. I then suggest that these poems are aligned not only by convivial motifs, but also by a shared mood (Stimmung). However, far from reading carpe diem as a hedonistic imperative to enjoy the present, I argue that Horace’s poetry suggests that pleasure comes from an accumulation of the past. Turning to the aesthetic tradition of Stimmung, I further note how atmosphere and mood are enveloped in Horace’s poetic longing for that past. This longing, I suggest, is like the engine driving classical reception itself. Taking up carpe diem as a heuristic device for how reception works, this dissertation then charts Horace’s diffuse and sometimes unseen influence on a series of modern figures who use his carpe diem odes to think through gender, queerness, climate, addiction, and poetic production itself. Among the figures studied are poets such as Alcaeus, Lord Byron, Ernest Dowson, and Hope Mirrlees; jazz musicians such as Johnny Mercer and Bill Evans; and twentieth-century philologists

SOCIAL ISOLATION AND SOCIAL STRATEGIES AMONG DISADVANTAGED YOUTH

While social isolation and exclusion have long been central topics in Sociology, the study of interpersonal isolation and social strategies has been more limited. I use three sources of qualitative data to explore the role of social isolation and social strategies in the lives of young people. All three sources provide data from youth facing considerable disadvantage, but the diversity of contexts and study populations allow a deep exploration of the role of social strategies in different environments. Drawing from interviews with 150 youth born into Baltimore’s poorest neighborhoods, I find that social isolation is a prominent theme in the narratives of these youth, and many of the youth describe deliberate strategies regarding friendships. Having a selective social strategy, such as seeking positive associates or avoiding negative ones, appears to be beneficial in maintaining employment or school enrollment. Conversely, a more isolationist strategy does not appear to be beneficial. Having no social strategy is more common among those disengaged from both work and school. In exploring the friendship strategies of 28 migrants from Karamoja, Uganda, I find that these youth feel considerable pressure to achieve economic success as migrants while maintaining their reputations. Many intentionally seek friends whom they consider to have good character, and many avoid those considered to have bad character. They also value and seek friends who are generous with both intangible and tangible support. Some strategically limit their friendships. From my analysis of open-ended survey responses from 308 Ugandan sex workers, I find an emphasis on the stigma experienced by sex workers, and relatedly, the need for friends who are trustworthy and amenable to emotional intimacy. These youth also seek friends who are generous with support of various kinds. Many youth value friendships with fellow sex workers, particularly for the industry-specific advice and client referrals given by their peers. Some limit their friendships. Drawing from all three data sources, this dissertation argues that context is of central importance in the development of friendships in disadvantaged environments and that youth deploy social strategy in response to the pressures specific to the context in which they operate

Using Polygenic Risk Scores in Risk Prediction: From Health Care Costs to Absolute Risk

Polygenic risk scores (PRSs) are powerful tools that summarize cumulative additive effects of genetic variants, and have had increasingly more applications to risk stratification and clinical decision making with regards to chronic diseases. However, limitations to the use of polygenic risk scores include a lack of focus on a broader set of health outcomes, rather than disease incidence; the potential ramifications of PRS estimation uncertainty to affect clinical decision making; and the disparity in the efficacy of risk prediction in diverse populations, which could lead to exacerbating health inequities. Here, we analyze the joint association between PRS of a broad set of common diseases and related risk factors in the Atherosclerosis Risk in Communities study with health care expenditure and show that polygenic predisposition can predict future inpatient health care costs for males and females. We further explore the uncertainty in PRS construction by providing a framework for determining the impact of the posterior standard deviation of PRSs derived from Bayesian algorithms in clinical decision making, and find that such uncertainty makes little impact in the ranking and selection of individuals based on breast cancer risk within UK Biobank European ancestry women. Finally, we propose a flexible model for evaluation of the absolute risk of a disease and mortality taking into consideration polygenic predisposition, self-identified race and ethnicity, and genetic ancestry. Application of the model to All of Us individuals reveals importance of contextualization of risk using our framework to understand the true impact of the differential burden of polygenic risk across individuals of diverse background. Overall, this thesis advances understanding of the complex impact of polygenic predisposition to diseases and traits on the entire life-course of individuals, going beyond disease incidence and taking into account racial, ethnic and ancestral diversity