Molecular engineering

Permanent URI for this collectionhttps://digital.lib.washington.edu/handle/1773/44474

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De novo design of RNA and nucleoprotein complexes
(2026-04-20) Favor, Andrew; Baker, David
Nucleic acids fold into sequence-dependent three-dimensional structures and carry out diverse biological functions, much like proteins. However, while considerable advances have been made in the de novo design of protein structure and function, the same has not yet been achieved for RNA structures of similar intricacy. In this work, I describe the development of structure-generative diffusion models for generalized de novo biopolymer design, and I demonstrate their use in creating novel RNA folds and nucleoprotein complexes. With these tools in hand, I investigate design principles governing pseudoknot topologies and show how precise tertiary interactions can stabilize conformationally variable structures. I validate the robustness of this design approach through experimental characterization, demonstrating that designed sequences reliably self-assemble into their intended three-dimensional structures, and that engineered nucleoprotein complexes can be realized with high accuracy. Together, this work extends the principles of structure-based de novo protein design to nucleic acids and hybrid biopolymer assemblies, providing a foundation for creating a wide range of new structures and advancing the broader goals of molecular engineering.
Scalable De Novo Binder Design Enabled by Integrated Computational Design and High-Throughput Screening
(2026-04-20) Gokce Alpkilic, Gizem; Bhardwaj, Gaurav G
Proteins mediate nearly all cellular processes, and selectively binding protein surfaces is central to both biological discovery and therapeutic development. While recent advances in computational de novo design and structure prediction have accelerated in silico modeling, a persistent bottleneck is that computational confidence does not reliably translate into functional binding, especially for short, flexible ligands where conformational dynamics and context-dependent stabilization are difficult to capture with standard metrics. This dissertation develops integrated computational–experimental workflows for de novo discovery and optimization of protein-binding ligands across two complementary modalities. First, it establishes a benchmark for structure-guided design using compact, stable miniprotein binders against Francisella-like lipoprotein 3 (Flpp3), a previously ligand-free protein target, combining large-scale design, yeast surface display screening, and biochemical and structural validation to connect designed models to experimentally realized binding modes. This workflow yielded multiple nanomolar-affinity binders, including three picomolar-affinity leads. An X-ray crystal structure of Flpp3 in complex with a designed binder closely matches the design model (Cα RMSD: 0.9 Å), validating the design model at near-atomic resolution. The work then focuses on disulfide-stapled macrocyclic peptides, a modality that offers compactness and interface adaptability while remaining challenging to design predictively. To enable library-scale evaluation, the thesis introduces a genetically encodable disulfide-stapled format compatible with yeast surface display and optimizes the display architecture to sensitively measure expression and binding for short peptides. To assess generality across diverse binding contexts, this platform was applied to four representative targets -DnaN, GABARAP, PCSK9, and MCL1- collectively evaluating tens of thousands of unique de novo designs and additional mutational variants through high-throughput screening and affinity maturation. These campaigns yielded medium- to high-affinity peptide binders for each target. Together, these studies couple generative design to large-scale experimental selection, clarifying where functional binders emerge relative to computational metrics and enabling iterative, feedback-informed improvements to de novo peptide design in future discovery efforts.
Sustainably Sourced Bacterial Cellulose Nanoparticles for Cellular Drug Delivery
(2026-04-20) Balistreri, Gabrielle Nicole; Nance, Elizabeth; Roumeli, Eleftheria
Sustainable nanomedicine is an emerging field of nanotherapeutics to combat the environmental impact of current synthetic nanomaterials. Green chemistry and engineering are implemented at the early stages of nanoparticle design and processing to utilize biologically derived nanomaterials, minimize waste generation and the use of harsh solvents, and to create commercially scalable and eco-friendly nanotherapeutics.In this dissertation, we established bacterial cellulose nanoparticles (BCNPs) as a new generation of sustainable nano-platforms, using two independent syntheses to formulate 100 nm and negatively charged BCNPs for protein-based drug loading and cellular delivery. In the first formulation, BCNPs were grown in a kombucha co-culture media in agitated and aerated conditions for 24 h and size separated using centrifugation and polysorbate 80 as a stabilizing surfactant. We reported the BCNPs to be primarily amorphous and thermally stable up to 90 °C. We also performed proof of concept studies to show drug loading capabilities by incorporating bovine serum albumin (BSA) as a model drug and quantified sustained release of BSA. These findings further motivate the use of BCNPs as a promising protein-based therapeutic platform. In a second process to generate nanoparticles, BCNPs were formulated via nanoprecipitation using dissolved bacterial cellulose (BC) in dimethylacetamide and lithium chloride and Pluronic® F-127 as a surfactant. Surface chemistries, such as hydroxyl-, methyl-, acetyl-, and amino- functional groups were applied to BC prior to formulation to create tunable and chemically functional nanoparticles for cellular delivery. Fourier Transformation Infrared Spectroscopy validated the presence of functional groups, and X-ray crystallography and atomic force microscopy revealed distinct structural consequences of the functionalization: 1) methylation caused complete amorphization and lack of nanofibril assembly; 2) acetylation reduced but did not eliminate crystallinity; 3) amination preserved the cellulose backbone connectivity but disrupted long-range order. We assessed the colloidal stability of the functionalized BCNPs in biologically relevant salt- and protein-based environments, where methyl- and amino-BCNPs remained dispersed for 48 h and acetyl-BCNPs agglomerated out of suspension; in comparison, hydroxyl-BCNPs gradually flocculated in salt-based media. To investigate the use of BCNPs for drug delivery to the brain, BCNPs were evaluated in an organotypic whole hemisphere (OWH) brain slice model and exhibited low cytotoxicity (<10%). In the OWH brain slice, we observed functional group-dependent localization and uptake in microglia cells, the brain’s resident immune cell population. Through this body of work, we have developed a small library of innovative BCNPs as a sustainably derived nanoplatform that show good biocompatibility and potential for targeted cell delivery. This foundational work to establish a BCNP platform provides a promising approach to generate eco-friendly nanotherapeutics.
De Novo Design of Antibacterial Therapeutics and Immune Modulating Proteins
(2026-04-20) Chazin-Gray, Adam; Baker, David
Poor antibiotic stewardship and other factors have accelerated the emergence of bacterial pathogens resistant to many frontline antibiotics, creating an urgent need for new therapeutic strategies. While advances in de novo protein design have enabled the rapid development of protein-based therapeutics against viral pathogens, snake venoms, and cancer targets, few efforts have successfully translated these approaches to bacterial pathogens, in part due to challenges in identifying tractable therapeutic targets. The central question that I sought to address during my PhD was how de novo protein design tools can be applied to identify and exploit bacterial therapeutic vulnerabilities, enabling the development of novel protein-based therapeutics. In this talk, I will outline the design principles and target classes that have emerged as particularly promising for protein-based intervention against infections by multidrug-resistant bacteria.
Protein Design at Library Scale
(2026-02-05) Gershon, Jacob; Baker, David
Recent advances in de novo protein design have made it increasingly feasibleto create proteins with novel functions, driven by rapid progress in both com- putational modeling and high-throughput experimentation. Modern tools can explore vast sequence-structure spaces and evaluate biomolecular interactions, while experimental assays can now screen billions of variants in parallel. Yet, a key limitation remains: our current predictive models still struggle to capture the complex physical and dynamical factors that underlie enzyme function. My the- sis addresses this gap by developing an integrated experimental–computational framework for enzyme design that couples large-scale protein library construc- tion with data-driven model development. I design and test extensive libraries of enzyme variants to both optimize catalytic activity and generate training data for next-generation predictors of protein function. Ultimately, this approach ad- vances our ability to connect sequence, structure, and function.
Variety is the spice of life: engineering tools for visualizing transcriptional heterogeneity and its effect on cell differentiation in Arabidopsis
(2026-02-05) Maranas, Cassandra; Nemhauser, Jennifer L
Two genetically identical cells exposed to the same signals will have differences in gene expression. Despite this variability, multicellular development proceeds remarkably robustly in most cases. How and when variation on the cellular level manifests in multicellular coordination and organogenesis is not well understood. Cell-to-cell variation in gene expression can be highly detrimental and actively buffered out; however, in other contexts, it is crucial and actively amplified. For example, variation must be minimized to build organs with consistent size and shape, yet the initiation of organogenesis requires a subset of cells to take on a new fate, a process that often relies on small differences between cells. Aiming to uncover the manifestation of cell-to-cell variation in development, I built a series of serine integrase-based transcriptional recorders to visualize cell-to-cell variation, and then used these tools to analyze Arabidopsis stomatal development and root initiation. In addition, I helped engineer tissue-specific Integrase Erasers to study essential genes. Finally, I showed that the plant hormone auxin acts as a gene expression driver and coordinator in root initiation. Auxin triggers cell-to-cell expression variation by assigning some cells a root precursor fate, while at the same time ensures that these precursor cells are coordinated for robust root formation. My thesis has provided genetic tools for synthetic biologists to apply across applications, and has also demonstrated how the application of these tools can elucidate the role, manifestation, and management of variation in development.
Development of Aptamer Technologies for Immune Cell Isolations
(2026-02-05) Ling, Melissa; Pun, Suzie H
Aptamers are short, single-stranded nucleic acid molecules that bind to target molecules with high affinity and specificity. Due to their cheap synthesis, long-term stability, and homogeneity, aptamers have emerged as an attractive affinity reagent for cell separations. Aptamers are discovered through a process called Systematic Evolution of Ligands by Exponential Enrichment (SELEX). However, traditional SELEX strategies are labor-intensive and lead to many nonspecific binders, limiting the translational application of aptamers. Chapter 1 introduces aptamers, the SELEX method, and the application of aptamers as affinity ligands for protein and cell separations. In Chapter 2, we develop a novel method to discover new aptamers for applications in immunotherapy using a protease-cleavable membrane protein expressed in mammalian cells. In Chapter 3, we employ a CD36-binding aptamer to isolate monocytes from peripheral blood mononuclear cells (PBMCs) on a magnetic column with high purity and yield. In Chapter 4, we adapt aptamers to a scaled-up, resin-based isolation system for high-throughput depletion of monocytes and selection of CD8+ T cells from PBMCs. Chapter 5 highlights the advantages of cleave-SELEX in aptamer discovery and the use of aptamers in immune cell isolations and presents future work for cleave-SELEX and the CD36 aptamer.
Metabolic Engineering Tools for Sustainable Bioproduction in Bacterial Systems
(2025-08-01) Cardiff, Ryan Asher Levine; Carothers, James M; Zalatan, Jesse G
The chemical industry’s reliance on fossil fuels drives significant carbon emissions, emphasizing the urgent need for sustainable alternatives. Microbial bioproduction presents a promising solution by enabling the synthesis of valuable chemicals from renewable feedstocks, such as CO2 and biomass waste. However, the ability to address wide chemical markets with bioproduction is limited by insufficient tools for metabolic pathway engineering and precise gene regulation. This work describes several strategies to improve bioproduction by prototyping engineered metabolic pathways and complex gene regulatory programs. We utilize an E. coli-based cell-free gene expression system to engineer high-performing synthetic promoters and investigate pathways for carbon-conserving bioproduction of industrially relevant chemicals. We then discuss recent progress and opportunities at the intersection of CRISPR-based metabolic engineering and systems-level modeling approaches for improved bioproduction. Finally, we adapt the RNA-targeting CRISPR-dCas13 system as a next-generation CRISPR tool to improve metabolic regulation in bacteria. Collectively, these works describe the development of several tools that advance metabolic engineers’ ability to construct complex gene expression programs, prototype engineered carbon-conserving pathways, and precisely regulate metabolism across bacterial genomes. These tools offer new approaches to engineer microorganisms that can incorporate renewable carbon feedstocks and efficiently upcycle them into value-added chemicals, advancing the goals of sustainable bioproduction and a reduced global reliance on fossil fuels.
Building and utilizing protein-based nanoparticles to modulate immune pathways
(2025-08-01) Tooley, Marti Rae; King, Neil; Baker, David
The goal of vaccines is to appropriately stimulate the immune system to elicit potent and long-term protection against each pathogen. Current vaccines boost immune activation with adjuvants, which most commonly consist of oil-in-water emulsions despite the fact that the mechanisms of action of these adjuvants are not fully understood. Recent research has turned to molecular adjuvants with the aim of tuning the immune system with greater precision. However, these approaches are currently limited by the lack of platforms that can systematically test an antigen alongside immune-activating proteins. Control over the spatial arrangement and combination of immune ligands is needed to better understand how to modulate the complex immune responses surrounding an antigen of interest. Protein design has enabled the creation of two-component, self-assembling protein nanocages that serve as scaffolds for displaying functional domains, including antigens, antibodies, and immune proteins. The goal of my research is to leverage these two-component protein nanoparticle platforms to identify immune-modulatory proteins that can enhance the potency of nanoparticle immunogens and to develop a new platform capable of driving immune cell colocalization to activate juxtacrine signaling.
Synthetic Polymers To Address Multiscale Drug Delivery Challenges For Cancer Immunotherapy
(2025-08-01) Nguyen, Dinh Chuong; Pun, Suzie H; Stayton, Patrick S
Immunotherapy has revolutionized cancer treatment, yet its clinical impact is limited by toxicity and/or low therapeutic response in many different tumor types. Eliciting optimal spatiotemporal antitumor immune responses is crucial to overcoming this hurdle, but is complicated by multiscale drug delivery challenges to immune activators. This work utilizes targeted, bioresponsive synthetic polymeric drug delivery platforms to address these challenges in engineering next-generation cancer immunotherapies. First, we adapted the Virus-Inspired Polymer for Endosomal Release (VIPER) platform to cytosolically deliver peptide antigens to lymphatic dendritic cells (DCs) for cancer vaccination. Co-polymerized mannose ligands confer lymph node targeting and DC internalization, while the VIPER design selectively lyses maturing endosome to release peptide antigens into the cytosol. This induces superior cytotoxic T-cell activation and tumor suppression compared to simple peptide vaccines and non-endosome releasing designs. Next, we engineered a targeted polymeric prodrug of Stimulator of Interferon Genes (STING) agonist for targeted immune activation in DCs in an intravenous immunotherapy application. A STING agonist is formulated into a monomer with an endosomal cathepsin-labile linker, and co-polymerized with mannose to form a STING ‘drugamer’ (polySTING) that selectively delivers agonist to DCs. Intravenous polySTING administration results in a DC-driven immune cascade that potently suppresses tumor growth in aggressive murine tumor models. Structural variants of STING drugamers were then co-formulated with VIPER to yield two distinct STING-adjuvanted polymeric vaccines that achieved partial remission through distinct antitumor immunity mechanisms. Finally, a T-cell-targeted cationic brush polymer platform is being developed for T-cell transfection for Chimeric Antigen Receptor (CAR) T-cell production.
Structure based stabilization of native-like antigens with deep learning
(2025-05-12) Jasti, Naveen; King, Neil
Effective vaccines prevent illness and death by stimulating protective immune responses against infectious pathogens. Protective immune responses can recognize and neutralize antigens that are important proteins used by pathogens to infect and replicate. However, these key proteins often evolve multiple conformations or instability to infect and evade the host immune system. Structure-guided design has advanced vaccine development by introducing mutations that stabilize these proteins to elicit stronger immune responses. Deep learning based methods have transformed our ability to predict and design protein structures. In this work, I investigated how to best apply these novel protein design methods to the stabilization of native-like antigens. I focused on four pathogens that cause significant morbidity and mortality: Human Rotavirus, Group A Streptococcus, Mycobacterium tuberculosis, and Rabies virus. For each pathogen, I chose key proteins that are compelling vaccine targets and present distinct challenges for antigen stabilization. By pairing existing methods with novel deep learning based tools, I identified mutations that improve antigen stability and immunogenicity. In the process, I have identified principles which may be applicable for structure guided design across a wide range of antigens.
Interactions at the interface between proteins and minerals
(2025-05-12) Stegmann, Amy Elizabeth; De Yoreo, James
Interactions at the interfaces between proteins and minerals drive both protein binding onto the surface of minerals and mineral formation on the surface of proteins. Understanding these interactions is fundamental to the rational design of self-assembling hierarchical structures. De novo designed proteins enable the precise placement of chemical functional groups in three-dimensional space and are thus ideal for investigating organic-mineral interactions. This research has been targeted to address both protein assembly and mineral formation. We investigated the role of charge patchiness in proteins that drive the formation of mineral crystals from precursors in solution. By designing charged template proteins, we gain insight into the assembly mechanisms of titanium oxides from titanium(IV) bis(ammonium lactate)dihydroxide (TiBALDH), where surface-displayed carboxyl and amine groups direct nucleation at room temperature, demonstrating sequence-driven control over titania nucleation phase and spatial organization using homo-oligomeric protein assemblies with D3 symmetry. We characterized the formation and growth of titanium dioxide as directed by the surface charge of various protein assemblies and developed the design principle that alternating positive and negative regions is optimal for forming titanium dioxide. Our research demonstrates that the precise control over functional group placement available to de novo designed proteins enables access to novel assemblies and can influence the crystallinity and morphology of mineral formation. We also employed machine learning and conventional analysis of high-speed atomic force microscopy data to better describe the assembly process of protein nanorods into a liquid crystal arrangement on the surface of mica and the interactions and solution conditions required for that liquid crystal to form. The symmetry of the mineral substrate and the resultant solution structure at the mineral surface influences the symmetry of the protein assembly. The designed interface of the protein allows access to an ordered assembly at the surface. These findings highlight the potential of de novo designed proteins to serve as precise scaffolds for controlling mineral nucleation and assembly, paving the way for the development of tailored bioinspired materials with tunable properties.
Biophysical and mechanistic impacts of small molecule and polyanionic aggregation modulators on tau4RD
(2025-05-12) James, Ellie; Nath, Abhinav; Guttman, Miklos
Tau is an intrinsically disordered protein (IDP) that pathologically aggregates in Alzheimer's disease and over twenty other neurodegenerative diseases known as tauopathies. Unlike structured proteins that exhibit one (or several) folded conformations, IDPs populate dynamic and interchanging conformational ensembles. This makes IDPs difficult to study structurally and challenging as drug targets. During aggregation, tau's ensemble is perturbed so that the disordered monomers assemble into ordered cross-beta-sheet amyloid structures. Recent advances in cryo-EM have revealed that many of the amyloid fibrils generated in different tauopathies display disease-specific morphologies. These morphologies are reproducible through prion-like seeding both in vivo and in vitro. While these observations imply that tau has a tunable self-assembly landscape, the structural and kinetic mechanisms that control tau's amyloid morphology remain unclear. Further, there could be great therapeutic potential in targeting species early in tau's aggregation pathway; aggregation intermediates (i.e., mid-stage oligomers) are considered toxic in neurodegenerative disease. Here, we describe the discovery and characterization of tryptanthrin and its synthetic analogs as extremely potent tau inhibitors that target the earliest stages of aggregation. We follow this with a pulsed hydrogen-deuterium exchange mass spectrometry (HDX-MS) investigation into the origins of tau's amyloid heterogeneity and find evidence that distinct amyloid morphologies are encoded at the start of aggregation. Together, these findings address critical open questions regarding drug development for IDPs and the timeline of amyloid structural divergence.
Applications of Machine Learning in The Optimization of Genetically Encoded Optogenetic Sensors
(2025-05-12) Wait, Sarah June; Berndt, Andre
Naturally occurring proteins provide a wealth of opportunities as tools in research, industry, and medicine. However, native proteins are rarely well suited for usage outside their biological setting. Therefore, the protein's functional ability and stability must be optimized by mutating its amino acid sequence. This challenge is complicated by the vastness of each protein's mutation space, where mutants containing desired biophysical characteristics are rare and become more difficult to find as more specifications are required. Traditional engineering techniques, such as point-mutation screening, compound this issue by being time- and resource-intensive. Here, we present an alternative approach that harnesses machine learning models to learn from sequence-to-function libraries and screen untested mutants computationally. To showcase this technique, we identified variants of the genetically encoded calcium sensor, GCaMP, that improved the fluorescent response by 5-fold (eGCaMP2+) and increased the decay speed by 3-fold (eGCaMP). To further demonstrate the capabilities of our machine learning platform, we utilized the same approach to engineer the functional capabilities of the red-shifted calcium indicator jRCaMP1b. Our study indicates that machine learning can efficiently learn from complex mutational datasets and harness their predictive power to guide the engineering of functional proteins. This methodology is poised to shift the protein engineering landscape by providing alternative methods to rapidly engineer proteins for desired characteristics.
Bottom-up design of calcium channels from selectivity filters
(2025-01-23) Liu, Yulai; Baker, David
Native ion channels play key roles in biological systems, and engineered versions are widely used as chemogenetic tools and in sensing devices. Protein design has been harnessed to generate pore-containing transmembrane proteins, but the capability to design ion selectivity based on the interactions between ions and selectivity filter residues has been constrained by the lack of methods to place the metal-coordinating residues with atomic-level precision. Here we develop a bottom-up approach to construct Ca2+ channels from selectivity filters with different coordination numbers and different geometries. Patch-clamp experiments show that the designed channels have higher conductance for Ca2+ than for Na+ and other divalent ions (Sr2+ and Mg2+). Cryo-electron microscopy shows that the structure of a designed Ca2+ channel is nearly identical to the design model. Our bottom-up design approach now enables the testing of hypotheses relating filter geometry to ion selectivity and provides a roadmap for creating selective ion channels for a wide range of applications.
Modular, targeted polymeric-prodrugs for the treatment of infectious diseases
(2025-01-23) Pottenger, Ayumi Epona; Stayton, Patrick
Infectious diseases have haunted mankind since time immemorial, from the oldest strains of Mycobacterium through the recent coronavirus pandemic. There is constant need for new and improved therapies in our never-ending arms race against pathogens. Reversible addition-fragmentation chain transfer (RAFT) polymerization is characterized by its broad range of polymerizable monomers, precise control of chain growth, and general ease of use without the need for toxic transition metals. These qualities make RAFT-based polymers a useful platform for drug delivery, where modularity, user-friendliness, reproducibility, and reduced lead time all contribute to a better, more cost-effective therapeutic platform. This work describes RAFT-based polymeric prodrugs which carry fully synthetic, enzyme- cleavable small molecule therapeutics to specific cell populations– a platform termed drugamers. The first portion of this work focuses on a serum stable peptide linker which improves the pharmacokinetic profile of the anti-malarial drug tafenoquine for the treatment of Plasmodium vivax malaria. P. vivax treatments, including tafenoquine, are contraindicated in patients with G6PD-deficiency due to an increased risk of hemolytic anemia. This design showed efficacy in a causal prophylaxis model using Plasmodium berghei-infected mice and reduced hemotoxicity in a humanized mouse model of G6PD-deficiency. The second portion of this work describes an inhalable, alveolar macrophage-targeted drugamer carrying dexamethasone for the treatment of pulmonary infection, particularly hyperinflammatory diseases such as COVID-19. This polymer design improved the pharmacokinetic profile of dexamethasone relative to free drug and reduced inflammation in a lipopolysaccharide-induced lung injury model. These projects highlight the versatility of drugamers as carriers for small molecule therapeutics to treat infectious diseases.
Optogenetic Methods for Spatiotemporally Resolved Observation of H2O2 in Biological Systems
(2025-01-23) Lee, Justin; Berndt, Andre
While hydrogen peroxide (H2O2) is widely recognized as a key redox signaling molecule essential for normal cellular functions, its supraphysiological accumulation is associated with the pathogenesis and progression of various diseases—including atherosclerosis, Duchenne muscular dystrophy (DMD), Alzheimer’s disease, and cancer—making it a primary target of antioxidative therapeutics. Due to its significant physiological role, precise understanding of peroxide dynamics at both intracellular and intercellular levels is crucial for effective and safe therapeutic discovery. Developing tools that enable site-specific and real-time detection of H2O2 in cells and model organisms is therefore essential.Guided by experimental and computational structural analyses, we engineered oROS, a multicolor fluorescence sensor suite for highly sensitive, real-time, in situ detection of H2O2. From human stem cell-derived models to animal models, oROS sensors demonstrate robust functionality in clinically relevant systems for studying peroxide biology. For instance, oROS elucidated the therapeutic efficacy of a putative antioxidative agent for Alzheimer’s disease and detected H2O2 signals in vivo to validate the NADPH oxidase-dependent opioid receptor inactivation mechanism in a systemic context. Furthermore, its multiplexed use with calcium and redox potential indicators enabled time-locked monitoring of H2O2 in relation to its key interactants. Lastly, oROS sensors were targeted to various subcellular compartments, including microdomains near the inner and outer plasma membranes, providing unprecedented precision in monitoring membrane H2O2 topology. We envision that oROS and its applications will stimulate new questions and discoveries in redox biology and medicine.
Inference of In Situ Microbial Physiologies via Sparse Tensor Decomposition of Metatranscriptomes: Application to Cyanobacteria Populations in the North Pacific
(2025-01-23) Blaskowski, Stephen; Armbrust, E. Virginia
Microbes respond to changes in their environment by adjusting their physiology through shifts in gene expression, which can be measured in the field by whole community RNA sequencing. The resulting metatranscriptomic data is inherently noisy, with unknown gene functions and fluctuations in organism abundance, all of which limit the utility of traditional methods. In the first chapter of this dissertation, I developed a novel statistical approach that uses sparse tensor decomposition to uncover patterns of gene co-expression. In the second chapter, I applied the method to metatranscriptomic data collected in the North Pacific, focusing on marine cyanobacteria, a group of highly abundant microbes that are responsible for up to a quarter of photosynthesis in global oceans. The analysis uncovered 25 robust co-expression patterns, including four that clarified how cyanobacteria respond in nature to scarce nitrogen and iron nutrients. In the final chapter I looked into another co-expression pattern that revealed how cyanobacteria respond to viral infection, placing this in the context of population diversity and evolution. Altogether this dissertation demonstrates the power of a new analytical approach to elucidate: 1) the functions of unknown genes, 2) how different organisms respond to environmental pressures, and 3) the ways in which microbial physiology and biogeochemical cycles interconnect in a changing ecosystem.
Brain-Derived Extracellular Vesicles as Therapeutic Vehicles and Molecular Probes in the Neonatal Brain
(2024-10-16) Nguyen, Nam Phuong; Nance, Elizabeth
In the central nervous system (CNS), intercellular communication through extracellular vesicles (EVs) is crucial for sustained trauma response and tissue repair following injury. EVs are biologically derived nanoparticles released by every cell that carry a diverse cargo of biomolecules important for cell communication including proteins, lipids, carbohydrates, and genetic material. The contents of EV cargo is an active research question in the field, and has been shown to be dependent on cell type, as well as environmental and physiological changes. As EVs are both produced and trafficked by cells, they are strong therapeutic candidates with several inherent design advantages over existing nanoparticle therapeutics: biostability, biocompatibility, lipid bilayer protection of cargo, and inherent cell uptake mechanisms. These advantages are especially important for drug delivery to the brain, which presents several therapeutic barriers such as the cerebral spinal fluid barrier and tortuous brain parenchyma. In addition, the blood brain barrier (BBB) poses a great challenge for therapeutics researchers as it excludes 98% of all small molecule and macromolecular drugs from passing but EVs have demonstrated an ability to cross. Despite growing interests in advancing EV therapeutics for brain injury and disease, there are two significant challenges hindering their development and clinical translation: 1) lack of physiologically relevant EV models and 2) a need for greater clarity about EV localization and transport in brain tissue. To address the first challenge, I evaluated the therapeutic efficacy of EVs derived from brain tissue (BEVs), rather than the standard approach of using EVs from cell culture. Compared to EVs derived from 2D cell monoculture models, those derived from 3D tissue are more physiologically relevant as they represent a heterogenous population that mirrors the existence of diverse cell types found in native brain tissue. When evaluating the therapeutic potential of BEVs in an ex vivo model of oxygen glucose deprivation (OGD), BEVs exhibited dose- and time-dependent therapeutic effects on injured tissue. BEVs induced a shift in the microglial morphology of OGD tissues from an inflammatory towards a restorative phenotype, while simultaneously increasing anti-inflammatory cytokine expression and decreasing cell cytotoxicity. These promising results led to further studies to address the second challenge—a lack in understanding about BEV localization and transport. To track BEVs in the brain we conjugated BEVs to either quantum dots (QDs) or novel oligonucleotide biobarcodes (oligobarcodes) using an efficient click chemistry reaction. Through a combination of confocal imaging and multiple particle tracking, the QD conjugation allowed us to visualize the spatial distribution of BEVs in brain tissue, which was regionally dependent. QD conjugations also allowed us to track BEV transport properties in real-time to confirm that BEV behavior was regionally dependent. We then used oligobarcoded BEVs to quantitatively measure the BEV uptake in both glial and non-glial cells in healthy and OGD brain tissue. Microglia, the resident immune cell of the brain, exhibited increased and preferential uptake of oligobarcoded BEVs compared to blank oligobarcode controls. We then expanded our oligobarcode-EV conjugation strategy to study the uptake of semen-derived EVs in the vaginal tract, demonstrating the broad translational opportunities that our platform provided to tracking EVs from any source. Collectively this work demonstrates the therapeutic potential of tissue-derived BEVs and offers a dual-conjugation technique to visualize and track EVs from any source in physiological environments. Our novel QD and oligobarcode conjugation strategy is an accessible technique that can be translated across different biological models to provide both quantitative and qualitative evaluation of EV visualization and tracking that will advance the EV therapeutics landscape.
Reducing Recombination in Halide Perovskite Solar Cells via Interface Engineering
(2024-09-09) Shi, Yangwei; Ginger, David S.
Halide perovskite solar cells have attracted tremendous attention and have been extensively studied over the last decade. Though the power conversion eciency of single junction of perovskite solar cells has reached 26.1%, it still lags behind the theoretical limit, which is largely due to the open-circuit voltage deficit that results from nonradiative recombination in the bulk of perovskite films and also at the interfaces between perovskite and transport layers. When transport layers contact with perovskite, it generally induces new nonradia- tive loss pathways at the interface, resulting in a decrease in device performance. In this dissertation, we engineer the interface of perovskite solar cells to minimize the nonradiative recombination loss via interlayer engineering, electronic decoupling, and surface field, to further enhance perovskite solar cells performance.First, we investigate a photo-crosslinkable naphthalene diimide polymer as the electron- transport layer for n-i-p perovskite solar cells. Inorganic metal oxides such as titanium dioxide (TiO2) and tin oxide (SnO2) have been widely used as the electron-transport layer in n-i-p perovskite solar cell. Nevertheless, these inorganic materials require high annealing temperature and may incur instability of the perovskite layer due to photoactivity. Organic polymers as electron-transport layers offer a new pathway for perovskite solar cells because of their low processing cost, good chemical and thermal stability, and ability to tune the energy levels. Thus, we study the thermal stability, conductivity with and without doping and solvent resistance of naphthalene diimide polymer. Furthermore, we incorporate the photo- crosslinkable naphthalene diimide polymer into perovskite solar cell as electron transport layer, studying the impact of this photo-crosslinkable polymer on device performance. We further explore the influence of this polymer on the structure and optoelectronic properties of perovskite film. Next, we focus on studying the surface/interface passivation of perovskite layer in p- i-n perovskite solar cells. Halide perovskite is polycrystalline material which has many grain boundaries. These grain boundaries as well as perovskite top surface are most defective due to abruptly broken atomic lattice and unsatisfied dangling bonds at a surface/interface, which results in enhanced electron-hole nonradiative recombination. We demonstrate reduced surface recombination velocity (SRV) and enhanced power-conversion eciency (PCE) in mixed-cation mixed-halide perovskite solar cells by using a surface pas- sivator called (3-aminopropyl)trimethoxysilane (APTMS). We show the APTMS serves to passivate defects at the perovskite surface, while also decoupling the perovskite from detrimental interactions at the C60 interface. Lastly, we design two ionic pair salts as interlayers and apply them in between wide bandgap perovskite and C60 layer. Wide-bandgap perovskite can be integrated in the perovskite/silicon tandems to overcome the theoretical limit of single junction solar cells. However, the substantial nonradiative interfacial recombination at the perovskite/C60 interface, limiting open-circuit voltage VOC and thus PCE. We show that benzylammonium tosylate (BzAOTs) and benzylammonium triflate (BzAOTf) interlayers reduced interfacial nonra- diative recombination at the perovskite/C60 interface and enhanced VOC in mixed-halide mixed-cation wide-bandgap (1.7 eV) perovskite solar cells. We unveil that The BzAOTs interlayer improves the device performance through reducing the interfacial nonradiative recombination via surface field while BzAOTf decouples the perovskite film from the detrimental interactions at C60 interface. Our research highlights that engineering interface in perovskite solar cell is an effective approach to reduce recombination in perovskite solar cell, which provides valuable insights for device optimization.

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