• 2:00 p.m. - Opening Remarks from BioE Program Deputy Director, Levi Wood
• 2:30 p.m. - Icebreaker / Networking Roundtable Discussions
• 3:30 p.m. - Opening Keynote Presentation: “From Grad School to Industry: Lessons Learned” - Distinguished BioE Alumnus
• 5:00 p.m. - Networking Dinner, Graduate Student Poster Session

Day 2: Friday, April 24, 2026
~ Research, Professional Branding, and Collaborations ~

• 10:00 a.m. - Lab tours led by graduate students
• 11:00 a.m. - Campus tours
• 12:00 p.m. - Lunch and Learn Panel: Academic-Industry Collaborations
• 1:30 p.m. - Interactive Session: Building Your Professional Brand to Increase Impact
• 2:30 p.m. - Reflections on Maintaining Connections within the GT BioEngineering Community
• 3:30 p.m. - Closing Keynote Presentation: “The Future of Bioengineering” - Distinguished BioE Alumnus
• 5:00 p.m. - Closing Dinner Reception - Georgia Tech Hotel & Conference Center

Symposium Organizers:
Lauren Priddy, Ivana Parker, Laura Paige
 

Ahmet F. Coskun, Ph.D. (Biomedical Engineering, Georgia Institute of Technology)

Committee:

Peng Qiu, Ph.D. (Department of Biomedical Engineering, Georgia Institute of Technology)

Saurabh Sinha, Ph.D. (Department of Biomedical Engineering, Georgia Institute of Technology)

Rabindra Tirouvanziam, Ph.D. (Department of Biomedical Engineering, Georgia Institute of Technology)

Marcus Cicerone, Ph.D. (Department of Chemistry & Biochemistry, Georgia Institute of Technology)

Timeseries Spatial Omics of Immune Cell Signaling in Inflammation

Cystic fibrosis (CF) affects over 162,000 people worldwide. Although FDA-approved therapies have shown promising results, chronic inflammation and bacterial infections persist, causing tissue damage and worsening quality of life despite a large immune cell presence. This thesis investigates the spatiotemporal dynamics of NF-κB signaling during inflammation by developing and applying spatial omics tools at the single-cell level across multiple biological contexts.

We first introduce PRISMS, an open-sourced, automated multiplexing pipeline for spatial transcriptomic and proteomic imaging compatible with Nikon widefield and Cephla spinning disk confocal microscopy. Using PRISMS, we apply pSigOmics static fixation to profile over 100,000 mouse fibroblasts stimulated with TNFα and IL-1β, revealing a novel asymmetric protein-RNA (APR) relationship between p65 RNA and protein. Graph neural network classification and PHATe trajectory analysis further delineate distinct APR subpopulations among stimulated fibroblasts.

We next extend pSigOmics with programmable fixation via helical perfusion to create a continuous gradient of cell response, confirming the APR phenomenon with finer temporal resolution through cross-correlation, generalized additive model smoothing, and pseudotime analyses. Together, static and programmable fixation establish a comprehensive spatiotemporal framework for studying oscillatory translational regulation in single cells.

We then develop graph-based super-resolution protein-protein interaction (GSR-PPI) analysis to predict cancer drug responses from spatial PPI networks in lung adenocarcinoma cells and patient-derived NSCLC tissues, and introduce multiplexed iterative sequential PLA (iseqPLA) to visualize 3D NF-κB supercomplex dynamics. Upstream supercomplexes containing TRAF-5_TRADD and TRAF-5_TRAF-2 undergo rapid dissociation upon cytokine stimulation, inversely correlated with p65 nuclear translocation. Macrophage-fibroblast coculture experiments reveal that CF airway supernatant-exposed macrophages impart a hyperinflammatory phenotype to neighboring fibroblasts through paracrine NF-κB activation. We additionally validate our NF-κB gene panel using scGPT foundation models trained on multi-disease transcriptomic datasets, establishing a mechanistic link between protein-level supercomplex dynamics and transcriptional outputs.

These contributions demonstrate the power of combining spatial multiplexing, temporal reconstruction, and computational modeling to decode immune signaling at single-cell and subcellular resolution, with implications for understanding chronic inflammation in CF and identifying opportune windows for therapeutic intervention.

James C. Gumbart, Ph.D. (School of Physics, Georgia Institute of Technology)  

Committee:  

M. G. Finn, Ph.D. (School of Chemistry and Biochemistry, Georgia Institute of Technology)

Peter Kasson, Ph.D. (School of Chemistry and Biochemistry; Coulter Department of Biomedical Engineering, Georgia Institute of Technology)

Jeffrey Skolnick, Ph.D. (School of Biological Sciences, Georgia Institute of Technology)

Adegboyega Oyelere, Ph.D. (School of Chemistry and Biochemistry, Georgia Institute of Technology)

Modulating Hepatitis B Virus Capsid Assembly and Function through Pharmacological Intervention  

Hepatitis B virus (HBV) is a major global health burden that causes chronic liver disease. Its replication depends on the assembly of a protein capsid, making this process an important target for antiviral intervention. This work integrates molecular dynamics simulations and biophysical experiments to investigate how small molecules interact with and modulate the HBV core protein across different structural contexts. First, biophysics-guided approaches were used to identify ligands targeting the inter-dimer assembly interface, showing that small molecules can perturb capsid assembly through changes in inter-subunit interactions. Second, free-energy calculations were conducted to characterize the conformational landscape of a key assembly intermediate, providing insight into structural features that may influence assembly nucleation. Third, a distinct intra-dimer pocket was characterized using fragment-based mapping and pharmacophore modeling, enabling virtual screening and experimental validation of ligands with extended binding modes. Together, these results provide a framework for understanding how small molecules can modulate HBV capsid behavior and highlight new directions for antiviral design.

Committee:

Alexander Alexeev, Ph.D. (ME, Georgia Institute of Technology)

Scott Danielsen, Ph.D. (MSE, Georgia Institute of Technology)

David Myers, Ph.D. (BME, Georgia Institute of Technology)

Guillem Pratx, Ph.D. (Radiology and Medical Physics, Stanford University) 

Optimization of Forces, Loading Rates and Strain for Cytosolic Delivery using Mechanoporation  

Efficient intracellular delivery of cargo remains a central challenge in biomedical engineering to improve gene editing, cell therapy production, and cell diagnostics. The optimal delivery not only introduces cargo into cells but achieves cytosolic access while preserving cell viability and normal function. Existing approaches often fall short of this balance. Viral and carrier-mediated methods can promote uptake of molecularly encoded genes but are limited by endosomal entrapment and intracellular degradation. Electroporation can disrupt cell membranes but also disturbs normal cellular physiology. These limitations have motivated interest in microfluidic mechanoporation, in which cells are transiently permeabilized through controlled mechanical deformation. However, the mechanism of mechanoporation remains poorly defined and, as such, performance remains difficult to predict and standardize. To bridge the gap, this dissertation establishes a framework connecting device geometry, transient loading dynamics, and delivery outcomes. A key learning is that mechanoporation performance is demonstrated to be better explained by cell loading kinetics than by deformation magnitude alone. Systematic channel width and ridge angle variation demonstrates how tuning force rate, directionality, and loading history improves delivery efficiency, cell survival and experimental consistency. Integration of high-speed trajectory analysis, computational fluid dynamics (CFD), and multivariate modeling further reveals that steady-state descriptors such as strain magnitude are insufficient to explain mechanoporation outcomes, which instead, correlate strongly with strain rate and history-dependent hydrodynamic forces. Extending these insights to nanoparticle delivery, imaging analyses demonstrate that optimized device geometries enable deeper intracellular access and improved cargo retention relative to conventional incubation-based approaches. Together, these results provide a force-based framework for mechanoporation that links device design to biologically meaningful intracellular delivery.

Dr. Young Jang, Emory Musculoskeletal Institute, Department of Orthopedics, Wallace H. Coulter Department of Biomedical Engineering Emory School of Medicine & Georgia Institute of Technology 

Dr. Melissa Kemp, Wallace H. Coulter Department of Biomedical Engineering, Emory School of Medicine & Georgia Institute of Technology 

Dr. Srikant Rangaraju, Department of Neurology, Yale University 

Dr. Annabelle Singer, Wallace H. Coulter Department of Biomedical Engineering, Emory School of Medicine & Georgia Institute of Technology

Rewiring CSF1R signaling in Alzheimer’s disease

Alzheimer's disease (AD) is the leading cause of dementia, affecting approximately 7 million people in the United States, yet no effective cure exists. The repeated failure of therapies targeting amyloid beta (Aβ) underscores the complexity of the disease and has shifted attention toward neuroinflammatory mechanisms, particularly the role of microglia. Colony stimulating factor 1 receptor (CSF1R) is the predominant regulator of microglial survival and function in the brain and has been widely used as a tool to deplete microglia. Despite its established role in microglial biology, the mechanisms by which AD pathology alters CSF1R signaling and its downstream consequences for microglial behavior remain poorly understood. Here, I investigated whether the AD microenvironment reshapes CSF1R-mediated signaling in a context-dependent manner and whether this transformation can be therapeutically exploited. Proteomic analysis of postmortem human AD brain tissue revealed that CSF1R co-expressed protein networks are completely distinct from those of age-matched controls, with disease-associated networks enriched for neurodegeneration and inflammatory pathways. Across multiple in vitro systems, Aβ pre-exposure consistently reprogrammed CSF1R signaling, driving sustained MAPK-ERK activation, suppression of Akt-mTOR, and site-specific transformation of CSF1R tyrosine phosphorylation. Notably, CSF1-induced ERK hyperactivation was identified as a primary driver of impaired microglial phagocytosis in the Aβ-primed state, establishing a direct mechanistic link between disease-driven CSF1R rewiring and microglial dysfunction. In vivo, CSF1R inhibition with BLZ945 in 5xFAD mice promoted microglial activation, normalized inflammatory proteomic signatures, and fully restored post-synaptic density after just 6 daily doses, effects entirely absent in wild-type animals. These findings demonstrate that CSF1R is not a static on-off switch for microglial activation, but a context-dependent signaling hub whose output is fundamentally shaped by the disease microenvironment. A deeper understanding of how AD pathology transforms CSF1R signaling and downstream microglial function will be essential for developing more targeted and effective therapeutic approaches for AD.

Dr. Jaydev Desai, Department of Biomedical Engineering, Georgia Institute of Technology

Dr. Omer Inan, School of Electrical and Computer Engineering, Georgia Institute of Technology

Dr. Yue Chen, Department of Biomedical Engineering, Georgia Institute of Technology

Design, Modeling, and Control of a Polymer-Based Continuum Robot

Minimally Invasive Surgery (MIS) is preferred over open surgery because it reduces patient trauma, shortens recovery time, and lowers the risk of complications. However, current MIS tools are typically passive and provide limited dexterity, making it difficult to access target locations within complex and tortuous anatomical structures. To address this limitation, this thesis presents the design of a meso-scale Hydraulic Polymer-based Continuum Robot (HyPo-CR) capable of achieving large, smooth bending motions. The proposed robot has an outer diameter of 2.14 mm and consists of a radially reinforced hydraulic actuator embedded within a laser-micromachined polyimide (PI) tube. Routing blocks are incorporated along the structure to maintain actuator alignment and improve force transmission. To better understand the mechanical behavior, three different design configurations are developed and experimentally evaluated, where the proposed design demonstrates improved planar bending and reduces undesired twisting by up to 58.8% compared to alternative designs. Furthermore, the robot is demonstrated in a two dimensional (2D) aortic arch phantom, where it successfully navigates through confined pathways and achieves bending angles greater than 180◦.To model the nonlinear behavior of the system, a Preisach hysteresis model is used to describe the relationship between the actuation force and the resulting tip deflection, achieving a validation error of 2.26◦. Since accurate knowledge of the robot configuration is critical for control, this work also investigates shape sensing methods. A camera-based approach is first implemented to provide high-resolution reference measurements of the robot shape. To enable more compact and practical sensing, an embedded Direct Laser Writing (DLW)-based resistive strain sensor is developed on the PI tube, along with an amplification circuit and a polynomial model to estimate the bending angle in real time. Building upon the modeling and sensing framework, both open-loop and closed-loop control strategies are implemented. These results demonstrate the potential of the proposed system for MIS applications and provide a foundation for future development of smaller-scale robotic guidewires and micro-catheters with integrated sensing and control capabilities.

M.G. Finn, Ph.D. (Chemistry and Biochemistry, Georgia Institute of Technology)

Nick Housley, Ph.D., DPT, PT (Biological Sciences, Georgia Institute of Technology)

Committee:

Julie Champion, Ph.D. (Chemical and Biomolecular Engineering, Georgia Institute of Technology)

Ankur Singh, Ph.D. (Mechanical Engineering, Georgia Institute of Technology)

Timothy Cope, Ph.D. (Biological Sciences, Georgia Institute of Technology) 

Exploring the Tumor Targeting Mechanism of Polymer “SANG” Nanoparticles, and Engineering SANGs for Drug Delivery to Treat Cancer

Despite substantial research into cancer therapies in the last few decades including targeted nanoparticle therapies and antibody drug conjugates, drug delivery specifically to cancer remains challenging, with less than ~1% of the injected drug dose in current cancer treatments ever getting to tumors. High chemotherapy drug doses necessary to overcome this limited delivery cause debilitating off-target toxicity in healthy tissues. A therapy that can be injected systemically and primarily target tumors without significant accumulation in healthy tissues is the main goal of cancer treatment. This work presents a novel polymer self-agglomerating nanohydrogel (SANG) that has shown significant accumulation in multiple types of solid tumors and metastases when injected systemically without any targeting ligands. SANG particles have also exhibited a unique agglomeration behavior in which above a certain concentration, the particles tend to stick to each other, forming larger aggregates. This work aims to better understand the tumor targeting capabilities and mechanism of SANGs, and exploit it by loading chemotherapeutic drugs on SANGs for application as an anti-cancer therapy. In Aim 1, the vascular mechanisms leading to SANG tumor accumulation are explored, comparing malformed, tortuous tumor vasculature to healthy vasculature. In Aim 2, chemotherapy drugs are loaded on SANGs and the anti-tumor effects of systemic administration of SANG-drugs are explored in vivo in breast and ovarian cancer models. Together, these efforts aim to advance the understanding of the tumor targeting mechanism of SANGs, and present the use of chemotherapy loaded SANGs as a novel cancer therapy for multiple types of solid tumors.

Committee:

Tara Deans, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)

Melissa Kemp, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)

Mark Prausnitz, Ph.D. (School of Chemical and Biomolecular Engineering, Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)

Todd Sulchek, Ph.D. (George W. Woodruff School of Mechanical Engineering Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University) 

Engineering Nanowires for FunctionalRejuvenation of Aged T Cell via Intracellular Engineering

Aging impairs T cell–mediated immunity, reducing protection against infection, vaccine efficacy, and immunotherapy responses. Aged CD8⁺ T cells harbor cell-intrinsic defects in signaling, transcription, metabolism, and organelle homeostasis that limit activation, proliferation, and persistence. Most existing interventions act extracellularly and fail to correct these intracellular dysfunctions, and in part due to the lack of cytocompatible platforms capable of manipulating intracellular programs in primary aged T cells without inducing stress, toxicity, or activation artifacts. Nanowire-based biointerfaces offer a unique opportunity to overcome this limitation by enabling direct cytosolic access to hard-to-transfect immune cells. This work aims to develop nanowire-enabled intracellular engineering as a strategy to rejuvenate aged CD8⁺ T cell function. Aim 1 will establish nanowire-mediated delivery of regulatory microRNAs to restore activation dynamics, metabolic fitness, proliferation, and effector function in resting aged CD8⁺ T cells, including validation in antigen-specific and in vivo infection models. Aim 2 will extend this intracellular programming framework to functional proteins and synthetic gene circuits to achieve durable, state-dependent control of aged T cell activation, differentiation, and persistence. Together, these advances will establish new translational strategies to enhance immunity in older and immunocompromised populations.

Levi Wood, Ph.D. (Woodruff School of Mechanical Engineering, Georgia Institute of Technology) 

Committee Members:

Hang Lu, Ph.D. (School of Chemical and Biomolecular Engineering, Georgia Institute of Technology)

Edward Botchwey, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)

Zhexing Wen, Ph.D. (Department of Psychiatry and Behavioral Sciences, Emory School of Medicine)

Srikant Rangaraju, M.D. (Department of Neurology, Yale School of Medicine) 

Harnessing MAPK/ERK Signaling with Receptor Tyrosine Kinases to Control Alzheimer's Disease Associated Microglia

In the Alzheimer’s disease brain, a subset of the brain resident immune cells, microglia, transition from a homeostatic population to an activated disease associated microglial (DAM) phenotype. These microglia possess hyperactivation of the ERK signaling protein and some protective functions. Preliminary analysis utilizing a computational model of cell signaling networks identified two receptor tyrosine kinases, CSF1R and TGFBR1/2, that are upstream of the MAPK/ERK pathway and have the capacity to modulate the DAM phenotype in vitro and in vivo and alter therapeutically relevant microglial function. Interestingly, despite the convergent signaling through the MAPK/ERK pathway by these receptors, there is a divergent functional response. CSF1R acts as a pro-DAM receptor, and TGFBR1/2 acts as a checkpoint on the transition into DAM. This work seeks to provide a clear mechanism of how these receptors signal through the MAPK/ERK pathway, including the specific temporal dynamics of activation, and determine the therapeutic relevance of targeting these receptors. Specifically, Aim 1 will validate the role of these receptors and their interaction with the MAPK/ERK pathway using proximity labeling of proteins. Aim 2 will deploy a real-time reporter system of ERK phosphorylation to establish the dynamics of ERK activation associated with the DAM phenotype. Aim 3 will target these receptors with inhibitors in a mouse model of Alzheimer’s disease and assess therapeutic potential. Together, this work will fill critical gaps in Alzheimer’s pathophysiology and identify novel therapeutic avenues to target microglia.

Committee:

Jun Ueda, Ph.D. (co-advisor)  (Georgia Institute of Technology)

Gregory Sawicki, Ph.D. (Georgia Institute of Technology)

Lewis Wheaton, Ph.D. (Georgia Institute of Technology)

Andrew Butler, Ph.D. ( University of Alabama at Birmingham)

      Development of Multi-modal Neuromodulation Techniques to Enhance Upper Limb Function Following Stroke and Healthy Aging

While upper limb rehabilitation after stroke is a prominent research area, clinical outcomes vary due to uniqueness of each stroke and limitations of current therapies. Adjacently, all humans encounter degradation of hand function during the natural aging process. Despite their differences, both stroke and aging rehabilitation techniques share common grounds, leveraging brain plasticity to relearn lost motor skills. This work aims to develop two new systems to modulate cortical activity to enhance acute motor output or memory consolidation during motor learning. In Aim 1, a unique sensorimotor environment will be developed to simulate unimpaired reaching and grasping movements controlled by the activation of their trunk muscles. Modulation of hand motor output will then be assessed. In Aim 2, a pipeline to assess acute effects of non-invasive neurostimulation will be developed and stimulation parameters will then be assessed with the validated pipeline. In Aim 3, a collection of novel closed-loop systems to optimally trigger neurostimulation specifically following successful movement across motor tasks will be developed and initially evaluated in older adults. A physical, enhanced sensorimotor environment and optimized neurostimulation to modify cortical pathways will enhance long term clinical outcomes following stroke and improve quality of life for aging adults.

Lakshmi Prasad Dasi, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)

Committee:

John Oshinski, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)

Rudolph Gleason, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)

Hanjoong Jo, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)

Vinod Thourani, M.D. (Piedmont Heart Institute, Piedmont Healthcare) 

 Predicting Transcatheter Aortic Valve Leaflet Thrombosis Risk Using Pre-Procedural Computational Modeling

    Aortic valve (AV) stenosis is the most common heart valve disease, present in about 30% of patients aged 65 or more and exacerbated by the congenitally abnormal bicuspid AV. Currently, the only treatment is an aortic valve replacement, which is commonly performed via transcatheter aortic valve (TAV) replacement (TAVR), a minimally invasive balloon-expandable (BE) or self-expandable (SE) procedure for patients at high surgical risk. However, the formation of blood clots on the TAV leaflets, or leaflet thrombosis (LT), is one of the most common adverse outcomes post-TAVR. About 15% of all patients who undergo TAVR develop LT, which increases the risk of stroke and early valve deterioration. Currently, LT is only diagnosed post-procedurally through detection of hypoattenuated leaflet thickening (HALT) in cardiac computed tomography (CT) scans taken days to months after procedure. Prior studies have examined direct correlations between various post-TAVR geometric and hemodynamic features on HALT risk, but no standardized methods have been developed to predict HALT pre-procedurally in the clinic. Hence, there is an urgent unmet need for rapid prediction of patient-specific post-TAVR HALT to aid in procedural planning. 

    So far, the project has resulted in a preliminary computational pipeline that predicts some post-TAVR geometric and hemodynamic features from pre-TAVR CT of tricuspid AV patients, but additional work is needed to further decrease the computational time and cost of these predictions, while incorporating additional TAVR models and bicuspid AVs. Therefore, the goal is to develop, validate, and test a robust computational pipeline that can predict patient-specific HALT risk after BE and SE TAVR in patients with tricuspid and bicuspid AVs, using only pre-procedural imaging. To do so, the following aims will be addressed: 1) Develop and validate a quick-response simulation-guided computational pipeline to pre-operatively predict post-TAVR geometric and hemodynamic features, 2) Predict HALT risk in patients following BE TAVR, and 3) Develop and test metrics to predict HALT risk following SE TAVR. By addressing one of the most common TAVR complications and methods to predict it while minimizing computational time and cost, this work will contribute to the development and validation of a rapidly deployable TAVR procedural planning tool that can be used in the clinic.

Committee:

Matthew Flavin, Ph.D.  (ECE, Georgia Institute of Technology)

Rudy Gleason, Ph.D. (ME, Georgia Institute of Technology)

Peter Hesketh, Ph.D. (ME, Georgia Institute of Technology)

Todd Sulchek, Ph.D. (ME, Georgia Institute of Technology) 

Development of Screen-Printed Flexible Sensing Systems for Biomedical Applications  

Significant progress has been made recently in the field of flexible electronics. Flexible electronics offer many advantages over traditional rigid systems in biomedical applications, such as light weight and conformality, which expands the device design space and allows for deployment of electronics in new use cases. Meanwhile, the ancient technique of screen printing presents a simple, yet precise method of creating thin conductive films over large areas. This proposal aims to take advantage of these unique properties by applying screen printing techniques to the creation of new flexible electronic devices. The proposed work targets two main areas: wearable health monitoring and cell therapy manufacturing. In Aim 1, a high-density piezoresistive sensor array, capable of continuous monitoring of plantar pressure distribution, is integrated into a wireless smart insole system using screen printing. For Aim 2, screen printing enables the development of another multi-sensor array to detect contamination in bioreactors during cell therapy amplification. Finally, Aim 3 seeks to build upon the bioreactor sensor system by expanding the sensor’s targeting capabilities and improving the wireless long-term monitoring functionality. In combination, this research plan aims to leverage the characteristics of screen printing to advance the field of flexible electronics and enable the deployment of new sensing systems for the benefit of a diverse range of patients.

Committee:
Julie Champion, Ph.D. (Georgia Institute of Technology)
Corey Wilson, Ph.D. (Georgia Institute of Technology)
Felipe Quiroz, Ph.D. (Georgia Institute of Technology)
William Ratcliff, Ph. D. (Georgia Institute of Technology)

 A Novel Platform for Simultaneous Control of Multiple Genes at High Throughput 

Complex cellular phenotypes and cars are similar in that one can observe their intended purpose (e.g., ability to survive for cells or mobility for cars) but struggle to understand the mechanisms that enable these features. While cars, because they are human-made, can undergo high throughput diagnostics to assess which parts combine to function to allow efficient mobility, methods with an analogous purpose do not exist for complex cellular phenotypes like their ability to survive. Particularly, numerous genes interact in parallel and non-parallel networks to give rise to these complex phenotypes, weakening the understanding gained by testing genes one at a time. In this vein, it is important to note that previous efforts with gene knockout and CRISPR activation/repression studies do not characterize the vast possibilities of achievable gene interactions per cell. Thus, the field of biology needs a high throughput investigative tool with enhanced characterization potential of these intricate gene networks that control complex phenotypes like survival in response to changing environments. To address this shortcoming, we have developed a novel method involving the high throughput creation of multi-single-guide RNA (sgRNA) cassettes. We have shown that it is feasible to assemble multiplex sgRNA cassettes by overlap extension polymerase chain reaction (OE-PCR), and that they can then allow for combinatorial gene expression control in the model organism, Saccharomyces cerevisiae. We will use our novel platform method to simultaneously activate and inhibit numerous genes to be able to enhance cell survival when exposed to extracellular stressors, such as hydrogen peroxide. Importantly, this technology will have applicability across eukaryotic organisms, providing “research mechanics” with a method that enables improved manipulation of cellular machinery—controlling the expression of multiple genes per cell in a high throughput manner, which is currently an impossible or at least very arduous task. 

Garrett Stanley, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)

Committee:

Bilal Haider, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)

Chris Rozell, Ph.D. (School of Electrical and Computer Engineering, Georgia Institute of Technology)

Audrey Sederberg, Ph.D. (School of Psychology, Georgia Institute of Technology)

Alan Emanuel, Ph.D. (Department of Cell Biology, Emory University)

Real-Time Cortical State Decoding for State-Aware Feedback Control

Perception depends not only on the stimulus, but also on the state of the brain when that stimulus arrives. The cortex fluctuates between distinct cortical states that affect how sensory signals are transformed and perceived. Although cortical states strongly influence neural responses, their rapidly shifting and variable nature has made it difficult to define the principles by which they shape sensory processing. This project aims to overcome that limitation by establishing a real-time framework for tracking and controlling cortical states, enabling state-aware experimentation to elucidate the mechanisms underlying state-dependent processing. We will develop the decoding and control algorithms underlying this framework within the constraints of real-time implementation, using the whisker primary somatosensory cortex (S1) of the awake mouse as a model system. In Aim 1, we will develop a model-based framework for real-time decoding of cortical state from local field potential (LFP) signals. In Aim 2, we will characterize how the activation of natural modulatory pathways shapes cortical state transitions. In Aim 3, we will integrate these components into a closed-loop controller that steers cortical activity toward targeted states and delivers sensory stimuli in a state-aware manner. Together, these advances will establish a novel framework for probing the precise roles of cortical state in sensory processing, with broader relevance for state tracking related to neurological disorders.

Committee:
Vida Jamali, Ph.D. (Georgia Institute of Technology)
Ravi Kane, Ph.D. (Georgia Institute of Technology)
Gabriel A. Kwong, Ph.D. (Georgia Institute of Technology)
Krishnendu Roy, Ph. D. (Vanderbilt University)
Younan Xia, Ph.D. (Georgia Institute of Technology)

Noninvasive monitoring of antitumor activity of T cells via plasmonic photoacoustic nanosensors

Adoptive T cell therapy (ACT) is a promising strategy for cancer treatment that harnesses a patient’s own T lymphocytes to enhance antitumor immunity. A major challenge in assessing therapeutic responses following ACT is the lack of robust, noninvasive tools to monitor antitumor T cell activity with anatomical context. This thesis presents an integrated strategy for noninvasive, longitudinal monitoring of ACT using plasmonic gold nanoconstructs in combination with ultrasound-guided photoacoustic (US/PA) imaging as follows: (1) We developed semi-connected gold nanoassemblies (GNAs) by tuning interparticle connectivity of gold nanospheres inside a polymer layer to enhance near-infrared (NIR) light absorption, photostability, and PA responses. This study demonstrates that interparticle coupling in gold nanoconstructs directly influences imaging contrast and signal reliability over repeated imaging sessions. (2) Building on this GNA design, we extended the platform toward functional monitoring of T cell immunotherapy. Membrane-bound GNAs on CAR T cells enable noninvasive, longitudinal PA imaging of T cells in heterogeneous solid tumors.  Longitudinal PA imaging revealed a correlation between early T cell trafficking and tumor responses. (3) Protease-activated plasmonic nanosensors were developed to detect granzyme B (GzmB), a key T cell effector protease. Upon exposure to GzmB, nanosensor aggregation is induced, leading to enhanced NIR light absorption. This significantly amplifies PA signals, enabling sensitive detection of GzmB with specificity. In murine ACT models, systemic nanosensor administration enables detection of tumor-infiltrating cytotoxic T cell activity, producing elevated PA signals in antigen-positive tumors compared to antigen-negative controls before measurable differences in tumor volume. Overall, this thesis demonstrates that the integration of plasmonic nanosensors with US/PA imaging not only advances the understanding of T cell-mediated antitumor responses but also provides a real-time monitoring platform to assess and potentially predict therapeutic outcomes in cancer immunotherapies.

Committee Members:

Dr. Amirali Aghazadeh  (School of Electrical and Computer Engineering, Georgia Institute of Technology)

Dr. Gordon Berman (Department of Biology, Emory University)

Dr. Nathan McDonald (School of Biological Sciences, Georgia Institute of Technology)

Dr. Anqi Wu  (School of Computational Science and Engineering, Georgia Institute of Technology)

How Does Aging Affect Odor Differentiation: Connecting Neural Dysregulation to Behavioral Changes in C. elegans

Cognitive decline, especially sensorimotor deficits, is a prominent part of healthy and pathological aging. Studies across species have found evidence that this loss of cognitive function is in part due to a dysregulation of neural circuits. However, how neuron level changes give rise to this population level effect is still not well understood. The overall objective of this proposal is to quantify the effects of aging on the brain's ability to process sensory information to make motor decisions. We will use the model organism, C. elegans and recent advances microscopy and microfluidics to capture the full path of sensorimotor information through their brains at single cell resolution. This model was selected due to the ease of maintaining isogenic populations and their short lifespans. We will analyze the neural activity in worms at distinct stages to better understand how information processing breaks down with age.  The tools developed in this thesis will be applicable not just to other biological questions in C. elegans but other small model organisms such as zebrafish and Drosophila.

Committee Members:

M.G. Finn, Ph.D. (School of Chemistry and Biochemistry, Georgia Institute of Technology)

John Blazeck, Ph.D. (School of Chemical and Biomolecular Engineering, Georgia Institute of Technology)

Julie Champion, Ph.D. (School of Chemical and Biomolecular Engineering, Georgia Institute of Technology)

Jihoon Kim, Ph.D. (School of Integrative Engineering, Chung-Ang University)

Engineered nanoparticle surface chemistry potentiates lymph node-directed transport and synergistic immunotherapeutic co-delivery

To design more efficient treatments for complex diseases, the properties of drug delivery vehicles are often modulated to better overcome biological barriers and enhance the delivery of bioactive molecules to their intended target, such as immunotherapy delivery to the lymphatic system to mediate the immune response in diseases such as cancer, infection, or autoimmune disorders. This thesis develops nanomaterial platforms to enable controlled nanoparticle delivery across lymphatic barriers in support of combination immunotherapeutic delivery to modulate the immune response. To further elucidate design considerations for effective drug delivery systems for lymphatic disease immunomodulation and diagnosis, the surface properties of model poly(propylene sulfide) nanoparticles are engineered to modulate their lymphatic transport and control the co-conjugation of synergistic immunostimulatory molecules. The effects of the copolymer properties on the nanoparticle properties were explored, along with the transport behaviors of the nanoparticle formulations using in vitro assays modeling drainage into the lymphatic system that predicted their in vivo lymphatic transport, facilitating the rational design of lymphatic-targeting drug delivery vehicles with desired transport properties. Furthermore, the nanoparticle surface was functionalized to display two orthogonal reactive groups capable of co-conjugating distinct biomolecules in controlled ratios and stimuli-responsive cleavage. These capabilities were leveraged for the formation of a subunit nanovaccine, co-conjugating immunostimulatory adjuvant with varying extents of antigen to modulate the potency of the antigen-specific immune response. Beyond enabling the design of optimized vaccination platforms, the design approaches explored herein facilitate the formulation of general combination therapeutic delivery systems with controlled lymphatic-directed transport to advance multifaceted approaches to improve patient outcomes in complex diseases.

Committee Members:

Karmella Haynes, PhD (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology)

John Blazeck, PhD (Department of Chemical Engineering, Georgia Institute of Technology)

Nicole Schmitt, PhD (School of Medicine, Winship Cancer Institute, Emory University)

Edward Botchwey, PhD (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology)

CHOLESTEROL IMPAIRS T-CELL RECEPTOR ANTIGEN RECOGNITION IN TUMOR MICROENVIRONMENT THROUGH CONVERGING T-REG AND ADENOSINERGIC IMMUNOSUPPRESSANT PATHWAYS

Tumor killing by cytotoxic T cells is initiated after the T cell receptor (TCR) recognizes tumor antigen through direct physical contact and bond formation. T cells decipher antigenic peptides by forming bonds between TCRs and peptide loaded major histocompatibility complexes (pMHCs). CD8+ T cells reactive against highly immunogenic antigens have a diminished anti-tumor protective effect when exposed to the TME. The mechanisms driving TME mediated immunosuppression are not fully understood. Advancing the understanding of immunosuppression in cancer will uncover useful information towards the advancement of therapeutic strategies. Our lab has previously shown that melanoma TME suppresses TCR 2D affinity, endogenous pulling forces, and activation in CD8+ cytotoxic T cells. Here, we examine the mechanisms driving suppressed TCR-pMHC interactions. Three immunosuppressants implicated in TME immune system evasion were screened as candidates of TCR inhibition. Directly targeting cholesterol metabolism, regulatory T cell (Treg) function, and adenosinergic pathways elucidated a compartment specific response to each inhibitor. These inhibitory pathways converge by altering cholesterol membrane accumulation.

Treatment with lovastatin, an FDA approved HMG-CoA reductase inhibitor (cholesterol synthesis inhibitor), reversed TME effects on impaired TCR binding affinity, endogenous pulling forces, and calcium fluxing. The current study also uncovers impaired TCR binding affinity and recovery with lovastatin using the MOC1 head and neck squamous cell carcinoma (HNSCC) animal model. Results show a progressive reduction in TCR 2D binding affinity of CD8+ T cells exposed to TME in HNSCC, and recovery when cholesterol synthesis is inhibited, similar to melanoma. Treatment with lovastatin was also confirmed to mitigate the TME effects on TCR antigen recognition by targeting membrane cholesterol accumulation. Reduction of membrane cholesterol via cholesterol sulfate (CS) also recovered TCR binding affinity by reducing membrane accumulation and average TCR site density/μm2. This suggests that the immunosuppression of CD8+ T cells in TME is attributed to impaired TCR antigen recognition, due, in part, to increased accumulation of membrane cholesterol.

In connection to findings from targeting cholesterol metabolic pathways, we explored Treg immunosuppression in TME mediated TCR inhibition and its possible connection to cholesterol mediated TCR inhibition. Treg depletion eliminated the compartment specific differences in binding affinity between cells exposed to TME and those that were not. This suggests Tregs as a role player in TCR inhibition. Results show regulatory T cell depletion reduces cholesterol accumulation in the membrane of CD8+ T cells exposed to TME, implicating Tregs in the mechanism of cholesterol-mediated TCR inhibition.

A well-known mechanism of Tregs cytotoxic CD8+ T cell inhibition works through the adenosinergic pathway through increased ectonucleotidase expression. We determine that ex-vivo stimulation with an adenosine-like receptor agonist increases the membrane cholesterol accumulation in CD8+ T cells exposed to TME. This data supports the notion that in cancer, Tregs drive membrane cholesterol accumulation in CD8+ T cells through the adenosinergic pathway. Finally, data shows targeting regulatory T cells lowers the concentration of adenosine in tumor infiltrating lymphocytes and enhances adenosine A2A receptor expression of non-TME exposed cells when regulatory T cells are selectively depleted, further connecting alterations in these pathways to membrane cholesterol accumulation and TCR inhibition in the TME. 

Committee Members:

Dr. Julie Champion (School of Chemical and Biomolecular Engineering, Georgia Institute of Technology)

Dr. Gabe Kwong (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University)

Dr. Raquel Lieberman (School of Chemistry and Biochemistry, Georgia Institute of Technology)

Dr. Amit Reddi (School of Chemistry and Biochemistry, Georgia Institute of Technology)

Creating and enhancing protease-responsive masked chimeric antigen receptors using engineering platforms in yeast

Immunotherapies such as chimeric antigen receptor (CAR)-T cell therapy have emerged as promising cancer treatments that can target tumors by binding to specific antigen targets. While these antigens are highly overexpressed in solid tumors, they are also expressed at low levels in healthy tissue, leading to the ‘on-target, off-tumor’ effect, in which CAR-T cells kill both healthy and cancerous cells. One strategy to combat this issue is through the conditional activation of therapeutics by the fusion of peptide masks to a protein drug. Masks block the binding of a protein to its intended target, and can be removed by proteases, which are overexpressed by cancers. 

We have developed a yeast display-based platform for the discovery of protease-removable peptide masks and have successfully isolated masks for a variety of cancer-relevant targets. However, some of these peptides have weak masking ability, only partially blocking target binding, while others do not fully unmask or allow for adequate restoration of binding upon protease treatment. Thus, we will first create a diversifying, dual adenine/cytosine base editor in yeast that can be used as a tool for in vivo mutagenesis for the improvement of mask affinity and ability to block antigen binding. Next, we will study the activity and specificity of proteases to allow for cancer-relevant proteolytic removal of masks. Finally, we will improve the efficiency of mask removal with the incorporation of protease exosite-binders into our masked CAR design. Overall, this project aims to create strong masks for cancer-targeting CARs which can be efficiently removed by tumor-associated proteases.

Committee Members:

Stavros Thomopoulos, PhD (Department of Orthopedic Surgery & Biomedical Engineering, Columbia University)

Yuhang Hu, PhD (Woodruff School of Mechanical Engineering, Georgia Institute of Technology)

Johnna Temenoff, PhD (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology)

Vladimir Tsukruk, PhD (School of Materials Science and Engineering, Georgia Institute of Technology)

Design and Fabrication of Novel Scaffolding Materials to Enhance Orthopedic Tissue Repair

Musculoskeletal injuries result in nearly 30 billion dollars of cost annually in the United States. Those affecting tendons and ligaments, including transections of intrasynovial flexor tendons of the hand and rotator cuff tears of the shoulder, are prevalent and typically result in significant pain and disability. Although advances have been made in surgical techniques and rehabilitation methods, the outcomes of tendon and tendon-to-bone insertion repair remain poor. For instance, current approaches often fail to restore hand function after flexor tendon injury due to poor healing that leads to gapping, repair-site failure, and motion-limiting adhesions, frequently requiring additional surgeries. For the more intricate tendon-to-bone repair, failure rates range from 20-94%, depending on the extent of the injury and the patient’s age. Tissue engineering strategies, including rationally-designed scaffolds, delivery of bioactive molecules, cell-based therapy, or a combination of these, offer promising routes to enhance musculoskeletal repair. In this dissertation, I focused on the first two aspects, tuning scaffold composition, stiffness, and topography, and delivering specific biochemical cues to the injury site to facilitate repair. With an initial focus on the tendon itself, I first designed a delivery system to address the specific challenges of intrasynovial flexor tendon injuries. The clinical success of the repair depends on reconciling the contrasting goals of suppressing matrix formation at the tendon surface while promoting it within the repair site. To address this clinical need, a targeted drug delivery film was developed with controlled bi-directional and bi-temporal release to concurrently modulate inflammation and promote matrix remodeling. Next, my focus shifted to the tendon-to-bone insertion site, where repair often fails due to the challenge of recreating the native transitional tissue of the tendon enthesis. Effective tendon-to-bone attachment critically depends on the spatially-graded composition and hierarchical structure of the extracellular matrix and a unique population of cells with a phenotypic gradient. Therefore, a promising strategy to address this clinical challenge involves the use of biomimetic scaffolds to promote the regeneration of a functionally-graded enthesis. To this end, scaffolds were engineered with a well-controlled mineral gradient and optimized interdigitation geometry using spin-coating followed by laser machining. Building on this design, an additional developmentally-inspired cue, hedgehog agonist, was incorporated into the scaffold to further guide the formation of a cell phenotype gradient across the scaffold, thereby more comprehensively mimicking the cellular phenotypes in native enthesis.

Ankur Singh, PhD (George W. Woodruff School of Mechanical Engineering at Georgia Tech, Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech and Emory University)

Committee Members:

Andrés J. García, PhD (George W. Woodruff School of Mechanical Engineering, Georgia Tech)

Susan N. Thomas, PhD (George W. Woodruff School of Mechanical Engineering, Georgia Tech)

Ahmet Coskun, PhD (Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech)

Jean L. Koff, MD, MS (Department of Hematology and Medical Oncology, Emory University)

Human immune organoids to decode B cell response in healthy donors and patients with lymphoma

Understanding human B cell differentiation is vital for developing effective vaccines and therapies, especially in immunocompromised patients such as those with B cell lymphoma. Current models based on secondary lymphoid tissues like tonsils have provided valuable insights but remain limited by tissue availability, intrinsic inflamed microenvironments, and the inability to mimic the complex human lymphoid microenvironment. 

To address this, this thesis presents the development of synthetic hydrogels that mimic the lymphoid tissue microenvironment, enabling human B cell maturation processes from tonsils and peripheral blood mononuclear cell (PBMC) -derived B cells. These organoids emulate lymphoid tissue biophysical properties, chemokine gradients, and cell–cell interactions, enabling the study of germinal center formation and antibody-producing plasma cell differentiation under physiologically relevant conditions. Next, we applied this platform to characterize B cell fate decisions across healthy donors and lymphoma patients through transcriptomic profiling and multiparametric metrics. We further integrated immune organoids with microfluidic devices to spatially regulate spatial organization via chemokine gradients, enabling mechanistic studies of B cell selection dynamics in health and diseases. Altogether, this system allows rapid, controlled modelling of immune responses and B cell disorders, developing next-generation immunotherapies.

Committee Members: 

Dr. Anant Paravastu (Georgia Institute of Technology)

Dr. Shuichi Takayama (Georgia Institute of Technology and Emory University)

Dr. Alberto Moreno (Emory University)

Dr. Levi Wood (Georgia Institute of Technology)

  Engineering protein-based vaccines and therapeutics 

Influenza is a global health concern, causing up to 650,000 deaths worldwide annually despite the availability of seasonal vaccines. Current vaccination strategies and natural infection mainly elicit antibodies against the immunodominant and variable head domain of the hemagglutinin (HA) viral membrane glycoprotein. The antibodies that target this domain are highly neutralizing, but the head domain constantly mutates due to selective pressure and causes the head-directed immune response to be strain-specific. The more conserved stalk domain, however, has shown to be a promising target for the development of a broadly protective influenza vaccine. We introduce two strategies – tethered antigenic suppression and antigenic reorientation – to refocus the immune response towards the conserved stalk domain of HA. 

            We demonstrate that tethering an antibody fragment to the HA head suppresses antibody responses against all five major antigenic sites on the head while enhancing the induction of anti-stalk antibodies in immunized mice. In addition, in a previous study, we had shown that presenting the HA in an inverted orientation on virus-like particles (VLPs) significantly enhances the induction of stalk-directed, cross-reactive antibodies compared to those elicited by presenting HA in a regular orientation on VLPs. With this promising result, we evaluated the protective efficacy of the inverted H1 HA VLP vaccine (VLP-HAinv) in BALB/cJ mice against homologous, heterologous, and heterosubtypic influenza A virus challenges. The VLP-HAinv vaccination in BALB/cJ mice with various dose regimes provided complete protection against homologous and 2009 pandemic H1N1 heterologous challenges. Moreover, we observed partial protection against a heterosubtypic bovine clade 2.3.4.4b H5N1 virus A/bovine/New Mexico/A240920343-93/2024, a pandemic potential avian influenza strain. We further aim to discover the mechanism of protection elicited by VLP-HAinv by characterizing the Fc-mediated effector functions, T and B cell populations, and the influence of pre-existing immunity.

            In addition to designing protein-based vaccines that elicit protective antibodies, we are also interested in identifying target-specific antibodies with possible therapeutic potential.  Our focus is on amyloid-β (Aβ) oligomers, increasingly recognized as the most neurotoxic species driving Alzheimer’s disease (AD) pathology. However, their structural and conformational heterogeneity has hindered the development of targeted therapeutics. In this study, we aim to isolate nanobodies with structural selectivity toward a well-defined and homogeneous 150 kDa Aβ oligomer. Preliminarily, we used the Kruse Lab’s yeast surface display nanobody library to perform successive rounds of magnetic-activated cell sorting and fluorescence-activated cell sorting to enrich clones that bind to the 150 kDa Aβ oligomer. We identified nine unique nanobodies, from which four were fused to a human IgG Fc domain to generate bivalent nanobody-Fc constructs. Among these, one nanobody-Fc construct expressed stably in mammalian cells and demonstrated binding to the 150 kDa Aβ oligomer in dot blot assays. However, cross-reactivity with Aβ monomers and fibrils was observed. Future work will incorporate negative selection screens using Aβ monomers to improve the specificity of the nanobody-Fc toward the Aβ oligomers. We will then perform cytokine release and cell viability assays to determine whether the oligomer specific nanobody-Fc can mitigate Aβ oligomer-induced neurotoxicity. 

Committee Members: 

Dr. Stanislav Emelianov (Georgia Institute of Technology and Emory University)

Dr. Erin M. Buckley (Georgia Institute of Technology and Emory University)

Dr. James Lah (Emory University)

Dr. Shella Keilholz (Georgia Institute of Technology and Emory University)

  Advancing Magnetic Resonance Imaging Methods for Assessing Cerebrovascular Contributions to Alzheimer's Disease

Alzheimer’s Disease (AD) is the leading cause of dementia, affecting millions of people each year with limited treatment options. AD has long been thought to be caused by the accumulation of neurotoxic amyloid and tau compounds. Cerebrovascular dysfunction is now understood to also play a role in AD progression; although, the exact pathological mechanisms are unclear. Amyloid and tau, while informative, are assessed using invasive procedures and may not be sensitive to earliest disease pathology. In contrast, cerebrovascular dysfunction has been observed in people at risk of AD before amyloid/tau accumulation or cognitive decline. Reliable, noninvasive methods to assess cerebrovascular dysfunction are therefore necessary to better understand its role in AD and to develop diagnostic and therapeutic tools. Magnetic resonance imaging (MRI) offers a promising approach to assess cerebrovascular health comprehensively and noninvasively through its ability to quantify multiple cerebrovascular biomarkers with high spatial resolution. Moreover, MRI-derived cerebrovascular biomarkers together with recent advancements in deep learning could aid our understanding of AD progression and/or lead to the establishment of novel biomarkers. In this work, we develop MRI techniques that assess multiple cerebrovascular parameters and apply these techniques with deep learning methods to investigate cerebrovascular dysfunction patterns occurring in early AD.

Committee Members:  

John Blazeck, Ph.D. (School of Chemical and Biomolecular Engineering, Georgia Tech)

Vida Jamali, Ph.D. (School of Chemical and Biomolecular Engineering, Georgia Tech)

Manu Platt, Ph.D. (NIH|NBIB, Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech)

Mark Prausnitz, Ph.D. (School of Chemical and Biomolecular Engineering, Georgia Tech) 

Engineering protein nanocages for Influenza and Chlamydia Vaccines

Recombinant protein subunit vaccines overcome challenges faced by traditional whole pathogen vaccines, including preservation of antigen structure and directing both a humoral and a cellular immune response towards specific epitopes. However, the immune system has evolved to recognize highly repetitive antigens presented on pathogen surfaces, not soluble antigens. To induce robust immune responses, antigen display platforms have been designed to mimic pathogen antigen display. There are many different types of protein antigen displays, such as crosslinked nanoparticles and de novo self-assembling proteins. This thesis explores the use of self-assembled protein nanocages (SAPN) to improve humoral immune responses for a universal influenza vaccine and to develop and evaluate a Chlamydia vaccine. SAPNs are comprised of coil peptides that self-assemble into a cage. For vaccine SAPNs, fusion proteins were made of coiled coils and antigens. For influenza and Chlamydia SAPNs, combinations of antigens from the pathogens were showcased on the outside or the inside of the cage. The SAPNs were used to investigate antigen display and the factors that can affect immune responses, including accessibility and selection. This includes how a glycine linker can improve accessibility of a small antigen on the cage to induce a significant humoral response, and how selection of antigens may have a greater impact on immune responses than display. Overall, this thesis demonstrates the modular nature of  SAPNs with the ability to display both viral and bacterial antigens. 

Committee Members:

Greg Sawicki, Ph.D. (George W. Woodruff School of Mechanical Engineering, School of Biological Sciences, Georgia Tech)

Josiah Hester, Ph.D. (School of Computer Science, Georgia Tech)

David Ewart, M.D. (Department of Rheumatology, Minneapolis Veteran’s Affairs Medical Center)

Minoru Shinohara Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, School of Biological Sciences, Georgia Tech) 

Advancing Wearable Sensing for Musculoskeletal Health Monitoring in Dynamic Everyday Environments 

Current musculoskeletal healthcare is largely reactive, not proactive. Often, injuries and disease are detected only after they have progressed to late stages when irreparable damage has already occurred. This delay largely results from current methods of evaluating musculoskeletal health being costly, immobile, and inaccessible, limiting their feasibility for regular monitoring in everyday environments where early-stage detection and intervention is possible. Emerging sensing technologies such as joint acoustic emissions (JAEs) and localized electrical bioimpedance (EBI) offer an objective, wearable alternative to traditional approaches, but limited research into their sensitivity to early-stage musculoskeletal injury and disease during movements and conditions where they would be realistically used has constrained their viability beyond laboratory environments, where their potential advantages can be fully realized. To enable broader clinical and real-world impact, advancements are required in both the sensitivity and accessibility of these sensing technologies to capture meaningful information on musculoskeletal function under the unpredictable conditions of daily living. This dissertation entails demonstrating their sensitivity to early signs of musculoskeletal pathology, deepening understanding of the physiological signals they capture during functional movement, and developing wearable hardware and algorithms capable of reliable operation outside controlled environments. By addressing these challenges, this work takes a crucial step towards more accessible, affordable, and actionable musculoskeletal health monitoring beyond traditional clinical and research settings. 

Advisor: Corey J. Wilson, Ph.D. (School of Chemical and Biomolecular Engineering, Georgia Tech)

Committee Members:

John J. Blazeck, Ph.D. (School of Chemical and Biomolecular Engineering, Georgia Institute of Technology)

Matthew J. Realff, Ph.D. (School of Chemical and Biomolecular Engineering, Georgia Institute of Technology)

Karmella Haynes, Ph.D. (Department of Biomedical Engineering, Emory University)

Thomas J. DiChristina, Ph.D. (School of Biological Sciences, Georgia Institute of Technology) 

Expanding Transcriptional Programming Wetware and Biocomputing Capacity

Synthetic biology aims to engineer cells with programmable behaviors by designing gene circuits that process information and respond to environmental cues. This thesis advances the Transcriptional Programming (T-Pro) platform through the development of novel anti-repressor biosensors and related software to enable scalable biocomputing capacity. In Aim 1, novel anti-repressor variants from the LacI/GalR family will be engineered to expand the regulatory toolkit available for constructing modular and orthogonal gene circuits. Aim 2 will focus on the development of a computational framework for designing compressed higher-order genetic circuits that leverage anti-repressor biosensors developed in Aim 1. The envisioned software will translate user-defined multi-input truth tables into compressed circuit architectures for >3-input Boolean operations. Aim 3 will apply the resulting wetware toward the development of novel biological security systems. Collectively, this work will increase T-Pro’s biocomputing capacity and enhance wetware applications in the context of biocontainment.

Douglas K. Graham, MD Ph.D. (Aflac Cancer & Blood Disorders Center, Emory University School of Medicine)

Committee Members:

Mark Styczynski, Ph.D. (School of Chemical and Biomolecular Engineering, Georgia Tech)

Melissa Kemp, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech)

Sunil Raikar, MD Ph.D. (Aflac Cancer & Blood Disorders Center, Emory University School of Medicine)

Developing High Throughput and Long-Term Human Bone Marrow Organoids for Modeling Acute Myeloid Leukemia 

Acute myeloid leukemia (AML) is an aggressive blood cancer caused by the uncontrolled growth of hematopoietic stem and progenitor cells (HSPCs) that are arrested at early stages of development. Despite therapeutic advances, relapse persists, driven in part by the bone marrow (BM) microenvironment, which provides hematopoietic niches essential for AML survival and expansion. Leukemic cells hijack these niches to establish a disease-permissive tumor microenvironment (TME). To address these challenges and improve therapeutic outcomes, there is a growing need for representative in vitro models that can faithfully recapitulate the human BM microenvironment. Organoids which are scaffold-free 3D structures formed from self-organizing cells, represent a promising platform due to their ability to replicate native tissue architecture and functionality.

This thesis presents the development of a physiologically relevant 3D BM organoid system to study AML, its interaction with TME, and use as a drug screening platform. We established vascularized mesenchymal organoids (VMOs) as a foundational platform by co-culturing human umbilical vein endothelial cells (HUVECs) with mesenchymal stromal/stem cells (MSCs) in a minimal Matrigel-based scaffold (Aim1). Then, we expanded this platform into a full tri-culture AML BM organoid model by directly co-seeding AML cells derived from cell lines, primary patient samples, and patient-derived xenografts (PDXs), with ECs and MSCs and characterized the TME (Aim2). Finally, we applied organoid model to evaluate therapeutic responses against chemotherapy and small molecule drug response (Aim3). 

Together, this system offers a scalable and biologically relevant platform that captures the structural and functional complexity of the TME for studying AML-microenvironment interactions and for evaluating therapeutic response within a humanized, multicellular bone marrow context.

Stanislav Emelianov, Ph. D. (School of Electrical and Computer Engineering, Georgia Institute of Technology)

Committee Members:

Omer Inan, Ph.D. (School of Electrical and Computer Engineering, Georgia Institute of Technology)

Rafael Davalos, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology)

Optimal Galvanic Cell Design for Powering Ingestible Devices in Varying Gastrointestinal Conditions

Energy harvesting using galvanic cells in the gastrointestinal (GI) tract can provide supplementary power and prolong the service life of ingestible devices. This work explores the impact of electrode type, dimension, load resistance, and varying GI conditions on the performance of galvanic cells for powering ingestible devices. In vitro experiments were conducted with varying cathode and anode combinations in synthetic gastric fluid (SGF) under a load resistance sweep to measure the voltage of the galvanic cell over time. 23 tests assessed the peak power, energy capacity, and longevity of each electrode pair. Galvanic cell performance was also evaluated under simulated GI conditions (including varying pH, salt concentration, added foreign substances, and simulated intestinal conditions), varying electrode dimensions, and varying set load resistances. Pt and Pd cathodes showed the highest peak power and energy capacity, while Mo was cost-effective for transient applications. Mg was the optimal anode for short-term use, while Zn, the AZ31B Mg alloy, or a Zn-Mg hybrid were preferred for long-term applications. Energy generation decreased with increasing pH but improved with higher salt concentration. Large substances in gastric fluid hindered performance, and energy generation in intestinal fluids was less efficient. Larger cathode-to-anode size ratios increased efficiency, while larger anodes provided greater longevity. Power efficiency was observed to be highest for the Pt-Zn and Pt-AZ31 combinations when the internal resistance was equal to the load resistance but was higher for Pt-Mg as the load resistance increased. This study successfully characterized the effects of electrode combinations, dimensions, GI conditions, and load resistance on the performance of galvanic cells, offering insight into the design of supplementary power sources for short-term and long-term applications in ingestible devices.

This work aims to advance the synthetic design of allosterically regulated systems by extracting sequence-function correlations from engineered LacI-based anti-repressors. Through deep mutational scanning, we have generated comprehensive datasets correlating single-mutant genotypes with functional phenotypes. Building upon the experimental dataset and alongside model development efforts that utilize it, I introduce a novel approach to complement these analyses. By projecting deep mutational scanning data onto a representative protein structure model, I enable visual inspection and procedural analysis of position-based relationships. This projection, combined with quantitative data analysis across multiple datasets, generates a comprehensive, site-specific value list that can be algorithmically manipulated. This integrated approach, blending structural visualization with quantitative analysis, provides a deeper understanding towards position linked factors integral in LacI allostery. Ultimately, this research seeks to establish a foundation for improved engineering strategies for synthetic transcription factors and to enhance the development of features relevant for phenotype prediction efforts by further elucidating the mechanistic underpinnings of anti-repressor function and contributing to the broader understanding of protein allostery.

Andrew J. Feola, PhD (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University; Department of Ophthalmology, Emory University; Atlanta VA Medical Center for Visual & Neurocognitive Rehabilitation)

C. Ross Ethier, PhD (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University)

Todd Sulchek, PhD (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University; George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology)

Levi Wood, PhD (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University; George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology)

W. Daniel Stamer, PhD (Department of Ophthalmology, Duke University)

Menopause-induced changes to the biomechanics and gene expression profile of the outflow pathway

Glaucoma, the leading cause of irreversible blindness worldwide, is characterized by peripheral vision loss due to retinal ganglion cell (RGC) loss. It’s projected to affect 112 million people by 2040, and 59% of the glaucomatous population are women. Past work suggests menopause, a hormonal process unique to females, that results in the decline of circulating estrogen and progesterone, might be a sex-specific factor associated with glaucoma.

Recent work found that the age onset of menopause had a linear association with the timing of glaucoma diagnosis. Other works have found that early-onset menopause increases the risk of developing glaucoma later in life and that menopause impacts intraocular pressure (IOP) – the only modifiable risk factor for glaucoma. Further, estrogen has been identified as an upstream regulator for genes associated with IOP, called IOP-associated genes. However, menopause’s role, particularly early-onset menopause, in glaucoma development is still not well understood. This work will address this gap by characterizing the potential impact early-onset menopause has over time on IOP, eye biomechanics, and gene expression associated with IOP and glaucoma.

Working with Brown Norway rats, Aim 1 will focus on determining the impact of early-onset menopause over time on IOP and aqueous humor (AH) outflow resistance. Aim 2 will investigate early-onset menopause’s impact on the stiffness of the trabecular meshwork’s (TM) distinct segmental flow regions (high flow (HF) and low flow (LF)), the major tissue helping regulate aqueous humor flow within the eye. Aim 3 will assess gene expression changes within the TM induced by early-onset menopause. We hypothesize that over time, early-onset menopause increases IOP via increased AH outflow resistance and TM stiffness that are mediated by IOP-associated gene expression. This will provide insight into how early-onset menopause is related to factors associated with glaucoma over time and potentially identify menopause-associated pathways for new treatment targets for all glaucomatous patients.

Committee Members: 

Dr. Raquel Lieberman, Georgia Institute of Technology, School of Chemistry & Biochemistry

Dr. Matthew Realff , Georgia Institute of Technology, School of Chemical and Biomolecular Engineering

Synthetic Transcription Factor Allostery Mapping and Analysis

This work aims to advance the synthetic design of allosterically regulated systems by extracting sequence-function correlations from engineered LacI-based anti-repressors. Through deep mutational scanning, we have generated comprehensive datasets correlating single-mutant genotypes with functional phenotypes. Building upon the experimental dataset and alongside model development efforts that utilize it, I introduce a novel approach to complement these analyses. By projecting deep mutational scanning data onto a representative protein structure model, I enable visual inspection and procedural analysis of position-based relationships. This projection, combined with quantitative data analysis across multiple datasets, generates a comprehensive, site-specific value list that can be algorithmically manipulated. This integrated approach, blending structural visualization with quantitative analysis, provides a deeper understanding towards position linked factors integral in LacI allostery. Ultimately, this research seeks to establish a foundation for improved engineering strategies for synthetic transcription factors and to enhance the development of features relevant for phenotype prediction efforts by further elucidating the mechanistic underpinnings of anti-repressor function and contributing to the broader understanding of protein allostery.

Committee:

Costas D. Arvanitis, Ph.D. (George. W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology)

Francisco E. Robles, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)

Erin M. Buckley, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)

William C. Ratcliff, Ph.D. (School of Biological Sciences, Georgia Institute of Technology)

Towards super-resolution neuromorphic scanning microscopy

Super-resolution microscopy has revolutionized the visualization of subcellular structures, yet it still relies on collecting numerous diffraction-limited frames for reconstruction. This requirement reduces temporal resolution, produces large redundant data sets, and demands complex optical configurations that impede real-time, high-throughput imaging. Frame-based cameras further limit their performance because their exposure time and dynamic range are compromised under rapid acquisitions. The goal of this proposal is to develop an affordable, accessible, and compact super-resolution microscope that concurrently delivers high-throughput imaging. In Aim 1, we will integrate neuromorphic event camera and develop dedicated reconstruction algorithms to reach kilohertz temporal resolution. Aim 2 focuses on designing and fabricating optical metasurfaces to replace diffractive microlens arrays for enhanced performance and to further simplify the hardware setup. Aim 3 will validate the complete neuromorphic scanning microscope on a range of biological specimens, demonstrating its versatility for broad applications. Successful completion of these aims will deliver the next generation of super-resolution microscopy, providing a robust and user-friendly platform for rapid biological imaging in both biological research and clinical applications.

Open to all Bioengineering Students and Faculty!

AGENDA 

• 9:30 a.m.        Coffee Corner
• 10:00 a.m.      Outstanding Advisor Presentation - Levi Wood, introduction by Sara Bitarafan
• 10:30 a.m.      Outstanding Thesis Presentation - Jihoon Lee, introduction by Shuichi Takayama
• 11:00 a.m.      Alumni Presentation - Philip Trusty, Manager, Clinical Research, Abbott
• 11:30 a.m.      Alumni Presentation - Ivana Parker, Assistant Professor, University of Florida
• 12:00 p.m.      Outstanding Paper Presentation - Zhe "Monica" Zhong (A. Singh lab),  Lunch provided
• 12:30 p.m.      Rapid Fire Presentations
• 2:00 p.m.        Alumni Panel
• 3:00 p.m.        Awards Announcements - Rapid Fire Awards, Christopher Ruffin Award
• 3:10 p.m.        Ice Cream and Popsicles - EBB patio
• 4:30 p.m.        Adjourn
  
  
   

BioE Ph.D. Proposal Presentation

May 9, 2025

10:30 AM -12:30 PM

Location: IBB Suddath Seminar Room 1128

https://gatech.zoom.us/j/95124754456

Meeting ID: 951 2475 4456 

Advisor: Susan N. Thomas, Ph.D. (Woodruff School of Mechanical Engineering, Georgia Institute of Technology) 

Committee:

Julie Champion, Ph.D. (School of Chemical and Biomolecular Engineering, Georgia Institute of Technology)

J. Brandon Dixon, Ph.D. (Woodruff School of Mechanical Engineering, Georgia Institute of Technology)

M.G. Finn, Ph.D. (School of Chemistry & Biochemistry, Georgia Institute of Technology)

Shuichi Takayama, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology)

Engineering microphysiological lymphatic tissue models to advance drug delivery and lymphatic medicine

The lymphatic system plays a critical role in immune regulation, fluid balance, and the transport of therapeutics. However, the effectiveness of lymphatic-targeted drug delivery is often limited by off-target effects and poor retention. Nanoparticles, synthetic or natural carriers typically ranging from tens to several hundreds of nanometers in size, hold promise for improving specificity and therapeutic outcomes, yet their interactions with the lymphatic system are not well understood. To address this, there is an unmet need for precisely engineered physiological models that replicate the lymphatic microenvironment. Accordingly, the overall objective of this research is to engineer microphysiological models of lymphatic tissue to study nanoparticle transport and drug release dynamics. The central hypothesis is that biomimetic lymphatic architectures will enable detailed analysis of nanoparticle behavior and mechanisms relevant to drug and vaccine delivery. Specifically, I will (Aim 1) develop a lymphatic microphysiological platform that recapitulates key structural and functional features of lymph node sinus floor and the paracortex, enabling controlled study of various nanoparticles transport behaviors and cellular engagement under homeostatic and inflammatory conditions; and (Aim 2) engineer a microfluidic platform mimicking the interstitial space between a therapeutic depot and initial lymphatics to investigate the release dynamics of different therapeutic formulations and their effects on lymphatic vessels’ function from various species. Overall, this work will improve our predictive understanding of lymphatic-targeted therapies and support the rational design of nanomedicines for applications in vaccine delivery, cancer immunotherapy, and lymphatic disorders such as lymphedema.

Advisor: 

Ankur Singh, PhD (George W. Woodruff School of Mechanical Engineering at Georgia Tech, Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech and Emory University)

Committee Members:

Andrés J. García, PhD (George W. Woodruff School of Mechanical Engineering, Georgia Tech)

Susan N. Thomas, PhD (George W. Woodruff School of Mechanical Engineering, Georgia Tech)

Ahmet Coskun, PhD (Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech)

Jean L. Koff, MD, MS (Department of Hematology and Medical Oncology, Emory University)

Human immune organoids to decode B cell response in healthy donors and patients with lymphoma

Understanding human B cell differentiation is vital for developing effective vaccines and therapies, especially in immunocompromised patients such as those with B cell lymphoma. Current models based on secondary lymphoid tissues like tonsils have provided valuable insights but remain limited by tissue availability, intrinsic inflamed microenvironments, and the inability to mimic the complex human lymphoid microenvironment. To address this, I propose the development of synthetic hydrogels that mimic the lymphoid tissue microenvironment, enabling human B cell maturation processes from tonsils and peripheral blood mononuclear cell-derived B cells. These organoids emulate lymphoid tissue biophysical properties, chemokine gradients, and cell–cell interactions, enabling the study of germinal center formation and antibody-producing plasma cell differentiation under physiologically relevant conditions. I will apply this platform to characterize B cell fate decisions across healthy donors and lymphoma patients through transcriptomic and epigenetic profiling using multiparametric approaches. I will integrate immune organoids with microfluidic devices to spatially regulate spatial organization via chemokine gradients, enabling mechanistic studies of B cell selection dynamics in health and diseases. Altogether, my research allows rapid, controlled modelling of immune responses and B cell disorders, developing next-generation immunotherapies.

Committee:

Alexander Alexeev, Ph.D. (ME, Georgia Institute of Technology)

Scott Danielsen (MSE, Georgia Institute of Technology)

David Myers, Ph.D. (BME, Georgia Institute of Technology)

Guillem Pratx, Ph.D. (Radiology and Medical Physics, Stanford University)  

Optimization of Forces, Loading Rates and Strain Rates for Cytosolic Delivery using Mechanoporation  

Intracellular delivery of biomolecules such as mRNA, radiotracers, and gene-editing tools is a critical to advance gene therapy, diagnostics, and regenerative medicine. Microfluidic mechanoporation uses physical deformation of cells to transiently open membrane pores offering a scalable and reagent-free alternative to traditional delivery methods. Its broader adoption is limited by unpredictable delivery outcomes and incomplete understanding of how mechanical forces impact cells. This research aims to establish a force-informed framework for designing microfluidic systems that can consistently and efficiently deliver biomolecules directly into cytosol, bypassing endocytic degradation. By studying how cells respond to dynamic adhesion, loading rate, and strain state across microsecond to millisecond time scales, this work seeks to make delivery outcomes more predictable and tunable. In Aim 1, we will investigate how adhesion and mechanical properties influence cell behavior under flow using atomic force microscopy (AFM) and microfluidic ridge geometries. Aim 2 focuses on developing and validating analytical models that isolate and quantify the mechanical forces driving membrane poration using custom channel designs that modulate shear loading rate. In Aim 3, we will evaluate the biological fate of delivered molecules by comparing cytosolic versus endosomal colocalization using fluorescent and radiolabeled cargo. Together, this work will provide key design principles for the next generation of intracellular delivery platforms, enabling more precise and effective delivery for time-sensitive and therapeutically potent molecules.

Committee:

Peng Qiu, Ph.D. (BME, Georgia Institute of Technology)

Saurabh Sinha (BME, Georgia Institute of Technology)

Rabindra Tirouvanziam, Ph.D. (BME, Emory University)

Marcus Cicerone, Ph.D. (Chem, Georgia Institute of Technology)  

Timeseries Spatial Omics Of Immune Cell Signaling In Inflammation  

Cystic fibrosis (CF) affects 100,000 people worldwide. Although FDA-approved therapies have remarkably succeeded, chronic inflammation and bacterial infections persist, causing tissue damage and worsening quality of life, despite a large immune cell presence. We investigate the spatiotemporal dynamics of these immune cells, specifically the Nuclear Factor kappa B (NFκB) pathway, during inflammation. We combine emerging spatial omics techniques with a time-series fixation method involving static stimulation and programmable formaldehyde perfusion to map pseudo-Signaling with Omics signatures (pSigOmics) of single-cell data from 100K+ cells. Examining NFκB in mouse fibroblasts, we discovered a novel asynchronous pseudotime regulation (APR) between p65 RNA and protein in the quintessential NFκB p65 protein using single-molecule spatial imaging. The observed p65 translational APR is evident in both statically sampled timepoints and dynamic response gradients from perfused fixation. This translational regulation is vital in CF, where resident macrophages and transmigrating neutrophils persist in high-inflammation lung areas despite successful treatment. The spatiotemporal activity of immune cells – fibroblasts, macrophages, neutrophils – poses significant clinical challenges because they fail to clear infection and engender tissue damage with prolonged activation. Examining the immune landscape spatiotemporal patterns is critical to identifying opportune windows for treatment and investigating why bactericidal capabilities are malfunctioning.

Committee Members:

Oliver Hobert, Ph.D. (Department of Biological Sciences, Columbia University)

Patrick McGrath, Ph.D. (School of Biological Sciences, Georgia Tech)

Eva Dyer, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech)

Ghassan AlRegib, Ph.D. (School of Electrical and Computer Engineering, Georgia Tech) 

Novel Computational Methods for Scalable C. elegans Neuroimaging Analysis

      Deciphering the relationship between neural circuit structure, function, and behavior requires powerful methods for observing and analyzing neural dynamics at scale, posing a fundamental challenge in neuroscience. The nematode Caenorhabditis elegans, with its fully mapped nervous system and powerful genetic tools, provides an exceptional model for dissecting these mechanisms, especially when combined with fluorescence microscopy to visualize neural structure and function in vivo. However, realizing the full potential of this approach is often limited by critical bottlenecks in data analysis throughput, inherent trade-offs in imaging parameters like speed and resolution, and the prohibitive labor cost associated with manually annotating large, dynamic datasets.

      This thesis focuses on developing novel computational tools, leveraging computer vision and machine learning, to overcome these specific limitations in C. elegans fluorescence neuroimaging. First, to address the challenge of quantifying synaptic structures at scale, I developed WormPsyQi, an automated pipeline using machine learning for robust, high-throughput synapse segmentation and analysis across diverse reporter types (Aim 1). Second, to mitigate imaging trade-offs that compromise functional studies, I created Deep Video DeBinning (DVDB), a semi-supervised video super-resolution method that computationally restores spatial detail lost to camera binning, enabling high-fidelity activity analysis from high-speed, high-SNR recordings for applications like studying rapid locomotion dynamics or performing volumetric whole-brain imaging (Aim 2). Third, confronting the annotation bottleneck in analyzing large volumetric neural activity datasets, I designed ASCENT, a self-supervised deep learning framework utilizing a Neuron Embedding Transformer (NETr) to achieve state-of-the-art 3D neuron tracking accuracy without requiring manual annotations (Aim 3).

      Together, these computational tools provide validated, scalable solutions that enhance our ability to perform quantitative analysis of neural circuit structure and function in C. elegans. By automating key analysis steps and computationally overcoming imaging limitations, this work lays the groundwork for deeper investigations into the structure, function, and dynamics of neural circuits in this powerful model system.

Committee:

Rudy Gleason, Ph.D. (ME, Georgia Institute of Technology)

Peter Hesketh, Ph.D. (ME, Georgia Institute of Technology)

Todd Sulchek, Ph.D. (ME, Georgia Institute of Technology)  

Alex Abramson, Ph.D.  (ChBE, Georgia Institute of Technology) 

Development of wireless implantable bioelectronics integrated on a unified platform with existing medical devices for enhancing physiological monitoring  

While technological advancements have heightened public awareness of health monitoring, significant barriers to obtaining quality health data persist for a large population, particularly high-risk patients. Many diagnoses require costly, time-consuming visits to well-resourced health facilities, adversely affecting patient health. As healthcare systems shift toward decentralization, there is a growing need for monitoring tools that can be used in outpatient clinics or procedural centers without sacrificing accuracy or reliability. This proposal seeks to address that need by developing wireless, implantable bioelectronic systems for accessible physiological monitoring of high-risk patients. This work aims to incorporate these systems into existing medical devices using an LC-circuit based design to wirelessly detect abnormal conditions outside of hospital settings. Achieving this technology requires a thorough understanding of biosensors, wireless monitoring, and pathophysiological signals. This work targets two diseases, atherosclerosis and end-stage-kidney disease (ESKD), both of which have costly invasive procedures to diagnose common complications. In Aim 1, a bioelectronic vascular stent, capable of wirelessly diagnosing in-stent restenosis, is optimized with a miniaturized sensor to integrate with current catheterization procedures. In Aim 2, a fully flexible wireless monitoring system is developed and studied to detect stenosis growth and location within arteriovenous grafts (AVG) used for dialysis. Lastly, Aim 3 looks to enhance the implanted system's wireless performance by modifying both the device and external reader to extend the wireless capabilities of the system. Together, these efforts aim to advance the fields of soft electronics and passive sensing while enabling more accessible, non-hospital-based diagnostics for high-risk patients.

Manu O. Platt, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech)

Edward A. Botchwey, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech)

Committee Members:

Spencer H. Bryngelson, Ph.D. (School of Computational Science and Engineering, Georgia Tech)

Rudolph L. Gleason, Ph.D. (George W. Woodruff School of Mechanical Engineering, Joint Appointment in the School of Biomedical Engineering, Georgia Tech)

John N. Oshinski, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech & Emory University)

Alessandro Veneziani, Ph.D. (Department of Mathematics, Emory University)

Longitudinal Magnetic Resonance Angiography to Quantify Arterial Remodeling in Sickle Cell Disease

Sickle cell disease (SCD) is a devastating inherited blood disorder associated with progressive arterial damage and a heightened stroke risk, particularly ischemic stroke in childhood and hemorrhagic stroke in early adulthood. The mechanisms driving arterial damage in SCD are still not fully understood. In clinical settings, magnetic resonance angiography (MRA) has become indispensable for evaluating cerebrovascular health and stroke management. While bone marrow transplantation (BMT) is the only curative therapy for SCD, some individuals remain at risk for stroke post-transplant, underscoring the need for optimized timing to prevent arterial complications. 

Using a humanized SCD mouse model, we performed non-contrast MRA to investigate arteriopathy by measuring common carotid artery luminal areas longitudinally. SCD mice exhibited expansive outward remodeling with age, indicating a weakened arterial wall. In addition, MRA revealed large artery abnormalities, including stenoses and occlusions in carotid and cerebral arteries, mirroring findings in SCD patients with stroke complications. To identify imaging biomarkers for early detection, we applied radiomics analysis to MRA images, distinguishing SCD from heterozygous mice based on quantitative radiomic features. We further optimized phase contrast-MRI methods for blood flow measurements in the common carotid arteries of SCD mice. In addition, we established a method for computational fluid dynamic modeling to evaluate the relation between common carotid artery geometries obtained from MRAs and hemodynamics. 

To explore potential therapeutic strategies, we investigated the role of cathepsin K, a potent collagenase and elastase upregulated in SCD, in arterial remodeling. Genetic knockout of cathepsin K in SCD mice mitigated expansive remodeling, medial thinning, and elastin and collagen degradation in the arterial wall. Finally, we assessed whether BMT could prevent arterial remodeling in SCD mice at different disease stages. Early BMT at 2 months prevented arterial remodeling, whereas late BMT at 4 months failed to reverse pre-existing damage. These results emphasize the importance of early intervention to prevent irreversible arterial damage in SCD. As the field continues to advance with gene-editing therapies, this work may provide valuable guidance on optimizing the timing of intervention to maximize the benefits of these innovative treatments. 

Kostas Konstantinidis, Ph.D. (School of Civil and Environmental Engineering, Georgia Tech)

Committee Members:

Kostas Konstantinidis, Ph.D. (School of Civil and Environmental Engineering, Georgia Tech)

Michael Woodworth, MD (Division of Infectious Diseases, Emory University)

Edward Botchwey, Ph.D. (School of Biomedical Engineering, Georgia Tech)

Identifying a potential consortium of bacterial species and functions for the reduction of enteric multidrug resistant organisms by microbiota transplantation

Antibiotic resistance is an urgent healthcare crisis. Traditional drug development is not able to keep up with the evolution of new resistant pathogens, leaving very few viable therapeutic options. Faecal microbiota transplantation (FMT) has shown remarkable promise in its success in preventing recurrent Clostridioides difficile infections (rCDI), with a success rate of up to 90% and the approval of two commercial products since 2022. FMT success in rCDI is often accompanied by significant shifts in the composition of antibiotic resistance genes of patients’ gut microbiomes, but studies evaluating the direct effect of FMT in treating multidrug resistant organisms (MDROs) have been met with mixed results. Success rates vary between studies, scalability and safety of FMT are ongoing challenges, and no consensus on the key bacterial taxa involved in successful applications has been reached, likely due to the high inter-individual heterogeneity of the human gut microbiome and the complex diversity of MDROs. Additionally, there is a lack of functional analysis to explain the mechanism behind successful FMT treatments. In this study, we use a temporal definition of engraftment and identify a consortium of fourteen bacterial species that are engrafting across different studies and are negatively correlated with pathogen abundance. This consortium differs from the taxa responsible for rCDI prevention, which has important implications for future drug development. We also identify gene functions that may facilitate the engraftment of these taxa, as engrafting genes are involved in growth, adhesion and environmental sensing. Overall, we show that our bioinformatic approach can identify a consensus in taxonomic and functional changes after FMT and could be adapted to other microbiota-responsive indications. Here, we apply our approach to efficiently nominate candidate strains to reduce MDRO colonisation and address the global threat of antibiotic resistance.

Committee Members:

Daniel I. Goldman, Ph.D. (School of Physics, Georgia Tech)

Patrick McGrath, Ph.D. (School of Biological Sciences, Georgia Tech)

Simon Sponberg, Ph.D. (School of Physics, Georgia Tech)

Lena Ting, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech)

The role of proprioception in locomotion control

      Animals must navigate through diverse terrain. This task requires them to adapt their locomotion strategy to the local environment. Locomotor adaptation requires integrating sensory feedback, particularly from proprioception, which provides critical information about body position and motion. While different proprioceptive neurons encode distinct sensory signals, how these inputs are integrated to modulate motor outputs remains unclear. I study proprioceptive integration and motor control using the model organism C. elegans. C. elegans moves using undulation, propagating a body wave from head to tail, and can adapt its gait to different physical environments. C. elegans is a useful model for studying locomotion adaptation due to its compact nervous system, ease of recording neural activity and readily available genetic tools. My thesis addresses this gap in proprioceptive integration and motor control by developing tools for improved functional imaging and using a combination of modeling and genetic perturbations to assess the role of proprioception and motor control in gait adaptation. First, I develop and apply deep learning tools to improve functional imaging during locomotion to determine the motor patterns used for gait adaptation (aim 1). Next, I investigate the role of several proprioceptive neurons in gait adaptation through genetic perturbation (aim 2). Finally, I develop a neuromechanical model based on locomotion changes in proprioceptive-deficient C. elegans mutants to gain insights into their proprioceptive control strategies (aim 3). The tools and framework developed in this work provide a foundation for future studies to further elucidate the role of proprioception in gait adaptation and motor control. This work provides insights into genetic mechanisms of proprioception for further study in other organisms and suggests control strategies for bioinspired robotics that require adaptive gait modulation across diverse environments.

Committee:

Marianne Alleyne, Ph.D. (Integrative Biology, University of Illinois Urbana-Champaign)

David Hu, Ph.D. (ME, Georgia Institute of Technology)

Yuhang Hu, Ph.D. (ME & ChBE, Georgia Institute of Technology)  

Todd Sulchek, Ph.D.  (ME, Georgia Institute of Technology) 

Wax “Tails” and Fairy Knots:

Dynamic Functions of Passive Adornments in Planthoppers and Humans 

The striking appearance of wax “tails” – posterior wax projections produced by planthopper nymphs (immature form) – has captivated entomologists and naturalists alike. Despite their common presence, the functional roles of these projections are not fully understood. During their powerful jumps, nymphs experience an airborne phase, making aerial stabilization strategies an important component of their locomotion. Other wingless insects generate stabilizing aerodynamic torques from appendage movements. Similarly, we hypothesize that wax-bearing nymphs leverage their wax structures for aerial stability and subsequent successful landings. In Aim 1, we analyze rotational stability and landing success rates from high-speed videos of nymph jumps with wax intact and wax removed. For Aim 2, we assess the role of stabilizing drag forces and develop a computational model of nymph jumps. These findings will provide insight into the adaptive significance of wax structures, revealing the relationship between wax morphology and aerial maneuverability.

The second research topic shifts the study of passive adornments from insect wax to human scalp hair. Fairy knots, also known as single-strand knots, are a common occurrence in coily-curly hair. The name evokes the knots' seemingly spontaneous and precise formation on a single strand of hair, indicating that only a small fairy could tie the tiny, meticulous knot unnoticed. Once formed, fairy knots are difficult to detangle and remove leading to breakage, hindered growth, and increased surface roughness. Despite their common occurrence in coily-curly hair, the mechanisms behind fairy knot formation, although having speculated causes, have not been formally investigated. This research aims to identify the biomechanical mechanisms behind fairy knot formation. In Aim 1, we characterize fairy knot form, frequency, and location as well as use new and established hair classification methods to characterize fairy knot prone hair. Aim 2 and Aim 3 examine how hair recoil, induced through mechanical manipulation (e.g., pulling and releasing, smoothing, and combing) or hydromechanical forces (e.g., wetting and drying), contributes to knotting. Additionally, measure relevant mechanical and physical properties of hair to link quantifiable parameters with knot formation. This research has broader implications for understanding hair behavior and can inform the development of hair care products and technologies (e.g., hairstyles) designed to prevent knot formation.

Thesis Committee:
Dr. Alexander Alexeev, Mechanical Engineering, Georgia Institute of Technology
Dr. Rudolph Gleason, Mechanical Engineering, Georgia Institute of Technology
Dr. Susan Thomas, Mechanical Engineering, Georgia Institute of Technology
Dr. Joseph Dayan, MD, MBA, Plastic & Reconstructive Surgeon, Board Certified in Plastic Surgery, Institute for Advanced Reconstruction

Modeling Lymphatic System Dynamics: Experimental and Computational Approaches to Lymphedema Treatment

Lymphedema is a debilitating condition caused by impaired lymphatic drainage, leading to chronic swelling and tissue damage. Despite its widespread prevalence, effective treatment options remain limited due to an incomplete understanding of the lymphatic system’s physiological responses to injury and treatment interventions. This thesis aims to bridge this knowledge gap by integrating experimental and clinical approaches with computational modeling to explore lymphatic function and remodeling. This work is structured around three specific aims. Aim 1 focuses on a large-animal study using a sheep model to characterize the growth and remodeling of lymphatic vessels following injury. By combining in-vivo imaging, ex-vivo vessel analysis, and mechanical modeling, this study will provide critical insights into the contractile dynamics and adaptive responses of lymphatic vessels under mechanical stress. Aim 2 develops a lumped parameter model to simulate lymphaticovenous anastomoses (LVA), a microsurgical intervention for lymphedema, assessing how different configurations influence lymphatic transport efficiency. Aim 3 integrates growth and remodeling responses into the computational model to predict long-term LVA adaptations under varying mechanical loads. By linking experimental observations with computational simulations, this research aims to advance our understanding of lymphatic adaptation mechanisms and inform the development of LVA treatment for lymphedema. The findings will contribute to the refinement of LVA techniques and provide a foundation for future studies on lymphedema interventions. 

Committee Members:

John Blazeck, Ph.D. (School of Chemical and Biomolecular Engineering, Georgia Tech)

Lily Cheung, Ph.D. (School of Chemical and Biomolecular Engineering, Georgia Tech)

Gabriel Kwong, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech )

Brian Hammer, Ph.D. (School of Biological Sciences, Georgia Tech) 

Multifaceted Rolling Circle Amplification Strategies to Reduce False Positives in Point-of-Care Biosensors

In modern warfare, developing sensors that can be used in the field to address the risks associated with biological weapons and infectious diseases is essential. Densely populated military bases enable the rapid spread of infectious diseases, requiring rapid and accurate detection despite limited resources. Particularly, false positives in a sensor result in a significant waste of workforce, time, and resources. Therefore, developing sensors with minimal false positives and ease of use is essential. Rolling Circle Amplification (RCA) is an isothermal DNA amplification technology making it ideal for point-of-care (POC) biosensors. However, RCA performed in a minimal-equipment POC setting operates at a temperature low enough to increase the rate of false positives, presenting an inherent limitation to its utility at the POC. Therefore, I propose a multifaceted approach to reduce false positives in RCA through the multiplexed detection of various targets while maintaining suitability for field deployment. First, I propose a strategy to enhance input selectivity to detect target pathogens accurately without false positives. I propose a novel approach using an AND gate to detect multiple genes simultaneously. Next, I will improve selectivity for a single gene by combining a gap-filling technique with mismatch endonucleases to require precise sequence complementarity for amplification. Then, I will reduce false positives by diversifying output signals for multiple targets within the same pathogen by combining Rolling Circle Transcription (RCT) with RNA fluorescent aptamers. For all of these approaches, I will aim to achieve field deployability by integrating the multiple reaction steps of RCA into one step and demonstrating functionality after lyophilization. Once successfully completed, the work proposed here will enable the development of biosensors that minimize false positives, are user-friendly, and present practical sensor technology applicable in the field.

Dr. Saad Bhamla, Chemical and Biomolecular Engineering, Georgia Institute of Technology

Thesis Committee:

Dr. Audrey Dussutour, Center for Research on Animal Cognition, National Center for Scientific Research (University of Toulouse)

Dr. William Ratcliff, Quantitative Biosciences, Georgia Institute of Technology 

Dr. David Hu, Mechanical Engineering, Georgia Institute of Technology

Dr. Kostas Konstantinidis, Civil and Environmental Engineering, Georgia Institute of Technology 

RNA-mediated Unicellular Learning and Cognition

Unicellular organisms, despite lacking neurons, exhibit diverse learning behaviors, including habituation and classical conditioning. While the validity of complex learning in unicellular systems remains debated, compelling evidence suggests that memories can be transferred between these organisms, with growing support for RNA as a molecular engram for memory storage. This proposal aims to elucidate RNA’s role in learning and challenge the cognitive limitations of unicellular organisms, proposing that unicellular learning mechanisms may not only precede but also influence neural-based learning. The ciliate Spirostomum ambiguum serves as an ideal model system, given its well-documented habituation profiles and unicellular architecture, which enables precise molecular investigations of learning without the confounding complexities of multicellular systems. Three interconnected objectives will be pursued to illuminate how cells can learn without neurons. Aim 1 focuses on inducing and molecularly characterizing habituation in S. ambiguum using novel transcriptomic methods, revisiting an outdated correlation between RNA dynamics and habituation with modern approaches to validate RNA's role in learning. Aim 2 challenges the cognitive boundaries of unicellular organisms by testing associative learning in S. ambiguum, demonstrating that the gap in learning capacity between neural and aneural organisms is smaller than previously assumed. Aim 3 explores collective learning mechanisms in swarming populations, investigating the ecological significance of learning for S. ambiguum. By pushing the cognitive boundaries of unicellular systems, this work will help establish S. ambiguum and similar organisms as a reductionist model for behavioral studies, providing insights into fundamental learning mechanisms that may serve as precursors to neural learning in more complex organisms.

Prof. Adam Marcus (School of Medicine, Winship Cancer Institute, Emory University)

Committee:

Prof. Sumin Kang (School of Medicine, Winship Cancer Institute, Emory University)

Prof. Shuichi Takayama (School of Biomedical Engineering, Georgia Institute of Technology)

Prof. Edward Botchwey (School of Biomedical Engineering, Georgia Institute of Technology)

Prof. Andrés García (School of Mechanical Engineering, Georgia Institute of Technology)

Spatiotemporal Interrogation of Metabolic Cooperation in Collective Cell Invasion

Cancer can be characterized by a lack of uniformity. There are the obvious distinctions of cancer type—lung vs prostate vs skin cancers—but even the cancer cells within a single tumor of an individual patient exhibit a variety of mutational and behavioral profiles. This heterogeneity contributes to the successful overall progression of cancer by means of drug resistance and, as we argue here, stress management. Previous work highlights metabolic heterogeneity within the H1299 non-small cell lung cancer (NSCLC) model cell line. One distinct subpopulation within the model, characterized by aggressive invasion, relies heavily on oxidative phosphorylation (OXPHOS) while a second subpopulation, characterized by less invasion but more proliferation, utilizes glycolysis for energy production. Our in-vivo data suggests that, while each subpopulation can independently form primary tumors, the combination of both is required for successful macro-metastasis to peripheral locations. This led us to hypothesize that metabolic heterogeneity in lung cancer enables metabolic cooperation which promotes cancer progression by means of valuable-resource sharing in harsh and otherwise unsustainable, nutrient-scarce microenvironments. To test this hypothesis, we aimed to 1) develop a methodology—incorporating genetic engineering, live-cell, high-resolution microscopy, and common end-point assays—capable of observing and characterizing this metabolic cooperation in NSCLC cells and amenable to simple translation for investigation of other forms of cooperation across cancer types and 2) uncover,  using this methodology, modes and mechanisms of glycolytic and OXPHOS-related cargo sharing within NSCLC. At the forefront of the race to reduce cancer deaths lies a fundamental understanding of how cancer progression and metastasis occur. This body of work provides an adaptable technique for interrogation of this process from a perspective focusing on the cooperative potential that intratumoral heterogeneity affords. It also contributes novel insight into how one specific cancer type makes use of cooperation to overcome obstacles to disease progression.

Dr. Martha Grover, Chemical and Biomolecular Engineering, Georgia Institute of Technology

Dr. Carson Meredith, Chemical and Biomolecular Engineering, Georgia Institute of Technology

Thesis Committee:

Dr. Hang Lu, Chemical and Biomolecular Engineering, Georgia Institute of Technology

Dr. Scott Danielsen, Materials Science and Engineering, Georgia Institute of Technology

Dr. Victor Fung, Computational Science and Engineering, Georgia Institute of Technology 

DATA-DRIVEN DESIGN OF POLYSACCHARIDE-BASED BARRIER FILMS

The widespread use of non-degradable petroleum-based plastics in food packaging, favored for their cost-effectiveness and excellent mechanical and barrier properties, has led to severe environmental issues. Cellulose and chitin, the most abundant polysaccharides in nature, offer a promising sustainable alternative to conventional plastics. Their nanomaterials, characterized by high crystallinity and strong hydrogen bonding, enable excellent mechanical and barrier properties, making them ideal candidates for developing barrier films to substitute petroleum-based plastics. To create high-performance barrier films, it is essential to minimize the transport of moisture and oxygen through the film, ensuring the preservation of packaged goods' quality, while maintaining mechanical stability. Achieving this requires a deep understanding of the process-structure-property (PSP) relationships for these films to optimize their performance. Traditionally, the discovery and development of new materials has been a time-consuming and resource-intensive process, often relying on trial-and-error, also known as the Edisonian approach, to discover and design materials within a span of decades. However, as a growing field, materials informatics offers great potential for accelerating the process of developing high-performing sustainable materials. Therefore, this thesis proposal aims to leverage data-driven materials informatics approaches to model PSP relationships in polysaccharide-based barrier films. Machine learning and data science techniques will be applied on curated experimental data to develop PSP models that guide future experiments aimed at enhancing barrier film performance. To evaluate the practical applicability of the developed models, predicted high-performing barrier films will be fabricated and tested after exposure to environmental conditions commonly faced by packaging materials.

Committee:

Dr. John Blazeck, Ph.D. (ChBE, Georgia Institute of Technology)

Dr. Julie Champion, Ph.D. (ChBE, Georgia Institute of Technology)

Dr. Yury Chernoff, Ph.D. (Biological Sciences, Georgia Institute of Technology)

Dr. Brian Hammer, Ph.D. (Biological Sciences, Georgia Institute of Technology)

Mapping Alternate Allosteric Communication of LacI Anti-repressors and Their Application in Saccharomyces cerevisiae

Regulatory proteins are powerful tools that control all life processes. Many regulatory proteins function by allosteric communication, a mechanism in which a signal is propagated between two functional surfaces across the protein. The lactose repressor (LacI) has been essential in unveiling the mechanism behind allostery. It has also been engineered to build anti-repressors of the inverse phenotype (anti-lacs), which together can build Transcriptional Programming (T-Pro) genetic circuits in E. coli. While LacI has been studied in great detail, I posited that the allosteric pathways of engineered anti-lacs differ from their native repressor. To test this hypothesis, I performed deep mutational scanning on two engineered anti-lacs to generate a single-mutation phenotype-genotype heat map for each anti-lac. Through this work, I compared the allosteric pathways of anti-lac transcription factors (TFs) and developed comprehensive design rules for engineering alternate allosteric communication. While these TFs were analyzed in E. coli, I posited that these design rules could be translated to any chassis. I successfully used the design rules developed from this work to build the first engineered anti-repressor in Saccharomyces cerevisiae, a model higher-order eukaryotic organism. Additionally, I developed a T-Pro reporter system in S. cerevisiae by engineering a high-performance promoter capable of regulating transcription with LacI TFs. Finally, by engineering alternate DNA recognition on my engineered anti-lac and on yeast-enhance LacI, I developed the building blocks for T-Pro in S. cerevisiae. This work verifies the importance of understanding the allosteric pathway of LacI TFs and lays the foundation for the design and implementation of more complex T-Pro circuits in S. cerevisiae.

Thesis Committee:

J. Brandon Dixon, Ph.D.  (Woodruff School of Mechanical Engineering, Georgia Institute of Technology)

May D. Wang, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology)

Wilbur A. Lam, M.D., Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Emory School of Medicine & Georgia Institute of Technology)

Michael J. Weiler, Ph.D. (CEO, LymphaTech Inc.)

Efficient longitudinal modeling of the 3D shape of women during gestation and its value in assessing the risk of cephalopelvic disproportion (CPD).

Cephalopelvic disproportion (CPD) is a mismatch in the size of the maternal pelvis and the fetus, which often leads to obstructed labor. Most cases of CPD require C-section for successful delivery and in low resource settings like Ethiopia, there is a lack of adequate facilities with the infrastructure or the expertise to perform a C-section. Currently, obstructed labor is known to account for 11 – 22 % of maternal deaths in Ethiopia. Early assessment of the risk of CPD would enable women in these settings to access the proper healthcare services and improve overall maternal health. This thesis aims to develop an algorithm that would use longitudinal shape modeling to analyze, in real-time, 3D scans of pregnant women and assess the risk of CPD-related obstructed labor at the earliest possible stages of gestation. The longitudinal shape model would be trained on 3D scans of pregnant women across different periods of gestation and would be optimized to run on devices with low computational power. The prognostic value of the model for assessing the risk of CPD would be compared to anthropometric measurements. This model is envisioned to be used by nurses and midwife personnel as part of point-of-care tools for routine antenatal care in low-resource settings.

MS Teams Meeting ID: 258 046 490 033

Passcode: WGaQw6

BIO
Jennifer Phillips-Cremins, Ph.D. is an Associate Professor and Deans' Faculty Fellow in Engineering and Medicine at the University of Pennsylvania with primary appointments in the Departments of Bioengineering and Genetics. Dr. Cremins obtained her Ph.D. in Biomedical Engineering from the Georgia Institute of Technology in the laboratory of Andres Garcia. She then conducted a multi-disciplinary postdoc in the laboratories of Job Dekker and Victor Corces. Dr. Cremins now runs the Chromatin Architecture and Systems Neurobiology laboratory at UPenn. Her primary research interests lie in understanding the long-range chromatin architecture mechanisms that govern neural specification and synaptic plasticity in healthy neurons and how these epigenetic mechanisms go awry in neurodevelopmental and neurodegenerative diseases. She has been selected as a 2014 New York Stem Cell Foundation Robertson Investigator, a 2015 Albert P. Sloan Foundation Fellow, a 2016 and 2018 Kavli Frontiers of Science Fellow, 2015 NIH Director's New Innovator Awardee, 2020 NSF CAREER Awardee, and a 2020 CZI Neurodegenerative Disease Pairs Awardee.

Thesis Committee:

Young Jang, Ph.D.  (Emory Musculoskeletal Institute, Department of Orthopedics, Wallace H. Coulter Department of Biomedical Engineering, Emory School of Medicine & Georgia Institute of Technology)

Melissa Kemp, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Emory School of Medicine & Georgia Institute of Technology)

Srikant Rangaraju, M.D. (Department of Neurology, Yale University)

Annabelle Singer, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Emory School of Medicine & Georgia Institute of Technology)

Re-wiring CSF1-R Signaling in Alzheimer’s Disease

Alzheimer’s disease (AD) is the most common cause of dementia, affecting over 6.9 million people in the US, a number projected to double by 2060 without a cure. Emerging evidence highlights the role of the brain’s immune system, particularly microglia, in AD-related neurodegeneration and cognitive decline. Microglia, the brain’s immune sentinels, transition from a protective "homeostatic" state to a "disease-associated" state (DAM) under chronic AD pathology, impairing phagocytosis, disrupting immune activity, and accelerating neurodegeneration. Microglial immunological shift and phenotypic transformation are orchestrated by variety of signaling pathways and cell surface receptors like colony-stimulating factor-1 receptor (CSF1-R). CSF1-R, expressed primarily on microglia in the brain, governs key processes including phagocytosis, polarization, and proliferation. Studies suggest that CSF1-R-mediated microglial depletion can improve cognitive function in AD models. However, the mechanisms by which Aβ accumulation alters CSF1-R signaling to disrupt microglial function and drive disease progression remain unclear, necessitating further investigation. My hypothesis is that CSF1-R control of downstream signaling events and microglial phenotype are perturbed by exposure to Alzheimer’s disease pathogen Aβ. The goal of this research proposal is three-fold: (Aim 1) determine how Aβ interacts with CSF1-R and its effect on specific CSF1-R phospho-site activity and its downstream signaling cascades in vitro, (Aim 2) illuminate how dysregulated CSF1-R-mediated signaling impacts microglial phenotypes and neuroimmune activity in vitro and in vivo  and (Aim 3) identify AD-driven proteomic and transcriptomic signatures associated with CSF1-R activity and downstream signaling from human samples. This research proposal aims to provide a mechanistic insight into how AD pathology alters CSF1-R signaling and its downstream effectors. Identifying mechanisms through which disturbed CSF1-R signaling contributes to DAM phenotype, disturbed neuroimmune activity and pathogenesis in AD could ultimately lead to a new paradigm for AD therapeutic development.

Committee:

Yunus Alapan, Ph.D. (Department of Mechanical Engineering, University of Wisconsin-Madison)

Andrés J. García, Ph.D. (Woodruff School of Mechanical Engineering, Georgia Institute of Technology)

Sarwish Rafiq, Ph.D. (Department of Hematology and Medical Oncology, Emory University School of Medicine)

Levi Wood, Ph.D. (Woodruff School of Mechanical Engineering, Georgia Institute of Technology)

Microfluidic-Enabled Adhesion Analysis of Therapeutic T cells for Lymph Node Homing PotentialAdoptive T cell therapy (ACT) remains a promising class of cancer therapy, where patient-extracted T cells are engineered or expanded ex vivo before re-infusion. Importantly, treatment efficacy is strongly dependent on transferred cell engraftment within target tissues. These targets include the tumor, where transferred T cells mediate direct cancer cell killing, and lymphoid tissues, including lymph nodes (LNs), which serve as specialized niches for T cell survival and priming. However, current patient responses to ACT are severely limited by poor engraftment within these target sites. To this end, the objective of this thesis is to engineer microfluidic devices to isolate T cell subsets with improved LN engraftment potential and evaluate the phenotype and therapeutic potential of isolated populations. My central hypothesis is that in vitro recapitulation of both physiological fluid flow and different adhesive motifs of the LN vascular microenvironment (termed high endothelial venules, HEVs) will result in capture of T cell subsets with enhanced LN homing capacity and therapeutic potency. Using these devices, I will evaluate the adhesion profiles of two distinct T cell products and their homing efficacy and therapeutic potency in in vivo adoptive transfer studies. These include 1) human CAR-T cell adhesion to homeostatic vs. inflamed LN HEV motifs associated with lymphoma and 2) murine CD8+ T cell adhesion to a tumor-draining LN HEV motif in the context of breast cancer. Lastly, I will interrogate the adhesive phenotypes of murine T cell subsets using engineered microfluidic devices that mimic anatomically distinct LN HEVs. Specifically, these will include peripheral versus mesenteric LNs, due to their specialized immune functions. Overall, these studies will demonstrate a scalable in-vitro methodology to relate different adhesion ligand/receptor profiles among heterogenous T cell products to their phenotypes and predict resulting therapeutic potency, based on homing capacity. 

          Dr. Holly Bauser-Heaton, MD, PhD (Emory University)

Committee:   Dr. Rudolph Gleason, PhD (Georgia Institute of Technology)
            Dr. Scott Hollister, PhD (Georgia Institute of Technology)
            Dr. Susan James, PhD (Colorado State University)
            Dr. Vinod Thourani, MD (Piedmont Healthcare)

Investigation of a Transcatheter Bio-Inspired Polymeric Valve for Hemodynamic Performance and Durability

 With the recent Food and Drug Administration (FDA) approval extending transcatheter aortic valve replacement (TAVR) to intermediate and low risk patients with aortic stenosis, the procedure’s landscape has evolved significantly to include patients under 65. However, current technology drawbacks limit the use of TAVR in younger patients and complex anatomies such as bicuspid aortic valve, thereby limiting the full potential and benefits offered by the TAVR method. Existing devices use animal-tissue leaflets, which present durability challenges due to calcification, structural valve degeneration, and issues like leaflet thrombosis and paravalvular leakage (PVL). These complications reduce device lifespan and impair hemodynamic performance, often requiring reinterventions. Thus, for TAVR to become a long-term solution for younger patients, the next generation of devices must overcome these limitations. This includes development of devices with durable, biocompatible materials that are designed for excellent hemodynamic performance.Towards this goal, this project is aimed at developing a bio-inspired polymeric TAVR that is biocompatible and is designed for excellent hemodynamic performance and durability. The overall hypothesis is that the polymeric TAVR will have superior hemodynamic performance and durability than commercially available bioprosthetic TAVRs. A comprehensive focus on its pressure and flow performance coupled with durability will inform further improvements to its design and assembly, enhancing the device. This polymeric TAVR will pave the way for a long-lasting and biocompatible TAVR suitable for younger patients. The hypothesis will be tested through the following specific aims: 1) Compare hemodynamics of polymeric TAVR with standard bioprosthetic TAVR, 2) Investigate the efficacy of a dynamic seal for preventing paravalvular leakage and 3) Evaluate the role of manufacturing and deployment on polymeric TAVR durability.

By addressing the critical challenges of hemodynamic performance and durability, this work will contribute to the development of innovative TAVR solutions that meet the growing demand for more resilient, long-lasting valves in younger and high-risk patient populations.

Advisor: James Dahlman, Ph.D. (BME, Georgia Institute of Technology & Emory University) 

Committee:

Dr. Leslie Chan, Ph.D. (BME, Georgia Institute of Technology & Emory)
Dr. Wilbur Lam, Ph.D. (BME, Georgia Institute of Technology & Emory)
Dr. Philip J. Santangelo, Ph.D. (BME, Georgia Institute of Technology & Emory)
Dr. Todd Sulchek, Ph.D. (ME, Georgia Institute of Technology) 

Characterizing lipid nanoparticle mRNA delivery to the central nervous system 

Lipid nanoparticles (LNPs) have demonstrated safety, versatility, and clinical relevance as vehicles for RNA delivery. Currently, there are three FDA-approved LNP-RNA drugs: ONPATTRO®, the systemically administrated siRNA treatment for hereditary liver disease from Alnylam; and two intramuscular mRNA vaccines against COVID-19: SPIKEVAX® produced by Moderna and by Pfizer-BioNTech’s COMIRNATY®. However, beyond vaccination and liver targeting, LNP-RNA drugs are far from reaching their full potential. Research has shown that LNPs can deliver RNA effectively to non-liver tissues, such as lung, spleen, solid tumors, and bone marrow. For the treatment and management of nervous system disorders, gene therapies hold great promise but require safe and effective delivery vehicles. Therefore, a need exists to design LNPs that transfect cells in the central nervous system (CNS). Presently, LNPs with CNS tropism either i) carry ligands, ii) rely on blood-brain barrier disruption, or iii) are administrated locally. In this work, we have investigated mRNA delivery to the CNS upon systemic administration without targeting ligands. Firstly, we optimized the isolation of various cell types from the brain. Secondly, we have studied mRNA delivery readouts for liver de-targeted LNPs, and identified nanoparticle characteristics for subsequent high-throughput LNP screening. Thirdly, we formulated and screened LNPs with these chosen characteristics that we administrated intravenously, and characterized the in vivo tropism of  brain-delivering LNPs at the cellular level. Lastly, we used spatial transcriptomics to understand where in the brain the best-performing LNP achieved functional delivery and how mRNA was distributed within the tissue. Through this work, we have shown CNS delivery by liver de-targeted LNPs, and demonstrated the feasibility of systemic delivery of therapeutic mRNA to the cells of the blood-brain barrier without the use of targeting ligands.

Committee:

Daniel Goldman, Ph.D. (Physics, Georgia Institute of Technology)

David Hu, Ph.D. (ME, Georgia Institute of Technology)

Jorn Dunkel, Ph.D. (Math, Massachusetts Institute of Technology)  

Emily Weigel, Ph.D.  (Biological Sciences, Georgia Institute of Technology)

Physically Entangled Collective Behavior of Aquatic Worm Blobs

California blackworms (Lumbriculus variegatus) form dense, physically entangled structures known as "worm blobs" through chemoattraction, conspecific thigmotaxis, and balancing oxygenation levels. Despite their seemingly stationary nature, these blobs exhibit complex, coordinated behaviors, including rapid transitions between entangled and untangled states. This thesis explores the dynamics of blackworm entanglement and collective behavior through an interdisciplinary approach, combining behavioral biology, active matter physics, and topology. 

First, we examine how dissolved oxygen (DO) levels shape their material-like properties. Worm blobs transition between solid-like and fluid-like states as they adapt to varying DO, forming stable, dense structures in high-oxygen conditions and more fluid configurations in low-oxygen environments. These findings align with behaviors observed in robophysical simulations of “smarticles,” where environmental shifts that impact their internal actuations similarly influence collective properties. We also study the worms' use of helical movements for rapid entanglement and disentanglement, crucial for maintaining cohesion and escaping predators. In interactions with freshwater leeches, blackworms form dense entangled barriers to deter predation, while coordinated helical motions enable swift escape. The leeches’ spiral entombment behavior shows an adaptive predatory strategy to counter this. Furthermore, we reveal emergent behaviors like mucus-mediated particle gathering, with implications for environmental applications such as microplastic collection. The newly identified "worm buoy" behavior showcases how blackworms use surface tension to form floating structures in low-oxygen conditions, enhancing their access to oxygen.

Overall, this study provides insights into physical entanglement, with applications in designing materials and technologies inspired by these collective behaviors. It opens pathways for developing soft entangled swarm robotics and adaptive materials that emulate the resilience and coordination of nature’s systems.

Dr. James C Gumbart (School of Physics)

Committee:

Dr. M. G. Finn (School of Chemistry & Biochemistry), Dr. Peter Kasson (School of Chemistry & Biochemistry), Dr. Jeffrey Skolnick (School of Biological Sciences), Dr. Adegboyega Oyelere (School of Chemistry & Biochemistry)

Altering Hepatitis B Virus Capsid Assembly through Pharmacological Intervention

Chronic hepatitis B virus (HBV) infection affects approximately 250 million people globally, leading to around 800,000 deaths annually from liver-related complications. This thesis focuses on disrupting HBV capsid assembly, a critical step in the viral life cycle, through pharmacological intervention, with the aim of advancing antiviral drug discovery. The research is structured around three key objectives. The first objective is to discover and optimize novel capsid assembly modulators (CAMs) using computational methods, including molecular docking and molecular dynamics simulations. This approach will identify compounds that interfere with HBV capsid assembly, followed by optimization to enhance their efficacy and drug-like properties. The second objective involves fragment-based drug design to explore the interactions of small molecular fragments with a novel binding site, distinct from the conventional CAM binding pocket. This will guide the design of larger drug molecules, opening up new avenues for targeting HBV life cycle. The third objective investigates how small molecules allosterically alter the viral assembly pathway. By employing computational techniques such as the string method and free energy calculations, this aim will explore the conformational changes and energy barriers associated with capsid formation, providing mechanistic insights that could inform future antiviral strategies. Through the integration of drug discovery, compound optimization, and mechanistic analysis, this research aims to contribute to the development of novel therapeutic agents for HBV, offering potential new treatments for viral infection.

Dr. Shuichi Takayama (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)

Dr. Douglas K. Graham (Aflac Cancer & Blood Disorders Center, Children’s Healthcare of Atlanta, and Department of Pediatrics, Emory University School of Medicine) 

Committee:

Dr. Mark Styczynski (School of Chemical and Biomolecular Engineering, Georgia Institute of Technology)

Dr. Melissa Kemp (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)

Dr. Sunil Raikar (Department of Pediatrics, Emory University School of Medicine)

Developing High Throughput and Long-Term Human Bone Marrow Perivascular Organoids for Modeling Acute Myeloid Leukemia 

The human bone marrow (BM) microenvironment is a complex system composed of hematopoietic progenitor cells (HSPC) and a non-hematopoietic stroma formed by endothelial and mesenchymal stem cells (MSC). This 3D structure regulates blood cell production through specialized niches. Replicating this complexity, especially for acute myeloid leukemia (AML), is challenging. AML, a blood cancer with a poor prognosis, is further complicated by the BM tumor microenvironment (TME), which creates a protective environment that limits therapy efficacy. Current in vivo models are limited by reliance on animal physiology, high costs, and low throughput, while in vitro models often lack the spatial and cellular complexity of the BM microenvironment and have a short lifespan. To address these limitations, herein the development a human in vitro vascular BM model that accurately recapitulates the 3D AML BM TME is proposed. This model will support long-term AML cell proliferation and enable high-throughput screening of therapeutic agents. Aim 1 involves establishing BM stroma organoids by co-culturing MSCs and HUVECs in various ratios, with structural and functional characteristics analyzed through imaging, immunofluorescence, and single-cell RNA sequencing. Aim 2 focuses on creating AML BM organoids by co-seeding AML cells with MSCs and HUVECs, optimizing organoid formation, and assessing their architecture, cell composition, and TME features. Aim 3 evaluates the protective effect of the AML TME on Ara-C and MRX-2843 drug therapies through drug response assays.

Dr. Ravi Kane (Chemical and Biomolecular Engineering)

Committee:

Dr. John Blazeck (Chemical and Biomolecular Engineering)

Dr. Julie Champion (Chemical and Biomolecular Engineering)

Dr. MG Finn (Chemistry and Biochemistry)

Dr. Mark Prausnitz (Chemical and Biomolecular Engineering)

Designing Protein-based Vaccines for Broad Protection Against Coronaviruses and Influenza

Vaccination is one of the most effective methods of reducing or preventing infectious diseases. A significant remaining challenge is the design of vaccines for long-lasting and broadly protective immunity against highly variable viruses. Many viruses mutate quickly to escape host immune systems, leading to diverse strains with variable surface proteins. The immune response to one of these viruses focuses on the immunodominant but variable regions, which results in a strain-specific response. It is desirable to instead redirect the immune response to conserved areas of viral proteins, producing an immune response that can recognize and effectively eliminate many strains.

In this work, we have developed recombinant proteins vaccines with the goal of eliciting broadly protective immune responses. We found that the highly immunogenic SARS-CoV-2 receptor binding domain elicits high titers of neutralizing antibodies against SARS-CoV-2 variants, while the more conserved S2 subunit elicits non-neutralizing though still protective immunity against SARS-CoV-2 and closely related viruses. The S proteins of SARS-CoV-2 and related CoVs can be combined into a cocktail vaccine to elicit neutralizing and broadly protective antibodies against clade 1 viruses. Lastly, we demonstrated that long-lasting immunity can be elicited by VLP-based HA vaccines. Together, the results of these different strategies may aid in the design of broadly protective vaccines.

Zoom Link

Committee Members: 

John Blazeck, Ph.D. (Chemical and Biomolecular Engineering) 

Julie Champion, Ph.D. (Chemical and Biomolecular Engineering) 

Corey Wilson, Ph.D. (Chemical and Biomolecular Engineering) 

Levi Wood, Ph.D. (Mechanical Engineering)  

Engineering Multivalent Nanobodies Against Amyloid Proteins and Other Antigens

      Tauopathies, such as Alzheimer’s disease, are neurodegenerative diseases that involve the misfolding and deposition of aggregates of the amyloid protein tau. These diseases are among the most widespread neurodegenerative diseases, yet there are few safe and effective disease-modifying treatments for them. Conformational antibodies and antibody fragments that target the various aggregate forms of tau are promising candidates for treatments to slow the progression of these tauopathies and are useful as reagents to understand the aggregation of tau and its role in disease progression. In this dissertation, we have explored the in vitro development and characterization of multivalent nanobodies, or single-domain antibody fragments, targeting complex and heterogeneous tau aggregates.

      We began with the development of a simple approach using a synthetic yeast surface display nanobody library and in vitro cell sorting to identify a pan-tau nanobody with specificity for tau protein relative to other amyloid proteins. We have shown that multivalent versions of our lead tau-binding nanobody have increased avidity towards tau aggregates and recognize pathogenic tau found in the brains of tau transgenic mice. We have also characterized tau fibril-specific nanobodies and modified them for improved delivery past the blood-brain barrier. Next, we modified our sorting strategy to generate conformational nanobodies that target oligomeric tau, a form of aggregated tau which is suspected to be the most toxic form present in Alzheimer’s disease. We demonstrated that our nanobodies are specific for tau oligomers relative to tau monomer and fibrils and bind to tau oligomers in brain samples from Alzheimer’s disease patients. We have extended this work to screen for nanobodies that target oligomers of another amyloid protein involved in Alzheimer’s disease, amyloid-β. Finally, we applied our in vitro antibody discovery strategies to target an antigen involved in infectious disease—the spike protein of the SARS-CoV-2 virus. We created multivalent nanobodies that bind with high affinity to the XBB spike protein and provide protection against an XBB challenge in mice.

      Overall, this work demonstrates significant progress in the development and characterization of nanobodies specific for complex multimeric antigens. The multivalent nanobodies that we have generated can be used to study amyloid proteins and their involvement in neurodegenerative disease progression and can be further engineered into potent therapies for neurodegenerative or infectious diseases.

https://gatech.zoom.us/j/98028112546?pwd=Z8sNubJKxIZUoaJnJgAaJvsCHex2wo.1

Committee: 

Ankur Singh, Ph.D. (Mechanical & Biomedical Engineering, Georgia Institute of Technology & Emory University) 

Sudhir Pai Kasturi, Ph.D. (Experimental Pathology and Laboratory Medicine, Emory University) 

Antibody-omics for Biomarker Discovery in Vaccinology and Infectious Diseases 

Antibodies play a critical role in the immune response by neutralizing toxins, thereby modulating vaccine response and disease outcome. Their protective effector functions are primarily regulated by the antigen-binding domain (Fab) and the crystallizable domain (Fc). While traditional methods of antibody profiling have successfully applied top-down approaches for mainly Fab analysis indicative of overall isotype titer, the Fc interactions between adaptive and innate immunity remain overlooked. As a result, a poorly defined antibody profile of heterogenous individuals can lead to incomplete conclusions regarding disease state or vaccine efficacy. Thus, the long-term objective of this research was to fully characterize the antibody profile using both top-down and bottom-up approaches in a rapid, cost-effective, and efficient manner for translational applications in biomarker discovery, point-of-care diagnostics, vaccine development, and therapeutics. The first specific aim focused on measuring Fc N-linked glycosylation, which is a common post-translational modification well known for its influence on pro- and anti-inflammatory antibody functionality. Currently, gold-standard methods of glycosylation analysis, such as mass spectrometry, are often sample and time-intensive, which can present a critical bottleneck in biomarker discovery. Here, I systematically validated the use of cost-effective sugar-binding lectins with glycoengineered antibodies for rapid (~2.5hr) high-throughput screening of antigen-specific antibody glycosylation. Ultimately, our established multiplexed antibody-omics platform was expanded for deep biophysical characterization on a broad set of antigen-specific antibodies including isotype, subclass, FcR-binding, and glycosylation analysis. The second specific aim was to apply our robust antibody-omics platform to characterize vaccine and adjuvant efficacy. While the role of adjuvants in improving the immunogenicity of vaccines has long been recognized and developed, maintaining and assessing vaccine efficacy over extended periods continues to be a critical challenge. Here, I evaluated the immunogenicity of two adjuvanted vaccine cohorts: HIV-1 and Onchocerciasis. Univariate statistical analysis indicated an IgG1 and IgG4 polarization in both vaccine studies across adjuvant groups, amongst other unique vaccine/adjuvant antibody correlates of protection. A similar experimental approach, with the addition of complement analysis, was performed in the third specific aim to assess and predict the risk of antibody-mediated rejection (ABMR) from sera of kidney transplant patients. While the chance of experiencing rejection is increased by the presence of donor specific antibodies (DSAs) against human leukocyte antigens (HLAs) on the graft, not all transplant recipients experience rejection. Thus, multivariate LASSO-SVM analysis was performed between ABMR+DSA+ and ABMR-DSA+ patients to elucidate the antibody signatures that led to rejection versus non-rejection. Ultimately, this work provides a foundation for rapid, multiplexed humoral profiling with the potential to screen antibody biomarkers across a range of disease and vaccine efficacy studies.

https://gatech.zoom.us/j/99510868434 

Meeting ID: 995 1086 8434

Michelle LaPlaca, Ph.D.  (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology)

Committee Members:

Brandon Dixon, Ph.D. (George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology)

Ari Glezer, Ph.D. (George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology)

Quantifying glymphatic system efflux and permeability following rmTBI

Traumatic brain injury (TBI) is a leading cause of death and injury that can lead to long-term health problems and decreased quality of life and has been shown to alter glymphatic clearance in preclinical and clinical TBI.     This study aims to measure glymphatic system efflux by measuring brain clearance 24 hours post-injury. Male Sprague Dawley rats were divided into Sham (n = 10) and TBI (n = 10) groups.  TBI animals obtained 3 closed head impacts at a velocity of 5 m/s at displacements 5, 2, and 2 mm in 2-minute intervals. Radiolabeled tracers containing 0.05 μCi of [14C]-inulin carboxyl (5000 Da) and [3H]-sucrose (342 Da) in 5 μL of artificial cerebrospinal fluid buffer (aCSF) were injected into the striatum 24 hours post-injury. Blood was collected at 30, 60, 90, and 120 minutes and the lymph nodes, brains, olfactory bulbs (OBs), nasopharynx (NP), and CSF were extracted at 120 minutes post-infusion. The brains were sectioned coronally into 5 mm sections anterior to posterior (BR1, 2, 3, 4). Samples were solubilized and then counted with a liquid scintillation counter. Results showed a significant increase in [14C]-inulin-carboxyl in the normalized counts of all lymph nodes (p = 0.01) and the superficial cervical lymph nodes (SCLNs) (p = 0.01) for TBI vs. Sham groups, indicating reduced glymphatic flux from the injection site. There were no significant differences in the whole brain or individual brain sections, deep cervical lymph nodes (DCLNs), blood, OBs, NP, or CSF between injured and Sham animals for either [14C]-inulin-carboxyl or [3H]-sucrose. Interestingly, we observed [14C]-inulin-carboxyl in the blood, which was intended to be a brain reference, and little to no [3H]-sucrose for TBI and Sham conditions. There were significant levels of both [14C]-inulin-carboxyl and [3H]-sucrose in the CSF, which suggests preferential glymphatic clearance over the blood-brain barrier (BBB). Additionally, there was low recovery of [3H]-sucrose in the whole animal, suggesting it may have been distributed to an unknown area or possibly excreted through the feces or urine. While we saw little injury effects, this study is only focused on a single time point. Injury effects may be more pronounced at other time points, and further studies looking at other times are needed to have a more concrete model of the efflux routes of the glymphatic system.

Andrés J. García, Ph.D., George W. Woodruff School of Mechanical Engineering, Georgia

Institute of Technology

Thesis Committee Members:

Hang Lu, Ph.D., School of Chemical and Biomolecular Engineering, Georgia Institute of

Technology

Ankur Singh, Ph.D., George W. Woodruff School of Mechanical Engineering, Georgia Institute

of Technology

Synthetic PEG-Maleimide Hydrogel For In vitro Culture of Primary Human

Intestinal Enteroids

Gastrointestinal diseases are becoming increasingly prevalent in developed countries,

stimulating the need for human-specific models of intestinal development and disease that can

recapitulate the structure and function of the gut in vitro. In the past decade, intestinal organoid

technology has advanced in vitro reproduction of intestinal organoids. Enteroids, epithelial

organoids derived from human intestinal tissue, are three-dimensional (3D) structures that can

model the identity, cell heterogeneity, and cell behaviors of the original tissue in vitro. This

makes them a powerful tool for drug screening, disease modeling, and reconstructing damaged

epithelium in conditions like ulcerative colitis.

Current protocols for organoid culture require expansion of intestinal stem cells within

Matrigel, a tumor-derived extracellular matrix (ECM) that exhibits considerable lot-to-lot

variability, poor experimental control, and inability to decouple matrix physical and biochemical

properties due to its ill-defined composition. The reliance on Matrigel for intestinal organoid

culture severely limits their translational potential. This thesis project aims to reduce the

requirement for biologically-derived ECMs to support intestinal organoid culture. To accomplish

this aim, we developed completely synthetic hydrogels presenting ECM-derived adhesive

ligands crosslinked with peptides susceptible to matrix metalloprotease (MMP) degradation to

identify gel compositions supporting the culture of enteroids starting from human tissue-derived

progenitor epithelial cells.

The synthetic hydrogel platforms designed were based on a four-arm poly(ethylene

glycol) (PEG) macromer with maleimide groups at each terminus (PEG-4MAL) and the RGD

integrin-binding peptide. Hydrogel biophysical properties and crosslinker type were key

parameters in engineering a synthetic ECM mimic that supported human ileum enteroids. A

PEG-4MAL hydrogel platform with the protease-degradable crosslinker IPES promoted the best

enteroid emergence and growth compared to Matrigel. In this synthetic matrix, human intestinal

enteroids emerge from single cells and express markers of intestinal stem cells. The modular

design of this synthetic matrix and its ability to support the in vitro culture of enteroids

strengthens the translational potential of this platform for regenerative medicine, disease

modeling, and other applications while reducing the dependency on Matrigel.

https://gatech.zoom.us/j/96045411587?pwd=hZJ6E6XuOEtCbbwiNNXlmgDUBwSDPa.1

Meeting ID: 960 4541 1587

Passcode: 109969

Gregory Sawicki, Ph.D. (Georgia Institute of Technology)

Thesis Committee:

Aaron Young Ph.D. (Georgia Institute of Technology)

Omer Inan, Ph.D. (Georgia Institute of Technology)

Karl Zelik, Ph.D. (Vanderbilt University)

Ajit Chaudhari, Ph.D. (Ohio State University)

Joint Loading in Industrial Lifts:  Informing Mitigation Strategies through Joint-Level Biomechanics

             Prolonged exposure to repetitive lifting and twisting under mechanical loading can lead to strain in soft tissues and degradation in bones, especially at the joints. Thus, leaving workers prone to prominent chronic ailments such as lower back pain and osteoarthritis which continue to plague the workforce, with about 50% of reported injuries stemming from the back or knee. Exoskeletons have been shown to reduce net joint loading from external forces and muscle activity in manual tasks. Additionally, wearable sensors (i.e., IMUs, insoles, or EMG) have been shown to be effective at estimating various biomechanical properties such as joint kinetics. Therefore, there is a critical gap to not only understand how internal joint loading manifests across various tasks, but also how wearable technology may affect and inform acute and chronic loading inside of the joint.

Joint contact forces capture the internal force felt by the bone and are largely influenced by muscle forces and external forces. During a daily workload, extreme postures, load carriage, and sudden movements can incite instantaneous and chronic bone and tissue loading, ultimately leading to injury. Exoskeletons are designed to offset net joint and muscle loading by aiding the target joint. However, it is not yet widely understood how they influence forces expressed inside the joint capsule. Joint kinematics, joint kinetics, and muscle activity play an important role in computing joint contact forces through neuromusculoskeletal modeling. We believe that obtaining these biological states from wearable sensors as input to machine learning will provide a mapping of a minimal sensor set to estimate joint contact forces. The near-term objectives of this work were to assess how forces within the joint capsule were influenced using exoskeletons and how to glean insight on joint contact forces for a given task through a minimal set of wearable sensors. My central hypotheses were that 1. exoskeletons can offload the biological muscle and joint effort to reduce joint contact forces in manual tasks, and 2. machine learning technologies informed by wearable sensing systems can reliably estimate joint contact forces across manual and dynamic tasks.

I leveraged EMG to measure muscle activity and neuromusculoskeletal modeling tools to estimate joint contact forces without exoskeleton assistance and with active knee and passive back exoskeletons. Additionally, I used information from IMUs, insoles, and EMG to estimate joint contact forces across various tasks using machine learning. The outcome from these aims provides better understanding of how the use of wearable technologies can modify and inform internal joint loading. Completion of the aims opens the door for future studies to explore how intervention technologies affect external and internal biomechanical and physiological states. Additionally, this work can influence the future design of exoskeletons, controllers, and real-time biofeedback systems.  

https://gatech.zoom.us/j/95381165774?pwd=7HrnH65byztS4ZaTINJSDjIKGjMD4Z.1

Committee:

M.G. Finn, Ph.D.                              (Chemistry and Biochemistry, Georgia Institute of Technology)

Andrés J. García, Ph.D.                   (Mechanical Engineering, Georgia Institute of Technology)

Rheinallt M. Jones, Ph.D.              (Pediatrics, Emory)

Gabe A. Kwong, Ph.D.                     (Biomedical Engineering, Georgia Institute of Technology & Emory)

Engineering Ingestible Probes for Breath-based Detection of Gastrointestinal Diseases

Gastrointestinal (GI) diseases are a significant healthcare burden and affect 70 million people in the United States. Endoscopic imaging plays a crucial role in the diagnosis and clinical management of many GI diseases, including GI cancers, gastroesophageal reflux disease, and inflammatory bowel disease (IBD). However, its invasive nature deters individuals from recommended testing and hinders its routine use as a monitoring tool. Non-invasive blood and fecal biomarker testing have not superseded endoscopy as the gold standard as they frequently rely on single biomarkers, which offer poor disease specificity compared to diagnostic signatures comprised of multiple biomarkers. Unfortunately, conventional biomarker discovery is an arduous and oftentimes black-box process with many barriers to success. Therefore, this proposal seeks to establish a new paradigm to engineer biomarker signatures de novo for GI disease by leveraging dysregulated glycosidase activities in the GI tract. Thousands of distinct host and microbiome glycosidases catalyze the degradation of carbohydrates and shape the overall intestinal “glycome”. Dysregulated intestinal glycosidase activities contribute to GI pathologies via disruption of host-microbiome interactions, intestinal immunity, and gut barrier function. To harness these activities for breath biomarker production, I will develop a new class of molecular probes that are ingestible and metabolized by pathologic glycosidase activities into volatile reporters that are exhaled and detectable in breath. Probe arrays will be designed so that probes for orthogonal glycosidases are barcoded with volatile reporters of distinct mass (i.e. volatile barcodes). Barcode concentrations in breath will be quantified via mass spectrometry and used to build classifiers of GI disease using machine learning. Altogether, I expect the catalytic processing of barcoded probe arrays by intestinal glycosidases will produce amplified, multiplexed breath signals for detection via simple breath testing. To build this platform, I will establish modular chemistries to synthesize probe arrays (Aim 1), characterize probe pharmacokinetics and breath signals after oral delivery (Aim 2), and develop probe arrays for breath-based detection of GI disease in mouse models of IBD and colorectal cancer (Aim 3).

https://gatech.zoom.us/j/92634639259?pwd=mXOBVUAQ7D7vUWC4nffYOWFZ3G7NOC.1

Committee:

Ravi S. Kane, Ph.D.           (School of Chemical and Biomolecular Engineering, Georgia Institute of Technology)

Susan N. Thomas, Ph.D. (Woodruff School of Mechanical Engineering, Georgia Institute of Technology)

John D. Altman, Ph.D.     (Department of Microbiology and Immunology, Emory University)

Sudhir P. Kasturi, Ph.D.   (Department of Pathology and Laboratory Medicine, Emory University)

Engineering Virus-like Particle Conjugate Vaccines for Enhanced B Cell Responses

Virus-like particles (VLPs) are self-assembling protein nanoparticles that are stable carriers for applications in conjugate vaccine design.  Their durable structure permits the high-density display of antigens imparting enhanced immunogenicity compared to free-antigen counterparts. Previous work has led to a defined VLP glycoconjugate design that achieves high-affinity antibody responses though several features remain unexplored. The modularity of the VLP platform not only permits antigen display but also the conjugation of immunologically interesting molecules to directly assess their influence in vaccine efficacy as well as enable the use of VLPs as a tool to probe fundamental questions about vaccine design. The broad theme of this thesis is to explore new nanoparticle compositions for the optimization of high-affinity antibody responses. Using orthogonal chemical, genetic, and enzymatic methods, this thesis will address the therapeutic relevance of new antigen targets, the immune potential of associating VLPs and adjuvants together, and clarify the relative importance of different helper cell modalities. Each of these aims will contribute to a more thorough understanding of VLP platform properties and how they may modulate the immune response to best achieve the desired humoral response. 

https://gatech.zoom.us/j/8379452691?pwd=RHloZjM0MUQvNEZCdklWaWdCRGZuUT09

Meeting ID: 837 945 2691

Passcode: 118019

Andrés J. García, Ph.D., George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology

Thesis Committee Members

Dr. Cheng Zhu, Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology

Dr. John Blazeck, School of Chemical and Biomolecular Engineering, Georgia Institute of Technology

Dr. Wilbur Lam, Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology

Dr. Jianping Fu, Department of Mechanical Engineering, University of Michigan

Mechanotransduction at Focal Adhesions: Interplay among Force, FAK, and YAP: 

The body experiences a variety of mechanical cues in day-to-day function: compressive and tensile stresses in bone and cartilage to latent mechanical signals from the extracellular matrix (ECM). Mechanical cues drive processes such as cell migration and proliferation. Cells sense mechanical signals via cell-ECM interactions, which are primarily facilitated through focal adhesions (FAs). FAs have 100s of unique components: a few key proteins are vinculin, talin, and focal adhesion kinase (FAK). While FA turnover has been well recognized, how cells translate mechanical signals at FAs into biochemical changes is less understood. Previous work demonstrated that yes-associated protein (YAP), a transcriptional coactivator, responds to changes in adhesive area and substrate rigidity. Deleting essential FA proteins alters YAP activity, and YAP upregulates FA-related genes. Our objective is to further our understanding of cell adhesion by elucidating how cells utilize focal adhesions to translate mechanical cues into biochemical signals. I hypothesize that FAs utilize interactions between vinculin, talin, and FAK and spatially and temporally coordinate FA turnover rates and forces to induce YAP activity. Therefore, as I alter vinculin-talin-FAK interactions, I expect a reduction in YAP activity. As I spatially direct cells to form more focal adhesions across the cell periphery and major axis, I expect to induce an increase in YAP activity. In this thesis, I demonstrated that reducing micropillar area while keeping array stiffness constant, which increases force map resolution, alters cell behavior by reducing cell contractility and spread area. I evaluated the impact of removing talin-FAK and talin-vinculin interactions on YAP activity. Upon removing vinculin, FAK, or talin; impairing FAK or vinculin’s functionality, or abrogating talin-FAK or talin-vinculin interactions, there was a drop in YAP’s nuclear accumulation and transcriptional activity. Lastly, I developed a platform for spatially and temporally directing FAs to monitor FA distribution, number, and cell generated traction forces. This work advances our understanding of mechanotransduction by dissecting the relationship between FAs and YAP, which aids in rationally designing biomaterial therapies for modulating YAP expression to treat cancer and fibrosis.

Zoom link: https://gatech.zoom.us/j/96421964446

Andrés J. García, Ph.D., George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology

Thesis Committee Members

Michael A. Helmrath, M.D.  Division of Pediatric Surgery, Cincinnati Children's Hospital Medical Center

Hang Lu, Ph.D., School of Chemical and Biomolecular Engineering, Georgia Institute of Technology

Asma Nusrat, M.D., Department of Pathology, University of Michigan Medical Campus

Johnna S. Temenoff, Ph.D., Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology

Engineered Synthetic Hydrogel Platform For Human Intestinal Organoids In Vitro Culture And In Vivo Therapeutic Delivery

Human intestinal organoids (HIOs) represent an excellent in vitro model of the human intestine and a promising source for intestinal tissue repair therapies. Major limitations to the clinical translatability of the HIO technology are limited HIO in vitro differentiation reproducibility and the lack of clinically relevant in vivo delivery materials. This thesis project aims to address these challenges by engineering a 2D synthetic hydrogel to support the initial stages of the HIO in vitro differentiation process and engineering a clinically translatable synthetic hydrogel vehicle to support in vivo HIO cell engraftment to the injured intestinal tissue. The objectives of this thesis were accomplished in two aims. In Aim 1, I generated a 2D synthetic hydrogel substrate that can support human induced pluripotent stem cell attachment and support definitive endoderm differentiation. In Aim 2, I engineered a synthetic hydrogel to deliver human intestinal organoids to the injured intestine enabling their engraftment into the intestinal wall. The results of this thesis will provide a foundation for enhanced HIO therapeutic potential and clinically translatable materials to advance the use of HIO in the regenerative medicine field. 

Zoom link: https://gatech.zoom.us/j/99129280007?pwd=Y8Ry5GbusfacOw1xRcyMNfXXSrY8t1.1

Andrés García, Ph.D. (Advisor) (School of Mechanical Engineering, Georgia Institute of Technology)

Edward Botchwey, Ph.D. (Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)

Rebecca Levit, M.D. (School of Medicine, Emory University)

Edward Phelps, Ph.D. (Department of Biomedical Engineering, University of Florida)

Krish Roy, Ph.D. (Department of Biomedical Engineering, Vanderbilt University)

Synthetic hydrogels for islet vascularization and engraftment in the subcutaneous space

Type 1 diabetes (T1D) is a chronic, debilitating disease characterized by the autoimmune destruction of insulin-producing beta cells within pancreatic islets. The gold standard for T1D cell therapy is clinical islet transplantation (CIT), the infusion of islets through the hepatic portal vein. While CIT recipients demonstrate enhanced blood glucose control, the procedure is limited to a marginal subset of T1D patients due to 1) the lack of donor islets and 2) the absolute immunosuppression required to overcome the inhospitable nature of the intrahepatic site. Indeed, an expected >60% loss of islets is expected within three days following transplantation. Thus, there is a significant need to establish an alternative extrahepatic transplant site that supports islet engraftment.

The subcutaneous space is an attractive extrahepatic transplant site for T1D cell therapy given its high clinical potential in terms of surgical accessibility, ease of monitoring, and convenience for replenishment and/or retrieval of therapeutic cargo. However, the unmodified subcutaneous space lacks the necessary vascularization to preserve islets. An elegant, facile strategy to promote vascularization is the biomaterial-mediated delivery of proangiogenic factors such as vascular endothelial growth factor (VEGF). The objective of my project was to engineer VEGF-delivering synthetic poly(ethylene glycol) hydrogels (VEGF-PEG) that promoted islet vascularization, engraftment, and function in the subcutaneous space. My central hypothesis was that VEGF-PEG can be tuned to do so. 

To test my hypothesis, I completed three specific aims. In Aim 1, I employed an in vitro co-culture of rat islets, human umbilical vein endothelial cells, and human mesenchymal stromal cells to screen key hydrogel parameters – namely, polymer density, tethered VEGF concentration, and adhesive peptide type – for endothelial cell network formation and islet-network interactions. In Aim 2, I demonstrated that my engineered VEGF-PEG platform supported rat islet survival, engraftment, and function upon subcutaneous delivery in immunocompromised, diabetic mice. Importantly, VEGF-PEG achieved normoglycemia and maintained islet graft function in diabetic mice for 12 weeks, aligning in performance to a leading natural biomaterial platform (islet viability matrix).  In Aim 3, I established a large animal model to evaluate the vasculogenic capabilities of engineered biomaterials. In healthy, nondiabetic Yucatan miniature pigs (n = 5), I demonstrated that a VEGF-PEG coating induced vascularization and local perfusion in the porcine subcutaneous space without detrimental health effects. I then successfully delivered neonatal Yorkshire pig islets in VEGF-PEG to an immunosuppressed, nondiabetic Yucatan miniature pig.

My work has resulted in an optimized synthetic hydrogel for islet vascularization, engraftment, and function in the subcutaneous space. My three-pronged, multi-model approach (in vitro co-culture of cells - in vivo studies in rodents - in vivo studies in pigs)  has provided a novel, logically translational strategy to engineer vasculogenic materials. This work provides a foundation for future studies in a translational, diabetic large animal model – recapitulating the human subcutaneous space more so than preclinical rodent models that comprise majority of the field.

Committee:

John Blazeck, Ph.D. (School of Chemical and Biomolecular Engineering, Georgia Institute of Technology)

Hang Lu, Ph.D. (School of Chemical and Biomolecular Engineering, Georgia Institute of Technology)

Ravi Kane, Ph.D. (School of Chemical and Biomolecular Engineering, Georgia Institute of Technology)

Richard M. Murray, Ph.D. (Division of Biology and Biological Engineering, California Institute of Technology)

Next-Generation Biosecurity: Advancing Tools for Multi-Layer Security

The rapid expansion of synthetic biology from laboratory spaces to industrial and healthcare sectors has brought about concerns of unwanted release of genetically modified organisms and protection of biological intellectual property. Current physical and operational security measures for these assets can be comprised by theft or accidental release. This thesis proposes the designing, building, and testing of a next-generation biosecurity system that is intrinsic to the engineered organism. While prior studies have demonstrated basic intrinsic security measures, there is considerable value in advancing the state of the art with novel tools, multi-layer security platforms, and the introduction of penetration testing. First, an 8-digit biological keypad will be developed in Escherichia coli for 2-input and 3-input passcodes to protect a biological asset. This technology will be combined with toxin-based penalties to design a first-of-its-kind Biohackathon challenge. Furthermore, a novel ‘Command Center’ for editing biological programs will be shown in situ using an engineered E. coli strain. The Command Center would be a promising tool for biosecurity applications. Finally, an authentication system will be engineered through synthetic auxotrophy, and will be deployed with other biosecurity measures to a design a second Biohackathon challenge. Together, these technologies will establish a foundation for integrating multi-layer biosecurity into biotechnology.

Shuichi Takayama, PhD (co-advisor) (Georgia Institute of Technology)

Valeria Milam, PhD (Georgia Institute of Technology)

3D FIBRIN MICROGEL SYSTEM FOR SENESCENSE DETECTION

With the scientific advances and improvements in quality of life over the past century, the percentage of the aged population has been steadily increasing. With age comes a multitude of age-related diseases including cardiovascular disease, hypertension, cancer, osteoporosis, Alzheimer’s disease, and more. One of the 12 hallmarks of aging, cellular senescence, has been directly linked to age-related pathologies. Treatment of cellular senescence via senolytics is a growing niche in aging research, due to the promise it shows in managing senescence accumulation and age-related diseases. Despite growing use of 3D systems in research, there is a lack of models for age-related drug screening. This thesis aims to refine a bio-printed fibroblast-containing fibrin gel model for the detection of cellular senescence. This fibrin microgel model closely mimics the early stages of wound healing, where clot formation occurs, and is subsequently degraded by a process known as fibrinolysis. First, we sought to establish reproducibility in the system. Gel parameters were studied to determine their relationship with an established readout of fibrinolysis time, and ways to reduce variability in the system were investigated. Second, different methods of senescence were tested to determine sensitivity of the fibrin gel model to cellular senescence. Comparing the effects of multiple forms of senescence in the model is necessary due to different pathways of senescence activation and potential differences in senescence associated secretory phenotypes (SASPs). Overall, the work accomplished in this thesis could help establish a novel marker for rapid cellular senescence detection and a tool for senolytic drug discovery and screening.

Committee:

M.G. Finn, Ph.D. (School of Chemistry and Biochemistry, Georgia Institute of Technology)

John Blazeck, Ph.D. (School of Chemical and Biomolecular Engineering, Georgia Institute of Technology)

Julie Champion, Ph.D. (School of Chemical and Biomolecular Engineering, Georgia Institute of Technology)

Jihoon Kim, Ph.D. (School of Integrative Engineering, Chung-Ang University)

Surface-tunable nanoparticles for studying lymphatic delivery dynamics

The properties of drug delivery vehicles are often modulated to better overcome biological barriers and enhance the delivery of bioactive molecules to their intended target, such as immunotherapeutic delivery to mediate the immune response to disease. In this presentation, I will describe my work in engineering the surface properties of poly(propylene sulfide) nanoparticles to modulate their transport behaviors and enable novel drug delivery dynamics and mechanisms. Using in vitro models recapitulating subcutaneous drug administration and uptake into the lymphatic system, the nanoparticle architecture and transport properties were characterized in the context of the copolymer properties comprising the nanoparticle surface. Furthermore, the nanoparticle surface was functionalized to display two reactive groups capable of conjugating two distinct antibodies in controlled ratios, enabling complex interactions with lymphocyte surface receptors. Additionally, a light-responsive cleavable linker will be used to form a photoactivatable fluorescent tracer able to evaluate nanoparticle delivery dynamics within the lymph node. This proposal enhances nanomaterial tools to evaluate nanoparticle delivery across different biological barriers in support of immunotherapeutic delivery to modulate the immune response.

*This will be an in-person event.

ABSTRACT
Periods of accelerated discovery can be defined by the technologies that are created and their costs. Almost all of us are familiar with the story about semiconductors, integrated circuits, and Moore’s Law. The development of this compute technology has placed what would be building-sized supercomputers from the 1980s into simple, handheld devices in the 2020s. However, many may not be familiar with the story of the development of genetic analysis systems in the first decade of this century by a startup called Illumina. This startup has transformed genetic analysis by first creating the leading genotyping platform and then developing the dominant next-generation sequencing (NGS) platforms.

There are many factors that contribute to the successful development of these platforms, such as corporate culture, strategic vision, technology management and product development. We will focus on some of these factors and how they were used to develop products that have transformed biological analysis. We will also discuss how discoveries enabled by these scalable technologies have created new clinical applications and avenues of research. The high specificity and tunable sensitivity of NGS have enabled the development of non-invasive prenatal testing, cancer therapy selection and detection of residual disease from blood samples. The low-price points in these technologies have created markets in consumer genomics, forensic genealogy, and population-scale whole-genome sequencing.

The current period of accelerated biological discovery is being driven by robust genetic analysis tools, accessible compute infrastructure and low price.

BIO
Richard Shen, Ph.D., is an innovator, investor, and business executive. He has over 25 years of experience in the genomics and molecular diagnostics markets. He is active in the investment community as part of NuFund in San Diego and is managing director of RS Technology Ventures, LLC. He is currently on the Board of Directors of public and private companies in the liquid biopsy and diagnostics markets.

Richard held many senior executive positions in his career. Most recently at PacBio he was Sr. Vice President of R&D, responsible for software and bioinformatics, applications, and platform development. Prior to that he was President of Omniome, a start-up that developed a high-accuracy Next Generation Sequencing (NGS) platform. In the year 2000, Richard joined a startup that was Illumina. In his 16-year career at Illumina, he was responsible for scaling and running operations, development of the genotyping and NGS platforms and Oncology R&D.

Richard holds several key patents in the fields of nucleic acid analysis and sequencing. One of his patents enabled the development of a process to sequence the human genome for less than $1,000.

Richard is an alumnus of UCLA (B.S.) and LSU Medical Center (Ph.D.). He did postdoctoral fellowships at University of Michigan Medical Center to study gene therapy and Lawrence Livermore National Laboratories to study variation in DNA repair genes. Richard is a certified director from the UCLA Anderson School of Management.

BIO
Ricardo Cruz-Acuña is an Assistant Professor of Cancer Engineering in the College of Dental Medicine at Columbia University Irving Medical Center. In his lab, Cruz-Acuña focuses on integrating aspects of biomaterial engineering, cell and molecular biology, and 3D organoid biology to (1) understand the contributions of the extracellular matrix properties to tumorigenesis, and (2) identify mechanisms important for epithelial developmental patterning and organogenesis. His work will help elucidate how cancer progresses within a dynamically evolving extracellular matrix that modulates every behavioral facet of the tumor cells, and will reveal novel mechanisms that drive human organ development.

Cruz-Acuña completed his Ph.D. in Bioengineering at the Georgia Institute of Technology under the supervision of Andrés J. García, Ph.D.. Cruz-Acuña then joined the laboratory of Anil K. Rustgi, Ph.D. at University of Pennsylvania and at the Herbert Irving Comprehensive Cancer Center in Columbia University Irving Medical Center for his postdoctoral research training.

In addition to several awards he received during his training, Cruz-Acuña is the recipient of a NIH/NIDDK K01 Research Scientist Development Award (2023). He is a member of the American Association for Cancer Research (AACR) and the Society for Biomaterials (SFB).

Open to all Bioengineering Students and Faculty!

AGENDA

9:30 a.m.        Coffee Corner
10:00 a.m.      Outstanding Advisor and Thesis Presentation
11:00 a.m.      Alumni Presentations
12:00 p.m.      Outstanding Paper Presentation and Lunch
12:30 p.m.      Rapid Fire Presentations
2:00 p.m.        Alumni Panel
3:00 p.m.        Awards and Ice Cream - Bioquad
4:30 p.m.        Adjourn


 

Dr. Cheng Zhu, Ph.D. (BME, Georgia Institute of Technology & Emory)

Committee:

Dr. Edward Botchwey, Ph.D. (BME, Georgia Institute of Technology & Emory)

Dr. Nicole Schmitt, M.D. (Department of Otolaryngology, Emory University)

Dr. Karmella Haynes, Ph.D. (BME, Georgia Institute of Technology & Emory)

Dr. John Blazeck, PhD. (Chemical & Biomolecular Engineering, Georgia Institute of Technology)

Mechanisms of impaired T cell antigen sensing in TP53 mutation expressing cancers, and the co-agonist effect of Wild Type (WT) p53 self-antigen

Immunotherapy is becoming increasingly more popular as a treatment option for cancer, especially in patients with chemotherapy resistant tumors. Although immunotherapy has been highly bought into as a treatment option for cancer patients, product efficacy is low. Taking interest in the rising occurrence of head and neck squamous cell carcinoma (HNSCC), consider anti-PD-1 (α-PD1), for example. α-PD1 is an FDA approved ICB treatment for metastatic HNSCC, but a marginal percentage of patients respond to treatment. Immunotherapies such as α-PD1, provide a future in cancer therapy that aims to reduce the toxic side effects of chemotherapy, however, further insight into TME immunosuppression is required to improve the efficacy of these treatment methods.

To advance the knowledge of TME immunosuppression, this study will focus on cytotoxic T cells, as they are integral in tumor clearance. CD8+ T cells are presented antigens in a histocompatibility complex (MHC) manner. The T cell receptor (TCR) forms a bond with the epitope presented in the binding groove of the major histocompatibility complex (pMHC). T cells exert endogenous forces on TCR–pMHC bonds to amplify antigen sensing. To bind pMHC, TCR experiences a conformational change. In the inactive TCR conformation, cholesterol binds the TCRβ subunit to allosterically regulate its function. Manipulation of cholesterol may enhance the anti-tumor immune response of cytotoxic T cells by unknown mechanisms. Recently, our lab demonstrated melanoma TME induces impaired T cell antigen response. We aim to expand these findings to determine if impaired TCR antigen recognition is conserved in other cancer types, test whether targeting cholesterol can restore TCR antigen recognition, and to identify TME immunosuppressive factors that may be contributing to this apparent loss in function. It is hypothesized that reduced TCR antigen response will be seen in other cancer types and can be recovered through cholesterol inhibition.

TCR based precision adoptive cell therapy has also demonstrated potential as a treatment option for cancer patients with tumors expressing tumor suppressor protein TP53 gene mutations. Still, extensively more work needs to be done to better characterize the TCR tumor antigen (neoantigen) response and improve clinical outcomes. We aim to advance the understanding of p53 mutant reactive TCRs and make contributions towards the development of parameters needed to determine their efficacy in ACT. Studies on ACT and other forms of immunotherapy suggest that TCR affinity, force, and downstream signaling are critical for optimal T-cell function and anti-tumor immune responses30.  We aim to explore differences in the affinity, signaling and mechanosensing of 5 patient-derived, R175H hot spot mutant reactive, TCRs to self vs. mutated ligand. We hypothesize that non-stimulatory wild-type (WT) p53 peptide will enhance binding of TCR to antigen via CD8.

• Dr. Lily Cheung (Ph.D. Advisor, Chemical Engineering, GT )

• Dr. Hang Lu (Chemical Engineering, GT)

• Dr. Mark Styczynski (Chemical Engineering, GT)

• Dr. John Blazeck (Chemical Engineering, GT)

• Dr. JC Gumbart (Chemistry and Biochemistry, GT)

Exploring the Oligomerization of Sugar Transporters for the Advancement in Plant Systems and Synthetic Biology 

Plant SWEET proteins play a pivotal role as sugar transporters, contributing to crucial processes in plants such as reproduction, stress resistance, and sugar distribution. This thesis proposal will investigate the oligomerization of these key membrane transporter proteins, aiming to unravel their complex emergent functions. By understanding these functions, the goal is to pioneer the engineering of sugar transporters with novel capabilities. Employing advanced characterization techniques, including native mass-spectrometry and fluorescence-based assays, this study aims to accurately quantify the stoichiometry of SWEET oligomers in both Arabidopsis thaliana and yeast heterologous expression systems. Furthermore, the research will establish a comprehensive quantitative model to describe sugar transport dynamics for the oligomeric transporters and their individual subunits. Emphasis will be placed on SWEET proteins associated with plant reproduction to create synthetic sugar pumps designed to enhance sugar allocation to endosperm tissues. Through this interdisciplinary approach, the study seeks to delineate the specific impact oligomerization has on sugar transport across plant membranes, thereby informing the intelligent engineering of plant sugar distribution mechanisms for advancements in agricultural productivity and food security. 

Todd Sulchek, PhD (Advisor)

Sunil Raikar, MD

Gabe Kwong, PhD

James Dahlman, PhD

Wilbur Lam, PhD

A Biomechanics-Based Delivery Strategy To Primary Immune Cells For Generating Cell Therapy With Multiple Gene Knockout

 Abstract: Adaptive T cell therapy has emerged as a promising strategy in cancer treatment, utilizing synthetic receptor modified T cells to specially target tumor antigens. Despite successes, challenges persist, including the need for multiplexed gene editing in production of allogeneic T cell product, expanding application to T cell malignancies, and overcoming T cell dysfunction. These challenges require new technologies that lead to safer and efficient multiplexed gene editing techniques to lead to improved therapies. Currently, multiplexed gene editing is performed in one process step, raising concerns regarding chromosome translocations. This thesis addresses safer and more efficient multiplexed gene editing by leveraging the innovative microfluidic volume exchange for cell transfection (VECT) platform. To achieve efficient and reproducible delivery of gene editing cargo to primary T cells, we propose to understand device and intrinsic cellular attributes that significantly impact delivery outcome. Then, we design optimal devices for sequential gene editing of primary T cells in CAR (Chimeric Antigen Receptor) T engineering pipeline, focusing on the reduction of chromosomal translocation. We hypothesize sequential multiplexed gene editing results in lower chromosomal translocation and improved T cell persistence. This study addresses the goals through 3 aims. Aim 1 focuses on identifying critical design elements (CDEs) for VECT devices, revealing device design and operational factors influencing delivery to primary T cells. Aim 2 demonstrates VECT's capability in functional Cas9 delivery and sequential gene editing of CAR T cells. Aim 3 focuses on intrinsic cell mechanics to reveal cell biomechanics' contributions to delivery efficiency. In completing the study, we created two easy fabrication methods to reproducibly generate high delivery to T cells, Then, we demonstrated an application of VECT to deliver CRISPR/Cas9 to mediate gene editing in T cells. VECT was shown to be capable of generating highly efficient and viable TCR and B2M knockout T cells in both batch and sequential workflow. Importantly, VECT sequential editing is shown to reduce the frequency of chromosomal translocations. Interestingly, we identified a combined effect of strain rate and acceleration to significantly improve delivery; and identified cell stiffness as an intrinsic determinant of delivery efficiency. Overall, this study underscores VECT's potential in industrial-scale multiplexed gene editing of T cells with improved safety profile.

Dr. Craig Forest (Mechanical Engineering, Georgia Institute of Technology)

Dr. Matthew Rowan (Biological Sciences, Emory University)

Committee Members:

Dr. Annabelle Singer (Biomedical Engineering, Georgia Institute of Technology)

Dr. Bilal Haider (Biomedical Engineering, Georgia Institute of Technology)

Dr. Christopher Rozell (Electrical and Computer Engineering, Georgia Institute of Technology)

Automated cellular electrophysiology to investigate the role of interneurons in Alzheimer’s disease

Alzheimer’s disease (AD) is a progressive neurodegenerative disease, accounting for about two thirds of dementia cases. Despite significant efforts to diagnose and cure AD there are still no effective therapeutics to halt disease progression. While the conventional understanding attributes memory loss to the buildup of amyloid and tau proteins, emerging evidence suggests that cognitive decline in AD may stem from neuronal circuit dysregulation rather than protein aggregation. Specifically, alterations in the excitability of inhibitory interneurons may contribute to circuit dysfunction, although the evolution of this dysregulation across brain regions and over time remains poorly understood. To address this gap, this thesis systematically investigated the emergence of parvalbumin interneuron dysfunction in AD, confirming their early involvement in vulnerable brain regions.

To study these PV interneurons at the single cell level, with sufficient spatial and temporal resolution, this thesis will utilize patch clamp electrophysiology. The patch clamp technique is remains necessary for fully elucidating cell-type-specific behavior, although it is difficult and time-intensive. While patch clamp systems have emerged that automate certain aspects of the procedure, there remain challenges that can be remedied with improved automation techniques. To overcome these obstacles, several strategies have been developed to improve the whole-cell success rates and facilitate the execution of automated, high-throughput investigations. In the initial identification of cells within acute brain slices, a deep learning methodology automatically nominate neurons for subsequent automated experiments. Addressing concerns regarding pipette localization errors, a convolutional neural network, specifically ResNet101, has been adapted and trained to autonomously detect and rectify the misplacement of pipette tips during automated in vitro patch clamp experiments. Furthermore, to facilitate investigations into synaptic connections between neurons, a method named patch-walking was demonstrated in brain slices, enabling efficient finding of synaptic connections.

Committee

• Dr. Wilbur Lam (Ph.D. Advisor, Biomedical Engineering, GT & Emory)

• Dr. Anant Madabhushi (Biomedical Engineering, GT & Emory)

• Dr. Paynabar Kamran (Industrial & Systems Engineering, GT)

• Dr. Eva Dyer (Electrical and Computer Engineering, GT)

• Dr. David Myers (Biomedical Engineering, GT & Emory)

Unraveling Hidden Heterogeneity: Quantitative Characterization of Cellular Heterogeneity

in Multicolor Flow Cytometry Data for Enhanced Insights

Varying health outcomes present a significant challenge in medicine. At the biological and microscopic level of human health, cells are the smallest functional with diverse functions, undergoing dynamic changes over time and exhibiting unique variations among individuals.

Understanding this intra- and inter-individual cellular diversity, and its impact on health is crucial for the implementation of personalized medicine. Multicolor flow cytometry is the most established single-cell technology, providing multi-parametric information about each cell's protein profiles. It has facilitated the discovery of cellular subpopulations and biomarkers for health and disease. However, current analyses of multicolor flow cytometry data fail to fully

capture multifaceted representations of cellular heterogeneity. The focus on population averages and frequencies neglects the amount, shape, and direction of cellular heterogeneity, which may collectively indicate various forms of cellular heterogeneity with biological and clinical significance. Yet, the lack of quantitative definitions for these aspects hinders objective analyses of their contribution to health. This research proposes and evaluates quantitative metrics to capture previously under-appreciated aspects of cellular heterogeneity in multicolor flow cytometry data. It first examines the biological significance of cellular heterogeneity in healthy platelets, elucidating its translation into functional diversity at the population-level in hemostasis and thrombosis. Subsequently, it investigates the clinical relevance of cellular heterogeneity in peripheral blood mononuclear cells (PBMCs) to understand the role of immune cell heterogeneity in the manifestations of long COVID. By providing a new quantitative lens to uncover hidden aspects of cellular heterogeneity, the proposed methods offer a more holistic understanding of cellular variability. Serving as biomarkers to establish the reference of homeostatic forms of cellular heterogeneity, the proposed metrics can be used to diagnose and monitor diseases and guide the design of tailored therapies. Ultimately, these metrics reveal “hidden heterogeneity”, which will help better resolve and manage inter-individual differences in disease manifestations and therapy responses, advancing personalized medicine.

Francisco E. Robles, Ph.D. (Georgia Institute of Technology and Emory University) 

Committee Members:  

Ahmet F. Coskun, Ph.D. (Georgia Institute of Technology and Emory University School of Medicine)   

Peng Qiu, Ph.D. (Georgia Institute of Technology and Emory University)  

Thomas K. Gaylord, Ph.D. (Georgia Institute of Technology)   

Wilbur A. Lam, M.D., Ph.D. (Georgia Institute of Technology and Emory University School of Medicine)   

Label-free Deep-Ultraviolet Microscopy: Accessible Molecular Imaging from Bench to Point of Care

Imaging with ultraviolet (UV) light (~ 200 - 400 nm) enables label-free molecular imaging due to the distinctive absorption and dispersion properties of several physiologically important, endogenous biomolecules in this spectral region. In addition, the shorter wavelength of UV light offers higher spatial resolution than conventional imaging systems that use visible light. Furthermore, advances in UV light sources and detectors have resulted in setups that enable contiguous imaging of live cells over long durations without significant photodamage.

This work aims to enhance the capabilities of deep-UV microscopy for accessible imaging of biological samples. Initially, we introduce a simple hyperspectral UV microscopy technique to extract quantitative absorption information from biological samples without prior knowledge of their optical properties. Following this, we employ multi-spectral deep-UV microscopy to quantify hemoglobin in red blood cells. Subsequently, we leverage recent advances in deep learning to develop an automated pipeline for label-free hematology analysis using single-wavelength UV microscopy images. In conjunction with a compact deep-UV microscope and custom microfluidic devices, this work can enable low-cost, efficient, and label-free hematology analysis within minutes, suitable for clinical, at-home, or low-resource settings. Additionally, we explore the development of a multispectral UV microscope for high-resolution, 3D tomographic imaging of cells.

Overall, this dissertation advances UV microscopy through improved instrumentation, analysis, and computational reconstruction, establishing it as an effective and economical label-free imaging tool for research, clinical, and point-of-care applications. We anticipate that the high-resolution molecular and structural information obtained from UV microscopy will further our understanding of fundamental biology and aid in disease diagnosis, monitoring, and treatment planning.

Eberhard O. Voit, Ph.D. (Ph.D. Advisor) (Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech and Emory University; Department of Biological Sciences, University of Texas at Dallas)

Qiang Zhang, M.D., Ph.D. (Co-Advisor) (Gangarosa Department of Environmental Health, School of Public Health, Emory University)

Dr. Melissa L. Kemp, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)

Peng Qiu, Ph.D. (Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University)

Mark Styczynski, Ph.D. (School of Chemical and Biomolecular Engineering, Georgia Institute of Technology)

Assessing the Impact of Dioxin on Human Health through Mathematical Modeling

Biological systems are organized in distinct but connected layers, which makes their analysis a challenge. The higher layers usually correspond to a “big picture” of a physiological event, whereas the lower levels account for increasing granularity and detail. It is infeasible to carry along all details from lower levels, partly for technical reasons, but also because they would overwhelm insights at the higher level due to their sheer numbers and the fact that they typically run on much faster time scales.

              This work addresses the well-known challenge of biomedical multiscale analysis with a novel adaptation of the Template-and-Anchor (T&A) modeling paradigm. It considers a template as a high-level, coarse-grained model that focuses exclusively on the main physiological components of a system and involves correspondingly few variables, processes and parameters. The template contains as variables the anchor models, which are modules of component sub-systems that provide more elaborate descriptions of specific biological details. This conceptual framework does not attempt to capture simultaneously all details within a single computable structure as many other multiscale models do. Instead, the often-overwhelming multilevel task is dissected into smaller, stand-alone models that are analyzed separately. This new adaptation of the T&A approach offers substantial advantages without losing resolution. First, the divide-and-conquer method enhances computational efficiency. Second, unlike other methods, each anchor is analyzed individually, producing a record of crucial input-output relationships that are ultimately used in the template model. Third, anchor models can be replaced with alternative representations without affecting the structure of the template or other anchors. Fourth, the T&A model provides flexible guidelines for its setup and for defining variables across scales. 

Using the T&A approach, this work addresses the health implications of exposure to dioxin (specifically, 2,3,7,8-tetrachlorodibenzo-p-dioxin), a persistent organic pollutant which can severely affect health, depending on the magnitude of exposure. The template captures the overall effects of dioxin on the dynamics of cholesterol, a prominent target of dioxin. The anchor models serving as variables in the overall template model include hepatic cholesterol biosynthesis (via the mevalonate pathway), lipoprotein metabolism, and estrogen synthesis. The creation and combination of anchor and template models enables a holistic evaluation of the impact of dioxin, which can be translated into a tool for comprehensive computational health risk assessments.

              On the theoretical side, this work discerns fundamental differences in the conceptual set-up of templates and anchors which may be viewed as dual structures of each other, as the variables in anchor models are material quantities, whereas the variables in template models are processes. T&A modeling, and multiscale modeling in general, hold promise for a deeper understanding of complex systems and for advancing personalized medicine and risk assessment, interspecies translation, and the development of virtual clinical trials.

Committee Members:
Stanislav Emelianov, PhD (Georgia Institute of Technology)

M. G. Finn, PhD (Georgia Institute of Technology)

Eric J. Sorscher, MD (Emory University School of Medicine)

Jason R. Spence, PhD (University of Michigan)

Human Airway Organoids with Reversed Biopolarity: Implications for Infectious Disease, Drug Discovery, and Pathophysiology

Organoid research is exploring a new niche: apical-out organoids. These engineered structures, characterised by their outward-facing apical membrane, offer unique and exciting avenues for research. This dissertation introduces human airway organoids with reversed polarity (AORBs) and demonstrates their potential in studying infectious diseases, drug discovery, and pathophysiology, with a specific focus on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and bronchiolitis obliterans syndrome (BOS). First, we successfully established a robust and optimised standard operating procedure (SOP) for generating AORBs from human primary upper airway epithelial cells, building upon a previously described minimal extracellular matrix (ECM) scaffolding method. The resulting AORBs were cultured free-floating in a high-throughput, single-organoid-per-well format. Single-cell RNA sequencing confirmed the in vivo-like cellular heterogeneity of AORBs, validating their close resemblance to natural airway physiology. Next, we demonstrated the utility of AORBs as a platform for SARS-CoV-2 infection and antiviral drug screening. AORBs supported efficient infection by five SARS-CoV-2 variants, while enabling high-throughput screening, effectively identifying false negatives and false positives. Furthermore, the SOP was refined to develop a tri-culture organoid model, integrating airway epithelial cells, fibroblasts, and peripheral blood stem cells, with the objective of addressing the lack of a human model and the limited translatability of existing animal models in studying BOS pathogenesis. By manipulating human leukocyte antigen matching between epithelial and immune cells in vitro, our BOS model can closely recapitulate the clinical condition, facilitating mechanistic studies and therapeutic discovery. Overall, this dissertation establishes AORBs as a versatile and standardised platform for investigating infectious diseases, drug discovery, and pathophysiology of the respiratory system. The standardisation capacity of the developed SOP holds broader implications for standardising organoids, aligning with the recently updated FDA regulation lifting the mandate for animal studies on therapeutic testing.

Saad Bhamla, Ph.D. (ChBE, Georgia Institute of Technology)

Marcus Cicerone, Ph.D. (Chemistry & Biochemistry, Georgia Institute of Technology)

Committee:

Nicholas Hud, Ph.D. (Chemistry & Biochemistry, Georgia Institute of Technology)

Mark Prausnitz, Ph.D. (ChBE, Georgia Institute of Technology)

Francisco E Robles, Ph.D. (BME, Georgia Institute of Technology)

Bringing Universal Diagnostics to the Point-of-Care: Raman Spectroscopy, Sample Preservation, and Machine Learning

Raman spectroscopy (RS) of biofluids such as blood serum, urine, and saliva can diagnose a wide range of diseases such as diabetes, malaria, tuberculosis, celiac disease, cancer, and Alzheimer's. This has been shown on conventional Raman spectrometers costing >$100,000. We are developing a sub-$100 “frugal” Raman spectrometer with comparable sensitivity for broad-based biofluid diagnostics at the point-of-care (POC). We predict that our method will have sufficient signal for many diagnostics in just a 3-minute scan. Unlike Surface Enhanced Raman Spectroscopy (RS), our technique requires no special reagents, allowing the cost per test to drop to almost zero. We will first target tuberculosis (TB), for which such a fast, affordable test, deployed at TB centers, can save nearly 200,000 lives per year by reducing patient loss to follow-up.

In parallel, we are developing a fast, sub-$100 POC sample-drying instrument that enables biofluids to be preserved and transported without a cold-chain. This will enable remote POCs to offer a wider array of diagnostic tests without forcing the patient to travel. Our $60 prototype can dry a 1 mL sample in under 20 minutes where the Labconco Centrivap, a >$20,000 commercial instrument, takes over 5 hours (18x faster).

Finally, we have developed two machine learning techniques for analyzing the metabolomic cell state in Raman microscopy images. We use these to show that Raman microscopy can potentially identify the state of live cells to comparable or better resolution than transcriptomics. One of the techniques, SampleMAP, is of interest to the wider data science community as a dimensionality reduction technique with a significantly enhanced ability to identify clusters in data compared to UMAP.

Automated pipeline for building whole-brain anatomical atlases and comparative analysis of diverse biological factors in C. elegans

Abstract
The roundworm C. elegans offers a unique opportunity as a model organism to develop necessary methodologies for studying head anatomy. Existing approaches, while providing valuable insights, have technical limitations in terms of accuracy, throughput, robustness, and accessibility. This proposal introduces an optimized pipeline to overcome these challenges and explore its application across diverse scenarios. In aim 1, an experimental and computational pipeline will be presented for constructing complete whole-brain data-driven anatomical atlases for N2 young adult worms. In Aim 2, the pipeline will be adapted for comparative studies across various biological factors such as genetic backgrounds and developmental stages, with carefully chosen metrics to understand underlying biology from observed differences. In Aim 3, our standard N2 atlas will be incorporated to address challenges in functional imaging analysis, accompanied by advancements in image processing techniques. This proposed pipeline has the potential to enhance our understanding of C. elegans brain and may contribute to a broader comprehension of nervous systems in other biological organisms.

Committee:

Eva Dyer, PhD – School of Biomedical Engineering, GT

Thad Starnder, PhD – School of Electrical & Computer Engineering, GT

Hua Wang, PhD – Department of Information Technology, ETH Zürich

Reza Sameni, PhD – Department of Bioinformatics, Emory

METHODS FOR GENERALIZED LOW-DIMENSIONAL EEG ANALYSIS
USING TRANSFER LEARNING

Polysomnography (PSG) is a widely used procedure for diagnosing sleep disorders such as narcolepsy and sleep apnea, however its invasive and time-consuming nature make it infeasible for any form of long-term monitoring. It requires patients to sleep in a hospital setting for several nights while their EEG and other vitals are continuously recorded, after which a trained human clinician must manually score every 30-second block in the entire recording. Long-term monitoring of treatment effectiveness or disease progression thus needs to be conducted using less reliable methods such as wrist actigraphy, sleep diaries, or subjective surveys of sleep quality. The lack of effective methods for long-term monitoring is also problematic for longitudinal studies examining the interaction between sleep quality and other pathologies such as Alzheimer's. There is thus considerable interest in automated sleep staging using at-home wearable sensors. 

A problem in developing automated sleep staging algorithms however is the lack of data available for wearable sensors. There is plenty of data available for in-hospital PSG, but very little for wearable sensors, as they aren't normally used in clinical practice. A possible solution however is the use of transfer learning - a method of boosting machine learning performance on one task using data from a similar task. 

In this thesis, we use transfer learning to make several advances in the field of sleep staging with wearable sensors: 1) We test a variety of transfer learning techniques under a variety of conditions and neural network architectures to determine which transfer learning method is most effective. 2) We develop a novel transfer learning algorithm augmenting training data with synthetic EEG generated using electrophysiological models designed to output data resembling that of the targeted wearable sensor. 3) We used transfer learning to develop a sleep staging model specifically designed for use on mild cognitive impairment patients which is far more effective than models trained on healthy subjects. 4) We used transfer learning to automate sleep staging with an experimental in-ear wearable which is far more comfortable and user-friendly than scalp wearables yet achieves superior sleep staging performance to some commercially available scalp wearables. 

Committee: 

Dr. Ankur Singh (School of Mechanical Engineering, Georgia Tech)

Dr. Ahmet Coskun (School of Biomedical Engineering, Georgia Tech)

Dr. Hang Lu (School of Chemical and Biomolecular Engineering, Georgia Tech)

Dr. Rabin Tirouvanziam (Department of Pediatric Infectious Diseases, Emory)

An immune-competent microvascularized human lung-on-chip device for studying immunopathologies of the lung

      Severe influenza affects 3-5 million people worldwide each year, resulting in >300,000 deaths. Standard-of-care antiviral therapeutics have limited effectiveness in these patients where infection severity is driven by an aberrant immune response. In severe influenza, the hyperactive immune system causes acute cytokine storm, cytopenia, and local tissue damage. Current preclinical models of severe influenza, in small animal models and in vitro, fail to recapitulate the human immune response to severe viral infection accurately. Here, we bioengineered a human lung tissue model that represents small airway structures with tissue-resident and circulatory immune cells. The immune-competent lung tissue model comprises of a 3D, perfusable microvascular network underneath a mature, differentiated epithelium at an air-liquid interface.

      With this model, we demonstrate that a conventional lung-on-chip (LOC) that lacks immune cells induces limited cytokine response to severe influenza infection, and while a LOC with tissue-resident macrophages induces significant response in the airway, the presence of both tissue-resident and circulatory immune cells was necessary to elicit a significant airway and interstitial cytokine storm. We demonstrate through extensive microscopy, secretome, and single-cell RNA sequencing analyses that severe flu infection results in significant lymphopenia, extracellular matrix remodeling, and transcriptional shutdown in fully immune-competent lung tissues. Lastly, we highlight the prominent role of stromal-immune interactions in the response to severe influenza infection, with stromal cells participating in both cytokine signaling and ECM remodeling. The introduction of both tissue-resident and circulatory immune cells into this lung-on-chip model allows for investigation into the distinct role of each immune cell type in the initiation and progression of influenza and may shed light on potential therapeutic avenues targeting immune dysregulation.

Committee:

Stephen Balakirsky, PhD – Georgia Tech Research Institute

Fani Bukouvala, PhD – School of Chemical and Biomolecular Engineering, GT

Johnna Temenoff, PhD – School of Biomedical Engineering, GT

Carolyn Yeago, PhD – Institute of Bioengineering and Bioscience, GT

Process Development and Process Analytical Technology Integration for Cell Therapy Manufacturing

Biomanufacturing of cell therapies involves highly complex and labor-intensive processes, where the process parameters and biological variabilities can significantly influence product quality, reproducibility, and therapeutic efficacy of the products. The complexity and largely manual unit operations contribute to product variability and high cost. To address these manufacturing challenges, we designed a digital-twin-enabled closed-loop cell manufacturing platform with automation and feedback controls. This platform integrates process analytical technologies (PAT) to enable deeper process understanding and provide real-time control of process variables. Specifically, we designed bench-scale bioreactors with automated sampling, at-line and in-line monitoring, digital twin-enabled media nutrients estimation, and feedback-controlled feeding capabilities. Human umbilical cord tissue-derived MSCs (CT-MSCs) and T cells were used as the example cell therapy product. At-line glucose and lactate monitoring confirmed the accuracy of the digital twin estimations. Spent media samples and detailed functional characterizations of the MSCs and T cells end-products generated from the automation-controlled bioreactor demonstrated that high expansion and functions of the MSCs and T cells were maintained in these closed-loop bioreactors. Real-time imaging with quantitative oblique back illumination microscopy showed high-resolution images of cells in-process in a dynamic 3D environment. Overall, the digital twin-enabled bioreactor platform reduced costs, labor, time, and, more importantly, perturbations; and could improve yield while maintaining the phenotype and quality of cell therapy products. Our integrated automation system provides a blueprint for multiplexed PAT integration, process optimization, feedback-controlled intelligent automation to enable the discovery, monitoring, and control of critical quality attributes and critical process parameters for cell therapy manufacturing.

Committee Members:

Jennifer E. Curtis, Ph.D. (Physics)

James E. Dahlman, Ph.D. (Biomedical Engineering)

Ravi S. Kane, Ph.D. (Chemical and Biomolecular Engineering)

Mark Prausnitz, Ph.D. (Chemical and Biomolecular Engineering) 

Surface Engineering of Protein Nanoparticles for Intranasal Vaccination

Intranasal delivery of vaccines offers a promising alternative approach to invasive intramuscular injection, with additional benefits such as inducing mucosal antibodies and cellular responses to neutralize pathogens before entering systemic circulation. However, nasal secretions and mucosa are biological barriers that have been shown to inhibit the delivery of antigens and nanoparticles to nasal-associated lymphoid tissue (NALT) and lungs. Protein nanoparticles are composed of proteins at high mass-to-carrier ratio, while allowing for biocompatibility and tunable physiochemical properties. They have been demonstrated to be effective vaccines and drug delivery carriers. The surfaces of these carriers can be decorated with coatings and chemical modifications, which can alter transport and immune responses due to their interaction with biological barriers and cells. In this work, we evaluate intranasal localization of engineered surface-coated protein nanoparticles and assess their immune response following vaccination in murine models. To understand the principles behind modifying nanoparticle surface formulations will assist in improving accessibility to the NALT and delivery of protein-based nanocarriers for non-vaccine intranasal delivery. We screened ovalbumin nanoparticles coated with polyethylene glycol (PEG) and layer-by-layer coating of trimethyl chitosan and CpG oligodeoxynucleotide adjuvants delivered intranasally in murine models and compared to unmodified protein nanoparticles. The localization and biodistribution were observed using non-invasive in vivo imaging and for regional localization and tissues using both flow cytometry and immunohistochemistry. Surface-coated nanoparticles were used for intranasal vaccination in a murine model and characterized for the mucosal antigen-specific response, as well as systemic humoral and cellular responses through antibody titers and T-cell activation. The findings and designs from screening coatings with model ovalbumin nanoparticles were incorporated into influenza antigen nanoparticle formulations.  Two influenza antigens (hemagglutinin and matrix protein 2 - (A/California/07/2009(H1N1)) were used to construct a subunit protein nanoparticle vaccine with surface structure control using bioconjugation. A layer-by-layer (LBL) coating approach was used to survey specific formulation based on their administration route. Overall, our findings indicated that LBL surface formulation improved nasal biodistribution and immune response upon intranasal delivery, highlighting a new nanoparticle formulation for nasal vaccines. 

Dr. Krishnendu Roy (Engineering, Vanderbilt University)

Committee Members:

Dr. Andres García (ME, Georgia Institute of Technology)

Dr. Erik Dreaden (BME, Georgia Institute of Technology)

Dr. Valeria Milam (MSE, Georgia Institute of Technology)

Dr. Susan M. Thomas (ME, Georgia Institute of Technology)

Utilizing Combinatory Adjuvant-Loaded Chitosan-Derived Nanoparticles for a Joint SARS-CoV-2/Influenza Vaccine

In the wake of the SARS-CoV-2 pandemic and the need for yearly vaccination for flu, there is an ever-growing demand for a single vaccine formulation that can target and immunize against both pathogens. While investigation is ongoing for joint vaccine candidates, the current focus has been mainly on the simultaneous administration of separate vaccines rather than a new hybrid vaccine design. In this work, we have designed and synthesized chitosan and chitosan-IAA-based nanoparticles to use as a platform for combinatorial delivery of multiple vaccine-adjuvants together with soluble delivery of flu and SARS-CoV-2 antigens. Specifically, we have used a combination of the TLR9 agonist CpG and the RLR agonist pUUC. In vitro testing in two distinct primary bone-marrow-derived antigen-presenting cell (APC) cultures demonstrated a strong cell-phenotype-dependent cytokine response to these nanoparticle systems. After administering these with SARS-CoV-2 and H5N1 influenza antigens in a dual-vaccine formulation, we confirmed high pathogen-specific antibody titers in serum and BAL fluid. Our results provide further insights into the impact of immune cell phenotype on vaccine responses and show promise for creating a novel joint subunit vaccine for two prevalent pathogens.

Lakshmi Prasad Dasi, Ph.D. (Georgia Institute of Technology)  

Committee:  

Ajit P. Yoganathan, Ph.D. (Georgia Institute of Technology)  

Christopher Breuer, M.D. (Nationwide Children’s Hospital)  

Rudolph Gleason, Ph.D. (Georgia Institute of Technology)  

Scott Hollister, Ph.D. (Georgia Institute of Technology)  

Development and Biomechanical Assessment of Heart Valve Replacements Designed for In Utero Deployment 

      Congenital heart diseases (CHDs) account for nearly one third of all congenital defects. Patients born with complex congenital cardiac anomalies often require heart valve replacements in their lifetimes. Prenatally, attempts have been made to restore biventricular healthy anatomy in utero by balloon valvuloplasty. A lot of patients that undergo this procedure develop re-atresia or re-stenosis, requiring valve replacements. There has been an investigation into providing a permanent solution to heart valve replacements in children using tissue engineering. 'Neo-tissue' develops using the patient’s own cells, and therefore eradicates the susceptibility of severe rejection possessing the ability to grow, repair and remodel. Tissue engineering can be used as a viable tool in the fetal population due to the high regenerative capacity. This study developed a fetal transcatheter pulmonary valve replacement. The overall hypothesis is that improved understanding of the biomechanics of manufacturing and testing of biodegradable materials can help engineer fetal sized tissue engineered heart valves (TEHVs) and guide future transcatheter device interventions. 

      Specific Aim 1 shed light on the stress distributions and stent characteristics of candidate stent designs simulated with four candidate materials (metal and polymeric).  Results showed differences in stress distributions and stent performance metrics (dog boning, foreshortening and recoil) in the three designs. Both metals performed favorably, although polymer performance (due to high elastic modulus) was better suited to current designs. It was also shown that design had a great effect on distribution of high stresses and composite materials need to be explored in the future to combine the advantages of both metals and polymers. Specific Aim 2 developed and tested alternative sutureless valve assembly techniques that can overcome potential premature failure of valves and benchtop tested patterns of leaflet degradation. Results showed that changing the material density in the valve assembly can help control degradation and performance of the valve in vivo. Specific Aim 3 looked at fetal valve hemodynamic performance and downstream fluid profiles in a pulse duplicator and durability in an AWT. Results showed that although performance values differ between prototypes, all performed well individually and durability in a non-degrading medium was high, indicating the possible longevity of valve in vivo. 

      The development of such a TEHV will eliminate the need for repeat interventions and serve as a permanent alternative. Given the few durable options for pediatric patients, this study will improve the feasibility of developing such a device right from the manufacturing to the testing stage. This critical integration of heart valve and tissue engineering may be the first step to the solution that is needed to reverse ventricular hypoplasia and eliminate single ventricle anomalies.