Traumatic Brain Injury (TBI) affects approximately two million people on an annual basis and increases the frequency and onset of Alzheimer’s disease (AD) and other related dementias (ADRDs). Mechanical damage and shearing of neuronal axons are thought to be responsible for producing toxic variants of proteins that contribute to disease pathology. Specifically, the tau, beta amyloid, alpha-synuclein, and TAR-binding DNA Protein-43 (TDP-43) variants contribute to the heterogenous pathology mechanisms of neurodegenerative diseases. The Sierks lab at Arizona State University has aimed to study how these protein variants collectively interact to contribute to pathologies characteristic of AD/ADRDs. This study focuses on the accumulation of toxic oligomeric variants of TDP-43 secondary to TBI. The first aim of this study was to identify the protein variant fingerprint as a function time following experimental diffuse TBI. The second aim was to investigate if toxic variants of TDP-43 were associated with cognitive and motor functional deficits. C57BL/6 mice were subjected to a single or repetitive diffuse TBI via midline fluid percussion injury or a control surgery (sham). Post-injury, mice were evaluated for cognitive performance, sensorimotor function, and depressive-like behavior at 7-, 14-, and 28-days post-injury. Tissue was collected for immunohistochemistry and stained for ADTDP-3, a single chain antibody variable fragment (ScFv) which binds to toxic variants of TDP-43 in amyotrophic lateral sclerosis (ALS) and AD tissue. A one-way analysis of variance (ANOVA) was performed to compare staining intensity across various brain regions. Subsequently, a Pearson correlation was performed to compare behavioral task performance to staining intensity by brain region for each injury group. There were significantly elevated levels of ADTDP3 binding in all regions except for the hippocampus, and there was a significant correlation between the cortex staining intensity vs the cognitive behavior test at 7 days post-injury. There was also a significant correlation between the thalamus staining intensity and sensorimotor test at 7 days post-injury. These findings support the hypothesis that the accumulation of toxic variants of TDP-43 can contribute to neurodegenerative pathology and loss of function. These variants also may contribute to behavioral deficits secondary to diffuse TBI.

Alzheimer’s Disease (AD) and Frontotemporal Dementia (FTD) are the leading causes of early onset dementia. There are currently no ways to slow down progression, to prevent or cure AD and FTD. Both AD and FTD share a lot of the symptoms and pathology. Initial symptoms such as confusion, memory loss, mood swings and behavioral changes are common in both these dementia subtypes. Neurofibrillary tau tangles and intraneuronal aggregates of TAR DNA Binding Protein 43 (TDP-43) are also observed in both AD and FTD. Hence, FTD cases are often misdiagnosed as AD due to a lack of accurate diagnostics. Prior to the formation of tau tangles and TDP-43 aggregates, tau and TDP-43 exist as intermediate protein variants which correlate with cognitive decline and progression of these neurodegenerative diseases. Effective diagnostic and therapeutic agents would selectively recognize these toxic, disease-specific variants. Antibodies or antibody fragments such as single chain antibody variable domain fragments (scFvs), with their diverse binding capabilities, can aid in developing reagents that can selectively bind these protein variants. A combination of phage display library and Atomic Force Microscopy (AFM)-based panning was employed to identify antibody fragments against immunoprecipitated tau and immunoprecipitated TDP-43 from human postmortem AD and FTD brain tissue respectively. Five anti-TDP scFvs and five anti-tau scFvs were selected for characterization by Enzyme Linked Immunosorbent Assays (ELISAs) and Immunohistochemistry (IHC). The panel of scFvs, together, were able to identify distinct protein variants present in AD but not in FTD, and vice versa. Generating protein variant profiles for individuals, using the panel of scFvs, aids in developing targeted diagnostic and therapeutic plans, gearing towards personalized medicine.

Alzheimer's disease (AD) is the most common form of dementia leading to cognitive dysfunction and memory loss as well as emotional and behavioral disorders. It is the 6th leading cause of death in United States, and the only one among top 10 death causes that cannot be prevented, cured or slowed. An estimated 5.4 million Americans live with AD, and this number is expected to triple by year 2050 as the baby boomers age. The cost of care for AD in the US is about $200 billion each year. Unfortunately, in addition to the lack of an effective treatment or AD, there is also a lack of an effective diagnosis, particularly an early diagnosis which would enable treatment to begin before significant neuronal damage has occurred.

Increasing evidence implicates soluble oligomeric forms of beta-amyloid and tau in the onset and progression of AD. While many studies have focused on beta-amyloid, soluble oligomeric tau species may also play an important role in AD pathogenesis. Antibodies that selectively identify and target specific oligomeric tau variants would be valuable tools for both diagnostic and therapeutic applications and also to study the etiology of AD and other neurodegenerative diseases.

Recombinant human tau (rhTau) in monomeric, dimeric, trimeric and fibrillar forms were synthesized and purified to perform LDH assay on human neuroblastoma cells, so that trimeric but not monomeric or dimeric rhTau was identified as extracellularly neurotoxic to neuronal cells. A novel biopanning protocol was designed based on phage display technique and atomic force microscopy (AFM), and used to isolate single chain antibody variable domain fragments (scFvs) that selectively recognize the toxic tau oligomers. These scFvs selectively bind tau variants in brain tissue of human AD patients and AD-related tau transgenic rodent models and have potential value as early diagnostic biomarkers for AD and as potential therapeutics to selectively target toxic tau aggregates.

The rheological properties at liquid-liquid interfaces are important in many industrial processes such as manufacturing foods, pharmaceuticals, cosmetics, and petroleum products. This dissertation focuses on the study of linear viscoelastic properties at liquid-liquid interfaces by tracking the thermal motion of particles confined at the interfaces. The technique of interfacial microrheology is first developed using one- and two-particle tracking, respectively. In one-particle interfacial microrheology, the rheological response at the interface is measured from the motion of individual particles. One-particle interfacial microrheology at polydimethylsiloxane (PDMS) oil-water interfaces depends strongly on the surface chemistry of different tracer particles. In contrast, by tracking the correlated motion of particle pairs, two-particle interfacial microrheology significantly minimizes the effects from tracer particle surface chemistry and particle size. Two-particle interfacial microrheology is further applied to study the linear viscoelastic properties of immiscible polymer-polymer interfaces. The interfacial loss and storage moduli at PDMS-polyethylene glycol (PEG) interfaces are measured over a wide frequency range. The zero-shear interfacial viscosity, estimated from the Cross model, falls between the bulk viscosities of two individual polymers. Surprisingly, the interfacial relaxation time is observed to be an order of magnitude larger than that of the PDMS bulk polymers. To explore the fundamental basis of interfacial nanorheology, molecular dynamics (MD) simulations are employed to investigate the nanoparticle dynamics. The diffusion of single nanoparticles in pure water and low-viscosity PDMS oils is reasonably consistent with the prediction by the Stokes-Einstein equation. To demonstrate the potential of nanorheology based on the motion of nanoparticles, the shear moduli and viscosities of the bulk phases and interfaces are calculated from single-nanoparticle tracking. Finally, the competitive influences of nanoparticles and surfactants on other interfacial properties, such as interfacial thickness and interfacial tension are also studied by MD simulations.