Loss of neurons in the retina underlie many blinding diseases, such as macular degeneration, glaucoma, and diabetic retinopathy. These retinal neurons are not replaceable. The Reh Lab has developed a strategy to achieve functional regeneration of neurons in the adult mammalian retina, but not enough regeneration to restore vision loss. One of the potential limitations to restoring vision is the inflammation that occurs during retinal injury or disease. All mammalian retinas contain microglia, which are the primary immune cells of the nervous system that respond to pathogens, injury, and disease. My goal is to determine how microglia respond to damage-induced regeneration in the retina. After damaging mice retinas with an excitotoxin (NMDA), we induced neuronal regeneration with a proneural transcription factor called Ascl1. Using immunohistochemistry and confocal fluorescence microscopy, I stained various markers that represent different inflammation states of microglia. I quantified microglia and analyzed their response to neural regeneration. Data from confocal fluorescence microscopy revealed that microglia surround newly regenerated neurons and display a variety of subtypes during regeneration. Follow up single-cell sequencing experiments confirmed that these immune cells show a molecular heterogeneity of states. This study provides a better understanding about how microglia function during retinal regeneration. Results from this study can help reveal targets for manipulation to improve regeneration of the retina. Further work can be done to analyze how these microglia behaviors impact regeneration of lost retinal neurons.

The circumgalactic medium (CGM) is a massive reservoir of gas surrounding a galaxy in which density and temperature range several orders of magnitude and contains more mass than the galaxy itself–similar to a cloud engulfing the galaxy. The CGM also plays a substantial role in the life of its galaxy as it will govern the accretion of matter for the galaxy to continue star formation. To better learn about the CGM, many astronomers utilize simulations to test theories by comparing their simulation data with observational data. Yet, current simulations struggle to replicate the CGM and its breadth of properties accurately. This project uses the TEMPEST and Patient0 simulations of Milky Way-type galaxies and a novel analysis method–known as synthetic spectroscopy–to better understand the effects of cosmic rays on altering how the CGM gas is ionized and how cooler CGM gas moves within the cloud. Many simulations tend to omit cosmic ray physics, however, cosmic rays are believed to provide non-thermal pressure support which will change the ionization structure of the CGM. Through our use of synthetic spectroscopy, we extracted column density and velocity information of various ions, such as HI and OVI, from our simulation to generate velocity histograms and plots of column density versus distance from the galaxy. Ultimately, this provided us further insight into the impacts of cosmic rays on setting the ionization and kinematic properties of the CGM which will better inform us on galactic evolution.

Blood clotting plays a heavy contribution to the mortality and morbidity in patients with diabetes mellitus. In blood clotting, the interaction between platelet glycoprotein Ib (GPIb) and blood protein von Willebrand Factor (VWF) is a catch bond, a bond whose lifetime increases under tensile force. Current, identification of this single-molecule behavior of a catch bond is useful but insufficient to understand behavior with multiple molecules known as clusters. It is recognized that patients with diabetes mellitus have higher levels of VWF and GPIb but there is no existing flow assay that accurately demonstrates the difference in thrombosis flow in diabetics. In addition, there is no definitive conclusion on the influences of the amount and geometry of the catch bond between GP1b and VWF in clusters. A recent innovation in the Thomas Lab has developed a DNA origami nanostructure that allows control over the number and spacing of ligands in a cluster, facilitating the study of clusters of catch bonds. I designed a method to quantify the nanostructure-presented ligands on a surface using 96-wellplate reader. This method was used to characterize the effect of cluster size on platelet rolling behavior. The result of the method suggests using quenching low concentration of biotin-4-fluorescein had the highest accuracy and was able to be picked up by the 96 well plate reader. The method allows observation seen in platelet rolling behavior over these surfaces that are cluster-size dependent rather than concentration-dependent. This will introduce a new assay for diabetic studies and further our understand difference in platelets rolling behavior over clusters between diabetic patients and non-diabetic patients.

Understanding the microbial process in the conversion of food waste into methane is necessary to realize the societal need to convert waste into a sustainable energy source. A critical step in the process is the synergistic breakdown of butyrate to methane. My project Food Waste to Energy allows us to mimic the degradation of food waste to isolate the microbial partners responsible for the production of methane. This process is carried out by a syntroph and a methanogen. Although we do not know the specifications of either organism, identification can allow us to improve the way we utilize bio-reactors dependent on food waste to produce clean energy. Each organism has been grown using media designed to allow for their specific development, doubling methane production within four months on average. We are in the process of conducting a dilution to extinction to reduce the contaminating microbes while selecting for the target majority by close observation of the purity of each sample microscopically. We will sequence the genome of each organism to characterize their respective genetic capabilities and identity which we suspect is novel. Activity and growth characteristics will then be studied to understand the growth kinetics when the organisms grow separately and together. Once the organisms are isolated, we look forward to accelerating methane production by selecting mutants that can catalyze the conversion of butyrate into methane. By identifying the organisms responsible for the conversion of butyrate to methane, we can begin to introduce highly productive bioreactors in urban, rural, and manufacturing settings to combat the use of non renewable energy and create energy from the 40 million tons of food waste produced annually in America.

Induced pluripotent stem cells (iPSCs) can be directed to create 3D mini retinas in vitro known as retinal organoids. Retinal organoids recapitulate the developmental timeline of the human fetal retina and have the potential to serve as disease models for a multitude of retinopathies. However, we have observed that retinal organoids contain a disorganized inner nuclear layer and discontinuous lamination hindering their ability to be considered as a comprehensive disease model. The protein β-catenin is produced from the canonical WNT signaling pathway and has been shown to be essential for retinal lamination in mice due to its role in cellular adhesion. I investigated the effects of a canonical WNT signaling pathway agonist, CHIR,  in order to improve the disorganization and lamination of retinal organoids so that we can develop a comprehensive disease model for different retinopathies. We have used three different stem cell lines to construct retinal organoids that I cultured with the addition of the WNT pathway agonist, CHIR. I performed immunohistochemistry staining followed by microscopy analysis and have obtained data that shows an increase in lamination and cellular organization with the addition of the WNT signaling pathway agonist. Our data suggests that the WNT signaling pathway plays a role in maintaining organization and lamination in the developing human fetal retina. 

A simple, but important, measure of the ability of models to simulate cloud properties is whether the vertical structure of cloud occurrence in the model is consistent with that from data. Observed cloud occurrence profiles in the tropical western Pacific typically exhibit three peaks, one near the top of the boundary layer, one near the freezing level, and a broad peak in the upper troposphere. There is considerable variation in the probability of occurrence and the strength of these peaks. Here, we investigate the ability of a new generation of high-resolution models to simulate these profiles. Our study uses Global Storm Resolving Models (GSRMs) from the DYAMOND project. Nine models were run globally for 40 days starting from initial conditions on August 1, 2016. We use two data sources: ground-based data from the Atmospheric Radiation Measurement (ARM) program site in Manus Island, Papua New Guinea and Nauru, as well as data from National Aeronautics and Space Administration (NASA) satellite products (CCCM). Our study consists of a determination of local variability in cloud occurrence profiles. We make use of the ARM data to construct profiles for each August in the data series. The ARM data are available at high frequency at a single location but the monthly average profiles are influenced by local weather variation. The CCCM data are sampled over a broader spatial region but at lower spatial and temporal resolution. These two data sets provide us with an accurate assessment of cloud occurrence and a measure of internal variability. We then compare the profiles from the models. Our results suggest that the models simulate the rough structure of cloud occurrence but that there are large differences in the relative strengths of the peaks among the models and the overall probability of occurrence.