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.

Chronic kidney disease affects millions of people worldwide. Although dialysis offers a temporary treatment for these patients, it cannot effectively remove indoxyl sulfate, a naturally produced uremic toxin which can cause major illness. Our goal is to remove the precursor of indoxyl sulfate, tryptophan, from the small intestine, before it is eventually broken down by the gut microbiome in the colon and circulates as indoxyl sulfate in the blood. We propose a novel method to remove excess tryptophan from the small intestine by utilizing an orally ingested, albumin-encapsulated hydrogel microsphere. Since tryptophan has a high binding affinity for human serum albumin, we can employ albumin encapsulated hydrogel microspheres to remove excess tryptophan from the distal end of the small intestine to prevent the ultimate production of indoxyl sulfate in patients with chronic kidney disease. In this work, we provide in vitro results demonstrating the feasibility of such a system: we show that our hydrogels can remove considerable quantities of tryptophan from solution. We also propose alternative hydrogel formulations to limit the leakage of important components. Finally, we display modeling in COMSOL which can somewhat replicate the diffusion and binding conditions in the gut and discuss its implications in supporting future work.

Endothelial cells (ECs) acquire their identities through interactions with surrounding matrices and parenchyma cells, which in turn guide organ development. Understanding the EC specificity is important for improved engineering outcomes of tissue regeneration and disease modeling. In particular, engineered cardiac patches are being explored as a method to supplement tissue function after a myocardial infarction. Successful vascularization has been a key criteria for host integration and tissue survival, however, heart specific vasculature has not yet been achieved. The Zheng Lab has engineered microvessel networks and seeded them with human embryonic stem cell-derived ECs, finding that the vessels effectively integrated into host tissues and were highly angiogenic. However, limited functional benefit has been shown in these vascularized patches. We hypothesize that this is due to a lack of organ specificity in the microvascular construct because heart microvascular ECs exhibit unique potential and metabolic function. Here I aim to construct a cardiac-specific microenvironment by engineering a hydrogel composed of decellularized myocardial extracellular matrix and Type I collagen to induce cardiac organ specificity in ECs. Gene expression analysis via reverse transcription quantitative PCR and protein expression analysis via immunofluorescence staining were used to quantify organ-specificity. A three-dimensional gel containing cardiomyocytes and ECs with a sharp boundary between the organ-specific hydrogel and Type 1 collagen was used to characterize the biochemical effects of the decellularized matrix. The organ-specific hydrogel was then used as a structural component of a grid microvascular network and seeded with beads to demonstrate that the gel maintains structural integrity under flow. This hydrogel has the potential to be adapted into numerous engineered tissue types by altering the decellularized matrix component, allowing for more physiologically significant studies on the effects of drugs and disease.

Induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) that have been engineered into three-dimensional heart tissues (EHTs) are valuable research tools for investigating debilitating genetic diseases that afflict the heart, such as Duchenne muscular dystrophy (DMD). Ensuring iPSC-CMs can be sufficiently matured to model such diseases remains a hurdle in current research, and maturational analysis techniques for iPSC-CMs are either qualitative, manual, or primarily based in two dimensions, leaving much to be desired. In this project, we created a suite of MATLAB image-processing scripts that can quantify the effect of three-dimensional culture and disease-causing DMD mutations on cardiomyocyte structure and maturation state. The iPSC-CMs were differentiated from stem cells, cast into EHTs, stained using immunofluorescence, and imaged using a confocal microscope. Using the scripts to analyze these 3D images of iPSC-CM stains, key maturational features of the cells can be quantified such as nuclei count; cardiomyocyte area; and sarcomere length, orientation, and z-disk width. Analyzing cardiomyocyte area can give key information on cardiomyocyte hypertrophy while examining sarcomere length, orientation, and Z-disk width can provide information on myofibril structure and organization. The suite allows analysis of these maturational features in both 2D and 3D cultures and offers a method for quantitatively assessing maturation in an automated manner. Measuring iPSC-CM maturation will also allow better comparison of existing maturational methods, such as mechanical loading, electrical stimulation, and small molecule treatment. The suite can also create graphical outputs to elegantly display data. Overall, the suite will help improve maturational analysis of EHTs, and hopefully contribute to the discovery of new treatments for diseases that affect the heart.

Coronavirus Disease 2019 (COVID-19) is caused by infection by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), mediated by the binding of its viral surface spike protein to its cellular receptor, angiotensin-converting enzyme 2 (ACE-2). Antibody-dependent Enhancement (ADE), which occurs when antibodies enhance viral entry, is one of the potential risks for the design of the COVID-19 vaccines. The overall goal of our project is to test a novel mechanism of ADE in COVID-19. The SARS-CoV-2 spike protein can switch between active and inactive conformation with its receptor binding domain (RBD) being exposed or masked. We hypothesize that antibodies that conformationally activate the structure of spike protein will mediate ADE, while those that do not activate it, or even stabilize its inactive conformation, will not enhance viral infection. To effectively characterize the allosteric properties of anti-spike antibodies, we will design two biochemical assays using enzyme-linked immunosorbent assays (ELISA). The “activation assay” detects conformational regulation through the binding of anti-spike antibodies to spike protein in different conformations. We suspect that antibodies that prefer to bind to an activatable over a locked-inactive spike ectodomain are conformational activators. The “inhibition assay” identifies the mechanisms for anti-spike antibodies to inhibit the binding of spike protein to ACE-2. We predict antibodies that inhibit the binding of ACE-2 with isolated RBD are competitive inhibitors, and antibodies that only inhibit the activatable ectodomain are conformational inhibitors. In both assays, the binding effectiveness will be quantified through the effective concentration of antibodies required for half-maximal binding (EC50). With this assay established, the lab’s overall project could move forward to test antibodies’ ability to mediate conformation-dependent ADE, which will provide essential feedback on antibody selection for vaccine development. Finally, these in vitro study results will contribute to the next stage of testing the clinical relevance of “conformation-dependent” ADE.

The spatial distribution and degree of colocalization for two or more proteins, based on their fluorescence intensities, are useful metrics for phenotyping cells and informing on biological function. Yet, most commercial and open-source image analysis tools report global colocalization statistics at the image-level, and offer limited analysis at the individual cell level. To address this, we are developing a python-based image analysis pipeline to quantify robust per-cell metrics of colocalization. Our pipeline stacks image tiff files acquired on high-throughput automated fluorescence microscopes into multichannel 3D image stacks. The images are then restored via deconvolution algorithms, and cropped to remove out-of-focus image planes using Laplacian variance algorithms. For image thresholding and cell segmentation, the pipeline incorporates scripts from the Allen Institute for Cell Sciences to threshold and segment individual cells. Finally, the pipeline calculates per cell colocalization metrics based on the fluorescent intensity of each voxel in each cell. CLARITY was used to quantify the spatial relationships of the peroxisomal biogenesis protein Pex3 with the endoplasmic reticulum protein Sec61 and peroxisomal membrane protein Pmp70. Pex3 colocalized with both Sec61 and Pmp70 and this colocalization could be manipulated by treatment with different kinase inhibitors. In several instances, these differences in localization contributed to a large variance in the measured Pearson’s Correlation Coefficient of cells within the same image. Morphometric analysis showed the volume of peroxisomes per cell negatively correlated with the number of peroxisomes per cell. The automation of per-cell image analysis leveraged in this pipeline will allow for systems-level phenotyping and data mining from fluorescent microscopy images.