Mutations in myosin may lead to severe muscle disorders that greatly reduce the quality of life. For example, the embryonic skeletal myosin (MYH3) mutation R672C leads to Freeman Sheldon Syndrome (FSS), a rare inherited disorder that causes severe contractures at birth. A comprehensive understanding of the relationship between protein structure and function is urgently needed to treat diseases such as FSS. Computational methods, such as molecular dynamics simulations, can be used to examine the effects of mutations on protein structure and function. However, the Protein Data Bank (PDB) is missing most human skeletal myosin heavy chain structures. We employed homology modelling to construct structures of human MYH3. To inform homology modeling, I generated a multiple sequence alignment of 7 human myosin genes. The extent of sequence identity was used to identify the optimum myosin isoforms to use as templates for model generation. For example, MYH3 and MYH7 were the most distinct at 78.93% similarity, which was expected as they are embryonic skeletal and adult cardiac myosin respectively. Specific sequence consensus at each position in the sequence was used to determine the most and least conserved regions of myosin. The cleft region was the most conserved; the N-terminal Domain was the least conserved. I used MYH7, adult cardiac myosin, as a template structure to derive a homology model of the ATP state of MYH3. A structure of MYH3 R672C was generated via in silico mutation of the wild type structure. Molecular dynamics of the resulting structures will be used to explore how R672C, which is located near myosin’s converter domain, alters myosin structure and function. This computational platform will model all phases of the cross-bridge cycle, potentially reveal new drug binding pockets, guide and be validated by in vitro experiments using human induced pluripotent stem cell derived myocytes (hiPSC-Ms).

In the United States, 1.5 million individuals suffer a fracture due to bone disease each year. In addition, there are many unknown mechanisms behind how muscular disorders and mechanical load adversely affect bone development, such as in the disease distal arthrogryposis. Disease research in human cell models has greater translational potential compared to animal models but have faced challenges when constructing highly-specialized tissues such as bone. We propose a novel, three-dimensional bone tissue model as a platform for musculoskeletal disease modeling that allows for compressive loading. By seeding induced pluripotent stem cell (iPSC) derived osteoblasts and osteoclasts in a 3D, porous, hydroxyapatite-coated poly-L-lactide scaffold, we propose to generate a bone tissue model that replicates human tissue in a laboratory. By applying compression to the novel 3D bone tissue model, we expect to observe phenotypes of bone disorders and bone development under mechanical loading. We propose to induce osteoblast and osteoclasts lineage from mesenchymal progenitor cells and hematopoietic progenitor cells, respectively, and co-culture to identify optimal conditions for cell growth. Preliminary experiments have found success in culturing active osteoblasts from iPSC-derived mesenchymal progenitor cells. By screening for markers of cell proliferation, calcium deposition, bone resorption and secretion, the cultures can be assessed for their robustness. In parallel, a porous scaffold will be fabricated by dissolving poly-L-lactide in chloroform and molding over sodium chloride particles. Coating said scaffold in fibronectin and hydroxyapatite will improve cell adhesion and uptake bone secretion. Seeding osteoclast and osteoblasts cells in a porous scaffold will allow for improved cell diffusion and 3D growth, mimicking the human microenvironment. We expect that combining robust, osteogenic tissue culture on a bioactive scaffold that allows 3D bone growth with mechanical loading will reveal phenotypes of distal arthrogryposis. Thus, this method has significant applications in accelerating laboratory findings to clinical research.

The dystrophin protein protects cardiac and skeletal muscle from damage during contraction and relaxation. Mutations in dystrophin lead to Duchenne muscular dystrophy (DMD), an incurable X-linked recessive disease affecting 1 in 3500 boys. Previous work has shown that several cardiac symptoms of DMD can be traced to calcium handling defects. To that end, a preliminary drug screen by our lab identified several L-type Calcium Channel blockers (CCBs) that were able to provide a cardioprotective effect. To conclusively determine the effectiveness of these CCBs, a platform that can accurately replicate physiological cardiomyocytes and screen these CCBs at semi-high throughput is needed. A major limitation with current drug screening platforms is that they use cardiomyocytes equivalent to the fetal heart. This is due to the limitations in current differentiation protocols, which fail to induce further maturity. Because symptoms of most inherited cardiomyopathies are exhibited in mature cardiomyocytes, these platforms are unable to predict drug efficacy accurately. Additionally, microelectrode array (MEA) systems - a system for high throughput drug studies - require highly accurate cell plating to provide good quality results, which requires extensive and costly training. Here, we addressed these issues by developing a novel platform that uses ComboMat, a technique used to enhance cardiomyocyte maturity, and designing an assistive device to plate cardiomyocytes in MEA plates. We showed that our platform with ComboMat-treated cardiomyocytes can give a more physiologically relevant response compared to platforms that use untreated cardiomyocytes. A MEA-based drug study is currently being performed to validate the CCBs identified in the preliminary drug screen. We expect to successfully validate a subset of the CCBs analyzed and further test them in animal models. This project will culminate in creating a novel and cost-effective platform that offers superior prediction of drug efficacy for DMD and potentially other cardiomyopathies as well.

Cancerous cells have a modified metabolism that supports their demands for increased proliferation. One of the essential molecules in cancer cell metabolism and proliferation is the amino acid aspartate. Aspartate is not only incorporated into proteins, but is also a substrate for nucleotides and other amino acids, including asparagine. Aspartate availability can constrain tumor growth rate, and the consumption of aspartate to generate downstream products can alter aspartate levels. One gene that draws from the aspartate pool is asparagine synthetase (ASNS). ASNS converts aspartate into asparagine, which is used in the production of proteins, but does not increase cell proliferation. Thus we hypothesized that ASNS expression and activity can affect aspartate levels. With this, we aimed to determine if ASNS expression could alter aspartate availability and change sensitivity to aspartate suppressing therapies. Since cancer cells express ASNS to varying degrees, my project sought to determine if ASNS expression could be used to identify those cancers that are most amenable to aspartate suppression therapies. To test this I generated cell lines that express ASNS in different ways and treated them with multiple electron transport chain inhibitors. Preliminary results suggest that cells that express ASNS to a higher degree are more susceptible to mitochondrial inhibitors. More broadly, this research sought to better understand the conditions that determine aspartate levels, and how to exploit those conditions to inhibit tumor growth in association with asparagine synthetase.

Aortic aneurysms form when the aorta, the large artery that carries blood from the heart, weakens and expands. Smooth muscle cells (SMC) in the aortic wall regulate aortic structure and contractility and help preserve normal aortic diameter. Transforming growth factor beta (TGF-β) signaling is integral to SMC function and abnormal TGF-β signaling and is implicated in aneurysm formation. However, whether excessive or deficient SMC TGF-β signaling promotes aneurysms is controversial. To determine if increased SMC TGF-β signaling is sufficient to cause aneurysms, we expressed a Constitutively Active Type I TGF-β Receptor (TβR1-CA) transgene in SMC of male and female mice (both hemizygous). Because the transgene is integrated into the X chromosome, and half of female X chromosomes undergo inactivation, expression of TβR1-CA in males and females may differ. This difference could affect the interpretation of studies that investigate the role of SMC TGF-β signaling in aneurysmal disease. We hypothesize that hemizygous females will have lower levels of TβR1-CA expression than males due to random X-inactivation. To test our hypothesis, we will quantify the mRNA levels of TβR1-CA relative to that of Gapdh (a reference gene for normalization) in aortic SMC of male and female hemizygous transgenic mice using real time (RT)-qPCR. To confirm that we can detect X chromosome inactivation using RT-qPCR, we will also measure mRNA levels of a gene that is known to undergo X-chromosome inactivation (Pgk1) and a gene that is known to escape X-chromosome inactivation (Kdm5c). If our hypothesis is correct, we will find that the amount of aortic TβR1-CA mRNA is ~50% lower in aortas of female versus male transgenic mice. The results of this project will be essential in helping us to interpret results of parallel experiments that investigate whether TβR1-CA expression (and activated SMC TGF-β signaling) causes aneurysms in male and female mice.

Humans hear through the conversion of pressure waves vibrating in the inner ear into chemical signals released by activated hair cells. Loss of function of hair cells due to damage can result in permanent hearing loss. Zebrafish are one of the model organisms used to study hair cells, since zebrafish have hair cells similar to humans. Unlike humans, zebrafish can regenerate their hair cells after damage. Regeneration occurs when support cells differentiate into hair cells. Determining how zebrafish support cells differentiate into hair cells is important to understand if human support cells can be induced to differentiate in a similar way. This requires comparing the structural differences between support cells and hair cells. One important aspect of neuronal signaling is the release of calcium ions from the cell’s endoplasmic reticulum (ER). This experiment looked to answer whether the ER in zebrafish hair and support cells was quantifiably different. Since structure mediates function and support cells do not signal to neurons, their ER structure should not be equivalent to the hair cells’. To test this, I manually segmented and reconstructed serial block-face scanning electron microscope (SBF-SEM) images of both cell types’ ER into 3D. Using SBF-SEM as a reconstruction method allowed for more detailed visualization of both the cell volume and the ER, in contrast to other methods such as confocal microscopy. Support cells had an ER volume of 50.51 µm3, while hair cells had an ER volume of 29.09 µm3. Support cells had a higher ER to cell volume and ER surface area to volume ratio than hair cells. It can be concluded that ER structures of support and hair cells are quantifiably different. Quantifying ER differences between support and hair cells is an important step toward discovering solutions to deafness caused by damage to human hair cells.

The Fermilab Muon g-2 experiment seeks to measure the anomalous magnetic moment of the muon to 140 ppb. A highly purified beam of muons is delivered to a magnetic storage ring in bursts of ~15,000 muons called fills. The rate of change of the angle between a muon’s momentum and spin while orbiting in the storage ring is the anomalous precession frequency, which is directly proportional to the anomalous magnetic moment. During each fill, muons orbit in the storage ring until they decay into positrons which spiral into electromagnetic calorimeters stationed around the ring. Positrons which impact the calorimeter deposit their energy in the calorimeters as Cherenkov radiation. The time dependance of the positron energy spectrum is used to extract the anomalous precession frequency of muons in the storage ring. “Early to late effects” are a class of systematic uncertainty in the experiment which result from coherent changes of experimental conditions within each fill. These effects can directly bias the measured anomalous precession frequency. One such effect arose from malfunctioning resistors in the ring’s electrostatic quadrupoles, resulting in non-ideal vertical focusing of the muon beam. This led to coherent downward motion of the beam during each fill. This directly couples into one of the largest systematic effects, as the calorimeter acceptance depends in part on the beam's vertical position. Using data from the calorimeters, I quantified early to late change in the beam’s vertical position and vertical distribution. These results were used to cross-check results from simulation programs. If the Fermilab Muon g-2 experiment retains the same central value as the previous generation measurement but with 140 ppb precision it will be in greater than 5-sigma tension with standard model calculations. Results from Run 1 of the experiment are expected to be published in early 2021.

5-hydroxymethylcytosine (5hmC) is a DNA modification studied in mammalian cells and tissues that has been implicated in embryonic stem cell differentiation, neuronal development, and formation of tumors. However, much is still unknown about the regulatory function of 5hmC and its genomic localization in diverse cell types. Recently, a novel, enzyme-based method was developed for 5hmC identification, APOBEC-Coupled Epigenetic Sequencing (ACE-seq), that is highly accurate, requires low input, and does not degrade DNA as commonly used bisulfite treatment methods do. ACE-seq is especially relevant to cellular environments that are epigenetically dynamic, including brain tissue and embryonic cell cultures. My project uses ACE-seq to generate high fidelity 5hmC characterizations in the Elf1 cell line across culture conditions that mimic early human embryonic development in which dramatic changes in DNA methylation occur. ACE-seq will be used on three human embryonic stem cell (hESC) conditions that mimic the transition from before embryonic implantation, naïve hESCs (two conditions), to near the time of embryonic implantation, primed hESCs. We hope to gain insight into 5hmC localization and regulatory function during this physiologically significant developmental event occurring during early embryogenesis. A more robust understanding of 5hmC regional abundance during this transition will help us elucidate the regulatory circuitry underlying early development. Knowledge gained in this project is especially relevant to the field of personalized medicine, as thorough understanding of pluripotency transitions will be significant to future applications of stem cell based therapies and precision healthcare. 

New technologies capable of controlling the position-and-spacing of nanostructures have advanced applications such as electronics, sensing, and catalysis. In contrast to conventional top-down approaches such as lithography, biological-macromolecule-templates offer an attractive way to direct the assembly of nanoparticles because their high-information content can be used to direct complex structures over multiple length-scales, just as they encode living structures. Here, we study the use of de novo designed protein-nanofibers to control the assembly of gold nanoparticle chains as a model system. We employ Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, which combines the energy contributions of van-der-Waals-attraction (vdW) and electrostatic-double-layer-repulsion (EDL) to understand the factors governing electrostatic assembly of gold nanoparticles along a protein-nanofiber anchored to a charged substrate, explain observed experimental results, and predict the assembly outcome under varying solution conditions. During the assembly process, as the distance between nanoparticle and protein-functionalized substrate decreases, we expect an increase in the magnitude of vdW and EDL forces. Varying nanoparticle size reveals particle-substrate EDL repulsion limits larger nanoparticles from reaching the protein despite an increase in vdW attraction, while tuning the pH varies EDL particle-protein-attraction and particle-substrate-repulsion, resulting in predictable particle density and binding specificity. We use Python 3.7.2 programming to calculate total system energies at different stages of the assembly process using equations based on the surface-element-integration method. By constructing a virtual representation of the protein-nanofiber as a chain of spheres on a flat plane and a spherical nanoparticle above the fiber at varying distances, we can use DLVO theory to map out the interaction energies for all solution conditions. With the ability to define the energy of a system, we will be able to design new biotemplates, indefinitely predict the solution conditions, and identify potential intervention points that would allow the self-assembly of plasmonic particles for new and/or difficult-to-achieve photonic applications.

Although RNA is most commonly regarded as a passive carrier of genetic information, throughout biology RNA molecules exhibit an exceptionally broad scope of other, non-coding functions. Exciting recent work has demonstrated that RNA plays diverse and fundamental roles in helping to pattern subcellular architecture, including that of numerous subnuclear structures that are essential to cellular function. Many such architectural RNAs are also causally dysregulated in human diseases, suggesting that they may represent a novel resource for untapped therapeutic targets. Yet, the mechanisms by which these architectural RNAs function have remained elusive. An essential first step towards deciphering RNA’s cellular function is to elucidate the complex networks of proteins, RNAs, and genomic loci with which that RNA interacts. Yet, this kind of analysis is impossible using conventional approaches. To address this critical need, the Shechner lab has been developing Oligonucleotide-directed biotinylation (ODB), a straightforward and universal method for mapping RNA interaction networks without taking them out of their native cellular context. Our recent results demonstrate that ODB enables precise targeting of individual RNA interactions in situ, enabling high-resolution proteomic, transcriptomic, and genome-interaction analysis in situ. The two goals of my project are to: (1) develop generalized and extensible ODB strategies that can be applicable to a wide range of RNA targets of interest, and (2) expand ODB's range of in situ labeling chemistries, enabling higher-precision analysis. To achieve these goals, I am performing a series of ODB experiments on 9 selected long non-coding RNAs of interest and establishing a high-precision localization pattern across all the RNA targets within the cellular context. The establishment of this powerful and general method can enable unprecedented dissection into RNAs that have been notoriously difficult to analyze by traditional approaches, and may potentially reveal new avenues for novel therapeutic target-discovery.

 Euphausia superba, commonly known as Antarctic krill, are the dominant krill species in the Southern Ocean, and one of the most abundant species on Earth. This project focused on the swimming patterns of Antarctic krill in increasing chlorophyll concentrations to help understand the relationship between food availability and krill response by using 3-D data points from synchronized videos. Samples were collected aboard the RV Gould throughout Autumn of 2019 at both the South Shetland Islands and Gerlaches Straight at depths of 100-150m using 750 micrometer mesh square 2 x 2m nets. Samples were stored in a 500L tank and kept at 6 degrees Celsius. For the trials, 5 krill were placed in a 50L tanks in varying chlorophyll-a concentrations and recoded for 10 minutes using synchronized cameras. Afterwards, krill movement was analyzed using MATLAB’s DLTdv8 software. R Studio was used to assign ‘bins’ to various tank depths and count the number of individuals in each bin at a given time. Currently, I am still working on the results, however, it is hypothesized that the time spent in multiple bins will decrease as the chlorophyll concentration increases, since the krill will develop a more horizontal swimming pattern. It is important to understand this mechanism because in future climates, phytoplankton abundance is uncertain, which could have negative consequences for krill and the surrounding environment because of their keystone species status.