Embryonic stem cells (ESCs) are capable of differentiation to cells of all three germ lineages and are therefore an attractive cell source for tissue engineering applications. ESC differentiation is commonly initiated through the formation of 3D cell spheroids termed embryoid bodies (EBs). EB differentiation is difficult to control by media manipulation alone due to complex 3D cell-cell and cell-matrix interactions; therefore biomaterial integration within EBs is used as a method for control of the cell microenvironment. Previous work has demonstrated that incorporation of morphogen-releasing, biomaterial microparticles (MPs) can be used for directed differentiation within EBs. In this study, the use of gelatin and heparin-modified gelatin MPs to engineer the EB microenvironment was investigated. Heparin was chosen for its intrinsic ability to bind growth factors within native tissues. The potential of heparin-modified MPs was assessed through analysis of growth factor (GF) binding capacity, sequestration of GFs secreted by EBs, and phenotypic effects on EB differentiation.

Epilepsy is a neurological disorder that affects tens of millions of people every year and is characterized by sudden-onset seizures which are often associated with physical convulsions. Effective treatments and management of epilepsy would be greatly improved if convulsions could be caught quickly through early seizure detection. However, this is still a largely open problem due to the challenge of finding a robust statistic from the neural measurements. This project suggests a new multivariate statistic by combining spectral techniques with matrix theory. Specifically, stereoelectroencephalography (SEEG) data was used to generate a series of coherence connectivity matrices which were then examined using singular value decomposition. Tracking the relative angles of the first singular vectors generated from this data provides an effective away of defining the most dominant characteristics of the SEEG during the normal, the pre-ictal, and the ictal states. These results indicate that the first singular vector has a characteristic direction indicative of the seizure state and illustrates a data analysis method that incorporates all neural data as opposed to a small selection of channels.

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is typically an autosomal dominant disease characterized by a particularly high incidence of lethal ventricular arrhythmias, fibrofatty infiltration of myocardium, and is a leading cause of sudden cardiac death. Several mechanisms have been proposed for the progressive degeneration of myocardium associated with ARVC. For example, it is widely believed, but not proven, that abnormal intercellular adhesion is a critical aspect of disease pathogenesis. Accordingly, we characterize the effects of mechanical shear, a force likely experienced by collagen-coupled myocardial sheets in vivo, on cardiac myocytes expressing two ARVC-causing mutations in the desmosomal gene encoding plakoglobin (JUP).

The skeleton is constantly adapting to environmental cues which include external forces that govern overall bone formation or bone resorption. Osteocytes, considered the main mechanosensing cells within bone, reside throughout mineralized bone matrix and possess mechanosensors with which to sense mechanical stimuli. Through mechanotransduction, osteocytes convert physical signals into biochemical and transcriptional responses; however, the mechanisms of mechanotransduction are not well understood. One potential osteocyte mechanosensor is the primary cilium, a nonmotile, solitary microtubule-based antenna that extends from the surface of most mammalian cells, including osteocytes. While its function was unknown for almost 100 years, recently, our lab and others have demonstrated that the primary cilium serves as a mechanosensor in several orthopaedic tissues, including bone. Removal of osteocyte primary cilia inhibits loading-induced increases in osteogenic gene expression in vitro and decreases mechanically-induced bone formation in vivo. Furthermore, we are investigating the roles of second messenger signals within the primary cilium and several key proteins that are enhanced in the primary cilia microdomain in regulating mechanotransduction. The purpose of our work is to elucidate primary cilia-mediated mechanisms of mechanotransduction in osteocytes, which may reveal potential therapeutic targets for treating bone loss diseases.

Neutrophils undergoing transendothelial migration (TEM) during an inflammatory reaction in the lungs, the eyes, and the skin face a unique microenvironment containing a 1:1 endothelial cell (EC) to pericyte (PC) ratio. While previous research in this field has focused solely on the neutrophil-EC interactions required for this process, understanding the influence of cell-cell contact, paracrine signaling, and protein deposition by the cells in mediating neutrophil migration is essential to properly address immunological dysfunction in these organs. Using a combination of polymeric biomaterials and human cells, we have created experimental models of the microvasculature, the site of neutrophil TEM. These models are capable of maintaining EC and PC function as would be seen in vivo and of isolating the individual roles of cell contact (neutrophil-EC, neutrophil-PC, and EC-PC), of paracrine signaling, and of basement membrane protein composition in the overall process of neutrophil TEM. With our first generation model, we confirm that cytokine release profiles are altered as a result of cell-cell and paracrine signaling, thereby demonstrating the necessity to take a systems-level approach to neutrophil research and the feasibility of using biomaterial-based models for this research.

Hydrogels are water swollen polymeric materials that can provide chemical and physical cues to control encapsulated drug and cell behavior. These materials are important in the realm of regenerative medicine and have been used to improve the clinical outcomes of drug and cellular therapies. Current injectable hydrogels are often delivered as liquids, whereupon they polymerize and gel in situ from changes in environmental conditions, from the addition of chemical linkers, or from photoinitiated free-radical generation. However, such stimuli for gel polymerization may be deleterious and may reduce the therapeutic effect of sensitive drugs or cells during delivery. We here describe a novel ‘Dock-and-Lock’ (DnL) self-assembling hydrogelation mechanism that can be used to build ‘smart’ injectable hydrogels, which can polymerize and encapsulate therapeutics under constant physiological conditions and without the need of chemical linkers or free radicals. The DnL system is based on engineered molecular interactions between recombinant multimeric polypeptides inspired from the docking domain of A-kinase anchoring protein (Dock) and the locking anchoring domain subunit of RIIa cAMP-dependent kinase A (Lock). Hydrogel physical properties, such as elasticity, stability, and micro-architecture can be simply tuned by adjusting material component compositions or valency. Encapsulated drugs can be released at controlled rates defined by the surface erosion profiles of the material. DnL gels are cytocompatible, and stem cells encapsulated within DnL gels and delivered with minimally invasive methods remain highly viable. Through molecular and protein engineering strategies, we have developed a highly modular biomaterial system that is well-suited for use in regenerative medicine.

Allosteric signal transmission plays important roles in the gating of ion channels. Kv1.2 and MlotiK1 are tetrameric K+ channels sharing a similar fold. Although activation of both channels results in a passive flow of K+ ions, Kv1.2 responds to changes in transmembrane
potential, while MlotiK1 is activated by binding of a cyclic nucleotide. We study the different mechanisms of allosteric signal transmission using the perturbation-based Markovian transmission (PMT) model. We found that perturbation at ionizable residues collectively in the TM region of Kv1.2 leads to the initiation of allostery. We showed allostery in the MlotiK1 can be initiated through combined perturbation of the C-linker and the S2-S3 loop. We reconstructed explicitly time-dependent signal transmission pathways in both channels, with on-pathway residues identified. For Kv1.2, 9 out of the 28 predicted on-pathway residues
have mutation data supporting their functional roles. Despite dierent activation mechanisms, we found the S1-S4 domain is a key component of the signal transmission pathway in both types of K-channels. Overall, our study suggested plausible mechanisms by which voltage-gated channel and cyclic nucleotide-binding channel initiate allosteric signal transmission differently. The significant enrichment of aromatic residues highlights the important roles of these residues in allostery.

Enzyme scaffolds enable the precise placement of components of an enzymatic cascade within nanometer distances. Recent advances in synthetic biology and nanobiotechnology demonstrate significantly increased throughput of enzymatic cascades as a result of the utilization of a scaffold, but the basis for this increase is not understood. Here, the concept of “metabolic channeling” as a result of nanometer separations between enzymes on scaffolds is examined using simulations and mathematical models. Random walk simulations were performed using MATLAB software to determine the relationship between enzyme separation and direct flux magnitude. Using COMSOL Multiphysics finite element analysis software a simulation of the enzyme cascade was constructed, solving the reaction-diffusion equation for a given topology. For an isolated enzyme pair an increase in cascade throughput is observed only in the micro- to millisecond range. By defining a “direct” path in which the intermediate substrate travels directly from the first enzyme to the second, we show that the time scale in which the scaffold makes a significant contribution is given by t = V/4?dD where V is the vessel volume, d is the distance between enzymes and D is the diffusion coefficient of the substrate of enzyme 2. For typical parameters, e.g. V = 1 µm3, d = 10 nm, D = 109 nm2/s, this time scale is on the order of milliseconds. In addition, the aggregation of numerous enzymes on a single scaffold is shown to increase cascade throughput even on the time scale of minutes. Our model shows that the increase in throughput cannot be explained based on diffusive transport alone. This is due to the low catalytic efficiency of most enzymes, which results in a low probability of complex formation at the second enzyme. By increasing the number of available “targets”, a two- or three-dimensional scaffold can increase the probability that a substrate molecule is captured and a higher production rate is observed.

Free energy scale is essential for understanding membrane protein folding and for predicting membrane protein structures. Hydrophobicity scales for membrane proteins have been measured experimentally in lipid bilayer and biological membrane. However, they were based on measurement of model peptides. Recently, a new biological scale of water-to-bilayer transfer free energy of 20 amino acids was obtained by measurement in the context of a native ?-barrel transmembrane protein OmpLA. Here we report results on computational transfer free energy. It is based on an energy function composed of three terms, single-body burial, inter-strand interaction and sequential nearest neighbor contact interaction. Using a mechanics and statistical model, we have computed the full partition function of OmpLA and the transfer free energy of residues. The computed result of free energy scale of 19 amino acid residues correlates well with experimental data (r2 >0.80). In addition, our results indicate that free energy changes are context dependant. Our computational results also show that the occurrence of Arg is depth dependant and is not be overly costly.

Image informatics is a field of science that develops methods to systematically store, describe, share, analyze, and visualize images and their associated data. It is revolutionizing the field of pathology by facilitating— (1) systematic storage and retrieval of images, (2) computer-aided decision support systems, and (3) discovery of new biologically relevant morphological patterns. Public repositories such as the cancer genome atlas (TCGA) provide access to large whole-slide images(WSIs) from hundreds of patients with various types of cancer. Image informatics tools are essential to successfully analyze this large amount of data and to discover novel informative bio-markers for the disease. In this talk, I will discuss image informatics methods for histopathological WSIs. First, I will discuss some challenges with histopathological WSIs including color batch-effect, image artifacts and image size. Because of variations in specimen preparation, staining, and imaging, resulting histopathological images may exhibit very different colors. I will discuss a novel color normalization technique to address this challenge. Image artifacts in TCGA's WSIs include tissue folds and pen-marks. I will discuss color-based methods for selecting regions-of-interest from WSIs that exclude image artifacts. Second, I will discuss some quantitative image features that capture morphological patterns in the histopathological images. Third, I will discuss an example of a supervised learning model for classifying tumor and non-tumor regions in a WSI. Fourth, I will discuss applications of unsupervised learning for discovering biologically relevant morphological patterns.

ß-lactam antibiotics are the most commonly used antibiotics due to their high effectiveness, low cost, ease of delivery and minimal side effects. As a result of wide use of these antibiotics, bacteria render resistance to ß-lactam antibiotics. One mechanism of ß-lactam resistance is the synthesis of ß-lactamase by both Gram-positive and Gram-negative bacteria. This enzyme hydrolyzes the amide bond of the ß-lactam antibiotics causing them to be ineffective. The most prevalent ß-lactamase is the class A TEM-1 ß-lactamase which is a periplasmic protein with 263 amino acids. Streptomyces clavuligerus produces a protein inhibitor of ß-lactamase called ß-lactamase inhibitor protein (BLIP) which is a 165 amino acid protein. BLIP inhibits class A ß-lactamases such as TEM-1 or SHV-1 with varying degrees. The aim of this study was to purify ß-lactamase and elucidate the intracellular binding and inhibition kinetics of BLIP and ß-lactamase. The interaction of these molecules has previously been verified by in-vitro studies. The wild-type form of TEM-1 ß-lactamase has been produced by E. Coli TB1 pUC18 cells and purified 5.1 times from the periplasmic protein extract by ultrafiltration and ion exchange chromatography methods. Purified enzymes are used for subsequent ß-lactamase assays. Competitive inhibition of commercial pure TEM-1 ß-lactamase by BLIP was demonstrated however BLIP was found to be an uncompetitive inhibitor of the purified periplasmic protein extract.