faculty

Unless treated, many health conditions become chronic and may eventually lead to additional comorbidities and declining health. More than a quarter of all Americans -and two out of three older Americans- are estimated to have at least two chronic physical or behavioral health problems. Treatment for people living with these multiple chronic conditions (MCC) currently accounts for an estimated 66 percent of the Nation's health care costs. Furthermore, as the U.S. population ages, the number of patients with MCC will continue to grow. This mounting challenge has become a major public health issue that is linked to suboptimal health outcomes and rising health care costs. However, fundamental knowledge gaps remain in our understanding of how MCC emerge at the population level. The progression of specific chronic conditions has been associated with the development of additional comorbidities. For example, obesity is associated with coronary artery disease, high blood pressure, stroke, and type 2 diabetes. While traditional epidemiological approaches have led to important findings of disease links and comorbidity associations, they are limited in their ability to answer questions with more complex data sets. Are there patterns of comorbidities that exist and how do these patterns emerge over time? What are the variables that affect change in the trajectory of health status? Finding answers to these questions requires an approach that can examine the simultaneous emergence of numerous chronic conditions at the population level and this has only recently become possible by using big data analytics and high performance computing. The ultimate goal of our work is to identify individuals at risk for MCC and to determine where in their course of disease acquisition is the best point to intervene and ultimately decrease their likelihood of having MCC. The goal of the proposed study is to use a probabilistic methodology that integrates advanced statistical learning methods, rigorous optimization techniques, and clinical expertise to understand the process of MCC emergence and progression over time. To achieve this goal, we will use retrospective healthcare data from approximately 100,000 patients with at least 8 years of care between 2002-2014.

The state-of-the-art high performance computing enables researchers to simulate the motions of millions of atoms interacting with one another. Now it is feasible to produce quantitative predictions of biological functions of a protein that are "deterministic" out of the atomistic interactions and motions that are stochastic in nature. Dr. Chen's team aims to study the functions of human aquaporins and look for ways to modulate/inhibit them. They build the aquaporins and their biological environments from atoms up, simulate their stochastic dynamics, and elucidate their deterministic functional behaviors under various controllable conditions. The inhibitors of water channels (AQP 1, 5 etc.) and glycerol channels (PfAQP, GlpF etc.) are medically relevant for treatment of hypertension, refractory edema, elevated airway mucus secretion during anesthesia, etc. Using the hybrid steered molecular dynamics method they developed for this research, Dr. Chen and associates are able to take full advantage of the high resolution protein structures and the mature CHARMM force field parameters. They are harnessing the massively parallel computing power of the day to better human health.

Each year in the United States alone approximately 100,000 patients are infected with enterohemorrhagic Escherichia coli (EHEC) of the O157:H7 serotype. Since its initial discovery and association with an outbreak of human disease in 1982, this food-borne pathogen has rapidly emerged from a then rare into the now dominant EHEC serotype in North America and is responsible for global widespread outbreaks of severe gastrointestinal disease. Infection of previously healthy individuals can rapidly progress into life-threatening complications, such as hemolytic uremic syndrome (HUS), the principal cause of acute kidney failure in children, hemorrhagic colitis (HC) and central nervous system (CNS) failure, frequently with lethal consequences. Our long-term objective is to identify key pathogenicity factors underlying human disease. For this study we have assembled a unique resource of more than 250 E. coli O157:H7 whole genome sequences, including archived bacterial cultures and strain-associated metadata, which altogether provide a robust foundation to achieve the proposed research objectives. This proposal is directed at determining the genomic diversity in E. coli O157:H7, and to correlate mutational differences in the pathogen's genetic make-up to its adverse pathogenic potential in affected patients. For this purpose, we will molecularly characterize clinical E. coli O157:H7 specimens by performing a whole-genome-sequence-typing (WGST) on a lineage-wide scale utilizing a custom bioinformatics pipeline to detect single nucleotide polymorphisms (SNPs) and to determine the strain's individual bacteriophage profile. The resulting enriched mutational database is critical to establish a refined phylogenomic framework that reveals epidemiological and genomic relationships of clinical outbreak isolates. The superior phylogenetic resolution and accuracy will allow to precisely determine the different genotypic and clinical characteristics of the subgroups of this pathogen. In addition, we have developed an assay indicative for the adverse pathogenic potential of clinical isolates during human infection that measures the strains' individual bacteriophage mobilization and toxin expression, which are crucial pathogenicity determinants to predict the severity of human infection. We will identify chromosomal and/or phage-borne genes that are recurrently mutated in isolates displaying increased bacteriophage mobilization and toxin expression. For this purpose, we will use PCR- and sequencing-based transcriptomics techniques to reveal a strains' toxin-specific and genome-wide regulatory expression changes. In conclusion, we envision that our findings will have immediate impact on the decrease of human morbidity rates. The identification of the genetic make-up of high level toxin producers is crucial to assess the risk in infected individuals for the progression of HUS offering improved diagnostic risk assessment. In addition, potentially new therapeutic targets are revealed enabling suppression of toxin production during human infection, and the resulting enriched genetic marker base is critical for higher-resolution molecular-guided pathogen surveillance and outbreak investigations.

Natural products have played a pivotal role in the discovery and development of modern chemotherapeutics. Thus, the genesis of more than 70% of all small molecule anti-cancer medicines approved in the last 70 years can be traced to natural products. Although the key role of natural products in drug discovery remains uncontested few of them have undergone comprehensive structure-activity relationship (SAR) studies and exhaustive bioactivity screenings. This is primarily due to the prevailing scarcity of the natural products compounded with limited options for structural modifications which are necessary for the SAR studies. Synthesis of these natural products offers the opportunity to access the natural product and its numerous congeners through changes in the synthetic strategy. Due to the limited number of reliable enantioselective catalytic reactions many syntheses rely on the elaboration of chiral starting materials along circuitous synthetic routes. This affects the efficiency and narrows flexibility and applicability of the syntheses. The 1,2-oxazine natural products have been particularly affected by this shortcoming. This is a serious limitation for the discovery of new chemotherapeutics since many of these natural products possess unique and exciting biological activities. We aim to make the 1,2-oxazine core readily accessible through rational design of a novel enantioselective and catalytic cyclization reaction. We will also develop a straightforward methodology for the conversion of the cyclization products to the 1,2-oxazine natural products and their structural analogs that are unattainable using currently available methods. This methodology will then be employed for the synthesis of two 1,2-oxazine natural products that possess unique anti-cancer activities. This approach is based on the unprecedented catalytic enantioselective cyclization reaction and is innovative because (a) it has the potential to combine the undisputed efficiency and practicality of a catalytic asymmetric method with the ready availability of both precursors; and (b) the asymmetric cyclization reaction will allow rapid access to a variety of structurally related natural products by way of simple structural editing. These studies will improve our understanding of their biological properties and will potentially provide new leads for anti-cancer drug discovery.

A common disorder of the temporomandibular joint (TMJ) results from displacement of the articular disc leading to degenerative joint disease. Among patients that experience TMJ disorders (TMD) a gender disparity exists with more women, generally during their reproductive years, than men seeking treatment. It has long been suggested that estrogen influences the maintenance and repair of the TMJ by directly and/or indirectly regulating protein synthesis, but the relationship between the two and the mechanisms underlying TMJ derangement are poorly understood. This application proposes to explore the role of estrogen in the regulation of the lubricating, secreted molecule proteoglycan 4 (PRG4) (also known as lubricin, megakaryocyte stimulating factor precursor, and superficial zone protein). Through a mucin domain encoded by exon 6, PRG4 provides boundary lubrication of articulating surfaces. Our preliminary studies detected putative estrogen response elements (ERE) in the PRG4 promoter region. Cells derived from TMJ disc, treated with estrogen, exhibit a decrease in PRG4 expression of all four isoforms. Additionally, a novel PRG4 transcript isoform that is lacking exon 6 was detected, thereby expected to yield a non-lubricating PRG4 isoform. These findings could help explain the mechanism leading to TMJ degeneration and its bias toward women. This application has three specific aims that will extend our preliminary findings. Aim 1 is to characterize the influence of estrogen on the levels of PRG4 alternatively spliced isoforms that are synthesized by cells derived from female and male adult baboon TMJ. Both steady-state and estrogen dose-response assays will be employed. Western blots and qPCR will record the levels of protein and transcripts inhibited by estrogen. Aim 2 is to test for and characterize the EREs in the PRG4 promoter using gene reporter assays, supershift assays, and mutagenesis of the putative EREs. Aim 3 is to test for the extent that estrogen decreases the lubrication capability of TMJ cell medium and organotypic cultures of TMJ disc, synovium and cartilage. Characterizing the novel isoform and its regulation by estrogen is expected to lead to new therapeutic treatments beneficial for TMD patients.

Esophageal adenocarcinoma arises from precancerous lesion "Barrett's metaplasia," in that the process involves discrete genetic mutations and epigenetic changes that are as yet poorly defined. Numerous efforts have been made to identify the genetic mutations associated with cancer. However, most recent finding suggests that the precancerous lesion is initiated from epigenetic abnormalities without genetic mutation. One such epigenetic alteration is change in the modification of histone proteins which package DNA. These epigenetic alterations are found both early and late in tumorigenesis and, in some cases, normal tissues before tumors arise. Our broad hypothesis is that epigenetic alterations resulting from aging as well as environmental and/or dietary factors may predispose an individual to cancer promoting events in esophageal adenocarcinoma. These factors usually do not acquire changes in DNA sequences of our genome. Instead they cause widespread changes in the "epigenome," such as modifications on histone proteins. These aberrant histone modifications may alter metabolism or cell growth, which is often associated with different types of cancers. Our preliminary study suggests that changes on histone proteins modification could happen very early in the developing esophageal malignancy and lead to widespread effects on gene expression. Therefore, extending from our initial finding, the immediate goal in this grant proposal is to identify the vulnerable targets under the aberrant histone modifications in both Barrett's metaplasia and esophageal adenocarcinoma. We anticipate that results from our proposed aims will thoroughly dissect the mechanism of cancerous initiation under aberrant epigenome responsible for esophageal cancer. In addition to early detection of Barrett's esophagus and EAC, characterization of epigenetic perturbation could open another avenue to provide direction for novel treatment strategy. The significance of this proposal is that we will identify the vulnerable molecular targets as biomarkers for early detection and also learn the mechanism underlying the development of esophageal cancer in the absence of genetic mutation. Ultimately, our findings could provide direction for novel treatment strategies and/or the prediction of patient therapeutic response.

Recently it has been reported that actin filaments and microtubules are able to transmit electric signals and sustain ionic conductance. Since the velocity of electrical signals along these filaments is, depending on specific conditions, of same range as the propagation of neural impulses, the concurrent propagation of electrical signals along these filaments and electrochemical currents along the axonal membrane is possible in principle. This novel conduction mechanism observed in cells opens unexplored frontiers that will change the current understanding of neural activities and neuronal networks. Not surprisingly, the ionic conduction of these structures has been associated with processes as diverse as directional growth, cytotoxicity, plasticity, and migration. However, the underlying biophysical principles that support this behavior are poorly understood. Therefore, the objective of this proposed research is to generate substantial preliminary results to advance the molecular understanding of ionic conductance and electric signal transmission properties of microtubules and actin filaments. We believe that filaments and axon membranes may be able to transmit different kinds of information. Such capability may be affected by age and physiological conditions in different manner and therefore the corresponding propagation of electrical signal along filaments and neural axon membrane might be associated to different neural activity dysfunctions. Without question, investigating the biophysical principles underlying the electric and solvation properties of these cable-like filaments can bring an urgently needed progress in the molecular causes of many developmental and degenerative brain disorders. We may not validate our hypothesis and address this gap in knowledge using conventional models and approaches. Therefore one of the aims of this project consists in developing a computational tool to rationally investigate the electrophysiological mechanisms that affect conformational changes and conductance of electrical signals in both extra- and intracellular environments. We will perform a systematic characterization of these properties at a molecular level. This theoretical framework would also make great contributions to conventional areas of biochemistry where electrostatics underlies a major part of molecular properties. The proposed computational model will be then further extended to produce the mathematical engine to investigate signal transduction in proteins. The outcomes of this proposal will have a significant impact on the understanding and clinical applications of non-neuronal signal transduction and could open new therapeutic avenues to help the millions of patients currently affected by these disorders. In addition, the computational model (which will be publicly available) will enable the advancement of various technological and biomedical applications involving electrical conductance in proteins such as electrochemical biosensors, electric stimulation of tissue growth, and biomolecular processors.

The long-term objective of this project is to study sinoatrial node dysfunction and discover an innovative way to precisely diagnose cardiac arrhythmias and predict sudden cardiac death at early stages. Sinoatrial node dysfunction leads to sick sinus syndrome (SSS) that is becoming a significant healthcare problem in a rapidly aging society. SSS develops asymptomatically and leads to sudden death if untreated. However, the diagnosis often involves invasive, long-term Holter monitoring. At present, no reliable diagnostic method exists for SSS, especially for patients with atrial fibrillation. Given the complex pathophysiology of heart diseases, interests have intensified in developing biochemical markers to predict susceptibility to cardiac events and aid in the early diagnosis and management. As such, the objectives of this project are (1) to establish and clinically validate a reliable association of levels of plasma biomarkers with development and severity of for arrhythmias such as SSS; and (2) to provide clinicians with a high-throughput, rapid, and accurate blood analysis methodology for these cardiac biomarkers by developing a novel multiplexed gold nanorod probes array to improve non-invasive diagnosis and sudden cardiac death prevention. This study provides a paradigm shift for the prevention of fatal arrhythmias and sudden death from invasive interpretation to non-invasive diagnostics. Results from the proposed project are clinically relevant and will bridge the knowledge gap in overall appraisal of risks associated with sudden cardiac death and will advance bioassay technology in clinics.

It is becoming clear that collective cell migration is involved in the dissemination of tumor cells. In collective cell migration, cells move through migration of cohesive multi-cellular units, the specifics of their motility depend on numerous factors including cell-cell, cell-matrix interaction, adhesion strength, extracellular matrix rigidity, organization of the cellular cytoskeleton, etc. How each individual factor affect the collective cel migration is still poorly understood and needs further investigation. This project will investigate fundamental mechanisms of collective cell migration from cell molecular biology perspective as well as from mechanics viewpoint. The research objective of this proposal is to establish a multiscale approach to investigate cell-cell, cell-matrix interaction and their influences on collective cell migration. The central hypothesis of the proposed research is that collective cell migration depends on interactions between cells and their microenvironment which can be quantified by biomechanical and biophysical parameters in an integrated multiscale model. To test the hypothesis, computational modeling and simulation approaches will be developed and three specific aims will be addressed: Aim 1 To build an active cell model with internal structures to capture the essential features of cell membrane, cytoskeleton and cell nucleus; Aim 2 To develop a multiscale cell migration model and to elucidate how different factors control collective cell migration motions; and Aim 3 To develop advanced simulation techniques for cell mechanics simulations.