REU Program Research Areas:
Keck Graduate Institute is dedicated to interdisciplinary research. Projects accessible to undergraduate students are grouped by research areas. Follow the links below for a brief outline of the research areas at KGI open to undergraduate students, the faculty members involved, and the research projects within each area. I think the most important thing I got from this program is actually seeing how it is to work in a lab full-time on an independent project. I would encourage next year's REU students to pick a project that is interesting to them, and to learn a little about the project so that they will know what they will be doing for 10 weeks. ~ Amy Yau, REU 2004 Microfluidics and Microfabrication  The research performed in the Microfluidics Research Laboratory at KGI is aimed at the development of miniaturized systems for biomolecular analysis and manipulation. Miniaturization is critical to the development of high-throughput biomolecular diagnostics and biosensors as it facilitates rapid processing and automation. Interest in miniaturization of these systems has led to the formation of a number of companies and a plethora of research activity around the world involving microfluidic “biochip” development. Biochips are being developed for applications in drug discovery and medical treatment and diagnostics. In support of this applied research, we are interested in a number of microfluidic phenomena including electrowetting-based manipulation of drops; electrokinetic phenomena; chip-based capillary electrophoresis; DNA diagnostics involving amplification and hybridization; etc. Current research topics appropriate for undergraduates in the REU program include efforts to further develop:
Project 1: Chip-Based Capillary Electrophoresis (Jim Sterling, Ali Nadim). We are using chip-based capillary electrophoresis to identify and separate bio-molecules, and to determine biochemical reaction rates (of reversible binding reactions) of molecules in free-solution or in a sieving matrix under electric fields that are higher than commonly used in CE or gel-based systems. Separation of short oligo-nucleotides in such a system is being investigated as a means of detecting multiplexed isothermal DNA amplification reactions.
Project 2: Electrowetting-Based Fluidic Control Systems (Jim Sterling, Ali Nadim). We are using the phenomenon of electrowetting to move droplet samples via application of electric potentials to arrays of embedded micro-electrodes. Clean-room photolithography techniques are used to fabricate electrode arrays and perform coating of various dielectric materials. Applications to cell and particle sorting and enrichment are of current interest.
Project 3: Positive Displacement Pumping in Flexible Pouches (Jim Sterling, Angelika Niemz). Medical diagnostic technologies suitable for point of care or near patient applications often employ a flexible pouch system to contain necessary reagents, control fluid flow, and to provide a reaction chamber for assay execution. Fluid flow within these pouch systems is in most cases accomplished through external actuation. The goal of this project is to develop a flexible pouch system with integrated positive-displacement pumping for execution of medical diagnostic tests in an inexpensive, self-contained format. Students will be involved in the optimization of pouch fabrication, test execution, data analysis, and theoretical modeling of the system.
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Medical Diagnostics and Devices  Medical devices are used for the diagnosis of disease or other conditions, or in the cure, mitigation, treatment, or prevention of disease. This broad and interdisciplinary field includes the development of bioassays, instrumentation and software, and requires knowledge in the areas of biochemistry, molecular biology, engineering, physics and computer science. Research in medical diagnostics at KGI focuses on miniaturization and multiplexing of nucleic acid based assays, and on the use of nanoscale materials to enable novel signal transduction mechanisms. Research in medical devices at KGI is focused on the application of system theory and advanced signal processing methods to patient monitoring. Related assays, instruments, and algorithms are also applicable in fundamental research, in drug and biomarker discovery, and in pharmacodiagnostics and personalized medicine.
Project 1: Optimization of Isothermal DNA Amplification (Angelika Niemz). Isothermal DNA amplification reactions can facilitate rapid and sensitive DNA detection requiring minimal instrumentation for clinical diagnostics and biothreat detection applications. The Exponential DNA Amplification Reaction (EXPAR) developed at KGI enables >10^6 fold isothermal amplification of short oligonucleotide trigger sequences in less than 10 minutes through combining DNA polymerization with single strand nicking. We have developed a two stage version of EXPAR coupled with colorimetric detection to facilitate simple and rapid point-of-care based detection of infectious pathogens. Students with a background in molecular biology, biochemistry, or bioengineering will have the opportunity to participate in further optimizing the sensitivity of EXPAR and associated reactions.
Project 2: Fast Detection of E. coli via Isothermal DNA Amplification (Jim Sterling, Ali Nadim, Robert Doebler & Angelika Niemz). The goal of this project will be to develop a rapid assay based on EXPAR, an isothermal DNA amplification method developed at KGI, for ultimate detection of pathogenic E. Coli O157:H7. The REU project will involve proof-of-principle detection of non-pathogenic E. coli. The assay will be optimized for performance in an isothermal fluorimeter, also developed at KGI, and will be characterized in terms of sensitivity, specificity and limit-of-detection. Time-permitting, we will attempt to integrate this assay with a sample-preparation technique (such as bead-beating to lyse the bacteria and make their DNA accessible) and DNA purification.
Project 3: Electronic DNA Detection on Semiconductors (Angelika Niemz). We are developing methods for rapid and sensitive electronic DNA detection on semiconductor surfaces, based on changes in surface impedance. This project involves characterizing the impedance changes occurring at a DNA functionalized semiconductor electrode, or on microfabricated arrays of sensor electrodes, upon hybridization of the complementary target DNA. The project further entails equivalent circuit modeling for different experimental configurations, to better understand and optimize experimental parameters. Students with a background in electrical engineering or electrochemistry, and fundamental understanding of biochemistry or molecular biology will have the opportunity to participate in hardware development, experimental optimization of impedance based DNA detection and in numerical modeling of equivalent circuits.
Project 4: Drowsiness Monitoring (Gail Baura). In 1997, U.S. commercial truck tractor crashes cost $14.7 B. 15% of these crashes involved driver fatigue. Even with recent changes in hours-of-service rules, a 2005 survey revealed that 40% of long distance truck drivers drove sleepily the previous week. If an accurate, early drowsiness detection monitor were placed in long distance trucks, each could warn his driver before he fell asleep. In the long term, this noninvasive monitor would provide an input to the intelligent vehicle systems currently under development, in order to pull the truck safely to the curb when drowsiness onset occurs. The student will participate in data acquisition, as well as processing of reference data.
back to top Computational Biology  A cell is a complex informational system of interacting molecules ranging from nucleic acids through proteins to small metabolites. A multicellular organism is an even more complex informational system where the component cells continually exchange signals and respond to one another and to the environment. The dynamics of these very large sets of interacting components appear to be highly orchestrated. Recent advances in genomics, proteomics, and in computer- and mathematical modeling are promising a better understanding of the dynamics of cells at the molecular level. The mathematical and computational analysis of biological networks is aimed at making precise models of the regulatory mechanisms underlying cell function, at predicting the biological response to specific perturbations (as in diseases or in stress), and at developing methods to integrate, quantify, and analyze intracellular and intercellular regulatory interactions. Our studies span several dimensions: from developing methods to process and evaluate genome- and proteome-wide experimental data to obtain regulatory information about cellular processes, through modeling of signal transduction pathways in computer or via electronic simulation, to mathematical analysis of networks of evolving genes and proteins. We are also approaching the problem from the opposite direction: what unitary analogs of regulatory modules can be identified in biological systems? Some of the on-going projects are described below:
Project 1: Understanding and Evolving Metabolic Networks (Christoph Adami, Arend Hintze). Genes, proteins, and molecules interact with each other in intricate ways that can be represented as graphs or networks. Acentral question of systems biology concerns how evolution shapes the modularity of networks, and hoe the modularity affects evolution. We have previously evolved artificial metabolic networks (Hintze and Adami http://front.math.ucdavis.edu/0705.4674) and investigated their underlying modularity. Still, many cell biological aspects like compartmentation and chemotaxis are not implemented. Together with implementing these artificial proteins many aspects of modularity and molecular functions can be investigated. The impact of compartmentation on modularity is of primary interest. Besides programming skills in C++, the student will learn a lot about graph theory, genetics and cell biology from a more theoretical point of view. Also, this project is a unique chance to obtain insights into artificial life combined with artificial chemistry.
Project 2: Evolution Experiments with Digital Organisms (Christoph Adami, Arend Hintze). In evolution, somewhere somehow haploid asexual organism became sexual and diploid. We are interested in the factors that influence this emergence. We already designed and started to implement a computational model system to study this topic. Preliminary results show interesting tendencies, but the final implementation is missing. Together with programming C++, a whole set of experiments need to be run and analyzed. The student will learn how to easily design experiments on his or her own and extend the experimental basis in this field. Besides programming skills in C++, the student will learn about sex and diploidity and also gain insights into experimental computational biology and artificial life.
Project 3: Topological Algorithms for Structural Genomics (Greg Dewey). As the number of protein structures continues to grow, structure comparison techniques have become an increasingly crucial bioinformatics tool. Because protein structures evolve more slowly than protein sequences, structure comparison can be used to assess distant evolutionary relationships and common functions for pairs that do not have high sequence similarity. Structure alignment is also a central tool for protein classification and structural genomic initiatives. Despite the importance of structure comparison, a number of fundamental issues remain unresolved. We are developing new algorithms and scoring systems for structural genomics. These algorithms are based on using topological measures of protein structures. By encoding topological measures into an alphabet, it is possible to convert structure alignment problems into sequence alignment problems. The advantage of this approach is that it allows us to use the mature and efficient algorithms that have been previously developed for sequence bioinformatics. This approach will be validated by benchmarking algorithm performance against existing structural bioinformatic algorithms.
Project 4: Inferring Gene Regulatory Networks in Breast Tumor Cell Lines (Greg Dewey). This work is a collaboration of Steve Ethier at the Karmonos Cancer Institute in Detroit that involves an analysis of microarray time series data and the inference of network structure from the data on normal and breast tumor cell lines. Time series data for the response of normal and cancer cells to an environmental perturbation are analyzed using a simple linear response theory. Using this simple analysis, hierarchical networks are seen for both cancer and normal cells. These networks both show hub-like structures centered on the expression of just a few genes. The identity of the hubs differs between the tumor lines and normal cell and the physiological significance of this difference remains to be elucidated. In addition to exploring the biological significance of existing results, we currently have a data from a number of different tumor cell lines that needs to be analyzed. This comparative information should be invaluable in identifying genes that are differential expressed between cancer and normal cells.
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Systems Biology in Model Organisms  Advances in genomics-, proteomics- and other “omics-” based technologies have resulted in the evolution of new approaches to address problems in modern biology. These new approaches are invariably interdisciplinary in nature, and require a combination of methodologies from molecular genetics, cellular biology, biochemistry, computational biology and bioengineering, although the specific combination depends on the problem at hand. The ultimate goal is to understand the molecular machineries behind life’s processes. Systems biology has many practical applications including the discovery of novel biomarkers and drug targets, the optimization of recombinant protein expression, and the ability to genetically engineer desired traits into an organism.
Project 1: Genomic and Proteomic Analysis of Yeast Meiosis-Sporulation (Animesh Ray). The budding yeast Sacharomyces cerevisiae is an excellent organism to study both cell development and cell division, since the environment of the cell and individual genes can both be easily manipulated. S. cerevisiae follows two alternative cell division pathways: mitotic division and growth, or meiosis and sporulation. Yeast sporulation is a developmental process in which diploid cells undergo meiosis to form haploid spores. It is initiated only when the cells are of the appropriate cell type, and are simultaneously starved for both glucose and nitrogen. Under these conditions, a developmental program is initiated, which involves a highly orchestrated set of chromosome dynamics and cell differentiation events. Many of these events during meiosis are common with repair of DNA due to damage and diseases (e.g., cancer and aging) in human. Thus, meiosis in yeast provides a general model system for studying gametogenesis and DNA/chromosome repair. We are characterizing the changing patterns of mRNA and protein profiles during various cellular landmark events in meiosis. This REU project involves measurement of DNA binding by proteins specifically induced in meiosis in wild type and meiosis-defective yeast strains, using DNA microarray technology.
Project 2: Improvement of the Pichia Pastroris Gene Expression System (James Cregg, Ilya Tolstorukov). This project in one part involves the construction of a new generation of P. pastoris recipient strains by molecular genetic methods, namely by knock-out of genes whose products are deleterious to recombinant protein production (e.g., proteases) and/or overexpress genes whose products may aid in recombinant protein synthesis (e.g., chaperones, protein disulfide isomerase). The target genes will be identified by analysis of the Pichia genome sequencing data and their sequences used to delete the gene from the P. pastoris genome or to overexpress the gene using standard yeast molecular genetic methods. Another part of the project is the construction of new expression vectors for Pichia pastoris. The modified strains and constructed vectors will then be tested for their effect on recombinant protein yields using reporter genes.
Project 3: Sterol Signaling in Plant Development (Kathrin Schrick). Sterols play a multifaceted role in eukaryotes, serving as components of cell membranes and precursors to steroid hormones. In humans the major sterol is cholesterol, which is essential to life, and has been the subject of 17 Nobel Prizes. In contrast, little is known about the roles of sterols in plant cells. Plants produce a complex mixture of sterols termed phytosterols, comprised largely of sitosterol, campesterol, and stigmasterol. The recent characterization of novel sterol biosynthesis mutants in our laboratory has led to the emerging view that sterols play critical roles in plant development. Sterol concentrations are highly dynamic during development, suggesting a link between sterol composition and signal transduction. Students will participate in our research program which focuses on functional genomics and proteomics approaches to elucidate the molecular basis of sterol signaling in plants using Arabidopsis as a model organism. One major focus is the identification of sterol-binding proteins. Putative sterol-binding proteins in plants include a family of homeodomain transcription factors having START (for StAR-related lipid transfer) lipid/sterol-binding domains. Our current studies address the hypothesis that START domains in homeodomain transcription factors control gene transcription by sterol binding, potentially revealing a molecular link between sterol metabolism and cell differentiation in plants. Another major focus of our laboratory is to reveal the molecular link between sterol biosynthesis and cellulose synthesis. Sterol composition is crucial for cellulose synthesis in vivo, suggesting that knowledge of sterol signaling pathways has applications in the production of biomass for alternative fuels. The long-term goal of our research is to functionally characterize sterol signaling pathways that define plant systems.
Project 4: Proteome Mapping of Aging in a Mouse Model (Deb Chakravarti, Bulbul Chakravarti). The proteome is the complete set of proteins present at any given time in a cell or tissue; its understanding is crucial since most cellular processes are carried out by proteins. The goal is to research the molecular basis of aging, the inevitable fate of all living organisms, at the level of the proteome. Using two-dimensional gel electrophoresis and mass spectrometry, proteome mapping of different organs of aging mice will be performed, with particular emphasis on the relationship between aging and the damages to proteins caused by reactive oxygen species derived from the oxygen essential for our survival. The participating student will be trained in current proteomic technology (two dimensional gel electrophoresis and/or mass spectrometry).
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Drug Discovery and Development  Advances in science and technology provide opportunities to better understand the cause of diseases and to develop treatments with improved mechanisms of action. Treatments of disease can range from small molecule drugs to peptide and protein pharmaceuticals, to stem cell therapy. At KGI, REU students have the opportunity to participate in the development of novel screening assays and instrumentation platforms, and in stem cell research.
Project 1: Cardiac Stem Cell Differentiation to Heart Cells (Ian Phillips, Yao-Liang Tang). Cardiac ischemia frequently results in irreversible damage to cardiomyocytes and cardiac function. A potential method to remedy myocardial damage is cell replacement therapy. Adult cardiac stem cells (CSCs) are multipotent cells residing in the heart and hold promise as a means to produce new cardiomyocytes. The project involves: a) extracting stem cells from heart tissue, and isolating and cloning pure lines; b) testing chemical inducers to differentiate the cells into heart cells; c) studying molecular changes during differentiation; and d) testing the functioning of the heart cells with immunocytochemistry and functional assays.
Project 2: Enzyme Kinetics Experiments within a Protein Microarray Format (Angelika Niemz, Ali Nadim). Protein microarray experiments are often limited to measuring expression levels or post-translational modifications of proteins within a complex proteome. Our goal is to enable miniaturized, high-throughput characterization of enzymatic activities in a gel-pad protein microarray format. In these studies, protein microarrays are fabricated by immobilizing enzymes within hemispherical acrylamide hydrogel pads on glass slides. Through mathematical modeling, we are able to predict the temporal and spatial evolution of a chromogenic or fluorogenic product within the hydrogel, as a function of gel pad geometry, substrate and product diffusion constants, and the Km and kcat of the enzyme. Experimentally, substrate is introduced into the microarray using a flow chamber, and product evolution is monitored under a microscope. Students with a background in biochemistry or bioengineering will have the opportunity to participate in the fabrication of microarrays and microfluidic components, and in performing enzyme microarray experiments. Students with a background in mathematical modeling will have the opportunity to participate in the development of analytical and numerical models for different experimental setups.
back to top Ethics and Business Research  KGI has a vibrant program of research in both ethics and industry dynamics within the life science industries. REU students may apply to work on directed projects supervised by KGI's ethics and business faculty. Business research at KGI is often linked to important public policy issues, such as ties between commercial biotechnology firms and university labs, cross-national comparisons of governmental policies towards the creation of life-science industries, or analyses of the development of regional biotechnology clusters. Students will gain experience in a variety of research methods appropriate to particular projects. These include: conducting literature and web-based research as well as interviews, assembling case studies to examine the interplay of business and ethical decision-making as it relates to the particular field under investigation, and deploying more quantitative research methods, such as bibliometrics and social network analysis.
Project 1: Careers, Commercial Biotechnology, and Competitive Lab Dynamics in the Life Sciences (Steven Casper). The project will explore how the emergence of commercial biotechnology has influenced the goals and organization of academic research labs in the life sciences. Much research has portrayed relationships between academic labs and firms in a negative light, suggesting that financial incentives offered by ties with biotechnology firms influence the research trajectories and goals of labs. Focusing in particular on the organization of large academic research labs and the career dynamics of scientists within these labs, the project will evaluate the proposition that financial ties are a secondary reason for the development of relationships between labs and companies: ties between labs and firms are only developed when such ties enhance the ability of labs to compete successfully in achieving major research discoveries in their scientific fields. Employment ties with major biotechnology firms and a record of founding spin-off companies can help a basic research lab recruit better junior scientists and, more generally, improve its competitiveness in conducting basic research. The project team will test this proposition through the use bibliometric research to examine and compare research outputs and career trajectories of scientists working within a relatively large number of academic research labs working within a life science discipline, such as cell biology.
Project 2: Creating Successful Biotech Clusters (Steven Casper). Why have San Diego and San Francisco been more successful than Los Angeles in creating a cluster of new biotech companies and attracting large pharmaceutical firms? This project is designed to understand the many factors that may contribute to or impede the growth of clusters of biotech enterprises and to use that knowledge to design appropriate policies that may stimulate the development of new biotech firms. It will have a particular focus on the key skills needed to fuel the growth of this industry and the way in which the labor market for this talent functions. We are especially interested in the problem of understanding why some clusters develop markedly higher innovative capacity than others - both the Los Angeles (LA) and San Diego (SD) clusters, for example, are successful in terms of employment and company creation, but the San Diego cluster appears to have a markedly higher performance in fostering radically innovative start-ups in new technologies. The goal of the project is to create a systematic comparison of cluster formation across California. The project will build upon a large dataset of company information and career histories of several thousand managers and scientists employed over the history of the California biotechnology cluster. This year's project will focus particular attention on developing data on the composition of the founding teams of California biotechnology companies and, using social network analysis tools, exploring whether the organization of social ties across founders differs across different areas of California in ways that could help explain the divergent trajectories of growth across Los Angeles, San Diego, and the San Francisco Bay area.
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