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REU Research Projects
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
Biomarker Research
The Center for Biomarker Research (CBR) at Keck Graduate Institute is dedicated to education and applied research activities that expand knowledge and development of biomarkers as a tool for diagnostics, drug development and the practice of medicine in the 21st century. Research projects offered involve collaborations between Keck Graduate Institute, Harvey Mudd College (HMC), Industry (Beckman Coulter), and the National Organization of Rare Disorders (NORD)). Projects are designed to train undergraduate students to become translational scientists and to discover and commercialize new disease-specific biomarkers. We are setting up a flow cytometry facility on the KGI campus. Research in the facility will focus on development and validation of biomarker assays for rare diseases. Participating students will learn to operate in a Good Laboratory Practice (GLP) facility that handles human samples, an experience that provides excellent preparation for the industrial laboratory work environment. Through exposure to this facility, the students will gain valuable hands-on experience in quality assurance, assay validation and regulatory compliance—areas that are not commonly addressed in an academic setting.
Project 1: Identification of biomarker panels for diagnosis of disease (Jim Osborne, Craig Adams). Biomarkers are measurable entities that are used to diagnose disease and monitor clinical responses to therapy. Many diseases are difficult to diagnose and patients with the same diagnosis often respond differently to a given therapy. Most approved diagnostic tests are based on a single biomarker. The Center for Biomarker Research (CBR) is investigating the use of biomarker panels to better diagnose disease and stratify patient populations for selection of therapy. Flow cytometry is a very powerful technique for measuring multiple markers on the surface and interior of cells. Nucleic acid and protein assays can also be multiplexed in a flow cytometer by designing assays on multicolored beads. CBR is developing and validating protocols using multiplex flow cytometry to investigate biomarker panels for diseases that have good therapeutic options, but are difficult to diagnose.
Project 2: Biomarker for Diagnosis and Monitoring of Hereditary Inclusion Body Myopathy (Jim Osborne, Craig Adams). Hereditary Inclusion Body Myopathies (HIBM or h-IBM) are a diverse group of muscle wasting disorders that share similar histopathology with sporadic Inclusion Body Myositis (s-IBM) and senile plaques seen in Alzheimer's brain disease. Various forms of HIBM are genetically and clinically diverse, with the autosomal recessive form (IBM2) as the most common. It usually affects young adults and often leads to severe disability and confinement to a wheelchair. IBM2 is also known as Quadriceps Sparing Myopathy (QSM), Distal Myopathy with Rimmed Vacuoles (DMRV), or Nonaka's Myopathy. As in many rare disorders, for IBM2 there is a significant need to develop biomarkers that can be useful in clinical and molecular evaluation of the disease. Such biomarkers will allow us to determine the effectiveness of promising therapeutic intervention currently in early clinical trials, which may translate to significant cost and time savings. Undergraduate students will work with researchers from the Center for Biomarker Research at KGI and from the HIBM Research Group (HRG), a California non-profit public benefit corporation, in a team oriented effort to develop and validate IBM2 specific biomarkers
Project 3: High throughput automated assay optimization using Design of Experiments (DOE) (Angelika Niemz, Jim Osborne). Assay optimization required for drug or biomarker discovery, for clinical diagnostics or for general research applications requires scanning of a large parameter space. One-parameter-at-a-time studies are often ineffective and can produce misleading results. High throughput automated multi-parameter optimization using DOE coupled with liquid handling and automated assay optimization software can facilitate identification and optimization of critical factors in a minimal number of runs. Undergraduate students will work closely with KGI researchers on designing suitable experiments using the software package Design Expert (or other suitable statistical analysis software that supports DOE), then would learn how to implement and run these experiments, which involves learning how to program, set up, and run the experiments using the BioMek liquid handling robot at Keck Graduate Institute, and how to use the Sagian Automated Assay Optimization software package that interfaces with the BioMek. Students will then process the raw data into a format that can be fed back into the DOE model, and will perform data evaluation using Design Expert, which will require an understanding of the the statistical and mathematical concepts underlying DOE. Students will work on fractional factorial experiments to identify the most relevant assay parameters to be optimized, and will perform response surface modeling experiments to optimize the significant parameters.
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 testing. 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: Isothermal DNA Amplification for Rapid Diagnosis of Infectious Diseases (Angelika Niemz). Isothermal DNA amplification reactions can facilitate rapid and sensitive DNA detection, requiring minimal instrumentation, and are therefore especially suited for clinical diagnosis of infectious diseases in low resource settings. The Exponential DNA Amplification Reaction (EXPAR) developed at KGI enables >10^6 fold isothermal amplification of short oligonucleotides in less than 10 minutes through combining DNA polymerization with single strand nicking. We have developed a two stage version of EXPAR coupled with lateral flow to facilitate simple and rapid point-of-care based detection of infectious pathogens. Our current assay enables diagnosis of Herpes Simplex Virus (HSV) from swab samples of herpetic lesions. We are working on establishing similar assays for detection of Mycobacterium tuberculosis from sputum, and for HIV viral load monitoring. TB and HIV are significant global health burdens, and better diagnostic technologies can facilitate improved patient treatment and containment of further spread. Students with a background in molecular biology, biochemistry, or bioengineering will have the opportunity to participate in the development ant optimizing of these assays.
Project 2: 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. Undergraduate students will participate in a team effort to develop a cartridge containing flexible pouches, with passive valves and integrated positive-displacement pumping for execution of medical diagnostic tests (in particular the assays developed under Project 1) in an inexpensive, self-contained format. We have established proof of principle for key components of this cartridge. Students will be involved in combining these components into a functional system, which entails pouch and cartridge fabrication, testing, and theoretical modeling of the system.
Project 3: Building devices for point of care nucleic acid based infectious disease testing (Angelika Niemz, Jim Sterling). The goal of the proposed project is to design and build a handheld, battery operated device that interfaces to a disposable cartridge in which isothermal DNA amplification takes place, coupled to visual detection using nucleic acid lateral flow (see projects 1 and 2). We have build and tested a first version of this device, which contains a heater with control circuit, connected to an external power supply. The goal of this project would be to develop the next iteration of this device, which would contain an embedded microprocessor to control the heating and timing of test execution, with a simple user interface (buttons and indicator LEDs). Another aspect involves making the system battery operated. Students with a strong EE background are sought to contribute in developing the required device electronics (in collaboration with KGI and a small local company). Students will further fabricate device prototypes through CAD-CNC machining and rapid prototyping.
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.
Computational and Systems 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 the speed of evolution (Christoph Adami, Arend Hintze)The evolution of complexity does not proceed at a constant rate, but rather, periods of intense evolutionary activity are separated by long periods of stasis. During the periods of fast adaptation, evolution appears to proceed faster than standard models would predict. Intense computer simulations have revealed a new mechanism that predicts that the evolutionary rate is elevated during the non-equilibrium periods where beneficial mutations go to fixation. In conjunction with our ongoing efforts in computational evolution, we want to investigate this phenomenon using real organisms in the lab by performing in vitro evolution. This is interdisciplinary project can enable a diligent and motivated student to learn laboratory techniques as well as evolutionary theory, including population genetics and dynamics.
Project 2: The evolution of cooperation and punishment (Christoph Adami, Arend Hintze) For more than 30 years now, social sciences and evolutionary biology have tried to understand how cooperation (a strategy that is vulnerable to cheating and defection) can evolve, and be maintained. We are trying to understand why particular strategies evolve under particular conditions, in various games. We have simulations where thousands of individual strategies compete against each other in games such as the iterated prisoners' dilemma, the "public goods" game, and the "centipede" game, and where the strategies are genetically encoded so as to allow a realistic implementation of biological evolution. Interested students with basic knowledge in C++ and Matlab will have the opportunity to learn about evolutionary game theory and social dilemmas, and will conduct experiments in computational biology, using simulation techniques and parallel computing.
Project 3: 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.Ethics and Business Research
Project 1: When does it make sense for society to cure rare diseases? (Steve Casper) Within the United States there are over 7000 "rare disease", categorized as an ailment affecting less than 200,000 people. Developing cures for these diseases is increasingly possible due to advances in biotechnology, but usually costs tens of millions of dollars. The US Orphan Drug Act grants special rights to companies researching new therapies for rare diseases. Companies receive market exclusivity for seven years and tax incentives designed to reduce the cost of clinical trials. Moreover, governments and insurance companies have agreed to pay extremely high prices for life-saving therapies: the biotechnology firm Genzyme markets a life saving cure for Gaucher's disease at over $200,000 a year for life-long treatment. Spurred by these incentives, numerous biotechnology companies have in recent years launched drug development projects aimed at rare diseases. The US Orphan Drug Act is an example of "market making" or "pull" policies, attempting to create a market for neglected disease research that previously did not exist. Another approach to policy is to move research for neglected disease out of corporate labs and into public research universities and non-profit organizations. Through passing on successful pre-clinical projects to biotechnology companies, academic research reduces the failure risk facing companies, strengthening the incentive to start development projects aimed at rare disease. Through examining several rare disease drug candidates currently in development, this project will help carefully explore the economic and social incentive structures facing companies, universities, and advocacy groups within several rare disease fields. The research will help explore the extent to which society benefits from public policy towards rare disease and help policy-makers understand the extent to which success in rare disease fields is primarily the result of "market making" policies or also influenced in important ways by public-private partnerships.
Project 2: Creating Successful Biotech Clusters: Network Visualization Project (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. The goal of this Summer's project will be to use geographical mapping software (ESRI/Arcview) to create visual maps of the emergence of biotechnology clusters in San Diego, San Francisco, and Los Angeles. We will develop geographic maps plotting the emergence of companies in each region from 1980 to 2005. We will also learn how to overlay social networks linking scientists and managers of these companies within the maps. A goal of the project is to help explore whether geographical proximity helps helps drive collaborative networks across biotechnology firms, networks that are widely seen as important in developing regional technology clusters such as Silicon Valley. This will be a computer intensive project. While computer programming skills are not required, students must be very willing to learn how work with fairly complex software environments.