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Single Molecule Imaging and Tracking for High-Throughput Screening

Single Molecule Imaging and Tracking for High-Throughput Screening. Greg Bashford Dept. of Biological Systems Engineering. Outline. Proposal overview and goals NIH review Recent progress. HTS and Drug Discovery.

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Single Molecule Imaging and Tracking for High-Throughput Screening

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  1. Single Molecule Imaging and Tracking for High-Throughput Screening Greg Bashford Dept. of Biological Systems Engineering

  2. Outline • Proposal overview and goals • NIH review • Recent progress

  3. HTS and Drug Discovery • High-throughput screening (HTS) methods have been an area of growing interest for the discovery and characterization of new drugs. • The development rate of new pharmaceutical compounds in recent years has greatly accelerated. • Thus, there is a large backlog of potential compounds needing to be screened for their therapeutic potential. • Therefore, an obvious need exists for developing new and improved HTS techniques to mitigate this backlog.

  4. Goals and Objectives • Long-term goal: • Create novel (and accelerate conventional) rapid bioanalysis methods by capitalizing on image analysis • Objective of this application: • Use computer modeling to determine the expected effects of using single molecule imaging and tracking for applications such as HTS for pharmaceuticals

  5. Background • Fluorescence Correlation Spectroscopy The size of the compound affects its diffusion coefficient Binding is detected by a larger compound size Pictures from Stowers Institute for Medical Research

  6. An “Extension” of FCS • Instead of point detection – image over a larger field of view Imaging area Microfluidics flowcell Laser waist Multiple observations of single molecules are made simultaneously

  7. Single Particle Tracking (SPT) • Molecules are tracked across multiple image frames • Assumption: within each frame, any particle doesn’t move “much” (else blurring) Frame 3 Frame 2 Frame 1

  8. In Contrast to SPT… Forced flow • Molecules are driven through the field of view by forced flow • Pressure-driven, EOF • Molecules move “fast” with respect to one image integration time • Results in blurring, or a particle “streak” • Horizontal: diffusion Hypothesis: we can back-calculate diffusion information from the image streak

  9. Obj A Computer Simulation of SMD/SMI Flow: Pressure, Eph, EOF lem • Molecule transport • Flowcell interaction • Photophysics • Optics • CCD Detection • Noise Through-objective TIR CCD Detector

  10. Specific Aim 1 • Refine and optimize a computer model of single fluorescent molecules imaged within a microfluidicsflowcell • To add: • Molecule adsorption to flowcell wall • TIR intensity enhancement • Blinking • Readout blur • Updated objective, camera specifications • Compare with model system – DNA/SfiI complex

  11. Specific Aim 2 • Develop image-analysis based algorithms for measuring molecular interactions of ligand-receptor pairs from CCD images • First, determine the “best” way to measure diffusion

  12. Specific Aim 2 • Develop image-analysis based algorithms for measuring molecular interactions of ligand-receptor pairs from CCD images • Next, determine how best to discriminate between species of differing diffusion

  13. Specific Aim 2 • Develop image-analysis based algorithms for measuring molecular interactions of ligand-receptor pairs from CCD images • Finally, determine the limits of measuring diffusion

  14. Specific Aim 2 • Also, test the limits of feature identification • How many molecules visible in this frame?

  15. Specific Aim 3 • Develop protocols in which the algorithms from Specific Aim 2 can be used to increase throughput and information content (compared to FCS) • For example: Consider a sample composed of a mixture of two different types of single molecules that have different diffusion constants - the goal of the measurement is to determine the fraction of each species

  16. Specific Aim 3 • Develop protocols in which the algorithms from Specific Aim 2 can be used to increase throughput and information content (compared to FCS) • Parameters to study: • Bulk flow • Ratio of diffusion coefficients • Concentration ratio of two species • Number of frames used in analysis

  17. NIH Review • Significance: “This project, if successful, could greatly increase the rate of high-throughput screening and improve its efficiency and potentially its success rate … The techniques could also have broader applications for the study of the interaction of ligands with intact cells.” • Innovation: “This is a very innovative approach that will build a model for single molecule imaging that can improve screening and analysis of molecular interactions.” • Investigator: “The project investigator is highly skilled and has the resources to complete this project.” • Environment: “The environment is excellent, with a good mentoring program and the resources to perform the development. There is good complementarity to other COBRE projects.” • Section Score: Outstanding (No changes recommended)

  18. Current Work • Starting on Specific Aim 1 (refine model) • Hosted visit from single-molecule detection consultant (Dr. Lloyd Davis) • Visited with Dr. Lyubchenko at UNMC • Goals for Spring 2009 • Incorporate changes to model to allow for diffusion measurement • Submit publication with Dr. Davis

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