Single Molecule Imaging and Tracking for High-Throughput Screening

Greg BashfordDept. of Biological Systems Engineering

Outline

Proposal overview and goalsNIH reviewRecent progress

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.

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

Background Fluorescence Correlation Spectroscopy

Pictures from Stowers Institute for Medical Research

The size of the compound affects its diffusion coefficientBinding is detected by a larger compound size

An “Extension” of FCS

Instead of point detection – image over a larger field of view

Laser waist

Imaging area

Microfluidics flowcell

Multiple observations of single molecules are made simultaneously

Single Particle Tracking (SPT)

Molecules are tracked across multiple image frames

Assumption: within each frame, any particle doesn’t move “much” (else blurring)

Frame 1 Frame 2 Frame 3

In Contrast to SPT…

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 streakF

orce

d flo

w

A Computer Simulation of SMD/SMI

Obj

CCD Detector

lem

Flow: Pressure, Eph, EOF

Through-objective TIR• Molecule transport• Flowcell interaction• Photophysics• Optics• CCD Detection• Noise

Specific Aim 1 Refine and optimize a computer model of

single fluorescent molecules imaged within a microfluidics flowcell To add:

• Molecule adsorption to flowcell wall• TIR intensity enhancement• Blinking• Readout blur• Updated objective, camera specifications

Compare with model system – DNA/SfiI complex

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

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

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

Specific Aim 2

Also, test the limits of feature identification How many molecules visible in this frame?

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

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

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)

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