Small forces – Big results Abhijit Sarkar Assistant Professor Physics Department The Catholic University of America Washington D.C.

Basic Principle m F Aspiration Pipette N S z x y Not to scale Top View of Flow Cell Bead diameter ~3µm Bead-to-Magnet Distance 0µm to 3500µm

Sample Cell with Microspray Pipette Aspiration Pipette m z x y Not to scale 1mm Protein Microspray Needle

CCD 3D Electronic Micromanipulator PC with Labview 3D Hydraulic Micromanipulator Objective 40X, 0.65NA Light Source Condenser Micropipettes Chamber Stage DNA Syringe Pump

Lambda DNA 50 kbp Anti-DIG DIG Avidin Biotin Putting Handles on DNA

L 0 = 16.4µm, b (persistence length) = 50nm, K 0 = 1000pN Force-Extension Measurement for Single DNA Molecule

Brownian Fluctuation Method f xx Stiff Pipette Calculate gradient over image Diffraction around bead produces a central peak and series of concentric circles of decreasing gradient intensity Detecting these concentric circles can then be used to obtain a most-likely bead center Allows sub-pixel determination of bead center (accuracy on order of 10nm) Force & Extension Measurements

Stokes Law Force Calibration m m m NS F Not to Scale Stokes Drag Force Law mmm

Grab frame and crop Convert to 8-bit grayscale with bright beads Apply filter to eliminate background Search for peaks Need to follow beads over time – which bead is which? Bead Velocity Measurements

Crocker algorithm – proved inefficient at high force, when bead displacement approaches bead separation Constraint of minimizing negative y-velocity Constraint of minimizing x- velocity deviation Iterative ranking of bead assignments consistent with these constraints – usually unique back-check to identity assignments Bead Tracking Method

Nucleosome Formation & Rupture Under Tension Single DNA Molecule f Nucleosome Formation N  l ~ N x 50 nm f Nucleosome Rupture Nf*  l =  G Predicted f* ~ 1.5 pN f*f*

Nucleosome Formation and Rupture

Nucleosomes Under Moderate Load f ~ 6.5pN

Start with extension as function of time Edge preservation is critical Red is raw data - Blue is Bilaterally filtered data Finding Nucleosome Pop-off Events Microns Time