Automatic Partiicle Tracking Software USE ER MANUAL Update: May 2015

Transcription

1 Automatic Particle Tracking Software USER MANUAL Update: May 2015

2 File Menu The micrograph below shows the panel displayed when a movie is opened, including a playback menu where most of the parameters can be controlled. Open: open the image sequence Open Project: Use this command to open an existing project (a file corresponding to a previous analysis of a movie) but you need to first open the image sequence corresponding to this project and to click on it. Save Project: Use this command to save the current project. All the parameters that have been used for tracking and analysed trajectories are saved in this file. Save Frame as bitmap: The current frame will be saved as a bitmap (bmp) file. Open Background: the image sequence view will be replaced by a previously saved image (bmp file). The trajectories were superimposed on this background (see below).

3 Setting parameters SETUP menu Video rate (s): specify the video rate of your captured movie. Resolution (μm): size of one pixel. Dim Part. (μm): estimated size of the particle you want to track. Max part. disp. (μm) : maximum distance covered by any of tracked particles between 2 consecutive frames (measured from the centre of the PSF). Death (frames): determines the maximum number of frames during which a tracked particle can be lost (above this value, the tracking is aborted). Short trajectory (frames): the minimum number of consecutive frames that validates a trajectory. Eccentricity max: a particle is considered as valid if its eccentricity is smaller or equal to this value (1 corresponds to the value for a round-shaped PSF). TRACKING menu In Tracking mode, the Gauss filter and the remove background function are activated by default.

4 Tracking mode: should be ticked for tracking. For a project, if you want too move through the video sequence without any lost of previously tracked trajectories, this function should not be activated (otherwise all trajectories after the cursor will be lost).. Track selected particle only: track only the selected particle; the other trajectories are not affected. Search new particle: automatically search new particles duringg the tracking. Automatic delete short trajectories: automatically delete shortt trajectories as specified in the setup menu. Manual delete short trajectories: you can delete individual trajectories at t the end of the tracking. Gauss filter: a spatial band pass filter smoothing the image andd subtracting the background. Removee background: if non-activated, the fitting procedure will be slightly affected but visualization of the trajectories will be accelerated. As shown below the track of the selected particle is white, the others o are blue. Selected particle. DISPLAY menu Peak zone search: : display a circle aroundd the particle corresponding to thee maximal displacement of the particle ass specified in the setup menu. Display PSF: the tracking particle is displayed by the 3D Gaussian shape of its signal. Invert: toggle before processing if the particles are darker than the background. View background: The movie is replacedd by a previously saved image (bmp file). Trajectories are superimposed on this new background.

5 ALEX menu When using laser-alternating excitation (Kapanidis et al, 2005), the video rate can be synchronised with the alternation frequency between lasers (select Alex 1-2 or Alex 2-1 depending on the initial excitation, right or left channel in dual-view microscopy). PLAYBACK RANGE menu The cursor is used for selecting the sequence of frames that you want to visualize. Save as avi: when Play is toggled, the video sequence and trajectories are recorded as an avi file. The name of this file is the same than the input file but with avi extension. PLAYBACK DELAY menu The value corresponds to the video rate and can be adjusted with the cursor. NUMBER OF PARTICLES menu: display the number of particles currently analyzed. Zoom function To zoom in a specific area, click and drag with the mouse to select the region and then click on the zoom function in the toolbar (see red circle). Scroll bars appear on the edges of the movie picture. Colours

6 The colour bar contains 3 buttons for different colour scales that are displayed on the left of the video frame. Contrast and/or threshold can be changed by moving cursors (triangles) on the colour scale (left click). Particle detection and selection Particles can be automatically detected using the Sel button. A dialog box is then opened (see the figure below). A round shaped thin line encircles automatically detected particles. If you want to modify the detection threshold, move the cursor Filter Particles (right menu). This new threshold will be used for particle detection during the analysis (for automatic detection of new particles with this threshold, do not forget to toggle Search new particle in the setting parameters menu). Particle detection can also be performed in a defined area that can be selected with a left-click inside the video frame (maintain the click during the selection procedure). The selected area can be shifted on the right or left by clicking on the button <-> (see the red circle below)

7 The Adapt contrast region button (blue circle above) increases the contrast in regards to the minimal and maximal values of the pixels contained in this region. Particles can also be manually picked up using the menu available with a right-click (see below) Menu: right-click on the particle you want to select and chose the function by leftclicking. Add Particle : left-click at the position where you want to add a new particle. Remove Particle : left-click on the particle to remove it. Select Particle : left-click on the particle to select it. Selection and modification of trajectories Theses functions only concern the currently selected particle Options are available in the right button menu. Go to end trace: simply click on the trajectory. Go to corresponding frame: click on the connection corresponding at the desired frame. Delete connection: simply click on the connection. Add connection: go to the previous frame just before adding connection, click at the desired new position. Move connection: click on the connection, and move at the desired new position

8 3D view of trajectories Display PSF The center of peaks was determined with sub-pixel resolution by fitting a two-dimensional elliptical Gaussian function with a background value. The equation of 2D Gaussian curve is of the general form: 2 2 F(x, y) = z + A*exp( 0.5* x xc y yc 0 + σ x σ y ) where x c and y c are the coordinates of the center of the peak and Zo the background value. You can display the result of the 2D Gaussian fit for selected particles.

9 ANALYSIS This menu is accessible by clicking on the curve (red circle above). Analysis is performed by default on the current selected particles. If you want to analyze an average of all peaks, toggle All Peaks in the menu. Different parameters can be visualized (only one at a time using the upper menu): MSD/ MOTION TYPE (automatic detection of motion modes using a neural network, see below)/ INSTANTANEOUS DIFFUSION/ INTENSITY/ VELOCITY/ TRAJECTORY/ LIFETIME; Each parameter can be modified on the fly and data can be visualized as histogram (toggle histogram). Important - Left clicking on the particle displays a cursor with x and y values. - You can zoom into a specific rectangular area of the graph by simply left clicking and dragging to draw a rectangular region. MSD (Mean Square displacement) The MSD fit is done according to the equation: N 1 n MSD(nδt) = {[ x( jδt + nδt) x( jδt) ] + [ y( jδt + nδt) y( jδt) ] } N 1 n j=1 where δt is the time interval between two successive frames, x(t) and y(t) are the particle coordinates at time t, N is the total number of frames, n is the number of time intervals (Sheetz et al, 1990; Qian et al, 1991; Kusumi et al, 1993). You can fit MSD with different models to determine diffusion parameters: Simple diffusion mode: MSD (Δt) = 4DΔt Directed diffusion mode: MSD (Δt) = 4DΔt + v 2 (Δt) 2 Confined diffusion mode: MSD (Δt) = (1/3) L 2 [1 exp (-12DΔt/ L 2 )] where v is the transport velocity, L 2 the area of a squared confined region and D the diffusion coefficient. The value of the cursor % corresponds to the percentage of points used for the fit (see below).

10 Detection of the motion mode using a back-propagation neural network We developed a new algorithm based on a back-propagated neural networkk to automatically detect modes of diffusion (typically Brownian, confined and directed) within a trajectory (identified segments appear in bold)(dosset et al, submitted).

11 Edit (red circle above): edit the calculation of the diffusion coefficient (D 2-4 ) for one or all the trajectories. Each trajectory can be split in segments according to the different modes of diffusion detected. The output code is 0 for Brownian, 1 for confined, 2 for directed, 3 for a mixture of Brownian and confined motion, 4 for a mixture of Brownian and directed motion, 5 for a mixture of confined and directed motion, and 6 for a mixture of the 3 types of motion. Intensity

12 Display the plot of the intensity of the pixel at the maximum of the Gaussian peak over time along the trajectory. Intensities correspond to filtered data or to raw data (if you toggle raw data ). Intensities Sum Corresponds to the sum of the intensities of the pixels composing the Gaussian peak (depend on the defined particle size). Of note, when using dual view imaging, the intensities window display the intensities corresponding position on the left window (left part of the CCD detector). Velocity Displays the plot of the velocity of particle over time along the trajectories.

13 Lifetime Displays the particle lifetime of analysed particles. Trajectory Display the coordinates of a selected trajectory

14 P(r) - Cumulative distribution function of the square displacements The lateral diffusion motion of a particle characterized by a diffusion coefficient D is described by the cumulative distribution function of the square displacements r 2 (Anderson et al., 1992): P(r 2,tlag) =1 exp r 2 2 r (tlag) (1) 0 where P(r 2,t lag ) is the probability that a particle starting at the origin will be found within a circle of radius r at time t lag. If there are two types of mobility for a molecule, the cumulative probability distribution function for the square displacements r 2 becomes: P(r 2,tlag) =1 α.exp r r (tlag) + (1 α).exp r 2 2 r (tlag) 2 (2) Equation 2 corresponds to a fast and a slow mobility component with diffusion constants D 1 and D 2, and fractions α and (1 - α), respectively (Schütz et al., 1997). Analysis of two populations of molecules In this example below, the distribution was fitted according to one-component model (left) and to two-component model (right) for a defined t lag. The fit with the two-component model describes the cumulative probability distribution significantly better than the fit with onecomponent model. One can assess that there are two types of mobility for these molecules.

15 Rall Fit of the square displacement distribution corresponding to the characteristic MSD for the fast ( r 1 2 ) (left) and slow ( r 2 ) (right) diffusing population of molecules for each tlag according to Equation 2. In this example, MSD data of the fast-diffusing fraction were fit according to a direct diffusion mode and MSD data of the slow-diffusing fraction were fit according to a simple diffusion mode. Non-valid fitted points can be deleted by right-clicking on them. The analysis can be extended to three-component model. Calibration for dual view imaging - You have to first open a reference file with fluorescents beads. - Select a series of particles in the left window by right-clicking on particles and then select the corresponding particles in the right window. A minimum of 3 peaks is necessary (in the simple case of shift). - Select the distortion parameters to fit.

16 - Click on the Fit button. Positions of particles for all the selected pairs of peaks are used to calculate a transformation matrix. The transformation is applied on the right window. Traces-> window1: if selected, the modified position of peaks on the right window is displayed in the left window to evaluate the transformation. - Save the transformation parameters on a file. When required, you can open the transformation file after downloading the movie and parameters are then applied to the frames sequence file.

17 References Anderson, C. M., G. N. Georgiou, et al. (1992). Tracking of cell surface receptors by fluorescence digital imaging microscopy using a charge-coupled device camera. Low- density lipoprotein and influenza virus receptor mobility at 4 C. J. Cell Sci. 101: Kapanidis, A. N., T. A. Laurence, et al. (2005). "Alternating-laser excitation of single molecules." Acc Chem Res 38(7): Kusumi, A., Y. Sako, et al. (1993). "Confined lateral diffusion of membrane receptors as studied by single particle tracking (nanovid microscopy). Effects of calcium-induced differentiation in cultured epithelial cells." Biophys J 65(5): Qian, H., M. P. Sheetz, et al. (1991). "Single particle tracking. Analysis of diffusion and flow in two-dimensional systems." Biophys J 60(4): Schutz, G. J., H. Schindler, et al. (1997). "Single-molecule microscopy on model membranes reveals anomalous diffusion." Biophys J 73(2):