Las prácticas lectoras y los Nuevos Estudios de Literacidad

Data was acquired in the form of movies using the Andor SOLIS software (V4.15, An- dor). Thereby, the electron multiplier gain of the EMCCD camera was enabled and set to 225, the pre-amplifier gain was set to 5x and the readout rate was usually set to 3 MHz at 14 bit. Generally, in smFRET experiments for the NPS analysis of Pol II open complexes (section 3) and of Chd1-nucleosome complexes (section 4.4), shortsif-movies were recorded with a total duration of 40 s and an integration time of 100 ms per frame (10 Hz frame rate, 400 frames). However, when nucleosome remodeling by Chd1 was investigated (section 4.3), long movies were acquired with a total of 1200-2000 frames to follow the FRET dynamics over an extended period of time. The integration time was set to either 100 ms yielding a total movie duration of 120-200 s, or, in order to observe faster dynamics, to 33 ms resulting in a total movie duration of 40-67 s. Long movies were saved astif-files due to the smaller size compared tosif-files.

The acquired data was analyzed using two different custom-written MATLAB (The Math- Works) programs. Shortsif-movies were processed and analyzed with the softwareSM FRET V5.7 written primarily by the former PhD student Robert Lewis and a very de- tailed description of the software can be found in his dissertation [196]. Longtif-movies were processed and analyzed with the softwareTrace Intensity analysis(TRACY), which was developed in the laboratory of Prof. Don Lamb (LMU Munich) by the PhD students Gregor Heiss and Martin Sikor. An elaborate description of TRACY can be found in the PhD thesis of Gregor Heiss [201].

Both programs had a similar workflow with a fully automated routine to find FRET pairs, extract fluorescence intensities of donor and acceptor fluorophores, calculate the local background and finally correct the fluorescence intensities. Subsequently, individual FRET pair fluorescence trajectories could be examined manually and FRET efficiency trajectories were computed for selected traces. In the following, I will describe in more detail the different steps of the workflow, thereby addressing differences between the two analysis programs.

Mapping

In the used TIRF setup, the fluorescence signals of donor and acceptor were spectrally separated with the help of dichroic mirrors and the separated images were projected onto different regions of the EMCCD chip (or later during this work onto two different cameras). Therefore, the first step of data processing was to overlap the images of both channels. Since non linear distortions introduced through optical abberations were always present, complete overlap could only be achieved by application of an image transformation map

2.3 Acquisition, processing and analysis of smFRET data

consisting of translation and dilation operations. To create such map, fluorescent beads with a broad emission spectrum, which could therefore be detected in both channels simul- taneously, were immobilized in the measurement chamber and imaged. In the resulting images of both channels, fluorescent spots were localized and spots belonging to the same molecule were identified. From matching pairs of fluorescent spots, a transformation map was generated. The identification of corresponding fluorescent peaks was done manually in the SM FRET program, but automatically with the option to manually interfere in

TRACY.

Identification of molecules

In the next step, a peak-finding algorithm was applied to detect the positions of single fluorescent molecules in the movies. Slightly different strategies were applied by the two software solutions. InSM FRET, the first 25 frames of the acceptor channel and frames 16-38 of the donor channel were averaged and the absolute minimum of counts per pixel of the entire movie was subtracted from each pixel. The local background was determined by identifying the local minimum in each square of a 16 x 16 pixel grid and this coarse grid of local minima was homogenized through a 20 x 20 pixel image filter and subtracted from the actual image. After scaling of intensities to a range from 0-255, the image was scanned pixel by pixel and all intensities below a certain threshold intensity (manually selected, between 95 % and 99.5 % of the absolutely highest intensity) were set to 0. Then, the image was scanned by a 7 x 7 pixel mask box to identify the location of local maxima with intensities higher than the threshold. Molecules that did not have a round shape or were in proximity to another molecule were discarded. It is important to note that the search for molecules was performed in the red acceptor channel after green excitation. (In ALEX movies, molecules were searched in the red channel after red excitation and in the red channel after green excitation and only if a molecule was present in both, it was considered.) The corresponding molecule in the donor channel was determined after application of the transformation map. In turn, in theTRACY software, a threshold was directly applied to the averaged image (average over a user-defined number of frames) of donor and acceptor channel by setting all but the 5 % brightest pixels to zero. Within this threshold image, the pixels with maximum intensities were identified as the center of molecules. This peak search was performed in both, donor and acceptor channel and only those molecules were considered that were found in both channels and could be overlaped using the transformation map. In the case of ALEX movies, acceptor molecules were searched for in the red channel after red excitation (direct excitation frames).

This deviation in the peak-finding algorithm represented the major difference between the two analysis programs. As a consequence, SM FRET was found to be better suited to the analysis of samples with a low number of molecules exhibiting FRET and noisy signal. Another difference between both programs was that SM FRET analyzed each movie as a whole, whereasTRACY divided each movie into segments that were analyzed

Figure 2.3.1.:Exemplary static FRET time trajectory with all parameters used forγ- andβ- factor determination. Fluorescence intensities of donor (green) and acceptor (red) are shown together with theγ-corrected total intensity (black).

sequentially. Therefore,TRACYwas better suited to the analysis of long movies recorded in the case of bright, long-lived molecules.

Extraction of fluorescence intensity time traces

In the next step, the intensity time traces of donor and acceptor fluorescence were ex- tracted. InSM FRET, the intensities within each 7 x 7 pixel box were summed up for each frame for donor and acceptor and corrected by subtracting the local background. InTRACY, the counts within a circular area (radius 3 pixels) around the detected max- ima were averaged and background corrected by subtracting the average counts of a ring around the molecule (3 pixels inner radius, 5 pixels outer radius).

Calculation of corrected FRET efficiencies

The FRET efficiencyEof each individual FRET pair can be calculated from the background- corrected fluorescence intensities of the donorID and the acceptor after donor excitation

IA as

EFRET=

IA−β·ID

IA+γ·ID

. (2.12)

Theγ-factor accounts for the relative detection efficiencies (ηA and ηD) in the different channels and for differences in the quantum yields (QA and QD) of acceptor and donor

2.3 Acquisition, processing and analysis of smFRET data

and is given by

γ= ηA·QA

ηD·QD

. (2.13)

It can be determined experimentally by comparing the fluorescence intensities before (I) and after (I0) acceptor bleaching (Figure 2.3.1) as

γ= IA−I 0 A I0 D−ID = ∆IA ∆ID . (2.14)

The β-factor accounts for the leakage of donor emission into the acceptor channel and can be expressed as β= I 0 A I0 D . (2.15)

Both correction factors were determined experimentally for each individual FRET pair. In traces, where the acceptor bleached before the donor,γandβcould be calculated from the respective time-averaged fluorescence intensity signals before and after acceptor bleaching. The corrected total intensity has to be constant until the donor bleaches (Figure 2.3.1, lower panel). TheSM FRET software only allowed for the analysis of traces, in which the acceptor bleached before the donor. Traces, in which the acceptor did not bleach before the donor, were discarded. In addition, for each molecule a constantγ-factor was assumed and thus, traces that showed dynamics in FRET could not be analyzed since theγ-factor is likely to change when the local environment of the fluorophore alters due to conformational dynamics. However,TRACY allowed for the analysis of static as well as dynamic FRET traces. For static traces, a constant γ-factor was assumed and the correction factors were determined as described above. For dynamic traces, the γ-factor was obtained by minimizing the standard deviation of the total intensity to fulfill the following equation

β= d

dγstd(IA+γ·ID) = 0. (2.16)

Finally,TRACY also allowed to include molecules that showed a static signal, but donor bleaching before acceptor bleaching. For such molecules,γandβcannot be determined, however in this case the average values from other molecules, for which the correction factors could be determined, was used to calculate the FRET efficiencies.

In the calculation of FRET efficiencies, direct excitation of the acceptor by the green laser was neglected, since it was less than 2% of the donor intensity and therefore including a correction factor did not alter the computed FRET efficiencies.

FRET efficiencies were calculated for every time point of a time trace, in the case of static traces after filtering the original data set using a 5- or 10-point sliding average filter. For every molecule, also a mean FRET value was calculated. From the FRET efficiency data,

”framewise” FRET efficiency histograms including every time point of several molecules as well as ”moleculewise” FRET efficiency histograms including the average value for each molecule were prepared. Finally, histograms were fit with one or more Gaussians and the maximum FRET efficiency as well as the standard error was extracted from the fit. A more detailed description of the way smFRET data was acquired and analyzed in the individual studies of this work can be found in the experimental procedure sections 3.6 and 4.6).