Feb 18, 2024
Version 2
Multi-parameter confocal TCSPC spectroscopy analysis V.2
This protocol is a draft, published without a DOI.
- 1University of Pennsylvania
Protocol Citation: Amber Yanas 2024. Multi-parameter confocal TCSPC spectroscopy analysis. protocols.io https://protocols.io/view/multi-parameter-confocal-tcspc-spectroscopy-analys-c9czz2x6Version created by Amber Yanas
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
We use this protocol and it's working
Created: February 16, 2024
Last Modified: February 18, 2024
Protocol Integer ID: 95353
Funders Acknowledgements:
Yale E. Goldman
Grant ID: R35GM118139
Abstract
The following outlines the analysis of data generated by multi-parameter confocal time-correlated single photon counting (TCSPC) microscopy and spectroscopy (MicroTime-200; PicoQuant, GmbH).
Conversion of .ptu to .hdf5
Conversion of .ptu to .hdf5
PQ_To_hdf5_All.ipynb Use program: PQ_To_hdf5_All.ipynb
Enter pathname and run all to convert files from .ptu to .hdf5
A new folder will be created with these hdf5 files
a. Hint – convert to hdf5 in bulk to save time
Processing .hdf5 files for burst analysis and FRET
Processing .hdf5 files for burst analysis and FRET
FRET_Anal_Y6_Vb.ipynb Use program: FRET_Anal_Y6_Vb.ipynb
Enter pathname and run RNA only sample
Check you are using the appropriate correction factors, usually beta is the only factor that varies from experiment to experiment. Make sure beta is set so that the double labeled population median is at 0.5.
Example 2D histogram
(Left) Example of the parameters used for leakage, direct excitation,
gamma, and beta. (Right) Example scatter plot produced when running the
FRETBursts program. The beta factor has been set so that the double labeled
bursts are clustered with a median of 0.5.
Make sure the time ranges are appropriate for your experiment and cover the decay fully.
Example decay curves
(Left) Example of the area of code to edit to ensure decay curves are
completely covered. (Right) Decay curves with the time ranges covering the
complete decay.
Enter pathname and run +protein sample
Make sure beta is set so that the double labeled population median is at 0.5.
Separate files into individual folders:
Example of data separation for easier analysis.
a. Anisotropy – Acceptor only, donor only, and double labeled
b. FRET efficiency folder (“efficiency” for short)
b. Stoichiometry (of each species)
FRET Efficiency Proportion Analysis
FRET Efficiency Proportion Analysis
FRET Efficiency Proportion Analysis
In the “FRET Efficiency” folder you created, go to the individual FRET Efficiency .csv file
Add up the number of bursts that had a FRET Efficiency above and below 0.5 from the “E” column in the .csv file
a. =IF(F5454>0.5,1,0)
b. This will assign 0 below 0.5 and 1 above 0.5
Sum the number of bursts that had a FRET efficiency above 0.5
a. =SUM(N2:N5454)
b. This will be the numerator for your high FRET efficiency bursts
Determine the number of bursts (sum the number of rows of data)
a. =ROWS(N2:N5454)
b. This is your denominator
Determine the proportion of bursts above 0.5 – this is proportion high FRET
a. Sum of bursts above 0.5 / sum of total bursts
Determine the proportion of bursts below 0.5 – this is proportion low FRET
a. Sum of bursts below 0.5 / sum of total bursts
Burst Analysis
Burst Analysis
Burst Analysis
The output will be called “BurstSearch.txt.”
Copy the entire text file contents to an excel sheet
Copy the bursts for acceptor only, double labeled, and donor only
Determine the proportion of these bursts by taking the quantity of these individual burst populations over the quantity of bursts in the RNA only sample
Normalize the RNA only sample to the maximum annealing proportion of 0.75 (for the RNA used in Yanas PNAS 2014 paper).
Processing files for Anisotropy
Processing files for Anisotropy
Anisotr_DDX2b_fig.py In Spyder - Use program: Anisotr_DDX2b_fig.py
Enter pathname (make sure you separate the files into AO, DO, DL)
Determine the t shift, G, and time period that fits the decay curve of the RNA only sample:
a. The G value should bring the decay curve to zero
b. The t shift should align the beginning of the horizontal and perpendicular anisotropy decays.
c. The time period should begin when the data is less sparse in the decay curve and end when the curve has flatlined
Use the “G” “e” “T” commands to set these parameters.
a. For example: type “G”, enter, then “1” (as your G value), enter. You have now set the G factor. Repeat for the other parameters.
Example time resolved fluorescence anisotropy
curves.
(Left) RNA only curve for a double labeled RNA. The anisotropy decay
should come completely to zero. All parameters have been set correctly for this
trace. (Right) RNA and protein curve showing high anisotropy. The parameters
were set with the RNA only sample and used for this sample.
Apply these values to the +protein and +protein/ATP samples
Stop program and enter pathname for +protein samples
a. Use the “G” “e” “T” commands to set these parameters.
The values will be saved to SavedData.csv file
Determine B/B0 by using the anisotropy of the tightly bound protein only sample as B0 and using the B value column as B. Plot these values over time to observe anisotropy changes.
Processing .hdf5 files for FCCS
Processing .hdf5 files for FCCS
FCS_AnalY4_All_B.ipynb PlotResults1.py PlotResults1_SPADS.py Use program: FCS_AnalY4_All_B.ipynb
Enter pathname and run all
Use beta value determined in the burst analysis program
Check each file has a good fit
In Spyder use program: PlotResults1.py
Enter pathname and run files
Extract file names, tau values, and N values
Copy and paste this output to excel
Split these cells into individual cells
Copy and paste transpose to sort data into vertical columns
Convert tau values to diffusion coefficients with the following equations: