FLIM readout, from optomicroquant course

readout steps using symphotime:

sympthotime explanation: sepp

open your work space
open first tab in analysis column
select Lifetime FRET option

select channel to analyze (from 780, you can get 4 channels, parallel/perp and gfp/rfp).

TCSPC binning - do we need this high time resolution (1 ps range...)? select 8-Chnl binning!

-> calculate fast flim

r/click image: "show data reader" = mouse-over shows counts now. can be useful

make an ROI either manual, or based on threshold (that you set depending on measured background, mouse over image to get info)

note: program now uses calculated IRF (but isn't too exact). we need to tell it to use ours later

-> use fitting model: multi-exp donor! multiple lifetime components (populations of molecules!) might be hiding in the gfp signals.

-> set "Decay" to ROI0 (selects our defined ROI)
-> set IRF from calculated to measured (import, take Ery KI function)

Everything below model parameters (parameter-data set screen) is already some results. Some fit.

-> click initial fit, to make the software make a first guess

click yes on popup of change amplitude etc.?

-> initial fit, see black line appear in histogram
-> then normal "fit" button to get real fit

how good is my fit?
- Chi-squared, how big is your error? 1.000 is the best (but you will never reach), eg. 1.050 is a good value.

i. Second graph, under histogram = residues at each time point! Should be as flat as possible. Sometimes early lifetimes have more residuals. Warning: if there is a "wave" pattern in the residuals, this indicates more components to fit might be needed. Demonstrated by adding a component when not necessary, and then re-evaluating the residuals graph.

data: especially interesting is
-Tau average Intensity ("intensity weighted lifetime", how intense are the pixels in terms of photons, and what is its contribution to each lifetime component, is weighted based on that). But, intensity of donor decreases, and acceptor increases, when FRET happens - so donor gets unfairly penalized!
-Tau average Amplitude ("amplitude weighted lifetime" - imagine, two components are located somewhere in the graph (right of peak). they are then fitting straight lines in parallel to the graph at those positions. The y-axis intercept, is the amplitude. This is weighted)

Now to extract results. EG. copying from sympthotime to excel (export to clipboard).

We also might want to show a picture with FRET effect-size as a pixel. To reveal whether there may be lower/higher lifetime regions. Students can use this in their report. However, for this you officially need the donor lifetime as known. Can use with a "guessed" value.

Evaluate: intensity weighted compared to amplitude weighted, see the difference. eg. 2.1 ns in intensity, 1.9 in amplitude weighted... in the end, something like 250 ps is a good, clear FRET effect. Will be underrepresented in intensity based.

Batch processing:

close the software

?? reopen in batch mode? or just reopen? BatchLTfret (lifetime fret)

in batch, you can also use threshold (lower, to get above background, and higher, to avoid pileup (eg. counts above the 5% of repetition rate (of 30 MHz)

→ ROI and thresholding, get a good one. calculate all and save, goes through them in batch mode.

we can there also enter the IRF, and apply it to all the to-be-measured batch files! "IRF to all"

Here, make sure that you perform an initial fit on an image with counts that roughly match the number of counts in the IRF measurement; and ideally a cell that has counts in the average range of the dataset. Then apply that to all.

Fit All starts with all parameters, and generates an overview table!

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more things to do with students:

compare fret flim to fret APB!

compare different groups fits for the same sample set.

compare over/under right amount of fitting parameters