[FLIMfit-users] Fwd: FLIMFit query

[Munro, Ian]

Hi Ewan

For the moment I’m just forwarding this to the users list in case somebody can answer immediately.
Otherwise I’ll have a look as soon as I can.

All the best

Ian

Begin forwarded message:

Hi

I’ve just been doing some double exponential fitting with FLIMFit and ran into a couple of “queries”…

1. When I used a pixel-by-pixel method you’d get a longer than expected lifetime and and shorter than expected lifetime (e.g. For a gfp-Tag-RFP fret pair, should be about 2.1 ns gfp lifetime, I got t1 = 3.2 ns and t2 = ~600 ps with b1 = ~0.3 and b2 = ~0.7), however, the weighted mean lifetime is the correct value?

2. Sometime the beta were negative for b2 and over 1 for b1 e.g. b1 = 1.41 and b2 = -0.42?

I’m guessing that this is because the model is finding it hard to fit perhaps through lack of signal?

When I fit the same data using global fitting (but locally vary the contributions) it behaves a bit better.

The smodel settings I used were: Global fitting, Fit Contributions = Fitted locally, Fit Reference = Fitted, Fit IRF Shift = Fitted. Stray light tab: Offest = Fitted gloabally, Scatter = Fitted gloabally, TV Background = Fitted globally.

The fit results are:

        tau 1   tau 2   b1      b2      weighted mean tau

mTagRFP 2374.9365       101.5567        1.04607 -0.0460605      2478.4242
control 2203.113        326.7455        0.60874 0.39126 2034.0543







wt - 2  2222.8235       74.7949 1.5714  -0.571393333    2258.200767


 Where mTagRFP, is just GFP only so 2.5’ish ns expected, control is positive FRET  so about 2 ns and wt-2 is the wild-type free to vary FRET sample (so somewhere between mTagRFP and control sample lifetimes).

Does this behaviour make sense to you?

Any help or insight would be really useful :-)

Hows things going otherwise? I shall email you the journal DOI when the paper is published that this is going into.

Speak to you soon,

Ewan

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