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Dear Confocal List,

Im a PhD student trying to do some colocalization anlysis on multiple
transcription factors in mouse neural tissue using uimmunofluorescence. To
get as clean data as possible I want to utilize the "online fingerprinting"
capabillity of our Zeiss 510 META confocal microscope.

I understand that the first step is to generate reference samples for each
fluorophore. So far so good. But what I am confused about is that in most
tutorials etc. it seems that online fingerprinting is explained in samples
where you only use one laser-line to excite all your fluorophores. For
example: I plan on doing online fingerprinting with Hoechst, Alexa 488,
Cy3, and Cy5. There is really no practical way to use the same laser to
exite both Hoeckst and Cy5. So optimally I would like to use 4 different
lasers in sequential scanning for the 4 different fluorophores. Is this
compatible with online fingerprinting? In my mind I guess this means that
for all reference samples I have to obtain reference spectra of each
fluorophore with all 4 lasers? So that means 4*4=16 reference spectra (+
background and autofluorencese references)? Moreover, I want to do this on
Z-stack samples, but that should be possible, right?


Another question: While it is important to use the same dichroic mirrors
and settings for the reference samples and real sample imaging, this will
not be possible if I want to image 4 fluorophores, because (as far as I
remember) the dichroic mirror is only optimized for 3 wavelengths so I have
to switch when going from Hoechst to, say, Cy5. However, this issue might
be solved if it turns out that I only need to generate 4 reference spectra,
and not each for each laser line (4*4=16), due to me misunderstanding the
concept properly.

Lastly, while it is important to use the same dichroic mirrors and other
settings for the reference samples and real sample imaging, can digital
offset and detector gain be adjusted when imaging real samples? If not it
might be difficult to get the grey values withing optimal ranges as there
is some natural variability between samples.

Best regards.