Early-run m/z + IM calibration (timsTOF / any Q-TOF ?)

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Early-run m/z + IM calibration (timsTOF / any Q-TOF ?) v delcourt  2022-06-30
 

Hi,

Coming from nanoflow QE area and recently adapting to a timsTOF, one thing that is pretty handy is the early-run calibration. Briefly, a loop is filled with calibrant (e.g. sodium acetate/formate + agilent tunemix) and is pushed into the MS while in the dead volume (e.g. 0.1-0.3 min window). This allows through the Bruker software "dataanalysis" to perform a post acquisition calibration for m/z and IMS (tims), which is really nice to reach sub 2 ppm mass and ~ 1 % CCS precisions. This is also implemented for nanoflow with different procedures.
Are you considering adding this kind module to Skyline which would be awesome for both proteomics and small molecule analysis ?

Thanks again for developing Skyline.
With kindest regards,
Vivian

 
 
Brian Pratt responded:  2022-06-30

Hi Vivian,

Normally Skyline (and MSConvert) leave that kind of deep system knowledge to the mass spec vendor, depending instead on the vendor supplied reader library to apply appropriate calibrations. Is it your impression that this is not happening with this data?

Best regards,

Brian Pratt

 
v delcourt responded:  2022-06-30

Hi Brian,

Thanks for your answer.
Technically, anyone could perform this kind of post-run manual recalibration (also this would be a nightmare if not done automatically for 10-100-1000-ish samples).
It implies :

  • knowing what kind of mixture has been pushed as calibrant (i.e. expected m/z)
  • what are apexes of m/z peaks detected within the associated RT window (i.e. dead volume)
  • correct observed m/z with expected m/z values and perform global correction of all m/z in the run using appropriate regression (in our case, 10-15 points quadratic regression is working fine)
  • what are apexes of IM (1/k0) peaks detected within the associated RT window (i.e. dead volume)
  • correct observed IM with expected IM values of specific m/z and perform global correction of all IM in the run using appropriate regression (in our case, three points -linear regression is working fine)

--> obtain a fully post-run recalibrated run.

If you want to put your hands on some data, I can provide some.

Best regards,
Vivian

 
Brian Pratt responded:  2022-06-30

This sounds a lot like what Waters does with lockmass calibration, except that with Waters it happens both before and, periodically, during a run. But, again, the resulting calibration is handled within their reader library. If this is a common procedure with the timsTOF, we should probably take it up with Bruker so that it's useful to the wider community (thinking of MSConvert, which we also maintain, and anything else that's using the Bruker-provided raw data reader).

 
v delcourt responded:  2022-06-30

Thanks for your answer.
Basically, it is exactly what waters does, but only for early run in conventional LC. I believe this is a common procedure for QTOFs (maybe more deployed in metabolomics). However, AlphaTims developped by Mann group looks like is considering implementing this kind of feature I believe (https://github.com/MannLabs/alphatims/issues/25). See also attached capture from their tutorial jupyter notebook. Note that this is nano so the calibrant is visible all over the run, which is different from pushing a 25 µL loop into the MS in conventional LC/UHPLC.

Don't hesitate if you consider implementing this and if you need any data.

Best regards,
Vivian

 
Brian Pratt responded:  2022-06-30

My strong preference would be to encourage Bruker to implement this in their reader API, so as to benefit the entire mass spec community instead of just users of software maintained by the MacCoss lab. If a motivated user such as yourself lets Bruker know that this is important, it's more likely to happen.

Best,

Brian

 
v delcourt responded:  2022-07-01

Thanks Brian,
The request has been forwarded to our contacts at Bruker. Please do the same. Also for anyone reading this and being interested by this kind of feature, please do the same.
Solutions may include batch scripting run recalibration in DataAnalysis and save as "recalibrated .d" file which we could not perform yet.

Thanks again for all.
Vivian