DO-MS: Data-Driven Optimization of Mass Spectrometry Methods

The
performance of ultrasensitive liquid chromatography and tandem
mass spectrometry (LC-MS/MS) methods, such as single-cell proteomics
by mass spectrometry (SCoPE-MS), depends on multiple interdependent
parameters. This interdependence makes it challenging to specifically
pinpoint the sources of problems in the LC-MS/MS methods and approaches
for resolving them. For example, a low signal at the MS2 level can
be due to poor LC separation, ionization, apex targeting, ion transfer,
or ion detection. We sought to specifically diagnose such problems
by interactively visualizing data from all levels of bottom-up LC-MS/MS
analysis. Many software packages, such as MaxQuant, already provide
such data, and we developed an open source platform for their interactive
visualization and analysis: Data-driven Optimization of MS (DO-MS).
We found that in many cases DO-MS not only specifically diagnosed
LC-MS/MS problems but also enabled us to rationally optimize them.
For example, by using DO-MS to optimize the sampling of the elution
peak apexes, we increased ion accumulation times and apex sampling,
which resulted in a 370% more efficient delivery of ions for MS2 analysis.
DO-MS is easy to install and use, and its GUI allows for interactive
data subsetting and high-quality figure generation. The modular design
of DO-MS facilitates customization and expansion. DO-MS v1.0.8 is
available for download from GitHub: https://github.com/SlavovLab/DO-MS. Additional documentation is available at https://do-ms.slavovlab.net.