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 .
Keywords: MaxQuant; R; Shiny; method development; optimizing mass spectrometry; quality control; single-cell analysis; single-cell proteomics by mass spectrometry; ultrasensitive proteomics; visualization.
Conflict of interest statement
The authors declare no competing financial interest.
compMS2Miner: An Automatable Metabolite Identification, Visualization, and Data-Sharing R Package for High-Resolution LC-MS Data Sets.Anal Chem. 2017 Apr 4;89(7):3919-3928. doi: 10.1021/acs.analchem.6b02394. Epub 2017 Mar 27. Anal Chem. 2017. PMID: 28225587 Free PMC article.
VisioProt-MS: interactive 2D maps from intact protein mass spectrometry.Bioinformatics. 2019 Feb 15;35(4):679-681. doi: 10.1093/bioinformatics/bty680. Bioinformatics. 2019. PMID: 30084957 Free PMC article.
Proteomics Quality Control: Quality Control Software for MaxQuant Results.J Proteome Res. 2016 Mar 4;15(3):777-87. doi: 10.1021/acs.jproteome.5b00780. Epub 2015 Dec 28. J Proteome Res. 2016. PMID: 26653327
"Polymeromics": Mass spectrometry based strategies in polymer science toward complete sequencing approaches: a review.Anal Chim Acta. 2014 Jan 15;808:56-69. doi: 10.1016/j.aca.2013.10.027. Epub 2013 Oct 21. Anal Chim Acta. 2014. PMID: 24370093 Review.
Screening of synthetic PDE-5 inhibitors and their analogues as adulterants: analytical techniques and challenges.J Pharm Biomed Anal. 2014 Jan;87:176-90. doi: 10.1016/j.jpba.2013.04.037. Epub 2013 May 6. J Pharm Biomed Anal. 2014. PMID: 23721687 Review.
Cited by 3 articles
Unpicking the proteome in single cells.Science. 2020 Jan 31;367(6477):512-513. doi: 10.1126/science.aaz6695. Science. 2020. PMID: 32001644 Free PMC article. No abstract available.
Accelerating Lipidomic Method Development through in Silico Simulation.Anal Chem. 2019 Aug 6;91(15):9698-9706. doi: 10.1021/acs.analchem.9b01234. Epub 2019 Jul 25. Anal Chem. 2019. PMID: 31298839
DART-ID increases single-cell proteome coverage.PLoS Comput Biol. 2019 Jul 1;15(7):e1007082. doi: 10.1371/journal.pcbi.1007082. eCollection 2019 Jul. PLoS Comput Biol. 2019. PMID: 31260443 Free PMC article.