QuaMeter: multivendor performance metrics for LC-MS/MS proteomics instrumentation

Abstract

LC-MS/MS-based proteomics studies rely on stable analytical system performance that can be evaluated by objective criteria. The National Institute of Standards and Technology (NIST) introduced the MSQC software to compute diverse metrics from experimental LC-MS/MS data, enabling quality analysis and quality control (QA/QC) of proteomics instrumentation. In practice, however, several attributes of the MSQC software prevent its use for routine instrument monitoring. Here, we present QuaMeter, an open-source tool that improves MSQC in several aspects. QuaMeter can directly read raw data from instruments manufactured by different vendors. The software can work with a wide variety of peptide identification software for improved reliability and flexibility. Finally, QC metrics implemented in QuaMeter are rigorously defined and tested. The source code and binary versions of QuaMeter are available under Apache 2.0 License at http://fenchurch.mc.vanderbilt.edu.

Figure 1

Workflow diagram for QuaMeter operation.

Figure 2

QuaMeter generates metrics similar to MSQC with the exception of chromatographic metrics due to the use of distinct chromatogram extraction tools. Metrics were generated from BSA QC experiments collected on a Thermo Fisher LTQ-XL mass spectrometer. The subgraph in bottom-left panel is a rescaled plot for DS-3B metric.

Figure 3

QuaMeter detects chromatographic peaks from instruments via the CRAWDAD module in ProteoWizard. Red lines represent experimentally measured intensities in MS, and blue lines are extracted ion chromatograms generated by CRAWDAD. Asterisks for the low abundance peptides signify the acquisition times for identified MS/MS scans.

Figure 4

QuaMeter computes QC metrics for multiple instrument platforms. Standard samples, such as BSA or β-galactosidase, were analyzed for routine instrument evaluation. C-2A: time period over which middle 50% of peptides were identified. C-4A, C-4B, C-4C: median peak width for identified peptides in first, last, and median RT decile.

Figure 5

Distinct peptide identification methods produce different QC metrics with similar variation. Five technical replicates of yeast lysate samples were analyzed on a Thermo Fisher LTQ-Velos mass spectrometer. Spectra were identified by a MyriMatch (MM) database search and a Pepitome (PP) spectral library search. Identifications from each search engine were used to compute QC metrics. P-2A, number of MS2 spectra identifying tryptic peptide ions; C-2A, time period over which middle 50% of peptides were identified; DS-2B, number of MS2 scans taken over C-2A; IS-3Bn number of 3+ peptides over 2+ peptides; MS1–5A, median real value of precursor errors; MS2–3, median number of peaks in MS2 scans.