Targeted proteomics coming of age – SRM, PRM and DIA performance evaluated from a core facility perspective

Quantitative mass spectrometry is a rapidly evolving methodology applied in a large number of omics‐type research projects. During the past years, new designs of mass spectrometers have been developed and launched as commercial systems while in parallel new data acquisition schemes and data analysis paradigms have been introduced. Core facilities provide access to such technologies, but also actively support the researchers in finding and applying the best‐suited analytical approach. In order to implement a solid fundament for this decision making process, core facilities need to constantly compare and benchmark the various approaches. In this article we compare the quantitative accuracy and precision of current state of the art targeted proteomics approaches single reaction monitoring (SRM), parallel reaction monitoring (PRM) and data independent acquisition (DIA) across multiple liquid chromatography mass spectrometry (LC‐MS) platforms, using a readily available commercial standard sample. All workflows are able to reproducibly generate accurate quantitative data. However, SRM and PRM workflows show higher accuracy and precision compared to DIA approaches, especially when analyzing low concentrated analytes.

[1]  M. Mann,et al.  Proteomics on an Orbitrap Benchtop Mass Spectrometer Using All-ion Fragmentation , 2010, Molecular & Cellular Proteomics.

[2]  Derek J. Bailey,et al.  Parallel Reaction Monitoring for High Resolution and High Mass Accuracy Quantitative, Targeted Proteomics* , 2012, Molecular & Cellular Proteomics.

[3]  D. Goodin The cambridge dictionary of statistics , 1999 .

[4]  Brendan MacLean,et al.  Panorama: A Targeted Proteomics Knowledge Base , 2014, Journal of proteome research.

[5]  Susan E. Abbatiello,et al.  Targeted Peptide Measurements in Biology and Medicine: Best Practices for Mass Spectrometry-based Assay Development Using a Fit-for-Purpose Approach* , 2014, Molecular & Cellular Proteomics.

[6]  Michael J MacCoss,et al.  Large-Scale Interlaboratory Study to Develop, Analytically Validate and Apply Highly Multiplexed, Quantitative Peptide Assays to Measure Cancer-Relevant Proteins in Plasma* , 2015, Molecular & Cellular Proteomics.

[7]  Werner Zolg,et al.  Quantification of C‐reactive protein in the serum of patients with rheumatoid arthritis using multiple reaction monitoring mass spectrometry and 13C‐labeled peptide standards , 2004, Proteomics.

[8]  B. Domon,et al.  Targeted Proteomic Quantification on Quadrupole-Orbitrap Mass Spectrometer* , 2012, Molecular & Cellular Proteomics.

[9]  Michael J MacCoss,et al.  Using BiblioSpec for Creating and Searching Tandem MS Peptide Libraries , 2007, Current protocols in bioinformatics.

[10]  Ruedi Aebersold,et al.  Conserved Peptide Fragmentation as a Benchmarking Tool for Mass Spectrometers and a Discriminating Feature for Targeted Proteomics* , 2014, Molecular & Cellular Proteomics.

[11]  S. Carr,et al.  Quantitative, Multiplexed Assays for Low Abundance Proteins in Plasma by Targeted Mass Spectrometry and Stable Isotope Dilution*S , 2007, Molecular & Cellular Proteomics.

[12]  Christoph H Borchers,et al.  Multi-site assessment of the precision and reproducibility of multiple reaction monitoring–based measurements of proteins in plasma , 2009, Nature Biotechnology.

[13]  E. Diamandis,et al.  The bottleneck in the cancer biomarker pipeline and protein quantification through mass spectrometry-based approaches: current strategies for candidate verification. , 2010, Clinical chemistry.

[14]  Albert J R Heck,et al.  Improving SRM assay development: a global comparison between triple quadrupole, ion trap, and higher energy CID peptide fragmentation spectra. , 2011, Journal of proteome research.

[15]  Brendan MacLean,et al.  Bioinformatics Applications Note Gene Expression Skyline: an Open Source Document Editor for Creating and Analyzing Targeted Proteomics Experiments , 2022 .

[16]  Leigh Anderson,et al.  Quantitative Mass Spectrometric Multiple Reaction Monitoring Assays for Major Plasma Proteins* , 2006, Molecular & Cellular Proteomics.

[17]  R. Aebersold,et al.  Selected reaction monitoring for quantitative proteomics: a tutorial , 2008, Molecular systems biology.

[18]  R. Aebersold,et al.  mProphet: automated data processing and statistical validation for large-scale SRM experiments , 2011, Nature Methods.

[19]  Lukas N. Mueller,et al.  Full Dynamic Range Proteome Analysis of S. cerevisiae by Targeted Proteomics , 2009, Cell.

[20]  Richard D. Smith,et al.  Advances and Challenges in Liquid Chromatography-Mass Spectrometry-based Proteomics Profiling for Clinical Applications* , 2006, Molecular & Cellular Proteomics.

[21]  Oliver M. Bernhardt,et al.  Extending the Limits of Quantitative Proteome Profiling with Data-Independent Acquisition and Application to Acetaminophen-Treated Three-Dimensional Liver Microtissues* , 2015, Molecular & Cellular Proteomics.

[22]  Christoph H Borchers,et al.  Design, Implementation and Multisite Evaluation of a System Suitability Protocol for the Quantitative Assessment of Instrument Performance in Liquid Chromatography-Multiple Reaction Monitoring-MS (LC-MRM-MS)* , 2013, Molecular & Cellular Proteomics.

[23]  Ludovic C. Gillet,et al.  Targeted Data Extraction of the MS/MS Spectra Generated by Data-independent Acquisition: A New Concept for Consistent and Accurate Proteome Analysis* , 2012, Molecular & Cellular Proteomics.

[24]  Jarrett D. Egertson,et al.  Multiplexed MS/MS for Improved Data Independent Acquisition , 2013, Nature Methods.

[25]  Knut Reinert,et al.  Transformation and other factors of the peptide mass spectrometry pairwise peak-list comparison process , 2005, BMC Bioinformatics.

[26]  Steven A Carr,et al.  Protein biomarker discovery and validation: the long and uncertain path to clinical utility , 2006, Nature Biotechnology.

[27]  D. N. Perkins,et al.  Probability‐based protein identification by searching sequence databases using mass spectrometry data , 1999, Electrophoresis.

[28]  G. Jarvik,et al.  Parallel reaction monitoring (PRM) and selected reaction monitoring (SRM) exhibit comparable linearity, dynamic range and precision for targeted quantitative HDL proteomics. , 2015, Journal of proteomics.

[29]  Pei Wang,et al.  Demonstrating the feasibility of large-scale development of standardized assays to quantify human proteins , 2013, Nature Methods.

[30]  L L Needham,et al.  Isotope dilution--mass spectrometric quantification of specific proteins: model application with apolipoprotein A-I. , 1996, Clinical chemistry.