Abstract
We describe a high-throughput method for co-fractionation mass spectrometry (CF-MS) profiling for native plasma protein profiling. CF-MS allows the profiling of endogenous protein complexes between samples. Proteins often interact with other proteins and form macromolecular complexes that are different in disease states as well as cell states and cell types. This protocol describes an example for the sample preparation of 954 individual size exclusion chromatography (SEC) fractions, derived from 18 plasma samples that were separated into 53 fractions. Eighteen plasma samples were chosen based on the TMTpro multiplexing, but this methodology can be adapted for fewer or larger numbers of samples as appropriate. Our automated sample preparation method allows for high-throughput native plasma profiling, and we provide detailed methods for both a label-free and an isobaric labeling approach, discuss the merits of each approach, and detail the advantages of combining these strategies for comprehensive native plasma proteome profiling.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Rhee H-W, Zou P, Udeshi ND et al (2013) Proteomic mapping of mitochondria in living cells via spatially restricted enzymatic tagging. Science 339:1328–1331
Roux KJ, Kim DI, Raida M et al (2012) A promiscuous biotin ligase fusion protein identifies proximal and interacting proteins in mammalian cells. J Cell Biol 196:801–810
Huttlin EL, Bruckner RJ, Navarrete-Perea J et al (2021) Dual proteome-scale networks reveal cell-specific remodeling of the human interactome. Cell 184:3022–3040.e28
Larance M, Kirkwood KJ, Tinti M et al (2016) Global membrane protein interactome analysis using in vivo crosslinking and mass spectrometry-based protein correlation profiling*. Mol Cell Proteom Mcp 15:2476–2490
Andersen JS, Wilkinson CJ, Mayor T et al (2003) Proteomic characterization of the human centrosome by protein correlation profiling. Nature 426:570–574
Dunkley TPJ, Watson R, Griffin JL et al (2004) Localization of organelle proteins by isotope tagging (LOPIT)*. Mol Cell Proteomics 3:1128–1134
Kirkwood KJ, Ahmad Y, Larance M et al (2013) Characterization of native protein complexes and protein isoform variation using size-fractionation-based quantitative proteomics*. Mol Cell Proteomics 12:3851–3873
Kristensen AR, Gsponer J, Foster LJ (2012) A high-throughput approach for measuring temporal changes in the interactome. Nat Methods 9:907–909
Havugimana PC, Hart GT, Nepusz T et al (2012) A census of human soluble protein complexes. Cell 150:1068–1081
Wessels HJCT, Vogel RO, van den Heuvel L et al (2009) LC‐MS/MS as an alternative for SDS‐PAGE in blue native analysis of protein complexes. Proteomics 9:4221–4228
Havugimana PC, Goel RK, Phanse S et al (2022) Scalable multiplex co-fractionation/mass spectrometry platform for accelerated protein interactome discovery. Nat Commun 13:4043
McAllister FE, Gygi SP (2013) Correlation profiling for determining kinase-substrate relationships. Methods 61:227–235
Foster LJ, de Hoog CL, Zhang Y et al (2006) A mammalian organelle map by protein correlation profiling. Cell 125:187–199
Dong M, Yang LL, Williams K et al (2008) A “Tagless” strategy for identification of stable protein complexes genome-wide by multidimensional orthogonal chromatographic separation and iTRAQ reagent tracking. J Proteome Res 7:1836–1849
Gaun AL, Olsson M et al (2022) Triple-threat quantitative multiplexed plasma proteomics analysis on immune complex disease MRL-lpr mice. Proteomics 22(19-20):2100242
Gaun A, Hardell KNL, Olsson N et al (2021) Automated 16-Plex plasma proteomics with real-time search and ion mobility mass spectrometry enables large-scale profiling in naked mole-rats and mice. J Proteome Res 20:1280–1295
Li J, Cai Z, Bomgarden RD et al (2021) TMTpro-18plex: the expanded and complete set of TMTpro reagents for sample multiplexing. J Proteome Res 20:2964–2972
Heusel M, Bludau I, Rosenberger G et al (2019) Complex‐centric proteome profiling by SEC‐SWATH‐MS. Mol Syst Biol 15:e8438
O’Connell JD, Paulo JA, O’Brien JJ et al (2018) Proteome-wide evaluation of two common protein quantification methods. J Proteome Res 17:1934–1942
Yu Q, Xiao H, Jedrychowski MP et al (2020) Sample multiplexing for targeted pathway proteomics in aging mice. Proc Natl Acad Sci USA 117:9723–9732
Gerber SA, Rush J, Stemman O et al (2003) Absolute quantification of proteins and phosphoproteins from cell lysates by tandem MS. Proc Natl Acad Sci 100:6940–6945
Käll L, Canterbury JD, Weston J et al (2007) Semi-supervised learning for peptide identification from shotgun proteomics datasets. Nat Methods 4:923–925
Huttlin EL, Jedrychowski MP, Elias JE et al (2010) A tissue-specific atlas of mouse protein phosphorylation and expression. Cell 143:1174–1189
Ting L, Rad R, Gygi SP et al (2011) MS3 eliminates ratio distortion in isobaric labeling-based multiplexed quantitative proteomics. Nat Methods 8:937–940
Hu LZ, Goebels F, Tan JH et al (2019) EPIC: software toolkit for elution profile-based inference of protein complexes. Nat Methods 16:737–742
Stacey RG, Skinnider MA, Scott NE et al (2017) A rapid and accurate approach for prediction of interactomes from co-elution data (PrInCE). BMC Bioinform 18:457
Van SJ, Haupt A, Schulte U et al (2021) CEDAR, an online resource for the reporting and exploration of complexome profiling data. Biochimica Et Biophysica Acta Bba - Bioenergetics 1862:148411
Eng JK, McCormack AL, Yates JR (1994) An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database. J Am Soc Mass Spectr 5:976–989
Perkins DN, Pappin DJC, Creasy DM et al (1999) Probability‐based protein identification by searching sequence databases using mass spectrometry data. Electrophoresis 20:3551–3567
Eng JK, Jahan TA, Hoopmann MR (2013) Comet: an open‐source MS/MS sequence database search tool. Proteomics 13:22–24
Orsburn BC (2021) Proteome discoverer—a community enhanced data processing suite for protein informatics. Proteomes 9:15
Zhang J, Xin L, Shan B et al (2012) PEAKS DB: De Novo sequencing assisted database search for sensitive and accurate peptide identification*. Mol Cell Proteom Mcp 11(M111):010587
Bern M, Kil YJ, Becker C (2012) Byonic: advanced peptide and protein identification software. Curr Protoc Bioinform 40:13.20.1–13.20.14
Tyanova S, Temu T, Cox J (2016) The MaxQuant computational platform for mass spectrometry-based shotgun proteomics. Nat Protoc 11:2301–2319
Kong AT, Leprevost FV, Avtonomov DM et al (2017) MSFragger: ultrafast and comprehensive peptide identification in shotgun proteomics. Nat Methods 14:513–520
Senkler J, Senkler M, Eubel H et al (2017) The mitochondrial complexome of Arabidopsis thaliana. Plant J 89:1079–1092
Páleníková P, Harbour ME, Ding S et al (2021) Quantitative density gradient analysis by mass spectrometry (qDGMS) and complexome profiling analysis (ComPrAn) R package for the study of macromolecular complexes. Biochimica Et Biophysica Acta Bba - Bioenergetics 1862:148399
Strien JV, Guerrero-Castillo S, Chatzispyrou IA et al (2019) COmplexome Profiling ALignment (COPAL) reveals remodeling of mitochondrial protein complexes in Barth syndrome. Bioinformatics 35:3083–3091
Giese H, Ackermann J, Heide H et al (2015) NOVA: a software to analyze complexome profiling data. Bioinformatics 31:440–441
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature
About this protocol
Cite this protocol
Gaun, A., Olsson, N., Wang, J.C.K., Eaton, D.L., McAllister, F.E. (2023). High-Throughput Proteome Profiling of Plasma and Native Plasma Complexes Using Native Chromatography. In: Greening, D.W., Simpson, R.J. (eds) Serum/Plasma Proteomics. Methods in Molecular Biology, vol 2628. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2978-9_5
Download citation
DOI: https://doi.org/10.1007/978-1-0716-2978-9_5
Published:
Publisher Name: Humana, New York, NY
Print ISBN: 978-1-0716-2977-2
Online ISBN: 978-1-0716-2978-9
eBook Packages: Springer Protocols