Login Register Cart 0
Generic placeholder image

Current Protein & Peptide Science

Editor-in-Chief

ISSN (Print): 1389-2037
ISSN (Online): 1875-5550

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Research Article

Number of Detected Proteins as the Function of the Sensitivity of Proteomic Technology in Human Liver Cells

Author(s): Nikita Vavilov, Ekaterina Ilgisonis, Andrey Lisitsa, Elena Ponomarenko, Tatiana Farafonova, Olga Tikhonova, Victor Zgoda and Alexander Archakov*

Volume 23, Issue 4, 2022

Published on: 09 June, 2022

Page: [290 - 298] Pages: 9

DOI: 10.2174/1389203723666220526092941

Price: $65

Abstract

Aims: The main goal of the Russian part of C-HPP is to detect and functionally annotate missing proteins (PE2-PE4) encoded by human chromosome 18. To achieve this goal, it is necessary to use the most sensitive methods of analysis.

Background: However, identifying such proteins in a complex biological mixture using mass spectrometry (MS)-based methods is difficult due to the insufficient sensitivity of proteomic analysis methods. A possible solution to the problem is the pre-fractionation of a complex biological sample at the sample preparation stage.

Objective: This study aims to measure the detection limit of SRM SIS analysis using a standard set of UPS1 proteins and find a way to enhance the sensitivity of the analysis and to, detect proteins encoded by the human chromosome 18 in liver tissue samples, and compare the data with transcriptomic analysis of the same samples.

Methods: Mass spectrometry, data-dependent acquisition, selected reaction monitoring, highperformance liquid chromatography, data-dependent acquisition in combination with pre-fractionation by alkaline reversed-phase chromatography, selected reaction monitoring in combination with prefractionation by alkaline reversed-phase chromatography methods were used in this study.

Results: The results revealed that 100% of UPS1 proteins in a mixture could only be identified at a concentration of at least 10-9 М. The decrease in concentration leads to protein losses associated with technology sensitivity, and no UPS1 protein is detected at a concentration of 10-13 М. Therefore, the two-dimensional fractionation of samples was applied to improve sensitivity. The human liver tissue was examined by selected reaction monitoring and shotgun methods of MS analysis using onedimensional and two-dimensional fractionation to identify the proteins encoded by human chromosome 18. A total of 134 proteins were identified. The overlap between proteomic and transcriptomic data in human liver tissue was ~50%.

Conclusion: The sample concentration technique is well suited for a standard UPS1 system that is not contaminated with a complex biological sample. However, it is not suitable for use with a complex biological protein mixture. Thus, it is necessary to develop more sophisticated fractionation systems for the detection of all low-copy proteins. This weak convergence is due to the low sensitivity of proteomic technology compared to transcriptomic approaches. Also, total mRNA was used to perform RNA-seq analysis, but not all detected mRNA molecules could be translated into proteins. This introduces additional uncertainty in the data; in the future, we plan to study only translated mRNA molecules-the translatome. Data is available via ProteomeXchange with identifier PXD026997.

Keywords: Proteomics, mass spectrometry, transcriptomics, 2D liquid chromatography, C-HPP, liver tissue, SRM SIS.

« Previous
Graphical Abstract

[1]
Archakov, A.; Aseev, A.; Bykov, V.; Grigoriev, A.; Govorun, V.; Ivanov, V.; Khlunov, A.; Lisitsa, A.; Mazurenko, S.; Makarov, A.A.; Ponomarenko, E.; Sagdeev, R.; Skryabin, K. Gene-centric view on the human proteome project: The example of the Russian roadmap for chromosome 18. Proteomics, 2011, 11(10), 1853-1856.
[http://dx.doi.org/10.1002/pmic.201000540] [PMID: 21563312]
[2]
Kopylov, A.T.; Ilgisonis, E.V.; Moysa, A.A.; Tikhonova, O.V.; Zavialova, M.G.; Novikova, S.E.; Lisitsa, A.V.; Ponomarenko, E.A.; Moshkovskii, S.A.; Markin, A.A.; Grigoriev, A.I.; Zgoda, V.G.; Archakov, A.I. Targeted quantitative screening of chromosome 18 encoded proteome in plasma samples of astronaut candidates. J. Proteome Res., 2016, 15(11), 4039-4046.
[http://dx.doi.org/10.1021/acs.jproteome.6b00384] [PMID: 27457493]
[3]
Vavilov, N.E.; Zgoda, V.G.; Tikhonova, O.V.; Farafonova, T.E.; Shushkova, N.A.; Novikova, S.E.; Yarygin, K.N.; Radko, S.P.; Ilgisonis, E.V.; Ponomarenko, E.A.; Lisitsa, A.V.; Archakov, A.I. Proteomic analysis of Chr 18 proteins using 2D fractionation. J. Proteome Res., 2020, 19(12), 4901-4906.
[http://dx.doi.org/10.1021/acs.jproteome.0c00856] [PMID: 33202127]
[4]
Zahn-Zabal, M.; Michel, P.A.; Gateau, A.; Nikitin, F.; Schaeffer, M.; Audot, E.; Gaudet, P.; Duek, P.D.; Teixeira, D.; Rech de Laval, V.; Samarasinghe, K.; Bairoch, A.; Lane, L. The neXtProt knowledgebase in 2020: Data, tools and usability improvements. Nucleic Acids Res., 2020, 48(D1), D328-D334.
[http://dx.doi.org/10.1093/nar/gkz995] [PMID: 31724716]
[5]
Cox, J.T.; Marginean, I.; Smith, R.D.; Tang, K. On the ionization and ion transmission efficiencies of different ESI-MS interfaces. J. Am. Soc. Mass Spectrom., 2015, 26(1), 55-62.
[http://dx.doi.org/10.1007/s13361-014-0998-5] [PMID: 25267087]
[6]
Hahne, H.; Pachl, F.; Ruprecht, B.; Maier, S.K.; Klaeger, S.; Helm, D.; Médard, G.; Wilm, M.; Lemeer, S.; Kuster, B. DMSO enhances electrospray response, boosting sensitivity of proteomic experiments. Nat. Methods, 2013, 10(10), 989-991.
[http://dx.doi.org/10.1038/nmeth.2610] [PMID: 23975139]
[7]
Mostovenko, E.; Hassan, C.; Rattke, J.; Deelder, A.M.; van Veelen, P.A.; Palmblad, M. Comparison of peptide and protein fractionation methods in proteomics. EuPA Open Proteom., 2013, 1, 30-37.
[http://dx.doi.org/10.1016/j.euprot.2013.09.001]
[8]
Kulak, N.A.; Geyer, P.E.; Mann, M. Loss-less nano-fractionator for high sensitivity, high coverage proteomics. Mol. Cell. Proteomics, 2017, 16(4), 694-705.
[http://dx.doi.org/10.1074/mcp.O116.065136] [PMID: 28126900]
[9]
Ilgisonis, E.; Vavilov, N.; Ponomarenko, E.; Lisitsa, A.; Poverennaya, E.; Zgoda, V.; Radko, S.; Archakov, A. Genome of the single human chromosome 18 as a “gold standard” for its transcriptome. Front. Genet., 2021, 12(6), 674534.
[http://dx.doi.org/10.3389/fgene.2021.674534] [PMID: 34194472]
[10]
Deinichenko, K.A.; Krasnov, G.S.; Radko, S.P.; Ptitsyn, K.G.; Shapovalova, V.V.; Timoshenko, O.S.; Khmeleva, S.A.; Kurbatov, L.K.; Kiseleva, Y.Y.; Ilgisonis, E.V.; Pyatnitskiy, M.A.; Poverennaya, E.V.; Kiseleva, O.I.; Vakhrushev, I.V.; Tsvetkova, A.V.; Buromski, I.V.; Markin, S.S.; Zgoda, V.G.; Archakov, A.I.; Lisitsa, A.V.; Ponomarenko, E.A. Human CHR18: “Stakhanovite” genes, missing and uPE1 proteins in liver tissue and HepG2 cells. Biomed. Chem. Res. Methods, 2021, 4(1), e00144.
[http://dx.doi.org/10.18097/BMCRM00144]
[11]
Tyanova, S.; Temu, T.; Cox, J. The MaxQuant computational platform for mass spectrometry-based shotgun proteomics. Nat. Protoc., 2016, 11(12), 2301-2319.
[http://dx.doi.org/10.1038/nprot.2016.136] [PMID: 27809316]
[12]
Kusebauch, U.; Campbell, D.S.; Deutsch, E.W.; Chu, C.S.; Spicer, D.A.; Brusniak, M.Y.; Slagel, J.; Sun, Z.; Stevens, J.; Grimes, B.; Shteynberg, D.; Hoopmann, M.R.; Blattmann, P.; Ratushny, A.V.; Rinner, O.; Picotti, P.; Carapito, C.; Huang, C.Y.; Kapousouz, M.; Lam, H.; Tran, T.; Demir, E.; Aitchison, J.D.; Sander, C.; Hood, L.; Aebersold, R.; Moritz, R.L. Human SRMAtlas: A resource of targeted assays to quantify the complete human proteome. Cell, 2016, 166(3), 766-778.
[http://dx.doi.org/10.1016/j.cell.2016.06.041] [PMID: 27453469]
[13]
Hood, C.A.; Fuentes, G.; Patel, H.; Page, K.; Menakuru, M.; Park, J.H. Fast conventional Fmoc solid-phase peptide synthesis with HCTU. J. Pept. Sci., 2008, 14(1), 97-101.
[http://dx.doi.org/10.1002/psc.921] [PMID: 17890639]
[14]
Pino, L.K.; Searle, B.C.; Bollinger, J.G.; Nunn, B.; MacLean, B.; MacCoss, M.J. The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics. Mass Spectrom. Rev., 2020, 39(3), 229-244.
[http://dx.doi.org/10.1002/mas.21540] [PMID: 28691345]
[15]
Donato, M.T.; Tolosa, L.; Gómez-Lechón, M.J. Culture and functional characterization of human hepatoma HepG2 cells. Methods Mol. Biol., 2015, 1250, 77-93.
[http://dx.doi.org/10.1007/978-1-4939-2074-7_5] [PMID: 26272135]
[16]
Hart, S.N.; Li, Y.; Nakamoto, K.; Subileau, E.A.; Steen, D.; Zhong, X.B. A comparison of whole genome gene expression profiles of HepaRG cells and HepG2 cells to primary human hepatocytes and human liver tissues. Drug Metab. Dispos., 2010, 38(6), 988-994.
[http://dx.doi.org/10.1124/dmd.109.031831] [PMID: 20228232]
[17]
Sebastián-Gámbaro, M.A.; Lirón-Hernández, F.J.; Fuentes-Arderiu, X. Intra- and inter-individual biological variability data bank. Eur. J. Clin. Chem. Clin. Biochem., 1997, 35(11), 845-852.
[PMID: 9426342]
[18]
Shi, T.; Su, D.; Liu, T.; Tang, K.; Camp, D.G., II; Qian, W.J.; Smith, R.D. Advancing the sensitivity of selected reaction monitoring-based targeted quantitative proteomics. Proteomics, 2012, 12(8), 1074-1092.
[http://dx.doi.org/10.1002/pmic.201100436] [PMID: 22577010]
[19]
Kuzyk, M.A.; Parker, C.E.; Domanski, D.; Borchers, C.H. Development of MRM-based assays for the absolute quantitation of plasma proteins. Methods Mol. Biol., 2013, 1023, 53-82.
[http://dx.doi.org/10.1007/978-1-4614-7209-4_4] [PMID: 23765619]
[20]
Agafonov, D.E.; Kolb, V.A.; Spirin, A.S. Ribosome-associated protein that inhibits translation at the aminoacyl-tRNA binding stage. EMBO Rep., 2001, 2(5), 399-402.
[http://dx.doi.org/10.1093/embo-reports/kve091] [PMID: 11375931]
[21]
Watson, C.N.; Belli, A.; Di Pietro, V. Small non-coding RNAs: New class of biomarkers and potential therapeutic targets in neurodegenerative disease. Front. Genet., 2019, 10(4), 364.
[http://dx.doi.org/10.3389/fgene.2019.00364] [PMID: 31080456]
[22]
King, H.A.; Gerber, A.P. Translatome profiling: Methods for genome-scale analysis of mRNA translation. Brief. Funct. Genomics, 2016, 15(1), 22-31.
[http://dx.doi.org/10.1093/bfgp/elu045] [PMID: 25380596]
[23]
Ponomarenko, E.A.; Kopylov, A.T.; Lisitsa, A.V.; Radko, S.P.; Kiseleva, Y.Y.; Kurbatov, L.K.; Ptitsyn, K.G.; Tikhonova, O.V.; Moisa, A.A.; Novikova, S.E.; Poverennaya, E.V.; Ilgisonis, E.V.; Filimonov, A.D.; Bogolubova, N.A.; Averchuk, V.V.; Karalkin, P.A.; Vakhrushev, I.V.; Yarygin, K.N.; Moshkovskii, S.A.; Zgoda, V.G.; Sokolov, A.S.; Mazur, A.M.; Prokhortchouck, E.B.; Skryabin, K.G.; Ilina, E.N.; Kostrjukova, E.S.; Alexeev, D.G.; Tyakht, A.V.; Gorbachev, A.Y.; Govorun, V.M.; Archakov, A.I. Chromosome 18 transcriptoproteome of liver tissue and HepG2 cells and targeted proteome mapping in depleted plasma: Update 2013. J. Proteome Res., 2014, 13(1), 183-190.
[http://dx.doi.org/10.1021/pr400883x] [PMID: 24328317]

Rights & Permissions Print Cite
Article Metrics
18
© 2024 Bentham Science Publishers | Privacy Policy