In-depth comparative proteomic analysis of yeast proteome using iTRAQ and SWATH based MS
- PMID: 26099114
- DOI: 10.1039/c5mb00234f
In-depth comparative proteomic analysis of yeast proteome using iTRAQ and SWATH based MS
Abstract
Quantitative proteomics using LC-MS has emerged as an essential tool for addressing different biological questions. Various labelling methods have been effectively employed for quantitative proteomics studies. However, these are fraught with several challenges, including reproducibility and the number of samples that can be analysed at a given time. To this end, unlabelled proteomics is a promising field, and the recently developed sequential window acquisition of all theoretical fragment ion spectra (SWATH-MS) method aims to address these limitations. In this study, we compared SWATH-MS to isobaric tag for relative and absolute quantitation (iTRAQ), a widely used labelled method for relative quantitation. For this, we used yeast, Saccharomyces cerevisiae, since almost all its proteins are identified. More importantly, the abundance of each protein is well documented. We found that although a similar number of proteins could be quantitated using the two techniques, SWATH had the advantage of quantifying a larger percentage of low abundance proteins (below 60 ppm). Thus, based on our analysis, we believe that these two techniques are complementary and can synergistically improve the number of quantifiable proteins. SWATH's ability to quantify low abundant proteins could be an asset in biomarker discovery studies.
Similar articles
-
Optimization of Acquisition and Data-Processing Parameters for Improved Proteomic Quantification by Sequential Window Acquisition of All Theoretical Fragment Ion Mass Spectrometry.J Proteome Res. 2017 Feb 3;16(2):738-747. doi: 10.1021/acs.jproteome.6b00767. Epub 2017 Jan 3. J Proteome Res. 2017. PMID: 27995803
-
Biomarker discovery in low-grade breast cancer using isobaric stable isotope tags and two-dimensional liquid chromatography-tandem mass spectrometry (iTRAQ-2DLC-MS/MS) based quantitative proteomic analysis.J Proteome Res. 2009 Jan;8(1):362-73. doi: 10.1021/pr800622b. J Proteome Res. 2009. PMID: 19053527
-
SWATH enables precise label-free quantification on proteome scale.Proteomics. 2015 Apr;15(7):1215-23. doi: 10.1002/pmic.201400270. Proteomics. 2015. PMID: 25560523
-
Clinical veterinary proteomics: Techniques and approaches to decipher the animal plasma proteome.Vet J. 2017 Dec;230:6-12. doi: 10.1016/j.tvjl.2017.10.022. Epub 2017 Nov 11. Vet J. 2017. PMID: 29208216 Review.
-
Shotgun proteomics using the iTRAQ isobaric tags.Brief Funct Genomic Proteomic. 2006 Jun;5(2):112-20. doi: 10.1093/bfgp/ell018. Epub 2006 May 10. Brief Funct Genomic Proteomic. 2006. PMID: 16772272 Review.
Cited by
-
Orthogonal Proteomic Platforms and Their Implications for the Stable Classification of High-Grade Serous Ovarian Cancer Subtypes.iScience. 2020 Jun 26;23(6):101079. doi: 10.1016/j.isci.2020.101079. Epub 2020 Apr 18. iScience. 2020. PMID: 32534439 Free PMC article.
-
Comparative Proteomic Investigation of Plasma Reveals Novel Potential Biomarker Groups for Acute Aortic Dissection.Dis Markers. 2020 Mar 18;2020:4785068. doi: 10.1155/2020/4785068. eCollection 2020. Dis Markers. 2020. PMID: 32256857 Free PMC article.
-
SWATH-MS analysis of plasma proteins among Indian HIV-1 infected patients.Bioinformation. 2023 Apr 30;19(4):392-398. doi: 10.6026/97320630019392. eCollection 2023. Bioinformation. 2023. PMID: 37822814 Free PMC article.
-
Comparative proteomics analyses of whey proteins from breastmilk collected from two ethnic groups in northeast China.Food Chem X. 2023 Jan 9;17:100568. doi: 10.1016/j.fochx.2023.100568. eCollection 2023 Mar 30. Food Chem X. 2023. PMID: 36845516 Free PMC article.
-
Ncl1-mediated metabolic rewiring critical during metabolic stress.Life Sci Alliance. 2019 Aug 15;2(4):e201900360. doi: 10.26508/lsa.201900360. Print 2019 Aug. Life Sci Alliance. 2019. PMID: 31416893 Free PMC article.
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Molecular Biology Databases