Suppr超能文献

使用谱计数对 SILAC 数据集进行定量分析。

Quantitative analysis of SILAC data sets using spectral counting.

机构信息

Biotechnology and Bioengineering Center, Medical College of Wisconsin, WI, USA.

出版信息

Proteomics. 2010 Apr;10(7):1408-15. doi: 10.1002/pmic.200900684.

Abstract

We report a new quantitative proteomics approach that combines the best aspects of stable isotope labeling of amino acids in cell culture (SILAC) labeling and spectral counting. The SILAC peptide count ratio analysis (SPeCtRA, http://proteomics.mcw.edu/visualize) method relies on MS(2) spectra rather than ion chromatograms for quantitation and therefore does not require the use of high mass accuracy mass spectrometers. The inclusion of a stable isotope label allows the samples to be combined before sample preparation and analysis, thus avoiding many of the sources of variability that can plague spectral counting. To validate the SPeCtRA method, we have analyzed samples constructed with known ratios of protein abundance. Finally, we used SPeCtRA to compare endothelial cell protein abundances between high (20 mM) and low (11 mM) glucose culture conditions. Our results demonstrate that SPeCtRA is a protein quantification technique that is accurate and sensitive as well as easy to automate and apply to high-throughput analysis of complex biological samples.

摘要

我们报告了一种新的定量蛋白质组学方法,它结合了稳定同位素标记的氨基酸在细胞培养中的最佳方面(SILAC)标记和光谱计数。SILAC 肽计数比分析(SPeCtRA,http://proteomics.mcw.edu/visualize)方法依赖于 MS(2)光谱而不是离子色谱图进行定量,因此不需要使用高质量精度的质谱仪。包含稳定同位素标记允许在样品制备和分析之前将样品组合,从而避免了许多可能困扰光谱计数的可变性来源。为了验证 SPeCtRA 方法,我们已经分析了用已知蛋白丰度比构建的样品。最后,我们使用 SPeCtRA 比较了高(20 mM)和低(11 mM)葡萄糖培养条件下内皮细胞蛋白丰度。我们的结果表明,SPeCtRA 是一种准确、敏感、易于自动化且适用于复杂生物样品高通量分析的蛋白质定量技术。

相似文献

1
Quantitative analysis of SILAC data sets using spectral counting.
Proteomics. 2010 Apr;10(7):1408-15. doi: 10.1002/pmic.200900684.
6
Stable isotope labeling by amino acids in cell culture for quantitative proteomics.
Methods Mol Biol. 2007;359:37-52. doi: 10.1007/978-1-59745-255-7_3.
7
Automated generic analysis tools for protein quantitation using stable isotope labeling.
Methods Mol Biol. 2010;604:257-72. doi: 10.1007/978-1-60761-444-9_17.
8
Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) for Quantitative Proteomics.
Adv Exp Med Biol. 2019;1140:531-539. doi: 10.1007/978-3-030-15950-4_31.
10
Super-SILAC: current trends and future perspectives.
Expert Rev Proteomics. 2015 Feb;12(1):13-9. doi: 10.1586/14789450.2015.982538. Epub 2014 Nov 18.

引用本文的文献

1
SILAC peptide ratio calculator: a tool for SILAC quantitation of peptides and post-translational modifications.
J Proteome Res. 2014 Feb 7;13(2):506-16. doi: 10.1021/pr400675n. Epub 2014 Jan 9.
2
Global analysis of condition-specific subcellular protein distribution and abundance.
Mol Cell Proteomics. 2013 May;12(5):1421-35. doi: 10.1074/mcp.O112.019166. Epub 2013 Jan 24.
3
Visualize: a free and open source multifunction tool for proteomics data analysis.
Proteomics. 2011 Mar;11(6):1058-63. doi: 10.1002/pmic.201000556. Epub 2011 Feb 7.

本文引用的文献

2
Prevention of amino acid conversion in SILAC experiments with embryonic stem cells.
Mol Cell Proteomics. 2008 Sep;7(9):1587-97. doi: 10.1074/mcp.M800113-MCP200. Epub 2008 May 16.
6
Relative quantification of peptide phosphorylation in a complex mixture using 18O labeling.
Physiol Genomics. 2007 Oct 22;31(2):357-63. doi: 10.1152/physiolgenomics.00096.2007. Epub 2007 Aug 7.
7
Quantitative mass spectrometry in proteomics: a critical review.
Anal Bioanal Chem. 2007 Oct;389(4):1017-31. doi: 10.1007/s00216-007-1486-6. Epub 2007 Aug 1.
8
Functional and quantitative proteomics using SILAC.
Nat Rev Mol Cell Biol. 2006 Dec;7(12):952-8. doi: 10.1038/nrm2067.
9
Detecting differential and correlated protein expression in label-free shotgun proteomics.
J Proteome Res. 2006 Nov;5(11):2909-18. doi: 10.1021/pr0600273.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验