Aarón Millán-Oropeza, Mélisande Blein-Nicolas, Véronique Monnet, Michel Zivy, Céline Henry
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Here, we used different label-free quantification techniques to estimate absolute protein abundance in the model yeast Saccharomyces cerevisiae. More specifically, we evaluated the performance of seven different quantification methods, based either on spectral counting (SC) or extracted-ion chromatogram (XIC), which were applied to samples from five different proteome backgrounds. We also compared the accuracy and reproducibility of two strategies for transforming relative abundance into absolute abundance: a UPS2-based strategy and the total protein approach (TPA). This study mentions technical challenges related to UPS2 use and proposes ways of addressing them, including utilizing a smaller, more highly optimized amount of UPS2. Overall, three SC-based methods (PAI, SAF, and NSAF) yielded the best results because they struck a good balance between experimental performance and protein quantification.</p>","PeriodicalId":20877,"journal":{"name":"Proteomes","volume":"10 1","pages":""},"PeriodicalIF":4.0000,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8788469/pdf/","citationCount":"8","resultStr":"{\"title\":\"Comparison of Different Label-Free Techniques for the Semi-Absolute Quantification of Protein Abundance.\",\"authors\":\"Aarón Millán-Oropeza, Mélisande Blein-Nicolas, Véronique Monnet, Michel Zivy, Céline Henry\",\"doi\":\"10.3390/proteomes10010002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>In proteomics, it is essential to quantify proteins in absolute terms if we wish to compare results among studies and integrate high-throughput biological data into genome-scale metabolic models. While labeling target peptides with stable isotopes allow protein abundance to be accurately quantified, the utility of this technique is constrained by the low number of quantifiable proteins that it yields. Recently, label-free shotgun proteomics has become the \\\"gold standard\\\" for carrying out global assessments of biological samples containing thousands of proteins. However, this tool must be further improved if we wish to accurately quantify absolute levels of proteins. Here, we used different label-free quantification techniques to estimate absolute protein abundance in the model yeast Saccharomyces cerevisiae. More specifically, we evaluated the performance of seven different quantification methods, based either on spectral counting (SC) or extracted-ion chromatogram (XIC), which were applied to samples from five different proteome backgrounds. We also compared the accuracy and reproducibility of two strategies for transforming relative abundance into absolute abundance: a UPS2-based strategy and the total protein approach (TPA). This study mentions technical challenges related to UPS2 use and proposes ways of addressing them, including utilizing a smaller, more highly optimized amount of UPS2. 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Comparison of Different Label-Free Techniques for the Semi-Absolute Quantification of Protein Abundance.
In proteomics, it is essential to quantify proteins in absolute terms if we wish to compare results among studies and integrate high-throughput biological data into genome-scale metabolic models. While labeling target peptides with stable isotopes allow protein abundance to be accurately quantified, the utility of this technique is constrained by the low number of quantifiable proteins that it yields. Recently, label-free shotgun proteomics has become the "gold standard" for carrying out global assessments of biological samples containing thousands of proteins. However, this tool must be further improved if we wish to accurately quantify absolute levels of proteins. Here, we used different label-free quantification techniques to estimate absolute protein abundance in the model yeast Saccharomyces cerevisiae. More specifically, we evaluated the performance of seven different quantification methods, based either on spectral counting (SC) or extracted-ion chromatogram (XIC), which were applied to samples from five different proteome backgrounds. We also compared the accuracy and reproducibility of two strategies for transforming relative abundance into absolute abundance: a UPS2-based strategy and the total protein approach (TPA). This study mentions technical challenges related to UPS2 use and proposes ways of addressing them, including utilizing a smaller, more highly optimized amount of UPS2. Overall, three SC-based methods (PAI, SAF, and NSAF) yielded the best results because they struck a good balance between experimental performance and protein quantification.
ProteomesBiochemistry, Genetics and Molecular Biology-Clinical Biochemistry
CiteScore
6.50
自引率
3.00%
发文量
37
审稿时长
11 weeks
期刊介绍:
Proteomes (ISSN 2227-7382) is an open access, peer reviewed journal on all aspects of proteome science. Proteomes covers the multi-disciplinary topics of structural and functional biology, protein chemistry, cell biology, methodology used for protein analysis, including mass spectrometry, protein arrays, bioinformatics, HTS assays, etc. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. Therefore, there is no restriction on the length of papers. Scope: -whole proteome analysis of any organism -disease/pharmaceutical studies -comparative proteomics -protein-ligand/protein interactions -structure/functional proteomics -gene expression -methodology -bioinformatics -applications of proteomics