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Peptide Selection for Accurate Targeted Protein Quantification via a Dimethylation High-Resolution Mass Spectrum Strategy with a Peptide Release Kinetic Model
[Image: see text] A crucial step in accurate targeted protein quantification using targeted proteomics is to determine optimal proteotypic peptides representing targeted proteins. In this study, a workflow of peptide selection to determine proteotypic peptides using a dimethylation high-resolution m...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7057324/ https://www.ncbi.nlm.nih.gov/pubmed/32149207 http://dx.doi.org/10.1021/acsomega.9b02002 |
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author | Chen, Qi Jiang, Yirong Ren, Yiping Ying, Meirong Lu, Baiyi |
author_facet | Chen, Qi Jiang, Yirong Ren, Yiping Ying, Meirong Lu, Baiyi |
author_sort | Chen, Qi |
collection | PubMed |
description | [Image: see text] A crucial step in accurate targeted protein quantification using targeted proteomics is to determine optimal proteotypic peptides representing targeted proteins. In this study, a workflow of peptide selection to determine proteotypic peptides using a dimethylation high-resolution mass spectrum strategy with a peptide release kinetic model was investigated and applied in peptide selection of bovine serum albumin. After specificity, digestibility, recovery, and stability evaluation of tryptic peptides in bovine serum albumin, the optimal proteotypic peptide was selected as LVNELTEFAK. The quantification method using LVNELTEFAK gave a linear range of 1–100 ppm with the coefficient greater than 0.9990, and the detection limit of bovine serum albumin in milk was 0.78 mg/kg. Compared with the proteotypic peptides selected by Skyline, the method showed a better performance in method validation. The workflow exhibited high comprehensiveness and efficiency in peptide selection, facilitating accurate targeted protein quantification in the food matrix, which lack protein standards. |
format | Online Article Text |
id | pubmed-7057324 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-70573242020-03-06 Peptide Selection for Accurate Targeted Protein Quantification via a Dimethylation High-Resolution Mass Spectrum Strategy with a Peptide Release Kinetic Model Chen, Qi Jiang, Yirong Ren, Yiping Ying, Meirong Lu, Baiyi ACS Omega [Image: see text] A crucial step in accurate targeted protein quantification using targeted proteomics is to determine optimal proteotypic peptides representing targeted proteins. In this study, a workflow of peptide selection to determine proteotypic peptides using a dimethylation high-resolution mass spectrum strategy with a peptide release kinetic model was investigated and applied in peptide selection of bovine serum albumin. After specificity, digestibility, recovery, and stability evaluation of tryptic peptides in bovine serum albumin, the optimal proteotypic peptide was selected as LVNELTEFAK. The quantification method using LVNELTEFAK gave a linear range of 1–100 ppm with the coefficient greater than 0.9990, and the detection limit of bovine serum albumin in milk was 0.78 mg/kg. Compared with the proteotypic peptides selected by Skyline, the method showed a better performance in method validation. The workflow exhibited high comprehensiveness and efficiency in peptide selection, facilitating accurate targeted protein quantification in the food matrix, which lack protein standards. American Chemical Society 2020-02-18 /pmc/articles/PMC7057324/ /pubmed/32149207 http://dx.doi.org/10.1021/acsomega.9b02002 Text en Copyright © 2020 American Chemical Society This is an open access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) , which permits copying and redistribution of the article or any adaptations for non-commercial purposes. |
spellingShingle | Chen, Qi Jiang, Yirong Ren, Yiping Ying, Meirong Lu, Baiyi Peptide Selection for Accurate Targeted Protein Quantification via a Dimethylation High-Resolution Mass Spectrum Strategy with a Peptide Release Kinetic Model |
title | Peptide Selection for Accurate Targeted Protein Quantification
via a Dimethylation High-Resolution Mass Spectrum Strategy with a
Peptide Release Kinetic Model |
title_full | Peptide Selection for Accurate Targeted Protein Quantification
via a Dimethylation High-Resolution Mass Spectrum Strategy with a
Peptide Release Kinetic Model |
title_fullStr | Peptide Selection for Accurate Targeted Protein Quantification
via a Dimethylation High-Resolution Mass Spectrum Strategy with a
Peptide Release Kinetic Model |
title_full_unstemmed | Peptide Selection for Accurate Targeted Protein Quantification
via a Dimethylation High-Resolution Mass Spectrum Strategy with a
Peptide Release Kinetic Model |
title_short | Peptide Selection for Accurate Targeted Protein Quantification
via a Dimethylation High-Resolution Mass Spectrum Strategy with a
Peptide Release Kinetic Model |
title_sort | peptide selection for accurate targeted protein quantification
via a dimethylation high-resolution mass spectrum strategy with a
peptide release kinetic model |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7057324/ https://www.ncbi.nlm.nih.gov/pubmed/32149207 http://dx.doi.org/10.1021/acsomega.9b02002 |
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