Literature DB >> 24591407

Quantitative analysis of human salivary gland-derived intact proteome using top-down mass spectrometry.

Si Wu1, Joseph N Brown, Nikola Tolić, Da Meng, Xiaowen Liu, Haizhen Zhang, Rui Zhao, Ronald J Moore, Pavel Pevzner, Richard D Smith, Ljiljana Paša-Tolić.   

Abstract

There are several notable challenges inherent for fully characterizing the entirety of the human saliva proteome using bottom-up approaches, including polymorphic isoforms, PTMs, unique splice variants, deletions, and truncations. To address these challenges, we have developed a top-down based LC-MS/MS approach, which cataloged 20 major human salivary proteins with a total of 83 proteoforms, containing a broad range of PTMs. Among these proteins, several previously reported disease biomarker proteins were identified at the intact protein level, such as beta-2 microglobulin. In addition, intact glycosylated proteoforms of several saliva proteins were also characterized, including intact N-glycosylated protein prolactin inducible protein and O-glycosylated acidic protein rich protein. These characterized proteoforms constitute an intact saliva proteoform database, which was used for quantitative comparison of intact salivary proteoforms among six healthy individuals. Human parotid and submandibular/sublingual gland secretion samples (2 μg of protein each) from six healthy individuals were compared using RPLC coupled with the 12T FT-ICR mass spectrometer. Significantly different proteoform profiles were resolved with high reproducibility between parotid secretion and submandibular/sublingual glands. The results from this study provide further insight into the potential mechanisms of PTM pathways in oral glandular secretion, expanding our knowledge of this complex yet easily accessible fluid. Intact protein LC-MS approach presented herein can potentially be applied for rapid and accurate identification of biomarkers from only a few microliters of human glandular saliva.
© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  AMT; FT-ICR; FTMS; Saliva; Technology; Top-down

Mesh:

Substances:

Year:  2014        PMID: 24591407     DOI: 10.1002/pmic.201300378

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  19 in total

1.  MASH Suite Pro: A Comprehensive Software Tool for Top-Down Proteomics.

Authors:  Wenxuan Cai; Huseyin Guner; Zachery R Gregorich; Albert J Chen; Serife Ayaz-Guner; Ying Peng; Santosh G Valeja; Xiaowen Liu; Ying Ge
Journal:  Mol Cell Proteomics       Date:  2015-11-23       Impact factor: 5.911

Review 2.  Progress in Top-Down Proteomics and the Analysis of Proteoforms.

Authors:  Timothy K Toby; Luca Fornelli; Neil L Kelleher
Journal:  Annu Rev Anal Chem (Palo Alto Calif)       Date:  2016-06-12       Impact factor: 10.745

3.  Evaluation of Spectral Counting for Relative Quantitation of Proteoforms in Top-Down Proteomics.

Authors:  Lucía Geis-Asteggiante; Suzanne Ostrand-Rosenberg; Catherine Fenselau; Nathan J Edwards
Journal:  Anal Chem       Date:  2016-10-31       Impact factor: 6.986

4.  Deep and quantitative top-down proteomics in clinical and translational research.

Authors:  Neil L Kelleher; Paul M Thomas; Ioanna Ntai; Philip D Compton; Richard D LeDuc
Journal:  Expert Rev Proteomics       Date:  2014-10-28       Impact factor: 3.940

5.  Proteomic profile of saliva collected directly from ducts: a systematic review.

Authors:  Camilla Vieira Esteves; Wladimir Gushiken de Campos; Juliana Amorim Dos Santos; Solange Kobayashi Velasco; Eliete Neves Silva Guerra; Walter L Siqueira; Celso Augusto Lemos
Journal:  Clin Oral Investig       Date:  2019-12-12       Impact factor: 3.573

Review 6.  High-throughput quantitative top-down proteomics.

Authors:  Kellye A Cupp-Sutton; Si Wu
Journal:  Mol Omics       Date:  2020-01-14

7.  Abundant Lysine Methylation and N-Terminal Acetylation in Sulfolobus islandicus Revealed by Bottom-Up and Top-Down Proteomics.

Authors:  Egor A Vorontsov; Elena Rensen; David Prangishvili; Mart Krupovic; Julia Chamot-Rooke
Journal:  Mol Cell Proteomics       Date:  2016-08-23       Impact factor: 5.911

Review 8.  Top-Down Proteomics: Ready for Prime Time?

Authors:  Bifan Chen; Kyle A Brown; Ziqing Lin; Ying Ge
Journal:  Anal Chem       Date:  2017-12-15       Impact factor: 6.986

9.  Comparative top down proteomics of peripheral blood mononuclear cells from kidney transplant recipients with normal kidney biopsies or acute rejection.

Authors:  John P Savaryn; Timothy K Toby; Adam D Catherman; Ryan T Fellers; Richard D LeDuc; Paul M Thomas; John J Friedewald; Daniel R Salomon; Michael M Abecassis; Neil L Kelleher
Journal:  Proteomics       Date:  2016-07       Impact factor: 3.984

10.  Quantitation and Identification of Thousands of Human Proteoforms below 30 kDa.

Authors:  Kenneth R Durbin; Luca Fornelli; Ryan T Fellers; Peter F Doubleday; Masashi Narita; Neil L Kelleher
Journal:  J Proteome Res       Date:  2016-02-11       Impact factor: 4.466

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