Literature DB >> 25746131

Surfactant-aided precipitation/on-pellet-digestion (SOD) procedure provides robust and rapid sample preparation for reproducible, accurate and sensitive LC/MS quantification of therapeutic protein in plasma and tissues.

Bo An1,2, Ming Zhang1,2, Robert W Johnson3, Jun Qu1,2.   

Abstract

For targeted protein quantification by liquid chromatography mass spectrometry (LC/MS), an optimal approach for efficient, robust and hi-throughput sample preparation is critical, but often remains elusive. Here we describe a straightforward surfactant-aided-precipitation/on-pellet-digestion (SOD) strategy that provides effective sample cleanup and enables high and constant peptide yields in various matrices, allowing reproducible, accurate and sensitive protein quantification. This strategy was developed using quantification of monocolnocal antibody in tissues and plasma as the model system. Surfactant treatment before precipitation substantially increased peptide recovery and reproducibility from plasma/tissue, likely because surfactant permits extensive denaturation/reduction/alkylation of proteins and inactivation of endogenous protease inhibitors, and facilitates removal of matrix components. The subsequent precipitation procedure effectively eliminates the surfactant and nonprotein matrix components, and the thorough denaturation by both surfactant and precipitation enabled very rapid on-pellet-digestion (45 min at 37 °C) with high peptide recovery. The performance of SOD was systematically compared against in-solution-digestion, in-gel-digestion and filter-aided-sample-preparation (FASP) in plasma/tissues, and then examined in a full pharmacokinetic study in rats. SOD achieved the best peptide recovery (∼21.0-700% higher than the other three methods across various matrices), reproducibility (3.75-10.9%) and sensitivity (28-30 ng/g across plasma and tissue matrices), and its performance was independent of matrix types. Finally, in validation and pharmacokinetic studies in rats, SOD outperformed other methods and provided highly accurate and precise quantification in all plasma samples without using stable isotope labeled (SIL)-protein internal standard (I.S.). In summary, the SOD method has proven to be highly robust, efficient and rapid, making it readily adaptable to large-scale clinical and pharmaceutical quantification of biomarkers or biotherapeutics.

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Year:  2015        PMID: 25746131     DOI: 10.1021/acs.analchem.5b00350

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  21 in total

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Journal:  J Proteome Res       Date:  2016-04-11       Impact factor: 4.466

2.  "Catch-and-Release" Anti-Carcinoembryonic Antigen Monoclonal Antibody Leads to Greater Plasma and Tumor Exposure in a Mouse Model of Colorectal Cancer.

Authors:  Frank A Engler; Joseph Ryan Polli; Tommy Li; Bo An; Michael Otteneder; Jun Qu; Joseph P Balthasar
Journal:  J Pharmacol Exp Ther       Date:  2018-05-07       Impact factor: 4.030

3.  Temporal Effects of Combined Birinapant and Paclitaxel on Pancreatic Cancer Cells Investigated via Large-Scale, Ion-Current-Based Quantitative Proteomics (IonStar).

Authors:  Xue Wang; Jin Niu; Jun Li; Xiaomeng Shen; Shichen Shen; Robert M Straubinger; Jun Qu
Journal:  Mol Cell Proteomics       Date:  2018-01-22       Impact factor: 5.911

4.  Characterization and Proteomic-Transcriptomic Investigation of Monocarboxylate Transporter 6 Knockout Mice: Evidence of a Potential Role in Glucose and Lipid Metabolism.

Authors:  Robert S Jones; Chengjian Tu; Ming Zhang; Jun Qu; Marilyn E Morris
Journal:  Mol Pharmacol       Date:  2019-07-10       Impact factor: 4.436

5.  An IonStar Experimental Strategy for MS1 Ion Current-Based Quantification Using Ultrahigh-Field Orbitrap: Reproducible, In-Depth, and Accurate Protein Measurement in Large Cohorts.

Authors:  Xiaomeng Shen; Shichen Shen; Jun Li; Qiang Hu; Lei Nie; Chengjian Tu; Xue Wang; Benjamin Orsburn; Jianmin Wang; Jun Qu
Journal:  J Proteome Res       Date:  2017-05-25       Impact factor: 4.466

6.  Inflammasome Activation in Retinal Pigment Epithelium from Human Donors with Age-Related Macular Degeneration.

Authors:  Mara C Ebeling; Cody R Fisher; Rebecca J Kapphahn; Madilyn R Stahl; Shichen Shen; Jun Qu; Sandra R Montezuma; Deborah A Ferrington
Journal:  Cells       Date:  2022-06-30       Impact factor: 7.666

7.  Quantitative proteomic and phosphoproteomic profiling of ischemic myocardial stunning in swine.

Authors:  Xue Wang; Xiaomeng Shen; Brian R Weil; Rebeccah F Young; John M Canty; Jun Qu
Journal:  Am J Physiol Heart Circ Physiol       Date:  2020-03-30       Impact factor: 4.733

8.  A Comprehensive, Open-source Platform for Mass Spectrometry-based Glycoproteomics Data Analysis.

Authors:  Gang Liu; Kai Cheng; Chi Y Lo; Jun Li; Jun Qu; Sriram Neelamegham
Journal:  Mol Cell Proteomics       Date:  2017-09-08       Impact factor: 5.911

9.  Non-enzymolytic adenosine barcode-mediated dual signal amplification strategy for ultrasensitive protein detection using LC-MS/MS.

Authors:  Wen Yang; Tengfei Li; Chang Shu; Shunli Ji; Lei Wang; Yan Wang; Duo Li; Michael Mtalimanja; Luning Sun; Li Ding
Journal:  Mikrochim Acta       Date:  2018-05-10       Impact factor: 5.833

10.  Spatially-Resolved Proteomics: Rapid Quantitative Analysis of Laser Capture Microdissected Alveolar Tissue Samples.

Authors:  Geremy Clair; Paul D Piehowski; Teodora Nicola; Joseph A Kitzmiller; Eric L Huang; Erika M Zink; Ryan L Sontag; Daniel J Orton; Ronald J Moore; James P Carson; Richard D Smith; Jeffrey A Whitsett; Richard A Corley; Namasivayam Ambalavanan; Charles Ansong
Journal:  Sci Rep       Date:  2016-12-22       Impact factor: 4.379

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