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      Toward a Consensus on Applying Quantitative Liquid Chromatography‐Tandem Mass Spectrometry Proteomics in Translational Pharmacology Research: A White Paper

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          Abstract

          Quantitative translation of information on drug absorption, disposition, receptor engagement and drug-drug interactions from bench to bedside requires models informed by physiological parameters that link in vitro studies to in vivo outcomes. To predict in vivo outcomes, biochemical data from experimental systems are routinely scaled using protein quantity in these systems and relevant tissues. Although several laboratories have generated useful quantitative proteomic data using state-of-the-art mass spectrometry, no harmonized guidelines exit for sample analysis and data integration to in vivo translation practices. To address this gap, a workshop was held on September 27 th and 28 th , 2018, in Cambridge, MA, with 100 experts attending from academia, the pharmaceutical industry and regulators. Various aspects of quantitative proteomics and its applications in translational pharmacology were debated. A summary of discussions and best practices identified by this expert panel are presented in this ‘White Paper’ alongside unresolved issues which were outlined for future debates.

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          Most cited references65

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          Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics.

          Quantitative proteomics has traditionally been performed by two-dimensional gel electrophoresis, but recently, mass spectrometric methods based on stable isotope quantitation have shown great promise for the simultaneous and automated identification and quantitation of complex protein mixtures. Here we describe a method, termed SILAC, for stable isotope labeling by amino acids in cell culture, for the in vivo incorporation of specific amino acids into all mammalian proteins. Mammalian cell lines are grown in media lacking a standard essential amino acid but supplemented with a non-radioactive, isotopically labeled form of that amino acid, in this case deuterated leucine (Leu-d3). We find that growth of cells maintained in these media is no different from growth in normal media as evidenced by cell morphology, doubling time, and ability to differentiate. Complete incorporation of Leu-d3 occurred after five doublings in the cell lines and proteins studied. Protein populations from experimental and control samples are mixed directly after harvesting, and mass spectrometric identification is straightforward as every leucine-containing peptide incorporates either all normal leucine or all Leu-d3. We have applied this technique to the relative quantitation of changes in protein expression during the process of muscle cell differentiation. Proteins that were found to be up-regulated during this process include glyceraldehyde-3-phosphate dehydrogenase, fibronectin, and pyruvate kinase M2. SILAC is a simple, inexpensive, and accurate procedure that can be used as a quantitative proteomic approach in any cell culture system.
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            Quantitative analysis of complex protein mixtures using isotope-coded affinity tags.

            We describe an approach for the accurate quantification and concurrent sequence identification of the individual proteins within complex mixtures. The method is based on a class of new chemical reagents termed isotope-coded affinity tags (ICATs) and tandem mass spectrometry. Using this strategy, we compared protein expression in the yeast Saccharomyces cerevisiae, using either ethanol or galactose as a carbon source. The measured differences in protein expression correlated with known yeast metabolic function under glucose-repressed conditions. The method is redundant if multiple cysteinyl residues are present, and the relative quantification is highly accurate because it is based on stable isotope dilution techniques. The ICAT approach should provide a widely applicable means to compare quantitatively global protein expression in cells and tissues.
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              Is Open Access

              Data‐independent acquisition‐based SWATH ‐ MS for quantitative proteomics: a tutorial

              Abstract Many research questions in fields such as personalized medicine, drug screens or systems biology depend on obtaining consistent and quantitatively accurate proteomics data from many samples. SWATH‐MS is a specific variant of data‐independent acquisition (DIA) methods and is emerging as a technology that combines deep proteome coverage capabilities with quantitative consistency and accuracy. In a SWATH‐MS measurement, all ionized peptides of a given sample that fall within a specified mass range are fragmented in a systematic and unbiased fashion using rather large precursor isolation windows. To analyse SWATH‐MS data, a strategy based on peptide‐centric scoring has been established, which typically requires prior knowledge about the chromatographic and mass spectrometric behaviour of peptides of interest in the form of spectral libraries and peptide query parameters. This tutorial provides guidelines on how to set up and plan a SWATH‐MS experiment, how to perform the mass spectrometric measurement and how to analyse SWATH‐MS data using peptide‐centric scoring. Furthermore, concepts on how to improve SWATH‐MS data acquisition, potential trade‐offs of parameter settings and alternative data analysis strategies are discussed.
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                Author and article information

                Journal
                Clinical Pharmacology & Therapeutics
                Clin. Pharmacol. Ther.
                Wiley
                0009-9236
                1532-6535
                August 13 2019
                September 2019
                July 26 2019
                September 2019
                : 106
                : 3
                : 525-543
                Affiliations
                [1 ]Department of Pharmaceutics University of Washington Seattle Washington USA
                [2 ]Centre for Applied Pharmacokinetic Research University of Manchester Manchester UK
                [3 ]Department of Pharmacy Uppsala University Uppsala Sweden
                [4 ]Genentech South San Francisco California USA
                [5 ]Gilead Sciences Foster City California USA
                [6 ]Eshelman School of Pharmacy University of North Carolina at Chapel Hill Chapel Hill North Carolina USA
                [7 ]Biochemical Proteomics Group Max Planck Institute of Biochemistry Martinsried Germany
                [8 ]Pharmacokinetics Pharmacodynamics & Drug Metabolism Merck & Co., Inc. West Point Pennsylvania USA
                [9 ]Graduate School of Pharmaceutical Sciences Tohoku University Sendai Japan
                [10 ]Takeda California San Diego California USA
                [11 ]Certara (Simcyp Division) Sheffield UK
                Article
                10.1002/cpt.1537
                6692196
                31175671
                0ed978da-c7b0-4e53-86b9-bbd38b15242d
                © 2019

                http://onlinelibrary.wiley.com/termsAndConditions#vor

                http://doi.wiley.com/10.1002/tdm_license_1.1

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