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      Extending the Limits of Quantitative Proteome Profiling with Data-Independent Acquisition and Application to Acetaminophen-Treated Three-Dimensional Liver Microtissues*

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          Abstract

          The data-independent acquisition (DIA) approach has recently been introduced as a novel mass spectrometric method that promises to combine the high content aspect of shotgun proteomics with the reproducibility and precision of selected reaction monitoring. Here, we evaluate, whether SWATH-MS type DIA effectively translates into a better protein profiling as compared with the established shotgun proteomics.

          We implemented a novel DIA method on the widely used Orbitrap platform and used retention-time-normalized (iRT) spectral libraries for targeted data extraction using Spectronaut. We call this combination hyper reaction monitoring (HRM). Using a controlled sample set, we show that HRM outperformed shotgun proteomics both in the number of consistently identified peptides across multiple measurements and quantification of differentially abundant proteins. The reproducibility of HRM in peptide detection was above 98%, resulting in quasi complete data sets compared with 49% of shotgun proteomics.

          Utilizing HRM, we profiled acetaminophen (APAP) 1 -treated three-dimensional human liver microtissues. An early onset of relevant proteome changes was revealed at subtoxic doses of APAP. Further, we detected and quantified for the first time human NAPQI-protein adducts that might be relevant for the toxicity of APAP. The adducts were identified on four mitochondrial oxidative stress related proteins (GATM, PARK7, PRDX6, and VDAC2) and two other proteins (ANXA2 and FTCD).

          Our findings imply that DIA should be the preferred method for quantitative protein profiling.

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          Most cited references29

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          Absolute quantification of proteins and phosphoproteins from cell lysates by tandem MS.

          A need exists for technologies that permit the direct quantification of differences in protein and posttranslationally modified protein expression levels. Here we present a strategy for the absolute quantification (termed AQUA) of proteins and their modification states. Peptides are synthesized with incorporated stable isotopes as ideal internal standards to mimic native peptides formed by proteolysis. These synthetic peptides can also be prepared with covalent modifications (e.g., phosphorylation, methylation, acetylation, etc.) that are chemically identical to naturally occurring posttranslational modifications. Such AQUA internal standard peptides are then used to precisely and quantitatively measure the absolute levels of proteins and posttranslationally modified proteins after proteolysis by using a selected reaction monitoring analysis in a tandem mass spectrometer. In the present work, the AQUA strategy was used to (i) quantify low abundance yeast proteins involved in gene silencing, (ii) quantitatively determine the cell cycle-dependent phosphorylation of Ser-1126 of human separase protein, and (iii) identify kinases capable of phosphorylating Ser-1501 of separase in an in vitro kinase assay. The methods described here represent focused, alternative approaches for studying the dynamically changing proteome.
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            OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data.

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              Automated approach for quantitative analysis of complex peptide mixtures from tandem mass spectra.

              To take advantage of the potential quantitative benefits offered by tandem mass spectrometry, we have modified the method in which tandem mass spectrum data are acquired in 'shotgun' proteomic analyses. The proposed method is not data dependent and is based on the sequential isolation and fragmentation of precursor windows (of 10 m/z) within the ion trap until a desired mass range has been covered. We compared the quantitative figures of merit for this method to those for existing strategies by performing an analysis of the soluble fraction of whole-cell lysates from yeast metabolically labeled in vivo with (15)N. To automate this analysis, we modified software (RelEx) previously written in the Yates lab to generate chromatograms directly from tandem mass spectra. These chromatograms showed improvements in signal-to-noise ratio of approximately three- to fivefold over corresponding chromatograms generated from mass spectrometry scans. In addition, to demonstrate the utility of the data-independent acquisition strategy coupled with chromatogram reconstruction from tandem mass spectra, we measured protein expression levels in two developmental stages of Caenorhabditis elegans.
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                Author and article information

                Journal
                Mol Cell Proteomics
                Mol. Cell Proteomics
                mcprot
                mcprot
                MCP
                Molecular & Cellular Proteomics : MCP
                The American Society for Biochemistry and Molecular Biology
                1535-9476
                1535-9484
                May 2015
                27 February 2015
                27 February 2015
                : 14
                : 5
                : 1400-1410
                Affiliations
                [1]From the ‡Biognosys, Wagistrasse 25, CH-8952 Schlieren, Switzerland;
                [2]§Institute of Molecular Systems Biology, ETH Zurich, Auguste-Piccard-Hof 1, 8093 Zurich, Switzerland;
                [3]¶Department of Statistics, Department of Computer Science, Purdue University, 150 N. University Street, West Lafayette, IN 47907-2068;
                [4]**InSphero AG, Wagistrasse 25, CH-8952 Schlieren, Switzerland
                Author notes
                To whom correspondence should be addressed: Wagistrasse 25, CH-8952 Schlieren, Switzerland. Tel.: +41 (0)44 738 20 43, Fax: +41 44 730 20 49; E-mail: reiter@ 123456biognosys.ch .

                ‡‡ These authors contributed to this work equally.

                Article
                M114.044305
                10.1074/mcp.M114.044305
                4424408
                25724911
                39851c79-0c92-4b7b-8d51-91cd1bd0ed00
                © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

                Author's Choice—Final version free via Creative Commons CC-BY license.

                History
                : 9 September 2014
                : 18 February 2015
                Categories
                Research

                Molecular biology
                Molecular biology

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