Extending the Limits of Quantitative Proteome Profiling with Data-Independent Acquisition and Application to Acetaminophen-Treated Three-Dimensional Liver Microtissues
2015; Elsevier BV; Volume: 14; Issue: 5 Linguagem: Inglês
10.1074/mcp.m114.044305
ISSN1535-9484
AutoresRoland Bruderer, Oliver M. Bernhardt, Tejas Gandhi, Saša M. Miladinović, Lin‐Yang Cheng, Simon Messner, Tobias Ehrenberger, Vito Riccardo Tomaso Zanotelli, Yulia Butscheid, Claudia Escher, Olga Vitek, Oliver Rinner, Lukas Reiter,
Tópico(s)Mass Spectrometry Techniques and Applications
ResumoThe 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) 1The abbreviations used are:APAPacetaminophenATPadenosine triphosphateCVcoefficient of variationDIAdata-independent acquisitionDDAdata-dependent acquisitionFDRfalse discovery rateHRMhyper reaction monitoringiRTindexed retention timeNAPQIN-acetyl-p-benzoquinone imineSRMselected reaction monitoring; DIA with 32 sequential windows of 25 Dalton width. 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. 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) 1The abbreviations used are:APAPacetaminophenATPadenosine triphosphateCVcoefficient of variationDIAdata-independent acquisitionDDAdata-dependent acquisitionFDRfalse discovery rateHRMhyper reaction monitoringiRTindexed retention timeNAPQIN-acetyl-p-benzoquinone imineSRMselected reaction monitoring; DIA with 32 sequential windows of 25 Dalton width. 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). acetaminophen adenosine triphosphate coefficient of variation data-independent acquisition data-dependent acquisition false discovery rate hyper reaction monitoring indexed retention time N-acetyl-p-benzoquinone imine selected reaction monitoring; DIA with 32 sequential windows of 25 Dalton width. Our findings imply that DIA should be the preferred method for quantitative protein profiling. Quantitative mass spectrometry is a powerful and widely used approach to identify differentially abundant proteins, e.g. for proteome profiling and biomarker discovery (1Liu Y. Hittenhain R. Collins B. Aebersold R. Mass spectrometric protein maps for biomarker discovery and clinical research.Expert Rev. Mol. Diagn. 2013; 13: 811-825Crossref PubMed Scopus (99) Google Scholar). Several tens of thousands of peptides and thousands of proteins can be routinely identified from a single sample injection in shotgun proteomics (2Mann M. Kulak N.A. Nagaraj N. Cox J. The coming age of complete, accurate, and ubiquitous proteomes.Mol. Cell. 2013; 49: 583-590Abstract Full Text Full Text PDF PubMed Scopus (285) Google Scholar). Shotgun proteomics, however, is limited by low analytical reproducibility. This is due to the complexity of the samples that results in under sampling (supplemental Fig. 1) and to the fact that the acquisition of MS2 spectra is often triggered outside of the elution peak apex. As a result, only 17% of the detectable peptides are typically fragmented, and less than 60% of those are identified. This translates in reliable identification of only 10% of the detectable peptides (3Michalski A. Cox J. Mann M. 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Tate S. Röst H. Selevsek N. Reiter L. Bonner R. Aebersold R. Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis.Mol. Cell Proteomics. 2012; 11Abstract Full Text Full Text PDF PubMed Scopus (1777) Google Scholar). For the originally published SWATH-MS, the mass spectrometer cycles through 32 predefined, contiguous, 25 Thomson wide precursor windows, and records high-resolution fragment ion spectra (19Gillet L.C. Navarro P. Tate S. Röst H. Selevsek N. Reiter L. Bonner R. Aebersold R. Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis.Mol. Cell Proteomics. 2012; 11Abstract Full Text Full Text PDF PubMed Scopus (1777) Google Scholar). This results in a comprehensive measurement of all detectable precursors of the selected mass range. The main novelty of SWATH-MS was in the analysis of the collected DIA data. Predefined fragment ions are extracted using precompiled spectrum libraries, which results in SRM-like data. Such targeted analyses are now enabled by several publicly available computational tools, in particular Spectronaut 4Bernhardt, O. M., Selevsek, N., Gillet, L. C., Rinner, O., Picotti, P., Aebersold, R., and Reiter, L. (2012) Spectronaut A fast and efficient algorithm for MRM-like processing of data independent acquisition (SWATH-MS) data. Proceedings of the 60th ASMS Conference on Mass Spectrometry and Allied Topics, 2012, Vancouver, BC, Canada. Skyline (20MacLean B. Tomazela D.M. Shulman N. Chambers M. Finney G.L. Frewen B. Kern R. Tabb D.L. Liebler D.C. MacCoss M.J. Skyline: An open source document editor for creating and analyzing targeted proteomics experiments.Bioinformatics. 2010; 26: 966-968Crossref PubMed Scopus (2963) Google Scholar), and OpenSWATH (21Röst H.L. Rosenberger G. Navarro P. 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It consists of comprehensive DIA acquisition and targeted data analysis with retention-time-normalized spectral libraries (24Escher C. Reiter L. MacLean B. Ossola R. Herzog F. Chilton J. MacCoss M.J. Rinner O. Using iRT, a normalized retention time for more targeted measurement of peptides.Proteomics. 2012; 12: 1111-1121Crossref PubMed Scopus (382) Google Scholar). Its high accuracy of peptide identification and quantification is due to three aspects. First, we developed a novel, improved DIA method. Second, we reimplemented the mProphet (22Reiter L. Rinner O. Picotti P. Hittenhain R. Beck M. Brusniak M.-Y. Hengartner M.O. Aebersold R. mProphet: Automated data processing and statistical validation for large-scale SRM experiments.Nat. Methods. 2011; 8: 430-435Crossref PubMed Scopus (365) Google Scholar) approach in the software Spectronaut (www.spectronaut.org). Third, we developed large, optimized, and retention-time-normalized (iRT) spectral libraries. We compared HRM and state-of-the-art shotgun proteomics in terms of ability to discover differentially abundant proteins. For this purpose, we used a "profiling standard sample set" with 12 non-human proteins spiked at known absolute concentrations into a stable human cell line protein extract. This resulted in quasi complete data sets for HRM and the detection of a larger number of differentially abundant proteins as compared with shotgun proteomics. We utilized HRM to identify changes in the proteome in primary three-dimensional human liver microtissues after APAP exposure (25Van Summeren A. Renes J. Lizarraga D. Bouwman F.G. Noben J.-P. van Delft J.H.M. Kleinjans J.C. Mariman E.C. Screening for drug-induced hepatotoxicity in primary mouse hepatocytes using acetaminophen, amiodarone, and cyclosporin a as model compounds: an omics-guided approach.OMICS. 2013; 17: 71-83Crossref PubMed Scopus (15) Google Scholar, 26Jaeschke H. McGill M.R. Ramachandran A. Pathophysiological relevance of proteomics investigations of drug-induced hepatotoxicity in HepG2 cells.Toxicol. Sci. 2011; 121 (author reply 431–433): 428-430Crossref PubMed Scopus (7) Google Scholar, 27Messner S. Agarkova I. Moritz W. Kelm J.M. Multi-cell type human liver microtissues for hepatotoxicity testing.Arch. Toxicol. 2013; 87: 209-213Crossref PubMed Scopus (234) Google Scholar). These primary hepatocytes exhibit active drug metabolism. With a starting material of only 12,000 cells per sample, the abundance of 2,830 proteins was quantified over an APAP concentration range. Six novel NAPQI-cysteine proteins adducts that might be relevant for the toxicity of APAP were found and quantified mainly on mitochondrion-related proteins. Conalbumin was purchased from Fluka. Ribonuclease B, beta casein, fibrinogen, and myoglobin were purchased from SIGMA AltrichSt. Louis, MO. 6 Bovine Tryptic Digest Equal Molar Mix was purchased from Bruker, Billerica, MA. The HEK-293cells were kindly provided by Dr. Audrey van Drogen (ETH, Zurich). Iodoacetamide, tris(2-carboxyethyl)phosphine, trifluoroacetic acid, acetonitrile (ACN), HPLC water, ammonium bicarbonate, acetaminophen, and urea were purchased from SIGMA-Aldrich. Trypsin sequencing grade was purchased from Promega, Madison, WI. RapiGest was purchased from Waters, Milford, MA. Synthetic, heavy-labeled peptides were purchased from Thermo Scientific, Waltham, MA. A 15-cm dish of confluent HEK-293 cells was lysed by resuspension in 8 m urea and 0.1 m ammonium bicarbonate (to 1 μg/μl protein). The lysate was reduced with 5 mm tris(2-carboxyethyl)phosphine for 1 h at 37 °C. Subsequently, the lysate was alkylated with 25 mm iodoacetamide for 20 min at 21 °C. The lysate was diluted to 2 m urea and digested with trypsin at a ratio 1:100 (enzyme to protein) at 37 °C for 15 h. The samples were spun at 20,000 g at 4 °C for 10 min. The peptides were desalted using C18 MacroSpin columns from The Nest Group, Southborough, MA according to manufacturer's instructions. After drying, the peptides were resuspended in 1% ACN and 0.1% formic acid. 100 μg of conalbumin and ribonuclease B, beta-casein, fibrinogen, and myoglobin were prepared as described for the cell lysate above. The Biognosys' HRM Calibration Kit was added to all of the samples according to manufacturer's instructions (required for the DIA analysis using Biognosys' Spectronaut) Schlierern, ZH, Switzerland. 3D InSight™ Human Liver Microtissues (InSphero AG InSphero, Schlieren, ZH, Switzerland) consisting of primary human hepatocytes (lot IZT) and primary human non-parenchymal cells (lot JJB) were cultivated in GravityTRAP™ plates with 70 μl 3D InSight™ Human Liver Maintenance Medium (InSphero AG) per well (27Messner S. Agarkova I. Moritz W. Kelm J.M. Multi-cell type human liver microtissues for hepatotoxicity testing.Arch. Toxicol. 2013; 87: 209-213Crossref PubMed Scopus (234) Google Scholar). The liver microtissues were treated at cultivation day 5 with 0, 1.5, 4.5, 13.7, 41.2, 123, 5, 370.4, 1,111.1, 3,333.3, and 10,000 μm APAP (dissolved in the medium) for 3 days without redosing. Biological triplicates of each concentration were measured with CellTiter-Glo® ATP-assay (Promega). 12 single microtissues from each condition were pooled in an Eppendorf tube. Next, the cells were spun at 200g for 5 min at room temperature and then washed twice with PBS with spinning as before. The cells were lysed in 20 μl of 10 m urea, 0.1 m ammonium bicarbonate, and 0.1% RapiGest, sonicated for 3 min and centrifuged at 16,000 g for 2 min at 18 °C. Subsequently, the samples were prepared as described for the cell lysate above. 1 μg of the samples was analyzed on a self-made analytical column (75 μm × 30 cm) packed with 3 μm Magic C18AQ medium (Bruker) at 50 °C, using an Easy-nLC connected to a Q Exactive mass spectrometer (Thermo Scientific). The peptides were separated by a 2 h linear gradient of from 5 to 35% ACN with 0.1% formic acid at 300 nl/min, followed by a linear increase to 98% ACN in 2 min and 98% for 8 min. For DDA acquisition, the "fast" method from Kelstrup was used with the following alterations (28Kelstrup C.D. Young C. Lavallee R. Nielsen M.L. Olsen J.V Optimized fast and sensitive acquisition methods for shotgun proteomics on a quadrupole Orbitrap mass spectrometer.J. Proteome Res. 2012; 11: 3487-3497Crossref PubMed Scopus (208) Google Scholar). The full scan was performed between 400–1,220 m/z. The automatic gain control target for the MS/MS scan was set to 5e5. Stepped collision energy was 10% at 25%. The HRM DIA method consisted of a survey scan at 35,000 resolution from 400 to 1,220 m/z (automatic gain control target of 5*106 or 120ms injection time). Then, 19 DIA windows were acquired at 35,000 resolution (automatic gain control target 3e6 and auto for injection time) (supplemental Table 1). Stepped collision energy was 10% at 25%. The spectra were recorded in profile type. The MS/MS spectra were recorded from 200 to 1800 m/z. SRM was performed on a linear gradient form 5 to 35% ACN of 10 min on a Thermo Scientific TSQ Vantage using a 10-cm column as described above, unscheduled with 40 ms dwell time and 0.8 Thompson isolation width. 0.5 μm sample was spiked with the stable isotope standards. The raw mass spectrometric data were stored at the public repository PeptideAtlas (http://www.peptideatlas.org, No. PASS00589, the username is PASS00589 and the password is WF6554orn). The DIA data were analyzed with Spectronaut 5, a mass spectrometer vendor-independent software from Biognosys. The default settings were used for the Spectronaut search. Retention time prediction type was set to dynamic iRT (correction factor for window 1). Decoy generation was set to scrambled (no decoy limit). Interference correction on MS2 level was enabled. The false discovery rate (FDR) was set to 1% at peptide level. The DDA spectra were analyzed with the MaxQuant Version 1.4.1.2 analysis software using default settings with the following alterations (29Cox J. Mann M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.Nat. Biotechnol. 2008; 26: 1367-1372Crossref PubMed Scopus (9150) Google Scholar). The minimal peptide length was set to 6. Search criteria included carbamidomethylation of cysteine as a fixed modification, oxidation of methionine and acetyl (protein N terminus) as variable modifications. The mass tolerance for the precursor was 4.5 ppm and for the fragment ions was 20 ppm. The DDA files were searched against the human UniProt fasta database (state 29.04.2013, 20,254 entries), the spike in proteins (12 entries), and the Biognosys iRT peptide sequences (11 entries). The identifications were filtered to satisfy FDR of 1% on peptide and protein level. For generation of the spectral libraries, 24 DDA measurements of the "profiling standard sample set" or six DDA measurements of the microtissues were performed. DDA spectra were analyzed as described above, and a spectral library was generated using spectral library generation in Spectronaut, similar to SpectraST (30Lam H. Deutsch E.W. Eddes J.S. Eng J.K. King N. Stein S.E. Aebersold R. Development and validation of a spectral library searching method for peptide identification from MS/MS.Proteomics. 2007; 7: 655-667Crossref PubMed Scopus (397) Google Scholar). Apart from annotation of precursors and fragment ions the library also contained normalized retention times (iRT). For the generation of the assays of the APAP adducts, a variable modification (C8H7NO2) was generated modifying the cysteine. The carbamidomethyl cysteine was set to variable modification. For the profiling standard sample set, peptides shared between HEK-293 proteome, the spike-in proteins, and contaminants from MaxQuant were removed. For precursors that were identified multiple times within one MS run using MaxQuant, the most intense identification was selected. Full peptide profiles were defined as full peptide precursor profiles not merging modified species and charge states. The microtissue candidate lists were generated with FDR of 0.05 (adj. p value) and fold change to control of more than 50%. Gene ontology enrichment was performed using DAVID Bioinformatics Resources 6.7 (31Huang da W. Sherman B.T. Lempicki R.A. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.Nat. Protoc. 2009; 4: 44-57Crossref PubMed Scopus (25338) Google Scholar). For both DDA and DIA, the log2-intensities of the peptides were summarized across all the samples and runs, and separately for each protein, in a linear mixed model implemented in MSstats (32Choi M. Chang C.-Y. Clough T. Broudy D. Killeen T. MacLean B. Vitek O. MSstats: An R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments.Bioinformatics. 2014; 30: 2524-2526Crossref PubMed Scopus (518) Google Scholar). The model is summarized below. Here [GRAPHIC] denotes sample [GRAPHIC], [GRAPHIC] denotes precursor [GRAPHIC], and [GRAPHIC] denotes run [GRAPHIC] denotes the log-intensities of the peptides, and [GRAPHIC] denotes the random nonsystematic deviations of the observed intensities that are not explained by the systematic sources of variation. Model: Linear Mixed Effects Model Implemented in MSstats Equation:yijk=μ+Si+Pj+Rk+εijkConstraints:ΣiSi=0,ΣjPj=0Assumption:εijk∼N0,σ2,Rk2∼N0,σrun2Hypothesis:H0:Si=SiHa:Si≠Si∀i≠i Model Fit. Restricted Maximum Likelihood Estimator (RMLE) Test Statistic:yi¯−yj¯21rpσ^2+1rσ^run2∼tp(r−1) Notation: r = the number of runs = 3, p = the numbers of precursors, σ̂2 = the RMLE of the variance of the random error, σ̂run2 = the RMLE of the variance of Run Note: The test statistic is given for the special case of a balanced dataset with no missing values. The model was used to perform all the 28 possible pairwise comparisons of samples, separately for each protein. The p values were adjusted for multiple testing using the Benjamini-Hochberg method (33Benjamini Y. Hochberg Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing.J. R. Stat. Soc. 1995; 57 (http://www.jstor.org/stable/2346101): 289-300Google Scholar). For unfeasible comparisons caused by missing values, the p value was set to 1, reflecting inability to detect differential abundance. The R package pROC was used to obtain the receiving operator characteristic curves, and calculate the areas under the curve. The areas under the curves obtained with two acquisition strategies were compared using the DeLong's test (34DeLong E.R. DeLong D.M. Clarke-Pearson D.L. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.Biometrics. 1988; 44: 837-845Crossref PubMed Scopus (14161) Google Scholar). A novel acquisition method was developed to enable high performance DIA on a Q Exactive instrument. It consists of one survey scan (MS1), and 19 variable DIA swaths (MS2) that adapt to the different total ion current complexity of precursor-ion mass range (Fig. 1A and supplemental Table 1). This method is utilizing the new DIA workflow of Xcalibur 3.0, which enables direct measurement of large DIA windows with automatic gain control. This reduces the cycle time (3.5 s) by a factor of 1.7 as compared with the previously used MS1/AIF (All Ion Fragmentation) method for DIA 3Bruderer, R. M., Miladinović, S. M., Bernhardt, O. B., Rinner, O., Aebersold, R., and Reiter L. (2013) Highly multiplexed protein profiling across large sets of samples: A comparison of SWATH acquisition with shotgun LC-MS/MS. 61th ASMS Conference on Mass Spectrometry and Allied Topics, 2013, Minneapolis Convention Center, Minneapolis, MN. , while matching the cycle time of the original SWATH-MS acquisition method (19Gillet L.C. Navarro P. Tate S. Röst H. Selevsek N. Reiter L. Bonner R. Aebersold R. Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis.Mol. Cell Proteomics. 2012; 11Abstract Full Text Full Text PDF PubMed Scopus (1777) Google Scholar). The DIA method is optimized to the used LC peak capacity resulting on average in six to eight data points per peak. To extract intensities of peptides from spectra of the DIA data, we have developed a mass spectrometer vendor-independent software called Spectronaut. Peak picking and scoring is largely similar to SRM (22Reiter L. Rinner O. Picotti P. Hittenhain R. Beck M. Brusniak M.-Y. Hengartner M.O. Aebersold R. mProphet: Automated data processing and statistical validation for large-scale SRM experiments.Nat. Methods. 2011; 8: 430-435Crossref PubMed Scopus (365) Google Scholar), with notable exceptions. First, fragment ions can be defined post acquisition. Second, the large-scale nature of DIA experiments facilitates the use of robust and efficient machine learning algorithms for peak picking and scoring. Retention time information can be used to accurately predict the elution of the peptides by in-measurement calibration of iRT values. This can be thought of as a computational scheduling procedure, which allows the usage of ion current extraction windows with the width of a few percent of the gradient expected to satisfy over 99% of peptides (Fig. 1B). Third, peptide quantification is further improved by means of an automated, advanced interference detection algorithm (Fig. 1C). The method of decoy generation is crucial for the accuracy of the resulting FDR (35Elias J.E. Gygi S.P. Target-decoy search strategy for mass spectrometry-based proteomics.Methods Mol. Biol. 2010; 604: 55-71Crossref PubMed Scopus (403) Google Scholar). The model implemented in Spectronaut was validated by searching yeast peptides in DIA-spectra derived from a human cell line. The score distribution of the decoys was compared with the score distributions of the spectra of the truly absent (yeast) peptides (Fig. 1D). To benchmark the profiling performance of HRM and to compare with the established shotgun proteomics, we generated a series of controlled mixtures termed the profiling standard sample set. 12 non-human proteins (supplemental Table 2) were spiked into a constant background (HEK-293). The profiling standard sample set presented two main challenges for mass spectrometric profiling: detection of a small number of differentially abundant proteins among a background of not-changing proteins and precise relative quantification. The 12 spike-in proteins were grouped into three master mixes. Two master mixes were diluted to introduce small differences in concentrations (10 and 60% changes) at limit of detection and at 10- and 50-fold higher concentrations. The third master mix was pipetted in a fourfold dilution series starting at the limit of detection (Fig. 2A). Spectra from the profiling standard samp
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