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• W2910656520 abstract "Quantitative cross-linking mass spectrometry (QCLMS) reveals structural detail on altered protein states in solution. On its way to becoming a routine technology, QCLMS could benefit from data-independent acquisition (DIA), which generally enables greater reproducibility than data-dependent acquisition (DDA) and increased throughput over targeted methods. Therefore, here we introduce DIA to QCLMS by extending a widely used DIA software, Spectronaut, to also accommodate cross-link data. A mixture of seven proteins cross-linked with bis[sulfosuccinimidyl] suberate (BS3) was used to evaluate this workflow. Out of the 414 identified unique residue pairs, 292 (70%) were quantifiable across triplicates with a coefficient of variation (CV) of 10%, with manual correction of peak selection and boundaries for PSMs in the lower quartile of individual CV values. This compares favorably to DDA where we quantified cross-links across triplicates with a CV of 66%, for a single protein. We found DIA-QCLMS to be capable of detecting changing abundances of cross-linked peptides in complex mixtures, despite the ratio compression encountered when increasing sample complexity through the addition of E. coli cell lysate as matrix. In conclusion, the DIA software Spectronaut can now be used in cross-linking and DIA is indeed able to improve QCLMS. Quantitative cross-linking mass spectrometry (QCLMS) reveals structural detail on altered protein states in solution. On its way to becoming a routine technology, QCLMS could benefit from data-independent acquisition (DIA), which generally enables greater reproducibility than data-dependent acquisition (DDA) and increased throughput over targeted methods. Therefore, here we introduce DIA to QCLMS by extending a widely used DIA software, Spectronaut, to also accommodate cross-link data. A mixture of seven proteins cross-linked with bis[sulfosuccinimidyl] suberate (BS3) was used to evaluate this workflow. Out of the 414 identified unique residue pairs, 292 (70%) were quantifiable across triplicates with a coefficient of variation (CV) of 10%, with manual correction of peak selection and boundaries for PSMs in the lower quartile of individual CV values. This compares favorably to DDA where we quantified cross-links across triplicates with a CV of 66%, for a single protein. We found DIA-QCLMS to be capable of detecting changing abundances of cross-linked peptides in complex mixtures, despite the ratio compression encountered when increasing sample complexity through the addition of E. coli cell lysate as matrix. In conclusion, the DIA software Spectronaut can now be used in cross-linking and DIA is indeed able to improve QCLMS. Cross-linking mass spectrometry (CLMS) 1The abbreviations used are:CLMScross-linking mass spectrometryAcHacetic acidACNacetonitrileAGCautomatic gain controlBS3bis[sulfosuccinimidyl] suberateCLcross-linkingCVcoefficient of variationDDAdata-dependent acquisitionDIAdata-independent acquisitionDTTdithiothreitolHCDhigh energy collision dissociationHAShuman serum albuminIAA2-iodoacetamideiTRAQisobaric tags for relative and absolute quantitationLC-MSliquid chromatography-mass spectrometryLFQlabel-free quantitationNH4Acammonium acetatePRMparallel reaction monitoringPSMpeptide spectrum matchesQCLMSquantitative cross-linking mass spectrometrySCXstrong cation exchange chromatographySILACstable isotope-labelled amino acidsSRM/MRMselected reaction monitoring/multiple reaction monitoringTMTtandem mass tagURPsunique residue pairs. 1The abbreviations used are:CLMScross-linking mass spectrometryAcHacetic acidACNacetonitrileAGCautomatic gain controlBS3bis[sulfosuccinimidyl] suberateCLcross-linkingCVcoefficient of variationDDAdata-dependent acquisitionDIAdata-independent acquisitionDTTdithiothreitolHCDhigh energy collision dissociationHAShuman serum albuminIAA2-iodoacetamideiTRAQisobaric tags for relative and absolute quantitationLC-MSliquid chromatography-mass spectrometryLFQlabel-free quantitationNH4Acammonium acetatePRMparallel reaction monitoringPSMpeptide spectrum matchesQCLMSquantitative cross-linking mass spectrometrySCXstrong cation exchange chromatographySILACstable isotope-labelled amino acidsSRM/MRMselected reaction monitoring/multiple reaction monitoringTMTtandem mass tagURPsunique residue pairs. is a powerful tool for studying the 3D structure of proteins and their complexes (1Sinz A. The advancement of chemical cross-linking and mass spectrometry for structural proteomics: from single proteins to protein interaction networks.Expert Rev. Proteomics. 2014; 11: 733-743Crossref PubMed Scopus (102) Google Scholar, 2Liu F. Heck A.J.R. Interrogating the architecture of protein assemblies and protein interaction networks by cross-linking mass spectrometry.Curr. Opin. Struct. Biol. 2015; 35: 100-108Crossref PubMed Scopus (84) Google Scholar, 3Leitner A. Faini M. Stengel F. Aebersold R. Crosslinking and mass spectrometry: an integrated technology to understand the structure and function of molecular machines.Trends Biochem. Sci. 2016; 41: 20-32Abstract Full Text Full Text PDF PubMed Scopus (253) Google Scholar, 4Schneider M. Belsom A. Rappsilber J. Protein tertiary structure by crosslinking/mass spectrometry.Trends Biochem. Sci. 2018; 43: 157-169Abstract Full Text Full Text PDF PubMed Scopus (57) Google Scholar, 5Chavez J.D. Bruce J.E. Chemical cross-linking with mass spectrometry: a tool for systems structural biology.Curr. Opin. Chem. Biol. 2018; 48: 8-18Crossref PubMed Scopus (84) Google Scholar). Chemical cross-linking helps to identify residue pairs that are in proximity in native structures but not necessarily in primary sequence, by introducing covalent bonds between these residues. Subsequent to the cross-linking reaction and the proteolytic digestion of proteins, cross-linked peptides can be enriched (using strong cation exchange (SCX) (6Chen Z.A. Jawhari A. Fischer L. Buchen C. Tahir S. Kamenski T. Rasmussen M. Lariviere L. Bukowski-Wills J.-C. Nilges M. Cramer P. Rappsilber J. Architecture of the RNA polymerase II-TFIIF complex revealed by cross-linking and mass spectrometry.EMBO J. 2010; 29: 717-726Crossref PubMed Scopus (324) Google Scholar) or size exclusion chromatography (SEC) (7Leitner A. Reischl R. Walzthoeni T. Herzog F. Bohn S. Förster F. Aebersold R. Expanding the chemical cross-linking toolbox by the use of multiple proteases and enrichment by size exclusion chromatography.Mol. Cell. Proteomics. 2012; 11 (M111.014126)Abstract Full Text Full Text PDF PubMed Scopus (212) Google Scholar), for example) and then identified through liquid chromatography-mass spectrometry (LC-MS) combined with database searching. cross-linking mass spectrometry acetic acid acetonitrile automatic gain control bis[sulfosuccinimidyl] suberate cross-linking coefficient of variation data-dependent acquisition data-independent acquisition dithiothreitol high energy collision dissociation human serum albumin 2-iodoacetamide isobaric tags for relative and absolute quantitation liquid chromatography-mass spectrometry label-free quantitation ammonium acetate parallel reaction monitoring peptide spectrum matches quantitative cross-linking mass spectrometry strong cation exchange chromatography stable isotope-labelled amino acids selected reaction monitoring/multiple reaction monitoring tandem mass tag unique residue pairs. cross-linking mass spectrometry acetic acid acetonitrile automatic gain control bis[sulfosuccinimidyl] suberate cross-linking coefficient of variation data-dependent acquisition data-independent acquisition dithiothreitol high energy collision dissociation human serum albumin 2-iodoacetamide isobaric tags for relative and absolute quantitation liquid chromatography-mass spectrometry label-free quantitation ammonium acetate parallel reaction monitoring peptide spectrum matches quantitative cross-linking mass spectrometry strong cation exchange chromatography stable isotope-labelled amino acids selected reaction monitoring/multiple reaction monitoring tandem mass tag unique residue pairs. Although a protein's function links to its three-dimensional structure, these structures are intrinsically dynamic and can change (8Debrunner P.G. Frauenfelder H. Dynamics of Proteins.Annu. Rev. Phys. Chem. 1982; 33: 283-299Crossref Google Scholar, 9Karplus M. Dynamics of proteins.Adv. Biophys. 1984; 18: 165-190Crossref PubMed Scopus (23) Google Scholar). Adding quantitative information to the relative abundances of cross-linked residue pairs offers a unique opportunity to study the structural flexibility and changes of proteins (10Chen Z.A. Rappsilber J. Protein dynamics in solution by quantitative cross-linking mass spectrometry.Trends Biochem. Sci. 2018; 43: 908-920Abstract Full Text Full Text PDF PubMed Scopus (36) Google Scholar). Previous studies using quantitative cross-linking mass spectrometry (QCLMS) have provided concepts and techniques for studying changing protein states including activation (11Huang B.X. Interdomain conformational changes in akt activation revealed by chemical cross-linking and tandem mass spectrometry.Mol. Cell. Proteomics. 2006; 5: 1045-1053Abstract Full Text Full Text PDF PubMed Scopus (46) Google Scholar), regulation of protein networks (12Huang B.X. Kim H.-Y. Probing Akt-inhibitor interaction by chemical cross-linking and mass spectrometry.J. Am. Soc. Mass Spectrom. 2009; 20: 1504-1513Crossref PubMed Scopus (15) Google Scholar, 13Chen Z.A. Pellarin R. Fischer L. Sali A. Nilges M. Barlow P.N. Rappsilber J. Structure of complement C3(H2O) revealed by quantitative cross-linking mass spectrometry and modeling.Mol. Cell. Proteomics. 2016; 15: 2730-2743Abstract Full Text Full Text PDF PubMed Scopus (47) Google Scholar, 14Chen Z. Fischer L. Tahir S. Bukowski-Wills J.-C. Barlow P. Rappsilber J. Quantitative cross-linking mass spectrometry reveals subtle protein conformational changes.Wellcome Open Res. 2016; 1: 5Crossref PubMed Scopus (21) Google Scholar, 15Herbert A.P. Makou E. Chen Z.A. Kerr H. Richards A. Rappsilber J. Barlow P.N. Complement Evasion Mediated by Enhancement of Captured Factor H: Implications for Protection of Self-Surfaces from Complement.J. Immunol. 2015; 195: 4986-4998Crossref PubMed Scopus (52) Google Scholar), maturation of complexes (16Tomko R.J. Taylor D.W. Chen Z.A. Wang H.W. Rappsilber J. Hochstrasser M. A single α helix drives extensive remodeling of the proteasome lid and completion of regulatory particle assembly.Cell. 2015; 163: 432-444Abstract Full Text Full Text PDF PubMed Scopus (58) Google Scholar), regulation of enzyme activity (17Schmidt C. Zhou M. Marriott H. Morgner N. Politis A. Robinson C.V. Comparative cross-linking and mass spectrometry of an intact F-type ATPase suggest a role for phosphorylation.Nat. Commun. 2013; 4: 1985Crossref PubMed Scopus (111) Google Scholar, 18Yu C. Mao H. Novitsky E.J. Tang X. Rychnovsky S.D. Zheng N. Huang L. Gln40 deamidation blocks structural reconfiguration and activation of SCF ubiquitin ligase complex by Nedd8.Nat. Commun. 2015; 6: 10053Crossref PubMed Scopus (32) Google Scholar, 19Boelt S.G. Norn C. Rasmussen M.I. André I. Čiplys Slibinskas E.R. Houen G. Højrup P. Mapping the Ca(2+) induced structural change in calreticulin.J. Proteomics. 2016; 142: 138-148Crossref PubMed Scopus (27) Google Scholar), protein-protein interactions (20Beilsten-Edmands V. Gordiyenko Y. Kung J.C. Mohammed S. Schmidt C. Robinson C.V. eIF2 interactions with initiator tRNA and eIF2B are regulated by post-translational modifications and conformational dynamics.Cell Discov. 2015; 1: 15020Crossref PubMed Scopus (20) Google Scholar, 21Koehler C. Sauter P.F. Wawryszyn M. Girona G.E. Gupta K. Landry J.J.M. Fritz M.H.-Y. Radic K. Hoffmann J.-E. Chen Z.A. Zou J. Tan P.S. Galik B. Junttila S. Stolt-Bergner P. Pruneri G. Gyenesei A. Schultz C. Biskup M.B. Besir H. Benes V. Rappsilber J. Jechlinger M. Korbel J.O. Berger I. Braese S. Lemke E.A. Genetic code expansion for multiprotein complex engineering.Nat. Methods. 2016; 13: 997-1000Crossref PubMed Scopus (46) Google Scholar) and interactome analysis of cancer cell lines (22Chavez J.D. Schweppe D.K. Eng J.K. Zheng C. Taipale A. Zhang Y. Takara K. Bruce J.E. Quantitative interactome analysis reveals a chemoresistant edgotype.Nat. Commun. 2015; 6: 7928Crossref PubMed Scopus (65) Google Scholar). Broadly speaking, two quantitative strategies are suitable for QCLMS: labeled and label-free. Although isotope-labeled cross-linkers (23Müller D.R. Schindler P. Towbin H. Wirth U. Voshol H. Hoving S. Steinmetz M.O. Isotope-tagged cross-linking reagents. A new tool in mass spectrometric protein interaction analysis.Anal. Chem. 2001; 73: 1927-1934Crossref PubMed Scopus (187) Google Scholar) are commonly used in labeling strategies (13, 14, 16–19, 24–29), other general strategies have also been adapted to QCLMS including SILAC (stable isotope-labeled amino acids) (22Chavez J.D. Schweppe D.K. Eng J.K. Zheng C. Taipale A. Zhang Y. Takara K. Bruce J.E. Quantitative interactome analysis reveals a chemoresistant edgotype.Nat. Commun. 2015; 6: 7928Crossref PubMed Scopus (65) Google Scholar, 30Ong S.-E. Blagoev B. Kratchmarova I. Kristensen D.B. Steen H. Pandey A. Mann M. Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics.Mol. Cell. Proteomics. 2002; 1: 376-386Abstract Full Text Full Text PDF PubMed Scopus (4569) Google Scholar, 31Chavez J.D. Schweppe D.K. Eng J.K. Bruce J.E. In vivo conformational dynamics of Hsp90 and its interactors.Cell Chem. Biol. 2016; 23: 716-726Abstract Full Text Full Text PDF PubMed Scopus (55) Google Scholar) and isobaric labeling by TMT (32Thompson A. Schäfer J. Kuhn K. Kienle S. Schwarz J. Schmidt G. Neumann T. Johnstone R. Mohammed A.K.A. Hamon C. Tandem mass tags: a novel quantification strategy for comparative analysis of complex protein mixtures by MS/MS.Anal. Chem. 2003; 75: 1895-1904Crossref PubMed Scopus (1709) Google Scholar, 33Yu C. Huszagh A. Viner R. Novitsky E.J. Rychnovsky S.D. Huang L. Developing a multiplexed quantitative cross-linking mass spectrometry platform for comparative structural analysis of protein complexes.Anal. Chem. 2016; 88: 10301-10308Crossref PubMed Scopus (45) Google Scholar) or iTRAQ (34Ross P.L. Huang Y.N. Marchese J.N. Williamson B. Parker K. Hattan S. Khainovski N. Pillai S. Dey S. Daniels S. Purkayastha S. Juhasz P. Martin S. Bartlet-Jones M. He F. Jacobson A. Pappin D.J. Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents.Mol. Cell. Proteomics. 2004; 3: 1154-1169Abstract Full Text Full Text PDF PubMed Scopus (3680) Google Scholar). In contrast, label-free quantitation (LFQ) might allow for a simpler experimental design and reduced costs. Importantly, although samples are processed separately during LFQ experiments, which may increase technical variance, label-free QCLMS is as reproducible as other proteomic techniques (35Müller F. Fischer L. Chen Z.A. Auchynnikava T. Rappsilber J. On the reproducibility of label-free quantitative cross-linking mass spectrometry.J. Am. Soc. Mass Spectrom. 2018; 29: 405-412Crossref PubMed Scopus (28) Google Scholar). Multiple approaches are used in proteomics for LFQ (36Nahnsen S. Bielow C. Reinert K. Kohlbacher O. Tools for label-free peptide quantification.Mol. Cell. Proteomics. 2013; 12: 549-556Abstract Full Text Full Text PDF PubMed Scopus (171) Google Scholar, 37Arike L. Valgepea K. Peil L. Nahku R. Adamberg K. Vilu R. Comparison and applications of label-free absolute proteome quantification methods on Escherichia coli.J. Proteomics. 2012; 75: 5437-5448Crossref PubMed Scopus (123) Google Scholar). Data-dependent acquisition (DDA) unfortunately results in poor reproducibility for low abundance proteins or peptides (38Bensimon A. Heck A.J.R. Aebersold R. Mass spectrometry-based proteomics and network biology.Annu. Rev. Biochem. 2012; 81: 379-405Crossref PubMed Scopus (317) Google Scholar, 39Gillet 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; 11 (O111.016717)Abstract Full Text Full Text PDF PubMed Scopus (1777) Google Scholar, 40Hu A. Noble W.S. Wolf-Yadlin A. Technical advances in proteomics: new developments in data-independent acquisition.F1000Res. 2016; 5: 419Crossref Scopus (135) Google Scholar) and therefore is not ideal for the typically low abundance cross-linked peptides. Targeted proteomic strategies such as SRM (MRM) or PRM excel for less abundant peptides (41Shi T. Su D. Liu T. Tang K. Camp 2nd, D.G. Qian W.J. Smith R.D. Advancing the sensitivity of selected reaction monitoring-based targeted quantitative proteomics.Proteomics. 2012; 12: 1074-1092Crossref PubMed Scopus (167) Google Scholar, 42Lange V. Picotti P. Domon B. Aebersold R. Selected reaction monitoring for quantitative proteomics: a tutorial.Mol. Syst. Biol. 2008; 4: 222Crossref PubMed Scopus (1121) Google Scholar, 43Picotti P. Aebersold R. Selected reaction monitoring-based proteomics: workflows, potential, pitfalls and future directions.Nat. Methods. 2012; 9: 555-566Crossref PubMed Scopus (991) Google Scholar, 44Gillette M.A. Carr S.A. Quantitative analysis of peptides and proteins in biomedicine by targeted mass spectrometry.Nat. Methods. 2013; 10: 28-34Crossref PubMed Scopus (359) Google Scholar, 45Peterson A.C. Russell J.D. Bailey D.J. Westphall M.S. Coon J.J. Parallel reaction monitoring for high resolution and high mass accuracy quantitative, targeted proteomics.Mol. Cell. Proteomics. 2012; 11: 1475-1488Abstract Full Text Full Text PDF PubMed Scopus (819) Google Scholar). Early targeted approaches on cross-linking mass spectrometry using an inclusion list were performed by Barysz et al. 2015 (46Barysz H. Kim J.H. Chen Z.A. Hudson D.F. Rappsilber J. Gerloff D.L. Earnshaw W.C. Three-dimensional topology of the SMC2/SMC4 subcomplex from chicken condensin I revealed by cross-linking and molecular modelling.Open Biol. 2015; 5: 150005Crossref PubMed Scopus (41) Google Scholar) and more recently, on MS2 level using parallel reaction monitoring (PRM) and Skyline (47Chavez J.D. Eng J.K. Schweppe D.K. Cilia M. Rivera K. Zhong X. Wu X. Allen T. Khurgel M. Kumar A. Lampropoulos A. Larsson M. Maity S. Morozov Y. Pathmasiri W. Perez-Neut M. Pineyro-Ruiz C. Polina E. Post S. Rider M. Tokmina-Roszyk D. Tyson K. Vieira Parrine Sant'Ana D. Bruce J.E. A general method for targeted quantitative cross-linking mass spectrometry.PLoS ONE. 2016; 11: e0167547Crossref PubMed Scopus (34) Google Scholar). However, the number of targets is limited, and the analysis is demanding. Data-independent acquisition (DIA) promises a solution to all these challenges by requiring minimal assay development and allowing large scale quantitative analysis with high reproducibility (48Bilbao A. Varesio E. Luban J. Strambio-De-Castillia C. Hopfgartner G. Müller M. Lisacek F. Processing strategies and software solutions for data-independent acquisition in mass spectrometry.Proteomics. 2015; 15: 964-980Crossref PubMed Scopus (116) Google Scholar, 49Bruderer R. Sondermann J. Tsou C.-C. Barrantes-Freer A. Stadelmann C. Nesvizhskii A.I. Schmidt M. Reiter L. Gomez-Varela D. New targeted approaches for the quantification of data-independent acquisition mass spectrometry.Proteomics. 2017; 17Crossref PubMed Scopus (22) Google Scholar). This has not yet been exploited in QCLMS because of current software restrictions regarding cross-linked peptides. In recent years, significant advances in software for both CLMS and QCLMS have propelled the cross-linking field forward, enabling a deeper understanding of dynamic protein systems and a wider range of workflows (50Yu C. Huang L. Cross-linking mass spectrometry: an emerging technology for interactomics and structural biology.Anal. Chem. 2018; 90: 144-165Crossref PubMed Scopus (171) Google Scholar). Here, we developed a DIA-QCLMS workflow that uses the Spectronaut software for the quantitation of observed unique residue pairs. We determined the accuracy and reproducibility of our DIA-QCLMS workflow at both MS1 as well as MS2 level, using a mix of seven proteins, each cross-linked using bis[sulfosuccinimidyl] suberate (BS3), and E. coli cell lysate as matrix. The seven-protein mix comprised human serum albumin (HSA), cytochrome C (bovine heart), ovotransferrin (Conalbumin, chicken egg white), myoglobin (equine heart), lysozyme C (chicken egg white), and catalase (bovine liver), all purchased individually from Sigma Aldrich (St. Louis, MO). Creatine kinase Type M (rabbit muscle) was purchased from Roche (Basel, Switzerland). The cross-linker BS3 was purchased from Thermo Scientific Pierce (Rockford, IL). Cross-linking reactions of the individual proteins were performed in parallel as previously described (35Müller F. Fischer L. Chen Z.A. Auchynnikava T. Rappsilber J. On the reproducibility of label-free quantitative cross-linking mass spectrometry.J. Am. Soc. Mass Spectrom. 2018; 29: 405-412Crossref PubMed Scopus (28) Google Scholar). In short, purified proteins were mixed separately with BS3 (1 μg/μl protein concentration), with a protein to cross-linker mass ratio of 1:4. After incubation on ice, the reaction was stopped using saturated ammonium bicarbonate. Cross-linked proteins were subjected to SDS-PAGE, visualized using Coomassie staining and monomer bands were excised for digestion. Cross-link protein gel bands were reduced, alkylated and digested using trypsin as described before (51Maiolica A. Cittaro D. Borsotti D. Sennels L. Ciferri C. Tarricone C. Musacchio A. Rappsilber J. Structural analysis of multiprotein complexes by cross-linking, mass spectrometry, and database searching.Mol. Cell. Proteomics. 2007; 6: 2200-2211Abstract Full Text Full Text PDF PubMed Scopus (181) Google Scholar). After digestion, peptides were extracted from gel bands using 80% v/v acetonitrile (ACN) and concentrated to a final ACN content of nominally 5% v/v using a Vacufuge Concentrator (Eppendorf, Germany). Tryptic peptides were enriched using strong cation exchange chromatography (SCX) as previously described (6Chen Z.A. Jawhari A. Fischer L. Buchen C. Tahir S. Kamenski T. Rasmussen M. Lariviere L. Bukowski-Wills J.-C. Nilges M. Cramer P. Rappsilber J. Architecture of the RNA polymerase II-TFIIF complex revealed by cross-linking and mass spectrometry.EMBO J. 2010; 29: 717-726Crossref PubMed Scopus (324) Google Scholar) but using SCX-StageTips (52Rappsilber J. Mann M. Ishihama Y. Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips.Nat. Protoc. 2007; 2: 1896-1906Crossref PubMed Scopus (2569) Google Scholar, 53Ishihama Y. Rappsilber J. Mann M. Modular stop and go extraction tips with stacked disks for parallel and multidimensional Peptide fractionation in proteomics.J. Proteome Res. 2006; 5: 988-994Crossref PubMed Scopus (224) Google Scholar) with minor modifications for activation of the Tip and gradient steps. The SCX-StageTips were activated using first methanol, following buffer 2 (0.5% AcH, 80% CAN), buffer 1 (0.5% AcH), high salt buffer (0.5% AcH, 20% CAN, 600 mm NH4Ac) and finally again buffer 1. Peptides were eluted in steps using: 50 mm NH4Ac (fraction 1), 100 mm NH4Ac (fraction 2), 200 mm MH4Ac (fraction 3), 300 mm NH4Ac (fraction 4), 500 mm NH4Ac (fraction 5), 600 mm NH4Ac (fraction 6). Peptides were then desalted using C18-StageTips (52Rappsilber J. Mann M. Ishihama Y. Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips.Nat. Protoc. 2007; 2: 1896-1906Crossref PubMed Scopus (2569) Google Scholar, 54Rappsilber J. Ishihama Y. Mann M. Stop and go extraction tips for matrix-assisted laser desorption/ionization, nanoelectrospray, and LC/MS sample pretreatment in proteomics.Anal. Chem. 2003; 75: 663-670Crossref PubMed Scopus (1795) Google Scholar) and eluted using 80% v/v ACN, 0.1% v/v TFA. Peptides were dried down and resuspended in 2% v/v ACN, 0.1% v/v formic acid (FA) to a final protein concentration of 0.75 μg/μl. LC-MS/MS analysis was performed using a tribrid Orbitrap mass spectrometer (Orbitrap Fusion™ Lumos, Thermo Fisher Scientific, CA) with a “high/high” (high-resolution MS1 and MS2) acquisition strategy. 1.5 μg peptides were injected for data-dependent acquisition (DDA) experiments. For data-independent acquisition (DIA), the stock solution (1.5 μg peptides) was diluted to reach 0.1×, 0.3×, 0.5×, 0.7×, 0.9×, and 1× (undiluted). 1.5 μg tryptic E. coli cell lysate was added as matrix to each sample of the dilution series to assess DIA in the context of analyzing a complex sample. iRT peptides (Biognosys, Switzerland) were added to each sample before MS acquisition. The peptide separation was carried out on an EASY-Spray column (50 cm × 75 μm ID, PepMap C18, 2 μm particles, 100 Å pore size, Thermo Fisher Scientific, Germany). Peptides were separated using a 150 min gradient and analyzed in DDA mode as described before (35Müller F. Fischer L. Chen Z.A. Auchynnikava T. Rappsilber J. On the reproducibility of label-free quantitative cross-linking mass spectrometry.J. Am. Soc. Mass Spectrom. 2018; 29: 405-412Crossref PubMed Scopus (28) Google Scholar). In short, precursor ions were detected in the Orbitrap at 120K resolution using m/z range 400–1600. Ions with charge states from 3+ to 7+ were selected for fragmentation. Selected ions were isolated and fragmented by high energy collision dissociation (HCD) and detected in Orbitrap at 30K resolution (55Kolbowski L. Mendes M.L. Rappsilber J. Optimizing the parameters governing the fragmentation of cross-linked peptides in a tribrid mass spectrometer.Anal. Chem. 2017; 89: 5311-5318Crossref PubMed Scopus (44) Google Scholar). In DIA mode, precursor ions were acquired using a MS1 master scan (m/z range: 400–1200, max. injection time: 60 ms, AGC target: 4 × 105, detector: Orbitrap, resolution: 60K), following 66 DIA scans for MS2 within a fragmentation rage of m/z 120–1200 using an isolation window width of m/z 12 and a max. injection time of 50 ms. Selected ions were isolated in the quadrupole, fragmented using HCD (normalized collision energy 30%) and detected in Orbitrap at 30K resolution. The raw mass spectrometric data files were processed into peak lists using MaxQuant (56Cox 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) (v. 1.5.0.0) as described previously (35Müller F. Fischer L. Chen Z.A. Auchynnikava T. Rappsilber J. On the reproducibility of label-free quantitative cross-linking mass spectrometry.J. Am. Soc. Mass Spectrom. 2018; 29: 405-412Crossref PubMed Scopus (28) Google Scholar). Xi (v. 1.6.723) (57Mendes M.L. Fischer L. Chen Z.A. Barbon M. O'Reilly F.J. Bohlke-Schneider M. Belsom A. Dau T. Combe C.W. Graham M. Eisele M.R. Baumeister W. Speck C. Rappsilber J. An integrated workflow for cross-linking mass spectrometry.bioRxiv. 2018; 355396Google Scholar) was used for database search. The database comprised the sequences of HSA (UniProt ID: P02768), cytochrome C (P62894), ovotransferrin (P02789), myoglobin (P68082), creatine kinase (P00563), lysozyme C (P00698), and catalase (P00432) and the reverse sequence of each of these proteins as decoys. Search parameters were: MS tolerance: 6 ppm, MS/MS tolerance: 20 ppm, enzyme: trypsin, missed cleavages: 4, cross-linker: BS3, fixed modification: carbamidomethylation of cysteine, variable modification: oxidation of methionine and modification by BS3 with the second NHS ester hydrolyzed or amidated, with BS3 reaction specificity at lysine, serine, threonine, tyrosine and N termini of proteins. In a cross-link analysis, the false discovery rate (FDR) can be calculated on different information levels: PSMs, peptide pairs, residue pairs (RPs) and protein pairs (58Fischer L. Rappsilber J. Quirks of error estimation in cross-linking mass spectrometry.anal. chem. 2017; 89: 3829-3833Crossref PubMed Scopus (85) Google Scholar). We here considered residue-pair FDR, which were estimated using xiFDR (v 1.0.21.45) with the equation: FDR = TD-DD/TT (58Fischer L. Rappsilber J. Quirks of error estimation in cross-linking mass spectrometry.anal. chem. 2017; 89: 3829-3833Crossref PubMed Scopus (85) Google Scholar) and filtering to only use cross-link PSMs within proteins. The max. protein ambiguity was set to 1. Other settings were left on default. Identification with 5% FDR at link level were accepted for quantitation. Quantitation was performed on MS1 and MS2 level using Spectronaut (version 11.0.15038.23.25164) (59Bruderer R. Bernhardt O.M. Gandhi T. Miladinović S.M. Cheng L.-Y. Messner S. Ehrenberger T. Zanotelli V. Butscheid Y. Escher C. Vitek O. Rinner O. Reiter L. Extending the limits of quantitative proteome profiling with data-independent acquisition and application to acetaminophen-treated three-dimensional liver microtissues.Mol. Cell. Proteomics. 2015; 14: 1400-1410Abstract Full Text Full Text PDF PubMed Scopus (521) Google Scholar, 60Bruderer R. Bernhardt O.M. Gandhi T. Xuan Y. Sondermann J. Schmidt M. Gomez-Varela D. Reiter L. Optimization of experimental parameters in data-independent mass spectrometry significantly increases depth and reproducibility of results.Mol. Cell. Proteomics. 2017; 16: 2296-2309Abstract Full Text Full Text PDF PubMed Scopus (188) Google Scholar). The spectral library of cross-linked peptides was introduced as a .csv file, following the standard format for custom libraries in Spectronaut (Manual for Spectronaut 11, available on Biognosis website). The .csv file was constructed from ou" @default.
• W2910656520 created "2019-01-25" @default.
• W2910656520 creator A5009958649 @default.
• W2910656520 creator A5013170226 @default.
• W2910656520 creator A5020905330 @default.
• W2910656520 creator A5023657229 @default.
• W2910656520 creator A5076844877 @default.
• W2910656520 date "2019-04-01" @default.
• W2910656520 modified "2023-10-16" @default.
• W2910656520 title "Data-independent Acquisition Improves Quantitative Cross-linking Mass Spectrometry" @default.
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