Fast Quantitative Analysis of timsTOF PASEF Data with MSFragger and IonQuant

Abstract

Ion mobility brings an additional dimension of separation to LC–MS, improving identification of peptides and proteins in complex mixtures. A recently introduced timsTOF mass spectrometer (Bruker) couples trapped ion mobility separation to TOF mass analysis. With the parallel accumulation serial fragmentation (PASEF) method, the timsTOF platform achieves promising results, yet analysis of the data generated on this platform represents a major bottleneck. Currently, MaxQuant and PEAKS are most used to analyze these data. However, because of the high complexity of timsTOF PASEF data, both require substantial time to perform even standard tryptic searches. Advanced searches (e.g. with many variable modifications, semi- or non-enzymatic searches, or open searches for post-translational modification discovery) are practically impossible. We have extended our fast peptide identification tool MSFragger to support timsTOF PASEF data, and developed a label-free quantification tool, IonQuant, for fast and accurate 4-D feature extraction and quantification. Using a HeLa data set published by Meier et al. (2018), we demonstrate that MSFragger identifies significantly (∼30%) more unique peptides than MaxQuant (1.6.10.43), and performs comparably or better than PEAKS X+ (∼10% more peptides). IonQuant outperforms both in terms of number of quantified proteins while maintaining good quantification precision and accuracy. Runtime tests show that MSFragger and IonQuant can fully process a typical two-hour PASEF run in under 70 min on a typical desktop (6 CPU cores, 32 GB RAM), significantly faster than other tools. Finally, through semi-enzymatic searching, we significantly increase the number of identified peptides. Within these semi-tryptic identifications, we report evidence of gas-phase fragmentation before MS/MS analysis. Ion mobility brings an additional dimension of separation to LC–MS, improving identification of peptides and proteins in complex mixtures. A recently introduced timsTOF mass spectrometer (Bruker) couples trapped ion mobility separation to TOF mass analysis. With the parallel accumulation serial fragmentation (PASEF) method, the timsTOF platform achieves promising results, yet analysis of the data generated on this platform represents a major bottleneck. Currently, MaxQuant and PEAKS are most used to analyze these data. However, because of the high complexity of timsTOF PASEF data, both require substantial time to perform even standard tryptic searches. Advanced searches (e.g. with many variable modifications, semi- or non-enzymatic searches, or open searches for post-translational modification discovery) are practically impossible. We have extended our fast peptide identification tool MSFragger to support timsTOF PASEF data, and developed a label-free quantification tool, IonQuant, for fast and accurate 4-D feature extraction and quantification. Using a HeLa data set published by Meier et al. (2018), we demonstrate that MSFragger identifies significantly (∼30%) more unique peptides than MaxQuant (1.6.10.43), and performs comparably or better than PEAKS X+ (∼10% more peptides). IonQuant outperforms both in terms of number of quantified proteins while maintaining good quantification precision and accuracy. Runtime tests show that MSFragger and IonQuant can fully process a typical two-hour PASEF run in under 70 min on a typical desktop (6 CPU cores, 32 GB RAM), significantly faster than other tools. Finally, through semi-enzymatic searching, we significantly increase the number of identified peptides. Within these semi-tryptic identifications, we report evidence of gas-phase fragmentation before MS/MS analysis. A major challenge to identification and quantification of proteins from tissue or cultured cells is the immense complexity of the peptide mixtures that result from enzymatic preparation of these samples for liquid chromatography-mass spectrometry (LC–MS) analysis. Ion mobility spectrometry brings an additional dimension of separation to LC–MS proteomics, significantly improving peptide identification. Following electrospray ionization, ion mobility differentiates gas-phase peptide ions by their size and charge before mass analysis. Ion mobility separation occurs on the millisecond timescale, improving selectivity without adding to analysis times. Recently, a commercially available instrument that couples trapped ion mobility spectrometry (TIMS) to time-of-flight (TOF) mass analysis (1Silveira J.A. Ridgeway M.E. Laukien F.H. Mann M. Park M.A. Parallel accumulation for 100% duty cycle trapped ion mobility-mass spectrometry.Int. J. Mass Spectrom. 2017; 413: 168-175Crossref Scopus (44) Google Scholar) has achieved promising depth of coverage, routinely identifying over 6000 proteins from individual 120-min LC gradients (2Meier F. Beck S. Grassl N. Lubeck M. Park M.A. Raether O. Mann M. Parallel accumulation–serial fragmentation (PASEF): multiplying sequencing speed and sensitivity by synchronized scans in a trapped ion mobility device.J. Proteome Res. 2015; 14: 5378-5387Crossref PubMed Scopus (176) Google Scholar, 3Meier F. Brunner A.D. Koch S. Koch H. Lubeck M. Krause M. Goedecke N. Decker J. Kosinski T. Park M.A. Bache N. Hoerning O. Cox J. Rather O. Mann M. Online Parallel Accumulation-Serial Fragmentation (PASEF) with a Novel Trapped Ion Mobility Mass Spectrometer.Mol. Cell. Proteomics. 2018; 17: 2534-2545Abstract Full Text Full Text PDF PubMed Scopus (339) Google Scholar). Owing to the dual TIMS design of this instrument, where the first region is used for storing ions and the second for ion mobility separation, peptides can be continually selected for sequencing with minimal reduction in duty cycle. This data acquisition method has been termed parallel accumulation-serial fragmentation (PASEF) (2Meier F. Beck S. Grassl N. Lubeck M. Park M.A. Raether O. Mann M. Parallel accumulation–serial fragmentation (PASEF): multiplying sequencing speed and sensitivity by synchronized scans in a trapped ion mobility device.J. Proteome Res. 2015; 14: 5378-5387Crossref PubMed Scopus (176) Google Scholar, 3Meier F. Brunner A.D. Koch S. Koch H. Lubeck M. Krause M. Goedecke N. Decker J. Kosinski T. Park M.A. Bache N. Hoerning O. Cox J. Rather O. Mann M. Online Parallel Accumulation-Serial Fragmentation (PASEF) with a Novel Trapped Ion Mobility Mass Spectrometer.Mol. Cell. Proteomics. 2018; 17: 2534-2545Abstract Full Text Full Text PDF PubMed Scopus (339) Google Scholar). For typical data-dependent acquisition (DDA) measurements, a survey scan is performed, and the N-highest abundance precursor ions are targeted for tandem mass spectrometry (MS/MS) analysis based on their m/z and mobility. Fast quadrupole switching times allow multiple peptide ions to be targeted for fragmentation during a single ion mobility scan. As a target precursor exits the TIMS region, the quadrupole switches to transmit the corresponding m/z determined by the survey scan. Synchronization of the TIMS device and quadrupole mass filter reduces chimeric spectra and enables removal of singly-charged contaminant ions. Additionally, because of the fast acquisition speed (50–200 ms for a full scan), low-abundance precursors can be repeatedly re-targeted to improve MS/MS spectrum quality (2Meier F. Beck S. Grassl N. Lubeck M. Park M.A. Raether O. Mann M. Parallel accumulation–serial fragmentation (PASEF): multiplying sequencing speed and sensitivity by synchronized scans in a trapped ion mobility device.J. Proteome Res. 2015; 14: 5378-5387Crossref PubMed Scopus (176) Google Scholar, 3Meier F. Brunner A.D. Koch S. Koch H. Lubeck M. Krause M. Goedecke N. Decker J. Kosinski T. Park M.A. Bache N. Hoerning O. Cox J. Rather O. Mann M. Online Parallel Accumulation-Serial Fragmentation (PASEF) with a Novel Trapped Ion Mobility Mass Spectrometer.Mol. Cell. Proteomics. 2018; 17: 2534-2545Abstract Full Text Full Text PDF PubMed Scopus (339) Google Scholar). A current major limitation of the PASEF proteomics method is long post-acquisition analysis time because of the high dimensionality of the data and large number of acquired MS/MS scans. MaxQuant (4Cox J. Mann M. MaxQuant enables high peptide identification rates, individualized ppb-range mass accuracies and proteome-wide protein quantification.Nat. Biotechnol. 2008; 26: 1367-1372Crossref PubMed Scopus (9150) Google Scholar, 5Prianichnikov N. Koch H. Koch S. Lubeck M. Heilig R. Brehmer S. Fischer R. Cox J. MaxQuant software for ion mobility enhanced shotgun proteomics.Mol. Cell. Proteomics. 2020; 19: 1058-1069Abstract Full Text Full Text PDF PubMed Scopus (56) Google Scholar) and PEAKS (6Zhang J. Xin L. Shan B. Chen W. Xie M. Yuen D. Zhang W. Zhang Z. Lajoie G.A. Ma B. PEAKS DB: de novo sequencing assisted database search for sensitive and accurate peptide identification.Mol. Cell. Proteomics. 2012; 11 (M111.010587)Abstract Full Text Full Text PDF Scopus (105) Google Scholar) are both capable of PASEF data require to perform a standard tryptic search a data from a two-hour MaxQuant PEAKS are for searches or open searches D. B. R. A database search identifies a large of spectra in shotgun proteomics Biotechnol. 2015; PubMed Scopus Google Scholar, D. and peptide identification in mass 2017; 14: PubMed Scopus Google are in post-translational We have recently introduced a ion method and in an database search tool MSFragger D. and peptide identification in mass 2017; 14: PubMed Scopus Google Scholar). speed of MSFragger for the analysis of large and complex data from timsTOF As from liquid to an represents challenge to min single two-hour LC–MS we extended MSFragger to the we demonstrate that MSFragger can perform peptide identification from timsTOF PASEF data in a of the time by other tools. A second challenge is to quantification of timsTOF PASEF data. of the ion mobility developed quantification to be extended to data. MaxQuant this is by a 4-D and multiple and and N. Koch H. Koch S. Lubeck M. Heilig R. Brehmer S. Fischer R. Cox J. MaxQuant software for ion mobility enhanced shotgun proteomics.Mol. Cell. Proteomics. 2020; 19: 1058-1069Abstract Full Text Full Text PDF PubMed Scopus (56) Google Scholar). MaxQuant TOF scan in feature represents a of the analysis PEAKS (6Zhang J. Xin L. Shan B. Chen W. Xie M. Yuen D. Zhang W. Zhang Z. Lajoie G.A. Ma B. PEAKS DB: de novo sequencing assisted database search for sensitive and accurate peptide identification.Mol. Cell. Proteomics. 2012; 11 (M111.010587)Abstract Full Text Full Text PDF Scopus (105) Google Scholar) has extended to support quantification of timsTOF PASEF data, with analysis times of this we IonQuant, a tool that and database search to perform fast ion quantification. Using data for in and ion mobility IonQuant min on a desktop IonQuant is with MSFragger D. and peptide identification in mass 2017; 14: PubMed Scopus Google Scholar) and the D. a for shotgun proteomics data 2020; Scholar). Using timsTOF PASEF HeLa data published by Meier et al. F. Brunner A.D. Koch S. Koch H. Lubeck M. Krause M. Goedecke N. Decker J. Kosinski T. Park M.A. Bache N. Hoerning O. Cox J. Rather O. Mann M. Online Parallel Accumulation-Serial Fragmentation (PASEF) with a Novel Trapped Ion Mobility Mass Spectrometer.Mol. Cell. Proteomics. 2018; 17: 2534-2545Abstract Full Text Full Text PDF PubMed Scopus (339) Google Scholar) and data published by et al. N. Koch H. Koch S. Lubeck M. Heilig R. Brehmer S. Fischer R. Cox J. MaxQuant software for ion mobility enhanced shotgun proteomics.Mol. Cell. Proteomics. 2020; 19: 1058-1069Abstract Full Text Full Text PDF PubMed Scopus (56) Google we show the of MSFragger and IonQuant to the analysis speed and and these to PEAKS and We demonstrate more semi-enzymatic and searches with MSFragger in these data, and large of peptides in the analysis. Additionally, our has and is fully with the for and targeted of the data. we a and accurate platform for timsTOF PASEF proteomics data. We used data from and ms TIMS accumulation published by Meier et al. F. Brunner A.D. Koch S. Koch H. Lubeck M. Krause M. Goedecke N. Decker J. Kosinski T. Park M.A. Bache N. Hoerning O. Cox J. Rather O. Mann M. Online Parallel Accumulation-Serial Fragmentation (PASEF) with a Novel Trapped Ion Mobility Mass Spectrometer.Mol. Cell. Proteomics. 2018; 17: 2534-2545Abstract Full Text Full Text PDF PubMed Scopus (339) Google Scholar) in the has Meier et al. F. Brunner A.D. Koch S. Koch H. Lubeck M. Krause M. Goedecke N. Decker J. Kosinski T. Park M.A. Bache N. Hoerning O. Cox J. Rather O. Mann M. Online Parallel Accumulation-Serial Fragmentation (PASEF) with a Novel Trapped Ion Mobility Mass Spectrometer.Mol. Cell. Proteomics. 2018; 17: 2534-2545Abstract Full Text Full Text PDF PubMed Scopus (339) Google Scholar) that the ms accumulation time the identification We used these with ms accumulation time tryptic semi-enzymatic open and quantification We used data generated from a of S. and published by et al. N. Koch H. Koch S. Lubeck M. Heilig R. Brehmer S. Fischer R. Cox J. MaxQuant software for ion mobility enhanced shotgun proteomics.Mol. Cell. Proteomics. 2020; 19: 1058-1069Abstract Full Text Full Text PDF PubMed Scopus (56) Google Scholar). are and that the of with to and We used these data to the quantification of For we the the search for in protein by mass PubMed Scopus Google Scholar, A survey of and for peptide and protein identification in shotgun Proteomics. PubMed Scopus Google Scholar). For we the quality with of and data from of HeLa acquired TIMS times on a timsTOF F. Brunner A.D. Koch S. Koch H. Lubeck M. Krause M. Goedecke N. Decker J. Kosinski T. Park M.A. Bache N. Hoerning O. Cox J. Rather O. Mann M. Online Parallel Accumulation-Serial Fragmentation (PASEF) with a Novel Trapped Ion Mobility Mass Spectrometer.Mol. Cell. Proteomics. 2018; 17: 2534-2545Abstract Full Text Full Text PDF PubMed Scopus (339) Google Scholar) from J.A. R. F. D. J.A. Z. T. N. M. L. S. R. L. H. proteomics data and Biotechnol. PubMed Scopus Google Scholar) For searches, a protein database of proteins from contaminant used generated and to the database for PEAKS and MaxQuant target with variable variable protein and peptide and mass and PEAKS and MaxQuant search set to used by For MSFragger searches, peptide identification with and with mass and and in used to filter and proteins to and protein analysis with IonQuant For PEAKS X+ searches, and and peptides to peptide by the on the is in PEAKS to filter the we protein from the to the the protein to MaxQuant and peptides to and the protein to protein are the from proteins and identified by data from the of N. Koch H. Koch S. Lubeck M. Heilig R. Brehmer S. Fischer R. Cox J. MaxQuant software for ion mobility enhanced shotgun proteomics.Mol. Cell. Proteomics. 2020; 19: 1058-1069Abstract Full Text Full Text PDF PubMed Scopus (56) Google Scholar) from J.A. R. F. D. J.A. Z. T. N. M. L. S. R. L. H. proteomics data and Biotechnol. PubMed Scopus Google Scholar) quality samples and from this and used to gas-phase fragmentation in more data. the quantification data are with We used MSFragger with and to perform a protein database the of H. S. and proteins from with We used IonQuant to perform analysis. For we MaxQuant with the from We these data MaxQuant and the protein database used by before to set to in to used in the HeLa analysis. Within precursor set to and set to with mass and and enzymatic set to precursor with peptides are a of preparation and is to these peptides from the of this Additionally, this precursor in more in number of to a in set to and the number to report the most and a of to search a spectrum used used in PEAKS and MaxQuant set to used by used by MSFragger for semi-tryptic searches to used in the searches with enzymatic peptide MaxQuant allow with semi-tryptic For of the identified semi-tryptic variable and from and and variable on peptide in the semi-enzymatic MSFragger search used to search HeLa from mass set from to and precursor and mass set to Mass and and the number of enzymatic set to set to number of to a in set to and the number to report the A of and the most used As are mass and time before and feature for quantification are to quantification tools. we to the for tool, have been to perform the in most IonQuant, mass set to time set to ion mobility set to and set to by ion and identification quantification with time with filter Mass and ion mobility set to and time used in set to min by the Fast with large set to where and number of by set to M. T. D. T. B. O. an for analysis of mass PubMed Scopus Google Scholar) used to protein from the ion by For MSFragger and ions and protein for peptide for to For and protein to with used to protein MSFragger and MaxQuant on a desktop with CPU and 32 GB of and PEAKS X+ used on an CPU with GB of the in in MS/MS acquired in PASEF can be by MSFragger the our a for in and Proteome Res. PubMed Scopus Google extended to with the or are to perform scan and the scans to MSFragger without additional MSFragger scans a for fast data in of the data. database with MSFragger are in the are R. to the of peptide by MS/MS and database PubMed Scopus Google Scholar) and R. A for identifying proteins by tandem mass PubMed Scopus Google Scholar) of the is used for and for the peptide and protein Finally, IonQuant is used to peptide ion for and quantification to the and generated by timsTOF PASEF are large and complex because of the fast TOF scan and additional ion mobility IonQuant, in and from the and and IonQuant first the ion mobility dimension with a IonQuant this 4-D to their ion and reduces and precursor ion and time from an identified MS/MS IonQuant first the corresponding to the precursor ion mobility with a the m/z the of the With these IonQuant to a of the data. Finally, the time and a by and in the time and m/z IonQuant the ion mobility dimension by to 4-D Finally, IonQuant the and of ion the m/z from a IonQuant to to 4-D corresponding to and the of these the quantified IonQuant IonQuant in and peptide and a quantified for used with IonQuant quantification to the and protein We that data have and a better we developed a in quantified IonQuant first a with the most ions. For of the other IonQuant of the ions with the the the to the of the protein from peptide ion multiple IonQuant first proteins with quantified ions than the IonQuant an that of D. B. M. H. for acquisition 2015; PubMed Scopus Google Scholar). is the of ions identified in of where and are with of and IonQuant the quantified and the from to an for analysis. We and sensitivity of database and quantification of HeLa data set MSFragger with IonQuant and with the from MaxQuant and MSFragger identified peptides and proteins from a standard tryptic more than the other of the peptide by and MSFragger from of HeLa is in MSFragger with IonQuant significantly analysis time than PEAKS or MaxQuant MSFragger used to perform searches on the with times under min more than times faster than PEAKS or MaxQuant We that a fast speed can be achieved to MSFragger of can be an additional in the software data a protein quantification be to is for quality or analysis H. B. D. D. M. of spectrometry PubMed Scopus Google of identification and quantification the proteins proteins of identified identified quantified proteins and protein of are number of quantified proteins to quantified in For searches, are for semi-enzymatic search that support For and are in Fast For IonQuant, and quantified ions are in protein quantification. is in protein from in a of identified identified quantified proteins and protein of are number of quantified proteins to quantified in For searches, are for semi-enzymatic search that support For and are in Fast For IonQuant, and quantified ions are in protein quantification. is in protein from We the of MSFragger with IonQuant and with MaxQuant and the tryptic search from the HeLa tool peptides and performs protein quantification we used to protein from ions quantified by these tools. the IonQuant with with of or than that from PEAKS and MaxQuant of for protein the is in proteins quantified in IonQuant with quantified the most proteins while the of with and by IonQuant with by PEAKS and MaxQuant with of and the tool, IonQuant, can perform peptide to protein and report quantification quantification in However, our analysis that or better than quantification for tools. For an additional filter of peptides protein for quantification in the protein to However, this with a in the number of proteins quantified in to IonQuant has a ion for quantification quantified ions the protein to with a corresponding reduction in the number of quantified proteins to the good precision of IonQuant, we used data from the of S. and published by et al. N. Koch H. Koch S. Lubeck M. Heilig R. Brehmer S. Fischer R. Cox J. MaxQuant software for ion mobility enhanced shotgun proteomics.Mol. Cell. Proteomics. 2020; 19: 1058-1069Abstract Full Text Full Text PDF PubMed Scopus (56) Google Scholar) to our accuracy. data set of samples and with of that the A and are and are of We first a search on these data MSFragger with and quantified IonQuant both ions set to and We used to the protein abundance a MaxQuant by the are used the proteins and identified by are proteins quantified by MaxQuant in both We the data MaxQuant with the protein database used by MSFragger and and of proteins quantified in both We used J. B. L. R. S. A software for label-free quantification.Nat. Biotechnol. PubMed Scopus Google Scholar) to the quantification and without additional S. proteins are in H. in and in to the of show the of the protein IonQuant and MaxQuant the IonQuant quantified more proteins with the of With a ion of IonQuant quantified significantly more proteins with with ion with an number of the ion is to protein the number of proteins from is to protein quantification with ion in than IonQuant method because of more peptide to protein Using MSFragger and IonQuant, we a open search on the HeLa acquired with ms accumulation and by mass corresponding to and and the most by a mass that to of with an from search the of many semi-tryptic peptides. the number of for of these mass are in MSFragger and IonQuant analysis times significantly for open the open we a number of semi-tryptic and with and by these we this of ion before MS/MS analysis. this we semi-enzymatic searches and on the HeLa data acquired with TIMS accumulation times F. Brunner A.D. Koch S. Koch H. Lubeck M. Krause M. Goedecke N. Decker J. Kosinski T. Park M.A. Bache N. Hoerning O. Cox J. Rather O. Mann M. Online Parallel Accumulation-Serial Fragmentation (PASEF) with a Novel Trapped Ion Mobility Mass Spectrometer.Mol. Cell. Proteomics. 2018; 17: 2534-2545Abstract Full Text Full Text PDF PubMed Scopus (339) Google during in the first TIMS region and mobility separation in the second the accumulation times in the and we that the number of with enzymatic with accumulation time accumulation time and semi-tryptic peptides is in to number of peptide ions that can be targeted for fragmentation with accumulation time F. Brunner A.D. Koch S. Koch H. Lubeck M. Krause M. Goedecke N. Decker J. Kosinski T. Park M.A. Bache N. Hoerning O. Cox J. Rather O. Mann M. Online Parallel Accumulation-Serial Fragmentation (PASEF) with a Novel Trapped Ion Mobility Mass Spectrometer.Mol. Cell. Proteomics. 2018; 17: 2534-2545Abstract Full Text Full Text PDF PubMed Scopus (339) Google ions are more to be accumulation times are This can be in where the of ion from semi-tryptic peptides the instrument has more time to these ions. We the abundance of tryptic peptide to corresponding semi-tryptic peptide and the accumulation time in this ms accumulation selected by the of the a semi-enzymatic MSFragger search in an increase in the number of identified peptides to or with and variable semi-tryptic and fully tryptic peptides number of identified proteins from the MSFragger search to or with and variable PEAKS and MSFragger identified more unique peptides with a semi-enzymatic search PEAKS identified more and MSFragger identified MaxQuant a This be to the that MaxQuant allow in semi-enzymatic searches. peptides with a single enzymatic identified by the semi-enzymatic the their tryptic We demonstrate that MSFragger with IonQuant more proteins in semi-tryptic tryptic search without is because of fast ion than for and open tryptic searches, of for semi-tryptic over MaxQuant and PEAKS is even more complex search semi-enzymatic searches We the of semi-tryptic peptides. We the times of semi-tryptic peptides to their corresponding peptide and the data set of accumulation of that these semi-tryptic peptides the identified semi-tryptic most to be to the with fragmentation of peptides to analysis of a database of peptide tandem mass PubMed Scopus Google Scholar, L. of the charge and of peptide PubMed Scopus Google Scholar). in the semi-enzymatic searches, we a of from We an increase in the of a with accumulation times be for a gas-phase fragmentation As L. of in of Mass Spectrom. PubMed Scopus Google Scholar, F. of and from in Proteome Res. PubMed Scopus Google Scholar, Fragmentation of peptides or Mass Spectrom. PubMed Scopus Google Scholar, R. of during of peptide PubMed Scopus Google from and is of peptides. the peptides identified with semi-tryptic we that or to the As the semi-tryptic peptides identified in these data set of peptide ion in the dual TIMS in the of the semi-tryptic peptides we high of semi-tryptic be to the timsTOF data used in this and these be more data we in instrument to peptide ion and fragmentation the of HeLa unique peptide on from a recently published timsTOF PASEF data set we that the of semi-tryptic peptides from to the accumulation time is For in that require of peptide S. S. H. Zhang W. T. T. S. J. T. Zhang N. A large most of the Biotechnol. 2020; PubMed Scopus Google Scholar, J. J. G.A. M. S. M. D. of by of Biotechnol. PubMed Scopus Google reduction in fragmentation with be the other the by the and ion can ion in many be to in the instrument ion the TIMS device to improve fragmentation of a semi-enzymatic search to the of peptides M.E. fragmentation and the of tryptic peptides in shotgun Proteome Res. PubMed Scopus Google Scholar) and the sensitivity of the of J. R. Parallel data acquisition of to the of PubMed Scopus Google Scholar) from to acquisition As the fragmentation to be the instrument to have the to perform these search from MSFragger with can be B. N. M. B. R. an open for and targeted proteomics 26: PubMed Scopus Google Scholar) to and peptide in can be used to perform targeted quantification from data acquisition data F. Brunner M. S. Lubeck M. Raether O. R. Parallel accumulation–serial fragmentation with acquisition proteomics with ion Scholar). with protein by in can be with protein and peptide ion (e.g. protein and peptide ion A for and the from MSFragger search in can be on the MSFragger the tool has been to be used with ion mobility data, and we this the MSFragger This feature from data of for quantification from data L. W. J. L. R. enables targeted analysis of acquisition Biotechnol. PubMed Scopus Google J. B. L. R. S. A software for label-free quantification.Nat. Biotechnol. PubMed Scopus Google or M. and in high 2020; 17: PubMed Scopus Google Scholar) support for data the time of on MSFragger tryptic search of the HeLa ms accumulation in a peptides. of the parallel accumulation and the selectivity of trapped ion the timsTOF PASEF method has achieved sensitive proteomics We have extended MSFragger to PASEF data for database searching, and developed IonQuant to peptides and proteins from these data. For standard tryptic searches, MSFragger than the analysis time by other that support PASEF data, and is to times faster for semi-enzymatic while the number of peptides the MSFragger is the search with the to open searches in by analysis times can be for post-translational modification or for of preparation or data we report data analysis times to than that a in the of timsTOF PASEF data. MSFragger and IonQuant and semi-enzymatic and open searches, for analysis A for IonQuant, is under and be in This can be through a or with the for are with and with proteomics data M. Zhang B. B. an proteomics data PubMed Scopus Google Scholar) for of peptide to MS/MS a of

Topics & Concepts