MASH Suite Pro: A Comprehensive Software Tool for Top-Down Proteomics
2015; Elsevier BV; Volume: 15; Issue: 2 Linguagem: Inglês
10.1074/mcp.o115.054387
ISSN1535-9484
AutoresWenxuan Cai, Hüseyin Güner, Zachery R. Gregorich, Albert J. Chen, Şerife Ayaz‐Güner, Ying Peng, Santosh G. Valeja, Xiaowen Liu, Ying Ge,
Tópico(s)Metabolomics and Mass Spectrometry Studies
ResumoTop-down mass spectrometry (MS)-based proteomics is arguably a disruptive technology for the comprehensive analysis of all proteoforms arising from genetic variation, alternative splicing, and posttranslational modifications (PTMs). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for data analysis in bottom-up proteomics, the data analysis tools in top-down proteomics remain underdeveloped. Moreover, despite recent efforts to develop algorithms and tools for the deconvolution of top-down high-resolution mass spectra and the identification of proteins from complex mixtures, a multifunctional software platform, which allows for the identification, quantitation, and characterization of proteoforms with visual validation, is still lacking. Herein, we have developed MASH Suite Pro, a comprehensive software tool for top-down proteomics with multifaceted functionality. MASH Suite Pro is capable of processing high-resolution MS and tandem MS (MS/MS) data using two deconvolution algorithms to optimize protein identification results. In addition, MASH Suite Pro allows for the characterization of PTMs and sequence variations, as well as the relative quantitation of multiple proteoforms in different experimental conditions. The program also provides visualization components for validation and correction of the computational outputs. Furthermore, MASH Suite Pro facilitates data reporting and presentation via direct output of the graphics. Thus, MASH Suite Pro significantly simplifies and speeds up the interpretation of high-resolution top-down proteomics data by integrating tools for protein identification, quantitation, characterization, and visual validation into a customizable and user-friendly interface. We envision that MASH Suite Pro will play an integral role in advancing the burgeoning field of top-down proteomics. Top-down mass spectrometry (MS)-based proteomics is arguably a disruptive technology for the comprehensive analysis of all proteoforms arising from genetic variation, alternative splicing, and posttranslational modifications (PTMs). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for data analysis in bottom-up proteomics, the data analysis tools in top-down proteomics remain underdeveloped. Moreover, despite recent efforts to develop algorithms and tools for the deconvolution of top-down high-resolution mass spectra and the identification of proteins from complex mixtures, a multifunctional software platform, which allows for the identification, quantitation, and characterization of proteoforms with visual validation, is still lacking. Herein, we have developed MASH Suite Pro, a comprehensive software tool for top-down proteomics with multifaceted functionality. MASH Suite Pro is capable of processing high-resolution MS and tandem MS (MS/MS) data using two deconvolution algorithms to optimize protein identification results. In addition, MASH Suite Pro allows for the characterization of PTMs and sequence variations, as well as the relative quantitation of multiple proteoforms in different experimental conditions. The program also provides visualization components for validation and correction of the computational outputs. Furthermore, MASH Suite Pro facilitates data reporting and presentation via direct output of the graphics. Thus, MASH Suite Pro significantly simplifies and speeds up the interpretation of high-resolution top-down proteomics data by integrating tools for protein identification, quantitation, characterization, and visual validation into a customizable and user-friendly interface. We envision that MASH Suite Pro will play an integral role in advancing the burgeoning field of top-down proteomics. With well-developed algorithms and computational tools for mass spectrometry (MS) 1The abbreviations used are:MSmass spectrometryMS/MStandem mass spectrometryLC-MSliquid chromatography-mass spectrometryFT-ICRFourier transform ion cyclotron resonanceS/Nsignal-to-noise ratioPTMsposttranslational modificationsTHRASHthorough high-resolution analysis of spectra by hornTopPICTop-Down Mass Spectrometry Based Proteoform Identification and CharacterizationPrSMproteoform spectrum match. data analysis, peptide-based bottom-up proteomics has gained considerable popularity in the field of systems biology (1.Gehlenborg N. O'Donoghue S.I. Baliga N.S. Goesmann A. Hibbs M.A. Kitano H. Kohlbacher O. Neuweger H. Schneider R. Tenenbaum D. Gavin A.C. Visualization of omics data for systems biology.Nat. Methods. 2010; 7: S56-S68Crossref PubMed Scopus (461) Google Scholar, 2.Cox J. Mann M. 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The first pilot project of the consortium for top-down proteomics: A status report.Proteomics. 2014; 14: 1130-1140Crossref PubMed Scopus (77) Google Scholar). However, the complexity of top-down high-resolution mass spectra presents a significant challenge for data analysis. In contrast to the well-developed software packages available for processing data from bottom-up proteomics experiments, the data analysis tools in top-down proteomics remain underdeveloped. mass spectrometry tandem mass spectrometry liquid chromatography-mass spectrometry Fourier transform ion cyclotron resonance signal-to-noise ratio posttranslational modifications thorough high-resolution analysis of spectra by horn Top-Down Mass Spectrometry Based Proteoform Identification and Characterization proteoform spectrum match. The initial step in the analysis of top-down proteomics data is deconvolution of high-resolution mass and tandem mass spectra. Thorough high-resolution analysis of spectra by horn (THRASH), which was the first algorithm developed for the deconvolution of high-resolution mass spectra (25.Horn D.M. Zubarev R.A. McLafferty F.W. Automated reduction and interpretation of high resolution electrospray mass spectra of large molecules.J. Am. Soc. Mass Spectrom. 2000; 11: 320-332Crossref PubMed Scopus (479) Google Scholar), is still widely used. THRASH automatically detects and evaluates individual isotopomer envelopes by comparing the experimental isotopomer envelope with a theoretical envelope and reporting those that score higher than a user-defined threshold. Another commonly used algorithm, MS-Deconv, utilizes a combinatorial approach to address the difficulty of grouping MS peaks from overlapping isotopomer envelopes (26.Liu X. Inbar Y. Dorrestein P.C. Wynne C. Edwards N. Souda P. Whitelegge J.P. Bafna V. Pevzner P.A. Deconvolution and database search of complex tandem mass spectra of intact proteins: A combinatorial approach.Mol. Cell. Proteomics. 2010; 9: 2772-2782Abstract Full Text Full Text PDF PubMed Scopus (132) Google Scholar). Recently, UniDec, which employs a Bayesian approach to separate mass and charge dimensions (27.Marty M.T. Baldwin A.J. Marklund E.G. Hochberg G.K. Benesch J.L. Robinson C.V. Bayesian deconvolution of mass and ion mobility spectra: From binary interactions to polydisperse ensembles.Anal. Chem. 2015; 87: 4370-4376Crossref PubMed Scopus (404) Google Scholar), can also be applied to the deconvolution of high-resolution spectra. Although these algorithms assist in data processing, unfortunately, the deconvolution results often contain a considerable amount of misassigned peaks as a consequence of the complexity of the high-resolution MS and MS/MS data generated in top-down proteomics experiments. Errors such as these can undermine the accuracy of protein identification and PTM localization and, thus, necessitate the implementation of visual components that allow for the validation and manual correction of the computational outputs. Following spectral deconvolution, a typical top-down proteomics workflow incorporates identification, quantitation, and characterization of proteoforms; however, most of the recently developed data analysis tools for top-down proteomics, including ProSightPC (28.LeDuc R.D. Taylor G.K. Kim Y.B. Januszyk T.E. Bynum L.H. Sola J.V. Garavelli J.S. Kelleher N.L. ProSight PTM: an integrated environment for protein identification and characterization by top-down mass spectrometry.Nucleic Acids Res. 2004; 32: W340-W345Crossref PubMed Scopus (172) Google Scholar, 29.Zamdborg L. LeDuc R.D. Glowacz K.J. Kim Y.B. Viswanathan V. Spaulding I.T. Early B.P. Bluhm E.J. Babai S. Kelleher N.L. ProSight PTM 2.0: improved protein identification and characterization for top down mass spectrometry.Nucleic Acids Res. 2007; 35: W701-W706Crossref PubMed Scopus (194) Google Scholar), Mascot Top Down (also known as Big-Mascot) (30.Karabacak N.M. Li L. Tiwari A. Hayward L.J. Hong P. Easterling M.L. Agar J.N. Sensitive and specific identification of wild type and variant proteins from 8 to 669 kDa using top-down mass spectrometry.Mol. Cell. Proteomics. 2009; 8: 846-856Abstract Full Text Full Text PDF PubMed Scopus (75) Google Scholar), MS-TopDown (31.Frank A.M. Pesavento J.J. Mizzen C.A. Kelleher N.L. Pevzner P.A. Interpreting top-down mass spectra using spectral alignment.Anal. Chem. 2008; 80: 2499-2505Crossref PubMed Scopus (64) Google Scholar), and MS-Align+ (32.Liu X. Sirotkin Y. Shen Y. Anderson G. Tsai Y.S. Ting Y.S. Goodlett D.R. Smith R.D. Bafna V. Pevzner P.A. Protein identification using top-down.Mol. Cell. Proteomics. 2012; 11 (M111.008524)Abstract Full Text Full Text PDF Scopus (112) Google Scholar), focus almost exclusively on protein identification. ProSightPC was the first software tool specifically developed for top-down protein identification. This software utilizes "shotgun annotated" databases (33.Pesavento J.J. Kim Y.B. Taylor G.K. Kelleher N.L. Shotgun annotation of histone modifications: A new approach for streamlined characterization of proteins by top down mass spectrometry.J. Am. Chem. Soc. 2004; 126: 3386-3387Crossref PubMed Scopus (140) Google Scholar) that include all possible proteoforms containing user-defined modifications. Consequently, ProSightPC is not optimized for identifying PTMs that are not defined by the user(s). Additionally, the inclusion of all possible modified forms within the database dramatically increases the size of the database and, thus, limits the search speed (32.Liu X. Sirotkin Y. Shen Y. Anderson G. Tsai Y.S. Ting Y.S. Goodlett D.R. Smith R.D. Bafna V. Pevzner P.A. Protein identification using top-down.Mol. Cell. Proteomics. 2012; 11 (M111.008524)Abstract Full Text Full Text PDF Scopus (112) Google Scholar). Mascot Top Down (30.Karabacak N.M. Li L. Tiwari A. Hayward L.J. Hong P. Easterling M.L. Agar J.N. Sensitive and specific identification of wild type and variant proteins from 8 to 669 kDa using top-down mass spectrometry.Mol. Cell. Proteomics. 2009; 8: 846-856Abstract Full Text Full Text PDF PubMed Scopus (75) Google Scholar) is based on standard Mascot but enables database searching using a higher mass limit for the precursor ions (up to 110 kDa), which allows for the identification of intact proteins. Protein identification using Mascot Top Down is fundamentally similar to that used in bottom-up proteomics (34.Mazur M.T. Fyhr R. An algorithm for identifying multiply modified endogenous proteins using both full-scan and high-resolution tandem mass spectrometric data.Rapid Commun. Mass Spectrom. 2011; 25: 3617-3626Crossref PubMed Scopus (5) Google Scholar), and, therefore, it is somewhat limited in terms of identifying unexpected PTMs. MS-TopDown (31.Frank A.M. Pesavento J.J. Mizzen C.A. Kelleher N.L. Pevzner P.A. Interpreting top-down mass spectra using spectral alignment.Anal. Chem. 2008; 80: 2499-2505Crossref PubMed Scopus (64) Google Scholar) employs the spectral alignment algorithm (35.Pevzner P.A. Dancík V. Tang C.L. Mutation-tolerant protein identification by mass spectrometry.J. Comput. Biol. 2000; 7: 777-787Crossref PubMed Scopus (118) Google Scholar), which matches the top-down tandem mass spectra to proteins in the database without prior knowledge of the PTMs. Nevertheless, MS-TopDown lacks statistical evaluation of the search results and performs slowly when searching against large databases. MS-Align+ also utilizes spectral alignment for top-down protein identification (32.Liu X. Sirotkin Y. Shen Y. Anderson G. Tsai Y.S. Ting Y.S. Goodlett D.R. Smith R.D. Bafna V. Pevzner P.A. Protein identification using top-down.Mol. Cell. Proteomics. 2012; 11 (M111.008524)Abstract Full Text Full Text PDF Scopus (112) Google Scholar). It is capable of identifying unexpected PTMs and allows for efficient filtering of candidate proteins when the top-down spectra are searched against a large protein database. MS-Align+ also provides statistical evaluation for the selection of proteoform spectrum match (PrSM) with high confidence. More recently, Top-Down Mass Spectrometry Based Proteoform Identification and Characterization (TopPIC) was developed (http://proteomics.informatics.iupui.edu/software/toppic/index.html). TopPIC is an updated version of MS-Align+ with increased spectral alignment speed and reduced computing requirements. In addition, MSPathFinder, developed by Kim et al., also allows for the rapid identification of proteins from top-down tandem mass spectra (http://omics.pnl.gov/software/mspathfinder) using spectral alignment. Although software tools employing spectral alignment, such as MS-Align+ and MSPathFinder, are particularly useful for top-down protein identification, these programs operate using command line, making them difficult to use for those with limited knowledge of command syntax. Recently, new software tools have been developed for proteoform characterization (36.Guner H. Close P.L. Cai W. Zhang H. Peng Y. Gregorich Z.R. Ge Y. MASH Suite: A user-friendly and versatile software interface for high-resolution mass spectrometry data interpretation and visualization.J. Am. Soc. Mass Spectrom. 2014; 25: 464-470Crossref PubMed Scopus (59) Google Scholar, 37.Fellers R.T. Greer J.B. Early B.P. Yu X. LeDuc R.D. Kelleher N.L. Thomas P.M. ProSight Lite: Graphical software to analyze top-down mass spectrometry data.Proteomics. 2014; 15: 1238-1253Google Scholar). Our group previously developed MASH Suite, a user-friendly interface for the processing, visualization, and validation of high-resolution MS and MS/MS data (36.Guner H. Close P.L. Cai W. Zhang H. Peng Y. Gregorich Z.R. Ge Y. MASH Suite: A user-friendly and versatile software interface for high-resolution mass spectrometry data interpretation and visualization.J. Am. Soc. Mass Spectrom. 2014; 25: 464-470Crossref PubMed Scopus (59) Google Scholar). Another software tool, ProSight Lite, developed recently by the Kelleher group (37.Fellers R.T. Greer J.B. Early B.P. Yu X. LeDuc R.D. Kelleher N.L. Thomas P.M. ProSight Lite: Graphical software to analyze top-down mass spectrometry data.Proteomics. 2014; 15: 1238-1253Google Scholar), also allows characterization of protein PTMs. However, both of these software tools require prior knowledge of the protein sequence for the effective localization of PTMs. In addition, both software tools cannot process data from liquid chromatography (LC)-MS and LC-MS/MS experiments, which limits their usefulness in large-scale top-down proteomics. Thus, despite these recent efforts, a multifunctional software platform enabling identification, quantitation, and characterization of proteins from top-down spectra, as well as visual validation and data correction, is still lacking. Herein, we report the development of MASH Suite Pro, an integrated software platform, designed to incorporate tools for protein identification, quantitation, and characterization into a single comprehensive package for the analysis of top-down proteomics data. This program contains a user-friendly customizable interface similar to the previously developed MASH Suite (36.Guner H. Close P.L. Cai W. Zhang H. Peng Y. Gregorich Z.R. Ge Y. MASH Suite: A user-friendly and versatile software interface for high-resolution mass spectrometry data interpretation and visualization.J. Am. Soc. Mass Spectrom. 2014; 25: 464-470Crossref PubMed Scopus (59) Google Scholar) but also has a number of new capabilities, including the ability to handle complex proteomics datasets from LC-MS and LC-MS/MS experiments, as well as the ability to identify unknown proteins and PTMs using MS-Align+ (32.Liu X. Sirotkin Y. Shen Y. Anderson G. Tsai Y.S. Ting Y.S. Goodlett D.R. Smith R.D. Bafna V. Pevzner P.A. Protein identification using top-down.Mol. Cell. Proteomics. 2012; 11 (M111.008524)Abstract Full Text Full Text PDF Scopus (112) Google Scholar). Importantly, MASH Suite Pro also provides visualization components for the validation and correction of the computational outputs, which ensures accurate and reliable deconvolution of the spectra and localization of PTMs and sequence variations. The default algorithm for spectral deconvolution in MASH Suite Pro is a modified version of THRASH (25.Horn D.M. Zubarev R.A. McLafferty F.W. Automated reduction and interpretation of high resolution electrospray mass spectra of large molecules.J. Am. Soc. Mass Spectrom. 2000; 11: 320-332Crossref PubMed Scopus (479) Google Scholar) that we developed in-house based on the Decon2LS open source code (38.Jaitly N. Mayampurath A. Littlefield K. Adkins J.N. Anderson G.A. Smith R.D. Decon2LS: An open-source software package for automated processing and visualization of high resolution mass spectrometry data.BMC Bioinformatics. 2009; 10: 87Crossref PubMed Scopus (177) Google Scholar). MS-Align+ (32.Liu X. Sirotkin Y. Shen Y. Anderson G. Tsai Y.S. Ting Y.S. Goodlett D.R. Smith R.D. Bafna V. Pevzner P.A. Protein identification using top-down.Mol. Cell. Proteomics. 2012; 11 (M111.008524)Abstract Full Text Full Text PDF Scopus (112) Google Scholar) has been integrated into the program and is used for top-down protein identification. The program is written on the Microsoft .NET framework. The main scientific algorithms are written in C++, and the visual development was written with C#. The windows were developed using Qios Devsuite, and the graphs and spectrum charts were developed using Microsoft Chart Controls. The graphical user interface of MASH Suite Pro was designed using tabbed document interface. The software architecture pattern was based on model view controller, and the data tables were constructed based on Listview and Datagrid structures (36.Guner H. Close P.L. Cai W. Zhang H. Peng Y. Gregorich Z.R. Ge Y. MASH Suite: A user-friendly and versatile software interface for high-resolution mass spectrometry data interpretation and visualization.J. Am. Soc. Mass Spectrom. 2014; 25: 464-470Crossref PubMed Scopus (59) Google Scholar). Approximately 20 mg of swine cardiac left ventricular tissue was homogenized thoroughly in 200 μl of HEPES extraction buffer (25 mm HEPES, pH 7.5, 50 mm NaF, 0.25 mm Na3VO4, 0.25 mm PMSF, 2.5 mm EDTA) at 4 °C using a Teflon pestle (1.5 ml tube flat tip, Scienceware, Pequannock, NJ). The resulting homogenate was centrifuged at 17,000 relative centrifugal force for 15 min at 4 °C, and the supernatant was removed (19.Peng Y. Gregorich Z.R. Valeja S.G. Zhang H. Cai W. Chen Y.-C. Guner H. Chen A.J. Schwahn D.J. Hacker T.A. Liu X. Ge Y. Top-down proteomics reveals concerted reductions in myofilament and Z-disc protein phosphorylation after acute myocardial infarction.Mol. Cell. Proteomics. 2014; 13: 2752-2764Abstract Full Text Full Text PDF PubMed Scopus (77) Google Scholar). The pellet was subsequently homogenized in 100 μl TFA extraction solution (1% TFA, 1 mm Tris (2-carboxyethyl) Phosphine) to extract the myofilament proteins. The homogenate was centrifuged at 17,000 relative centrifugal force for 15 min at 4 °C, and the supernatant, which is enriched in myofilament proteins, was transferred to a new 1.5 ml microfuge tube and centrifuged for an additional 60 min at 17,000 relative centrifugal force and 4 °C. The resulting supernatant was subject to LC-MS analysis. LC separation of the myofilament proteins and low-resolution MS analysis were performed as previously described (19.Peng Y. Gregorich Z.R. Valeja S.G. Zhang H. Cai W. Chen Y.-C. Guner H. Chen A.J. Schwahn D.J. Hacker T.A. Liu X. Ge Y. Top-down proteomics reveals concerted reductions in myofilament and Z-disc protein phosphorylation after acute myocardial infarction.Mol. Cell. Proteomics. 2014; 13: 2752-2764Abstract Full Text Full Text PDF PubMed Scopus (77) Google Scholar) with minor modifications. Briefly, 3 μl of the myofilament extract (equivalent to 600 μg of tissue per injection) were injected, and the proteins in the mixture were eluted at a flow rate of 12.5 μl/min with a gradient going from 20% mobile phase B to 95% mobile phase B in 57 min (mobile phase A: 0.10% formic acid in water; mobile phase B: 0.10% formic acid in 1:1 acetonitrile:ethanol). The flow was split after LC separation with ∼10% of the eluting sample being ionized via electrospray ionization through a 50 μm inner diameter tip, and analyzed directly by a linear ion trap mass spectrometer (Thermo Scientific, Bremen, Germany). The remaining ∼90% of the sample was simultaneously collected as fractions on ice for subsequent high-resolution MS and MS/MS analyses. Fractions containing unknown proteins were analyzed using a 7 Tesla linear ion trap/FT-ICR mass spectrometer (LTQ/FT Ultra, Thermo Scientific) equipped with an automated chip-based nanoelectrospray ionization source (Triversa NanoMate, Advion Bioscience, Ithaca, NY) as described previously (19.Peng Y. Gregorich Z.R. Valeja S.G. Zhang H. Cai W. Chen Y.-C. Guner H. Chen A.J. Schwahn D.J. Hacker T.A. Liu X. Ge Y. Top-down proteomics reveals concerted reductions in myofilament and Z-disc protein phosphorylation after acute myocardial infarction.Mol. Cell. Proteomics. 2014; 13: 2752-2764Abstract Full Text Full Text PDF PubMed Scopus (77) Google Scholar). The sample was introduced into the mass spectrometer using a spray voltage of 1.3 to 1.5 kV versus the inlet of the mass spectrometer. The resolving power of the FT-ICR was set at 200,000 at 400 m/z. The automatic gain control for a full scan in the linear ion trap, FT-ICR cell, MSn FT-ICR cell, and electron capture dissociation were 3E4, 5E5, 5E5, and 8E5, respectively. For MS/MS experiments, the protein molecular ions of the individual charge states were first isolated and then fragmented using 1.5% to 4.5% electron energy for electron capture dissociation (corresponding to 0.6 to 3.5 eV) with a 70 ms duration without additional delay. The detailed experimental procedures were described previously (39.Valeja S.G. Xiu L. Gregorich Z.R. Guner H. Jin S. Ge Y. Three dimensional liquid chromatography coupling ion exchange chromatography/hydrophobic interaction chromatography/reverse phase chromatography for effective protein separation in top-down proteomics.Anal. Chem. 2015; 87: 5363-5371Crossref PubMed Scopus (52) Google Scholar). Human embryonic kidney (HEK) 293 cell lysate was subject to ion exchange chromatography followed by reverse phase chromatography coupled to a Q Exactive benchtop Orbitrap mass spectrometer (Thermo Scientific). LC-MS/MS data were acquired with eight microscans at a resolving power of 70,000 (at 200 m/z) with automatic gain control set to 5E5 ions. A 10 V offset in the source was used for all of the experiments. In the top two data-dependent MS/MS scans, the intact protein ions were injected into the collision cell for higher energy collision dissociation (25 V) with a 10 s dynamic exclusion window. The tandem mass spectra collected for unknown proteins were used to test MASH Suite Pro in terms of protein identification. Deconvolution was performed using enhanced-THRASH with a signal-to-noise ratio (S/N) threshold of 3 and a minimum fit of 60%. All deconvoluted masses were manually validated prior to identification with the targeted database from NCBI (Sscrofa10.2, containing 24,476 protein sequences) using MS-Align+. Alternatively, the raw MS/MS data were converted to mzXML files in centroid mode and deconvoluted using MS-Deconv (26.Liu X. Inbar Y. Dorrestein P.C. Wynne C. Edwards N. Souda P. Whitelegge J.P. Bafna V.
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