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QE-HF companion data for Construction of Human Proteoform Families from 21 Tesla FT-ICR Mass Spectrometry Top-Down Proteomic Data

ABSTRACT: Single injections of GelFREE fractions 1-6 of 2 biological replicates of MCF-7 cells

INSTRUMENT(S): Q Exactive HF

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Lloyd M. Smith

PROVIDER: MSV000086148 | MassIVE |

REPOSITORIES: MassIVE

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Construction of Human Proteoform Families from 21 Tesla FT-ICR Mass Spectrometry Top-Down Proteomic Data

Project description:MCF-7 cell lysate was fractionated using a 10% GELFrEE cartridge. Each fraction was analyzed by 21 T FT-ICR at the National High Magnetic Field Laboratory.

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Construction of Human Proteoform Families from 21 Tesla Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Top-Down Proteomic Data.

Project description:Identification of proteoforms, the different forms of a protein, is important to understand biological processes. A proteoform family is the set of different proteoforms from the same gene. We previously developed the software program Proteoform Suite, which constructs proteoform families and identifies proteoforms by intact-mass analysis. Here, we have applied this approach to top-down proteomic data acquired at the National High Magnetic Field Laboratory 21 tesla Fourier transform ion cyclotron resonance mass spectrometer (data available on the MassIVE platform with identifier MSV000085978). We explored the ability to construct proteoform families and identify proteoforms from the high mass accuracy data that this instrument provides for a complex cell lysate sample from the MCF-7 human breast cancer cell line. There were 2830 observed experimental proteforms, of which 932 were identified, 44 were ambiguous, and 1854 were unidentified. Of the 932 unique identified proteoforms, 766 were identified by top-down MS2 analysis at 1% false discovery rate (FDR) using TDPortal, and 166 were additional intact-mass identifications (∼4.7% calculated global FDR) made using Proteoform Suite. We recently published a proteoform level schema to represent ambiguity in proteoform identifications. We implemented this proteoform level classification in Proteoform Suite for intact-mass identifications, which enables users to determine the ambiguity levels and sources of ambiguity for each intact-mass proteoform identification.

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Expanding Proteoform Identifications in Top-Down Proteomic Analyses by Constructing Proteoform Families.

Project description:In top-down proteomics, intact proteins are analyzed by tandem mass spectrometry and proteoforms, which are defined forms of a protein with specific sequences of amino acids and localized post-translational modifications, are identified using precursor mass and fragmentation data. Many proteoforms that are detected in the precursor scan (MS1) are not selected for fragmentation by the instrument and therefore remain unidentified in typical top-down proteomic workflows. Our laboratory has developed the open source software program Proteoform Suite to analyze MS1-only intact proteoform data. Here, we have adapted it to provide identifications of proteoform masses in precursor MS1 spectra of top-down data, supplementing the top-down identifications obtained using the MS2 fragmentation data. Proteoform Suite performs mass calibration using high-scoring top-down identifications and identifies additional proteoforms using calibrated, accurate intact masses. Proteoform families, the set of proteoforms from a given gene, are constructed and visualized from proteoforms identified by both top-down and intact-mass analyses. Using this strategy, we constructed proteoform families and identified 1861 proteoforms in yeast lysate, yielding an approximately 40% increase over the original 1291 proteoform identifications observed using traditional top-down analysis alone.

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Constructing Human Proteoform Families Using Intact-Mass and Top-Down Proteomics with a Multi-Protease G-PTM-D Database

Project description:This data set contains the following: 1) 66 raw files for NeuCode-labeled human proteoforms from the Jurkat cell line analyzed via "intact-mass" (i.e., LC-MS, with no precursor fragmentation). Three biological replicates were performed (files from the different replicates are labeled with 022317, 031617, or 031817, respectively). For each replicate, proteoforms were separated offline using a 12% Tris-acetate Gelfree cartridge and 11 fractions were collected. Two technical replicate LC-MS injections of each fraction were performed, yielding a total of 66 raw files (3 biological replicates x 11 fractions x 2 injections). 2) 22 raw files for label-free human proteoforms from the Jurkat cell line analyzed via "top-down" (i.e., LC-MS/MS, with precursor fragmentation). One biological replicate was performed (labeled 032017). Proteoforms were separated offline using a 12% Tris-acetate Gelfree cartridge and 11 fractions were collected. Two technical replicate LC-MS/MS injections of each fraction were performed, yielding a total of 22 raw files (1 biological replicate x 11 fractions x 2 injections). 3) Multi-protease and trypsin-only pruned G-PTM-D databases used for proteoform identification. Note that the bottom-up data used to generate these databases can be found elsewhere on MassIVE (MSV000083304).

2019-05-13 | MSV000083768 | MassIVE

Expanding Proteoform Identifications in Top-Down Proteomic Analyses by Constructing Proteoform Families

Project description:Raw top-down LC-MS/MS files from 12% GELFREE separated fractions of yeast. Raw files for 2 technical replicates of each fraction, in total 24 raw files.

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Project description:Intact mass analyses (HPLC-ESI-MS) of GELFREE separated fractions of yeast. A total of 66 raw files, representing two replicate analyses.

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SPECTRUM - A MATLAB Toolbox for Proteoform Identification from Top-Down Proteomics Data.

Project description:Top-Down Proteomics (TDP) is an emerging proteomics protocol that involves identification, characterization, and quantitation of intact proteins using high-resolution mass spectrometry. TDP has an edge over other proteomics protocols in that it allows for: (i) accurate measurement of intact protein mass, (ii) high sequence coverage, and (iii) enhanced identification of post-translational modifications (PTMs). However, the complexity of TDP spectra poses a significant impediment to protein search and PTM characterization. Furthermore, limited software support is currently available in the form of search algorithms and pipelines. To address this need, we propose 'SPECTRUM', an open-architecture and open-source toolbox for TDP data analysis. Its salient features include: (i) MS2-based intact protein mass tuning, (ii) de novo peptide sequence tag analysis, (iii) propensity-driven PTM characterization, (iv) blind PTM search, (v) spectral comparison, (vi) identification of truncated proteins, (vii) multifactorial coefficient-weighted scoring, and (viii) intuitive graphical user interfaces to access the aforementioned functionalities and visualization of results. We have validated SPECTRUM using published datasets and benchmarked it against salient TDP tools. SPECTRUM provides significantly enhanced protein identification rates (91% to 177%) over its contemporaries. SPECTRUM has been implemented in MATLAB, and is freely available along with its source code and documentation at https://github.com/BIRL/SPECTRUM/.

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Coupling Capillary Zone Electrophoresis to a Q Exactive HF Mass Spectrometer for Top-down Proteomics: 580 Proteoform Identifications from Yeast.

Project description:We used reversed-phase liquid chromatography to separate the yeast proteome into 23 fractions. These fractions were then analyzed using capillary zone electrophoresis (CZE) coupled to a Q-Exactive HF mass spectrometer using an electrokinetically pumped sheath flow interface. The parameters of the mass spectrometer were first optimized for top-down proteomics using a mixture of seven model proteins; we observed that intact protein mode with a trapping pressure of 0.2 and normalized collision energy of 20% produced the highest intact protein signals and most protein identifications. Then, we applied the optimized parameters for analysis of the fractionated yeast proteome. From this, 580 proteoforms and 180 protein groups were identified via database searching of the MS/MS spectra. This number of proteoform identifications is two times larger than that of previous CZE-MS/MS studies. An additional 3,243 protein species were detected based on the parent ion spectra. Post-translational modifications including N-terminal acetylation, signal peptide removal, and oxidation were identified.

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Project description:Intact mass (66 files), top-down (18 files) and bottom-up (66 files) .raw files of GELFREE separated fractions of yeast.

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