MSTopDiff: A Tool for the Visualization of Mass Shifts in Deconvoluted Top-Down Proteomics Data for the Database-Independent Detection of Protein Modifications

Kaulich, Philipp T.; Winkels, Konrad; Kaulich, Tobias B.; Treitz, Christian; Cassidy, Liam; Tholey, Andreas

doi:10.1021/acs.jproteome.1c00766

Cited by 9 publications

(10 citation statements)

References 33 publications

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“…For quality control, deconvoluted (FlashDeconv) spectra were inspected by MSTopDiff, which is a tool for the database-independent detection of modifications in top-down data (Figure S6). In both workflows, no indications for artificial modifications introduced during sample preparation (e.g., over- or underalkylation) or for SDS adducts (due to incomplete SDS removal) were found. This further demonstrates that SDS can be efficiently removed using the PEPPI-AnExSP protocol …”

Section: Resultsmentioning

confidence: 95%

Size-Based Proteome Fractionation through Polyacrylamide Gel Electrophoresis Combined with LC–FAIMS–MS for In-Depth Top-Down Proteomics

et al. 2022

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The combination of liquid chromatography (LC) and gas-phase separation by field-asymmetric ion mobility spectrometry (FAIMS) is a powerful proteoform separation system for top-down proteomics. Here, we present an in-depth top-down proteomics workflow, GeLC–FAIMS–MS, in which a molecular-weight-based proteome fractionation approach using SDS-polyacrylamide gel electrophoresis is performed prior to LC–FAIMS–MS. Since individual bands and their corresponding mass ranges require different compensating voltages (CVs), the MS parameters for each gel band and CV were optimized to increase the number and reliability of proteoform identifications further. We developed an easy-to-implement and inexpensive procedure combining the earlier established Passively Eluting Proteins from Polyacrylamide gels as Intact species (PEPPI) protocol with an optimized Anion-Exchange disk-assisted Sequential sample Preparation (AnExSP) method for the removal of stains and SDS. The protocol was compared with a methanol–chloroform–water (MCW)-based protein precipitation protocol. The results show that the PEPPI-AnExSP procedure is better suited for the identification of low-molecular-weight proteoforms, whereas the MCW-based protocol showed advantages for higher-molecular-weight proteoforms. Moreover, complementary results were observed with the two methods in terms of hydrophobicity and isoelectric points of the identified proteoforms. In total, 8500 proteoforms could be identified in a human proteome standard, showing the effectiveness of the gel-based sample fractionation approaches in combination with LC–FAIMS–MS.

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Section: Resultsmentioning

confidence: 95%

Size-Based Proteome Fractionation through Polyacrylamide Gel Electrophoresis Combined with LC–FAIMS–MS for In-Depth Top-Down Proteomics

et al. 2022

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“…The isoelectric point and the grand average of hydropathy (GRAVY) score of the proteoforms (without considering modifications) were calculated using Pyteomics . For quality control, all raw data were assessed using MSTopDiff (v1.0.0), which allowed for the database-independent detection of modifications in deconvoluted top-down data . Besides previously described artificial modifications (oxidation or formylation introduced during sample preparation) or biological modifications (phosphorylation, acetylation), no prominent unexpected mass shifts were observed (Figure S1).…”

Section: Methodsmentioning

confidence: 99%

Improved Identification of Proteoforms in Top-Down Proteomics Using FAIMS with Internal CV Stepping

et al. 2022

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In top-down (TD) proteomics, prefractionation prior to mass spectrometric (MS) analysis is a crucial step for both the high confidence identification of proteoforms and increased proteome coverage. In addition to liquid-phase separations, gas-phase fractionation strategies such as field asymmetric ion mobility spectrometry (FAIMS) have been shown to be highly beneficial in TD proteomics. However, so far, only external compensation voltage (CV) stepping has been demonstrated for TD proteomics, i.e., single CVs were applied for each run. Here, we investigated the use of internal CV stepping (multiple CVs per acquisition) for single-shot TD analysis, which has huge advantages in terms of measurement time and the amount of sample required. In addition, MS parameters were optimized for the individual CVs since different CVs target certain mass ranges. For example, small proteoforms identified mainly with more negative CVs can be identified with lower resolution and number of microscans than larger proteins identified primarily via less negative CVs. We investigated the optimal combination and number of CVs for different gradient lengths and validated the optimized settings with the low-molecular-weight proteome of CaCo-2 cells obtained using a range of different sample preparation techniques. Compared to measurements without FAIMS, both the number of identified protein groups (+60–94%) and proteoforms (+46–127%) and their confidence were significantly increased, while the measurement time remained identical. In total, we identified 684 protein groups and 2675 proteoforms from CaCo-2 cells in less than 24 h using the optimized multi-CV method.

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“…elegans sample was subjected to GELFrEE separation and subsequently analyzed via RP–LC–MS/MS using EThcD and CID. In our experiment, significant under- and/or overlabeling could not be detected, neither by manual inspection of the MS1 trace nor by systematic evaluation via MSTopDIFF (Figure S15). Our findings align with the experiments conducted by Liu et al who employed reductive dimethylation for quantification of intact proteins and reported high labeling efficiencies as well …”

Section: Resultsmentioning

confidence: 61%

Validation of Top-Down Proteomics Data by Bottom-Up-Based N-Terminomics Reveals Pitfalls in Top-Down-Based Terminomics Workflows

et al. 2022

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Bottom-up proteomics (BUP)-based N-terminomics techniques have become standard to identify protein N-termini. While these methods rely on the identification of N-terminal peptides only, top-down proteomics (TDP) comes with the promise to provide additional information about post-translational modifications and the respective C-termini. To evaluate the potential of TDP for terminomics, two established TDP workflows were employed for the proteome analysis of the nematode Caenorhabditis elegans. The N-termini of the identified proteoforms were validated using a BUP-based N-terminomics approach. The TDP workflows used here identified 1658 proteoforms, the N-termini of which were verified by BUP in 25% of entities only. Caveats in both the BUP- and TDP-based workflows were shown to contribute to this low overlap. In BUP, the use of trypsin prohibits the detection of arginine-rich or arginine-deficient N-termini, while in TDP, the formation of artificially generated termini was observed in particular in a workflow encompassing sample treatment with high acid concentrations. Furthermore, we demonstrate the applicability of reductive dimethylation in TDP to confirm biological N-termini. Overall, our study shows not only the potential but also current limitations of TDP for terminomics studies and also presents suggestions for future developments, for example, for data quality control, allowing improvement of the detection of protein termini by TDP.

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MSTopDiff: A Tool for the Visualization of Mass Shifts in Deconvoluted Top-Down Proteomics Data for the Database-Independent Detection of Protein Modifications

Cited by 9 publications

References 33 publications

Size-Based Proteome Fractionation through Polyacrylamide Gel Electrophoresis Combined with LC–FAIMS–MS for In-Depth Top-Down Proteomics

Size-Based Proteome Fractionation through Polyacrylamide Gel Electrophoresis Combined with LC–FAIMS–MS for In-Depth Top-Down Proteomics

Improved Identification of Proteoforms in Top-Down Proteomics Using FAIMS with Internal CV Stepping

Validation of Top-Down Proteomics Data by Bottom-Up-Based N-Terminomics Reveals Pitfalls in Top-Down-Based Terminomics Workflows

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