TDFragMapper: a visualization tool for evaluating experimental parameters in top-down proteomics.
Ontology highlight
ABSTRACT: Motivation
We present a new software-tool allowing an easy visualization of fragment ions and thus a rapid evaluation of key experimental parameters on the sequence coverage obtained for the MS/MS analysis of intact proteins. Our tool can process data obtained from various deconvolution and fragment assignment software.Results
We demonstrate that TDFragMapper can rapidly highlight the experimental fragmentation parameters that are critical to the characterization of intact proteins of various size using top-down proteomics.Availability
TDFragMapper, a demonstration video and user tutorial are freely available for academic use at https://msbio.pasteur.fr/tdfragmapper; all data are thus available from the ProteomeXchange consortium (identifier PXD024643).Supplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Dhenin J
PROVIDER: S-EPMC8796372 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:New software-tool allowing an easy visualization of fragment ions and thus a rapid evaluation of key experimental parameters on the sequence coverage obtained for the MS/MS analysis of intact proteins. Our tool can deal with multiple fragmentation methods. We demonstrate that TDFragMapper can rapidly highlight the experimental fragmentation parameters that are critical to the characterization of intact proteins of various size using top-down proteomics.
2021-12-30 | PXD024643 | Pride
Project description: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.
| S-EPMC4739683 | biostudies-literature
Project description:Recent progress in top-down proteomics has driven the demand for chromatographic methods compatible with mass spectrometry (MS) that can separate intact proteins. Hydrophilic interaction liquid chromatography (HILIC) has recently shown good potential for the characterization of glycoforms of intact proteins. In the present study, we demonstrate that HILIC can separate a wide range of proteins exhibiting orthogonal selectivity with respect to reversed-phase LC (RPLC). However, the application of HILIC to the analysis of low abundance proteins (e.g., in proteomics analysis) is hampered by low volume loadability, hindering down-scaling of the method to column diameters below 2.1 mm. Moreover, HILIC-MS sensitivity is decreased due to ion suppression from the trifluoroacetic acid (TFA) often used as the ion-pair agent to improve the selectivity and efficiency in the analysis of glycoproteins. Here, we introduce a capillary-based HILIC-MS method that overcomes these problems. Our method uses RPLC trap-columns to load and inject the sample, circumventing issues of protein solubility and volume loadability in capillary columns (200 μm ID). The low flow rates and use of a dopant gas in the electrospray interface improve protein-ionization efficiencies and reduce suppression by TFA. Overall, this allows the separation and detection of small protein quantities (down to 5 ng injected on column) as indicated by the analysis of a mixture of model proteins. The potential of the new capillary HILIC-MS is demonstrated by the analysis of a complex cell lysate.
| S-EPMC5990932 | biostudies-literature
Project description:Applying high-throughput Top-Down MS to an entire proteome requires a yet-to-be-established model for data processing. Since Top-Down is becoming possible on a large scale, we report our latest software pipeline dedicated to capturing the full value of intact protein data in automated fashion. For intact mass detection, we combine algorithms for processing MS1 data from both isotopically resolved (FT) and charge-state resolved (ion trap) LC-MS data, which are then linked to their fragment ions for database searching using ProSight. Automated determination of human keratin and tubulin isoforms is one result. Optimized for the intricacies of whole proteins, new software modules visualize proteome-scale data based on the LC retention time and intensity of intact masses and enable selective detection of PTMs to automatically screen for acetylation, phosphorylation, and methylation. Software functionality was demonstrated using comparative LC-MS data from yeast strains in addition to human cells undergoing chemical stress. We further these advances as a key aspect of realizing Top-Down MS on a proteomic scale.
| S-EPMC3073374 | biostudies-literature
Project description:The revised legislation on medicinal cannabis has triggered a surge of research studies in this space. Yet, cannabis proteomics is lagging. In a previous study, we optimised the protein extraction of mature buds for bottom-up proteomics. In this follow-up study, we developed a top-down mass spectrometry (MS) proteomics strategy to identify intact denatured protein from cannabis apical buds. After testing different source-induced dissociation (SID), collision-induced dissociation (CID), higher-energy collisional dissociation (HCD), and electron transfer dissociation (ETD) parameters on infused known protein standards, we devised three LC-MS/MS methods for top-down sequencing of cannabis proteins. Different MS/MS modes produced distinct spectra, albeit greatly overlapping between SID, CID, and HCD. The number of fragments increased with the energy applied; however, this did not necessarily translate into greater sequence coverage. Some precursors were more amenable to fragmentation than others. Sequence coverage decreased as the mass of the protein increased. Combining all MS/MS data maximised amino acid (AA) sequence coverage, achieving 73% for myoglobin. In this experiment, most cannabis proteins were smaller than 30 kD. A total of 46 cannabis proteins were identified with 136 proteoforms bearing different post-translational modifications (PTMs), including the excision of N-terminal M, the N-terminal acetylation, methylation, and acetylation of K resides, and phosphorylation. Most identified proteins are involved in photosynthesis, translation, and ATP production. Only one protein belongs to the phytocannabinoid biosynthesis, olivetolic acid cyclase.
| S-EPMC6958505 | biostudies-literature
Project description: Not available
| S-EPMC6138622 | biostudies-literature
Project description:We report the identification of a photocleavable anionic surfactant, 4-hexylphenylazosulfonate (Azo), which can be rapidly degraded by ultraviolet irradiation, for top-down proteomics. Azo can effectively solubilize proteins with performance comparable to that of sodium dodecyl sulfate (SDS) and is compatible with mass spectrometry. Azo-aided top-down proteomics enables the solubilization of membrane proteins for comprehensive characterization of post-translational modifications. Moreover, Azo is simple to synthesize and can be used as a general SDS replacement in SDS-polyacrylamide gel electrophoresis.
| S-EPMC6532422 | biostudies-literature
Project description:Top-down proteomics, the analysis of intact proteins in their endogenous form, preserves valuable information about post-translation modifications, isoforms and proteolytic processing. The quality of top-down liquid chromatography-tandem MS (LC-MS/MS) data sets is rapidly increasing on account of advances in instrumentation and sample-processing protocols. However, top-down mass spectra are substantially more complex than conventional bottom-up data. New algorithms and software tools for confident proteoform identification and quantification are needed. Here we present Informed-Proteomics, an open-source software suite for top-down proteomics analysis that consists of an LC-MS feature-finding algorithm, a database search algorithm, and an interactive results viewer. We compare our tool with several other popular tools using human-in-mouse xenograft luminal and basal breast tumor samples that are known to have significant differences in protein abundance based on bottom-up analysis.
| S-EPMC5578875 | biostudies-literature
Project description:With the prospect of resolving whole protein molecules into their myriad proteoforms on a proteomic scale, the question of their quantitative analysis in discovery mode comes to the fore. Here, we demonstrate a robust pipeline for the identification and stringent scoring of abundance changes of whole protein forms <30 kDa in a complex system. The input is ~100-400 μg of total protein for each biological replicate, and the outputs are graphical displays depicting statistical confidence metrics for each proteoform (i.e., a volcano plot and representations of the technical and biological variation). A key part of the pipeline is the hierarchical linear model that is tailored to the original design of the study. Here, we apply this new pipeline to measure the proteoform-level effects of deleting a histone deacetylase (rpd3) in S. cerevisiae. Over 100 proteoform changes were detected above a 5% false positive threshold in WT vs the Δrpd3 mutant, including the validating observation of hyperacetylation of histone H4 and both H2B isoforms. Ultimately, this approach to label-free top down proteomics in discovery mode is a critical technical advance for testing the hypothesis that whole proteoforms can link more tightly to complex phenotypes in cell and disease biology than do peptides created in shotgun proteomics.
| S-EPMC4033644 | biostudies-literature
Project description:Proteomic investigations of Alzheimer's and Parkinson's disease have provided valuable insights into neurodegenerative disorders. Thus far, these investigations have largely been restricted to bottom-up approaches, hindering the degree to which one can characterize a protein's "intact" state. Top-down proteomics (TDP) overcomes this limitation; however, it is typically limited to observing only the most abundant proteoforms and of a relatively small size. Therefore, fractionation techniques are commonly used to reduce sample complexity. Here, we investigate gas-phase fractionation through high-field asymmetric waveform ion mobility spectrometry (FAIMS) within TDP. Utilizing a high complexity sample derived from Alzheimer's disease (AD) brain tissue, we describe how the addition of FAIMS to TDP can robustly improve the depth of proteome coverage. For example, implementation of FAIMS with external compensation voltage (CV) stepping at -50, -40, and -30 CV could more than double the mean number of non-redundant proteoforms, genes, and proteome sequence coverage compared to without FAIMS. We also found that FAIMS can influence the transmission of proteoforms and their charge envelopes based on their size. Importantly, FAIMS enabled the identification of intact amyloid beta (Aβ) proteoforms, including the aggregation-prone Aβ1-42 variant which is strongly linked to AD. Raw data and associated files have been deposited to the ProteomeXchange Consortium via the MassIVE data repository with data set identifier PXD023607.
| S-EPMC8672206 | biostudies-literature