Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Increased sensitivity with automated validation of XL-MS cleavable peptide crosslinks.

ABSTRACT: MOTIVATION:Peptides crosslinked with cleavable chemical crosslinkers are identified with mass spectrometry by independent database search of spectra associated with the two linked peptides. A major challenge is to combine together the evidence of the two peptides into an overall assessment of the two-peptide crosslink. RESULTS:Here, we describe software that models crosslink specific information to automatically validate XL-MS cleavable peptide crosslinks. Using a dataset of crosslinked protein mixtures, we demonstrate that it computes accurate and highly discriminating probabilities, enabling as many as 75% more identifications than was previously possible using only search scores and a predictable false discovery rate. AVAILABILITY AND IMPLEMENTATION:XLinkProphet software is freely available on the web at http://brucelab.gs.washington.edu. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.

SUBMITTER: Keller A

PROVIDER: S-EPMC6394394 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Increased sensitivity with automated validation of XL-MS cleavable peptide crosslinks.

Keller Andrew A Chavez Juan D JD Bruce James E JE

Bioinformatics (Oxford, England) 20190301 5

<h4>Motivation</h4>Peptides crosslinked with cleavable chemical crosslinkers are identified with mass spectrometry by independent database search of spectra associated with the two linked peptides. A major challenge is to combine together the evidence of the two peptides into an overall assessment of the two-peptide crosslink.<h4>Results</h4>Here, we describe software that models crosslink specific information to automatically validate XL-MS cleavable peptide crosslinks. Using a dataset of cross ...[more]

PMID: 30137231

Similar Datasets

XLinkProphet ReACT XL-MS - Increased sensitivity with automated validation of XL-MS cleavable peptide crosslinks

Project description:Control Data Crosslink ReACT Results Searched with Comet

2019-07-12 | PXD009001 | Pride

Improved Peptide Backbone Fragmentation Is the Primary Advantage of MS-Cleavable Crosslinkers.

Project description:Proteome-wide crosslinking mass spectrometry studies have coincided with the advent of mass spectrometry (MS)-cleavable crosslinkers that can reveal the individual masses of the two crosslinked peptides. However, recently, such studies have also been published with noncleavable crosslinkers, suggesting that MS-cleavability is not essential. We therefore examined in detail the advantages and disadvantages of using the commonly used MS-cleavable crosslinker, disuccinimidyl sulfoxide (DSSO). Indeed, DSSO gave rise to signature peptide fragments with a distinct mass difference (doublet) for nearly all identified crosslinked peptides. Surprisingly, we could show that it was not these peptide masses that proved the main advantage of MS cleavability of the crosslinker, but improved peptide backbone fragmentation which reduces the ambiguity of peptide identifications. This also holds true for another commonly used MS-cleavable crosslinker, DSBU. We show furthermore that the more intricate MS3-based data acquisition approaches lack sensitivity and specificity, causing them to be outperformed by the simpler and faster stepped higher-energy collisional dissociation (HCD) method. This understanding will guide future developments and applications of proteome-wide crosslinking mass spectrometry.

| S-EPMC9178559 | biostudies-literature

MS Ana: Improving Sensitivity in Peptide Identification with Spectral Library Search.

Project description:Spectral library search can enable more sensitive peptide identification in tandem mass spectrometry experiments. However, its drawbacks are the limited availability of high-quality libraries and the added difficulty of creating decoy spectra for result validation. We describe MS Ana, a new spectral library search engine that enables high sensitivity peptide identification using either curated or predicted spectral libraries as well as robust false discovery control through its own decoy library generation algorithm. MS Ana identifies on average 36% more spectrum matches and 4% more proteins than database search in a benchmark test on single-shot human cell-line data. Further, we demonstrate the quality of the result validation with tests on synthetic peptide pools and show the importance of library selection through a comparison of library search performance with different configurations of publicly available human spectral libraries.

| S-EPMC9903325 | biostudies-literature

An experimentally generated peptide database increases the sensitivity in XL-MS of complex samples

Project description:The application of non-cleavable cross-linkers to complex samples in XL-MS workflows is limited by the n² problem, a quadratic expansion of the search space with increasing database size. Here, a peptide-focused approach is proposed, for which cross-linking peptide candidates are identified in a parallel experiment by using a thiol-cleavable cross-linker with equal reactivity. Samples are reduced and alkylated, thereby releasing cross-linked peptides with a variable modification on the initially cross-linked residue. Modified peptides are identified by database search and concatenated to a peptide database, which is finally used for the analysis of the sample cross-linked with a non-cleavable cross-linker. This way, the search space is dramatically reduced leading to a higher sensitivity, because there is less chance for random hits to false positive sequences. The approach was benchmarked on cross-linked purified protein complexes (20 S Proteasome, yeast PolII, and TFIIH), and in vivo cross-linked bacteria (Bacillus subtilis, Bacillus cereus) by comparing it to the conventional approach of searching against the protein sequences.

2020-03-26 | PXD016554 | Pride

Design and validation of a frugal, automated, solid-phase peptide synthesizer.

Project description:Solid phase peptide synthesis (SPPS) has enabled widespread use of synthetic peptides in applications ranging from pharmaceuticals to materials science. The demand for synthetic peptides has driven recent efforts to produce automated SPPS synthesizers which utilize fluid-handling components common to chemistry laboratories to drive costs down to several thousand dollars. Herein, we describe the design and validation of a more 'frugal' SPPS synthesizer that uses inexpensive, consumer-grade fluid-handling components to achieve a prototype price point between US$300 and $600. We demonstrated functionality by preparing and characterizing peptides with a variety of distinct properties including binding functionality, nanoscale self-assembly, and oxidation-induced fluorescence. This system yielded micromoles of peptide at a cost of approximately $1/residue, a cost which may be further reduced by optimization and bulk purchasing.

| S-EPMC7437905 | biostudies-literature

Development and Validation of a Novel LC-MS/MS Assay for C-Peptide in Human Serum.

Project description:IntroductionC-peptide is used as a marker of endogenous insulin secretion in the assessment of residual β-cell function in diabetes and in the diagnostic workup of hypoglycemia. Previously developed LC-MS/MS methods to quantify serum concentrations of C-peptide have monitored intact peptide, which ionizes poorly. As a result, methods have leveraged immunoaffinity enrichment or two-dimensional chromatography. In this study, we aimed to use proteolysis during sample preparation to enhance the sensitivity of traditional LC-MS/MS.MethodsDue to the absence of arginine and lysine residues in C-peptide, we utilized Glu-C as the proteolytic enzyme in the method. After protein precipitation using acetonitrile and solid phase extraction with mixed anion exchange, lower molecular weight polypeptides were reduced, alkylated, and proteolyzed. The two amino-terminal peptide fragments, EAEDLQVGQVE and LGGGPGAGSLQPLALE, were monitored using multiple reaction monitoring in positive ion mode (Acquity ULPC-Xevo TQ-S, Waters). The former peptide was used for quantification and the latter for quality assurance.ResultsGlu-C was determined to be a reliable proteolytic enzyme with monotonic digestion kinetics. The assay was linear between 0.1 and 15 ng/mL and had a lower limit of quantification of 0.06 ng/mL. Total imprecision was 7.7 %CV and long-term imprecision at 0.16 ng/mL was 10.0%. Spike-recovery experiments demonstrated a mean recovery of 98.2 % (± 9.1 %) and the method compared favorably with a commercially available immunoassay and a reference measurement procedure.ConclusionProtein precipitation with solid phase extraction and proteolysis with Glu-C is a robust sample preparation method for quantification of C-peptide in human serum by LC-MS/MS.

| S-EPMC8553002 | biostudies-literature

Multidimensional Separation Using HILIC and SCX Pre-fractionation for RP LC-MS/MS Platform with Automated Exclusion List-based MS Data Acquisition with Increased Protein Quantification.

Project description:Liquid chromatography-mass spectrometry (LC-MS) based proteomics is one of the most widely used analytical platforms for global protein discovery and quantification. One of the challenges is the difficulty of identifying low abundance biomarker proteins from limited biological samples. Extensive fractionation could expand proteomics dynamic range, however, at the cost of high sample and time consumption. Extensive fractionation would increase the sample need and the labeling cost. Also quantitative proteomics depending on high resolution MS have the limitation of spectral acquisition speed. Those practical problems hinder the in-depth quantitative proteomics analysis such as tandem mass tag (TMT) experiments. We found the joint use of hydrophilic interaction liquid chromatography (HILIC) and strong cation exchange Chromatography (SCX) prefractionation at medium level could improve MS/MS efficiency, increase proteome coverage, shorten analysis time and save valuable samples. In addition, we scripted a program, Exclusion List Convertor (ELC), which automates and streamlines data acquisition workflow using the precursor ion exclusion (PIE) method. PIE reduces redundancy of high abundance MS/MS analyses by running replicates of the sample. The precursor ions detected in the initial run(s) are excluded for MS/MS in the subsequent run. We compared PIE methods with standard data dependent acquisition (DDA) methods running replicates without PIE for their effectiveness in quantifying TMT-tagged peptides and proteins in mouse tears. We quantified a total of 845 proteins and 1401 peptides using the PIE workflow, while the DDA method only resulted in 347 proteins and 731 peptides. This represents a 144% increase of protein identifications as a result of PIE analysis.

| S-EPMC4720167 | biostudies-literature

Identification of MS-Cleavable and Noncleavable Chemically Cross-Linked Peptides with MetaMorpheus.

Project description:Protein chemical cross-linking combined with mass spectrometry has become an important technique for the analysis of protein structure and protein-protein interactions. A variety of cross-linkers are well developed, but reliable, rapid, and user-friendly tools for large-scale analysis of cross-linked proteins are still in need. Here we report MetaMorpheusXL, a new search module within the MetaMorpheus software suite that identifies both MS-cleavable and noncleavable cross-linked peptides in MS data. MetaMorpheusXL identifies MS-cleavable cross-linked peptides with an ion-indexing algorithm, which enables an efficient large database search. The identification does not require the presence of signature fragment ions, an advantage compared with similar programs such as XlinkX. One complication associated with the need for signature ions from cleavable cross-linkers such as DSSO (disuccinimidyl sulfoxide) is the requirement for multiple fragmentation types and energy combinations, which is not necessary for MetaMorpheusXL. The ability to perform proteome-wide analysis is another advantage of MetaMorpheusXL compared with programs such as MeroX and DXMSMS. MetaMorpheusXL is also faster than other currently available MS-cleavable cross-link search software programs. It is imbedded in MetaMorpheus, an open-source and freely available software suite that provides a reliable, fast, user-friendly graphical user interface that is readily accessible to researchers.

| S-EPMC6501566 | biostudies-literature

RawVegetable 2.0: Refining XL-MS Data Acquisition through Enhanced Quality Control.

Project description:We present RawVegetable 2.0, a software tailored for assessing mass spectrometry data quality and fine-tuned for cross-linking mass spectrometry (XL-MS) applications. Building upon the capabilities of its predecessor, RawVegetable 2.0 introduces four main modules, each providing distinct and new functionalities: 1) Pair Finder, which identifies ion doublets characteristic of cleavable cross-linking experiments; 2) Diagnostic Peak Finder, which locates potential reporter ions associated with a specific cross-linker; 3) Precursor Signal Ratio, which computes the ratio between precursor intensity and the total signal in an MS/MS scan; and 4) Xrea, which evaluates spectral quality by analyzing the heterogeneity of peak intensities within a spectrum. These modules collectively streamline the process of optimizing mass spectrometry data acquisition for both Proteomics and XL-MS experiments. RawVegetable 2.0, along with a comprehensive tutorial is freely accessible for academic use at: http://patternlabforproteomics.org/rawvegetable2.

| S-EPMC11301677 | biostudies-literature

Increased power for the analysis of label-free LC-MS/MS proteomics data by combining spectral counts and peptide peak attributes.

Project description:Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics provides a wealth of information about proteins present in biological samples. In bottom-up LC-MS/MS-based proteomics, proteins are enzymatically digested into peptides prior to query by LC-MS/MS. Thus, the information directly available from the LC-MS/MS data is at the peptide level. If a protein-level analysis is desired, the peptide-level information must be rolled up into protein-level information. We propose a principal component analysis-based statistical method, ProPCA, for efficiently estimating relative protein abundance from bottom-up label-free LC-MS/MS data that incorporates both spectral count information and LC-MS peptide ion peak attributes, such as peak area, volume, or height. ProPCA may be used effectively with a variety of quantification platforms and is easily implemented. We show that ProPCA outperformed existing quantitative methods for peptide-protein roll-up, including spectral counting methods and other methods for combining LC-MS peptide peak attributes. The performance of ProPCA was validated using a data set derived from the LC-MS/MS analysis of a mixture of protein standards (the UPS2 proteomic dynamic range standard introduced by The Association of Biomolecular Resource Facilities Proteomics Standards Research Group in 2006). Finally, we applied ProPCA to a comparative LC-MS/MS analysis of digested total cell lysates prepared for LC-MS/MS analysis by alternative lysis methods and show that ProPCA identified more differentially abundant proteins than competing methods.

| S-EPMC3101957 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data