Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A quantitative proteomics design for systematic identification of protease cleavage events.

ABSTRACT: We present here a novel proteomics design for systematic identification of protease cleavage events by quantitative N-terminal proteomics, circumventing the need for time-consuming manual validation. We bypass the singleton detection problem of protease-generated neo-N-terminal peptides by introducing differential isotopic proteome labeling such that these substrate reporter peptides are readily distinguished from all other N-terminal peptides. Our approach was validated using the canonical human caspase-3 protease and further applied to mouse cathepsin D and E substrate processing in a mouse dendritic cell proteome, identifying the largest set of protein protease substrates ever reported and gaining novel insight into substrate specificity differences of these cathepsins.

SUBMITTER: Impens F

PROVIDER: S-EPMC2953924 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

A quantitative proteomics design for systematic identification of protease cleavage events.

Impens Francis F Colaert Niklaas N Helsens Kenny K Ghesquière Bart B Timmerman Evy E De Bock Pieter-Jan PJ Chain Benjamin M BM Vandekerckhove Joël J Gevaert Kris K

Molecular & cellular proteomics : MCP 20100713 10

We present here a novel proteomics design for systematic identification of protease cleavage events by quantitative N-terminal proteomics, circumventing the need for time-consuming manual validation. We bypass the singleton detection problem of protease-generated neo-N-terminal peptides by introducing differential isotopic proteome labeling such that these substrate reporter peptides are readily distinguished from all other N-terminal peptides. Our approach was validated using the canonical huma ...[more]

PMID: 20627866

Similar Datasets

A quantitative proteomics design for systematic identification of protease cleavage events.

Project description:Recombinant mouse cathepsin D was added to lysates of mouse dendritic cells. Neo-N-terminal peptides were isolated by N-terminal COFRADIC and their presence in ratios distributed distinct from other peptides was induced by mixing light and heavy labeled proteins according to a novel quantitative design.

2010-08-03 | PRD000281 | Pride

Identification of Protease Specificity by Combining Proteome-Derived Peptide Libraries and Quantitative Proteomics.

Project description:We present protease specificity profiling based on quantitative proteomics in combination with proteome-derived peptide libraries. Peptide libraries are generated by endoproteolytic digestion of proteomes without chemical modification of primary amines before exposure to a protease under investigation. After incubation with a test protease, treated and control libraries are differentially isotope-labeled using cost-effective reductive dimethylation. Upon analysis by liquid chromatography-tandem mass spectrometry, cleavage products of the test protease appear as semi-specific peptides that are enriched for the corresponding isotope label. We validate our workflow with two proteases with well-characterized specificity profiles: trypsin and caspase-3. We provide the first specificity profile of a protease encoded by a human endogenous retrovirus and for chlamydial protease-like activity factor (CPAF). For CPAF, we also highlight the structural basis of negative subsite cooperativity between subsites S1 and S2'. For A disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS) -4, -5, and -15, we show a canonical preference profile, including glutamate in P1 and glycine in P3'. In total, we report nearly 4000 cleavage sites for seven proteases. Our protocol is fast, avoids enrichment or synthesis steps, and enables probing for lysine selectivity as well as subsite cooperativity. Due to its simplicity, we anticipate usability by most proteomic laboratories.

| S-EPMC4937521 | biostudies-literature

Addressing the Protease Bias in Quantitative Proteomics.

Project description:Protein quantification strategies using multiple proteases have been shown to deliver poor interprotease accuracy in label-free mass spectrometry experiments. By utilizing six different proteases with different cleavage sites, this study explores the protease bias and its effect on accuracy and precision by using recombinant protein standards. We established 557 SRM assays, using a recombinant protein standard resource, toward 10 proteins in human plasma and determined their concentration with multiple proteases. The quantified peptides of these plasma proteins spanned 3 orders of magnitude (0.02-70 μM). In total, 60 peptides were used for absolute quantification and the majority of the peptides showed high robustness. The retained reproducibility was achieved by quantifying plasma proteins using spiked stable isotope standard recombinant proteins in a targeted proteomics workflow.

| S-EPMC9552229 | biostudies-literature

Cleavage entropy as quantitative measure of protease specificity.

Project description:A purely information theory-guided approach to quantitatively characterize protease specificity is established. We calculate an entropy value for each protease subpocket based on sequences of cleaved substrates extracted from the MEROPS database. We compare our results with known subpocket specificity profiles for individual proteases and protease groups (e.g. serine proteases, metallo proteases) and reflect them quantitatively. Summation of subpocket-wise cleavage entropy contributions yields a measure for overall protease substrate specificity. This total cleavage entropy allows ranking of different proteases with respect to their specificity, separating unspecific digestive enzymes showing high total cleavage entropy from specific proteases involved in signaling cascades. The development of a quantitative cleavage entropy score allows an unbiased comparison of subpocket-wise and overall protease specificity. Thus, it enables assessment of relative importance of physicochemical and structural descriptors in protease recognition. We present an exemplary application of cleavage entropy in tracing substrate specificity in protease evolution. This highlights the wide range of substrate promiscuity within homologue proteases and hence the heavy impact of a limited number of mutations on individual substrate specificity.

| S-EPMC3630115 | biostudies-literature

A statistics-based platform for quantitative N-terminome analysis and identification of protease cleavage products.

Project description:Terminal amine isotopic labeling of substrates (TAILS), our recently introduced platform for quantitative N-terminome analysis, enables wide dynamic range identification of original mature protein N-termini and protease cleavage products. Modifying TAILS by use of isobaric tag for relative and absolute quantification (iTRAQ)-like labels for quantification together with a robust statistical classifier derived from experimental protease cleavage data, we report reliable and statistically valid identification of proteolytic events in complex biological systems in MS2 mode. The statistical classifier is supported by a novel parameter evaluating ion intensity-dependent quantification confidences of single peptide quantifications, the quantification confidence factor (QCF). Furthermore, the isoform assignment score (IAS) is introduced, a new scoring system for the evaluation of single peptide-to-protein assignments based on high confidence protein identifications in the same sample prior to negative selection enrichment of N-terminal peptides. By these approaches, we identified and validated, in addition to known substrates, low abundance novel bioactive MMP-2 targets including the plasminogen receptor S100A10 (p11) and the proinflammatory cytokine proEMAP/p43 that were previously undescribed.

| S-EPMC2871423 | biostudies-literature

Cancer proteomics by quantitative shotgun proteomics.

Project description:A major scientific challenge at the present time for cancer research is the determination of the underlying biological basis for cancer development. It is further complicated by the heterogeneity of cancer's origin. Understanding the molecular basis of cancer requires studying the dynamic and spatial interactions among proteins in cells, signaling events among cancer cells, and interactions between the cancer cells and the tumor microenvironment. Recently, it has been proposed that large-scale protein expression analysis of cancer cell proteomes promises to be valuable for investigating mechanisms of cancer transformation. Advances in mass spectrometry technologies and bioinformatics tools provide a tremendous opportunity to qualitatively and quantitatively interrogate dynamic protein-protein interactions and differential regulation of cellular signaling pathways associated with tumor development. In this review, progress in shotgun proteomics technologies for examining the molecular basis of cancer development will be presented and discussed.

| S-EPMC2352161 | biostudies-other

Identification of protease exosite-interacting peptides that enhance substrate cleavage kinetics.

Project description:Many peptidases are thought to require non-active site interaction surfaces, or exosites, to recognize and cleave physiological substrates with high specificity and catalytic efficiency. However, the existence and function of protease exosites remain obscure owing to a lack of effective methods to identify and characterize exosite-interacting substrates. To address this need, we modified the cellular libraries of peptide substrates (CLiPS) methodology to enable the discovery of exosite-interacting peptide ligands. Invariant cleavage motifs recognized by the active sites of thrombin and caspase-7 were displayed on the outer surface of bacteria adjacent to a candidate exosite-interacting peptide. Exosite peptide libraries were then screened for ligands that accelerate cleavage of the active site recognition motif using two-color flow cytometry. Exosite CLiPS (eCLiPS) identified exosite-binding peptides for thrombin that were highly similar to a critical exosite interaction motif in the thrombin substrate, protease-activated receptor 1. Protease activity probes incorporating exosite-binding peptides were cleaved ten-fold faster than substrates without exosite ligands, increasing their sensitivity to thrombin activity in vitro. For comparison, screening with caspase-7 yielded peptides that modestly enhanced (two-fold) substrate cleavage rates. The eCLiPS method provides a new tool to profile the ligand specificity of protease exosites and to develop improved substrates.

| S-EPMC3858821 | biostudies-literature

Identification of beta-secretase (BACE1) substrates using quantitative proteomics.

Project description:Beta-site APP cleaving enzyme 1 (BACE1) is a transmembrane aspartyl protease with a lumenal active site that sheds the ectodomains of membrane proteins through juxtamembrane proteolysis. BACE1 has been studied principally for its role in Alzheimer's disease as the beta-secretase responsible for generating the amyloid-beta protein. Emerging evidence from mouse models has identified the importance of BACE1 in myelination and cognitive performance. However, the substrates that BACE1 processes to regulate these functions are unknown, and to date only a few beta-secretase substrates have been identified through candidate-based studies. Using an unbiased approach to substrate identification, we performed quantitative proteomic analysis of two human epithelial cell lines stably expressing BACE1 and identified 68 putative beta-secretase substrates, a number of which we validated in a cell culture system. The vast majority were of type I transmembrane topology, although one was type II and three were GPI-linked proteins. Intriguingly, a preponderance of these proteins are involved in contact-dependent intercellular communication or serve as receptors and have recognized roles in the nervous system and other organs. No consistent sequence motif predicting BACE1 cleavage was identified in substrates versus non-substrates. These findings expand our understanding of the proteins and cellular processes that BACE1 may regulate, and suggest possible mechanisms of toxicity arising from chronic BACE1 inhibition.

| S-EPMC2793532 | biostudies-literature

A bead-based cleavage method for large-scale identification of protease substrates.

Project description:Proteolysis is a major form of post translational modification which occurs when a protease cleaves peptide bonds in a target protein to modify its activity. Tracking protease substrates is indispensable for understanding its cellular functions. However, it is difficult to directly identify protease substrates because the end products of proteolysis, the cleaved protein fragments, must be identified among the pool of cellular proteins. Here we present a bead-based cleavage approach using immobilized proteome as the screening library to identify protease substrates. This method enables efficient separation of proteolyzed proteins from background protein mixture. Using caspase-3 as the model protease, we have identified 1159 high confident substrates, among which, strikingly, 43.9% of substrates undergo degradation during apoptosis. The huge number of substrates and positive support of in vivo evidence indicate that the BBC method is a powerful tool for protease substrates identification.

| S-EPMC4776233 | biostudies-literature

Prediction of missed cleavage sites in tryptic peptides aids protein identification in proteomics.

Project description:Protein identification via peptide mass fingerprinting (PMF) remains a key component of high-throughput proteomics experiments in post-genomic science. Candidate protein identifications are made using bioinformatic tools from peptide peak lists obtained via mass spectrometry (MS). These algorithms rely on several search parameters, including the number of potential uncut peptide bonds matching the primary specificity of the hydrolytic enzyme used in the experiment. Typically, up to one of these "missed cleavages" are considered by the bioinformatics search tools, usually after digestion of the in silico proteome by trypsin. Using two distinct, nonredundant datasets of peptides identified via PMF and tandem MS, a simple predictive method based on information theory is presented which is able to identify experimentally defined missed cleavages with up to 90% accuracy from amino acid sequence alone. Using this simple protocol, we are able to "mask" candidate protein databases so that confident missed cleavage sites need not be considered for in silico digestion. We show that that this leads to an improvement in database searching, with two different search engines, using the PMF dataset as a test set. In addition, the improved approach is also demonstrated on an independent PMF data set of known proteins that also has corresponding high-quality tandem MS data, validating the protein identifications. This approach has wider applicability for proteomics database searching, and the program for predicting missed cleavages and masking Fasta-formatted protein sequence databases has been made available via http:// ispider.smith.man.ac uk/MissedCleave.

| S-EPMC2664920 | 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