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Trypsin and MALDI matrix pre-coated targets simplify sample preparation for mapping proteomic distributions within biological tissues by imaging mass spectrometry.
Zubair F, Laibinis PE, Swisher WG, Yang J, Spraggins JM, Norris JL, Caprioli RM
(2016) J Mass Spectrom 51: 1168-1179
MeSH Terms: Animals, Brain Chemistry, Molecular Imaging, Peptide Fragments, Peptide Mapping, Proteomics, Rats, Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization, Trypsin
Show Abstract · Added March 10, 2017
Prefabricated surfaces containing α-cyano-4-hydroxycinnamic acid and trypsin have been developed to facilitate enzymatic digestion of endogenous tissue proteins prior to matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS). Tissue sections are placed onto slides that were previously coated with α-cyano-4-hydroxycinnamic acid and trypsin. After incubation to promote enzymatic digestion, the tissue is analyzed by MALDI IMS to determine the spatial distribution of the tryptic fragments. The peptides detected in the MALDI IMS dataset were identified by Liquid chromatography-tandem mass spectrometry/mass spectrometry. Protein identification was further confirmed by correlating the localization of unique tryptic fragments originating from common parent proteins. Using this procedure, proteins with molecular weights as large as 300 kDa were identified and their distributions were imaged in sections of rat brain. In particular, large proteins such as myristoylated alanine-rich C-kinase substrate (29.8 kDa) and spectrin alpha chain, non-erythrocytic 1 (284 kDa) were detected that are not observed without trypsin. The pre-coated targets simplify workflow and increase sample throughput by decreasing the sample preparation time. Further, the approach allows imaging at higher spatial resolution compared with robotic spotters that apply one drop at a time. Copyright © 2016 John Wiley & Sons, Ltd.
Copyright © 2016 John Wiley & Sons, Ltd.
1 Communities
3 Members
0 Resources
9 MeSH Terms
Site-specific mapping and quantification of protein S-sulphenylation in cells.
Yang J, Gupta V, Carroll KS, Liebler DC
(2014) Nat Commun 5: 4776
MeSH Terms: Acetylation, Cell Line, Tumor, Cysteine, Epidermal Growth Factor, Epithelial Cells, Gene Expression, Humans, Hydrogen Peroxide, Hypoxia-Inducible Factor 1, alpha Subunit, Molecular Sequence Annotation, Oxidation-Reduction, Peptide Mapping, Phosphorylation, Protein Processing, Post-Translational, Sirtuins, Sulfenic Acids, Ubiquitination
Show Abstract · Added January 20, 2015
Cysteine S-sulphenylation provides redox regulation of protein functions, but the global cellular impact of this transient post-translational modification remains unexplored. We describe a chemoproteomic workflow to map and quantify over 1,000 S-sulphenylation sites on more than 700 proteins in intact cells. Quantitative analysis of human cells stimulated with hydrogen peroxide or epidermal growth factor measured hundreds of site selective redox changes. Different cysteines in the same proteins displayed dramatic differences in susceptibility to S-sulphenylation. Newly discovered S-sulphenylations provided mechanistic support for proposed cysteine redox reactions and suggested novel redox mechanisms, including S-sulphenyl-mediated redox regulation of the transcription factor HIF1A by SIRT6. S-sulphenylation is favored at solvent-exposed protein surfaces and is associated with sequence motifs that are distinct from those for other thiol modifications. S-sulphenylations affect regulators of phosphorylation, acetylation and ubiquitylation, which suggest regulatory crosstalk between redox control and signalling pathways.
0 Communities
1 Members
0 Resources
17 MeSH Terms
Integrating genomic, transcriptomic, and interactome data to improve Peptide and protein identification in shotgun proteomics.
Wang X, Zhang B
(2014) J Proteome Res 13: 2715-23
MeSH Terms: Animals, Gene Expression Profiling, Humans, Peptide Mapping, Protein Interaction Mapping, Proteome, Proteomics, Tandem Mass Spectrometry
Show Abstract · Added May 21, 2014
Mass spectrometry (MS)-based shotgun proteomics is an effective technology for global proteome profiling. The ultimate goal is to assign tandem MS spectra to peptides and subsequently infer proteins and their abundance. In addition to database searching and protein assembly algorithms, computational approaches have been developed to integrate genomic, transcriptomic, and interactome information to improve peptide and protein identification. Earlier efforts focus primarily on making databases more comprehensive using publicly available genomic and transcriptomic data. More recently, with the increasing affordability of the Next Generation Sequencing (NGS) technologies, personalized protein databases derived from sample-specific genomic and transcriptomic data have emerged as an attractive strategy. In addition, incorporating interactome data not only improves protein identification but also puts identified proteins into their functional context and thus facilitates data interpretation. In this paper, we survey the major integrative bioinformatics approaches that have been developed during the past decade and discuss their merits and demerits.
0 Communities
1 Members
0 Resources
8 MeSH Terms
IDPQuantify: combining precursor intensity with spectral counts for protein and peptide quantification.
Chen YY, Chambers MC, Li M, Ham AJ, Turner JL, Zhang B, Tabb DL
(2013) J Proteome Res 12: 4111-21
MeSH Terms: Fungal Proteins, Humans, Peptide Mapping, Principal Component Analysis, Proteome, Proteomics, Reference Standards, Sensitivity and Specificity, Software, Tandem Mass Spectrometry, Yeasts
Show Abstract · Added March 7, 2014
Differentiating and quantifying protein differences in complex samples produces significant challenges in sensitivity and specificity. Label-free quantification can draw from two different information sources: precursor intensities and spectral counts. Intensities are accurate for calculating protein relative abundance, but values are often missing due to peptides that are identified sporadically. Spectral counting can reliably reproduce difference lists, but differentiating peptides or quantifying all but the most concentrated protein changes is usually beyond its abilities. Here we developed new software, IDPQuantify, to align multiple replicates using principal component analysis, extract accurate precursor intensities from MS data, and combine intensities with spectral counts for significant gains in differentiation and quantification. We have applied IDPQuantify to three comparative proteomic data sets featuring gold standard protein differences spiked in complicated backgrounds. The software is able to associate peptides with peaks that are otherwise left unidentified to increase the efficiency of protein quantification, especially for low-abundance proteins. By combing intensities with spectral counts from IDPicker, it gains an average of 30% more true positive differences among top differential proteins. IDPQuantify quantifies protein relative abundance accurately in these test data sets to produce good correlations between known and measured concentrations.
0 Communities
3 Members
0 Resources
11 MeSH Terms
Comprehensive proteomics analysis reveals new substrates and regulators of the fission yeast clp1/cdc14 phosphatase.
Chen JS, Broadus MR, McLean JR, Feoktistova A, Ren L, Gould KL
(2013) Mol Cell Proteomics 12: 1074-86
MeSH Terms: Active Transport, Cell Nucleus, CDC2 Protein Kinase, Cell Cycle Proteins, Cell Nucleus, Karyopherins, Peptide Mapping, Phosphorylation, Protein Interaction Mapping, Protein Interaction Maps, Protein Processing, Post-Translational, Protein Tyrosine Phosphatases, Proteomics, Schizosaccharomyces, Schizosaccharomyces pombe Proteins
Show Abstract · Added March 5, 2014
The conserved family of Cdc14 phosphatases targets cyclin-dependent kinase substrates in yeast, mediating late mitotic signaling events. To discover substrates and regulators of the Schizosaccharomyces pombe Cdc14 phosphatase Clp1, TAP-tagged Clp1, and a substrate trapping mutant (Clp1-C286S) were purified from asynchronous and mitotic (prometaphase and anaphase) cells and binding partners were identified by 2D-LC-MS/MS. Over 100 Clp1-interacting proteins were consistently identified, over 70 of these were enriched in Clp1-C286S-TAP (potential substrates) and we and others detected Cdk1 phosphorylation sites in over half (44/73) of these potential substrates. According to GO annotations, Clp1-interacting proteins are involved in many essential cellular processes including mitosis, cytokinesis, ribosome biogenesis, transcription, and trafficking among others. We confirmed association and dephosphorylation of multiple candidate substrates, including a key scaffolding component of the septation initiation network called Cdc11, an essential kinase of the conserved morphogenesis-related NDR kinase network named Shk1, and multiple Mlu1-binding factor transcriptional regulators. In addition, we identified Sal3, a nuclear β-importin, as the sole karyopherin required for Clp1 nucleoplasmic shuttling, a key mode of Cdc14 phosphatase regulation. Finally, a handful of proteins were more abundant in wild type Clp1-TAP versus Clp1-C286S-TAP, suggesting that they may directly regulate Clp1 signaling or serve as scaffolding platforms to localize Clp1 activity.
0 Communities
1 Members
0 Resources
14 MeSH Terms
Pepitome: evaluating improved spectral library search for identification complementarity and quality assessment.
Dasari S, Chambers MC, Martinez MA, Carpenter KL, Ham AJ, Vega-Montoto LJ, Tabb DL
(2012) J Proteome Res 11: 1686-95
MeSH Terms: Algorithms, Blood Proteins, Cell Line, Databases, Protein, Humans, Models, Statistical, Neural Networks (Computer), Peptide Mapping, Proteome, Reference Standards, Search Engine, Sequence Analysis, Protein, Serum Albumin, Bovine, Software, Tandem Mass Spectrometry
Show Abstract · Added August 21, 2013
Spectral libraries have emerged as a viable alternative to protein sequence databases for peptide identification. These libraries contain previously detected peptide sequences and their corresponding tandem mass spectra (MS/MS). Search engines can then identify peptides by comparing experimental MS/MS scans to those in the library. Many of these algorithms employ the dot product score for measuring the quality of a spectrum-spectrum match (SSM). This scoring system does not offer a clear statistical interpretation and ignores fragment ion m/z discrepancies in the scoring. We developed a new spectral library search engine, Pepitome, which employs statistical systems for scoring SSMs. Pepitome outperformed the leading library search tool, SpectraST, when analyzing data sets acquired on three different mass spectrometry platforms. We characterized the reliability of spectral library searches by confirming shotgun proteomics identifications through RNA-Seq data. Applying spectral library and database searches on the same sample revealed their complementary nature. Pepitome identifications enabled the automation of quality analysis and quality control (QA/QC) for shotgun proteomics data acquisition pipelines.
0 Communities
2 Members
0 Resources
15 MeSH Terms
Protein identification using customized protein sequence databases derived from RNA-Seq data.
Wang X, Slebos RJ, Wang D, Halvey PJ, Tabb DL, Liebler DC, Zhang B
(2012) J Proteome Res 11: 1009-17
MeSH Terms: Amino Acid Sequence, Base Sequence, Cell Line, Tumor, Computational Biology, Databases, Protein, Gene Expression Profiling, Humans, Molecular Sequence Data, Peptide Mapping, Peptides, Proteins, RNA, Sequence Analysis, RNA, Transcriptome
Show Abstract · Added July 26, 2012
The standard shotgun proteomics data analysis strategy relies on searching MS/MS spectra against a context-independent protein sequence database derived from the complete genome sequence of an organism. Because transcriptome sequence analysis (RNA-Seq) promises an unbiased and comprehensive picture of the transcriptome, we reason that a sample-specific protein database derived from RNA-Seq data can better approximate the real protein pool in the sample and thus improve protein identification. In this study, we have developed a two-step strategy for building sample-specific protein databases from RNA-Seq data. First, the database size is reduced by eliminating unexpressed or lowly expressed genes according to transcript quantification. Second, high-quality nonsynonymous coding single nucleotide variations (SNVs) are identified based on RNA-Seq data, and corresponding protein variants are added to the database. Using RNA-Seq and shotgun proteomics data from two colorectal cancer cell lines SW480 and RKO, we demonstrated that customized protein sequence databases could significantly increase the sensitivity of peptide identification, reduce ambiguity in protein assembly, and enable the detection of known and novel peptide variants. Thus, sample-specific databases from RNA-Seq data can enable more sensitive and comprehensive protein discovery in shotgun proteomics studies.
1 Communities
4 Members
0 Resources
14 MeSH Terms
Proteomic consequences of a single gene mutation in a colorectal cancer model.
Halvey PJ, Zhang B, Coffey RJ, Liebler DC, Slebos RJ
(2012) J Proteome Res 11: 1184-95
MeSH Terms: Cell Line, Tumor, Cluster Analysis, Colorectal Neoplasms, Cytoplasm, Genes, APC, Humans, Models, Genetic, Mutation, Peptide Mapping, Proteome, Proteomics, Reproducibility of Results, Signal Transduction, Tandem Mass Spectrometry
Show Abstract · Added March 12, 2014
The proteomic effects of specific cancer-related mutations have not been well characterized. In colorectal cancer (CRC), a relatively small number of mutations in key signaling pathways appear to drive tumorigenesis. Mutations in adenomatous polyposis coli (APC), a negative regulator of Wnt signaling, occur in up to 60% of CRC tumors. Here we examine the proteomic consequences of a single gene mutation by using an isogenic CRC cell culture model in which wildtype APC expression has been ectopically restored. Using LC-MS/MS label free shotgun proteomics, over 5000 proteins were identified in SW480Null (mutant APC) and SW480APC (APC restored). We observed 155 significantly differentially expressed proteins between the two cell lines, with 26 proteins showing opposite expression trends relative to gene expression measurements. Protein changes corresponded to previously characterized features of the APCNull phenotype: loss of cell adhesion proteins, increase in cell cycle regulators, alteration in Wnt signaling related proteins, and redistribution of β-catenin. Increased expression of RNA processing and isoprenoid biosynthetic proteins occurred in SW480Null cells. Therefore, shotgun proteomics reveals proteomic differences associated with a single gene change, including many novel differences that fall outside known target pathways.
1 Communities
4 Members
0 Resources
14 MeSH Terms
Spatial mapping by imaging mass spectrometry offers advancements for rapid definition of human skin proteomic signatures.
Taverna D, Nanney LB, Pollins AC, Sindona G, Caprioli R
(2011) Exp Dermatol 20: 642-7
MeSH Terms: Adult, Aged, Dermis, Epidermis, Humans, Mass Spectrometry, Middle Aged, Peptide Mapping, Proteome, Proteomics, Skin, Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
Show Abstract · Added May 28, 2014
Investigations into the human skin proteome by classical analytical procedures have not addressed spatial molecular distributions in whole-skin biopsies. The aim of this study was to develop methods for the detection of protein signatures and their spatial disposition in human skin using advanced molecular imaging technology based on mass spectrometry technologies. This technology allows for the generation of protein images at specific molecular weight values without the use of antibody while maintaining tissue architecture. Two experimental approaches were employed: MALDI-MS profiling, where mass spectra were taken from discrete locations based on histology, and MALDI-IMS imaging, where complete molecular images were obtained at various MW values. In addition, proteins were identified by in situ tryptic digestion, sequence analysis of the fragment peptides and protein database searching. We have detected patterns of protein differences that exist between epidermis and dermis as well as subtle regional differences between the papillary and reticular dermis. Furthermore, we were able to detect proteins that are constitutive features of human skin as well as those associated with unique markers of individual variability.
© 2011 John Wiley & Sons A/S.
0 Communities
1 Members
0 Resources
12 MeSH Terms
Few residues within an extensive binding interface drive receptor interaction and determine the specificity of arrestin proteins.
Vishnivetskiy SA, Gimenez LE, Francis DJ, Hanson SM, Hubbell WL, Klug CS, Gurevich VV
(2011) J Biol Chem 286: 24288-99
MeSH Terms: Amino Acid Substitution, Animals, Arrestin, Binding Sites, Cattle, Humans, Mutation, Missense, Peptide Mapping, Protein Structure, Tertiary, Receptors, G-Protein-Coupled
Show Abstract · Added December 10, 2013
Arrestins bind active phosphorylated forms of G protein-coupled receptors, terminating G protein activation, orchestrating receptor trafficking, and redirecting signaling to alternative pathways. Visual arrestin-1 preferentially binds rhodopsin, whereas the two non-visual arrestins interact with hundreds of G protein-coupled receptor subtypes. Here we show that an extensive surface on the concave side of both arrestin-2 domains is involved in receptor binding. We also identified a small number of residues on the receptor binding surface of the N- and C-domains that largely determine the receptor specificity of arrestins. We show that alanine substitution of these residues blocks the binding of arrestin-1 to rhodopsin in vitro and of arrestin-2 and -3 to β2-adrenergic, M2 muscarinic cholinergic, and D2 dopamine receptors in intact cells, suggesting that these elements critically contribute to the energy of the interaction. Thus, in contrast to arrestin-1, where direct phosphate binding is crucial, the interaction of non-visual arrestins with their cognate receptors depends to a lesser extent on phosphate binding and more on the binding to non-phosphorylated receptor elements.
0 Communities
1 Members
0 Resources
10 MeSH Terms