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User's Research and Papers

Here's a repository of some papers we found to be interesting, submitted by our users.

2010-03-05	Accurate MALDI-TOF/TOF Sequencing	PEAKS
Jaehong Lim	Su Seong Lee, Jaehong Lim, Sylvia Tan, Junhoe Cha, Shi Yun Yeo, Heather D. Agnew, and James R. Heath. Institute of Bioengineering and Nanotechnology. Accurate Maldi-TOF-TOF Sequencing of One-Bead-One Compound peptide Libraries with Application to the identification of Multiligand protein Affiinity agents using in Siti click Chemistry Screening. Analytical Chemistry, Vol. 82, No. 2, January 15, 2010. Pg: 672–679. [download 3490.286 Kb] Combinatorial one-bead-one-compound (OBOC) peptide libraries are widely used for affinity screening, and the sequencing of peptides from hit beads is a key step in the process. For rapid sequencing, CNBr cleavage of the peptides from the beads, followed by de novo sequencing by MALDI-TOF/TOF, is explored. We report on a semiautomated sequencing algorithm and validate it through comparison against Edman degradation sequencing. The initial 44% sequencing success rate of the standard de novo sequencing software was improved to nearly 100%. The sequencing algorithm incorporates existing knowledge of amino acid chemistry and a new strategy for differentiating isobaric amino acids. We tested the algorithm by using MALDI-TOF/TOF to identify a peptide biligand affinity agent against the protein bovine carbonic anhydrase II, starting from comprehensive onebead-one-compound peptide libraries comprised of nonnatural and artificial amino acid components and using the strategy of in situ click/OBOC library screening.
2009-10-07	Identification of the Amniotic Fluid Isulin-Like Growth...	PEAKS
Monica Galliano	Lorenzo Dolcini1, Alberto Sala1, Monica Campagnoli1, Sara Labo` 1, Maurizia Valli1, Livia Visai1,2, Lorenzo Minchiotti1, Hugo L. Monaco3 and Monica Galliano1. 1 Department of Biochemistry ‘A. Castellani’, University of Pavia, Italy. 2 Center for Tissue Engineering (C. I. T), University of Pavia, Italy. 3 Biocrystallography Laboratory, Department of Biotechnology, University of Verona, Italy. Identification of the Amniotic Fluid Isulin-Like Growth. The FEBS Journal. doi:10.1111/j.1742-4658.2009.07318.x. 19 August 2009. [download 559.34 Kb] Insulin-like growth factor binding protein-1 (IGFBP-1) is the major secreted protein of human decidual cells during gestation and, as a modulator of insulin-like growth factors or by independent mechanisms, regulates embryonic implantation and growth. The protein is phosphorylated and this post-translational modification is regulated in pregnancy and represents an important determinant of its biological activity. We have isolated, from human normal amniotic fluid collected in the weeks 16–18, the intact nonphosphorylated IGFBP-1 and five electrophoretically distinct phosphoisoforms and have determined their in vivo phosphorylation state. The unmodified protein was the most abundant component and mono-, bi-, triand tetraphosphorylated forms were present in decreasing amounts. The phosphorylation sites of IGFBP-1 were identified by liquid chromatography–tandem mass spectrometry analysis of the peptides generated with trypsin, chymotrypsin and Staphylococcus aureus V8 protease. Five serines were found to be phosphorylated and, of these, four are localized in the central, weakly conserved, region, at positions 95, 98, 101 and 119, whereas one, Ser169, is in the C-terminal domain. The post-translational modification predominantly involves the hydrophilic stretch of amino acids representing a potential PEST sequence (proline, glutamic acid, serine, threonine) and our results show that the phosphorylation state influences the propensity of IGFBP-1 to proteolysis.
2009-10-05	Nanoscale Characterization of Spider Venom Peptides...	PEAKS
Pierre Escoubas	Claire Dauly (1) Pierre Escoubas (2), Graham M. Nicholson (3), Glenn F. King (4), Martin Hornshaw (5). (1) Thermo Fisher Scientific, 16 Avenue du Quebec, 91963 Courtaboeuf cedex, France, (2) University of of Nice Sophia Antipolis, Institute of Molecular and Cellular Pharmacology, Valbonne, France, (3) Department of Medical & Molecular Biosciences University of Technology Sydney, Sydney, Australia, (4) Institute for Molecular Biosciences, University of Queensland, Brisbane, Australia, (5) Thermo Fisher Scientific, Boundary Way, Hemel Hempstead, UK. Nanoscale characterization of spider venom peptides by high-resolution LC-MS/MS analysis. IMSC 2009 Poster. [download 211.946 Kb] Nanoscale characterization of spider venom peptides by high-resolution LC-MS/MS analysis. Animal venoms are natural libraries of biologically active peptides. They encompass a wide variety of structures and pharmacological activities and represent an enormous resource of novel molecules to be used as insecticide, therapeutic and drug models. However, the obstacle of sample size is daunting as many venomous species are of a size too small for classical bioassay-guided fractionation and biochemical characterization. High-resolution mass spectrometry can be used as an alternative technology for peptide sequence determination and sequence tag generation to permit the use of cDNA libraries. Venom profiling can be used for species identification and to indicate the presence of potentially unknown toxins. Here we demonstrate that de novo sequencing at the nanoscale level is applicable to venomics research.
2009-06-18	A New Strategy to Accelerate Peptide Discovery	PEAKS
Weifeng Cao	Weifeng Cao, Mingming Ma, Qiang Fu, Lingjun Li. University of Wisconsin, Madison. HyPep: A New Strategy to Accelerate Peptide Discovery with A Combination of De Novo Sequencing and Homology Database Search. ASMS 2009 Poster. [download 1420.192 Kb] PEAKS was used for automatic de novo sequencing. An in-house neuropeptide database containing 5825 entries was built for homology database searching. The sequence motif of a given peptide family was used for homology searching and the best-match database sequence can be assigned to the corresponding query sequence. A PO extract from Cancer borealis was used to evaluate this hybrid strategy. 17 possible peptides were screened from a total of 82 precursor ions and then 4 peptides were identified within minutes, while it typically requires a full-day work with manual sequencing alone. This hybrid method is efficient, accurate and more sensitive than BLAST.
2009-02-18	Proteomic analysis of maternal serum in down syndrome	PEAKS
Srinivasa Nagalla	Nagalla SR, Canick JA, Jacob T, Schneider KA, Reddy AP, Thomas A, Dasari S, Lu X, Lapidus JA, Lambert-Messerlian GM, Gravett MG, Roberts CT Jr, Luthy D, Malone FD, D'Alton ME. Proteomic analysis of maternal serum in down syndrome: identification of novel protein biomarkers. Journal of Proteome Research. 2007 Apr;6(4):1245-57. Epub 2007 Mar 21. [Link to Abstract] Down syndrome (DS) is the most prevalent chromosomal disorder, accounting for significant morbidity and mortality. Definitive diagnosis requires invasive amniocentesis, and current maternal serum-based testing requires a false-positive rate of about 5% to detect 85% of affected pregnancies. We have performed a comprehensive proteomic analysis to identify potential serum biomarkers to detect DS. First- and second-trimester maternal serum samples of DS and gestational age-matched controls were analyzed using multiple, complementary proteomic approaches, including fluorescence 2-dimensional gel electrophoresis (2D-DIGE), 2-dimensional liquid chromatography-chromatofocusing (2D-CF), multidimensional protein identification technology (MudPIT; LC/LC-MS/MS), and MALDI-TOF-MS peptide profiling. In total, 28 and 26 proteins were differentially present in first- and second-trimester samples, respectively. Of these, 19 were specific for the first trimester and 16 for the second trimester, and 10 were differentially present in both trimesters. Analysis of MALDI-TOF-MS peptide profiles with patternrecognition software also discriminated between DS and controls in both trimesters, with an average recognition capability approaching 96%. A majority of the biomarkers identified are serum glycoproteins that may play a role in cellular differentiation and growth of fetus. Further characterization and quantification of these markers in a larger cohort of subjects may provide the basis for new tests for improved DS screening.
2008-08-06	Isolation and Characterization of Carnocyclin A	PEAKS
Randy Whittal	Leah A. Martin-Visscher, Marco J. van Belkum, Sylvie Garneau-Tsodikova, Randy M. Whittal, Jing Zheng, Lynn M. McMullen, and John C. Vederas. Isolation and Characterization of Carnocyclin A, a Novel Circular Bacteriocin Produced by Carnobacterium maltaromaticum UAL307, Applied and Environmental Microbiology, Aug. 2008, p. 4756–4763. [download 795.016 Kb] Carnobacterium maltaromaticum UAL307, isolated from fresh pork, exhibits potent activity against a number of gram-positive organisms, including numerous Listeria species. Three bacteriocins were isolated from culture supernatant, and using matrix-assisted laser desorption ionization–time of flight mass spectrometry and Edman sequencing, two of these bacteriocins were identified as piscicolin 126 and carnobacteriocin BM1, both of which have previously been described. The remaining bacteriocin, with a molecular mass of 5,862 Da, could not be sequenced by traditional methods, suggesting that the peptide was either cyclic or N-terminally blocked. This bacteriocin showed remarkable stability over a wide temperature and pH range and was unaffected by a variety of proteases. After digestion with trypsin and -chymotrypsin, the peptide was de novo sequenced by tandem mass spectrometry and a linear sequence deduced, consisting of 60 amino acids. Based on this sequence, the molecular mass was predicted to be 5,880 Da, 18 units higher than the observed molecular mass, which suggested that the peptide has a cyclic structure. Identification of the genetic sequence revealed that this peptide is circular, formed by a covalent linkage between the N and C termini following cleavage of a 4-residue peptide leader sequence. The results of structural studies suggest that the peptide is highly structured in aqueous conditions. This bacteriocin, named carnocyclin A, is the first reported example of a circular bacteriocin produced by Carnobacterium spp.
2008-04-04	Analysis of iTRAQ data using Mascot and PEAKS Quantification	PEAKS
Carla Lacerda	Carla M.R. Lacerda, Lei Xin, Iain Rogers and Kenneth F. Reardon. Analysis of iTRAQ Data Using Mascot and PEAKS Quantification Algorithms. Briefings in Functional Genomics and Proteomics Advance Access published April 4, 2008. [download 207.511 Kb] The field of proteomics has been developing rapidly toward quantification of proteins. Despite the variety of experimental techniques available for peptide and protein labelling, there are few commercially available analytical tools with the ability to interpret data from any mass spectrometer. In this study, we compare two software packages, Mascot and PAEKS, for the analysis of iTRAQ data from ESI-Q/TOF mass spectrometry. In the case of a six-protein mixture combined in a known proportion, the output of the PEAKS algorithm deviated from the correct result by 14% on average, while the error of the Mascot quantification was nearly 200%.When the software were used to analyse iTRAQ data from a complex protein sample, the quantification results agreed within 20% for only 26% of the quantified proteins, showing significant differences in the two quantification algorithms.This comparison and analysis revealed major intricacies in peptide and protein quantification that must be taken into consideration for software development.
2007-11-12	De novo protein sequence analysis of Macaca mulatta	PEAKS
Nilesh	N. Tannu and S. Hemby, De novo protein sequence analysis of Macaca mulatta, (BMC Genomics 2007; 8, 270). [Link to Abstract] The current study validates a robust method to confidently characterize the proteins from an incomplete sequence database of Macaca mulatta, using the PEAKS de novo sequencing software, facilitating the use of this animal model in various neuroproteomics studies.
2007-09-24	tubulin formation in individuals with HRD	PEAKS
Ravi	G. Tian, M. Huang, R. Parvari, G. A. Diaz, and N. J. Cowan, Cryptic out-of-frame translational initiation of TBCE rescues tubulin formation in compound heterozygous HRD , PNAS September 5, 2006 vol. 103 no. 36 13491–13496 [download 986.88 Kb] The research explains how individuals with HRD can survive and point to a limiting capacity to fold tubulin heterodimers de novo as a contributing factor to disease pathogenesis. "...were analyzed by nano liquid chromatography tandem MS (MSMS) on a Micromass a(Manchester, U.K.) Q-TOF 2. De novo sequencing of selected peptides was done by using PEAKS software ..."
2007-07-20	Evaluating one-hit-wonders using de novo sequence tag search	PEAKS
Kostas	K. Thalassinos, G. Efstathiou, S. E. Slade, J. H. Scrivens An Objective Organism-Based Evaluation of Tandem Mass Spectrometric Data Obtained from Proteomic Studies, ASMS 2007 poster presentation. [download 2790.866 Kb] An oligomer-segmented organism specific database approach has been developed which, when combined with de-novo sequencing information, provides objective evaluation of the information content of peptide MS/MS spectra. The majority of one-hit-wonder identifications by traditional database searching were found to be false positives, but some were confirmed, and several new proteins discovered.
2007-06-20	Proteomic characterization of Pedobacter cryoconitis	PEAKS
Ana	A.G. Pereira-Medrano; R. Margesin; P.C. Wright, Proteomic characterization of the psychrophile Pedobacter cryoconitis based on both 15N metabolic labeling and de novo sequencing, ASMS 2007 Poster presentation. [download 500.588 Kb] Characterising the proteome of an unsequenced psychrophile grown with different carbon sources and under temperature extremes employing 15N metabolic labeling, 2DGE, tandem mass spectrometry, N-constrained ortholog searching, and de novo sequencing.
2006-11-15	Performance Evaluation of Existing De Novo Sequencing Algori	PEAKS
Sergey Pevtsov	J. Proteome Res., 5 (11), 3018 -3028, 2006. 10.1021/pr060222h S1535-3893(06)00222-3 Sergey Pevtsov, Irina Fedulova, Hamid Mirzaei, Charles Buck, and Xiang Zhang* [Link to Abstract] Two methods have been developed for protein identification from tandem mass spectra: database searching and de novo sequencing. De novo sequencing identifies peptide directly from tandem mass spectra. Among many proposed algorithms, we evaluated the performance of the five de novo sequencing algorithms, AUDENS, Lutefisk, NovoHMM, PepNovo, and PEAKS. Our evaluation methods are based on calculation of relative sequence distance (RSD), algorithm sensitivity, and spectrum quality. We found that de novo sequencing algorithms have different performance in analyzing QSTAR and LCQ mass spectrometer data, but in general, perform better in analyzing QSTAR data than LCQ data. For the QSTAR data, the performance order of the five algorithms is PEAKS > Lutefisk, PepNovo > AUDENS, NovoHMM. The performance of PEAKS, Lutefisk, and PepNovo strongly depends on the spectrum quality and increases with an increase of spectrum quality. However, AUDENS and NovoHMM are not sensitive to the spectrum quality. Compared with other four algorithms, PEAKS has the best sensitivity and also has the best performance in the entire range of spectrum quality. For the LCQ data, the performance order is NovoHMM > PepNovo, PEAKS > Lutefisk > AUDENS. NovoHMM has the best sensitivity, and its performance is the best in the entire range of spectrum quality. But the overall performance of NovoHMM is not significantly different from the performance of PEAKS and PepNovo. AUDENS does not give a good performance in analyzing either QSTAR and LCQ data.
2006-07-18	peptide identification wtih MS/MS	PEAKS
Bin Ma	Changjiang Xu and Bin Ma. Software for computational peptide identification from MS/MS data. Drug Discovery Today 11(13/14):595-600, 2006. [download 197.072 Kb] Review article.
2006-07-13	Software for Computational Peptide Identification from MS–MS	PEAKS
Brian Munro	Xu, Changjiang & Ma, Bin. Software for Computational Peptide Identification from MS–MS. Drug Discovery Today. Volume 11, Numbers 13/14. July 2006. [download 197.072 Kb] Protein identification in biological samples is an important task in drug discovery research. Protein identification is nowadays regularly performed by tandem mass spectrometry (MS–MS). Because of the difficulty of measuring intact proteins using MS–MS, typically a protein is enzymically digested into peptides and the MS–MS spectrum of each peptide is measured. Computational methods are then invoked to identify the peptides, which are later combined together to identify the protein. The most recognized peptide identification software packages can be classified into four categories: database searching, de novo sequencing, sequence tagging and consensus of multiple engines.
2005-12-13	Proteomic study of Australian Brown Snake venom	PEAKS
Geoff	Birrell GW, Earl S, Masci PP, de Jersey J, Wallis TP, Gorman JJ, Lavin MF. Molecular diversity in venom from the Australian brown snake, pseudonaja textilis. Mol Cell Proteomics. 2005 Nov 10; [Epub ahead of print] [Link to Abstract] In this study, we have performed a proteomic identification of the venom using two dimensional gel electrophoresis, mass spectrometry and de novo peptide sequencing. We have identified most of the venom proteins including proteins previously not known to be present in the venom.
2005-11-01	Skin elastin peptide characterization	PEAKS
Christian	Mass spectrometric characterization of human skin elastin peptides produced by proteolytic digestion with pepsin and thermitase, C. Schmelzer, M. Getie, R. Neubert, Journal of Chromatography A, 1083 (2005) 120–126 [download 588.165 Kb] The research was only possible at this level of detail using PEAKS.
2005-10-21	Finding the 22nd amino acid in sequence	PEAKS
IainR	S. K. Blight, R. C. Larue, A. Mahapatra, D. G. Longstaff, E. Chang, G. Zhao, P. T. Kang, K. B. Green-Church, M. K. Chan & J. A. Krzycki, Direct charging of tRNACUA with pyrrolysine in vitro and in vivo Nature, 2004. [download 519.568 Kb] In this paper, the team at Ohio State University works to discover how the 22nd amino acid fits into a protein sequence. Peaks played an important role in the mass spectrometry phase of the experiment. "... only Peaks allowed us to easily input Pyrrolysine, and it was really good at finding them too," says Kari Green-Church, Associate Director of MS at Ohio State's CCIC.
2005-09-30	The first posting	PEAKS
IainR	From talking to some of our users, I note a lot of compelling research that's going on out there. I hope you'll share yours here. We've got a lot of traffic comming through our website, so you're papers will get a lot of publicity. So post, or post someone else's paper that you found interesting.