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User's Research and Papers
Here's a repository of some papers we found to be interesting. Some of them were submitted by our users. Please share your research.
2008-08-06 |
Isolation and Characterization of Carnocyclin A |
PEAKS |
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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. |
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2007-11-12 |
De novo protein sequence analysis of Macaca mulatta |
PEAKS |
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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. |
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2007-09-24 |
tubulin formation in individuals with HRD |
PEAKS |
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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 ..." |
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2007-07-20 |
Evaluating one-hit-wonders using de novo sequence tag search |
PEAKS |
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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. |
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2007-06-20 |
Proteomic characterization of Pedobacter cryoconitis |
PEAKS |
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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. |
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2006-11-15 |
Performance Evaluation of Existing De Novo Sequencing Algori |
PEAKS |
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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. |
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2006-07-18 |
peptide identification wtih MS/MS |
PEAKS |
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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. |
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2006-07-13 |
Software for Computational Peptide Identification from MS–MS |
PEAKS |
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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. |
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2005-12-13 |
Proteomic study of Australian Brown Snake venom |
PEAKS |
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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. |
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2005-11-01 |
Skin elastin peptide characterization |
PEAKS |
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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. |
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2005-10-21 |
Finding the 22nd amino acid in sequence |
PEAKS |
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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. |
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2005-09-30 |
The first posting |
PEAKS |
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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. |
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