Journal: Cancer, April 25
Title: N-glycoprotein profiling of lung denocarcinoma pleural effusions by shotgun proteomics
Authors: A Soltermann, R Ossola; S Kilgus-Hawelski; A von Eckardstein; T Suter; R Aebersold; H Moch
Saying that malignant pleural effusions of advance lung adenocarnioma may be a source of detection of biomarkers, such as N-glycosylated proteins, the authors aimed to create N-GP effusion profiles from routine cytology specimens to detect relevant biomarkers. They collected malignant pleural effusions from five patients with lung adenocarcinoma and five non-malignant controls for triplicate N-GP capture by solid-phase extraction. After trypsin digestion and PNGase F release, LC-MS/MS was done. They concluded that “reduction of sample complexity by N-GP capturing allows detection of proteins in the [microgram] to ng/mL range,” according to the abstract. “Pleural effusion is a useful source for biomarker research in lung cancer,” the authors write.
Journal: Analytical Chemistry, April 17 [Epub ahead of print]
Title: Multiplexed Proteomics Mapping of Yeast RNA Polymerase II and III Allows Near-Complete Sequence Coverage and Reveals Several Novel Phosphorylation Sites
Authors: S Mohammed; K Lorenzen; R Kerkhoven; BV Breukelen; A Vannini; P Cramer; AJ Heck
Authors analyzed both yeast polymerase II and III by multiplexed mass spectrometric analysis using “various proteases and both collision induced and electron transfer dissociation,” according to the abstract. The data obtained from using the various proteases and the two peptide fragmentation approaches allowed them to map nearly the complete sequences of all constituents of Pol II and III.
They detected 19 phosphorylation sites, including 12 that had not been previously reported. The approach, they say, is generic and shows that it is possible to map a protein complex to near completion while applying less than five micrograms of total starting material.
Journal: Biotechnology and Applied Biochemistry, April 15 [Epub ahead of print]
Title: Development of affinity columns for the removal of high-abundant proteins in cerebrospinal fluid
Authors: M Ramström; A Zuberovic; C Grönwall; J Hanrieder; J Bergquist; S Hober
Authors chose five high-abundant CSF proteins to design a CSF-specific depletion set-up. Affibody molecules with specificity toward human HSA, IgG, transferrin, and transthyretin were combined into an affinity column. Polyclonal antibodies against cystatin C were also coupled to chromatographic beads and packed in a separate column.
The authors report that the proportion of depleted proteins were estimated to be 99 percent, 95 percent, 74 percent, 92 percent and 83 percent for HSA, IgG, transferrin, transthyretin, and cystatin C, respectively. SDS-PAGE analysis was used to monitor and identify proteins in native CSF, depleted CSF samples, and captured fractions. Shotgun proteomics was also used to identify proteins in native and depleted CSF. The data were then compared. “Enhanced identification of lower abundant components was observed in the depleted fraction, in terms of more detected peptides per protein,” according to the abstract.
Journal: Molecular & Cellular Proteomics, April 13 [Epub ahead of print]
Title: Targeted quantitative analysis of Streptococcus pyogenes virulence factors by multiple reaction monitoring
Authors: V Lange; JA Malmström; J Didion; NL King; BP Johansson; J Schäfer; J Rameseder; CH Wong CH; EW Deutsch; MY Brusniak; P Bühlmann P; L Björck; B Domon; R Aebersold
A targeted quantitative approach “by which pre-determined protein sets are first identified and subsequently quantified at high sensitivity reliably in multiple samples,” according to the abstract. The first step of the approach consists of mapping out the proteome by multidimensional fractionation and MS/MS. Data is assembled in the PeptideAtlas database. Then based on the proteome map, peptides identifying the proteins of interest are selected and MRM transitions are established and validated by MS2 spectrum acquisition. Lastly, the selected target protein set is quantified in multiple samples by MRM.
Journal: Bioconjugate Chemistry, April 12 [Epub ahead of print]
Title: Synthesis and Proteomic Activity Evaluation of a new Isotope-Coded Affinity Tagging (ICAT) Reagent
Authors: A Guaragna; A Amoresano; V Pinto; G Monti; G Mastrobuoni; G Marino
Authors investigate the utility of a modified ICAT reagent, BAA-ICAT, for beta-alanine-arm-ICAT, in which a polyether linker is replaced by a more water-soluble polyamide one.
Journal: Rapid Communications in Mass Spectrometry : RCM, April 10 [Epub ahead of print]
Title: Comparison of mass spectra of peptides in different matrices using matrix-assisted laser desorption/ionization and a multi-turn time-of-flight mass spectrometer, MULTUM-IMG
Authors: H Hazama; H Nagao; R Suzuki; M Toyoda; K Masuda; Y Naito; K Awazu
Authors compared the mass spectra of peptides from different matrices using a MALDI ion source and a multi-turn TOF mass spectrometer, or MULTUM-IMG, developed at Osaka University. Two types of solid matrices, alpha-cyano-4-hydroxycinnamic acid and 2.5-dihydroxybenoic acid, and a liquid matrix made from a mixture of 3-aminoquinoline and CHCA were used.
Journal: BMC Bioinformatics, April 10 [Epub ahead of print]
Title: Significance analysis of microarray for relative quantitation of LC/MS data in proteomics
Authors: BA Roxas; Q Li
The significance analysis of microarray method was applied to a differential proteomics problem of two samples with replicates. Using a nanoLC-linear ion trap Fourier transform mass spectrometer, they performed a quantitative proteomic analysis of two Mycobacterium smegmatis unlabeled cell cultures grown at pH 5 and pH 7, with the objective to compare protein reative abundance between the two unlabeled cell cultures. They conclude that the SAM method “can be adapted for effective significance analysis of proteomic data,” according to the abstract.
Journal: Proteomics, April 8 [Epub ahead of print]
Title: A proteome map of murine heart and skeletal muscle
Authors; K Raddatz; D Albrecht; F Hochgräfe; M Hecker; M Gotthardt
Using a proteomics approach, the authors set out to generate protein reference maps for the mouse heart and skeletal muscle, with the objective that they would serve as a molecular basis for future functional and pathophysiological studies. They identified 351 cardiac and 284 skeletal muscle protein spots, representing 249 and 214 different proteins, respectively. They also visualized the protein pattern of mouse heart and skeletal muscle at defined conditions comparing knock-out animals “deficient in the sarcomeric protein titin … and control littermates,” they say in the abstract, and found 20 proteins differently expressed linking titin’s kinase region to the heat-shock- and proteasomal stress response.
Journal: Electrophoresis, April 7 [Epub ahead of print]
Title: Coupling a microchip with electrospray ionization quadrupole time-of-flight mass spectrometer for peptide separation and identification
Authors: HF Li; J Liu; Z Cai; JM Lin
Reported is a method to couple a glass microchip to an ESI Q-TOF MS. They constructed a sheath-flow electrospray interface based on attaching a short fused-silica capillary to the chip. Dead volume at the interface “was effectively reduced by wet etching an approximate flat-bottom capillary insertion channel coaxial to the end of separation microchannel and using a wire-controlled epoxy-blocking attachment method,” according to the abstract. “The coupled microchip/ESI-QTOF-MS system was successfully used to carry out electrophoresis separation of peptides and ESI-QTOF-MS identification,” according to the abstract.
Journal: Bioinformatics, April 7 [Epub ahead of print]
Title:Peak Bagging for Peptide Mass Fingerprinting
Authors: Z He; C Yang; W Yu
Authors propose a peak bagging method for single mass spectrometry-based protein identification, combining results from peptide mass fingerprinting algorithms, where each PMF algorithm takes as input a random peak subset.
Journal: Briefings in Functional Genomics & Proteomics, April 4 [Epub ahead of print]
Title: Analysis of iTRAQ data using Mascot and Peaks quantification algorithms
Authors: CM Lacerda; L Xin; I Rogers; KF Reardon
The two software packages were compared for iTRAQ data from ESI-Q/TOF mass spectrometry. In a six-protein mixture combined in known proportion, the output of the Peaks algorithm deviated from the correct result by 14 percent on average, while the error of the Mascot quantification was almost 200 percent, the authors say in the abstract. When used to analyze a complex protein sample, the quantification results agreed with 20 percent for only 26 percent of the quantified proteins “showing significant differences in the two quantification algorithms,” they say.
Journal: Nucleic Acids Research, April 4 [Epub ahead of print]
Title: Using support vector machine combined with auto covariance to predict protein-protein interactions from protein sequences
Authors: Y Guo; L Yu; Z Wen; M Li
Authors propose a sequence-based method for protein-protein interaction identification. They combine a new feature representation using auto covariance and support vector machine. Using it on the yeast S. cerevisiae, “the method achieved a very promising prediction result,” according to the abstract. An 88.09 percent accuracy was achieved when an independent data set of 11,474 yeast PPIs was used to evaluate the prediction model.
Journal: American Journal of Clinical Pathology, April
Title: CSF Multianalyte profile distinguishes Alzheimer and Parkinson diseases
Authors: J Zhang; I Sokal; ER Peskind; JF Quinn; J Jankovic; C Kenney; KA Chung; SP Millard; JG Nutt; TJ Montine
Authors validated their multianalyte profile in CSF from 95 control subjects, 48 patients with probable AD, and 40 patients with probable PD. The MAP consisted of tau; brain-derived neurotrophic factor; interleukin 8: Abeta42; beta2-microglobulin; vitamin D binding protein; apoliprotein A II, and apoliprotein E. The eight-member MAP corresponded with expert diagnosis for 90 control patients, 36 patients with probable AD, and 38 patients with probable PD, suggesting “a panel of eight CSF proteins that are highly effective at identifying PD and moderately effective at identifying AD,” according to the abstract.