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Recent Research Papers of Note in Proteomics: Apr 3, 2008

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Journal: Experimental Biology and Medicine, April
Title: An integrated strategy in two-dimensional electrophoresis analysis able to identify discriminants between different clinical conditions
Authors: L Pattini; S Mazzara; A Conti; S Iannaccone; S Cerutti; M Alessio
 
To address the challenge of automatically extracting information from gel images, the authors present a strategy comprising a “computational procedure of support to the discriminant of different clinical conditions associated with the samples.”
 
They generated 24 2DE maps from cerebrospinal fluid and processed them. “Quantitative features were defined to describe each image and treated with a method of dimensionality reduction,” they say in the abstract. They were able to see the gel of the data set as items in a three-dimensional space. The method, they say, could be a tool of classification that can be used repeatedly to capture the essential impression from separation images.
 

 
Journal: Protein Science; A Publication of the Protein Society, April
Title: The epitope space of the human proteome
Authors: L Berglund; J Andrade; J Odeberg; M Uhlén
 
Authors show the results from a proteome-wide effort to map linear epitopes “based on uniqueness relative to the entire human proteome,” according to the abstract. They based their analysis on a sliding window sequence similarity search using short windows, such as 8-,10-, and 12-amino acid residues. They performed a comparison of exact string matching and a heuristic method, and showed that a heuristic approach combined with a grid strategy allows for whole proteome analysis with high accuracy and feasible run-times.
 
“The analysis shows that it is possible to find unique antigens for a majority of the human proteins, with relatively strict rules involving low sequence identity of the possible linear epitopes,” they say in the abstract. “The implications for human antibody-based proteomics efforts are discussed.”
 

 
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; JF Nutt; TJ Montine
 
Authors validated their proteomics-discovered multianalyte profile, or MAP, in CSF from 95 control subjects, 48 patients with probable Alzheimer’s, and 40 patients with probable Parkinson’s. They then used an eight-member MAP to screen CSF from their subjects, resulting in correct diagnoses for 90 control subjects, 36 patients with probable AD, and 38 patients with probable PD. The MAP consisted of tau, brain-derived neurotrophic factor, interleukin 8; Abeta42; beta2-microglobulin; vitamin D binding protein; apoliproprotein (apo) AII; and apoE.  
 

 
Journal: BMC Bioinformatics, March 26 [Epub ahead of print]
Title: OpenMS — An open-source software framework for mass spectrometry
Authors: M Sturm; B Bertsch; C Groepl; A Hildebrandt; R Hussong; E Lange; N Pfeifer; O Schulz-Trieglaff; A Zerck; K Reinert; O Kohlbacher
 
Presented is a software framework for rapid application development in mass spectrometry. “OpenMS is designed to be portable, easy to use, and robust while offering a rich functionality ranging from basic data structures to sophisticated algorithms for data analysis,” according to the abstract.
 

 
Journal: Journal of Proteome Research, March 25 [Epub ahead of print]
Title: The proteomes of human parotid and submandibular/sublingual gland salivas collected as the ductal secretions
Authors: P Denny; FK Hagen; M Hardt; L Liao; W Yan; M Arellanno; S Bassilian; GS Bedi; P Boontheung; D Cociorva; CM Delahunty; T Denny; J Dunsmore; KF Faull; J Gilligan; M Gonzalez-Begne; F Halgand; SC Hall; X Han; B Henson; J Hewel; S Hu; S Jeffrey; J Jiang; JA Loo; RR Ogorzalek Loo; D Malamud; JE Melvin; O Miroshnychenko; M Navazesh; R Niles; SK Park; A Prakobphol; P Ramachandran; M Richert; S Robinson; M Sondej; P Souda; MA Sullivan; J Takashima; S Than; J Wang; JP Whitelegge; HE Witkowska; L Wolinsky; Y Xie; T Xu; W Yu; J Ytterberg; DT Wong; JR Yates; SJ Fisher
 
Researchers working in three groups identified 1,166 proteins produced by ductal secretions — 914 in parotid and 917 in submandibular/sublingual glands. The authors say in their abstract a “high proportion” of proteins found in plasma and/or tears are also found in saliva, and the proteins that were identified are involved in various molecular processes including structural functions and enzymatic/catalytic activities. “A catalogue of the salivary proteome of healthy individuals allows future analyses of salivary samples from individuals with oral and systemic diseases, with the goal of identifying biomarkers with diagnostic and/or prognostic value for these conditions; another is the possibility of therapeutic targets,” according to the abstract (See feature story, this issue).
 

 
Journal: Analytical Chemistry, March 20 [Epub ahead of print]
Title: “Proteotyping”: Population proteomics of human leukocytes using top down mass spectrometry
Authors: MJ Roth; BA Parks; JT Ferguson; MT Ii; NL Kelleher
 
Authors used a 2D platform dubbed multidimensional protein characterization by automated top-down, or MudCAT, and identified 108 protein forms in the absence of MS/MS in four days. They report that MudCAT enables the quantitation of allele rations for heterozygotes and post-translational modifications for phosphorylated species. ”The diversity of the human proteome is embodied in the fact that 32 of the identified proteins harbored cSNPs, PTMs, or were detected as proteolysis products,” they say in the abstract. “Among the information were three partially phosphorylated proteins and three proteins heterozygous at known cSNP loci, with evidence for non-1:1 expression ratios obtained for different alleles.”
 

 
Journal: Bioinformatics, March 18 [Epub ahead of print]
Title: A noise model for mass spectrometry based proteomics
Authors: P Du; G Stolovitzky; P Horvatovich; R Bischoff; J Lim; F Suits
 
Saying that good noise models are required to properly detect and quantify peptides, the authors characterized noise in Q-TOF and ion trap data and constructed models for the noise. They found that the noise in Q-TOF data from ABI’s QSTAR “fits well to a combination of multinomial and Poisson model with detector dead time corrected,” according to the abstract. Ion trap noise from Agilent Technologies’ ASD-TRAP-SL is larger than the Q-TOF noise and proportional to Poisson noise. By estimating appropriate cutoffs of “the goodness of fit parameter at prescribed error rates,” they demonstrate that the noise model can be used to improve de-isotoping for peptide detection.
 

 
Journal: Nature Methods, March 16 [Epub ahead of print]
Title: A quantitative analysis of software tool for mass spectrometry-based proteomics
Authors: SK Park; JD Venable; T Xu; JR Yates
 
Described is Census, a quantitative software tool compatible with many labeling strategies. It is also compatible with label-free analyses, single-stage mass spectrometry and MS/MS scans and high- and low-resolution mass spectrometry data.
 

 
Journal: Briefings in Bioinformatics, March 11 [Epub ahead of print]
Title: Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods
Authors: T Villmann; FM Schleif; M Kostrzewa; A Walch; B Hammer
 
Authors propose two recently developed classification algorithms for the analysis of mass spectrometry generated data — the supervised neural gas and the fuzzy-labeled self-organizing map. The algorithms are “inherently regularizing … for these spectral data because of its high dimensionality and the sparseness for specific problems,” they say in the abstract. The algorithms are prototype-based, leading to an easy interpretation of the generated classification model.

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