title: Design and analysis of quantitative differential proteomics investigations using LC-MS technology.
abstract: Liquid chromatography-mass spectrometry (LC-MS)-based proteomics is becoming an increasingly important tool in characterizing the abundance of proteins in biological samples of various types and across conditions. Effects of disease or drug treatments on protein abundance are of particular interest for the characterization of biological processes and the identification of biomarkers. Although state-of-the-art instrumentation is available to make high-quality measurements and commercially available software is available to process the data, the complexity of the technology and data presents challenges for bioinformaticians and statisticians. Here, we describe a pipeline for the analysis of quantitative LC-MS data. Key components of this pipeline include experimental design (sample pooling, blocking, and randomization) as well as deconvolution and alignment of mass chromatograms to generate a matrix of molecular abundance profiles. An important challenge in LC-MS-based quantitation is to be able to accurately identify and assign abundance measurements to members of protein families. To address this issue, we implement a novel statistical method for inferring the relative abundance of related members of protein families from tryptic peptide intensities. This pipeline has been used to analyze quantitative LC-MS data from multiple biomarker discovery projects. We illustrate our pipeline here with examples from two of these studies, and show that the pipeline constitutes a complete workable framework for LC-MS-based differential quantitation. Supplementary material is available at http://iec01.mie.utoronto.ca/~thodoros/Bukhman/.
authors.affiliation: Protana Inc, Toronto, Ontario, Canada. ybukhman@uhnres.utoronto.ca
authors.forename: Yury V
authors.initials: YV
authors.lastname: Bukhman
authors.forename: Moyez
authors.initials: M
authors.lastname: Dharsee
authors.forename: Rob
authors.initials: R
authors.lastname: Ewing
authors.forename: Peter
authors.initials: P
authors.lastname: Chu
authors.forename: Thodoros
authors.initials: T
authors.lastname: Topaloglou
authors.forename: Thierry
authors.initials: T
authors.lastname: Le Bihan
authors.forename: Theo
authors.initials: T
authors.lastname: Goh
authors.forename: Henry
authors.initials: H
authors.lastname: Duewel
authors.forename: Ian I
authors.initials: II
authors.lastname: Stewart
authors.forename: Jacek R
authors.initials: JR
authors.lastname: Wisniewski
authors.forename: Nancy F
authors.initials: NF
authors.lastname: Ng
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D001709:Biotechnology / Q000379:methods; D002853:Chromatography, Liquid / Q000379:methods*; D013058:Mass Spectrometry / Q000379:methods*; D008969:Molecular Sequence Data; D010449:Peptide Mapping / Q000379:methods*; D020543:Proteome / Q000737:chemistry*; D040901:Proteomics / Q000379:methods*; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software; D012985:Software Design
chemical_list: D020543:Proteome