title: High throughput proteome screening for biomarker detection.
abstract: Mass spectrometry-based quantitative proteomics has become an important component of biological and clinical research. Current methods, while highly developed and powerful, are falling short of their goal of routinely analyzing whole proteomes mainly because the wealth of proteomic information accumulated from prior studies is not used for the planning or interpretation of present experiments. The consequence of this situation is that in every proteomic experiment the proteome is rediscovered. In this report we describe an approach for quantitative proteomics that builds on the extensive prior knowledge of proteomes and a platform for the implementation of the method. The method is based on the selection and chemical synthesis of isotopically labeled reference peptides that uniquely identify a particular protein and the addition of a panel of such peptides to the sample mixture consisting of tryptic peptides from the proteome in question. The platform consists of a peptide separation module for the generation of ordered peptide arrays from the combined peptide sample on the sample plate of a MALDI mass spectrometer, a high throughput MALDI-TOF/TOF mass spectrometer, and a suite of software tools for the selective analysis of the targeted peptides and the interpretation of the results. Applying the method to the analysis of the human blood serum proteome we demonstrate the feasibility of using mass spectrometry-based proteomics as a high throughput screening technology for the detection and quantification of targeted proteins in a complex system.
authors.affiliation: Institute for Systems Biology, Seattle, WA 98103, USA.
authors.forename: Sheng
authors.initials: S
authors.lastname: Pan
authors.forename: Hui
authors.initials: H
authors.lastname: Zhang
authors.forename: John
authors.initials: J
authors.lastname: Rush
authors.forename: Jimmy
authors.initials: J
authors.lastname: Eng
authors.forename: Ning
authors.initials: N
authors.lastname: Zhang
authors.forename: Dale
authors.initials: D
authors.lastname: Patterson
authors.forename: Michael J
authors.initials: MJ
authors.lastname: Comb
authors.forename: Ruedi
authors.initials: R
authors.lastname: Aebersold
mesh_terms: D001331:Automation; D015415:Biomarkers; D001769:Blood / Q000378:metabolism; D001798:Blood Proteins / Q000737:chemistry*; D030562:Databases, Protein; D006031:Glycosylation; D006801:Humans; D010449:Peptide Mapping / Q000379:methods*; D010455:Peptides / Q000737:chemistry; D011506:Proteins / Q000737:chemistry; D020543:Proteome; D040901:Proteomics / Q000295:instrumentation* / Q000379:methods*; D012984:Software; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods; D013997:Time Factors; D014357:Trypsin / Q000494:pharmacology
chemical_list: D015415:Biomarkers; D001798:Blood Proteins; D010455:Peptides; D011506:Proteins; D020543:Proteome; D014357:Trypsin