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Combinatorial libraries of synthetic peptides as a model for shotgun proteomics.

ABSTRACT: A synthetic approach to model the analytical complexity of biological proteolytic digests has been developed. Combinatorial peptide libraries ranging in length between 9 and 12 amino acids that represent typical tryptic digests were designed, synthesized, and analyzed. Individual libraries and mixtures thereof were studied by replicate liquid chromatography-ion trap mass spectrometry and compared to a tryptic digest of Deinococcus radiodurans. Similar to complex proteome analysis, replicate study of individual libraries identified additional unique peptides. Fewer novel sequences were revealed with each additional analysis in a manner similar to that observed for biological data. Our results demonstrate a bimodal distribution of peptides sorting to either very low or very high levels of detection. Upon mixing of libraries at equal abundance, a length-dependent bias in favor of longer sequence identification was observed. Peptide identification as a function of site-specific amino acid content was characterized with certain amino acids proving to be of considerable importance. This report demonstrates that peptide libraries of defined character can serve as a reference for instrument characterization. Furthermore, they are uniquely suited to delineate the physical properties that influence identification of peptides, which provides a foundation for optimizing the study of samples with less defined heterogeneity.

SUBMITTER: Bohrer BC

PROVIDER: S-EPMC2927099 | biostudies-literature | 2010 Aug

REPOSITORIES: biostudies-literature

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Combinatorial libraries of synthetic peptides as a model for shotgun proteomics.

Bohrer Brian C BC Li Yong Fuga YF Reilly James P JP Clemmer David E DE DiMarchi Richard D RD Radivojac Predrag P Tang Haixu H Arnold Randy J RJ

Analytical chemistry 20100801 15

A synthetic approach to model the analytical complexity of biological proteolytic digests has been developed. Combinatorial peptide libraries ranging in length between 9 and 12 amino acids that represent typical tryptic digests were designed, synthesized, and analyzed. Individual libraries and mixtures thereof were studied by replicate liquid chromatography-ion trap mass spectrometry and compared to a tryptic digest of Deinococcus radiodurans. Similar to complex proteome analysis, replicate stud ...[more]

PMID: 20669997

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Project description:Epithelial ovarian cancer is the most deadly gynecological cancer around the world, with high morbidity in industrialized countries. Early diagnosis is key in reducing its morbidity rate. Yet, robust biomarkers, diagnostics, and animal models are still limited for ovarian cancer. This calls for broader omics and systems science oriented diagnostics strategies. In this vein, the domestic chicken has been used as an ovarian cancer animal model, owing to its high rate of developing spontaneous epithelial ovarian tumors. Chicken blood has thus been considered a surrogate reservoir from which cancer biomarkers can be identified. However, the presence of highly abundant proteins in chicken blood has compromised the applicability of proteomics tools to study chicken blood owing to a lack of immunodepletion methods. Here, we demonstrate that a combinatorial peptide ligand library (CPLL) can efficiently remove highly abundant proteins from chicken blood samples, consequently doubling the number of identified proteins. Using an integrated CPLL-1DGE-LC-MSMS workflow, we identified a catalog of 264 unique proteins. Functional analyses further suggested that most proteins were coagulation and complement factors, blood transport and binding proteins, immune- and defense-related proteins, proteases, protease inhibitors, cellular enzymes, or cell structure and adhesion proteins. Semiquantitative spectral counting analysis identified 10 potential biomarkers from the present chicken ovarian cancer model. Additionally, many human homologs of chicken blood proteins we have identified have been independently suggested as diagnostic biomarkers for ovarian cancer, further triangulating our novel observations reported here. In conclusion, the CPLL-assisted proteomic workflow using the chicken ovarian cancer model provides a feasible platform for translational research to identify ovarian cancer biomarkers and understand ovarian cancer biology. To the best of our knowledge, we report here the most comprehensive survey of the chicken blood proteome to date.

Dataset Information

Combinatorial libraries of synthetic peptides as a model for shotgun proteomics.

Publications

Combinatorial libraries of synthetic peptides as a model for shotgun proteomics.

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