Dataset Information

Multiphasic chip performance characterization using human thyroid cancer cell line SW1736 and human plasma

ABSTRACT: Development of an online peptide fractionation system comprising a multiphasic LC chip that integrates reversed phase and strong cation exchange chromatography upstream of the MS based on the multi-dimensional protein identification technology (mudPIT). Chips were assessed in terms of chromatographic as well as protein and peptide identification reproducibility using five-step fractionation of 0, 2, 50, 500 and 1500 mM ammonium acetate. Further, a comparison of multiphase LC chip protein and peptide identification versus conventional reversed phase LC-MSMS was performed.

INSTRUMENT(S): TripleTOF 5600

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Plasma, Epithelial Cell, Cell Culture

SUBMITTER: Christoph Krisp

LAB HEAD: Assoc Prof Mark P Molloy

PROVIDER: PXD001464 | Pride | 2015-04-15

REPOSITORIES: Pride

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Publications

Online Peptide fractionation using a multiphasic microfluidic liquid chromatography chip improves reproducibility and detection limits for quantitation in discovery and targeted proteomics.

Krisp Christoph C Yang Hao H van Soest Remco R Molloy Mark P MP

Molecular & cellular proteomics : MCP 20150407 6

Comprehensive proteomic profiling of biological specimens usually requires multidimensional chromatographic peptide fractionation prior to mass spectrometry. However, this approach can suffer from poor reproducibility because of the lack of standardization and automation of the entire workflow, thus compromising performance of quantitative proteomic investigations. To address these variables we developed an online peptide fractionation system comprising a multiphasic liquid chromatography (LC) c ...[more]

PMID: 25850434

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Dataset Information

Multiphasic chip performance characterization using human thyroid cancer cell line SW1736 and human plasma

Publications

Online Peptide fractionation using a multiphasic microfluidic liquid chromatography chip improves reproducibility and detection limits for quantitation in discovery and targeted proteomics.

Similar Datasets

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