Dataset Information

SP2: Rapid and Automatable Contaminant Removal from Peptide Samples for Proteomic Analyses.

ABSTRACT: Peptide cleanup is essential for the removal of contaminating substances that may be introduced during sample preparation steps in bottom-up proteomic workflows. Recent studies have described benefits of carboxylate-modified paramagnetic particles over traditional reversed-phase methods for detergent and polymer removal, but challenges with reproducibility have limited the widespread implementation of this approach among laboratories. To overcome these challenges, the current study systematically evaluated key experimental parameters regarding the use of carboxylate-modified paramagnetic particles and determined those that are critical for maximum performance and peptide recovery and those for which the protocol is tolerant to deviation. These results supported the development of a detailed, easy-to-use standard operating protocol, termed SP2, which can be applied to remove detergents and polymers from peptide samples while concentrating the sample in solvent that is directly compatible with typical LC-MS workflows. We demonstrate that SP2 can be applied to phosphopeptides and glycopeptides and that the approach is compatible with robotic liquid handling for automated sample processing. Altogether, the results of this study and accompanying detailed operating protocols for both manual and automated processing are expected to facilitate reproducible implementation of SP2 for various proteomics applications and will especially benefit core or shared resource facilities where unknown or unexpected contaminants may be particularly problematic.

SUBMITTER: Waas M

PROVIDER: S-EPMC6571012 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Publications

SP2: Rapid and Automatable Contaminant Removal from Peptide Samples for Proteomic Analyses.

Waas Matthew M Pereckas Michaela M Jones Lipinski Rachel A RA Ashwood Christopher C Gundry Rebekah L RL

Journal of proteome research 20190228 4

Peptide cleanup is essential for the removal of contaminating substances that may be introduced during sample preparation steps in bottom-up proteomic workflows. Recent studies have described benefits of carboxylate-modified paramagnetic particles over traditional reversed-phase methods for detergent and polymer removal, but challenges with reproducibility have limited the widespread implementation of this approach among laboratories. To overcome these challenges, the current study systematicall ...[more]

PMID: 30795648

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Project description:The search for clinically useful protein biomarkers using advanced mass spectrometry approaches represents a major focus in cancer research. However, the direct analysis of human samples may be challenging due to limited availability, the absence of appropriate control samples, or the large background variability observed in patient material. As an alternative approach, human tumors orthotopically implanted into a different species (xenografts) are clinically relevant models that have proven their utility in pre-clinical research. Patient derived xenografts for glioblastoma have been extensively characterized in our laboratory and have been shown to retain the characteristics of the parental tumor at the phenotypic and genetic level. Such models were also found to adequately mimic the behavior and treatment response of human tumors. The reproducibility of such xenograft models, the possibility to identify their host background and perform tumor-host interaction studies, are major advantages over the direct analysis of human samples. At the proteome level, the analysis of xenograft samples is challenged by the presence of proteins from two different species which, depending on tumor size, type or location, often appear at variable ratios. Any proteomics approach aimed at quantifying proteins within such samples must consider the identification of species specific peptides in order to avoid biases introduced by the host proteome. Here, we present an in-house methodology and tool developed to select peptides used as surrogates for protein candidates from a defined proteome (e.g., human) in a host proteome background (e.g., mouse, rat) suited for a mass spectrometry analysis. The tools presented here are applicable to any species specific proteome, provided a protein database is available. By linking the information from both proteomes, PeptideManager significantly facilitates and expedites the selection of peptides used as surrogates to analyze proteins of interest.

Dataset Information

SP2: Rapid and Automatable Contaminant Removal from Peptide Samples for Proteomic Analyses.

Publications

SP2: Rapid and Automatable Contaminant Removal from Peptide Samples for Proteomic Analyses.

Similar Datasets

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