Top-down analysis of the low molecular weight proteome in human plasma samples by use of GELFrEE coupled to nanoLC tandem mass spectrometry
- Top-down analysis of the low molecular weight proteome in human plasma samples by use of GELFrEE coupled to nanoLC tandem mass spectrometry
- 천동희; 남은지; 장소은; 이수민; 이혜진; 박규형; 우세준; 이철주; 이지은
- Issue Date
- KHUPO 13th Annual International Proteomics Conference
- While human plasma is one of the most informative and important proteomes from a clinical perspective, the low molecular weight (LMW) proteome (≤30 kDa) of human plasma has recently shown to contain valuable biomarkers that can be potentially used for the purpose of diagnosis for cancer and other diseases. In most cases, the LMW plasma proteome analyses have been pursued by enrichment of the LMW plasma proteins using centrifugal ultrafiltration followed by protease digestion for mass spectrometric analysis. However, the proteolytic digestion often eliminates specific information of the protein sequences that occur naturally in the plasma and are known to be changed depending disease states. We here attempt to perform top-down analysis of the LMW plasma proteome without protease digestion, which allows for complete characterization of the protein sequences and post-translational modifications. First, plasma proteins were fractionated based on molecular weight by use of gel-eluted liquid fraction entrapment electrophoresis (GELFrEE). Then, between 5 and 8 GELFrEE fractions containing up to 30 kDa proteins were subjected to nanocapillary–LC–MS/MS with Orbitrap mass spectrometer. From the results, tens of proteins were identified with 100% sequence coverage, including multiple protein isoforms originating from endogenous cleavage products and single amino acid variants. It was also observed that the relative expression of protein isoforms produced from cleavage of a parent protein was changed between healthy and disease states of plasma, which implies that the protein isoforms could be potential biomarkers that can be used for diagnosis.
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