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  • P-ISSN 2233-4203
  • E-ISSN 2093-8950

An Automated High Throughput Proteolysis and Desalting Platform for Quantitative Proteomic Analysis

Mass Spectrometry Letters / Mass Spectrometry Letters, (P)2233-4203; (E)2093-8950
2013, v.4 no.2, pp.25-29
https://doi.org/10.5478/MSL.2013.4.2.25
Arul Albert-Baskar (Gachon University)
Han Na-Young (Gachon University)
Lee Hookeun (Gachon University)
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Abstract

Proteomics for biomarker validation needs high throughput instrumentation to analyze huge set of clinical samplesfor quantitative and reproducible analysis at a minimum time without manual experimental errors. Sample preparation, a vitalstep in proteomics plays a major role in identification and quantification of proteins from biological samples. Tryptic digestion amajor check point in sample preparation for mass spectrometry based proteomics needs to be more accurate with rapid processingtime. The present study focuses on establishing a high throughput automated online system for proteolytic digestion anddesalting of proteins from biological samples quantitatively and qualitatively in a reproducible manner. The present study comparesonline protein digestion and desalting of BSA with conventional off-line (in-solution) method and validated for real timesample for reproducibility. Proteins were identified using SEQUEST data base search engine and the data were quantified usingIDEALQ software. The present study shows that the online system capable of handling high throughput samples in 96 well formatscarries out protein digestion and peptide desalting efficiently in a reproducible and quantitative manner. Label free quantificationshowed clear increase of peptide quantities with increase in concentration with much linearity compared to off linemethod. Hence we would like to suggest that inclusion of this online system in proteomic pipeline will be effective in quantificationof proteins in comparative proteomics were the quantification is really very crucial.

keywords
Proteomics, Peptide linearity, IDEALQ, Online digestion, Comparative proteomics, Peptide quantification


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Submission Date
2013-05-29
Revised Date
2013-06-12
Accepted Date
2013-06-17
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