Web Release Date: September 16,
Proteome Analysis of Microdissected Tumor Tissue Using a Capillary Isoelectric Focusing-Based Multidimensional Separation Platform Coupled with ESI-Tandem MS





and
Department of Chemistry and Biochemistry and Department of Mechanical Engineering and Bioengineering Program, University of Maryland, College Park, Maryland 20742, Calibrant Biosystems, 910 Clopper Road, Suite 220N, Gaithersburg, Maryland 20878, and Molecular Pathogenesis Unit, Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, Bethesda, Maryland 20892
Received for review March 23, 2005. Accepted August 16, 2005.
Abstract:
This study demonstrates the ability to perform sensitive
proteome analysis on the limited protein quantities available through tissue microdissection. Capillary isoelectric
focusing combined with nano-reversed-phase liquid chromatography in an automated and integrated platform not
only provides systematic resolution of complex peptide
mixtures based on their differences in isoelectric point
and hydrophobicity but also eliminates peptide loss and
analyte dilution. In comparison with strong cation exchange chromatography, the significant advantages of
electrokinetic focusing-based separations include high
resolving power, high concentration and narrow analyte
bands, and effective usage of electrospray ionization-tandem MS toward peptide identifications. Through the
use of capillary isoelectric focusing-based multidimensional peptide separations, a total of 6866 fully tryptic
peptides were detected, leading to the identification of
1820 distinct proteins. Each distinct protein was identified by at least one distinct peptide sequence. These high
mass accuracy and high-confidence identifications were
generated from three proteome runs of a single glioblastoma multiforme tissue sample, each run consuming only
10
g of total protein, an amount corresponding to 20 000
selectively isolated cells. Instead of performing multiple
runs of multidimensional separations, the overall peak
capacity can be greatly enhanced for mining deeper into
tissue proteomics by increasing the number of CIEF
fractions without an accompanying increase in sample
consumption.
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