Serum peptide profiling by magnetic particle-assisted, automated sample processing and MALDI-TOF mass spectrometry

J Villanueva, J Philip, D Entenberg… - Analytical …, 2004 - ACS Publications
J Villanueva, J Philip, D Entenberg, CA Chaparro, MK Tanwar, EC Holland, P Tempst
Analytical chemistry, 2004ACS Publications
Human serum contains a complex array of proteolytically derived peptides (serum
peptidome) that may provide a correlate of biological events occurring in the entire
organism; for instance, as a diagnostic for solid tumors (Petricoin, EF; Ardekani, AM; Hitt, BA;
Levine, PJ; Fusaro, VA; Steinberg, SM; Mills, GB; Simone, C.; Fishman, DA; Kohn, EC; Liotta,
L. Lancet 2002, 359, 572− 577). Here, we describe a novel, automated technology platform
for the simultaneous measurement of serum peptides that is simple, scalable, and generates …
Human serum contains a complex array of proteolytically derived peptides (serum peptidome) that may provide a correlate of biological events occurring in the entire organism; for instance, as a diagnostic for solid tumors (Petricoin, E. F.; Ardekani, A. M.; Hitt, B. A.; Levine, P. J.; Fusaro, V. A.; Steinberg, S. M.; Mills, G. B.; Simone, C.; Fishman, D. A.; Kohn, E. C.; Liotta, L. Lancet 2002, 359, 572−577). Here, we describe a novel, automated technology platform for the simultaneous measurement of serum peptides that is simple, scalable, and generates highly reproducible patterns. Peptides are captured and concentrated using reversed-phase (RP) batch processing in a magnetic particle-based format, automated on a liquid handling robot, and followed by a MALDI TOF mass spectrometric readout. The protocol is based on a detailed investigation of serum handling, RP ligand and eluant selection, small-volume robotics design, an optimized spectral acquisition program, and consistent peak extraction plus binning across a study set. The improved sensitivity and resolution allowed detection of 400 polypeptides (0.8−15-kDa range) in a single droplet (∼50 μL) of serum, and almost 2000 unique peptides in larger sample sets, which can then be analyzed using common microarray data analysis software. A pilot study indicated that sera from brain tumor patients can be distinguished from controls based on a pattern of 274 peptide masses. This, in turn, served to create a learning algorithm that correctly predicted 96.4% of the samples as either normal or diseased.
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