ac035229m_si_001.pdf (446.33 kB)
Improving Reproducibility and Sensitivity in Identifying Human Proteins by Shotgun Proteomics
journal contribution
posted on 2004-07-01, 00:00 authored by Katheryn A. Resing, Karen Meyer-Arendt, Alex M. Mendoza, Lauren D. Aveline-Wolf, Karen R. Jonscher, Kevin G. Pierce, William M. Old, Hiu T. Cheung, Steven Russell, Joy L. Wattawa, Geoff R. Goehle, Robin D. Knight, Natalie G. AhnIdentifying proteins in cell extracts by shotgun proteomics
involves digesting the proteins, sequencing the resulting
peptides by data-dependent mass spectrometry (MS/MS),
and searching protein databases to identify the proteins
from which the peptides are derived. Manual analysis and
direct spectral comparison reveal that scores from two
commonly used search programs (Sequest and Mascot)
validate less than half of potentially identifiable MS/MS
spectra (class positive) from shotgun analyses of the
human erythroleukemia K562 cell line. Here we demonstrate increased sensitivity and accuracy using a focused
search strategy along with a peptide sequence validation
script that does not rely exclusively on XCorr or Mowse
scores generated by Sequest or Mascot, but uses consensus between the search programs, along with chemical
properties and scores describing the nature of the fragmentation spectrum (ion score and RSP). The approach
yielded 4.2% false positive and 8% false negative frequencies in peptide assignments. The protein profile is then
assembled from peptide assignments using a novel peptide-centric protein nomenclature that more accurately
reports protein variants that contain identical peptide
sequences. An Isoform Resolver algorithm ensures that
the protein count is not inflated by variants in the protein
database, eliminating ∼25% of redundant proteins. Analysis of soluble proteins from a human K562 cells identified
5130 unique proteins, with ∼100 false positive protein
assignments.