An iterative strategy for precursor ion selection for LC-MS/MS based shotgun proteomics.
Currently, the precursor ion selection strategies in LC-MS mainly choose the most prominent peptide signals for MS/MS analysis. Consequently, high-abundance proteins are identified by MS/MS of many peptides, whereas proteins of lower abundance might elude identification. We present a novel, iterative and result-driven approach for precursor ion selection that significantly increases the efficiency of an MS/MS analysis by decreasing data redundancy and analysis time. By simulating different strategies for precursor ion selection on an existing data set, we compare our method to existing result-driven strategies and evaluate its performance with regard to mass accuracy, database size, and sample complexity.
Zerck
Alexandra
A
Max Planck Institute for Molecular Genetics, Department Vertebrate Genomics, Ihnestr. 63-73, D-14195 Berlin, Germany. zerck@molgen.mpg.de
Nordhoff
Eckhard
E
Resemann
Anja
A
Mirgorodskaya
Ekaterina
E
Suckau
Detlef
D
Reinert
Knut
K
Lehrach
Hans
H
Gobom
Johan
J
D000465:Algorithms; D002460:Cell Line; D002853:Chromatography, Liquid / Q000379:methods*; D003198:Computer Simulation; D030562:Databases, Protein; D004926:Escherichia coli / Q000378:metabolism; D006801:Humans; D007477:Ions; D013058:Mass Spectrometry / Q000379:methods*; D015233:Models, Statistical; D010455:Peptides / Q000032:analysis; D011506:Proteins / Q000737:chemistry; D040901:Proteomics / Q000379:methods*; D015203:Reproducibility of Results; D012984:Software
D007477:Ions; D010455:Peptides; D011506:Proteins