A new algorithm using cross-assignment for label-free quantitation with LC-LTQ-FT MS.
A new algorithm is described for label-free quantitation of relative protein abundances across multiple complex proteomic samples. Q-MEND is based on the denoising and peak picking algorithm, MEND, previously developed in our laboratory. Q-MEND takes advantage of the high resolution and mass accuracy of the hybrid LTQ-FT MS mass spectrometer (or other high-resolution mass spectrometers, such as a Q-TOF MS). The strategy, termed "cross-assignment", is introduced to increase substantially the number of quantitated proteins. In this approach, all MS/MS identifications for the set of analyzed samples are combined into a master ID list, and then each LC-MS run is searched for the features that can be assigned to a specific identification from that master list. The reliability of quantitation is enhanced by quantitating separately all peptide charge states, along with a scoring procedure to filter out less reliable peptide abundance measurements. The effectiveness of Q-MEND is illustrated in the relative quantitative analysis of Escherichia coli samples spiked with known amounts of non-E. coli protein digests. A mean quantitation accuracy of 7% and mean precision of 15% is demonstrated. Q-MEND can perform relative quantitation of a set of LC-MS data sets without manual intervention and can generate files compatible with the Guidelines for Proteomic Data Publication.
Andreev
Victor P
VP
Barnett Institute and Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts 02115, USA.
Li
Lingyun
L
Cao
Lei
L
Gu
Ye
Y
Rejtar
Tomas
T
Wu
Shiaw-Lin
SL
Karger
Barry L
BL
D000465:Algorithms; D002853:Chromatography, Liquid / Q000379:methods*; D004926:Escherichia coli / Q000737:chemistry; D013058:Mass Spectrometry / Q000379:methods*; D010455:Peptides / Q000032:analysis; D011506:Proteins / Q000032:analysis*; D040901:Proteomics / Q000379:methods*; D015203:Reproducibility of Results
D010455:Peptides; D011506:Proteins