A New Algorithm Using Cross-Assignment for Label-Free Quantitation with LC-LTQ-FT MS

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• 作者：Victor P. Andreev ; Lingyun Li ; Lei Cao ; Ye Gu ; Tomas Rejtar ; Shiaw-Lin Wu ; Barry L. Karger
• 刊名：Journal of Proteome Research
• 出版年：2007
• 出版时间：June 2007
• 年：2007
• 卷：6
• 期：6
• 页码：2186 - 2194
• 全文大小：293K
• 年卷期：v.6,no.6(June 2007)
• ISSN：1535-3907

文摘

A new algorithm is described for label-free quantitation of relative protein abundances across multiplecomplex 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 massaccuracy 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 substantiallythe number of quantitated proteins. In this approach, all MS/MS identifications for the set of analyzedsamples are combined into a master ID list, and then each LC-MS run is searched for the features thatcan be assigned to a specific identification from that master list. The reliability of quantitation is enhancedby quantitating separately all peptide charge states, along with a scoring procedure to filter out lessreliable peptide abundance measurements. The effectiveness of Q-MEND is illustrated in the relativequantitative analysis of Escherichia coli samples spiked with known amounts of non-E. coli proteindigests. A mean quantitation accuracy of 7% and mean precision of 15% is demonstrated. Q-MENDcan perform relative quantitation of a set of LC-MS data sets without manual intervention and cangenerate files compatible with the Guidelines for Proteomic Data Publication.