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J Biomol Tech. 2007 February; 18(1): 66.
PMCID: PMC2291932

P191-M A Comparison of nLC-ESI-MS/MS and nLC-MALDI-MS/MS for GeLC-Based Protein Identification and iTRAQ-Based Shotgun Quantitative Proteomics


The use of nano-HPLC electrospray ionization multistage tandem mass spectrometry (nLC-ESI-MS/MS) in shotgun proteomics experiments and nano-liquid-chromatography tandem mass spectrometry (GeLC-MS/MS) analysis is well accepted and routinely available in most proteomics laboratories. The same can not be said for nLC-MALDI MS/MS, which has yet to experience such widespread acceptance. This is not totally surprising, given the inability to monitor the separation performance in real time and the time-consuming processes of off-line data analysis and interpretation that are associated with MALDI. This is unfortunate, as the MALDI technology offers several critical advantages over ESI that can be exploited to improve experimental outcomes. Here, we re-evaluate and demonstrate both the complementary nature of the two approaches and the synergism attainable through the employment of both ionization technologies to two common applications: protein identification in 1D gel bands and quantification of the dynamics of protein expression during ontogenesis.

Our results show that by using MALDI in addition to ESI in GeLC-MS/MS experiments, not only did the number of proteins identified increase by an average of 15% but the average sequence coverage for proteins identified by both techniques increased by 175% over what it was when ESI was used alone. The size of the unique peptides identified by MALDI was, on average, 25% larger than the unique peptides identified by ESI. Furthermore, the higher resolution of the TOF/TOF instrument and the greater numbers of peptides detected using MALDI improved the sensitivity, accuracy, and precision of the data over what was obtained using only electrospray ionization in iTRAQ experiments carried out on a linear ion trap. These results demonstrate that the combination of nanoLC with two ionization technologies improves proteome coverage and quantitation in complex samples.

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