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Evaluating Chromatographic Approaches for the Quantitative Analysis of a Human Proteome on Orbitrap-Based Mass Spectrometry Systems.

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The Orbitrap is now a core component of several different instruments. However, evaluating the capabilities of each system is lacking in the field. Here, we compared the performance of multidimensional… Click to show full abstract

The Orbitrap is now a core component of several different instruments. However, evaluating the capabilities of each system is lacking in the field. Here, we compared the performance of multidimensional protein identification (MudPIT) on Velos Pro Orbitrap and Velos Orbitrap Elite mass spectrometers to reversed phase liquid chromatography (RPLC) on a Q-Exactive Plus and an Orbitrap Fusion Lumos. Using HeLa cell protein digests, we carried out triplicate analyses of 16 different chromatography conditions on four different instrumentation platforms. We first optimized RPLC conditions by varying column lengths, inner diameters, and particle sizes. We found that smaller particle sizes improve results but only with smaller inner diameter microcapillary columns. We then selected one chromatography condition on each system and varied gradient lengths. We used distributed normalized spectral abundance factor (dNSAF) values to determine quantitative reproducibility. With Pearson product-moment correlation coefficient r values routinely above 0.96, single RPLC on both the QE+ and Orbitrap Lumos outperformed MudPIT on the Orbitrap Elite mass spectrometer. In addition, when comparing dNSAF values measured for the same proteins across the different platforms, RPLC on the Orbitrap Lumos had greater sensitivity than MudPIT, as demonstrated by the detection and quantification of histone deacetylase complex components. Data are available via ProteomeXchange with identifier 10.6019/PXD009875.

Keywords: evaluating chromatographic; chromatographic approaches; mass; orbitrap; approaches quantitative; proteome

Journal Title: Journal of proteome research
Year Published: 2019

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