Toward a Universal Sample Preparation Method for Denaturing Top-Down Proteomics of Complex Proteomes
A universal and standardized sample preparation method becomes vital for denaturing top-down proteomics (dTDP) to advance the scale and accuracy of proteoform delineation in complex biological systems. It needs to have high protein recovery, minimum bias, good reproducibility, and compatibility with...
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Veröffentlicht in: | Journal of proteome research 2020-08, Vol.19 (8), p.3315-3325 |
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Sprache: | eng |
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Zusammenfassung: | A universal and standardized sample preparation method becomes vital for denaturing top-down proteomics (dTDP) to advance the scale and accuracy of proteoform delineation in complex biological systems. It needs to have high protein recovery, minimum bias, good reproducibility, and compatibility with downstream mass spectrometry (MS) analysis. Here, we employed a lysis buffer containing sodium dodecyl sulfate for extracting proteoforms from cells and, for the first time, compared membrane ultrafiltration (MU), chloroform–methanol precipitation (CMP), and single-spot solid-phase sample preparation using magnetic beads (SP3) for proteoform cleanup for dTDP. The MU method outperformed CMP and SP3 methods, resulting in high and reproducible protein recovery from both Escherichia coli cell (59 ± 3%) and human HepG2 cell (86 ± 5%) samples without a significant bias. Single-shot capillary zone electrophoresis (CZE)-MS/MS analyses of the prepared E. coli and HepG2 cell samples using the MU method identified 821 and 516 proteoforms, respectively. Nearly 30 and 50% of the identified E. coli and HepG2 proteins are membrane proteins. CZE-MS/MS identified 94 histone proteoforms from the HepG2 sample with various post-translational modifications, including acetylation, methylation, and phosphorylation. Our results suggest that combining the SDS-based protein extraction and the MU-based protein cleanup could be a universal sample preparation method for dTDP. The MS raw data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD018248. |
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ISSN: | 1535-3893 1535-3907 |
DOI: | 10.1021/acs.jproteome.0c00226 |