Strong cation exchange-reversed phase liquid chromatography-capillary zone electrophoresis-tandem mass spectrometry...

Two-dimensional (2D) liquid chromatography (LC)-tandem mass spectrometry (MS/MS) are typically employed for deep bottom-up proteomics, and the state-of-the-art 2D-LC-MS/MS has approached over 8000 protein identifications (IDs) from mammalian cell lines or tissues in 1-3 days of mass spectrometer time. Capillary zone electrophoresis (CZE)-MS/MS has been suggested as an alternative to LC-MS/MS for bottom-up proteomics. CZE-MS/MS and LC-MS/MS are complementary in protein/peptide ID from complex proteome digests because CZE and LC are orthogonal for peptide separation. In addition, the migration time of peptides from CZE-MS can be predicted accurately, which is invaluable for evaluating the confidence of peptide ID from the database search and even guiding the database search. However, the number of protein IDs from complex proteomes using CZE-MS/MS is still much lower than the state of the art using 2D-LC-MS/MS. In this work, for the first time, we established a strong cation exchange (SCX)-reversed phase LC (RPLC)-CZE-MS/MS platform for deep bottom-up proteomics. The platform identified around 8200 protein groups and 65,000 unique peptides from a mouse brain proteome digest in 70 h. The data represents the largest bottom-up proteomics dataset using CZE-MS/MS and provides a valuable resource for further improving the tool for prediction of peptide migration time in CZE. The peak capacity of the orthogonal SCX-RPLC-CZE platform was estimated to be around 7000. SCX-RPLC-CZE-MS/MS produced comparable numbers of protein and peptide IDs with 2D-LC-MS/MS (8200 vs. 8900 protein groups, 65,000 vs. 70,000 unique peptides) from the mouse brain proteome digest using comparable instrument time. This is the first time that CZE-MS/MS showed its capability to approach comparable performance to the state-of-the-art 2D-LC-MS/MS for deep proteomic sequencing. SCX-RPLC-CZE-MS/MS and 2D-LC-MS/MS showed good complementarity in protein and peptide IDs and combining those two methods improved the number of protein group and unique peptide IDs by nearly 10% and over 40%, respectively, compared with 2D-LC-MS/MS alone.