Expanding Proteome Coverage with CHarge Ordered Parallel Ion aNalysis (CHOPIN) Combined with Broad Specificity Proteolysis

Abstract

The "deep" proteome has been accessible by mass spectrometry for some time. However, the number of proteins identified in cells of the same type has plateaued at ∼8000-10 000 without ID transfer from reference proteomes/data. Moreover, limited sequence coverage hampers the discrimination of protein isoforms when using trypsin as standard protease. Multienzyme approaches appear to improve sequence coverage and subsequent isoform discrimination. Here we expanded proteome and protein sequence coverage in MCF-7 breast cancer cells to an as yet unmatched depth by employing a workflow that addresses current limitations in deep proteome analysis in multiple stages: We used (i) gel-aided sample preparation (GASP) and combined trypsin/elastase digests to increase peptide orthogonality, (ii) concatenated high-pH prefractionation, and (iii) CHarge Ordered Parallel Ion aNalysis (CHOPIN), available on an Orbitrap Fusion (Lumos) mass spectrometer, to achieve 57% median protein sequence coverage in 13 728 protein groups (8949 Unigene IDs) in a single cell line. CHOPIN allows the use of both detectors in the Orbitrap on predefined precursor types that optimizes parallel ion processing, leading to the identification of a total of 179 549 unique peptides covering the deep proteome in unprecedented detail.

Keywords: LC−MS/MS; deep proteome; isoform profiling; protein sequence coverage; sequence coverage.

Figure 1

Comprehensive cell proteome coverage by prefractionation and CHOPIN MS analysis workflow. (A) Mass spectrometry acquisition methods demonstrating the dynamic segmentation of analytical channels for MS1 FT (Orbitrap), Q (Quadrupole), and MS2 LTQ (Linear Ion Trap) that were designed for the Universal (upper panel) and CHarge Ordered Parallel Ion aNalysis (CHOPIN) method (lower panel). The Universal Method makes use of the parallel acquisition of MS1 scan in the Orbitrap, while peptide fragments are scanned in the LTQ, ordered by decreasing precursor intensity. Additional parallelization is achieved by concurrent MS2 scans and isolation of the following precursor. Precursor ion accumulation is allowed to proceed for up to 250 ms if no previously unselected precursor is found. CHOPIN adds another level of parallelization by triaging intense and highly charged ions to be analyzed by an Orbitrap MS2 scan, while low abundant precursor ions are prioritized for the more sensitive MS2 scan in the linear ion trap. CHOPIN and the data analysis is further described in Supporting Information. (B) Methodological workflow for the analysis of the MCF-7 breast cancer cell line deep proteome. MCF-7 cell extracts were digested with either trypsin or elastase, and peptide mixtures were separated by high-pH reversed-phase (RP) HPLC to collect 30 fractions that were pooled in a concatenated fashion to 15 fractions. Also, tryptic and elastase digest was mixed and prefractionated as above (“Post Digest Mix”, PDM), followed by concatenation or distinct fraction analysis. Each fraction was subsequently analyzed by LC–MS/MS using both the Universal and CHOPIN acquisition methods. Detailed results for each individual experiment are shown in the Supporting Information. (Orbitrap Fusion Lumos photo by RF).

Figure 2

CHOPIN enhances MS/MS interpretation rates. (A) The density plot shows the number of identifications over precursor mass and peptide score (−10lgP) to demonstrate the gain of spectra quality for peptides by HCD/FT detection (Chopin HCD/FT) in a tryptic digest. The Chopin CID/IT spectra show a similar score distribution compared to peptides identified with the Universal Method. However, the combined data of the CHOPIN result show a clear improvement in the number of identified peptides and confidence. Density plots for the Elastase digest and the Post Digest Mix are shown in Figure S2. (B) Improvements on the peptide level are carried through to ID confidence on the protein group level, especially in the trypsin and Post Digest Mix samples. Because of the inclusion of singly charged precursors, the benefit in the elastase-digested samples is limited to high-confidence identifications.

Figure 3

Improved global protein sequence coverage using the CHOPIN workflow. (A) Protein sequence coverages observed with different analytical strategies illustrate the benefit of the methods used to improve protein sequence coverage and protein grouping as the number of identified protein groups could be increased significantly. The median protein sequence coverage of 13 728 protein groups (leading protein) was 57%, with 7935 protein groups being identified with more than 50% coverage. (B) Plotting sequence coverage of the combined data (leading protein per group) over molecular protein mass shows a distribution plume similar to a tornado (“Tornado plot”). Interestingly, the density of data points is relatively uniform across protein mass while showing highest density at 70–80% coverage, indicating a similar abundance for the majority of the proteome, independent of molecular weight. The right panel shows the archived protein sequence coverage in the different digests. Trypsin digests alone cannot generate sequence comprehensive data, while elastase digests can cover proteins better. However, the mixture of tryptic and elastase digest (“PDM”) appears to retain the benefits of both proteases and specifically benefits from the improved duty cycle in CHOPIN due to its extreme complexity (compare Table 1). (C) 6323 proteins and corresponding iBAQ values could be matched to previously published deep proteome data in MCF-7 cells by Geiger et al. The median sequence coverage for the same set proteins could be improved from 43 to 61%.

Figure 4

Comprehensive elastase cleavage profile analysis reveals preference toward small aliphatic amino acids. This study demonstrates the feasibility of using elastase as orthogonal protease to trypsin with the potential to replace the classical, narrow specificity multienzyme approach. We detected similar specificity as Rietschel et al. based now on 129 677 observed cleavages. 86.77% of cleavages were specific to A, V, I, T, L, and S as P1. However, additional 10.3% of cleavages were detected on R, G, M, and K as P1, indicating a broad but high cleavage specificity of elastase.