Identification and Quantification of Proteoforms by Mass Spectrometry

A proteoform is a defined form of a protein derived from a given gene with a specific amino acid sequence and localized post-translational modifications. In top-down proteomic analyses, proteoforms are identified and quantified through mass spectrometric analysis of intact proteins. Recent technological developments have enabled comprehensive proteoform analyses in complex samples, and an increasing number of laboratories are adopting top-down proteomic workflows. In this review, we outline some recent advances and discuss current challenges and future directions for the field

Bridged Hybrid Monolithic Column Coupled to High-Resolution Mass Spectrometry for Top-Down Proteomics

Top-down mass spectrometry (MS)-based proteomics has become a powerful tool for comprehensive characterization of intact proteins. However, because of the high complexity of the proteome, highly effective separation of intact proteins from complex mixtures prior to MS analysis remains challenging. Monolithic columns have shown great promise for intact protein separation due to their high permeability, low backpressure, and fast mass transfer. Herein, for the first time, we developed bridged hybrid bis(triethoxysilyl)ethylene (BTSEY) monolith with C8 functional groups (C8@BTSEY) for highly effective protein separation and coupled it to high-resolution MS for identification of intact proteins from complex protein mixtures. We have optimized mobile phase conditions of our monolith -based reverse-phase chromatography (RPC) for online liquid chromatography (LC)-MS analysis and evaluated separation reproducibility of the C8pBTSEY column. We further assessed the chromatographic performance of this column by separating a complex protein mixture extracted from swine heart tissue. Using our monolithic column (i.d. 100 mu m X 35 cm), we separated over 300 proteoforms (up to 104 kDa) from 360 ng of protein mixture in an 80 min one-dimensional (1D) LC run. The highly effective separation and recovery of intact proteins from this monolithic column allowed unambiguous identification of similar to 100 proteoforms including a large protein, alpha actinin2 (103.77 kDa), by online ID LC-MS/MS-analysis for the first time. As demonstrated, this C8pBTSEY column is reproducible and effective in separation of intact proteins, which shows high promise for top-down proteomics

Top-Down Proteomics of Large Proteins up to 223 kDa Enabled by Serial Size Exclusion Chromatography Strategy

Mass spectrometry (MS)-based top-down proteomics is a powerful method for the comprehensive analysis of proteoforms that arise from genetic variations and post-translational modifications (PTMs). However, top-down MS analysis of high molecular weight (MW) proteins remains challenging mainly due to the exponential decay of signal-to-noise ratio with increasing MW. Size exclusion chromatography (SEC) is a favored method for size-based separation of biomacromolecules but typically suffers from low resolution. Herein, we developed a serial size exclusion chromatography (sSEC) strategy to enable high-resolution size-based fractionation of intact proteins (10–223 kDa) from complex protein mixtures. The sSEC fractions could be further separated by reverse phase chromatography (RPC) coupled online with high-resolution MS. We have shown that two-dimensional (2D) sSEC-RPC allowed for the identification of 4044 more unique proteoforms and a 15-fold increase in the detection of proteins above 60 kDa, compared to one-dimensional (1D) RPC. Notably, effective sSEC-RPC separation of proteins significantly enhanced the detection of high MW proteins up to 223 kDa and also revealed low abundance proteoforms that are post-translationally modified. This sSEC method is MS-friendly, robust, and reproducible and, thus, can be applied to both high-efficiency protein purification and large-scale proteomics analysis of cell or tissue lysate for enhanced proteome coverage, particularly for low abundance and high MW proteoforms

Top-Down Proteomics of Large Proteins up to 223 kDa Enabled by Serial Size Exclusion Chromatography Strategy

Mass spectrometry (MS)-based top-down proteomics is a powerful method for the comprehensive analysis of proteoforms that arise from genetic variations and post-translational modifications (PTMs). However, top-down MS analysis of high molecular weight (MW) proteins remains challenging mainly due to the exponential decay of signal-to-noise ratio with increasing MW. Size exclusion chromatography (SEC) is a favored method for size-based separation of biomacromolecules but typically suffers from low resolution. Herein, we developed a serial size exclusion chromatography (sSEC) strategy to enable high-resolution size-based fractionation of intact proteins (10–223 kDa) from complex protein mixtures. The sSEC fractions could be further separated by reverse phase chromatography (RPC) coupled online with high-resolution MS. We have shown that two-dimensional (2D) sSEC-RPC allowed for the identification of 4044 more unique proteoforms and a 15-fold increase in the detection of proteins above 60 kDa, compared to one-dimensional (1D) RPC. Notably, effective sSEC-RPC separation of proteins significantly enhanced the detection of high MW proteins up to 223 kDa and also revealed low abundance proteoforms that are post-translationally modified. This sSEC method is MS-friendly, robust, and reproducible and, thus, can be applied to both high-efficiency protein purification and large-scale proteomics analysis of cell or tissue lysate for enhanced proteome coverage, particularly for low abundance and high MW proteoforms

Top-Down Proteomics of Large Proteins up to 223 kDa Enabled by Serial Size Exclusion Chromatography Strategy

Mass spectrometry (MS)-based top-down proteomics is a powerful method for the comprehensive analysis of proteoforms that arise from genetic variations and post-translational modifications (PTMs). However, top-down MS analysis of high molecular weight (MW) proteins remains challenging mainly due to the exponential decay of signal-to-noise ratio with increasing MW. Size exclusion chromatography (SEC) is a favored method for size-based separation of biomacromolecules but typically suffers from low resolution. Herein, we developed a serial size exclusion chromatography (sSEC) strategy to enable high-resolution size-based fractionation of intact proteins (10–223 kDa) from complex protein mixtures. The sSEC fractions could be further separated by reverse phase chromatography (RPC) coupled online with high-resolution MS. We have shown that two-dimensional (2D) sSEC-RPC allowed for the identification of 4044 more unique proteoforms and a 15-fold increase in the detection of proteins above 60 kDa, compared to one-dimensional (1D) RPC. Notably, effective sSEC-RPC separation of proteins significantly enhanced the detection of high MW proteins up to 223 kDa and also revealed low abundance proteoforms that are post-translationally modified. This sSEC method is MS-friendly, robust, and reproducible and, thus, can be applied to both high-efficiency protein purification and large-scale proteomics analysis of cell or tissue lysate for enhanced proteome coverage, particularly for low abundance and high MW proteoforms

A five-level classification system for proteoform identifications

International audienceTo the editorThe term proteoform, introduced in Nature Methods in 2013 (ref. 1), has rapidly gained acceptance in the proteomics community. The challenge and importance of comprehensively identifying proteoforms in complex samples has been recognized, and reports have begun to appear of new platforms towards that end2,3,4,5. However, one interesting central ambiguity has emerged, namely determining precisely what is meant by a ‘proteoform identification’. At present, the only practical approaches for establishing the exact primary structure of a proteoform employ mass spectrometry (MS), and a wide range of MS results claim proteoform identifications6. This seemingly small matter has significant impact, as the ambiguity in what is meant by an ‘identification’ makes it difficult to compare results from different laboratories and approaches. This situation hinders the ability of the community to evaluate technological progress and to efficiently expand biological knowledge