RPLC-RPLC-MS/MS for Proteoform Identification

The implication of non-AUG-initiated N-terminally extended proteoforms in cancer

Dysregulated translation is a hallmark of cancer, and recent genome-wide studies in tumour cells have uncovered widespread translation of non-canonical reading frames that often initiate at non-AUG codons. If an upstream non-canonical start site is located within a frame with an annotated coding sequence (CDS), such translation events can lead to the production of proteoforms with altered N-termini (PANTs). Certain examples of PANTs from oncogenes (e.g. c-MYC) and tumour suppressors (e.g. PTEN) have been previously linked to cancer. We have performed a systematic computational analysis on recently identified non-AUG initiation-derived N-terminal extensions of cancer-associated proteins, and we discuss how these extended proteoforms may acquire new oncogenic properties. We identified a loss of stability for the N-terminally extended proteoforms of oncogenes TCF-4 and SOX2. Furthermore, we discovered likely functional short linear motifs within the N-terminal extensions of oncogenes and tumour suppressors (SOX2, SUFU, SFPQ, TOP1 and SPEN/SHARP) that could provide an explanation for previously described functionalities or interactions of the proteins. In all, we identify novel cases where PANTs likely show different localization, functions, partner binding or turnover rates compared to the annotated proteoforms. Therefore, we propose that alterations in the stringency of translation initiation, often seen under conditions of cellular stress, may result in reprogramming of translation to generate novel PANTs that influence cancer progression.

Multidimensional Separations in Top-Down Proteomics

Top-down proteomics (TDP) identifies, quantifies, and characterizes proteins at the intact proteoform level in complex biological samples to understand proteoform function and cellular mechanisms. However, analyzing complex biological samples using TDP is still challenging due to high sample complexity and wide dynamic range. High-resolution separation methods are often applied prior to mass spectrometry (MS) analysis to decrease sample complexity and increase proteomics throughput. These separation methods, however, may not be efficient enough to characterize low abundance intact proteins in complex samples. As such, multidimensional separation techniques (combination of two or more separation methods with high orthogonality) have been developed and applied that demonstrate improved separation resolution and more comprehensive identification in TDP. A suite of multidimensional separation methods that couple various types of liquid chromatography (LC), capillary electrophoresis (CE), and/or gel electrophoresis-based separation approaches have been developed and applied in TDP to analyze complex biological samples. Here, we reviewed multidimensional separation strategies employed for TDP, summarized current applications, and discussed the gaps that may be addressed in the future.

Optimization of Higher-Energy Collisional Dissociation Fragmentation Energy for Intact Protein-Level Tandem Mass Tag Labeling

Isobaric chemical tag labeling (e.g., TMT) is a commonly used approach in quantitative proteomics, and quantification is enabled through detection of low-mass reporter ions generated after MS2 fragmentation. Recently, we have introduced and optimized an intact protein-level TMT labeling platform that demonstrated >90% labeling efficiency in complex samples with top-down proteomics. Higher-energy collisional dissociation (HCD) is commonly utilized for isobaric tag-labeled peptide fragmentation because it produces accurate reporter ion intensities and avoids loss of low mass ions. HCD energies have been optimized for isobaric tag labeled-peptides but have not been systematically evaluated for isobaric tag-labeled intact proteins. In this study, we report a systematic evaluation of normalized HCD fragmentation energies (NCEs) on TMT-labeled HeLa cell lysate using top-down proteomics. Our results suggested that reporter ions often result in higher ion intensities at higher NCEs. Optimal fragmentation of intact proteins for identification, however, required relatively lower NCE. We further demonstrated that a stepped NCE scheme with energies from 30% to 50% resulted in optimal quantification and identification of TMT-labeled HeLa proteins. These parameters resulted in an average reporter ion intensity of ∼4E4 and average proteoform spectrum matches (PrSMs) of >1000 per RPLC-MS/MS run with a 1% false discovery rate (FDR) cutoff.

A benchmarking protocol for intact protein-level Tandem Mass Tag (TMT) labeling for quantitative top-down proteomics

Isobaric chemical tag labeling for quantification of intact proteins in complex samples is limited due to the tendency of intact proteins precipitate under labeling conditions and increased sample complexity as a result of side products (i.e., incomplete labeling or labeling of unintended residues). To reduce precipitation under labeling conditions, we developed a technique to remove large proteoforms that allowed for the labeling and characterization of small proteoforms (<35 kDa) using top-down proteomics. We also systematically optimized protein-level Tandem Mass Tag (TMT) labeling conditions to obtain optimal labeling parameters for complex samples. Here, we present a benchmarking protocol for protein-level TMT labeling for quantitative top-down proteomics, including complex intact protein sample preparation, protein-level TMT labeling, top-down LC/MS analysis, and TMT reporter ion quantification.•

An optimized protocol for protein-level TMT labeling in complex sample.

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Limits production of incorrectly labeled side products for minimization of spectral complexity.

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A guideline for isobaric chemical tag quantification in top-down proteomics.