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, some recent advances are outlined and current challenges and future directions for the field are discussed.

Successful chemotherapeutic intervention for management of lung cancer requires an efficient drug delivery system. Gold nanoparticles (GNPs) can incorporate various therapeutics; however, GNPs have limitations as drug carriers. Nano-sized cellular vesicles like exosomes (Exo) can ferry GNP-therapeutic complexes without causing any particle aggregation or immune response. In the present study, we describe the development and testing of a novel Exo-GNP-based therapeutic delivery system -‘nanosomes’- for lung cancer therapy. This system consists of GNPs conjugated to anticancer drug doxorubicin (Dox) by a pH-cleavable bond that is physically loaded onto the exosomes (Exo-GNP-Dox). The therapeutic efficacy of Dox in nanosomes was assessed in H1299 and A549 non-small cell lung cancer cells, normal MRC9 lung fibroblasts, and Dox-sensitive human coronary artery smooth muscle cells (HCASM). The enhanced rate of drug release under acidic conditions, successful uptake of the nanosomes by the recipient cells and the cell viability assays demonstrated that nanosomes exhibit preferential cytotoxicity towards cancer cells and have minimal activity on non-cancerous cells. Finally, the underlying mechanism of cytotoxicity involved ROS-mediated DNA damage. Results from this study mark the establishment of an amenable drug delivery vehicle and highlight the advantages of a natural drug carrier that demonstrates reduced cellular toxicity and efficient delivery of therapeutics to cancer cells.

Application of quantitative methods to top-down mass spectrometry has illustrated the importance of proteoforms and proteoform abundance in biological systems.

De novo sequencing of proteins and peptides is one of the most important problems in mass spectrometry-driven proteomics. A variety of methods have been developed to accomplish this task from a set of bottom-up tandem (MS/MS) mass spectra. However, a more recently emerged top-down technology, now gaining more and more popularity, opens new perspectives for protein analysis and characterization, implying a need for efficient algorithms to process this kind of MS/MS data. Here, we describe a method that allows for the retrieval, from a set of top-down MS/MS spectra, of long and accurate sequence fragments of the proteins contained in the sample. To this end, we outline a strategy for generating high-quality sequence tags from top-down spectra, and introduce the concept of a T-Bruijn graph by adapting to the case of tags the notion of an A-Bruijn graph widely used in genomics. The output of the proposed approach represents the set of amino acid strings spelled out by optimal paths in the connected components of a T-Bruijn graph. We illustrate its performance on top-down data sets acquired from carbonic anhydrase 2 (CAH2) and the Fab region of alemtuzumab.

Advancements in chromatographic separation are critical to in-depth top-down proteomics of complex intact protein samples. Reversed-phase liquid chromatography is the most prevalent technique for top-down proteomics. However, in cases of high complexities and large dynamic ranges, 1D-RPLC may not provide sufficient coverage of the proteome. To address these challenges, orthogonal separation techniques are often combined to improve the coverage and the dynamic range of detection. In this study, a “salt-free” high-pH RPLC was evaluated as an orthogonal dimension of separation to conventional low-pH RPLC with top-down MS. The RPLC separations with low-pH conditions (pH=2) and high-pH conditions (pH=10) were compared to confirm the good orthogonality between high-pH and low-pH RPLC’s. The offline 2D RPLC-RPLC-MS/MS analyses of intact E. coli samples were evaluated for the improvement of intact protein identifications as well as intact proteoform characterizations. Compared to the 163 proteins and 328 proteoforms identified using a 1D RPLC-MS approach, 365 proteins and 886 proteoforms were identified using the 2D RPLC-RPLC top-down MS approach. Our results demonstrate that the 2D RPLC-RPLC top-down approach holds great potential for in-depth top-down proteomics studies by utilizing the high resolving power of RPLC separations and by using mass spectrometry compatible buffers for easy sample handling for online MS analysis.

Glycosylation is one of the most prominent and extensively studied protein post-translational modifications. However, traditional proteomic studies at the peptide level (bottom-up) rarely characterize intact glycopeptides (glycosylated peptides without removing glycans), so no glycoprotein heterogeneity information is retained. Intact glycopeptide characterization, on the other hand, provides opportunities to simultaneously elucidate the glycan structure and the glycosylation site needed to reveal the actual biological function of protein glycosylation. Recently, significant improvements have been made in the characterization of intact glycopeptides, ranging from enrichment and separation, mass spectroscopy (MS) detection, to bioinformatics analysis. In this review, we recapitulated currently available intact glycopeptide characterization methods with respect to their advantages and limitations as well as their potential applications.

Labeling approaches using isobaric chemical tags (e.g., isobaric tagging for relative and absolute quantification, iTRAQ and tandem mass tag, TMT) have been widely applied for the quantification of peptides and proteins in bottom-up MS. However, until recently, successful applications of these approaches to top-down proteomics have been limited because proteins tend to precipitate and “crash” out of solution during TMT labeling of complex samples making the quantification of such samples difficult. In this study, we report a top-down TMT MS platform for confidently identifying and quantifying low molecular weight intact proteoforms in complex biological samples. To reduce the sample complexity and remove large proteins from complex samples, we developed a filter-SEC technique that combines a molecular weight cutoff filtration step with high-performance size exclusion chromatography (SEC) separation. No protein precipitation was observed in filtered samples under the intact protein-level TMT labeling conditions. The proposed top-down TMT MS platform enables high-throughput analysis of intact proteoforms, allowing for the identification and quantification of hundreds of intact proteoforms from Escherichia coli cell lysates. To our knowledge, this represents the first high-throughput TMT labeling-based, quantitative, top-down MS analysis suitable for complex biological samples.

No abstract