Defining the Sarcomeric Proteoform Landscape in Ischemic Cardiomyopathy by Top-Down Proteomics

Post-translational modifications of vertebrate striated muscle myosin heavy chains

Post-translational modifications (PTMs) play a crucial role in regulating the function of many sarcomeric proteins, including myosin. Myosins comprise a family of motor proteins that play fundamental roles in cell motility in general and muscle contraction in particular. A myosin molecule consists of two myosin heavy chains (MyHCs) and two pairs of myosin light chains (MLCs); two MLCs are associated with the neck region of each MyHC's N-terminal head domain, while the two MyHC C-terminal tails form a coiled-coil that polymerizes with other MyHCs to form the thick filament backbone. Myosin undergoes extensive PTMs, and dysregulation of these PTMs may lead to abnormal muscle function and contribute to the development of myopathies and cardiovascular disorders. Recent studies have uncovered the significance of PTMs in regulating MyHC function and showed how these PTMs may provide additional modulation of contractile processes. Here, we discuss MyHC PTMs that have been biochemically and/or functionally studied in mammals' and rodents' striated muscle. We have identified hotspots or specific regions in three isoforms of myosin (MYH2, MYH6, and MYH7) where the prevalence of PTMs is more frequent and could potentially play a significant role in fine-tuning the activity of these proteins.

Native Top-Down Mass Spectrometry for Characterizing Sarcomeric Proteins Directly from Cardiac Tissue Lysate

Native top-down mass spectrometry (nTDMS) has emerged as a powerful structural biology tool that can localize post-translational modifications (PTMs), explore ligand-binding interactions, and elucidate the three-dimensional structure of proteins and protein complexes in the gas-phase. Fourier-transform ion cyclotron resonance (FTICR) MS offers distinct capabilities for nTDMS, owing to its ultrahigh resolving power, mass accuracy, and robust fragmentation techniques. Previous nTDMS studies using FTICR have mainly been applied to overexpressed recombinant proteins and protein complexes. Here, we report the first nTDMS study that directly analyzes human heart tissue lysate by direct infusion FTICR MS without prior chromatographic separation strategies. We have achieved comprehensive nTDMS characterization of cardiac contractile proteins that play critical roles in heart contraction and relaxation. Specifically, our results reveal structural insights into ventricular myosin light chain 2 (MLC-2v), ventricular myosin light chain 1 (MLC-1v), and alpha-tropomyosin (α-Tpm) in the sarcomere, the basic contractile unit of cardiac muscle. Furthermore, we verified the calcium (Ca2+) binding domain in MLC-2v. In summary, our nTDMS platform extends the application of FTICR MS to directly characterize the structure, PTMs, and metal-binding of endogenous proteins from heart tissue lysate without prior separation methods.

Post-translational modifications of proteins in cardiovascular diseases examined by proteomic approaches

Over 400 different types of post-translational modifications (PTMs) have been reported and over 200 various types of PTMs have been discovered using mass spectrometry (MS)-based proteomics. MS-based proteomics has proven to be a powerful method capable of global PTM mapping with the identification of modified proteins/peptides, the localization of PTM sites and PTM quantitation. PTMs play regulatory roles in protein functions, activities and interactions in various heart related diseases, such as ischemia/reperfusion injury, cardiomyopathy and heart failure. The recognition of PTMs that are specific to cardiovascular pathology and the clarification of the mechanisms underlying these PTMs at molecular levels are crucial for discovery of novel biomarkers and application in a clinical setting. With sensitive MS instrumentation and novel biostatistical methods for precise processing of the data, low-abundance PTMs can be successfully detected and the beneficial or unfavorable effects of specific PTMs on cardiac function can be determined. Moreover, computational proteomic strategies that can predict PTM sites based on MS data have gained an increasing interest and can contribute to characterization of PTM profiles in cardiovascular disorders. More recently, machine learning- and deep learning-based methods have been employed to predict the locations of PTMs and explore PTM crosstalk. In this review article, the types of PTMs are briefly overviewed, approaches for PTM identification/quantitation in MS-based proteomics are discussed and recently published proteomic studies on PTMs associated with cardiovascular diseases are included.

Small-Scale Serial Size Exclusion Chromatography (s3SEC) for High Sensitivity Top-Down Proteomics of Large Proteoforms

Top-down-mass spectrometry (MS)-based proteomics has emerged as a premier technology to examine proteins at the proteoform level, enabling characterization of genetic mutations, alternative splicing, and post-translational modifications. However, significant challenges that remain in top-down proteomics include the analysis of large proteoforms and the sensitivity required to examine proteoforms from minimal amounts of sample. To address these challenges, we have developed a new method termed "small-scale serial Size Exclusion Chromatography" (s3SEC), which incorporates a small-scale protein extraction (1 mg of tissue) and serial SEC without postfractionation sample handling, coupled with online high sensitivity capillary reversed-phase liquid chromatography tandem MS (RPLC-MS/MS) for analysis of large proteoforms. The s3SEC-RPLC-MS/MS method significantly enhanced the sensitivity and reduced the proteome complexity across the fractions, enabling the detection of high MW proteoforms previously undetected in one-dimensional (1D)-RPLC analysis. Importantly, we observed a drastic improvement in the signal intensity of high MW proteoforms in early fractions when using the s3SEC-RPLC method. Moreover, we demonstrate that this s3SEC-RPLC-MS/MS method also allows the analysis of lower MW proteoforms in subsequent fractions without significant alteration in proteoform abundance and equivalent or improved fragmentation efficiency to that of the 1D-RPLC approach. Although this study focuses on the use of cardiac tissue, the s3SEC-RPLC-MS/MS method could be broadly applicable to other systems with limited sample inputs.

The 2023 Report on the Proteome from the HUPO Human Proteome Project

Since 2010, the Human Proteome Project (HPP), the flagship initiative of the Human Proteome Organization (HUPO), has pursued two goals: (1) to credibly identify the protein parts list and (2) to make proteomics an integral part of multiomics studies of human health and disease. The HPP relies on international collaboration, data sharing, standardized reanalysis of MS data sets by PeptideAtlas and MassIVE-KB using HPP Guidelines for quality assurance, integration and curation of MS and non-MS protein data by neXtProt, plus extensive use of antibody profiling carried out by the Human Protein Atlas. According to the neXtProt release 2023-04-18, protein expression has now been credibly detected (PE1) for 18,397 of the 19,778 neXtProt predicted proteins coded in the human genome (93%). Of these PE1 proteins, 17,453 were detected with mass spectrometry (MS) in accordance with HPP Guidelines and 944 by a variety of non-MS methods. The number of neXtProt PE2, PE3, and PE4 missing proteins now stands at 1381. Achieving the unambiguous identification of 93% of predicted proteins encoded from across all chromosomes represents remarkable experimental progress on the Human Proteome parts list. Meanwhile, there are several categories of predicted proteins that have proved resistant to detection regardless of protein-based methods used. Additionally there are some PE1-4 proteins that probably should be reclassified to PE5, specifically 21 LINC entries and ∼30 HERV entries; these are being addressed in the present year. Applying proteomics in a wide array of biological and clinical studies ensures integration with other omics platforms as reported by the Biology and Disease-driven HPP teams and the antibody and pathology resource pillars. Current progress has positioned the HPP to transition to its Grand Challenge Project focused on determining the primary function(s) of every protein itself and in networks and pathways within the context of human health and disease.

Improved characterization of trastuzumab deruxtecan with PTCR and internal fragments implemented in middle-down MS workflows

Antibody-drug conjugates (ADCs) are highly complex proteins mainly due to the structural microvariability of the mAb, along with the additional heterogeneity afforded by the bioconjugation process. Top-down (TD) and middle-down (MD) strategies allow the straightforward fragmentation of proteins to elucidate the conjugated amino acid residues. Nevertheless, these spectra are very crowded with multiple overlapping and unassigned ion fragments. Here we report on the use of dedicated software (ClipsMS) and application of proton transfer charge reduction (PTCR), to respectively expand the fragment ion search space to internal fragments and improve the separation of overlapping fragment ions for a more comprehensive characterization of a recently approved ADC, trastuzumab deruxtecan (T-DXd). Subunit fragmentation allowed between 70 and 90% of sequence coverage to be obtained. Upon addition of internal fragment assignment, the three subunits were fully sequenced, although internal fragments did not contribute significantly to the localization of the payloads. Finally, the use of PTCR after subunit fragmentation provided a moderate sequence coverage increase between 2 and 13%. The reaction efficiently decluttered the fragmentation spectra allowing increasing the number of fragment ions characteristic of the conjugation site by 1.5- to 2.5-fold. Altogether, these results show the interest in the implementation of internal fragment ion searches and more particularly the use of PTCR reactions to increase the number of signature ions to elucidate the conjugation sites and enhance the overall sequence coverage of ADCs, making this approach particularly appealing for its implementation in R&D laboratories.

Top-Down Proteomics and the Challenges of True Proteoform Characterization

Top-down proteomics (TDP) aims to identify and profile intact protein forms (proteoforms) extracted from biological samples. True proteoform characterization requires that both the base protein sequence be defined and any mass shifts identified, ideally localizing their positions within the protein sequence. Being able to fully elucidate proteoform profiles lends insight into characterizing proteoform-unique roles, and is a crucial aspect of defining protein structure-function relationships and the specific roles of different (combinations of) protein modifications. However, defining and pinpointing protein post-translational modifications (PTMs) on intact proteins remains a challenge. Characterization of (heavily) modified proteins (>∼30 kDa) remains problematic, especially when they exist in a population of similarly modified, or kindred, proteoforms. This issue is compounded as the number of modifications increases, and thus the number of theoretical combinations. Here, we present our perspective on the challenges of analyzing kindred proteoform populations, focusing on annotation of protein modifications on an "average" protein. Furthermore, we discuss the technical requirements to obtain high quality fragmentation spectral data to robustly define site-specific PTMs, and the fact that this is tempered by the time requirements necessary to separate proteoforms in advance of mass spectrometry analysis.

Multi-omic analyses and network biology in cardiovascular disease

Heart disease remains a leading cause of death in North America and worldwide. Despite advances in therapies, the chronic nature of cardiovascular diseases ultimately results in frequent hospitalizations and steady rates of mortality. Systems biology approaches have provided a new frontier toward unraveling the underlying mechanisms of cell, tissue, and organ dysfunction in disease. Mapping the complex networks of molecular functions across the genome, transcriptome, proteome, and metabolome has enormous potential to advance our understanding of cardiovascular disease, discover new disease biomarkers, and develop novel therapies. Computational workflows to interpret these data-intensive analyses as well as integration between different levels of interrogation remain important challenges in the advancement and application of systems biology-based analyses in cardiovascular research. This review will focus on summarizing the recent developments in network biology-level profiling in the heart, with particular emphasis on modeling of human heart failure. We will provide new perspectives on integration between different levels of large "omics" datasets, including integration of gene regulatory networks, protein-protein interactions, signaling networks, and metabolic networks in the heart.

Comprehensive Characterization of Endogenous Phospholamban Proteoforms Enabled by Photocleavable Surfactant and Top-down Proteomics

Top-down mass spectrometry (MS)-based proteomics has become a powerful tool for analyzing intact proteins and their associated post-translational modifications (PTMs). In particular, membrane proteins play critical roles in cellular functions and represent the largest class of drug targets. However, the top-down MS characterization of endogenous membrane proteins remains challenging, mainly due to their intrinsic hydrophobicity and low abundance. Phospholamban (PLN) is a regulatory membrane protein located in the sarcoplasmic reticulum and is essential for regulating cardiac muscle contraction. PLN has diverse combinatorial PTMs, and their dynamic regulation has significant influence on cardiac contractility and disease. Herein, we have developed a rapid and robust top-down proteomics method enabled by a photocleavable anionic surfactant, Azo, for the extraction and comprehensive characterization of endogenous PLN from cardiac tissue. We employed a two-pronged top-down MS approach using an online reversed-phase liquid chromatography tandem MS method on a quadrupole time-of-flight MS and a direct infusion method via an ultrahigh-resolution Fourier-transform ion cyclotron resonance MS. We have comprehensively characterized the sequence and combinatorial PTMs of endogenous human cardiac PLN. We have shown the site-specific localization of phosphorylation to Ser16 and Thr17 by MS/MS for the first time and the localization of S-palmitoylation to Cys36. Moreover, we applied our method to characterize PLN in disease and reported the significant reduction of PLN phosphorylation in human failing hearts with ischemic cardiomyopathy. Taken together, we have developed a streamlined top-down targeted proteomics method for comprehensive characterization of combinatorial PTMs in PLN toward better understanding the role of PLN in cardiac contractility.

Top-down proteomics of myosin light chain isoforms define chamber-specific expression in the human heart

Myosin functions as the "molecular motor" of the sarcomere and generates the contractile force necessary for cardiac muscle contraction. Myosin light chains 1 and 2 (MLC-1 and -2) play important functional roles in regulating the structure of the hexameric myosin molecule. Each of these light chains has an 'atrial' and 'ventricular' isoform, so called because they are believed to exhibit chamber-restricted expression in the heart. However, recently the chamber-specific expression of MLC isoforms in the human heart has been questioned. Herein, we analyzed the expression of MLC-1 and -2 atrial and ventricular isoforms in each of the four cardiac chambers in adult non-failing donor hearts using top-down mass spectrometry (MS)-based proteomics. Strikingly, we detected an isoform thought to be ventricular, MLC-2v (gene: MYL2), in the atria and confirmed the protein sequence using tandem MS (MS/MS). For the first time, a putative deamidation post-translation modification (PTM) located on MLC-2v in atrial tissue was localized to amino acid N13. MLC-1v (MYL3) and MLC-2a (MYL7) were the only MLC isoforms exhibiting chamber-restricted expression patterns across all donor hearts. Importantly, our results unambiguously show that MLC-1v, not MLC-2v, is ventricle-specific in adult human hearts. Moreover, we found elevated MLC-2 phosphorylation in male hearts compared to female hearts across each cardiac chamber. Overall, top-down proteomics allowed an unbiased analysis of MLC isoform expression throughout the human heart, uncovering previously unexpected isoform expression patterns and PTMs.

Recent progress in quantitative phosphoproteomics

INTRODUCTION

Protein phosphorylation is a critical post-translational modification involved in the regulation of numerous cellular processes from signal transduction to modulation of enzyme activities. Knowledge of dynamic changes of phosphorylation levels during biological processes, under various treatments or between healthy and disease models is fundamental for understanding the role of each phosphorylation event. Thereby, LC-MS/MS based technologies in combination with quantitative proteomics strategies evolved as a powerful strategy to investigate the function of individual protein phosphorylation events.

AREAS COVERED

State-of-the-art labeling techniques including stable isotope and isobaric labeling provide precise and accurate quantification of phosphorylation events. Here, we review the strengths and limitations of recent quantification methods and provide examples based on current studies, how quantitative phosphoproteomics can be further optimized for enhanced analytic depth, dynamic range, site localization, and data integrity. Specifically, reducing the input material demands is key to a broader implementation of quantitative phosphoproteomics, not least for clinical samples.

EXPERT OPINION

Despite quantitative phosphoproteomics is one of the most thriving fields in the proteomics world, many challenges still have to be overcome to facilitate even deeper and more comprehensive analyses as required in the current research, especially at single cell levels and in clinical diagnostics.