Top-Down Proteomics and the Challenges of True Proteoform Characterization

Exploring snake venoms beyond the primary sequence: From proteoforms to protein-protein interactions

Snakebite envenomation has been a long-standing global issue that is difficult to treat, largely owing to the flawed nature of current immunoglobulin-based antivenom therapy and the complexity of snake venoms as sophisticated mixtures of bioactive proteins and peptides. Comprehensive characterisation of venom compositions is essential to better understanding snake venom toxicity and inform effective and rationally designed antivenoms. Additionally, a greater understanding of snake venom composition will likely unearth novel biologically active proteins and peptides that have promising therapeutic or biotechnological applications. While a bottom-up proteomic workflow has been the main approach for cataloguing snake venom compositions at the toxin family level, it is unable to capture snake venom heterogeneity in the form of protein isoforms and higher-order protein interactions that are important in driving venom toxicity but remain underexplored. This review aims to highlight the importance of understanding snake venom heterogeneity beyond the primary sequence, in the form of post-translational modifications that give rise to different proteoforms and the myriad of higher-order protein complexes in snake venoms. We focus on current top-down proteomic workflows to identify snake venom proteoforms and further discuss alternative or novel separation, instrumentation, and data processing strategies that may improve proteoform identification. The current higher-order structural characterisation techniques implemented for snake venom proteins are also discussed; we emphasise the need for complementary and higher resolution structural bioanalytical techniques such as mass spectrometry-based approaches, X-ray crystallography and cryogenic electron microscopy, to elucidate poorly characterised tertiary and quaternary protein structures. We envisage that the expansion of the snake venom characterisation "toolbox" with top-down proteomics and high-resolution protein structure determination techniques will be pivotal in advancing structural understanding of snake venoms towards the development of improved therapeutic and biotechnology applications.

I'm Walking into Spiderwebs: Making Sense of Protein-Protein Interaction Data

Protein-protein interactions (PPIs) are at the heart of the molecular landscape permeating life. Proteomics studies can explore this protein interaction landscape using mass spectrometry (MS). Thanks to their high sensitivity, mass spectrometers can easily identify thousands of proteins within a single sample, but that same sensitivity generates tangled spiderwebs of data that hide biologically relevant findings. So, what does a researcher do when she finds herself walking into spiderwebs? In a field focused on discovery, MS data require rigor in their analysis, experimental validation, or a combination of both. In this Review, we provide a brief primer on MS-based experimental methods to identify PPIs. We discuss approaches to analyze the resulting data and remove the proteomic background. We consider the advantages between comprehensive and targeted studies. We also discuss how scoring might be improved through AI-based protein structure information. Women have been essential to the development of proteomics, so we will specifically highlight work by women that has made this field thrive in recent years.

Filling the gaps in peptide maps with a platform assay for top-down characterization of purified protein samples

Liquid chromatography-mass spectrometry (LC-MS) intact mass analysis and LC-MS/MS peptide mapping are decisional assays for developing biological drugs and other commercial protein products. Certain PTM types, such as truncation and oxidation, increase the difficulty of precise proteoform characterization owing to inherent limitations in peptide and intact protein analyses. Top-down MS (TDMS) can resolve this ambiguity via fragmentation of specific proteoforms. We leveraged the strengths of flow-programmed (fp) denaturing online buffer exchange (dOBE) chromatography, including robust automation, relatively high ESI sensitivity, and long MS/MS window time, to support a TDMS platform for industrial protein characterization. We tested data-dependent (DDA) and targeted strategies using 14 different MS/MS scan types featuring combinations of collisional- and electron-based fragmentation as well as proton transfer charge reduction. This large, focused dataset was processed using a new software platform, named TDAcquireX, that improves proteoform characterization through TDMS data aggregation. A DDA-based workflow provided objective identification of αLac truncation proteoforms with a two-termini clipping search. A targeted TDMS workflow facilitated the characterization of αLac oxidation positional isomers. This strategy relied on using sliding window-based fragment ion deconvolution to generate composite proteoform spectral match (cPrSM) results amenable to fragment noise filtering, which is a fundamental enhancement relevant to TDMS applications generally.

The path forward for protein footprinting, covalent labeling, and mass spectrometry-based protein conformational analyses

Mass spectrometry-based approaches to assess protein conformation have become widely utilized due to their sensitivity, low sample requirements, and broad applicability to proteins regardless of size and environment. Their wide applicability and sensitivity also make these techniques suitable for the analysis of complex mixtures of proteins, and thus, they have been applied at the cell and even the simple organism levels. These works are impressive, but they predominately employ "bottom-up" workflows and require proteolytic digestion prior to analysis. Once digested, it is not possible to distinguish the proteoform from which any single peptide is derived and therefore, one cannot associate distal-in primary structure-concurrent post-translational modifications (PTMs) or covalent labels, as they would be found on separate peptides. Thus, analyses via bottom-up proteomics report the average PTM status and higher-order structure (HOS) of all existing proteoforms. Second, these works predominately employ promiscuous reagents to probe protein HOS. While this does lead to improved conformational resolution, the formation of many products can divide the signal associated with low-copy number proteins below signal-to-noise thresholds and complicate the bioinformatic analysis of these already challenging systems. In this perspective, I further detail these limitations and discuss the positives and negatives of top-down proteomics as an alternative.

Playing pin-the-tail-on-the-protein in extracellular vesicle (EV) proteomics

Extracellular vesicles (EVs) are anucleate particles enclosed by a lipid bilayer that are released from cells via exocytosis or direct budding from the plasma membrane. They contain an array of important molecular cargo such as proteins, nucleic acids, and lipids, and can transfer these cargoes to recipient cells as a means of intercellular communication. One of the overarching paradigms in the field of EV research is that EV cargo should reflect the biological state of the cell of origin. The true relationship or extent of this correlation is confounded by many factors, including the numerous ways one can isolate or enrich EVs, overlap in the biophysical properties of different classes of EVs, and analytical limitations. This presents a challenge to research aimed at detecting low-abundant EV-encapsulated nucleic acids or proteins in biofluids for biomarker research and underpins technical obstacles in the confident assessment of the proteomic landscape of EVs that may be affected by sample-type specific or disease-associated proteoforms. Improving our understanding of EV biogenesis, cargo loading, and developments in top-down proteomics may guide us towards advanced approaches for selective EV and molecular cargo enrichment, which could aid EV diagnostics and therapeutics research.

Top-down proteomics

Proteoforms, which arise from post-translational modifications, genetic polymorphisms and RNA splice variants, play a pivotal role as drivers in biology. Understanding proteoforms is essential to unravel the intricacies of biological systems and bridge the gap between genotypes and phenotypes. By analysing whole proteins without digestion, top-down proteomics (TDP) provides a holistic view of the proteome and can decipher protein function, uncover disease mechanisms and advance precision medicine. This Primer explores TDP, including the underlying principles, recent advances and an outlook on the future. The experimental section discusses instrumentation, sample preparation, intact protein separation, tandem mass spectrometry techniques and data collection. The results section looks at how to decipher raw data, visualize intact protein spectra and unravel data analysis. Additionally, proteoform identification, characterization and quantification are summarized, alongside approaches for statistical analysis. Various applications are described, including the human proteoform project and biomedical, biopharmaceutical and clinical sciences. These are complemented by discussions on measurement reproducibility, limitations and a forward-looking perspective that outlines areas where the field can advance, including potential future applications.

Tracking Inhibition of Human Small C-Terminal Domain Phosphatase 1 Using 193 nm Ultraviolet Photodissociation Mass Spectrometry

Working in tandem with kinases via a dynamic interplay of phosphorylation and dephosphorylation of proteins, phosphatases regulate many cellular processes and thus represent compelling therapeutic targets. Here we leverage ultraviolet photodissociation to shed light on the binding characteristics of two covalent phosphatase inhibitors, T65 and rabeprazole, and their respective interactions with the human small C-terminal domain phosphatase 1 (SCP1) and its single-point mutant C181A, in which a nonreactive alanine replaces one key reactive cysteine. Top-down MS/MS analysis is used to localize the binding of T65 and rabeprazole on the two proteins and estimate the relative reactivities of each cysteine residue.

The potential of proteomics for in-depth bioanalytical investigations of satellite cell function in applied myology

INTRODUCTION

Regenerative myogenesis plays a crucial role in mature myofibers to counteract muscular injury or dysfunction due to neuromuscular disorders. The activation of specialized myogenic stem cells, called satellite cells, is intrinsically involved in proliferation and differentiation, followed by myoblast fusion and the formation of multinucleated myofibers.

AREAS COVERED

This report provides an overview of the role of satellite cells in the neuromuscular system and the potential future impact of proteomic analyses for biomarker discovery, as well as the identification of novel therapeutic targets in muscle disease. The article reviews the ways in which the systematic analysis of satellite cells, myoblasts, and myocytes by single-cell proteomics can help to better understand the process of myofiber regeneration.

EXPERT OPINION

In order to better comprehend satellite cell dysfunction in neuromuscular disorders, mass spectrometry-based proteomics is an excellent large-scale analytical tool for the systematic profiling of pathophysiological processes. The optimized isolation of muscle-derived cells can be routinely performed by mechanical/enzymatic dissociation protocols, followed by fluorescence-activated cell sorting in specialized flow cytometers. Ultrasensitive single-cell proteomics using label-free quantitation methods or approaches that utilize tandem mass tags are ideal bioanalytical approaches to study the pathophysiological role of stem cells in neuromuscular disease.

Proteomics-The State of the Field: The Definition and Analysis of Proteomes Should Be Based in Reality, Not Convenience

With growing recognition and acknowledgement of the genuine complexity of proteomes, we are finally entering the post-proteogenomic era. Routine assessment of proteomes as inferred correlates of gene sequences (i.e., canonical 'proteins') cannot provide the necessary critical analysis of systems-level biology that is needed to understand underlying molecular mechanisms and pathways or identify the most selective biomarkers and therapeutic targets. These critical requirements demand the analysis of proteomes at the level of proteoforms/protein species, the actual active molecular players. Currently, only highly refined integrated or integrative top-down proteomics (iTDP) enables the analytical depth necessary to provide routine, comprehensive, and quantitative proteome assessments across the widest range of proteoforms inherent to native systems. Here we provide a broad perspective of the field, taking in historical and current realities, to establish a more balanced understanding of where the field has come from (in particular during the ten years since Proteomes was launched), current issues, and how things likely need to proceed if necessary deep proteome analyses are to succeed. We base this in our firm belief that the best proteomic analyses reflect, as closely as possible, the native sample at the moment of sampling. We also seek to emphasise that this and future analytical approaches are likely best based on the broad recognition and exploitation of the complementarity of currently successful approaches. This also emphasises the need to continuously evaluate and further optimize established approaches, to avoid complacency in thinking and expectations but also to promote the critical and careful development and introduction of new approaches, most notably those that address proteoforms. Above all, we wish to emphasise that a rigorous focus on analytical quality must override current thinking that largely values analytical speed; the latter would certainly be nice, if only proteoforms could thus be effectively, routinely, and quantitatively assessed. Alas, proteomes are composed of proteoforms, not molecular species that can be amplified or that directly mirror genes (i.e., 'canonical'). The problem is hard, and we must accept and address it as such, but the payoff in playing this longer game of rigorous deep proteome analyses is the promise of far more selective biomarkers, drug targets, and truly personalised or even individualised medicine.