Quantitation and Identification of Thousands of Human Proteoforms below 30 kDa

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.

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.

Cyclic Ion Mobility-Mass Spectrometry and Tandem Collision Induced Unfolding for Quantification of Elusive Protein Biomarkers

Sensitive analytical techniques that are capable of detecting and quantifying disease-associated biomolecules are indispensable in our efforts to understand disease mechanisms and guide therapeutic intervention through early detection, accurate diagnosis, and effective monitoring of disease. Parkinson's Disease (PD), for example, is one of the most prominent neurodegenerative disorders in the world, but the diagnosis of PD has primarily been based on the observation of clinical symptoms. The protein α-synuclein (α-syn) has emerged as a promising biomarker candidate for PD, but a lack of analytical methods to measure complex disease-associated variants of α-syn has prevented its widespread use as a biomarker. Antibody-based methods such as immunoassays and mass spectrometry-based approaches have been used to measure a limited number of α-syn forms; however, these methods fail to differentiate variants of α-syn that display subtle differences in only the sequence and structure. In this work, we developed a cyclic ion mobility-mass spectrometry method that combines multiple stages of activation and timed ion selection to quantify α-syn variants using both mass- and structure-based measurements. This method can allow for the quantification of several α-syn variants present at physiological levels in biological fluid. Taken together, this approach can be used to galvanize future efforts aimed at understanding the underlying mechanisms of PD and serves as a starting point for the development of future protein-structure-based diagnostics and therapeutic interventions.

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.

Infrared Photoactivation Enables Improved Native Top-Down Mass Spectrometry of Transmembrane Proteins

Membrane proteins are often challenging targets for native top-down mass spectrometry experimentation. The requisite use of membrane mimetics to solubilize such proteins necessitates the application of supplementary activation methods to liberate protein ions prior to sequencing, which typically limits the sequence coverage achieved. Recently, infrared photoactivation has emerged as an alternative to collisional activation for the liberation of membrane proteins from surfactant micelles. However, much remains unknown regarding the mechanism by which IR activation liberates membrane protein ions from such micelles, the extent to which such methods can improve membrane protein sequence coverage, and the degree to which such approaches can be extended to support native proteomics. Here, we describe experiments designed to evaluate and probe infrared photoactivation for membrane protein sequencing, proteoform identification, and native proteomics applications. Our data reveal that infrared photoactivation can dissociate micelles composed of a variety of detergent classes, without the need for a strong IR chromophore by leveraging the relatively weak association energies of such detergent clusters in the gas phase. Additionally, our data illustrate how IR photoactivation can be extended to include membrane mimetics beyond micelles and liberate proteins from nanodiscs, liposomes, and bicelles. Finally, our data quantify the improvements in membrane protein sequence coverage produced through the use of IR photoactivation, which typically leads to membrane protein sequence coverage values ranging from 40 to 60%.

Identification of Splice Variants and Isoforms in Transcriptomics and Proteomics

Alternative splicing is pivotal to the regulation of gene expression and protein diversity in eukaryotic cells. The detection of alternative splicing events requires specific omics technologies. Although short-read RNA sequencing has successfully supported a plethora of investigations on alternative splicing, the emerging technologies of long-read RNA sequencing and top-down mass spectrometry open new opportunities to identify alternative splicing and protein isoforms with less ambiguity. Here, we summarize improvements in short-read RNA sequencing for alternative splicing analysis, including percent splicing index estimation and differential analysis. We also review the computational methods used in top-down proteomics analysis regarding proteoform identification, including the construction of databases of protein isoforms and statistical analyses of search results. While many improvements in sequencing and computational methods will result from emerging technologies, there should be future endeavors to increase the effectiveness, integration, and proteome coverage of alternative splicing events.

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.

Improved Label-Free Quantification of Intact Proteoforms Using Field Asymmetric Ion Mobility Spectrometry

The high-throughput quantification of intact proteoforms using a label-free approach is typically performed on proteins in the 0-30 kDa mass range extracted from whole cell or tissue lysates. Unfortunately, even when high-resolution separation of proteoforms is achieved by either high-performance liquid chromatography or capillary electrophoresis, the number of proteoforms that can be identified and quantified is inevitably limited by the inherent sample complexity. Here, we benchmark label-free quantification of proteoforms of Escherichia coli by applying gas-phase fractionation (GPF) via field asymmetric ion mobility spectrometry (FAIMS). Recent advances in Orbitrap instrumentation have enabled the acquisition of high-quality intact and fragmentation mass spectra without the need for averaging time-domain transients prior to Fourier transform. The resulting speed improvements allowed for the application of multiple FAIMS compensation voltages in the same liquid chromatography-tandem mass spectrometry experiment without increasing the overall data acquisition cycle. As a result, the application of FAIMS to label-free quantification based on intact mass spectra substantially increases the number of both identified and quantified proteoforms without penalizing quantification accuracy in comparison to traditional label-free experiments that do not adopt GPF.

A Current State of Proteomics in Adult and Pediatric Inflammatory Bowel Diseases: A Systematic Search and Review

Inflammatory bowel diseases (IBD) are systemic immune-mediated conditions with predilection for the gastrointestinal tract and include Crohn's disease and ulcerative colitis. Despite the advances in the fields of basic and applied research, the etiopathogenesis remains largely unknown. As a result, only one third of the patients achieve endoscopic remission. A substantial portion of the patients also develop severe clinical complications or neoplasia. The need for novel biomarkers that can enhance diagnostic accuracy, more precisely reflect disease activity, and predict a complicated disease course, thus, remains high. Genomic and transcriptomic studies contributed substantially to our understanding of the immunopathological pathways involved in disease initiation and progression. However, eventual genomic alterations do not necessarily translate into the final clinical picture. Proteomics may represent a missing link between the genome, transcriptome, and phenotypical presentation of the disease. Based on the analysis of a large spectrum of proteins in tissues, it seems to be a promising method for the identification of new biomarkers. This systematic search and review summarize the current state of proteomics in human IBD. It comments on the utility of proteomics in research, describes the basic proteomic techniques, and provides an up-to-date overview of available studies in both adult and pediatric IBD.

Establishing 20S Proteasome Genetic, Translational and Post-Translational Status from Precious Biological and Patient Samples with Top-Down MS

The mammalian 20S catalytic core of the proteasome is made of 14 different subunits (α1-7 and β1-7) but exists as different subtypes depending on the cell type. In immune cells, for instance, constitutive catalytic proteasome subunits can be replaced by the so-called immuno-catalytic subunits, giving rise to the immunoproteasome. Proteasome activity is also altered by post-translational modifications (PTMs) and by genetic variants. Immunochemical methods are commonly used to investigate these PTMs whereby protein-tagging is necessary to monitor their effect on 20S assembly. Here, we present a new miniaturized workflow combining top-down and bottom-up mass spectrometry of immunopurified 20S proteasomes that analyze the proteasome assembly status as well as the full proteoform footprint, revealing PTMs, mutations, single nucleotide polymorphisms (SNPs) and induction of immune-subunits in different biological samples, including organoids, biopsies and B-lymphoblastoid cell lines derived from patients with proteasome-associated autoinflammatory syndromes (PRAAS). We emphasize the benefits of using top-down mass spectrometry in preserving the endogenous conformation of protein modifications, while enabling a rapid turnaround (1 h run) and ensuring high sensitivity (1–2 pmol) and demonstrate its capacity to semi-quantify constitutive and immune proteasome subunits.

The utility of proteases in proteomics, from sequence profiling to structure and function analysis

In mass spectrometry (MS)-based bottom-up proteomics, protease digestion plays an essential role in profiling both proteome sequences and post-translational modifications (PTMs). Trypsin is the gold standard in digesting intact proteins into small-size peptides, which are more suitable for high-performance liquid chromatography (HPLC) separation and tandem MS (MS/MS) characterization. However, protein sequences lacking Lys and Arg cannot be cleaved by trypsin and may be missed in conventional proteomic analysis. Proteases with cleavage sites complementary to trypsin are widely applied in proteomic analysis to greatly improve the coverage of proteome sequences and PTM sites. In this review, we survey the common and newly emerging proteases used in proteomics analysis mainly in the last 5 years, focusing on their unique cleavage features and specific proteomics applications such as missing protein characterization, new PTM discovery, and de novo sequencing. In addition, we summarize the applications of proteases in structural proteomics and protein function analysis in recent years. Finally, we discuss the future development directions of new proteases and applications in proteomics.

MS-TAFI: A Tool for the Analysis of Fragment Ions Generated from Intact Proteins

Tandem mass spectrometry (MS/MS) spectra of intact proteins can be difficult to interpret owing to the variety of fragment ion types and abundances. This information is crucial for maximizing the information derived from top-down mass spectrometry of proteins and protein complexes. MS-TAFI (Mass Spectrometry Tool for the Analysis of Fragment Ions) is a free Python-based program which offers a streamlined approach to the data analysis and visualization of deconvoluted MS/MS data of intact proteins. The application also contains tools for native mass spectrometry experiments with the ability to search for fragment ions that retain ligands (holo ions) as well as visualize the location of charge sites obtained from 193 nm ultraviolet photodissociation data. The source code and complete application for MS-TAFI is available for download at https://github.com/kylejuetten.

Neutral-Coating Capillary Electrophoresis Coupled with High-Resolution Mass Spectrometry for Top-Down Identification of Hemoglobin Variants

BACKGROUND

Identification of hemoglobin (Hb) variants is of significant value in the clinical diagnosis of hemoglobinopathy. However, conventional methods for identification of Hb variants in clinical laboratories can be inadequate due to the lack of structural characterization. We describe the use of neutral-coating capillary electrophoresis coupled with high-resolution mass spectrometry (CE-HR-MS) to achieve high-performance top-down identification of Hb variants.

METHODS

An Orbitrap Q-Exactive Plus mass spectrometer was coupled with an ECE-001 capillary electrophoresis (CE) unit through an EMASS-II ion source. A PS1 neutral-coating capillary was used for CE. Samples of red blood cells were lysed in water and diluted in 10 mM ammonium formate buffer for analysis. Deconvolution of raw mass spectrometry data was carried out to merge multiple charge states and isotopic peaks of an analyte to obtain its monoisotopic mass.

RESULTS

The neutral-coating CE could baseline separate individual Hb subunits dissociated from intact Hb forms, and the HR-MS could achieve both intact-protein analysis and top-down analysis of analytes. A number of patient samples that contain Hb subunit variants were analyzed, and the variants were successfully identified using the CE-HR-MS method.

CONCLUSIONS

The CE-HR-MS method has been demonstrated as a useful tool for top-down identification of Hb variants. With the ability to characterize the primary structures of Hb subunits, the CE-HR-MS method has significant advantages to complement or partially replace the conventional methods for the identification of Hb variants.

Middle-Down Mass Spectrometry Reveals Activity-Modifying Phosphorylation Barcode in a Class C G Protein-Coupled Receptor

G protein-coupled receptors (GPCRs) are the largest family of membrane receptors in humans. They mediate nearly all aspects of human physiology and thus are of high therapeutic interest. GPCR signaling is regulated in space and time by receptor phosphorylation. It is believed that different phosphorylation states are possible for a single receptor, and each encodes for unique signaling outcomes. Methods to determine the phosphorylation status of GPCRs are critical for understanding receptor physiology and signaling properties of GPCR ligands and therapeutics. However, common proteomic techniques have provided limited quantitative information regarding total receptor phosphorylation stoichiometry, relative abundances of isomeric modification states, and temporal dynamics of these parameters. Here, we report a novel middle-down proteomic strategy and parallel reaction monitoring (PRM) to quantify the phosphorylation states of the C-terminal tail of metabotropic glutamate receptor 2 (mGluR2). By this approach, we found that mGluR2 is subject to both basal and agonist-induced phosphorylation at up to four simultaneous sites with varying probability. Using a PRM tandem mass spectrometry methodology, we localized the positions and quantified the relative abundance of phosphorylations following treatment with an agonist. Our analysis showed that phosphorylation within specific regions of the C-terminal tail of mGluR2 is sensitive to receptor activation, and subsequent site-directed mutagenesis of these sites identified key regions which tune receptor sensitivity. This study demonstrates that middle-down purification followed by label-free quantification is a powerful, quantitative, and accessible tool for characterizing phosphorylation states of GPCRs and other challenging proteins.

Deciphering combinatorial post-translational modifications by top-down mass spectrometry

Post-translational modifications (PTMs) create vast structural and functional diversity of proteins, ultimately modulating protein function and degradation, influencing cellular signaling, and regulating transcription. The combinatorial patterns of PTMs increase the heterogeneity of proteins and further mediates their interactions. Advances in mass spectrometry-based proteomics have resulted in identification of thousands of proteins and allowed characterization of numerous types and sites of PTMs. Examination of intact proteins, termed the top-down approach, offers the potential to map protein sequences and localize multiple PTMs on each protein, providing the most comprehensive cataloging of proteoforms. This review describes some of the dividends of using mass spectrometry to analyze intact proteins and showcases innovative strategies that have enhanced the promise of top-down proteomics for exploring the impact of combinatorial PTMs in unsurpassed detail.

FLASHIda enables intelligent data acquisition for top-down proteomics to boost proteoform identification counts

The detailed analysis and structural characterization of proteoforms by top-down proteomics (TDP) has gained a lot of interest in biomedical research. Data-dependent acquisition (DDA) of intact proteins is non-trivial due to the diversity and complexity of proteoforms. Dedicated acquisition methods thus have the potential to greatly improve TDP. Here, we present FLASHIda, an intelligent online data acquisition algorithm for TDP that ensures the real-time selection of high-quality precursors of diverse proteoforms. FLASHIda combines fast charge deconvolution algorithms and machine learning-based quality assessment for optimal precursor selection. In an analysis of E. coli lysate, FLASHIda increases the number of unique proteoform level identifications from 800 to 1500 or generates a near-identical number of identifications in one third of the instrument time when compared to standard DDA mode. Furthermore, FLASHIda enables sensitive mapping of post-translational modifications and detection of chemical adducts. As a software extension module to the instrument, FLASHIda can be readily adopted for TDP studies of complex samples to enhance proteoform identification rates.

Current Insights on the Impact of Proteomics in Respiratory Allergies

Respiratory allergies affect humans worldwide, causing extensive morbidity and mortality. They include allergic rhinitis (AR), asthma, pollen food allergy syndrome (PFAS), aspirin-exacerbated respiratory disease (AERD), and nasal polyps (NPs). The study of respiratory allergic diseases requires new technologies for early and accurate diagnosis and treatment. Omics technologies provide the tools required to investigate DNA, RNA, proteins, and other molecular determinants. These technologies include genomics, transcriptomics, proteomics, and metabolomics. However, proteomics is one of the main approaches to studying allergic disorders' pathophysiology. Proteins are used to indicate normal biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. In this field, the principal goal of proteomics has been to discover new proteins and use them in precision medicine. Multiple technologies have been applied to proteomics, but that most used for identifying, quantifying, and profiling proteins is mass spectrometry (MS). Over the last few years, proteomics has enabled the establishment of several proteins for diagnosing and treating respiratory allergic diseases.

Laser capture microdissection-capillary zone electrophoresis-tandem mass spectrometry (LCM-CZE-MS/MS) for spatially resolved top-down proteomics: a pilot study of zebrafish brain

Mass spectrometry (MS)-based spatially resolved top-down proteomics (TDP) of tissues is crucial for understanding the roles played by microenvironmental heterogeneity in the biological functions of organs and for discovering new proteoform biomarkers of diseases. There are few published spatially resolved TDP studies. One of the challenges relates to the limited performance of TDP for the analysis of spatially isolated samples using, for example, laser capture microdissection (LCM) because those samples are usually mass-limited. We present the first pilot study of LCM-capillary zone electrophoresis (CZE)-MS/MS for spatially resolved TDP and used zebrafish brain as the sample. The LCM-CZE-MS/MS platform employed a non-ionic detergent and a freeze-thaw method for efficient proteoform extraction from LCM isolated brain sections followed by CZE-MS/MS without any sample cleanup step, ensuring high sensitivity. Over 400 proteoforms were identified in a CZE-MS/MS analysis of one LCM brain section via consuming the protein content of roughly 250 cells. We observed drastic differences in proteoform profiles between two LCM brain sections isolated from the optic tectum (Teo) and telencephalon (Tel) regions. Proteoforms of three proteins (npy, penkb, and pyya) having neuropeptide hormone activity were exclusively identified in the isolated Tel section. Proteoforms of reticulon, myosin, and troponin were almost exclusively identified in the isolated Teo section, and those proteins play essential roles in visual and motor activities. The proteoform profiles accurately reflected the main biological functions of the Teo and Tel regions of the brain. Additionally, hundreds of post-translationally modified proteoforms were identified.

The Human Proteoform Atlas: a FAIR community resource for experimentally derived proteoforms

The Human Proteoform Atlas (HPfA) is a web-based repository of experimentally verified human proteoforms on-line at http://human-proteoform-atlas.org and is a direct descendant of the Consortium of Top-Down Proteomics' (CTDP) Proteoform Atlas. Proteoforms are the specific forms of protein molecules expressed by our cells and include the unique combination of post-translational modifications (PTMs), alternative splicing and other sources of variation deriving from a specific gene. The HPfA uses a FAIR system to assign persistent identifiers to proteoforms which allows for redundancy calling and tracking from prior and future studies in the growing community of proteoform biology and measurement. The HPfA is organized around open ontologies and enables flexible classification of proteoforms. To achieve this, a public registry of experimentally verified proteoforms was also created. Submission of new proteoforms can be processed through email vianrtdphelp@northwestern.edu, and future iterations of these proteoform atlases will help to organize and assign function to proteoforms, their PTMs and their complexes in the years ahead.

Online μSEC2-nRPLC-MS for Improved Sensitivity of Intact Protein Detection of IEF-Separated Nonhuman Primate Cerebrospinal Fluid Proteins

Proteoform-resolved information, obtained by top-down (TD) "intact protein" proteomics, is expected to contribute substantially to the understanding of molecular pathogenic mechanisms and, in turn, identify novel therapeutic and diagnostic targets. However, the robustness of mass spectrometry (MS) analysis of intact proteins in complex biological samples is hindered by the high dynamic range in protein concentration and mass, protein instability, and buffer complexity. Here, we describe an evolutionary step for intact protein investigations through the online implementation of tandem microflow size-exclusion chromatography with nanoflow reversed-phase liquid chromatography and MS (μSEC2-nRPLC-MS). Online serial high-/low-pass SEC filtration overcomes the aforementioned hurdles to intact proteomic analysis through automated sample desalting/cleanup and enrichment of target mass ranges (5-155 kDa) prior to nRPLC-MS. The coupling of μSEC to nRPLC is achieved through a novel injection volume control (IVC) strategy of inserting protein trap columns, pre- and post-μSEC columns, to enable injection of dilute samples in high volumes without loss of sensitivity or resolution. Critical characteristics of the approach are tested via rigorous investigations on samples of varied complexity and chemical background. Application of the platform to cerebrospinal fluid (CSF) prefractionated by OFFGEL isoelectric focusing drastically increases the number of intact mass tags (IMTs) detected within the target mass range (5-30 kDa) in comparison to one-dimensional nRPLC-MS with approximately 100× less CSF than previous OFFGEL studies. Furthermore, the modular design of the μSEC2-nRPLC-MS platform is robust and promises significant flexibility for large-scale TDMS analysis of diverse samples either directly or in concert with other multidimensional fractionation steps.

Biopharmaceutical quality control with mass spectrometry

Mass spectrometry (MS) is a powerful technique for protein identification, quantification and characterization that is widely applied in biochemical studies, and which can provide data on the quantity, structural integrity and post-translational modifications of proteins. It is therefore a versatile and widely used analytic tool for quality control of biopharmaceuticals, especially in quantifying host-cell protein impurities, identifying post-translation modifications and structural characterization of biopharmaceutical proteins. Here, we summarize recent advances in MS-based analyses of these key quality attributes of the biopharmaceutical development and manufacturing processes.

Quantitative Top-Down Proteomics by Isobaric Labeling with Thiol-Directed Tandem Mass Tags

While identification-centric (qualitative) top-down proteomics (TDP) has seen rapid progress in the recent past, the quantification of intact proteoforms within complex proteomes is still challenging. The by far mostly applied approach is label-free quantification, which, however, provides limited multiplexing capacity, and its use in combination with multidimensional separation is encountered with a number of problems. Isobaric labeling, which is a standard quantification approach in bottom-up proteomics, circumvents these limitations. Here, we introduce the application of thiol-directed isobaric labeling for quantitative TDP. For this purpose, we analyzed the labeling efficiency and optimized tandem mass spectrometry parameters for optimal backbone fragmentation for identification and reporter ion formation for quantification. Two different separation schemes, gel-eluted liquid fraction entrapment electrophoresis × liquid chromatography-mass spectrometry (LC-MS) and high/low-pH LC-MS, were employed for the analyses of either Escherichia coli (E. coli) proteomes or combined E. coli/yeast samples (two-proteome interference model) to study potential ratio compression. While the thiol-directed labeling introduces a bias in the quantifiable proteoforms, being restricted to Cys-containing proteoforms, our approach showed excellent accuracy in quantification, which is similar to that achievable in bottom-up proteomics. For example, 876 proteoforms could be quantified with high accuracy in an E. coli lysate. The LC-MS data were deposited to the ProteomeXchange with the dataset identifier PXD026310.

Mesh Fragmentation Improves Dissociation Efficiency in Top-down Proteomics

Top-down proteomics is a key mass spectrometry-based technology for comprehensive analysis of proteoforms. Proteoforms exhibit multiple high charge states and isotopic forms in full MS scans. The dissociation behavior of proteoforms in different charge states and subjected to different collision energies is highly variable. The current widely employed data-dependent acquisition (DDA) method selects a narrow m/z range (corresponding to a single proteoform charge state) for dissociation from the most abundant precursors. We describe here Mesh, a novel dissociation strategy, to dissociate multiple charge states of one proteoform with multiple collision energies. We show that the Mesh strategy has the potential to generate fragment ions with improved sequence coverage and improve identification ratios in top-down proteomic analyses of complex samples. The strategy is implemented within an open-source instrument control software program named MetaDrive to perform real time deconvolution and precursor selection.

Mass spectrometry-based proteomic platforms for better understanding of SARS-CoV-2 induced pathogenesis and potential diagnostic approaches

While protein–protein interaction is the first step of the SARS‐CoV‐2 infection, recent comparative proteomic profiling enabled the identification of over 11,000 protein dynamics, thus providing a comprehensive reflection of the molecular mechanisms underlying the cellular system in response to viral infection. Here we summarize and rationalize the results obtained by various mass spectrometry (MS)‐based proteomic approaches applied to the functional characterization of proteins and pathways associated with SARS‐CoV‐2‐mediated infections in humans. Comparative analysis of cell‐lines versus tissue samples indicates that our knowledge in proteome profile alternation in response to SARS‐CoV‐2 infection is still incomplete and the tissue‐specific response to SARS‐CoV‐2 infection can probably not be recapitulated efficiently by in vitro experiments. However, regardless of the viral infection period, sample types, and experimental strategies, a thorough cross‐comparison of the recently published proteome, phosphoproteome, and interactome datasets led to the identification of a common set of proteins and kinases associated with PI3K‐Akt, EGFR, MAPK, Rap1, and AMPK signaling pathways. Ephrin receptor A2 (EPHA2) was identified by 11 studies including all proteomic platforms, suggesting it as a potential future target for SARS‐CoV‐2 infection mechanisms and the development of new therapeutic strategies. We further discuss the potentials of future proteomics strategies for identifying prognostic SARS‐CoV‐2 responsive age‐, gender‐dependent, tissue‐specific protein targets.

Genomics as a potential tool to unravel the rhizosphere microbiome interactions on plant health

Intense agricultural practices to meet rising food demands have caused ecosystem perturbations. For sustainable crop production, biological agents are gaining attention, but exploring their functional potential on a multi-layered complex ecosystem like the rhizosphere is challenging. This review explains the significance of genomics as a culture-independent molecular tool to understand the diversity and functional significance of the rhizosphere microbiome for sustainable agriculture. It discusses the recent significant studies in the rhizosphere environment carried out using evolving techniques like metagenomics, metatranscriptomics, and metaproteomics, their challenges, constraints infield application, and prospective solutions. The recent advances in techniques such as nanotechnology for the development of bioformulations and visualization techniques contemplating environmental safety were also discussed. The need for development of metagenomic data sets of regionally important crops, their plant microbial interactions and agricultural practices for narrowing down significant data from huge databases have been suggested. The role of taxonomical and functional diversity of soil microbiota in understanding soil suppression and part played by the microbial metabolites in the process have been analyzed and discussed in the context of 'omics' approach. 'Omics' studies have revealed important information about microbial diversity, their responses to various biotic and abiotic stimuli, and the physiology of disease suppression. This can be translated to crop sustainability and combinational approaches with advancing visualization and analysis methodologies fix the existing knowledge gap to a huge extend. With improved data processing and standardization of the methods, details of plant-microbe interactions can be successfully decoded to develop sustainable agricultural practices.

Quantifying Positional Isomers (QPI) by Top-Down Mass Spectrometry

Proteomics has exposed a plethora of posttranslational modifications, but demonstrating functional relevance requires new approaches. Top-down proteomics of intact proteins has the potential to fully characterize protein modifications in terms of amount, site(s), and the order in which they are deposited on the protein; information that so far has been elusive to extract by shotgun proteomics. Data acquisition and analysis of intact multimodified proteins have however been a major challenge, in particular for positional isomers that carry the same number of modifications at different sites. Solutions were previously proposed to extract this information from fragmentation spectra, but these have so far mainly been limited to peptides and have entailed a large degree of manual interpretation. Here, we apply high-resolution Orbitrap fusion top-down analyses in combination with bioinformatics approaches to attempt to characterize multiple modified proteins and quantify positional isomers. Automated covalent fragment ion type definition, detection of mass precision and accuracy, and extensive use of replicate spectra increase sequence coverage and drive down false fragment assignments from 10% to 1.5%. Such improved performance in fragment assignment is key to localize and quantify modifications from fragment spectra. The method is tested by investigating positional isomers of Ubiquitin mixed in known concentrations, which results in quantification of high ratios at very low standard errors of the mean (<5%), as well as with synthetic phosphorylated peptides. Application to multiphosphorylated Bora provides an estimation of the so far unknown stoichiometry of the known set of phosphosites and uncovers new sites from hyperphosphorylated Bora.

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ETD fragmentation reveals the presence of positional isomers.

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For proteins up to 40 kDa these positional isomers can accurately be quantified.

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For in-vitro phosphorylated BoraNT a wide array of positional isomers is revealed.

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Use of Fragment ion FDR levels improve the quality of extracted stoichiometries.

ClipsMS: An Algorithm for Analyzing Internal Fragments Resulting from Top-Down Mass Spectrometry

Top-down mass spectrometry (TD-MS) of peptides and proteins results in product ions that can be correlated to polypeptide sequence. Fragments can either be terminal fragments, which contain either the N- or the C-terminus, or internal fragments that contain neither termini. Normally, only terminal fragments are assigned due to the computational difficulties of assigning internal fragments. Here we describe ClipsMS, an algorithm that can assign both terminal and internal fragments generated by top-down MS fragmentation. Further, ClipsMS can be used to locate various modifications on the protein sequence. Using ClipsMS to assign TD-MS generated product ions, we demonstrate that for apo-myoglobin, the inclusion of internal fragments increases the sequence coverage up to 78%. Interestingly, many internal fragments cover complementary regions to the terminal fragments that enhance the information that is extracted from a single top-down mass spectrum. Analysis of oxidized apo-myoglobin using terminal and internal fragment matching by ClipsMS confirmed the locations of oxidation sites on the two methionine residues. Internal fragments can be beneficial for top-down protein fragmentation analysis, and ClipsMS can be a valuable tool for assigning both terminal and internal fragments present in a top-down mass spectrum. Data are available via the MassIVE community resource with the identifiers MSV000086788 and MSV000086789.

Robustness and Ruggedness of Isoelectric Focusing and Superficially Porous Liquid Chromatography with Fourier Transform Mass Spectrometry

An investigation of a multidimensional proteomics workflow composed of off-gel isoelectric focusing (IEF) and superficially porous liquid chromatography (SPLC) with Fourier transform mass spectrometry (FTMS) was completed in order to assess various figures of merit associated with intact protein measurements. Triplicate analysis performed at both high and low FTMS resolutions on the E. coli proteome resulted in ∼900 redundant proteoforms from 3 to 95 kDa. Normalization of the chromatographic axis to identified proteoforms enabled reproducible physicochemical property measurements between proteome replicates with inter-replicate variances of ±3 ppm mass error for proteoforms <30 kDa, ±1.1 Da for proteins >30 kDa, ±12 s retention time error, and ±0.21 pI units. The results for E. coli and standard proteins revealed a correlation between pI precision and proteoform abundance with species detected in multiple IEF fractions exhibiting pI precisions less than the theoretical resolution of the off-gel system (±0.05 vs ±0.17, respectively). Evaluation of differentially modified proteoforms of standard proteins revealed that high sample loads (100s μgrams) change the IEF pH gradient profile, leading to sample broadening that facilitates resolution of charged post-translational modifications (e.g., phosphorylation, sialylation). Despite the impact of sample load on IEF resolution, results on standard proteins measured directly or after being spiked into E. coli demonstrated that the reproducibility of the workflow permitted recombination of the MS signal across IEF fractions in a manner supporting the evaluation of three label-free quantitation metrics for intact protein studies (proteoforms, proteoform ratios, and protein) over 102-103 sample amount with low femtomole detection limits.

Virus systems biology: Proteomics profiling of dynamic protein networks during infection

The host cell proteome undergoes a variety of dynamic changes during viral infection, elicited by the virus itself or host cell defense mechanisms. Studying these changes on a global scale by integrating functional and physical interactions within protein networks during infection is an important tool to understand pathology. Indeed, proteomics studies dissecting protein signaling cascades and interaction networks upon infection showed how global information can significantly improve understanding of disease mechanisms of diverse viral infections. Here, we summarize and give examples of different experimental designs, proteomics approaches and bioinformatics analyses that allow profiling proteome changes and host-pathogen interactions to gain a molecular systems view of viral infection.

Proteoform Identification by Combining RNA-Seq and Top-Down Mass Spectrometry

In proteogenomic studies, genomic and transcriptomic variants are incorporated into customized protein databases for the identification of proteoforms, especially proteoforms with sample-specific variants. Most proteogenomic research has been focused on combining genomic or transcriptomic data with bottom-up mass spectrometry data. In the last decade, top-down mass spectrometry has attracted increasing attention because of its capacity to identify various proteoforms with alterations. However, top-down proteogenomics, in which genomic or transcriptomic data are combined with top-down mass spectrometry data, has not been widely adopted, and there is still a lack of software tools for top-down proteogenomic data analysis. In this paper, we introduce TopPG, a proteogenomic tool for generating proteoform sequence databases with genetic alterations and alternative splicing events. Experiments on top-down proteogenomic data of DLD-1 colorectal cancer cells showed that TopPG coupled with database search confidently identified proteoforms with sample-specific alterations.

Top-down proteomics: challenges, innovations, and applications in basic and clinical research

Introduction- A better understanding of the underlying molecular mechanism of diseases is critical for developing more effective diagnostic tools and therapeutics toward precision medicine. However, many challenges remain to unravel the complex nature of diseases. Areas covered- Changes in protein isoform expression and post-translation modifications (PTMs) have gained recognition for their role in underlying disease mechanisms. Top-down mass spectrometry (MS)-based proteomics is increasingly recognized as an important method for the comprehensive characterization of proteoforms that arise from alternative splicing events and/or PTMs for basic and clinical research. Here, we review the challenges, technological innovations, and recent studies that utilize top-down proteomics to elucidate changes in the proteome with an emphasis on its use to study heart diseases. Expert opinion- Proteoform-resolved information can substantially contribute to the understanding of the molecular mechanisms underlying various diseases and for the identification of novel proteoform targets for better therapeutic development . Despite the challenges of sequencing intact proteins, top-down proteomics has enabled a wealth of information regarding protein isoform switching and changes in PTMs. Continuous developments in sample preparation, intact protein separation, and instrumentation for top-down MS have broadened its capabilities to characterize proteoforms from a range of samples on an increasingly global scale.

Diagenetiforms: A new term to explain protein changes as a result of diagenesis in paleoproteomics

The term proteoform describes all combinations of change in a protein, as elucidated through intact mass proteomics. Paleoproteomic studies have begun using digestion-free and top-down techniques to access information from ancient and historical remains. However, to discuss protein changes that uniquely occur to archaeological and paleontological proteomes as the result of diagenesis (i.e., physical and chemical change imparted by burial), a novel term is needed that both addresses issues of combinatorics and distinguishes diagenetic-specific alteration. SIGNIFICANCE: The term diagenetiform provides the opportunity to communicate clearly the sets of diagenetic changes found on preserved proteins. The diagenetiform nomenclature will allow for top-down paleoproteomic studies to accurately describe the total changes detected on ancient proteins.

Evaluation of bottom-up and top-down mass spectrum identifications with different customized protein sequences databases

MOTIVATION

Generally, bottom-up and top-down are two complementary approaches for proteoforms identification. The inference of proteoforms relies on searching mass spectra against an accurate proteoform sequence database. A customized protein sequence database derived by RNA-Seq data can be used to better identify the proteoform existed in a studied species. However, the quality of sequences in customized databases which constructed by different strategies affect the performances of mass spectrometry (MS) identification. Additionally, performances of identifications between bottom-up and top-down using customized databases are also needed to be evaluated.

RESULTS

Three customized databases were constructed with different strategies separately. Two of them were based on translating assembled transcripts with or without genomic annotation, and the third one is a variant-extending protein database. By testing with bottom-up and top-down MS data separately, a variant-extending protein database could identify not only the most number of spectra but also the alleles expressed at the same time in diploid cells. An assembled database could identify the spectrum missed in reference database and amino acid (AA) alterations existed in studied species.

AVAILABILITY AND IMPLEMENTATION

Experimental results demonstrated that the proteoform sequences in an annotated database are more suitable for identifying AA alterations and peptide sequences missed in reference database. An unannotated database instead of a reference proteome database gets an enough high sensitivity of identifying mass spectra. The variant-extending reference database is the most sensitive to identify mass spectra and single AA variants.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The status of proteomics as we enter the 2020s: Towards personalised/precision medicine

The last decade has seen many major advances in proteomics, with over 70,000 publications in the field since 2010. A comprehensive omics toolbox has been developed facilitating rapid in depth analysis of the human proteome. Such studies are advancing our understanding of the biology of both health and disease. The combination of proteomics with other omics platforms (the omics pipeline), in particular proteogenomics, is giving important insights to the molecular changes leading to disease, covering the spectrum from genotype to phenotype and identifying potential biomarkers for disease detection, surveillance and monitoring, and revealing potential new drug targets. Discovery-based finding are now being translated to clinical application, supporting the rollout of precision/personalised medicine. This perspective has focused on twelve areas of importance that have fuelled the field. Recent exemplars are given to illustrate this and show how, together with some emerging technologies, they are anticipated to lead to further advances in the field. However, hurdles still remain to be overcome, especially in the area of Big Data analysis.

Thorough Performance Evaluation of 213 nm Ultraviolet Photodissociation for Top-down Proteomics

Top-down proteomics studies intact proteoform mixtures and offers important advantages over more common bottom-up proteomics technologies, as it avoids the protein inference problem. However, achieving complete molecular characterization of investigated proteoforms using existing technologies remains a fundamental challenge for top-down proteomics. Here, we benchmark the performance of ultraviolet photodissociation (UVPD) using 213 nm photons generated by a solid-state laser applied to the study of intact proteoforms from three organisms. Notably, the described UVPD setup applies multiple laser pulses to induce ion dissociation, and this feature can be used to optimize the fragmentation outcome based on the molecular weight of the analyzed biomolecule. When applied to complex proteoform mixtures in high-throughput top-down proteomics, 213 nm UVPD demonstrated a high degree of complementarity with the most employed fragmentation method in proteomics studies, higher-energy collisional dissociation (HCD). UVPD at 213 nm offered higher average proteoform sequence coverage and degree of proteoform characterization (including localization of post-translational modifications) than HCD. However, previous studies have shown limitations in applying database search strategies developed for HCD fragmentation to UVPD spectra which contains up to nine fragment ion types. We therefore performed an analysis of the different UVPD product ion type frequencies. From these data, we developed an ad hoc fragment matching strategy and determined the influence of each possible ion type on search outcomes. By paring down the number of ion types considered in high-throughput UVPD searches from all types down to the four most abundant, we were ultimately able to achieve deeper proteome characterization with UVPD. Lastly, our detailed product ion analysis also revealed UVPD cleavage propensities and determined the presence of a product ion produced specifically by 213 nm photons. All together, these observations could be used to better elucidate UVPD dissociation mechanisms and improve the utility of the technique for proteomic applications.

Comprehensive LESA Mass Spectrometry Imaging of Intact Proteins by Integration of Cylindrical FAIMS

The benefits of high field asymmetric waveform ion mobility spectrometry (FAIMS) for mass spectrometry imaging of intact proteins in thin tissue sections have been demonstrated previously. In those works, a planar FAIMS device coupled with a Thermo Elite mass spectrometer was employed. Here, we have evaluated a newly introduced cylindrical FAIMS device (the FAIMS Pro) coupled with a Thermo Fusion Lumos mass spectrometer for liquid extraction surface analysis mass spectrometry imaging of intact proteins in thin tissue sections from rat testes, kidney, and brain. The method makes use of multiple FAIMS compensation values at each location (pixel) of the imaging array. A total of 975 nonredundant protein species were detected in the testes imaging dataset, 981 in the kidney dataset, and 249 in the brain dataset. These numbers represent a 7-fold (brain) and over 10-fold (testes, kidney) improvement on the numbers of proteins previously detected in LESA FAIMS imaging, and a 10-fold to over 20-fold improvement on the numbers detected without FAIMS on this higher performance mass spectrometer, approaching the same order of magnitude as those obtained in top-down proteomics of cell lines. Nevertheless, high throughput identification within the LESA FAIMS imaging workflow remains a challenge.

Elucidating Proteoform Dynamics Underlying the Senescence Associated Secretory Phenotype

Primary diploid cells exit the cell cycle in response to exogenous stress or oncogene activation through a process known as cellular senescence. This cell-autonomous tumor-suppressive mechanism is also a major mechanism operative in organismal aging. To date, temporal aspects of senescence remain understudied. Therefore, we use quantitative proteomics to investigate changes following forced HRAS^G12V expression and induction of senescence across 1 week in normal diploid fibroblasts. We demonstrate that global intracellular proteomic changes correlate with the emergence of the senescence-associated secretory phenotype and the switch to robust cell cycle exit. The senescence secretome reinforces cell cycle exit, yet is largely detrimental to tissue homeostasis. Previous studies of secretomes rely on ELISA, bottom-up proteomics or RNA-seq. To date, no study to date has examined the proteoform complexity of secretomes to elucidate isoform-specific, post-translational modifications or regulated cleavage of signal peptides. Therefore, we use a quantitative top-down proteomics approach to define the molecular complexity of secreted proteins <30 kDa. We identify multiple forms of immune regulators with known activities and affinities such as distinct forms of interleukin-8, as well as GROα and HMGA1, and temporally resolve secreted proteoform dynamics. Together, our work demonstrates the complexity of the secretome past individual protein accessions and provides motivation for further proteoform-resolved measurements of the secretome.

Mass spectrometry based proteomics and metabolomics in personalized oncology

Precision medicine (PM) means the customization of healthcare with decisions and practices adjusted to the individual patient. It includes personalized diagnostics, patients' sub-classification, individual treatment selection and the monitoring of its effectiveness. Currently, in oncology, PM is based on the molecular and cellular features of a tumor, its microenvironment and the patient's genetics and lifestyle. Surprisingly, the available targeted therapies were found effective only in a subset of patients. An in-depth understanding of tumor biology is crucial to improve their effectiveness and develop new therapeutic targets. Completion of genetic information with proteomics and metabolomics can give broader knowledge about tumor biology which consequently provides novel biomarkers and indicates new therapeutic targets. Recently, metabolomics and proteomics have extensively been applied in the field of oncology. In the context of PM, human studies, with the use of mass spectrometry (MS) which allows the detection of thousands of molecules in a large number of samples, are the most valuable. Such studies, focused on cancer biomarkers discovery or patients' stratification, are presented in this review. Moreover, the technical aspects of MS-based clinical proteomics and metabolomics are described.

Deep Intact Proteoform Characterization in Human Cell Lysate Using High-pH and Low-pH Reversed-Phase Liquid Chromatography

Post-translational modifications (PTMs) play critical roles in biological processes and have significant effects on the structures and dynamics of proteins. Top-down proteomics methods were developed for and applied to the study of intact proteins and their PTMs in human samples. However, the large dynamic range and complexity of human samples makes the study of human proteins challenging. To address these challenges, we developed a 2D pH RP/RPLC-MS/MS technique that fuses high-resolution separation and intact protein characterization to study the human proteins in HeLa cell lysate. Our results provide a deep coverage of soluble proteins in human cancer cells. Compared to 225 proteoforms from 124 proteins identified when 1D separation was used, 2778 proteoforms from 628 proteins were detected and characterized using our 2D separation method. Many proteoforms with critically functional PTMs including phosphorylation were characterized. Additionally, we present the first detection of intact human GcvH proteoforms with rare modifications such as octanoylation and lipoylation. Overall, the increase in the number of proteoforms identified using 2DLC separation is largely due to the reduction in sample complexity through improved separation resolution, which enables the detection of low-abundance PTM-modified proteoforms. We demonstrate here that 2D pH RP/RPLC is an effective technique to analyze complex protein samples using top-down proteomics.

Capillary Zone Electrophoresis-Tandem Mass Spectrometry with Activated Ion Electron Transfer Dissociation for Large-scale Top-down Proteomics

Capillary zone electrophoresis (CZE)-tandem mass spectrometry (MS/MS) has been recognized as an efficient approach for top-down proteomics recently for its high-capacity separation and highly sensitive detection of proteoforms. However, the commonly used collision-based dissociation methods often cannot provide extensive fragmentation of proteoforms for thorough characterization. Activated ion electron transfer dissociation (AI-ETD), that combines infrared photoactivation concurrent with ETD, has shown better performance for proteoform fragmentation than higher energy-collisional dissociation (HCD) and standard ETD. Here, we present the first application of CZE-AI-ETD on an Orbitrap Fusion Lumos mass spectrometer for large-scale top-down proteomics of Escherichia coli (E. coli) cells. CZE-AI-ETD outperformed CZE-ETD regarding proteoform and protein identifications (IDs). CZE-AI-ETD reached comparable proteoform and protein IDs with CZE-HCD. CZE-AI-ETD tended to generate better expectation values (E values) of proteoforms than CZE-HCD and CZE-ETD, indicating a higher quality of MS/MS spectra from AI-ETD respecting the number of sequence-informative fragment ions generated. CZE-AI-ETD showed great reproducibility regarding the proteoform and protein IDs with relative standard deviations less than 4% and 2% (n = 3). Coupling size exclusion chromatography (SEC) to CZE-AI-ETD identified 3028 proteoforms and 387 proteins from E. coli cells with 1% spectrum level and 5% proteoform-level false discovery rates. The data represents the largest top-down proteomics dataset using the AI-ETD method so far. Single-shot CZE-AI-ETD of one SEC fraction identified 957 proteoforms and 253 proteins. N-terminal truncations, signal peptide cleavage, N-terminal methionine removal, and various post-translational modifications including protein N-terminal acetylation, methylation, S-thiolation, disulfide bonds, and lysine succinylation were detected.

Proton Transfer Charge Reduction Enables High-Throughput Top-Down Analysis of Large Proteoforms

Despite the recent technological advances in Fourier transform mass spectrometry (FTMS) instrumentation, top-down proteomics (TDP) is currently mostly applied to the characterization of proteoforms <30 kDa due to the poor performance of high-resolution FTMS for the analysis of larger proteoforms and the high complexity of intact proteomes in the 30-60 kDa mass range. Here, we propose a novel data acquisition method based on ion-ion proton transfer, herein termed proton transfer charge reduction (PTCR), to investigate large proteoforms of Pseudomonas aeruginosa in a high-throughput fashion. We designed a targeted data acquisition strategy, named tPTCR, which applies two consecutive gas phase fractionation steps for obtaining intact precursor masses: first, a narrow (1.5 m/z-wide) quadrupole filter m/z transmission window is used to select a subset of charge states from all ionized proteoform cations; second, this aliquot of protein cations is subjected to PTCR in order to reduce their average charge state: upon m/z analysis in an Orbitrap, proteoform mass spectra with minimal m/z peak overlap and easy-to-interpret charge state distributions are obtained, simplifying the proteoform mass calculation. Subsequently, the same quadrupole-selected narrow m/z region of analytes is subjected to collisional dissociation to obtain proteoform sequence information, which used in combination with intact mass information leads to proteoform identification through an off-line database search. The newly proposed method was benchmarked against the previously developed "medium/high" data-dependent acquisition strategy and doubled the number of UniProt entries and proteoforms >30 kDa identified on the liquid chromatography time scale.

VisioProt-MS: interactive 2D maps from intact protein mass spectrometry

SUMMARY

VisioProt-MS is designed to summarize and analyze intact protein and top-down proteomics data. It plots the molecular weights of eluting proteins as a function of their retention time, thereby allowing inspection of runs from liquid chromatography coupled to mass spectrometry (LC-MS). It also overlays MS/MS identification results. VisioProt-MS is compatible with outputs from many different top-down dedicated software. To our knowledge, this is the only open source standalone application that allows the dynamic comparison of several MS files, a prerequisite for comparative analysis of different biological conditions. With its dynamic rendering, this user-friendly web application facilitates inspection, comparison and export of publication quality 2 D maps from deconvoluted LC-MS run(s) and top-down proteomics data.

AVAILABILITY AND IMPLEMENTATION

The Shiny-based web application VisioProt-MS is suitable for non-R users. It can be found at https://masstools.ipbs.fr/mstools/visioprot-ms/ and the corresponding scripts are downloadable at https://github.com/mlocardpaulet/VisioProt-MS. It is governed by the CeCILL license (http://www.cecill.info).

Capillary zone electrophoresis-mass spectrometry for top-down proteomics

Mass spectrometry (MS)-based top-down proteomics characterizes complex proteomes at the intact proteoform level and provides an accurate picture of protein isoforms and protein post-translational modifications in the cell. The progress of top-down proteomics requires novel analytical tools with high peak capacity for proteoform separation and high sensitivity for proteoform detection. The requirements have made capillary zone electrophoresis (CZE)-MS an attractive approach for advancing large-scale top-down proteomics. CZE has achieved a peak capacity of 300 for separation of complex proteoform mixtures. CZE-MS has shown drastically better sensitivity than commonly used reversed-phase liquid chromatography (RPLC)-MS for proteoform detection. The advanced CZE-MS identified 6,000 proteoforms of nearly 1,000 proteoform families from a complex proteome sample, which represents one of the largest top-down proteomic datasets so far. In this review, we focus on the recent progress in CZE-MS-based top-down proteomics and provide our perspectives about its future directions.

Constructing Human Proteoform Families Using Intact-Mass and Top-Down Proteomics with a Multi-Protease Global Post-Translational Modification Discovery Database

Complex human biomolecular processes are made possible by the diversity of human proteoforms. Constructing proteoform families, groups of proteoforms derived from the same gene, is one way to represent this diversity. Comprehensive, high-confidence identification of human proteoforms remains a central challenge in mass spectrometry-based proteomics. We have previously reported a strategy for proteoform identification using intact-mass measurements, and we have since improved that strategy by mass calibration based on search results, the use of a global post-translational modification discovery database, and the integration of top-down proteomics results with intact-mass analysis. In the present study, we combine these strategies for enhanced proteoform identification in total cell lysate from the Jurkat human T lymphocyte cell line. We collected, processed, and integrated three types of proteomics data (NeuCode-labeled intact-mass, label-free top-down, and multi-protease bottom-up) to maximize the number of confident proteoform identifications. The integrated analysis revealed 5950 unique experimentally observed proteoforms, which were assembled into 848 proteoform families. Twenty percent of the observed proteoforms were confidently identified at a 3.9% false discovery rate, representing 1207 unique proteoforms derived from 484 genes.

Top-Down and Intact Protein Mass Spectrometry Data Visualization for Proteoform Analysis Using VisioProt-MS

The rise of intact protein analysis by mass spectrometry (MS) was accompanied by an increasing need for flexible tools allowing data visualization and analysis. These include inspection of the deconvoluted molecular weights of the proteoforms eluted alongside liquid chromatography (LC) through their representation in three-dimensional (3D) liquid chromatography coupled to mass spectrometry (LC-MS) maps (plots of deconvoluted molecular weights, retention times, and intensity of the MS signal). With this aim, we developed a free and open-source web application named VisioProt-MS (https://masstools.ipbs.fr/mstools/visioprot-ms/). VisioProt-MS is highly compatible with many algorithms and software developed by the community to integrate and deconvolute top-down and intact protein MS data. Its dynamic and user-friendly features greatly facilitate analysis through several graphical representations dedicated to MS and tandem mass spectrometry (MS/MS) analysis of proteoforms in complex samples. Here, we will illustrate the importance of LC-MS map visualization to optimize top-down acquisition/search parameters and analyze intact protein MS data. We will go through the main features of VisioProt-MS using the human proteasomal 20S core particle as a user-case.

Large-Scale Qualitative and Quantitative Top-Down Proteomics Using Capillary Zone Electrophoresis-Electrospray Ionization-Tandem Mass Spectrometry with Nanograms of Proteome Samples

Capillary zone electrophoresis-electrospray ionization-tandem mass spectrometry (CZE-ESI-MS/MS) has attracted attention recently for top-down proteomics because it can achieve highly efficient separation and very sensitive detection of proteins. However, separation window and sample loading volume of CZE need to be boosted for a better proteome coverage using CZE-MS/MS. Here, we present an improved CZE-MS/MS system that achieved a 180-min separation window and a 2-μL sample loading volume for top-down characterization of protein mixtures. The system obtained highly efficient separation of proteins with nearly one million theoretical plates for myoglobin and enabled baseline separation of three different proteoforms of myoglobin. The CZE-MS/MS system identified 797 ± 21 proteoforms and 258 ± 7 proteins (n = 2) from an Escherichia coli (E. coli) proteome sample in a single run with only 250 ng of proteins injected. The system still identified 449 ± 40 proteoforms and 173 ± 6 proteins (n = 2) from the E. coli sample when only 25 ng of proteins were injected per run. Single-shot CZE-MS/MS analyses of zebrafish brain cerebellum (Cb) and optic tectum (Teo) regions identified 1730 ± 196 proteoforms (n = 3) and 2024 ± 255 proteoforms (n = 3), respectively, with only 500-ng proteins loaded per run. Label-free quantitative top-down proteomics of zebrafish brain Cb and Teo regions revealed significant differences between Cb and Teo regarding the proteoform abundance. Over 700 proteoforms from 131 proteins had significantly higher abundance in Cb compared to Teo, and these proteins were highly enriched in several biological processes, including muscle contraction, glycolytic process, and mesenchyme migration. Graphical Abstract.

Expanding the mass range for UVPD-based native top-down mass spectrometry

Native top-down proteomics using UVPD extended to mega Dalton protein assemblies.

Native top-down mass spectrometry is emerging as a methodology that can be used to structurally investigate protein assemblies. To extend the possibilities of native top-down mass spectrometry to larger and more heterogeneous biomolecular assemblies, advances in both the mass analyzer and applied fragmentation techniques are still essential. Here, we explore ultraviolet photodissociation (UVPD) of protein assemblies on an Orbitrap with extended mass range, expanding its usage to large and heterogeneous macromolecular complexes, reaching masses above 1 million Da. We demonstrate that UVPD can lead not only to the ejection of intact subunits directly from such large intact complexes, but also to backbone fragmentation of these subunits, providing enough sequence information for subunit identification. The Orbitrap mass analyzer enables simultaneous monitoring of the precursor, the subunits, and the subunit fragments formed upon UVPD activation. While only partial sequence coverage of the subunits is observed, the UVPD data yields information about the localization of chromophores covalently attached to the subunits of the light harvesting complex B-phycoerythrin, extensive backbone fragmentation in a subunit of a CRISPR-Cas Csy (type I–F Cascade) complex, and sequence modifications in a virus-like proteinaceous nano-container. Through these multiple applications we demonstrate for the first time that UVPD based native top-down mass spectrometry is feasible for large and heterogeneous particles, including ribonucleoprotein complexes and MDa virus-like particles.