Top-Down Proteomics of Large Proteins up to 223 kDa Enabled by Serial Size Exclusion Chromatography Strategy

Mass spectrometry-intensive top-down proteomics: an update on technology advancements and biomedical applications

Proteoforms are all forms of protein molecules from the same gene because of variations at the DNA, RNA, and protein levels, e.g., alternative splicing and post-translational modifications (PTMs). Delineation of proteins in a proteoform-specific manner is crucial for understanding their biological functions. Mass spectrometry (MS)-intensive top-down proteomics (TDP) is promising for comprehensively characterizing intact proteoforms in complex biological systems. It has achieved substantial progress in technological development, including sample preparation, proteoform separations, MS instrumentation, and bioinformatics tools. In a single TDP study, thousands of proteoforms can be identified and quantified from a cell lysate. It has also been applied to various biomedical research to better our understanding of protein function in regulating cellular processes and to discover novel proteoform biomarkers of diseases for early diagnosis and therapeutic development. This review covers the most recent technological development and biomedical applications of MS-intensive TDP.

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.

Increasing protein identifications in bottom-up proteomics of T. castaneum - Exploiting synergies of protein biochemistry and bioinformatics

Depending on the respective research question, LC-MS/MS based bottom-up proteomics poses challenges from the initial biological sample all the way to data evaluation. The focus of this study was to investigate the influence of sample preparation techniques and data analysis parameters on protein identification in Tribolium castaneum by applying free software proteomics platform Max Quant. Multidimensional protein extraction strategies in combination with electrophoretic or chromatographic off-line protein pre-fractionation were applied to enhance the spectrum of isolated proteins from T. castaneum and reduce the effect of co-elution and ion suppression effects during nano-LC-MS/MS measurements of peptides. For comprehensive data analysis, MaxQuant was used for protein identification and R for data evaluation. A wide range of parameters were evaluated to gain reproducible, reliable, and significant protein identifications. A simple phosphate buffer, pH 8, containing protease and phosphatase inhibitor cocktail and application of gentle extraction conditions were used as a first extraction step for T.castaneum proteins. Furthermore, a two-dimensional extraction procedure in combination with electrophoretic pre-fractionation of extracted proteins and subsequent in-gel digest resulted in almost 100% increase of identified proteins when compared to chromatographic fractionation as well as one-pot-analysis. The additionally identified proteins could be assigned to new molecular functions or cell compartments, emphasizing the positive effect of extended sample preparation in bottom-up proteomics. Besides the number of peptides during post-processing, MaxQuant's Match between Runs exhibited a crucial effect on the number of identified proteins. A maximum relative standard deviation of 2% must be considered for the data analysis. Our work with Tribolium castaneum larvae demonstrates that sometimes - depending on matrix and research question - more complex and time-consuming sample preparation can be advantageous for isolation and identification of additional proteins in bottom-up proteomics.

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.

Precursor deconvolution error estimation: The missing puzzle piece in false discovery rate in top-down proteomics

Top-down proteomics (TDP) directly analyzes intact proteins and thus provides more comprehensive qualitative and quantitative proteoform-level information than conventional bottom-up proteomics (BUP) that relies on digested peptides and protein inference. While significant advancements have been made in TDP in sample preparation, separation, instrumentation, and data analysis, reliable and reproducible data analysis still remains one of the major bottlenecks in TDP. A key step for robust data analysis is the establishment of an objective estimation of proteoform-level false discovery rate (FDR) in proteoform identification. The most widely used FDR estimation scheme is based on the target-decoy approach (TDA), which has primarily been established for BUP. We present evidence that the TDA-based FDR estimation may not work at the proteoform-level due to an overlooked factor, namely the erroneous deconvolution of precursor masses, which leads to incorrect FDR estimation. We argue that the conventional TDA-based FDR in proteoform identification is in fact protein-level FDR rather than proteoform-level FDR unless precursor deconvolution error rate is taken into account. To address this issue, we propose a formula to correct for proteoform-level FDR bias by combining TDA-based FDR and precursor deconvolution error rate.

Characterizing Age-related Changes in Intact Mitochondrial Proteoforms in Murine Hearts using Quantitative Top-Down Proteomics

Cardiovascular diseases (CVDs) are the leading cause of death worldwide, and the prevalence of CVDs increases markedly with age. Due to the high energetic demand, the heart is highly sensitive to mitochondrial dysfunction. The complexity of the cardiac mitochondrial proteome hinders the development of effective strategies that target mitochondrial dysfunction in CVDs. Mammalian mitochondria are composed of over 1000 proteins, most of which can undergo post-translational protein modifications (PTMs). Top-down proteomics is a powerful technique for characterizing and quantifying all protein sequence variations and PTMs. However, there are still knowledge gaps in the study of age-related mitochondrial proteoform changes using this technique. In this study, we used top-down proteomics to identify intact mitochondrial proteoforms in young and old hearts and determined changes in protein abundance and PTMs in cardiac aging.

METHODS

Intact mitochondria were isolated from the hearts of young (4-month-old) and old (24-25-month-old) mice. The mitochondria were lysed, and mitochondrial lysates were subjected to denaturation, reduction, and alkylation. For quantitative top-down analysis, there were 12 runs in total arising from 3 biological replicates in two conditions, with technical duplicates for each sample. The collected top-down datasets were deconvoluted and quantified, and then the proteoforms were identified.

RESULTS

From a total of 12 LC-MS/MS runs, we identified 134 unique mitochondrial proteins in the different sub-mitochondrial compartments (OMM, IMS, IMM, matrix). 823 unique proteoforms in different mass ranges were identified. Compared to cardiac mitochondria of young mice, 7 proteoforms exhibited increased abundance and 13 proteoforms exhibited decreased abundance in cardiac mitochondria of old mice. Our analysis also detected PTMs of mitochondrial proteoforms, including N-terminal acetylation, lysine succinylation, lysine acetylation, oxidation, and phosphorylation.

CONCLUSION

By combining mitochondrial protein enrichment using mitochondrial fractionation with quantitative top-down analysis using ultrahigh-pressure liquid chromatography (UPLC)-MS and label-free quantitation, we successfully identified and quantified intact proteoforms in the complex mitochondrial proteome. Using this approach, we detected age-related changes in abundance and PTMs of mitochondrial proteoforms in the heart.

Concentrated ionic liquids for proteomics: Caveat emptor!

The use of concentrated ionic liquids (ILs) in the bioanalytical chemistry of proteins is sparse; typically, dilute aqueous IL solutions are used. Concentrated ILs have unique properties that may allow researchers to dissolve previously insoluble protein analytes, to increase the depth and robustness of sample preparation and the analysis of proteins. Previous research using concentrated ILs for this purpose is sparse and there is a need to systematically investigate the structure-activity relationship between the IL structure and its capacity to solubilise proteins. Here, bovine serum albumin was dissolved in various ionic liquids and monitored over time by light microscopy and SDS-PAGE. While qualitative, these measures provide a good estimate of, respectively, the dissolving power of an IL towards the given protein and the retained integrity of the protein. Hydrophilic ILs show the best solubilisation capacity and higher temperatures (in a restricted sense) improve the solubility of the protein. Higher temperatures and longer reaction times reduce the molecular weight of the protein, which could inhibit their applicability in proteomics, unless the conditions are judiciously controlled. Researchers should exercise caution when using concentrated ILs for protein analysis until the full scope and limitations are known, an aspect we are presently investigating.

Protein LC-MS Tools for the Next Generation of Biotherapeutic Analyses from Preclinical and Clinical Serum

LC-MS analysis of therapeutic antibodies and other biotherapeutics from in-life studies (e.g., serum/plasma) has evolved from simple peptide digestion to peptide mapping and intact mass monitoring. From more advanced analytical approaches, a deeper understanding as to the fate of the biotherapeutic in vivo is gained. Here, we examine the next generation of approaches to facilitate the most comprehensive understanding of large molecule drug fate in circulation. Three case studies are presented: (1) use of relative and absolute calibration curves for biotherapeutic quantitation from the same sample set; (2) top-down mass spectrometry applied to bioanalytical assays; (3) biotherapeutic protein complexes from serum analyzed by native protein MS. We anticipate that these approaches will be further adapted and applied by other research groups.

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.

Coupling High-Field Asymmetric Waveform Ion Mobility Spectrometry with Capillary Zone Electrophoresis-Tandem Mass Spectrometry for Top-Down Proteomics

Capillary zone electrophoresis-tandem mass spectrometry (CZE-MS/MS) has emerged as an essential technique for top-down proteomics (TDP), providing superior separation efficiency and high detection sensitivity for proteoform analysis. Here, we aimed to further enhance the performance of CZE-MS/MS for TDP via coupling online gas-phase proteoform fractionation using high-field asymmetric waveform ion mobility spectrometry (FAIMS). When the compensation voltage (CV) of FAIMS was changed from -50 to 30 V, the median mass of identified proteoforms increased from less than 10 kDa to about 30 kDa, suggesting that FAIMS can efficiently fractionate proteoforms by their size. CZE-FAIMS-MS/MS boosted the number of proteoform identifications from a yeast sample by nearly 3-fold relative to CZE-MS/MS alone. It particularly benefited the identification of relatively large proteoforms, improving the number of proteoforms in a mass range of 20-45 kDa by 6-fold compared to CZE-MS/MS alone. FAIMS fractionation gained nearly 20-fold better signal-to-noise ratios of randomly selected proteoforms than no FAIMS. We expect that CZE-FAIMS-MS/MS will be a useful tool for further advancing the sensitivity and coverage of TDP. This work shows the first example of coupling CE with ion mobility spectrometry (IMS) for TDP.

High sensitivity top-down proteomics captures single muscle cell heterogeneity in large proteoforms

Single-cell proteomics has emerged as a powerful method to characterize cellular phenotypic heterogeneity and the cell-specific functional networks underlying biological processes. However, significant challenges remain in single-cell proteomics for the analysis of proteoforms arising from genetic mutations, alternative splicing, and post-translational modifications. Herein, we have developed a highly sensitive functionally integrated top-down proteomics method for the comprehensive analysis of proteoforms from single cells. We applied this method to single muscle fibers (SMFs) to resolve their heterogeneous functional and proteomic properties at the single-cell level. Notably, we have detected single-cell heterogeneity in large proteoforms (>200 kDa) from the SMFs. Using SMFs obtained from three functionally distinct muscles, we found fiber-to-fiber heterogeneity among the sarcomeric proteoforms which can be related to the functional heterogeneity. Importantly, we detected multiple isoforms of myosin heavy chain (~223 kDa), a motor protein that drives muscle contraction, with high reproducibility to enable the classification of individual fiber types. This study reveals single muscle cell heterogeneity in large proteoforms and establishes a direct relationship between sarcomeric proteoforms and muscle fiber types, highlighting the potential of top-down proteomics for uncovering the molecular underpinnings of cell-to-cell variation in complex systems.

Technological development of multidimensional liquid chromatography-mass spectrometry in proteome research

Liquid chromatography-mass spectrometry (LC-MS) is the method of choice for high-throughput proteomic research. Limited by the peak capacity, the separation performance of conventional single-dimensional LC hampers the development of proteomics. Combining different separation modes orthogonally, multidimensional liquid chromatography (MDLC) with high peak capacity was developed to address this challenge. MDLC has evolved rapidly since its establishment, and the progress of proteomics has been greatly facilitated by the advent of novel MDLC-MS-based methods. In this paper, we will review the advances of MDLC-MS-based methodologies and technologies in proteomics studies, from different perspectives including novel application scenarios and proteomic targets, automation, miniaturization, and the improvement of the classic methods in recent years. In addition, attempts regarding new MDLC-MS models are also mentioned together with the outlook of MDLC-MS-based proteomics methods.

Prediction of Proteins in Cerebrospinal Fluid and Application to Glioma Biomarker Identification

Cerebrospinal fluid (CSF) proteins are very important because they can serve as biomarkers for central nervous system diseases. Although many CSF proteins have been identified with wet experiments, the identification of CSF proteins is still a challenge. In this paper, we propose a novel method to predict proteins in CSF based on protein features. A two-stage feature-selection method is employed to remove irrelevant features and redundant features. The deep neural network and bagging method are used to construct the model for the prediction of CSF proteins. The experiment results on the independent testing dataset demonstrate that our method performs better than other methods in the prediction of CSF proteins. Furthermore, our method is also applied to the identification of glioma biomarkers. A differentially expressed gene analysis is performed on the glioma data. After combining the analysis results with the prediction results of our model, the biomarkers of glioma are identified successfully.

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

Ischemic cardiomyopathy (ICM) is a prominent form of heart failure, but the molecular mechanisms underlying ICM remain relatively understudied due to marked phenotypic heterogeneity. Alterations in post-translational modifications (PTMs) and isoform switches in sarcomeric proteins play important roles in cardiac pathophysiology. Thus, it is essential to define sarcomeric proteoform landscape to better understand ICM. Herein, we have implemented a top-down liquid chromatography (LC)-mass spectrometry (MS)-based proteomics method for the identification and quantification of sarcomeric proteoforms in the myocardia of donors without heart diseases (n = 16) compared to end-stage ICM patients (n = 16). Importantly, quantification of post-translational modifications (PTMs) and expression reveal significant changes in various sarcomeric proteins extracted from ICM tissues. Changes include altered phosphorylation and expression of cardiac troponin I (cTnI) and enigma homologue 2 (ENH2) as well as an increase in muscle LIM protein (MLP) and calsarcin-1 (Cal-1) phosphorylation in ICM hearts. Our results imply that the contractile apparatus of the sarcomere is severely dysregulated during ICM. Thus, this is the first study to uncover significant molecular changes to multiple sarcomeric proteins in the LV myocardia of the end-stage ICM patients using liquid chromatography-mass spectrometry (LC-MS)-based top-down proteomics. Raw data are available via the PRIDE repository with identifier PXD038066.

Recent advances in top-down proteome sample processing ahead of MS analysis

Top-down proteomics is emerging as a preferred approach to investigate biological systems, with objectives ranging from the detailed assessment of a single protein therapeutic, to the complete characterization of every possible protein including their modifications, which define the human proteoform. Given the controlling influence of protein modifications on their biological function, understanding how gene products manifest or respond to disease is most precisely achieved by characterization at the intact protein level. Top-down mass spectrometry (MS) analysis of proteins entails unique challenges associated with processing whole proteins while maintaining their integrity throughout the processes of extraction, enrichment, purification, and fractionation. Recent advances in each of these critical front-end preparation processes, including minimalistic workflows, have greatly expanded the capacity of MS for top-down proteome analysis. Acknowledging the many contributions in MS technology and sample processing, the present review aims to highlight the diverse strategies that have forged a pathway for top-down proteomics. We comprehensively discuss the evolution of front-end workflows that today facilitate optimal characterization of proteoform-driven biology, including a brief description of the clinical applications that have motivated these impactful contributions.

Mass spectrometry-based targeted proteomics for analysis of protein mutations

Cancers are caused by accumulated DNA mutations. This recognition of the central role of mutations in cancer and recent advances in next-generation sequencing, has initiated the massive screening of clinical samples and the identification of 1000s of cancer-associated gene mutations. However, proteomic analysis of the expressed mutation products lags far behind genomic (transcriptomic) analysis. With comprehensive global proteomics analysis, only a small percentage of single nucleotide variants detected by DNA and RNA sequencing have been observed as single amino acid variants due to current technical limitations. Proteomic analysis of mutations is important with the potential to advance cancer biomarker development and the discovery of new therapeutic targets for more effective disease treatment. Targeted proteomics using selected reaction monitoring (also known as multiple reaction monitoring) and parallel reaction monitoring, has emerged as a powerful tool with significant advantages over global proteomics for analysis of protein mutations in terms of detection sensitivity, quantitation accuracy and overall practicality (e.g., reliable identification and the scale of quantification). Herein we review recent advances in the targeted proteomics technology for enhancing detection sensitivity and multiplexing capability and highlight its broad biomedical applications for analysis of protein mutations in human bodily fluids, tissues, and cell lines. Furthermore, we review recent applications of top-down proteomics for analysis of protein mutations. Unlike the commonly used bottom-up proteomics which requires digestion of proteins into peptides, top-down proteomics directly analyzes intact proteins for more precise characterization of mutation isoforms. Finally, general perspectives on the potential of achieving both high sensitivity and high sample throughput for large-scale targeted detection and quantification of important protein mutations are discussed.

Large-scale top-down proteomics of the Arabidopsis thaliana leaf and chloroplast proteomes

We present a large-scale top-down proteomics (TDP) study of plant leaf and chloroplast proteins, achieving the identification of over 4700 unique proteoforms. Using capillary zone electrophoresis coupled with tandem mass spectrometry analysis of offline size-exclusion chromatography fractions, we identify 3198 proteoforms for total leaf and 1836 proteoforms for chloroplast, with 1024 and 363 proteoforms having post-translational modifications, respectively. The electrophoretic mobility prediction of capillary zone electrophoresis allowed us to validate post-translational modifications that impact the charge state such as acetylation and phosphorylation. Identified modifications included Trp (di)oxidation events on six chloroplast proteins that may represent novel targets of singlet oxygen sensing. Furthermore, our TDP data provides direct experimental evidence of the N- and C-terminal residues of numerous mature proteoforms from chloroplast, mitochondria, endoplasmic reticulum, and other sub-cellular localizations. With this information, we suggest true transit peptide cleavage sites and correct sub-cellular localization signal predictions. This large-scale analysis illustrates the power of top-down proteoform identification of post-translational modifications and intact sequences that can benefit our understanding of both the structure and function of hundreds of plant proteins.

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

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

Chromatographic separation of peptides and proteins for characterization of proteomes

Characterization of proteomes aims to comprehensively characterize proteins in cells or tissues via two main strategies: (1) bottom-up strategy based on the separation and identification of enzymatic peptides; (2) top-down strategy based on the separation and identification of intact proteins. However, it is challenged by the high complexity of proteomes. Consequently, the improvements in peptide and protein separation technologies for simplifying the sample should be critical. In this feature article, separation columns for peptide and protein separation were introduced, and peptide separation technologies for bottom-up proteomic analysis as well as protein separation technologies for top-down proteomic analysis were summarized. The achievement, recent development, limitation and future trends are discussed. Besides, the outlook on challenges and future directions of chromatographic separation in the field of proteomics was also presented.

Deep top-down proteomics revealed significant proteoform-level differences between metastatic and nonmetastatic colorectal cancer cells

Understanding cancer metastasis at the proteoform level is crucial for discovering previously unknown protein biomarkers for cancer diagnosis and drug development. We present the first top-down proteomics (TDP) study of a pair of isogenic human nonmetastatic and metastatic colorectal cancer (CRC) cell lines (SW480 and SW620). We identified 23,622 proteoforms of 2332 proteins from the two cell lines, representing nearly fivefold improvement in the number of proteoform identifications (IDs) compared to previous TDP datasets of human cancer cells. We revealed substantial differences between the SW480 and SW620 cell lines regarding proteoform and single amino acid variant (SAAV) profiles. Quantitative TDP unveiled differentially expressed proteoforms between the two cell lines, and the corresponding genes had diversified functions and were closely related to cancer. Our study represents a pivotal advance in TDP toward the characterization of human proteome in a proteoform-specific manner, which will transform basic and translational biomedical research.

Evaluation of Machine Learning Models for Proteoform Retention and Migration Time Prediction in Top-Down Mass Spectrometry

Reversed-phase liquid chromatography (RPLC) and capillary zone electrophoresis (CZE) are two primary proteoform separation methods in mass spectrometry (MS)-based top-down proteomics. Proteoform retention time (RT) prediction in RPLC and migration time (MT) prediction in CZE provide additional information for accurate proteoform identification and quantification. While existing methods are mainly focused on peptide RT and MT prediction in bottom-up MS, there is still a lack of methods for proteoform RT and MT prediction in top-down MS. We systematically evaluated eight machine learning models and a transfer learning method for proteoform RT prediction and five models and the transfer learning method for proteoform MT prediction. Experimental results showed that a gated recurrent unit (GRU)-based model with transfer learning achieved a high accuracy (R = 0.978) for proteoform RT prediction and that the GRU-based model and a fully connected neural network model obtained a high accuracy of R = 0.982 and 0.981 for proteoform MT prediction, respectively.

Fourier-transform ion cyclotron resonance mass spectrometry for characterizing proteoforms

Proteoforms contribute functional diversity to the proteome and aberrant proteoforms levels have been implicated in biological dysfunction and disease. Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS), with its ultrahigh mass-resolving power, mass accuracy, and versatile tandem MS capabilities, has empowered top-down, middle-down, and native MS-based approaches for characterizing proteoforms and their complexes in biological systems. Herein, we review the features which make FT-ICR MS uniquely suited for measuring proteoform mass with ultrahigh resolution and mass accuracy; obtaining in-depth proteoform sequence coverage with expansive tandem MS capabilities; and unambiguously identifying and localizing post-translational and noncovalent modifications. We highlight examples from our body of work in which we have quantified and comprehensively characterized proteoforms from cardiac and skeletal muscle to better understand conditions such as chronic heart failure, acute myocardial infarction, and sarcopenia. Structural characterization of monoclonal antibodies and their proteoforms by FT-ICR MS and emerging applications, such as native top-down FT-ICR MS and high-throughput top-down FT-ICR MS-based proteomics at 21 T, are also covered. Historically, the information gleaned from FT-ICR MS analyses have helped provide biological insights. We predict FT-ICR MS will continue to enable the study of proteoforms of increasing size from increasingly complex endogenous mixtures and facilitate the benchmarking of sensitive and specific assays for clinical diagnostics. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

Global profiling of phosphorylation-dependent changes in cysteine reactivity

Proteomics has revealed that the ~20,000 human genes engender a far greater number of proteins, or proteoforms, that are diversified in large part by post-translational modifications (PTMs). How such PTMs affect protein structure and function is an active area of research but remains technically challenging to assess on a proteome-wide scale. Here, we describe a chemical proteomic method to quantitatively relate serine/threonine phosphorylation to changes in the reactivity of cysteine residues, a parameter that can affect the potential for cysteines to be post-translationally modified or engaged by covalent drugs. Leveraging the extensive high-stoichiometry phosphorylation occurring in mitotic cells, we discover numerous cysteines that exhibit phosphorylation-dependent changes in reactivity on diverse proteins enriched in cell cycle regulatory pathways. The discovery of bidirectional changes in cysteine reactivity often occurring in proximity to serine/threonine phosphorylation events points to the broad impact of phosphorylation on the chemical reactivity of proteins and the future potential to create small-molecule probes that differentially target proteoforms with PTMs.

Size Exclusion Chromatography Strategies and MASH Explorer for Large Proteoform Characterization

Top-down mass spectrometry (MS)-based analysis of larger proteoforms (>50 kDa) is typically challenging due to an exponential decay in the signal-to-noise ratio with increasing protein molecular weight (MW) and coelution with low-MW proteoforms. Size exclusion chromatography (SEC) fractionates proteins based on their size, separating larger proteoforms from those of smaller size in the proteome. In this protocol, we initially describe the use of SEC to fractionate high-MW proteoforms from low-MW proteoforms. Subsequently, the SEC fractions containing the proteoforms of interest are subjected to reverse-phase liquid chromatography (RPLC) coupled online with high-resolution MS. Finally, proteoforms are characterized using MASH Explorer, a user-friendly software environment for in-depth proteoform characterization.

Membrane Ultrafiltration-Based Sample Preparation Method and Sheath-Flow CZE-MS/MS for Top-Down Proteomics

Mass spectrometry (MS)-based denaturing top-down proteomics (dTDP) identify proteoforms without pretreatment of enzyme proteolysis. A universal sample preparation method that can efficiently extract protein, reduce sample loss, maintain protein solubility, and be compatible with following up liquid-phase separation, MS, and tandem MS (MS/MS) is vital for large-scale proteoform characterization. Membrane ultrafiltration (MU) was employed here for buffer exchange to efficiently remove the sodium dodecyl sulfate (SDS) detergent in protein samples used for protein extraction and solubilization, followed by capillary zone electrophoresis (CZE)-MS/MS analysis. The MU method showed good protein recovery, minimum protein bias, and nice compatibility with CZE-MS/MS. Single-shot CZE-MS/MS analysis of an Escherichia coli sample prepared by the MU method identified over 800 proteoforms.

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.

The glycosylation in SARS-CoV-2 and its receptor ACE2

Coronavirus disease 2019 (COVID-19), a highly infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has infected more than 235 million individuals and led to more than 4.8 million deaths worldwide as of October 5 2021. Cryo-electron microscopy and topology show that the SARS-CoV-2 genome encodes lots of highly glycosylated proteins, such as spike (S), envelope (E), membrane (M), and ORF3a proteins, which are responsible for host recognition, penetration, binding, recycling and pathogenesis. Here we reviewed the detections, substrates, biological functions of the glycosylation in SARS-CoV-2 proteins as well as the human receptor ACE2, and also summarized the approved and undergoing SARS-CoV-2 therapeutics associated with glycosylation. This review may not only broad the understanding of viral glycobiology, but also provide key clues for the development of new preventive and therapeutic methodologies against SARS-CoV-2 and its variants.

Sequential Ion-Ion Reactions for Enhanced Gas-Phase Sequencing of Large Intact Proteins in a Tribrid Orbitrap Mass Spectrometer

Obtaining extensive sequencing of an intact protein is essential in order to simultaneously determine both the nature and exact localization of chemical and genetic modifications which distinguish different proteoforms arising from the same gene. To effectively achieve such characterization, it is necessary to take advantage of the analytical potential offered by the top-down mass spectrometry approach to protein sequence analysis. However, as a protein increases in size, its gas-phase dissociation produces overlapping, low signal-to-noise fragments. The application of advanced ion dissociation techniques such as electron transfer dissociation (ETD) and ultraviolet photodissociation (UVPD) can improve the sequencing results compared to slow-heating techniques such as collisional dissociation; nonetheless, even ETD- and UVPD-based approaches have thus far fallen short in their capacity to reliably enable extensive sequencing of proteoforms ≥30 kDa. To overcome this issue, we have applied proton transfer charge reduction (PTCR) to limit signal overlap in tandem mass spectra (MS²) produced by ETD (alone or with supplemental ion activation, EThcD). Compared to conventional MS² experiments, following ETD/EThcD MS² with PTCR MS³ prior to m/z analysis of deprotonated product ions in the Orbitrap mass analyzer proved beneficial for the identification of additional large protein fragments (≥10 kDa), thus improving the overall sequencing and in particular the coverage of the central portion of all four analyzed proteins spanning from 29 to 56 kDa. Specifically, PTCR-based data acquisition led to 39% sequence coverage for the 56 kDa glutamate dehydrogenase, which was further increased to 44% by combining fragments obtained via HCD followed by PTCR MS³.

Solving Complex Biologics Truncation Problems by Top-Down Mass Spectrometry

With increasing protein therapeutics being designed as non-mAb (non-monoclonal antibody) modalities, additional efforts and resources are required to develop and characterize such therapeutic proteins. Truncation is an emerging issue for manufacturing of non-mAb drug substances and requires sophisticated methods to investigate. In this paper, we describe two cases with complex truncation problems where traditional methods such as intact mass spectrometry led to inclusive or wrong identifications. Therefore, we developed an online top-down LC-MS (liquid chromatography-mass spectrometry) based workflow to study truncated drug substances, and we successfully identified the clipping locations. Compared to other orthogonal methods, this method provides a unique capability of solving protein clipping problems. The successful identification of truncated species and the high compatibility to routine intact MS make it a very valuable tool for resolving truncation problems during protein production in the pharmaceutical industry.

Intact Protein Mass Spectrometry for Therapeutic Protein Quantitation, Pharmacokinetics, and Biotransformation in Preclinical and Clinical Studies: An Industry Perspective

Recent advancements in immunocapture methods and mass spectrometer technology have enabled intact protein mass spectrometry to be applied for the characterization of antibodies and other large biotherapeutics from in-life studies. Protein molecules have not been traditionally studied by intact mass or screened for catabolites in the same manner as small molecules, but the landscape has changed. Researchers have presented methods that can be applied to the drug discovery and development stages, and others are exploring the possibilities of the new approaches. However, a wide variety of options for assay development exists without clear recommendation on best practice, and data processing workflows may have limitations depending on the vendor. In this perspective, we share experiences and recommendations for current and future application of mass spectrometry for biotherapeutic molecule monitoring from preclinical and clinical studies.

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.

Quantitative Top-Down Proteomics in Complex Samples Using Protein-Level Tandem Mass Tag Labeling

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

Capillary Zone Electrophoresis-Electron-Capture Collision-Induced Dissociation on a Quadrupole Time-of-Flight Mass Spectrometer for Top-Down Characterization of Intact Proteins

Mass spectrometry (MS)-based denaturing top-down proteomics (dTDP) requires high-capacity separation and extensive gas-phase fragmentation of proteoforms. Herein, we coupled capillary zone electrophoresis (CZE) to electron-capture collision-induced dissociation (ECciD) on an Agilent 6545 XT quadrupole time-of-flight (Q-TOF) mass spectrometer for dTDP for the first time. During ECciD, the protein ions were first fragmented using ECD, followed by further activation and fragmentation by applying a CID potential. In this pilot study, we optimized the CZE-ECciD method for small proteins (lower than 20 kDa) regarding the charge state of protein parent ions for fragmentation and the CID potential applied to maximize the protein backbone cleavage coverage and the number of sequence-informative fragment ions. The CZE-ECciD Q-TOF platform provided extensive backbone cleavage coverage for three standard proteins lower than 20 kDa from only single charge states in a single CZE-MS/MS run in the targeted MS/MS mode, including ubiquitin (97%, +7, 8.6 kDa), superoxide dismutase (SOD, 87%, +17, 16 kDa), and myoglobin (90%, +16, 17 kDa). The CZE-ECciD method produced comparable cleavage coverage of small proteins (i.e., myoglobin) with direct-infusion MS studies using electron transfer dissociation (ETD), activated ion-ETD, and combinations of ETD and collision-based fragmentation on high-end orbitrap mass spectrometers. The results render CZE-ECciD a new tool for dTDP to enhance both separation and gas-phase fragmentation of proteoforms.

Novel Strategies to Address the Challenges in Top-Down Proteomics

Top-down mass spectrometry (MS)-based proteomics is a powerful technology for comprehensively characterizing proteoforms to decipher post-translational modifications (PTMs) together with genetic variations and alternative splicing isoforms toward a proteome-wide understanding of protein functions. In the past decade, top-down proteomics has experienced rapid growth benefiting from groundbreaking technological advances, which have begun to reveal the potential of top-down proteomics for understanding basic biological functions, unraveling disease mechanisms, and discovering new biomarkers. However, many challenges remain to be comprehensively addressed. In this Account & Perspective, we discuss the major challenges currently facing the top-down proteomics field, particularly in protein solubility, proteome dynamic range, proteome complexity, data analysis, proteoform-function relationship, and analytical throughput for precision medicine. We specifically review the major technology developments addressing these challenges with an emphasis on our research group's efforts, including the development of top-down MS-compatible surfactants for protein solubilization, functionalized nanoparticles for the enrichment of low-abundance proteoforms, strategies for multidimensional chromatography separation of proteins, and a new comprehensive user-friendly software package for top-down proteomics. We have also made efforts to connect proteoforms with biological functions and provide our visions on what the future holds for top-down proteomics.

Process analytical technology for on-line monitoring of quality attributes during single-use ultrafiltration/diafiltration

Process analytical technology (PAT) is a fast-growing field within bioprocessing that enables innovation in biological drug manufacturing. This study demonstrates novel PAT methods for monitoring multiple quality attributes simultaneously during the ultrafiltration and diafiltration (UF/DF) process operation, the final step of monoclonal antibody (mAb) purification. Size exclusion chromatography (SEC) methods were developed to measure excipients arginine, histidine, and high molecular weight (HMW) species using a liquid chromatography (LC) system with autosampler for both on-line and at-line PAT modes. The methods were applied in UF/DF studies for the comparison of single-use tangential flow filtration (TFF) cassettes to standard reusable cassettes to achieve very high concentration mAb drug substance (DS) in the order of 100-200 g/L. These case studies demonstrated that single-use TFF cassettes are a functionally equivalent, low-cost alternative to standard reusable cassettes, and that the on-line PAT measurement of purity and excipient concentration was comparable to orthogonal offline methods. These PAT applications using an on-line LC system equipped with onboard sample dilution can become a platform system for monitoring of multiple attributes over a wide dynamic range, a potentially valuable tool for biological drug development and manufacturing.

High-molecular weight impurity screening by size-exclusion chromatography on a reversed-phase column

Monitoring polymerization events leading to the discovery of new high-molecular weight (MW) impurities is challenging during chemical syntheses of active pharmaceutical ingredients. Employing reversed-phase chromatography (RPC) stationary phases (SPs) in size-exclusion chromatography (SEC) mode could be a potential solution given their high efficiency, sensitivity, and extensive solvent compatibility. However, there is a lack of generalized means for trace polymeric impurities across a wide range of physicochemical properties. Herein, we developed a SEC-based approach with a C18 SP for screening such high-MW impurities. Seven polymer standards presenting a variety of functional groups, consisting of hydrophobic, heterocyclic, ionic, and neutral hydrophilic moieties, were utilized as model impurities to establish the screening conditions. Nine mobile phases (tetrahydrofuran-based, buffered methanol, and buffered acetonitrile) were proposed to cover all model polymers and a majority of potential high-MW impurities in small molecule chemical syntheses. The established screening system demonstrated a linearity of 0.05-1.0 % w/w (R²>0.99) for the selected model impurities with proper elution conditions. Two real high-MW impurities, BMT-041910 (polymeric degradation) and poly(phenyl thiirane) (by-product polymerization), were identified from the proposed high-MW impurity screening. The successful conditions yielded a quantitative limit better than 0.1 % w/w in both cases. We believe the developed screening platform is applicable to the analysis of a wide variety of unknown high-MW impurities of low abundance potentially generated during drug substance development.

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.

Top-Down Proteomics of Endogenous Membrane Proteins Enabled by Cloud Point Enrichment and Multidimensional Liquid Chromatography-Mass Spectrometry

Although top-down proteomics has emerged as a powerful strategy to characterize proteins in biological systems, the analysis of endogenous membrane proteins remains challenging due to their low solubility, low abundance, and the complexity of the membrane subproteome. Here, we report a simple but effective enrichment and separation strategy for top-down proteomics of endogenous membrane proteins enabled by cloud point extraction and multidimensional liquid chromatography coupled to high-resolution mass spectrometry (MS). The cloud point extraction efficiently enriched membrane proteins using a single extraction, eliminating the need for time-consuming ultracentrifugation steps. Subsequently, size-exclusion chromatography (SEC) with an MS-compatible mobile phase (59% water, 40% isopropanol, 1% formic acid) was used to remove the residual surfactant and fractionate intact proteins (6-115 kDa). The fractions were separated further by reversed-phase liquid chromatography (RPLC) coupled with MS for protein characterization. This method was applied to human embryonic kidney cells and cardiac tissue lysates to enable the identification of 188 and 124 endogenous integral membrane proteins, respectively, some with as many as 19 transmembrane domains.

Construction of Human Proteoform Families from 21 Tesla Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Top-Down Proteomic Data

Identification of proteoforms, the different forms of a protein, is important to understand biological processes. A proteoform family is the set of different proteoforms from the same gene. We previously developed the software program Proteoform Suite, which constructs proteoform families and identifies proteoforms by intact-mass analysis. Here, we have applied this approach to top-down proteomic data acquired at the National High Magnetic Field Laboratory 21 tesla Fourier transform ion cyclotron resonance mass spectrometer (data available on the MassIVE platform with identifier MSV000085978). We explored the ability to construct proteoform families and identify proteoforms from the high mass accuracy data that this instrument provides for a complex cell lysate sample from the MCF-7 human breast cancer cell line. There were 2830 observed experimental proteforms, of which 932 were identified, 44 were ambiguous, and 1854 were unidentified. Of the 932 unique identified proteoforms, 766 were identified by top-down MS2 analysis at 1% false discovery rate (FDR) using TDPortal, and 166 were additional intact-mass identifications (∼4.7% calculated global FDR) made using Proteoform Suite. We recently published a proteoform level schema to represent ambiguity in proteoform identifications. We implemented this proteoform level classification in Proteoform Suite for intact-mass identifications, which enables users to determine the ambiguity levels and sources of ambiguity for each intact-mass proteoform identification.

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.

Recent advances on protein separation and purification methods

Protein, as the material basis of vita, is the crucial undertaker of life activities, which constitutes the framework and main substance of human tissues and organs, and takes part in various forms of life activities in organisms. Separating proteins from biomaterials and studying their structures and functions are of great significance for understanding the law of life activities and clarifying the essence of life phenomena. Therefore, scientists have proposed the new concept of proteomics, in which protein separation technology plays a momentous role. It has been diffusely used in the food industry, agricultural biological research, drug development, disease mechanism, plant stress mechanism, and marine environment research. In this paper, combined with the recent research situation, the progress of protein separation technology was reviewed from the aspects of extraction, precipitation, membrane separation, chromatography, electrophoresis, molecular imprinting, microfluidic chip and so on.

Distinct hypertrophic cardiomyopathy genotypes result in convergent sarcomeric proteoform profiles revealed by top-down proteomics

Hypertrophic cardiomyopathy (HCM) is the most common heritable heart disease. Although the genetic cause of HCM has been linked to mutations in genes encoding sarcomeric proteins, the ability to predict clinical outcomes based on specific mutations in HCM patients is limited. Moreover, how mutations in different sarcomeric proteins can result in highly similar clinical phenotypes remains unknown. Posttranslational modifications (PTMs) and alternative splicing regulate the function of sarcomeric proteins; hence, it is critical to study HCM at the level of proteoforms to gain insights into the mechanisms underlying HCM. Herein, we employed high-resolution mass spectrometry-based top-down proteomics to comprehensively characterize sarcomeric proteoforms in septal myectomy tissues from HCM patients exhibiting severe outflow track obstruction (n = 16) compared to nonfailing donor hearts (n = 16). We observed a complex landscape of sarcomeric proteoforms arising from combinatorial PTMs, alternative splicing, and genetic variation in HCM. A coordinated decrease of phosphorylation in important myofilament and Z-disk proteins with a linear correlation suggests PTM cross-talk in the sarcomere and dysregulation of protein kinase A pathways in HCM. Strikingly, we discovered that the sarcomeric proteoform alterations in the myocardium of HCM patients undergoing septal myectomy were remarkably consistent, regardless of the underlying HCM-causing mutations. This study suggests that the manifestation of severe HCM coalesces at the proteoform level despite distinct genotype, which underscores the importance of molecular characterization of HCM phenotype and presents an opportunity to identify broad-spectrum treatments to mitigate the most severe manifestations of this genetically heterogenous disease.

Separation of saccharides using fullerene-bonded silica monolithic columns via π interactions in liquid chromatography

We report on a potential method to separate sugars by using the specific interaction between fullerenes and saccharides in liquid chromatography (LC). Aromatic rings with high electron density are believed to interact strongly with saccharides due to CH–π and/or OH–π interactions. In this study, the fullerene-bonded columns were used to separate saccharides by LC under aqueous conditions. As a result, 2-aminobenzamide-labeled glucose homopolymer (Glcs) was effectively separated by both C60 and C70 columns in the range of Glc-1 to Glc-20 and high blood glucose level being retained in greater quantity. Furthermore, similar separations were identified by LC–mass spectrometry with non-labeled glucose homopolymers. Theoretical study based on molecular dynamics and DFT calculation demonstrated that a supramolecular complex of saccharide–fullerene was formed through CH–π and/or OH–π interactions, and that the interactions between saccharide and fullerene increase with the increase units of the saccharide. Additionally, the C60 column retained disaccharides containing maltose, trehalose, and sucrose. In this case, it was assumed that the retention rates were determined by the difference of the dipole moment in each saccharide. These results suggest that the dipole-induced dipole interaction was dominant, and that maltose—with the higher dipole moment—was more strongly retained compared to other disaccharides having lower dipole moment.

PEPPI-MS: Polyacrylamide-Gel-Based Prefractionation for Analysis of Intact Proteoforms and Protein Complexes by Mass Spectrometry

Prefractionation of complex mixtures of proteins derived from biological samples is indispensable for proteome analysis via top-down mass spectrometry (MS). Polyacrylamide gel electrophoresis (PAGE), which enables high-resolution protein separation based on molecular size, is a widely used technique in biochemical experiments and has the potential to be useful in sample fractionation for top-down MS analysis. However, the lack of a means to efficiently recover the separated proteins in-gel has always been a barrier to its use in sample prefractionation. In this study, we present a novel experimental workflow, called Passively Eluting Proteins from Polyacrylamide gels as Intact species for MS ("PEPPI-MS"), which allows top-down MS of PAGE-separated proteins. The optimization of Coomassie brilliant blue staining followed by the passive extraction step in the PEPPI-MS workflow enabled the efficient recovery of proteins, separated on commercial precast gels, from a wide range of molecular weight regions in under 10 min. Two-dimensional separation combining offline PEPPI-MS with online reversed-phase liquid chromatographic separation resulted in identification of over 1000 proteoforms recovered from the target region of the gel (≤50 kDa). Given the widespread availability and relatively low cost of traditional sodium dodecyl sulfate (SDS)-PAGE equipment, the PEPPI-MS workflow will be a powerful prefractionation strategy for top-down proteomics.